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Sample records for modelling rainfall interception

  1. Neural network modelling of rainfall interception in four different forest stands

    OpenAIRE

    Ibrahim Yurtseven; Mustafa Zengin

    2013-01-01

    The objective of this study is to reveal whether it is possible to predict rainfall, throughfall and stemflow in forest ecosystems with less effort, using several measurements of rainfall interception (hereafter interception) and an artificial neural network based linear regression model (ANN model). To this end, the Kerpe Research Forest in the province of Kocaeli, which houses stands of mixed deciduous-broadleaf forest (Castanea sativa Mill., Fagus orientalis Lipsky, Quercus spp.), black pi...

  2. Modelling rainfall interception by a lowland tropical rain forest in northeastern Puerto Rico

    Science.gov (United States)

    Schellekens, J.; Scatena, F. N.; Bruijnzeel, L. A.; Wickel, A. J.

    1999-12-01

    Recent surveys of tropical forest water use suggest that rainfall interception by the canopy is largest in wet maritime locations. To investigate the underlying processes at one such location—the Luquillo Experimental Forest in eastern Puerto Rico—66 days of detailed throughfall and above-canopy climatic data were collected in 1996 and analysed using the Rutter and Gash models of rainfall interception. Throughfall occurred on 80% of the days distributed over 80 rainfall events. Measured interception loss was 50% of gross precipitation. When Penman-Monteith based estimates for the wet canopy evaporation rate (0.11 mm h -1 on average) and a canopy storage of 1.15 mm were used, both models severely underestimated measured interception loss. A detailed analysis of four storms using the Rutter model showed that optimizing the model for the wet canopy evaporation component yielded much better results than increasing the canopy storage capacity. However, the Rutter model failed to properly estimate throughfall amounts during an exceptionally large event. The analytical model, on the other hand, was capable of representing interception during the extreme event, but once again optimizing wet canopy evaporation rates produced a much better fit than optimizing the canopy storage capacity. As such, the present results support the idea that it is primarily a high rate of evaporation from a wet canopy that is responsible for the observed high interception losses.

  3. Neural network modelling of rainfall interception in four different forest stands

    Directory of Open Access Journals (Sweden)

    Ibrahim Yurtseven

    2013-12-01

    Full Text Available The objective of this study is to reveal whether it is possible to predict rainfall, throughfall and stemflow in forest ecosystems with less effort, using several measurements of rainfall interception (hereafter ‘interception’ and an artificial neural network based linear regression model (ANN model. To this end, the Kerpe Research Forest in the province of Kocaeli, which houses stands of mixed deciduous-broadleaf forest (Castanea sativa Mill., Fagus orientalis Lipsky, Quercus spp., black pine (Pinus nigra Arnold, maritime pine (Pinus pinaster Aiton and Monterey pine (Pinus radiata D. Don, was selected study site. Four different forest stands were observed for a period of two years, during which rainfall, throughfall and stemflow measurements were conducted. These measurements were separately calculated for each individual stand, based on interception values and the use of stemflow data in strict accordance with the rainfall data, and the measured throughfall interception values were compared with values estimated by the ANN model. In this comparison, 70% of the total data was used for testing, and 30% was used for estimation and performance evaluation. No significant differences were found between values predicted with the help of the model and the measured values. In other words, interception values predicted by the ANN models were parallel with the measured values. In this study, the most success was achieved with the models of the Monterey pine stand (r2 = 0.9968; Mean Squared Error MSE = 0.16 and the mixed deciduous forest stand (r2 = 0.9964; MSE = 0.08, followed by models of the maritime pine stand (r2 = 0.9405; MSE = 1.27 and the black pine stand (r2 = 0.843, MSE = 17.36.

  4. Neural network modelling of rainfall interception in four different forest stands

    Directory of Open Access Journals (Sweden)

    İbrahim Yurtseven

    2013-11-01

    Full Text Available The objective of this study is to reveal whether it is possible to predict rainfall, through fall and stem flow in forest ecosystems with less effort, using several measurements of rainfall interception (hereafter ‘interception’ and an artificial neural network based linear regression model (ANN model. To this end, the Kerpe Research Forest in the province of Kocaeli, which houses stands of mixed deciduous-broadleaf forest (Castanea sativa Mill., Fagusorientalis Lipsky, Quercus spp., black pine (Pinus nigra Arnold, maritime pine (Pinus pinaster Aiton and Monterey pine (Pinus radiata D. Don, was selected study site. Four different forest stands were observed for a period of two years, during which rainfall, throughfall and stemflow measurements were conducted. These measurements were separately calculated for each individual stand, based on interception values and the use of stemflow data in strict accordance with the rainfall data, and the measured throughfall interceptionvalues were compared with values estimated by the ANN model.In this comparison, 70% of the total data was used for testing, and 30% was used for estimation and performance evaluation. No significant differences were found between values predicted with the help of the model and the measured values. In other words, interception values predicted by the ANN models were parallel with the measured values. In this study, the most success was achieved with the models of the Monterey pine stand (r2 = 0.9968; Mean Squared Error MSE = 0.16 and the mixed deciduous forest stand (r2 = 0.9964; MSE = 0.08, followed by models of the maritime pine stand (r2 = 0.9405; MSE = 1.27 and the black pine stand (r2 = 0.843, MSE = 17.36.

  5. Modelling rainfall interception by forests: a new method for estimating the canopy storage capacity

    Science.gov (United States)

    Pereira, Fernando; Valente, Fernanda; Nóbrega, Cristina

    2015-04-01

    Evaporation of rainfall intercepted by forests is usually an important part of a catchment water balance. Recognizing the importance of interception loss, several models of the process have been developed. A key parameter of these models is the canopy storage capacity (S), commonly estimated by the so-called Leyton method. However, this method is somewhat subjective in the selection of the storms used to derive S, which is particularly critical when throughfall is highly variable in space. To overcome these problems, a new method for estimating S was proposed in 2009 by Pereira et al. (Agricultural and Forest Meteorology, 149: 680-688), which uses information from a larger number of storms, is less sensitive to throughfall spatial variability and is consistent with the formulation of the two most widely used rainfall interception models, Gash analytical model and Rutter model. However, this method has a drawback: it does not account for stemflow (Sf). To allow a wider use of this methodology, we propose now a revised version which makes the estimation of S independent of the importance of stemflow. For the application of this new version we only need to establish a linear regression of throughfall vs. gross rainfall using data from all storms large enough to saturate the canopy. Two of the parameters used by the Gash and the Rutter models, pd (the drainage partitioning coefficient) and S, are then derived from the regression coefficients: pd is firstly estimated allowing then the derivation of S but, if Sf is not considered, S can be estimated making pd= 0. This new method was tested using data from a eucalyptus plantation, a maritime pine forest and a traditional olive grove, all located in Central Portugal. For both the eucalyptus and the pine forests pd and S estimated by this new approach were comparable to the values derived in previous studies using the standard procedures. In the case of the traditional olive grove, the estimates obtained by this methodology

  6. A Modified Gash Model for Estimating Rainfall Interception Loss of Forest Using Remote Sensing Observations at Regional Scale

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    Yaokui Cui

    2014-04-01

    Full Text Available Rainfall interception loss of forest is an important component of water balance in a forested ecosystem. The Gash analytical model has been widely used to estimate the forest interception loss at field scale. In this study, we proposed a simple model to estimate rainfall interception loss of heterogeneous forest at regional scale with several reasonable assumptions using remote sensing observations. The model is a modified Gash analytical model using easily measured parameters of forest structure from satellite data and extends the original Gash model from point-scale to the regional scale. Preliminary results, using remote sensing data from Moderate Resolution Imaging Spectroradiometer (MODIS products, field measured rainfall data, and meteorological data of the Automatic Weather Station (AWS over a picea crassifolia forest in the upper reaches of the Heihe River Basin in northwestern China, showed reasonable accuracy in estimating rainfall interception loss at both the Dayekou experimental site (R2 = 0.91, RMSE = 0.34 mm∙d −1 and the Pailugou experimental site (R2 = 0.82, RMSE = 0.6 mm∙d −1, compared with ground measurements based on per unit area of forest. The interception loss map of the study area was shown to be strongly heterogeneous. The modified model has robust physics and is insensitive to the input parameters, according to the sensitivity analysis using numerical simulations. The modified model appears to be stable and easy to be applied for operational estimation of interception loss over large areas.

  7. Modelling rainfall interception by a lowland tropical rain forest in northeastern Puerto Rico.

    NARCIS (Netherlands)

    Schellekens, J.; Scatena, F.N.; Bruijnzeel, L.A.; Wickel, A.J.

    1999-01-01

    Recent surveys of tropical forest water use suggest that rainfall interception by the canopy is largest in wet maritime locations. To investigate the underlying processes at one such location-the Luquillo Experimental Forest in eastern Puerto Rico-66 days of detailed throughfall and above-canopy

  8. Comparison of rainfall interception models in isolated individuals of Pinus pinea and Cistus ladanifer

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    R. Pérez-Arellano

    2016-07-01

    Full Text Available This paper presents a comparison of several simulation models of interception process commonly used in numerous studies, such as the classic versions of Rutter and Gash, also the version of Valente adapted by sparse forests. The aim is to analyze the applicability of different models in isolated especimens of two species of Mediterranean climate, Pinus pinea and Cistus ladanifer. The data collection was carried out in the watershed of “El Cabril” (Córdoba, from October 2010 to June 2015. The differences obtained between measurements and the results of the different models are less than 6%. Original version of Rutter model and original version of Gash model present a greater adjustment for pine and for cistus respectively.

  9. Rainfall interception of three trees in Oakland, California

    Science.gov (United States)

    Qingfu Xiao; E. Gregory McPherson

    2011-01-01

    A rainfall interception study was conducted in Oakland, California to determine the partitioning of rainfall and the chemical composition of precipitation, throughfall, and stemflow. Rainfall interception measurements were conducted on a gingko (Ginkgo biloba) (13.5 m tall deciduous tree), sweet gum (Liquidambar styraciflua) (8...

  10. Rainfall interception from a lowland tropical rainforest in Brunei

    Science.gov (United States)

    Dykes, A. P.

    1997-12-01

    Results from a programme of throughfall measurements in a lowland tropical rainforest in Brunei, northwest Borneo, indicate that interception losses amount to 18% of the gross incident rainfall. The high annual rainfall experienced by the study area results in annual interception losses of around 800 mm, which may result in total annual evapotranspiration losses significantly higher than in other rainforest locations. An improved version of Gash's analytical interception model is tested on the available data using assumed values for the "forest" parameters, and is found to predict interception losses extremely well. The model predictions are based on an estimated evaporation rate during rainfall of 0.71 mm h -1. This is significantly higher than has been reported in other tropical studies. It is concluded that these results are distinctive when compared with previous results from rainforests, and that further, detailed work is required to establish whether the enhanced evaporation rate is due to advective effects associated with the maritime setting of the study area.

  11. Water storage and evaporation as constituents of rainfall interception

    NARCIS (Netherlands)

    Klaassen, W; Bosveld, F; de Water, E

    1998-01-01

    Intercepted rainfall may be evaporated during or after the rain event. Intercepted rain is generally determined as the difference between rainfall measurements outside and inside the forest. Such measurements are often used to discriminate between water storage and evaporation during rain as well.

  12. Effects of Mediterranean shrub species on rainfall interception

    International Nuclear Information System (INIS)

    Garcia-Estringana, P.; Alonso-Blazquez, N.; Marques, M. J.; Bienes, R.; Alegre, J.

    2009-01-01

    Rainfall is intercepted by vegetation. Water intercepted could be evaporated, or it could drip from the leaves and stems to the soil or it could run down the stems to the base of the plant. In the Mediterranean, where water is a scant resource, interception loss could have an influence on hydrology. Water storage capacity depends on vegetation type. In the Mediterranean, there are many types of shrubs, and many of them are able to intercept large volumes of water depending on the shrub type. many lands of the Mediterranean basin of Europea Union have been abandoned in the last decades and consequently vegetation type changes too. This modifies hydrologic processes, changing the volume and the way in which the rainfall reaches the soil. The aim of this study was to characterize water storage capacity in 9 Mediterranean shrub species, working with the whole plant and comparing results obtained by two methods, rainfall simulation and submersion method in laboratory conditions. (Author) 12 refs.

  13. Estimating Vegetation Rainfall Interception Using Remote Sensing Observations at Very High Resolution

    Science.gov (United States)

    Cui, Y.; Zhao, P.; Hong, Y.; Fan, W.; Yan, B.; Xie, H.

    2017-12-01

    Abstract: As an important compont of evapotranspiration, vegetation rainfall interception is the proportion of gross rainfall that is intercepted, stored and subsequently evaporated from all parts of vegetation during or following rainfall. Accurately quantifying the vegetation rainfall interception at a high resolution is critical for rainfall-runoff modeling and flood forecasting, and is also essential for understanding its further impact on local, regional, and even global water cycle dynamics. In this study, the Remote Sensing-based Gash model (RS-Gash model) is developed based on a modified Gash model for interception loss estimation using remote sensing observations at the regional scale, and has been applied and validated in the upper reach of the Heihe River Basin of China for different types of vegetation. To eliminate the scale error and the effect of mixed pixels, the RS-Gash model is applied at a fine scale of 30 m with the high resolution vegetation area index retrieved by using the unified model of bidirectional reflectance distribution function (BRDF-U) for the vegetation canopy. Field validation shows that the RMSE and R2 of the interception ratio are 3.7% and 0.9, respectively, indicating the model's strong stability and reliability at fine scale. The temporal variation of vegetation rainfall interception loss and its relationship with precipitation are further investigated. In summary, the RS-Gash model has demonstrated its effectiveness and reliability in estimating vegetation rainfall interception. When compared to the coarse resolution results, the application of this model at 30-m fine resolution is necessary to resolve the scaling issues as shown in this study. Keywords: rainfall interception; remote sensing; RS-Gash analytical model; high resolution

  14. Interception of rainfall and surface runoff in the Brazilian Cerrado

    Science.gov (United States)

    Tarso Oliveira, Paulo; Wendland, Edson; Nearing, Mark; Perea Martins, João

    2014-05-01

    The Brazilian Cerrado plays a fundamental role in water resources dynamics because it distributes fresh water to the largest basins in Brazil and South America. In recent decades, the native Cerrado vegetation has increasingly been replaced by agricultural crops and pasture. These land cover and land use changes have altered the hydrological processes. Meanwhile, little is known about the components of the water balance in the Brazilian Cerrado, mainly because the experimental field studies in this region are scarce or nonexistent. The objective of this study was to evaluate two hydrological processes under native Cerrado vegetation, the canopy interception (CI) and the surface runoff (R). The Cerrado physiognomy was classified as "cerrado sensu stricto denso" with an absolute density of 15,278 trees ha-1, and a basal area of 11.44 m2 ha-1. We measured the gross rainfall (P) from an automated tipping bucket rain gauge (model TB4) located in a tower with 11 m of height on the Cerrado. Throughfall (TF) was obtained from 15 automated tipping bucket rain gauges (model Davis) spread below the Cerrado vegetation and randomly relocated every month during the wet season. Stemflow (SF) was measured on 12 trees using a plastic hose wrapped around the trees trunks, sealed with neutral silicone sealant, and a bucket to store the water. The canopy interception was computed by the difference between P and the sum of TF and SF. Surface runoff under undisturbed Cerrado was collected in three plots of 100 m2(5 x 20 m) in size and slope steepness of approximately 0.09 m m-1. The experimental study was conducted between January 2012 and November 2013. We found TF of 81.0% of P and SF of 1.6% of P, i.e. the canopy interception was calculated at 17.4% of P. There was a statistically significant correlation (p 0.8. Our results suggest that the rainfall intensity, the characteristics of the trees trunks (crooked and twisted) and stand structure are the main factors that have influenced

  15. Rainfall Interception in Mangrove in the Southeastern Coast of Brazil

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    Emerson Galvani

    2016-06-01

    Full Text Available Mangroves are among the ecosystems biologically more productive and important in the world, providing unique goods and services to societies and coastal systems. These areas, however, are increasingly fragmented, contributing to the loss of their services and benefits. The rains have an important influence in this ecosystem is central to the dissolution of sea salts. This study investigated the total rainfall in the mangroves located in the Coastal System Cananeia-Iguape (SP at different time scales (daily, monthly, sea-sonal and annual and its interception by the mangrove canopy. It found an intercept of 8.8%, ranging from 13% to 4% in the annual scale, showing that the annual variation of rainfall, which reflects both its quantity and its intensity contributes to the percentage of that interception by the canopy. It was also found that as the intensity of precipitation increases, trapping the mangrove canopy reduces.

  16. Rainfall interception by two arboreal species in urban green area

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    Luzia Ferreira da Silva

    2010-12-01

    Full Text Available Rainfall interception by the two most usual species in forest urban spaces was analysed by measuring of interception (I or interception losses, through fall (Th, stem flow (St and gross precipitation (Pg. The chosen species were Caesalpinia pluviosa DC. (Fabaceae: Caesalpinoideae or sibipiruna, and Tipuana tipu O. Kuntze (Fabaceae: Faboideae or tipuana. The individuals analysed were more than 50 years old, with three separate individuals and three individuals in each studied group of species at the campus of ”Luiz de Queiroz” College of Agriculture (University of Sao Paulo, Piracicaba. The experiments were carried out from January to February 2007. Water was collected using seven-litre pails, in the edges and in the centre of the canopies. A high correlation of Th with Pg was observed on the centre of the crow of tipuana and by the edges of sibipiruna. St and I had low correlation with Pg for both species. The average of rain interception was greater in the edges of the crow of sibipiruna individuals, 60.6%, and in the centre of tipuana crow, 59.40%. Thus, both species intercepted up to 60% of the water rainfall, which indicates a great potential of both species for arborisation in urban environments.

  17. A Preliminary Study on Rainfall Interception Loss and Water Yield Analysis on Arabica Coffee Plants in Central Aceh Regency, Indonesia

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    Reza Benara

    2012-12-01

    Full Text Available Rainfall interception loss from plants or trees can reduce a net rainfall as source of water yield. The amount of rainfall interception loss depends on kinds of plants and hydro-meteorological characteristics. Therefore, it is important to study rainfall interception loss such as from Arabica Coffee plantation which is as main agricultural commodity for Central Aceh Regency. In this study, rainfall interception loss from Arabica Coffee plants was studied in Kebet Village of Central Aceh Regency, Indonesia from January 20 to March 9, 2011. Arabica coffee plants used in this study was 15 years old, height of 1.5 m and canopy of 4.567 m2. Rainfall interception loss was determined based on water balance approach of daily rainfall, throughfall, and stemflow data. Empirical regression equation between rainfall interception loss and rainfall were adopted as a model to estimate rainfall interception loss from Arabica Coffee plantation, which the coefficient of correlation, r is 0.98. In water yield analysis, this formula was applied and founded that Arabica Coffee plants intercept 76% of annual rainfall or it leaved over annual net rainfall 24% of annual rainfall. Using this net rainfall, water yield produced from Paya Bener River which is the catchment area covered by Arabica Coffee plantation was analyzed in a planning of water supply project for water needs domestic of 3 sub-districts in Central Aceh Regency. Based on increasing population until year of 2025, the results showed that the water yield will be not enough from year of 2015. However, if the catchment area is covered by forest, the water yield is still enough until year of 2025

  18. Rainfall interception and spatial variability of throughfall in spruce stand

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    Dohnal Michal

    2014-12-01

    Full Text Available The interception was recognized as an important part of the catchment water balance in temperate climate. The mountainous forest ecosystem at experimental headwater catchment Liz has been subject of long-term monitoring. Unique dataset in terms of time resolution serves to determine canopy storage capacity and free throughfall. Spatial variability of throughfall was studied using one weighing and five tipping bucket rain gauges. The basic characteristics of forest affecting interception process were determined for the Norway spruce stand at the experimental area - the leaf area index was 5.66 - 6.00 m2 m-2, the basal area was 55.7 m2 ha-1, and the crown closure above individual rain gauges was between 19 and 95%. The total interception loss in both growing seasons analyzed was 34.5%. The mean value of the interception capacity determined was about 2 mm. Throughfall exhibited high variability from place to place and it was strongly affected by character of rainfall. On the other hand, spatial pattern of throughfall in average showed low variability.

  19. How is rainfall interception in urban area affected by meteorological parameters?

    Science.gov (United States)

    Zabret, Katarina; Rakovec, Jože; Mikoš, Matjaž; Šraj, Mojca

    2017-04-01

    Rainfall interception is part of the hydrological cycle. Precipitation, which hits vegetation, is retained on the leaves and branches, from which it eventually evaporates into the atmosphere (interception) or reaches the ground by dripping from the canopy, falling through the gaps (throughfall) and running down the stems (stemflow). The amount of rainfall reaching the ground depends on various meteorological and vegetation parameters. Rainfall, throughfall and stemflow have been measured in the city of Ljubljana, Slovenia since the beginning of 2014. Manual and automatic measurements are performed regularly under Betula pendula and Pinus nigra trees in urban area. In 2014, there were detected 178 rainfall events with total amount of 1672.1 mm. In average B. pendula intercepted 44% of rainfall and P. nigra intercepted 72% of rainfall. In 2015 we have detected 117 events with 1047.4 mm of rainfall, of which 37% was intercepted by B. pendula and 60% by P. nigra. The effect of various meteorological parameters on the rainfall interception was analysed in the study. The parameters included in the analysis were rainfall rate, rainfall duration, drop size distribution (average drop velocity and diameter), average wind speed, and average temperature. The results demonstrate decreasing rainfall interception with longer rainfall duration and higher rainfall intensity although the impact of the latter one is not statistically significant. In the case of very fast or very slow rainfall drops, the interception is higher than for the mean rain drop velocity values. In the case of P. nigra the impact of the rain drop diameter on interception is similar to the one of rain drop velocity while for B. pendula increasing of drop diameter also increases the interception. As expected, interception is higher for warmer events. This trend is more evident for P. nigra than for B. pendula. Furthermore, the amount of intercepted rainfall also increases with wind although it could be

  20. Impact of rainfall interception on hydrologic partitioning and soil erosion in natural and managed seasonally dry ecosystems

    Science.gov (United States)

    Moura, A. E.; Montenegro, S. M.; Silva, B. B.; Bartlett, M. S.; Porporato, A. M.; Antonino, A. C.

    2013-12-01

    Quantifying the effects of land use change and rainfall variability in seasonal, dry ecosystems is crucial to sustainable management of soil and water resources. In particular, changes in rainfall interception effects on hydrologic partitioning and soil erosion due to land use change are among the least known processes, despite their importance for water resource managements, in terms of water availability for ecosystem and society and water quality and erosion problems. In this work we quantify the interception losses in different types of vegetation (coffee, lemon and vegetation of natural forest) found in the Tapacurá basin in the Pernambuco state of NE Brazil, coupling field experiments and analytical models. The interception losses were measured with rain gauges installed in three types of vegetation along with stemflow collectors. Close to the coffee plantation, a meteorological station was also installed for measurement of the necessary variables for the model calibrations. As expected, the results show that rainfall events of smaller magnitude proportionally have larger relative interception losses, with larger differences in the wet season. The model results also allow us to quantify the nonlinear behavior of the interception process, at the same time providing a valuable tool to estimate the interception loss due to changes in vegetation and rainfall regime and thus to improve water resource management in seasonally dry tropics .

  1. Interception loss, throughfall and stemflow in a maritime pine stand. II. An application of Gash's analytical model of interception

    Science.gov (United States)

    Loustau, D.; Berbigier, P.; Granier, A.

    1992-10-01

    Interception, throughfall and stemflow were determined in an 18-year-old maritime pine stand for a period of 30 months. This involved 71 rainfall events, each corresponding either to a single storm or to several storms. Gash's analytical model of interception was used to estimate the sensitivity of interception to canopy structure and climatic parameters. The seasonal cumulative interception loss corresponded to 12.6-21.0% of the amount of rainfall, whereas throughfall and stemflow accounted for 77-83% and 1-6%, respectively. On a seasonal basis, simulated data fitted the measured data satisfactorily ( r2 = 0.75). The rainfall partitioning between interception, throughfall and stemflow was shown to be sensitive to (1) the rainfall regime, i.e. the relative importance of light storms to total rainfall, (2) the climatic parameters, rainfall rate and average evaporation rate during storms, and (3) the canopy structure parameters of the model. The low interception rate of the canopy was attributed primarily to the low leaf area index of the stand.

  2. Quantifying Rainfall Interception Loss of a Subtropical Broadleaved Forest in Central Taiwan

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    Yi-Ying Chen

    2016-01-01

    Full Text Available The factors controlling seasonal rainfall interception loss are investigated by using a double-mass curve analysis, based on direct measurements of high-temporal resolution gross rainfall, throughfall and stemflow from 43 rainfall events that occurred in central Taiwan from April 2008 to April 2009. The canopy water storage capacity for the wet season was estimated to be 1.86 mm, about twice that for the dry season (0.91 mm, likely due to the large reduction in the leaf area index (LAI from 4.63 to 2.23 (m2·m−2. Changes in seasonal canopy structure and micro-meteorological conditions resulted in temporal variations in the amount of interception components, and rainfall partitioning into stemflow and throughfall. Wet canopy evaporation after rainfall contributed 41.8% of the wet season interception loss, but only 17.1% of the dry season interception loss. Wet canopy evaporation during rainfall accounted for 82.9% of the dry season interception loss, but only 58.2% of the wet season interception loss. Throughfall accounted for over 79.7% of the dry season precipitation and 76.1% of the wet season precipitation, possibly due to the change in gap fraction from 64.2% in the dry season to 50.0% in the wet season. The reduced canopy cover in the dry season also produced less stemflow than that of the wet season. The rainfall stemflow ratio ( P s f / P g was reduced from 12.6% to 8.9%. Despite relatively large changes in canopy structure, seasonal variation of the ratio of rainfall partitioned to interception was quite small. Rainfall interception loss accounted for nearly 12% of gross precipitation for both dry and wet seasons.

  3. Rainfall interception and spatial variability of throughfall in spruce stand

    Czech Academy of Sciences Publication Activity Database

    Dohnal, M.; Černý, T.; Votrubová, J.; Tesař, Miroslav

    2014-01-01

    Roč. 62, č. 4 (2014), s. 277-284 ISSN 0042-790X R&D Projects: GA TA ČR TA02021451 Institutional support: RVO:67985874 Keywords : Interception loss * Interception capacity * Free throughfall * Evaporation * Hydrological balance of vegetation cover Subject RIV: DA - Hydrology ; Limnology Impact factor: 1.486, year: 2014

  4. Generalization of Random Intercept Multilevel Models

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    Rehan Ahmad Khan

    2013-10-01

    Full Text Available The concept of random intercept models in a multilevel model developed by Goldstein (1986 has been extended for k-levels. The random variation in intercepts at individual level is marginally split into components by incorporating higher levels of hierarchy in the single level model. So, one can control the random variation in intercepts by incorporating the higher levels in the model.

  5. Rainfall interception and the coupled surface water and energy balance

    NARCIS (Netherlands)

    Van Dijk, A.I.J.M.; et al., et al.; Moors, E.J.

    2015-01-01

    Evaporation from wet canopies (. E) can return up to half of incident rainfall back into the atmosphere and is a major cause of the difference in water use between forests and short vegetation. Canopy water budget measurements often suggest values of E during rainfall that are several times greater

  6. On interception modelling of a lowland coastal rainforest in northern Queensland, Australia

    Science.gov (United States)

    Wallace, Jim; McJannet, Dave

    2006-10-01

    SummaryRecent studies of the water balance of tropical rainforests in northern Queensland have revealed that large fractions of rainfall, up to 30%, are intercepted by the canopy and lost as evaporation. These loss rates are much higher than those reported for continental rainforests, for example, in the Amazon basin, where interception is around 9% of rainfall. Higher interception losses have been found in coastal and mountain rainforests and substantial advection of energy during rainfall is proposed to account for these results. This paper uses a process based model of interception to analyse the interception losses at Oliver Creek, a lowland coastal rainforest site in northern Queensland with a mean annual rainfall of 3952 mm. The observed interception loss of 25% of rainfall for the period August 2001 to January 2004 can be reproduced by the model with a suitable choice of the three key controlling variables, the canopy storage capacity, mean rainfall rate and mean wet canopy evaporation rate. Our analyses suggest that the canopy storage capacity of the Oliver Creek rainforest is between 3.0 and 3.5 mm, higher than reported for most other rainforests. Despite the high canopy capacity at our site, the interception losses can only be accounted for with energy advection during rainfall in the range 40-70% of the incident energy.

  7. Gross rainfall amount and maximum rainfall intensity in 60-minute influence on interception loss of shrubs: a 10-year observation in the Tengger Desert.

    Science.gov (United States)

    Zhang, Zhi-Shan; Zhao, Yang; Li, Xin-Rong; Huang, Lei; Tan, Hui-Juan

    2016-05-17

    In water-limited regions, rainfall interception is influenced by rainfall properties and crown characteristics. Rainfall properties, aside from gross rainfall amount and duration (GR and RD), maximum rainfall intensity and rainless gap (RG), within rain events may heavily affect throughfall and interception by plants. From 2004 to 2014 (except for 2007), individual shrubs of Caragana korshinskii and Artemisia ordosica were selected to measure throughfall during 210 rain events. Various rainfall properties were auto-measured and crown characteristics, i.e., height, branch and leaf area index, crown area and volume of two shrubs were also measured. The relative interceptions of C. korshinskii and A. ordosica were 29.1% and 17.1%, respectively. Rainfall properties have more contributions than crown characteristics to throughfall and interception of shrubs. Throughfall and interception of shrubs can be explained by GR, RI60 (maximum rainfall intensities during 60 min), RD and RG in deceasing importance. However, relative throughfall and interception of two shrubs have different responses to rainfall properties and crown characteristics, those of C. korshinskii were closely related to rainfall properties, while those of A. ordosica were more dependent on crown characteristics. We highlight long-term monitoring is very necessary to determine the relationships between throughfall and interception with crown characteristics.

  8. Rainfall-interception-evaporation-runoff relationships in a semi-arid catchment, northern Limpopo basin, Zimbabwe

    NARCIS (Netherlands)

    Love, D.; Uhlenbrook, S.; Corzo Perez, G.; Twomlow, S.; Zaag, van der P.

    2010-01-01

    Characterizing the response of a catchment to rainfall, in terms of the production of runoff vs the interception, transpiration and evaporation of water, is the first important step in understanding water resource availability in a catchment. This is particularly important in small semi-arid

  9. Measurement of rainfall distribution on a small catchment for the evaluation of canopy interception effects

    Science.gov (United States)

    Maurer, Thomas; Schapp, Andrea; Büchner, Steffen; Menzel, Hannes; Hinz, Christoph

    2014-05-01

    Variability of rainfall and throughfall is an essential characteristic of the water balance at spatial scales ranging from meters to hundreds of meters or even kilometers. The amount of throughfall is governed by the characteristics of the vegetation canopy and the involved interception and stemflow effects. In initial, developing ecosystems, distinct patterns of the growing vegetation (e.g. patchiness) supposedly govern the spatial distribution of water in the system, thereby initiating and supporting hydro-ecological feedback processes. Questions are i) is the spatial variability of vegetation relevant for the system as a whole, and ii) how does the distribution of the effective precipitation (i.e. the infiltration) change over time in dependency of vegetation succession? We present the first results of a spatially distributed measurement approach of surface-near precipitation on the constructed catchment "Hühnerwasser" ("Chicken Creek"). The 6-ha site is located in the recultivation area of the lignite open-cast mine "Welzow-Süd" in Lower Lusatia, Brandenburg, Germany. Here, the free development of an initial ecosystem is investigated since September 2005. After eight years of succession, the spatial distribution of plant species is highly heterogeneous, and gains increasing influence on throughfall patterns, thus impacting the distribution of soil humidity and possibly even surface runoff. For spatially distributed precipitation measurement, 47 tipping bucket rain gauges were installed in heights of 0.5 m and 1.0 m along two transects on the catchment. Rain gauge data were collected by a wireless sensor node network provided by the Sens4U joint research project. The transects run NW-SE and NE-SW and cover the range of plant communities presently existing in the ecosystem: locust copses, dense sallow thorn bushes and reeds, base herbaceous and medium-rise small-reed vegetation, and open areas covered by moss and lichens. The raw measurement data were

  10. Influence of Spatial and Temporal Factors in Determining Rainfall Interception at Dipterocarp Forest Canopy, Lake Chini, Pahang

    International Nuclear Information System (INIS)

    Nur Munirah Abdullah; Mohd Ekhwan Toriman; Haslinur Mohd Din

    2013-01-01

    The reduction of rainfall by interception process is influenced by two mechanisms namely climate and plant physiographic features. Climate features that affecting the interception loss including total rainfall (mm), wind speed (m/s) and temperature (degree Celsius). Meanwhile plant physiographic features that affect interception loss consists of trees height, skin, diameter, canopy, twigs and branches. Looking the role of climate and plant physiographic features in the interception process, this study was conducted in order to measure the throughfall, stem flow and interception loss and the factors that influence it. The assessment of throughfall and interception loss were carried out on study plot sized 100 x 100 meter in Dipterocarp Forest of Tasik Chini, Pahang. The study was conducted from October 2009 until January of 2010. Thirty tree samples are used and each tree is well-identified based on their species, family, diameter breast height (DBH), canopy size and its density. Four sets of throughfall were used to do throughfall measurements. Results of this study found that the value of throughfall and stem flow collected based on four rainfall events namely in October 2009 where 0.66 % (TF) and 99.34 % (SF), November 2009-0.54 % (TF) and 99.46 % (SF), December 2009-0.72 % (TF) and 99.28 % (SF) and January of 2010-0.49 % (TF) and 99.51 % (SF). Statistical analysis also indicates the existence of the relationship between total rainfall and interception loss with significant levels in 0.571 (r 2 ) in December of 2009. This study provides important information that related to the hydrological cycle and how plants canopy can be acted as a medium of water balance in the environment. (author)

  11. Measuring and modelling interception loss by an isolated olive tree in a traditional olive grove - pasture system

    Science.gov (United States)

    Nóbrega, Cristina; Pereira, Fernando L.; Valente, Fernanda

    2015-04-01

    Water losses associated to the rainfall interception process by trees can be an important component of the local hydrologic balance and must be accounted for when implementing any sustainable water management programme. In many dry areas of the Mediterranean region where agro-forestry systems are common, those programmes are crucial to foster adequate water conservation measures. Recent studies have shown that the evaluation of interception loss in sparse forests or tree plantations should be made for individual trees, being the total value determined as the sum of the individual contributions. Following this approach, rainfall interception was measured and modelled over two years, in an isolated Olea europeaea L. tree, in a traditional low-density olive grove in Castelo Branco, central Portugal. Total interception loss over the experimental period was 243.5 mm, on a tree crown projected area basis, corresponding to 18.0% of gross rainfall (Pg). Modelling made for each rainfall event using the sparse version of the Gash model, slightly underestimated interception loss with a value of 240.5 mm, i.e., 17.8 % ofPg. Modelling quality, evaluated according to a number of criteria, was good, allowing the conclusion that the methodology used was adequate. Modelling was also made on a daily basis, i.e., assuming a single storm per rainday. In this case, interception loss was overestimated by 12%, mostly because 72% of all rainfall events lasted for more than a day.

  12. Interception of wet deposited atmospheric pollutants by herbaceous vegetation: Data review and modelling

    Energy Technology Data Exchange (ETDEWEB)

    Gonze, M.-A., E-mail: marc-andre.gonze@irsn.fr; Sy, M.M.

    2016-09-15

    Better understanding and predicting interception of wet deposited pollutants by vegetation remains a key issue in risk assessment studies of atmospheric pollution. We develop different alternative models, following either empirical or semi-mechanistic descriptions, on the basis of an exhaustive dataset consisting of 440 observations obtained in controlled experiments, from 1970 to 2014, for a wide variety of herbaceous plants, radioactive substances and rainfall conditions. The predictive performances of the models and the uncertainty/variability of the parameters are evaluated under Hierarchical Bayesian modelling framework. It is demonstrated that the variability of the interception fraction is satisfactorily explained and quite accurately modelled by a process-based alternative in which absorption of ionic substances onto the foliage surfaces is determined by their electrical valence. Under this assumption, the 95% credible interval of the predicted interception fraction encompasses 81% of the observations, including situations where either plant biomass or rainfall intensity are unknown. This novel approach is a serious candidate to challenge existing empirical relationships in radiological or chemical risk assessment tools. - Highlights: • Literature data on the interception of atmospheric pollutants by herbs were reviewed • Predictive models were developed and evaluated in the Bayesian modelling framework • Sensitivity of interception to environmental conditions was satisfactorily explained • 81% of the observations were satisfactorily predicted by a semi-mechanistic model • This model challenges empirical relationships currently used in risk assessment tools.

  13. Rainfall Stochastic models

    Science.gov (United States)

    Campo, M. A.; Lopez, J. J.; Rebole, J. P.

    2012-04-01

    This work was carried out in north of Spain. San Sebastian A meteorological station, where there are available precipitation records every ten minutes was selected. Precipitation data covers from October of 1927 to September of 1997. Pulse models describe the temporal process of rainfall as a succession of rainy cells, main storm, whose origins are distributed in time according to a Poisson process and a secondary process that generates a random number of cells of rain within each storm. Among different pulse models, the Bartlett-Lewis was used. On the other hand, alternative renewal processes and Markov chains describe the way in which the process will evolve in the future depending only on the current state. Therefore they are nor dependant on past events. Two basic processes are considered when describing the occurrence of rain: the alternation of wet and dry periods and temporal distribution of rainfall in each rain event, which determines the rainwater collected in each of the intervals that make up the rain. This allows the introduction of alternative renewal processes and Markov chains of three states, where interstorm time is given by either of the two dry states, short or long. Thus, the stochastic model of Markov chains tries to reproduce the basis of pulse models: the succession of storms, each one composed for a series of rain, separated by a short interval of time without theoretical complexity of these. In a first step, we analyzed all variables involved in the sequential process of the rain: rain event duration, event duration of non-rain, average rainfall intensity in rain events, and finally, temporal distribution of rainfall within the rain event. Additionally, for pulse Bartlett-Lewis model calibration, main descriptive statistics were calculated for each month, considering the process of seasonal rainfall in each month. In a second step, both models were calibrated. Finally, synthetic series were simulated with calibration parameters; series

  14. Random Intercept and Random Slope 2-Level Multilevel Models

    Directory of Open Access Journals (Sweden)

    Rehan Ahmad Khan

    2012-11-01

    Full Text Available Random intercept model and random intercept & random slope model carrying two-levels of hierarchy in the population are presented and compared with the traditional regression approach. The impact of students’ satisfaction on their grade point average (GPA was explored with and without controlling teachers influence. The variation at level-1 can be controlled by introducing the higher levels of hierarchy in the model. The fanny movement of the fitted lines proves variation of student grades around teachers.

  15. Numerical modelling of new rockfall interception nets

    Science.gov (United States)

    von Boetticher, Albrecht; Volkwein, Axel; Wendeler, Corinna

    2010-05-01

    The design and certification of effective rockfall protection barriers is mainly achieved through 1:1 prototype testing. In order to reduce development costs of a prototype it is recommended that pre-studies using numerical simulations are performed. A large component to modelling rockfall protection systems is the numerical simulation of the nets. To date there exist several approaches to model the different mesh types such as ring nets or diagonal meshes (Nicot 1999, Cazzani et al. 2002, Volkwein 2004). However, the consideration of chain link meshes has not yet been realised. Chain link meshes are normally found as standard fence structures. However, they also exist in setups using high-strength steel and wire bundles. These variants show an enormous capacity to retain loads e.g. rockfalls, and at the same time are very efficient due to their low demand of steel material. The increasing application of chain link mesh in barrier systems requires an accurate model is available to complete prototype studies. A new approach now aims to perform a Finite Element simulation of such chain link meshes. The main challenge herein is to achieve the net deformation behaviour that is observed in field tests also in the simulation. A simulation using simple truss elements would not work since it neglects the out-of-plane-height of the mesh construction providing important reserves for local and global high deformations. Thus addressing this, a specially developed Discrete Element is able to reconstruct the mechanical behaviour of the single chain wire (bundles). As input parameters it utilises typical properties such as longitudinal and transversal mesh widths, and break loads resulting from in-plane-tension tests and steel strength. The single chain elements then can be combined to a complete mesh (e.g. 130 x 65 mm, 3 - 4 mm wire with a strength of 1770 N-mm2). Combining these elements with a supporting structure consisting of posts, ropes and energy absorbers, enables the

  16. Visuo-motor coordination and internal models for object interception.

    Science.gov (United States)

    Zago, Myrka; McIntyre, Joseph; Senot, Patrice; Lacquaniti, Francesco

    2009-02-01

    Intercepting and avoiding collisions with moving objects are fundamental skills in daily life. Anticipatory behavior is required because of significant delays in transforming sensory information about target and body motion into a timed motor response. The ability to predict the kinematics and kinetics of interception or avoidance hundreds of milliseconds before the event may depend on several different sources of information and on different strategies of sensory-motor coordination. What are exactly the sources of spatio-temporal information and what are the control strategies remain controversial issues. Indeed, these topics have been the battlefield of contrasting views on how the brain interprets visual information to guide movement. Here we attempt a synthetic overview of the vast literature on interception. We discuss in detail the behavioral and neurophysiological aspects of interception of targets falling under gravity, as this topic has received special attention in recent years. We show that visual cues alone are insufficient to predict the time and place of interception or avoidance, and they need to be supplemented by prior knowledge (or internal models) about several features of the dynamic interaction with the moving object.

  17. Stochastic and simulation models of maritime intercept operations capabilities

    OpenAIRE

    Sato, Hiroyuki

    2005-01-01

    The research formulates and exercises stochastic and simulation models to assess the Maritime Intercept Operations (MIO) capabilities. The models focus on the surveillance operations of the Maritime Patrol Aircraft (MPA). The analysis using the models estimates the probability with which a terrorist vessel (Red) is detected, correctly classified, and escorted for intensive investigation and neutralization before it leaves an area of interest (AOI). The difficulty of obtaining adequate int...

  18. Analytical Modelling of Canopy Interception Loss from a Juvenile Lodgepole Pine (Pinus contorta var. latifolia) Stand

    Science.gov (United States)

    Carlyle-Moses, D. E.; Lishman, C. E.

    2015-12-01

    In the central interior of British Columbia (BC), Canada, the mountain pine beetle (Dendroctonus ponderosae Hopkins) (MPB) has severely affected the majority of pine species in the region, especially lodgepole pine (Pinus contorta Douglas ex Louden var. latifolia Engelm. ex S. Watson). The loss of mature lodgepole pine stands, including those lost to salvage logging, has resulted in an increase in the number of juvenile pine stands in the interior of BC through planting and natural regrowth. With this change from mature forests to juvenile forests at such a large spatial scale, the water balance of impacted areas may be altered, although the magnitude of such change is uncertain. Previous studies of rainfall partitioning by lodgepole pine and lodgepole pine dominated canopies have focused on mature stands. Thus, rainfall, throughfall and stemflow were measured and canopy interception loss was derived during the growing season of 2010 in a juvenile lodgepole pine dominated stand located approximately 60 km NNW of Kamloops, BC at 51°12'49" N 120°23'43" W, 1290 m above mean sea level. Scaling up from measurements for nine trees, throughfall, stemflow and canopy interception loss accounted for 87.7, 1.8 and 10.5 percent of the 252.9 mm of rain that fell over 38 events during the study period, respectively. The reformulated versions of the Gash and Liu analytical interception loss models estimated cumulative canopy interception loss at 24.7 and 24.6 mm, respectively, compared with the observed 26.5 mm; an underestimate of 1.8 and 1.9 mm or 6.8 and 7.2% of the observed value, respectively. Our results suggest that canopy interception loss is reduced in juvenile stands compared to their mature counterparts and that this reduction is due to the decreased storage capacity offered by these younger canopies. Evaporation during rainfall from juvenile canopies is still appreciable and may be a consequence of the increased proportion of the canopy exposed to wind during events.

  19. Marginal and Random Intercepts Models for Longitudinal Binary Data with Examples from Criminology

    Science.gov (United States)

    Long, Jeffrey D.; Loeber, Rolf; Farrington, David P.

    2009-01-01

    Two models for the analysis of longitudinal binary data are discussed: the marginal model and the random intercepts model. In contrast to the linear mixed model (LMM), the two models for binary data are not subsumed under a single hierarchical model. The marginal model provides group-level information whereas the random intercepts model provides…

  20. Bartlett correction in the stable AR(1) model with intercept and trend

    NARCIS (Netherlands)

    van Giersbergen, N.P.A.

    2004-01-01

    The Bartlett correction is derived for testing hypotheses about the autoregressive parameter ρ in the stable: (i) AR(1) model; (ii) AR(1) model with intercept; (iii) AR(1) model with intercept and linear trend. The correction is found explicitly as a function of ρ. In the models with deterministic

  1. Light regimes in Populus plantations using the Voxel-based Light Interception Model

    NARCIS (Netherlands)

    Van der Zande, D.; Dieussart, K.; Stuckens, J.; Verstraeten, W.W.; Coppin, P.

    2011-01-01

    Three-dimensional light interception by three uniform Populus canopies was studied using the Voxel-based Light Interception Model (VLIM) in combination with ground-based Light Detection and Ranging (LiDAR) measurements. As the VLIM was developed and validated in a virtual environment to ensure

  2. Towards a 3D structural tomato model for calculating light interception

    NARCIS (Netherlands)

    Sarlikioti, V.; Marcelis, L.F.M.; Visser, de P.H.B.

    2011-01-01

    A number of physiological tomato models have been proposed the last decades, their main challenge being the correct simulation of fruit yield. For this, an accurate simulation of light interception, and thus photosynthesis, is of primary importance. Light interception is highly dependent of the

  3. Statistical Modelling of Extreme Rainfall in Taiwan

    NARCIS (Netherlands)

    L-F. Chu (Lan-Fen); M.J. McAleer (Michael); C-C. Chang (Ching-Chung)

    2012-01-01

    textabstractIn this paper, the annual maximum daily rainfall data from 1961 to 2010 are modelled for 18 stations in Taiwan. We fit the rainfall data with stationary and non-stationary generalized extreme value distributions (GEV), and estimate their future behaviour based on the best fitting model.

  4. Statistical Modelling of Extreme Rainfall in Taiwan

    NARCIS (Netherlands)

    L. Chu (LanFen); M.J. McAleer (Michael); C-H. Chang (Chu-Hsiang)

    2013-01-01

    textabstractIn this paper, the annual maximum daily rainfall data from 1961 to 2010 are modelled for 18 stations in Taiwan. We fit the rainfall data with stationary and non-stationary generalized extreme value distributions (GEV), and estimate their future behaviour based on the best fitting model.

  5. Modelling rainfall erosion resulting from climate change

    Science.gov (United States)

    Kinnell, Peter

    2016-04-01

    It is well known that soil erosion leads to agricultural productivity decline and contributes to water quality decline. The current widely used models for determining soil erosion for management purposes in agriculture focus on long term (~20 years) average annual soil loss and are not well suited to determining variations that occur over short timespans and as a result of climate change. Soil loss resulting from rainfall erosion is directly dependent on the product of runoff and sediment concentration both of which are likely to be influenced by climate change. This presentation demonstrates the capacity of models like the USLE, USLE-M and WEPP to predict variations in runoff and erosion associated with rainfall events eroding bare fallow plots in the USA with a view to modelling rainfall erosion in areas subject to climate change.

  6. Intercept Centering and Time Coding in Latent Difference Score Models

    Science.gov (United States)

    Grimm, Kevin J.

    2012-01-01

    Latent difference score (LDS) models combine benefits derived from autoregressive and latent growth curve models allowing for time-dependent influences and systematic change. The specification and descriptions of LDS models include an initial level of ability or trait plus an accumulation of changes. A limitation of this specification is that the…

  7. Censored rainfall modelling for estimation of fine-scale extremes

    Science.gov (United States)

    Cross, David; Onof, Christian; Winter, Hugo; Bernardara, Pietro

    2018-01-01

    Reliable estimation of rainfall extremes is essential for drainage system design, flood mitigation, and risk quantification. However, traditional techniques lack physical realism and extrapolation can be highly uncertain. In this study, we improve the physical basis for short-duration extreme rainfall estimation by simulating the heavy portion of the rainfall record mechanistically using the Bartlett-Lewis rectangular pulse (BLRP) model. Mechanistic rainfall models have had a tendency to underestimate rainfall extremes at fine temporal scales. Despite this, the simple process representation of rectangular pulse models is appealing in the context of extreme rainfall estimation because it emulates the known phenomenology of rainfall generation. A censored approach to Bartlett-Lewis model calibration is proposed and performed for single-site rainfall from two gauges in the UK and Germany. Extreme rainfall estimation is performed for each gauge at the 5, 15, and 60 min resolutions, and considerations for censor selection discussed.

  8. Temporal rainfall estimation using input data reduction and model inversion

    Science.gov (United States)

    Wright, A. J.; Vrugt, J. A.; Walker, J. P.; Pauwels, V. R. N.

    2016-12-01

    Floods are devastating natural hazards. To provide accurate, precise and timely flood forecasts there is a need to understand the uncertainties associated with temporal rainfall and model parameters. The estimation of temporal rainfall and model parameter distributions from streamflow observations in complex dynamic catchments adds skill to current areal rainfall estimation methods, allows for the uncertainty of rainfall input to be considered when estimating model parameters and provides the ability to estimate rainfall from poorly gauged catchments. Current methods to estimate temporal rainfall distributions from streamflow are unable to adequately explain and invert complex non-linear hydrologic systems. This study uses the Discrete Wavelet Transform (DWT) to reduce rainfall dimensionality for the catchment of Warwick, Queensland, Australia. The reduction of rainfall to DWT coefficients allows the input rainfall time series to be simultaneously estimated along with model parameters. The estimation process is conducted using multi-chain Markov chain Monte Carlo simulation with the DREAMZS algorithm. The use of a likelihood function that considers both rainfall and streamflow error allows for model parameter and temporal rainfall distributions to be estimated. Estimation of the wavelet approximation coefficients of lower order decomposition structures was able to estimate the most realistic temporal rainfall distributions. These rainfall estimates were all able to simulate streamflow that was superior to the results of a traditional calibration approach. It is shown that the choice of wavelet has a considerable impact on the robustness of the inversion. The results demonstrate that streamflow data contains sufficient information to estimate temporal rainfall and model parameter distributions. The extent and variance of rainfall time series that are able to simulate streamflow that is superior to that simulated by a traditional calibration approach is a

  9. Improving the representation of radiation interception and photosynthesis for climate model applications

    International Nuclear Information System (INIS)

    Mercado, Lina M.; Huntingford, Chris; Gash, John H.C.; Cox, Peter M.; Jogireddy, Venkata

    2007-01-01

    The Joint UK Land Environment Simulator (JULES) (which is based on Met Office Surface Exchange Scheme MOSES), the land surface scheme of the Hadley Centre General Circulation Models (GCM) has been improved to contain an explicit description of light interception for different canopy levels, which consequently leads to a multilayer approach to scaling from leaf to canopy level photosynthesis. We test the improved JULES model at a site in the Amazonian rainforest by comparing against measurements of vertical profiles of radiation through the canopy, eddy covariance measurements of carbon and energy fluxes, and also measurements of carbon isotopic fractionation from top canopy leaves. Overall, the new light interception formulation improves modelled photosynthetic carbon uptake compared to the standard big leaf approach used in the original JULES formulation. Additional model improvement was not significant when incorporating more realistic vertical variation of photosynthetic capacity. Even with the improved representation of radiation interception, JULES simulations of net carbon uptake underestimate eddy covariance measurements by 14%. This discrepancy can be removed by either increasing the photosynthetic capacity throughout the canopy or by explicitly including light inhibition of leaf respiration. Along with published evidence of such inhibition of leaf respiration, our study suggests this effect should be considered for inclusion in other GCMs

  10. Genomic-Enabled Prediction Kernel Models with Random Intercepts for Multi-environment Trials

    Science.gov (United States)

    Cuevas, Jaime; Granato, Italo; Fritsche-Neto, Roberto; Montesinos-Lopez, Osval A.; Burgueño, Juan; Bandeira e Sousa, Massaine; Crossa, José

    2018-01-01

    In this study, we compared the prediction accuracy of the main genotypic effect model (MM) without G×E interactions, the multi-environment single variance G×E deviation model (MDs), and the multi-environment environment-specific variance G×E deviation model (MDe) where the random genetic effects of the lines are modeled with the markers (or pedigree). With the objective of further modeling the genetic residual of the lines, we incorporated the random intercepts of the lines (l) and generated another three models. Each of these 6 models were fitted with a linear kernel method (Genomic Best Linear Unbiased Predictor, GB) and a Gaussian Kernel (GK) method. We compared these 12 model-method combinations with another two multi-environment G×E interactions models with unstructured variance-covariances (MUC) using GB and GK kernels (4 model-method). Thus, we compared the genomic-enabled prediction accuracy of a total of 16 model-method combinations on two maize data sets with positive phenotypic correlations among environments, and on two wheat data sets with complex G×E that includes some negative and close to zero phenotypic correlations among environments. The two models (MDs and MDE with the random intercept of the lines and the GK method) were computationally efficient and gave high prediction accuracy in the two maize data sets. Regarding the more complex G×E wheat data sets, the prediction accuracy of the model-method combination with G×E, MDs and MDe, including the random intercepts of the lines with GK method had important savings in computing time as compared with the G×E interaction multi-environment models with unstructured variance-covariances but with lower genomic prediction accuracy. PMID:29476023

  11. Stochastic modelling of daily rainfall sequences

    NARCIS (Netherlands)

    Buishand, T.A.

    1977-01-01

    Rainfall series of different climatic regions were analysed with the aim of generating daily rainfall sequences. A survey of the data is given in I, 1. When analysing daily rainfall sequences one must be aware of the following points:
    a. Seasonality. Because of seasonal variation

  12. Mathematical and physical modeling of rainfall in centrifuge

    OpenAIRE

    CAICEDO, Bernardo; THOREL, Luc; TRISTANCHO, Julian

    2015-01-01

    Rainfall simulation in centrifuge models is important for modelling soil-atmosphere interactions. However, the presence of Coriolis force, drag forces, evaporation and wind within the centrifuge may affect the distribution of rainfall over the model. As a result, development of appropriate centrifuge rain simulators requires a demanding process of experimental trial and error. This paper highlights the key factors involved in controlling rainfall in centrifuge simulations, develops a mathemat...

  13. Internal models of target motion: expected dynamics overrides measured kinematics in timing manual interceptions.

    Science.gov (United States)

    Zago, Myrka; Bosco, Gianfranco; Maffei, Vincenzo; Iosa, Marco; Ivanenko, Yuri P; Lacquaniti, Francesco

    2004-04-01

    Prevailing views on how we time the interception of a moving object assume that the visual inputs are informationally sufficient to estimate the time-to-contact from the object's kinematics. Here we present evidence in favor of a different view: the brain makes the best estimate about target motion based on measured kinematics and an a priori guess about the causes of motion. According to this theory, a predictive model is used to extrapolate time-to-contact from expected dynamics (kinetics). We projected a virtual target moving vertically downward on a wide screen with different randomized laws of motion. In the first series of experiments, subjects were asked to intercept this target by punching a real ball that fell hidden behind the screen and arrived in synchrony with the visual target. Subjects systematically timed their motor responses consistent with the assumption of gravity effects on an object's mass, even when the visual target did not accelerate. With training, the gravity model was not switched off but adapted to nonaccelerating targets by shifting the time of motor activation. In the second series of experiments, there was no real ball falling behind the screen. Instead the subjects were required to intercept the visual target by clicking a mousebutton. In this case, subjects timed their responses consistent with the assumption of uniform motion in the absence of forces, even when the target actually accelerated. Overall, the results are in accord with the theory that motor responses evoked by visual kinematics are modulated by a prior of the target dynamics. The prior appears surprisingly resistant to modifications based on performance errors.

  14. Modelling solar radiation interception in row plantation. 3. Application to a traditional vineyard

    International Nuclear Information System (INIS)

    Sinoquet, H.; Valancogne, C.; Lescure, A.; Bonhomme, R.

    1992-01-01

    Modeling solar radiation interception in row plantation. III. Application to a traditional vineyard. A previously described model of solar radiation interception was applied to a spatially discontinuous canopy: that of a traditional vineyard in which the classical terms of the radiative balance and the spatial distribution of the radiation transmitted to the soil were measured. Comparison of measured and simulated data gave satisfactory agreement for reflected radiation (fig 4), but major discrepancies appeared for mean transmitted radiation (fig 5). The use of small stationary sensors for measuring the transmitted radiation explains the latter observation, since most of the time they measured radiation received on the ground in the sunflecks or in the shaded area rather than mean radiation. This was verified by comparing the measured and simulated spatial distribution of transmitted radiation (figs 7, 8). Finally, the influence of the woody parts which were not taken into consideration in the model was clearly identified : it significantly reduced the transmission of incident radiation (fig 9), and to a greater degrees the closer the sensor was to the vegetation row [fr

  15. Exploring the spatial distribution of light interception and photosynthesis of canopies by means of a functional–structural plant model

    Science.gov (United States)

    Sarlikioti, V.; de Visser, P. H. B.; Marcelis, L. F. M.

    2011-01-01

    Background and Aims At present most process-based models and the majority of three-dimensional models include simplifications of plant architecture that can compromise the accuracy of light interception simulations and, accordingly, canopy photosynthesis. The aim of this paper is to analyse canopy heterogeneity of an explicitly described tomato canopy in relation to temporal dynamics of horizontal and vertical light distribution and photosynthesis under direct- and diffuse-light conditions. Methods Detailed measurements of canopy architecture, light interception and leaf photosynthesis were carried out on a tomato crop. These data were used for the development and calibration of a functional–structural tomato model. The model consisted of an architectural static virtual plant coupled with a nested radiosity model for light calculations and a leaf photosynthesis module. Different scenarios of horizontal and vertical distribution of light interception, incident light and photosynthesis were investigated under diffuse and direct light conditions. Key Results Simulated light interception showed a good correspondence to the measured values. Explicitly described leaf angles resulted in higher light interception in the middle of the plant canopy compared with fixed and ellipsoidal leaf-angle distribution models, although the total light interception remained the same. The fraction of light intercepted at a north–south orientation of rows differed from east–west orientation by 10 % on winter and 23 % on summer days. The horizontal distribution of photosynthesis differed significantly between the top, middle and lower canopy layer. Taking into account the vertical variation of leaf photosynthetic parameters in the canopy, led to approx. 8 % increase on simulated canopy photosynthesis. Conclusions Leaf angles of heterogeneous canopies should be explicitly described as they have a big impact both on light distribution and photosynthesis. Especially, the vertical

  16. Exploring the spatial distribution of light interception and photosynthesis of canopies by means of a functional-structural plant model.

    Science.gov (United States)

    Sarlikioti, V; de Visser, P H B; Marcelis, L F M

    2011-04-01

    At present most process-based models and the majority of three-dimensional models include simplifications of plant architecture that can compromise the accuracy of light interception simulations and, accordingly, canopy photosynthesis. The aim of this paper is to analyse canopy heterogeneity of an explicitly described tomato canopy in relation to temporal dynamics of horizontal and vertical light distribution and photosynthesis under direct- and diffuse-light conditions. Detailed measurements of canopy architecture, light interception and leaf photosynthesis were carried out on a tomato crop. These data were used for the development and calibration of a functional-structural tomato model. The model consisted of an architectural static virtual plant coupled with a nested radiosity model for light calculations and a leaf photosynthesis module. Different scenarios of horizontal and vertical distribution of light interception, incident light and photosynthesis were investigated under diffuse and direct light conditions. Simulated light interception showed a good correspondence to the measured values. Explicitly described leaf angles resulted in higher light interception in the middle of the plant canopy compared with fixed and ellipsoidal leaf-angle distribution models, although the total light interception remained the same. The fraction of light intercepted at a north-south orientation of rows differed from east-west orientation by 10 % on winter and 23 % on summer days. The horizontal distribution of photosynthesis differed significantly between the top, middle and lower canopy layer. Taking into account the vertical variation of leaf photosynthetic parameters in the canopy, led to approx. 8 % increase on simulated canopy photosynthesis. Leaf angles of heterogeneous canopies should be explicitly described as they have a big impact both on light distribution and photosynthesis. Especially, the vertical variation of photosynthesis in canopy is such that the

  17. Prediction of Annual Rainfall Pattern Using Hidden Markov Model ...

    African Journals Online (AJOL)

    ADOWIE PERE

    Hidden Markov model is very influential in stochastic world because of its ... the earth from the clouds. The usual ... Rainfall modelling and ... Markov Models have become popular tools ... environment sciences, University of Jos, plateau state,.

  18. Interception of values as a result of the business model restructuring – case study

    Directory of Open Access Journals (Sweden)

    Nogalski Bogdan

    2017-12-01

    Full Text Available The main objective of this paper is to present a case of value interception as a result of restructuring the business model of a manufacturing company that operates in the agricultural machinery sector. A company that focuses on core activities in the value chain and commissions the manufacturing of most components to specialised suppliers – as a result of restructuring – becomes an integrator that controls all parts of the supply chain; from obtaining a raw material, through its own production of a possibly large number of components, to the distribution of a finished composite product. The framework of the conducted research featured the identification of the relationships occurring between own production of components comprising a given product, and an alternative solution, i.e. possibility of acquiring them by way of co-operation. The authors assumed that a derivative of the value intercepted in the finished product implementation process is the number of components manufactured using own production resources.

  19. Modeling rainfall-runoff relationship using multivariate GARCH model

    Science.gov (United States)

    Modarres, R.; Ouarda, T. B. M. J.

    2013-08-01

    The traditional hydrologic time series approaches are used for modeling, simulating and forecasting conditional mean of hydrologic variables but neglect their time varying variance or the second order moment. This paper introduces the multivariate Generalized Autoregressive Conditional Heteroscedasticity (MGARCH) modeling approach to show how the variance-covariance relationship between hydrologic variables varies in time. These approaches are also useful to estimate the dynamic conditional correlation between hydrologic variables. To illustrate the novelty and usefulness of MGARCH models in hydrology, two major types of MGARCH models, the bivariate diagonal VECH and constant conditional correlation (CCC) models are applied to show the variance-covariance structure and cdynamic correlation in a rainfall-runoff process. The bivariate diagonal VECH-GARCH(1,1) and CCC-GARCH(1,1) models indicated both short-run and long-run persistency in the conditional variance-covariance matrix of the rainfall-runoff process. The conditional variance of rainfall appears to have a stronger persistency, especially long-run persistency, than the conditional variance of streamflow which shows a short-lived drastic increasing pattern and a stronger short-run persistency. The conditional covariance and conditional correlation coefficients have different features for each bivariate rainfall-runoff process with different degrees of stationarity and dynamic nonlinearity. The spatial and temporal pattern of variance-covariance features may reflect the signature of different physical and hydrological variables such as drainage area, topography, soil moisture and ground water fluctuations on the strength, stationarity and nonlinearity of the conditional variance-covariance for a rainfall-runoff process.

  20. Application of the rainfall infiltration breakthrough (RIB) model for ...

    African Journals Online (AJOL)

    Application of the rainfall infiltration breakthrough (RIB) model for groundwater recharge estimation in west coastal South Africa. ... the data from Oudebosch with different rainfall and groundwater abstraction inputs are simulated to explore individual effects on water levels as well as recharge rate estimated on a daily basis.

  1. PDS-Modelling and Regional Bayesian Estimation of Extreme Rainfalls

    DEFF Research Database (Denmark)

    Madsen, Henrik; Rosbjerg, Dan; Harremoës, Poul

    1994-01-01

    rainfalls. The method is applied to two variables: the total precipitation depth and the maximum 10-minute rain intensity of individual storms. On the basis of the atsite modelling a regional analysis is carried out. It is shown that the previous assumption of spatial homogeneity of extreme rainfalls...

  2. Congo Basin rainfall climatology: can we believe the climate models?

    Science.gov (United States)

    Washington, Richard; James, Rachel; Pearce, Helen; Pokam, Wilfried M; Moufouma-Okia, Wilfran

    2013-01-01

    The Congo Basin is one of three key convective regions on the planet which, during the transition seasons, dominates global tropical rainfall. There is little agreement as to the distribution and quantity of rainfall across the basin with datasets differing by an order of magnitude in some seasons. The location of maximum rainfall is in the far eastern sector of the basin in some datasets but the far western edge of the basin in others during March to May. There is no consistent pattern to this rainfall distribution in satellite or model datasets. Resolving these differences is difficult without ground-based data. Moisture flux nevertheless emerges as a useful variable with which to study these differences. Climate models with weak (strong) or even divergent moisture flux over the basin are dry (wet). The paper suggests an approach, via a targeted field campaign, for generating useful climate information with which to confront rainfall products and climate models.

  3. Dynamic Hydrological Modeling in Drylands with TRMM Based Rainfall

    Directory of Open Access Journals (Sweden)

    Elena Tarnavsky

    2013-12-01

    Full Text Available This paper introduces and evaluates DryMOD, a dynamic water balance model of the key hydrological process in drylands that is based on free, public-domain datasets. The rainfall model of DryMOD makes optimal use of spatially disaggregated Tropical Rainfall Measuring Mission (TRMM datasets to simulate hourly rainfall intensities at a spatial resolution of 1-km. Regional-scale applications of the model in seasonal catchments in Tunisia and Senegal characterize runoff and soil moisture distribution and dynamics in response to varying rainfall data inputs and soil properties. The results highlight the need for hourly-based rainfall simulation and for correcting TRMM 3B42 rainfall intensities for the fractional cover of rainfall (FCR. Without FCR correction and disaggregation to 1 km, TRMM 3B42 based rainfall intensities are too low to generate surface runoff and to induce substantial changes to soil moisture storage. The outcomes from the sensitivity analysis show that topsoil porosity is the most important soil property for simulation of runoff and soil moisture. Thus, we demonstrate the benefit of hydrological investigations at a scale, for which reliable information on soil profile characteristics exists and which is sufficiently fine to account for the heterogeneities of these. Where such information is available, application of DryMOD can assist in the spatial and temporal planning of water harvesting according to runoff-generating areas and the runoff ratio, as well as in the optimization of agricultural activities based on realistic representation of soil moisture conditions.

  4. Accuracy of some simple models for predicting particulate interception and retention in agricultural systems

    International Nuclear Information System (INIS)

    Pinder, J.E. III; McLeod, K.W.; Adriano, D.C.

    1989-01-01

    The accuracy of three radionuclide transfer models for predicting the interception and retention of airborne particles by agricultural crops was tested using Pu-bearing aerosols released to the atmosphere from nuclear fuel facilities on the U.S. Department of Energy's Savannah River Plant, near Aiken, SC. The models evaluated were: (1) NRC, the model defined in U.S. Nuclear Regulatory Guide 1.109; (2) FOOD, a model similar to the NRC model that also predicts concentrations in grains; and (3) AGNS, a model developed from the NRC model for the southeastern United States. Plutonium concentrations in vegetation and grain were predicted from measured deposition rates and compared to concentrations observed in the field. Crops included wheat, soybeans, corn and cabbage. Although predictions of the three models differed by less than a factor of 4, they showed different abilities to predict concentrations observed in the field. The NRC and FOOD models consistently underpredicted the observed Pu concentrations for vegetation. The AGNS model was a more accurate predictor of Pu concentrations for vegetation. Both the FOOD and AGNS models accurately predicted the Pu concentrations for grains

  5. Seasonal predictability of Kiremt rainfall in coupled general circulation models

    Science.gov (United States)

    Gleixner, Stephanie; Keenlyside, Noel S.; Demissie, Teferi D.; Counillon, François; Wang, Yiguo; Viste, Ellen

    2017-11-01

    The Ethiopian economy and population is strongly dependent on rainfall. Operational seasonal predictions for the main rainy season (Kiremt, June-September) are based on statistical approaches with Pacific sea surface temperatures (SST) as the main predictor. Here we analyse dynamical predictions from 11 coupled general circulation models for the Kiremt seasons from 1985-2005 with the forecasts starting from the beginning of May. We find skillful predictions from three of the 11 models, but no model beats a simple linear prediction model based on the predicted Niño3.4 indices. The skill of the individual models for dynamically predicting Kiremt rainfall depends on the strength of the teleconnection between Kiremt rainfall and concurrent Pacific SST in the models. Models that do not simulate this teleconnection fail to capture the observed relationship between Kiremt rainfall and the large-scale Walker circulation.

  6. Interception of radioactive fallout by vegetation

    International Nuclear Information System (INIS)

    Chamberlain, A.C.; Garland, J.A.

    1991-12-01

    A review has been carried out of information on the fraction of radioactive material, deposited by dry or wet deposition processes, that is intercepted by vegetation. The amount of information available is limited, but it is clear that a substantial fraction may be intercepted in some circumstances. In dry deposition, the results of measurements indicate that interception decreases with increasing particle size for particles larger than about 40 μm. In low volume water sprays, interception fractions for 7 Be, 89 Sr and microspheres of 3 to 25 μm diameter were similar, but that for periodate was lower. The fraction intercepted decreased with an increase in the amount of simulated rainfall. The data are particularly sparse for dry deposition of particles smaller than 30 μm diameter. In addition, there is no information on interception at the moderate rates of rainfall common in Britain, and little is known of the differences between various species of plants. (author)

  7. Stochastic modeling of hourly rainfall times series in Campania (Italy)

    Science.gov (United States)

    Giorgio, M.; Greco, R.

    2009-04-01

    Occurrence of flowslides and floods in small catchments is uneasy to predict, since it is affected by a number of variables, such as mechanical and hydraulic soil properties, slope morphology, vegetation coverage, rainfall spatial and temporal variability. Consequently, landslide risk assessment procedures and early warning systems still rely on simple empirical models based on correlation between recorded rainfall data and observed landslides and/or river discharges. Effectiveness of such systems could be improved by reliable quantitative rainfall prediction, which can allow gaining larger lead-times. Analysis of on-site recorded rainfall height time series represents the most effective approach for a reliable prediction of local temporal evolution of rainfall. Hydrological time series analysis is a widely studied field in hydrology, often carried out by means of autoregressive models, such as AR, ARMA, ARX, ARMAX (e.g. Salas [1992]). Such models gave the best results when applied to the analysis of autocorrelated hydrological time series, like river flow or level time series. Conversely, they are not able to model the behaviour of intermittent time series, like point rainfall height series usually are, especially when recorded with short sampling time intervals. More useful for this issue are the so-called DRIP (Disaggregated Rectangular Intensity Pulse) and NSRP (Neymann-Scott Rectangular Pulse) model [Heneker et al., 2001; Cowpertwait et al., 2002], usually adopted to generate synthetic point rainfall series. In this paper, the DRIP model approach is adopted, in which the sequence of rain storms and dry intervals constituting the structure of rainfall time series is modeled as an alternating renewal process. Final aim of the study is to provide a useful tool to implement an early warning system for hydrogeological risk management. Model calibration has been carried out with hourly rainfall hieght data provided by the rain gauges of Campania Region civil

  8. Exploring the spatial distribution of light interception and photosynthesis of canopies by means of a functional-structural plant model

    NARCIS (Netherlands)

    Sarlikioti, V.; Visser, de P.H.B.; Marcelis, L.F.M.

    2011-01-01

    Background and Aims - At present most process-based models and the majority of three-dimensional models include simplifications of plant architecture that can compromise the accuracy of light interception simulations and, accordingly, canopy photosynthesis. The aim of this paper is to analyse canopy

  9. Parameters for modelling the interception and retention of deposits from atmosphere by grain and leafy vegetables

    International Nuclear Information System (INIS)

    Simmonds, J.R.; Linsley, G.S.

    1982-01-01

    The Normalised Specific Activity (NSA), a quantity which relates the concentration of a contaminant per unit mass of vegetation to its daily rate of ground deposition, has been used as the basis for determining interception factors and retention half-lives for radioactive contaminants deposited on grain and leafy vegetables. The values are for use in assessing contamination levels on crops at harvest during condition of continuous deposition. The approach implicitly takes account of other processes which influence foliar contamination, namely, translocation and dilution due to plant growth. The respective NSA values for grain and prepared leafy vegetables determined from several separate experimental studies are fairly constant and are of about the same level for fall-out strontium and caesium. There is evidence from previous studies on herbage to suggest that similar NSA values might be expected for other contaminants on grain and leafy vegetables. Plutonium is an exception in that NSA values for grain and prepared leafy vegetables are lower than those for the fission products by factors of between 5 and 10 depending upon the source of the contaminant. Consideration has been given to determining the most appropriate value of the fraction of activity transferred from grain to flour during refining. This is an element dependent parameter and the values estimated for strontium, caesium and plutonium are respectively 0.15, 0.5 and 0.1. The study has indicated the need for data in several areas in order to improve the capability to model interception and retention on field crops in continuous and acute release conditions. (author)

  10. Mathematical rainfall model for hydrographic demarcation of Manabi ...

    African Journals Online (AJOL)

    PROMOTING ACCESS TO AFRICAN RESEARCH ... To achieve this objective, the basins of the Hydrographic Demarcation of Manabí ... Keywords: multiple regression; mathematical model; GIS; Hydrology; rainfall. ... HOW TO USE AJOL.

  11. Model simulations of rainfall over southern Africa and its eastern ...

    African Journals Online (AJOL)

    2016-01-01

    Jan 1, 2016 ... Rainfall simulations over southern and tropical Africa in the form of low-resolution Atmospheric Model ..... provision of sea-surface temperatures and sea-ice fields of a host ...... with variability of the Atlantic Ocean. Bull.

  12. Development of rainfall-runoff forecast model | Oyebode | Journal of ...

    African Journals Online (AJOL)

    ... and meterological variables involved in rainfall-runoff process to improve forecast accuracy of rainfallrunoff. ... The simulation was done using MATLAB® 7.0. The simulation results showed that neurofuzzy-based model has higher coefficient ...

  13. Soft error modeling and analysis of the Neutron Intercepting Silicon Chip (NISC)

    International Nuclear Information System (INIS)

    Celik, Cihangir; Unlue, Kenan; Narayanan, Vijaykrishnan; Irwin, Mary J.

    2011-01-01

    Soft errors are transient errors caused due to excess charge carriers induced primarily by external radiations in the semiconductor devices. Soft error phenomena could be used to detect thermal neutrons with a neutron monitoring/detection system by enhancing soft error occurrences in the memory devices. This way, one can convert all semiconductor memory devices into neutron detection systems. Such a device is being developed at The Pennsylvania State University and named Neutron Intercepting Silicon Chip (NISC). The NISC is envisioning a miniature, power efficient, and active/passive operation neutron sensor/detector system. NISC aims to achieve this goal by introducing 10 B-enriched Borophosphosilicate Glass (BPSG) insulation layers in the semiconductor memories. In order to model and analyze the NISC, an analysis tool using Geant4 as the transport and tracking engine is developed for the simulation of the charged particle interactions in the semiconductor memory model, named NISC Soft Error Analysis Tool (NISCSAT). A simple model with 10 B-enriched layer on top of the lumped silicon region is developed in order to represent the semiconductor memory node. Soft error probability calculations were performed via the NISCSAT with both single node and array configurations to investigate device scaling by using different node dimensions in the model. Mono-energetic, mono-directional thermal and fast neutrons are used as the neutron sources. Soft error contribution due to the BPSG layer is also investigated with different 10 B contents and the results are presented in this paper.

  14. Simulation of daily rainfall through markov chain modeling

    International Nuclear Information System (INIS)

    Sadiq, N.

    2015-01-01

    Being an agricultural country, the inhabitants of dry land in cultivated areas mainly rely on the daily rainfall for watering their fields. A stochastic model based on first order Markov Chain was developed to simulate daily rainfall data for Multan, D. I. Khan, Nawabshah, Chilas and Barkhan for the period 1981-2010. Transitional probability matrices of first order Markov Chain was utilized to generate the daily rainfall occurrence while gamma distribution was used to generate the daily rainfall amount. In order to achieve the parametric values of mentioned cities, method of moments is used to estimate the shape and scale parameters which lead to synthetic sequence generation as per gamma distribution. In this study, unconditional and conditional probabilities of wet and dry days in sum with means and standard deviations are considered as the essential parameters for the simulated stochastic generation of daily rainfalls. It has been found that the computerized synthetic rainfall series concurred pretty well with the actual observed rainfall series. (author)

  15. Distributed modelling of shallow landslides triggered by intense rainfall

    Directory of Open Access Journals (Sweden)

    G. B. Crosta

    2003-01-01

    Full Text Available Hazard assessment of shallow landslides represents an important aspect of land management in mountainous areas. Among all the methods proposed in the literature, physically based methods are the only ones that explicitly includes the dynamic factors that control landslide triggering (rainfall pattern, land-use. For this reason, they allow forecasting both the temporal and the spatial distribution of shallow landslides. Physically based methods for shallow landslides are based on the coupling of the infinite slope stability analysis with hydrological models. Three different grid-based distributed hydrological models are presented in this paper: a steady state model, a transient "piston-flow" wetting front model, and a transient diffusive model. A comparative test of these models was performed to simulate landslide occurred during a rainfall event (27–28 June 1997 that triggered hundreds of shallow landslides within Lecco province (central Southern Alps, Italy. In order to test the potential for a completely distributed model for rainfall-triggered landslides, radar detected rainfall intensity has been used. A new procedure for quantitative evaluation of distributed model performance is presented and used in this paper. The diffusive model results in the best model for the simulation of shallow landslide triggering after a rainfall event like the one that we have analysed. Finally, radar data available for the June 1997 event permitted greatly improving the simulation. In particular, radar data allowed to explain the non-uniform distribution of landslides within the study area.

  16. Modelling solar radiation interception in row plantation. 3. Application to a traditional vineyard

    International Nuclear Information System (INIS)

    Sinoquet, H.; Valancogne, C.; Lescure, A.; Bonhomme, R.

    1992-01-01

    A previously described model of solar radiation interception was applied to a spatially discontinuous canopy: that of a traditional vineyard in which the classical terms of the radiative balance and the spatial distribution of the radiation transmitted to the soil were measured. Comparison of measured and simulated data gave satisfactory agreement for reflected radiation (fig 4), but major discrepancies appeared for mean transmitted radiation (fig 5). The use of small stationary sensors for measuring the transmitted radiation explains the latter observation, since most of the time they measured radiation received on the ground in the sunflecks or in the shaded area rather than mean radiation. This was verified by comparing the measured and simulated spatial distribution of transmitted radiation (figs 7, 8). Finally, the influence of the woody parts which were not taken into consideration in the model was clearly identified : it significantly reduced the transmission of incident radiation (fig 9), and to a greater degrees the closer the sensor was to the vegetation row. (author) [fr

  17. The modification of the typhoon rainfall climatology model in Taiwan

    Directory of Open Access Journals (Sweden)

    C.-S. Lee

    2013-01-01

    Full Text Available This study is focused on the modification of a typhoon rainfall climatological model, by using the dataset up to 2006 and including data collected from rain gauge stations established after the 921 earthquake (1999. Subsequently, the climatology rainfall models for westward- and northward-moving typhoons are established by using the typhoon track classification from the Central Weather Bureau. These models are also evaluated and examined using dependent cases collected between 1989 and 2006 and independent cases collected from 2007 to 2011. For the dependent cases, the average total rainfall at all rain gauge stations forecasted using the climatology rainfall models for westward- (W-TRCM12 and northward-moving (N-TRCM12 typhoons is superior to that obtained using the original climatological model (TRCM06. Model W-TRCM12 significantly improves the precipitation underestimation of model TRCM06. The independent cases show that model W-TRCM12 provides better accumulated rainfall forecasts and distributions than model TRCM06. A climatological model for accompanied northeastern monsoons (A-TRCM12 for special typhoon types has also been established. The current A-TRCM12 model only contains five historical cases and various typhoon combinations can cause precipitation in different regions. Therefore, precipitation is likely to be significantly overestimated and high false alarm ratios are likely to occur in specific regions. For example, model A-TRCM12 significantly overestimates the rainfall forecast for Typhoon Mitag, an independent case from 2007. However, it has a higher probability of detection than model TRCM06. From a disaster prevention perspective, a high probability of detection is much more important than a high false alarm ratio. The modified models can contribute significantly to operational forecast.

  18. Assessment of runoff contributing catchment areas in rainfall runoff modelling

    DEFF Research Database (Denmark)

    Thorndahl, Søren; Johansen, C.; Schaarup-Jensen, Kjeld

    2006-01-01

    In numerical modelling of rainfall caused runoff in urban sewer systems an essential parameter is the hydrological reduction factor which defines the percentage of the impervious area contributing to the surface flow towards the sewer. As the hydrological processes during a rainfall are difficult...... to determine with significant precision the hydrological reduction factor is implemented to account all hydrological losses except the initial loss. This paper presents an inconsistency between calculations of the hydrological reduction factor, based on measurements of rainfall and runoff, and till now...... recommended literature values for residential areas. It is proven by comparing rainfall-runoff measurements from four different residential catchments that the literature values of the hydrological reduction factor are over-estimated for this type of catchment. In addition, different catchment descriptions...

  19. Downscaling of rainfall in Peru using Generalised Linear Models

    Science.gov (United States)

    Bergin, E.; Buytaert, W.; Onof, C.; Wheater, H.

    2012-04-01

    The assessment of water resources in the Peruvian Andes is particularly important because the Peruvian economy relies heavily on agriculture. Much of the agricultural land is situated near to the coast and relies on large quantities of water for irrigation. The simulation of synthetic rainfall series is thus important to evaluate the reliability of water supplies for current and future scenarios of climate change. In addition to water resources concerns, there is also a need to understand extreme heavy rainfall events, as there was significant flooding in Machu Picchu in 2010. The region exhibits a reduction of rainfall in 1983, associated with El Nino Southern Oscillation (SOI). NCEP Reanalysis 1 data was used to provide weather variable data. Correlations were calculated for several weather variables using raingauge data in the Andes. These were used to evaluate teleconnections and provide suggested covariates for the downscaling model. External covariates used in the model include sea level pressure and sea surface temperature over the region of the Humboldt Current. Relative humidity and temperature data over the region are also included. The SOI teleconnection is also used. Covariates are standardised using observations for 1960-1990. The GlimClim downscaling model was used to fit a stochastic daily rainfall model to 13 sites in the Peruvian Andes. Results indicate that the model is able to reproduce rainfall statistics well, despite the large area used. Although the correlation between individual rain gauges is generally quite low, all sites are affected by similar weather patterns. This is an assumption of the GlimClim downscaling model. Climate change scenarios are considered using several GCM outputs for the A1B scenario. GCM data was corrected for bias using 1960-1990 outputs from the 20C3M scenario. Rainfall statistics for current and future scenarios are compared. The region shows an overall decrease in mean rainfall but with an increase in variance.

  20. EVALUATION OF RAINFALL-RUNOFF MODELS FOR MEDITERRANEAN SUBCATCHMENTS

    Directory of Open Access Journals (Sweden)

    A. Cilek

    2016-06-01

    Full Text Available The development and the application of rainfall-runoff models have been a corner-stone of hydrological research for many decades. The amount of rainfall and its intensity and variability control the generation of runoff and the erosional processes operating at different scales. These interactions can be greatly variable in Mediterranean catchments with marked hydrological fluctuations. The aim of the study was to evaluate the performance of rainfall-runoff model, for rainfall-runoff simulation in a Mediterranean subcatchment. The Pan-European Soil Erosion Risk Assessment (PESERA, a simplified hydrological process-based approach, was used in this study to combine hydrological surface runoff factors. In total 128 input layers derived from data set includes; climate, topography, land use, crop type, planting date, and soil characteristics, are required to run the model. Initial ground cover was estimated from the Landsat ETM data provided by ESA. This hydrological model was evaluated in terms of their performance in Goksu River Watershed, Turkey. It is located at the Central Eastern Mediterranean Basin of Turkey. The area is approximately 2000 km2. The landscape is dominated by bare ground, agricultural and forests. The average annual rainfall is 636.4mm. This study has a significant importance to evaluate different model performances in a complex Mediterranean basin. The results provided comprehensive insight including advantages and limitations of modelling approaches in the Mediterranean environment.

  1. Markov modulated Poisson process models incorporating covariates for rainfall intensity.

    Science.gov (United States)

    Thayakaran, R; Ramesh, N I

    2013-01-01

    Time series of rainfall bucket tip times at the Beaufort Park station, Bracknell, in the UK are modelled by a class of Markov modulated Poisson processes (MMPP) which may be thought of as a generalization of the Poisson process. Our main focus in this paper is to investigate the effects of including covariate information into the MMPP model framework on statistical properties. In particular, we look at three types of time-varying covariates namely temperature, sea level pressure, and relative humidity that are thought to be affecting the rainfall arrival process. Maximum likelihood estimation is used to obtain the parameter estimates, and likelihood ratio tests are employed in model comparison. Simulated data from the fitted model are used to make statistical inferences about the accumulated rainfall in the discrete time interval. Variability of the daily Poisson arrival rates is studied.

  2. Rainfall estimation with TFR model using Ensemble Kalman filter

    Science.gov (United States)

    Asyiqotur Rohmah, Nabila; Apriliani, Erna

    2018-03-01

    Rainfall fluctuation can affect condition of other environment, correlated with economic activity and public health. The increasing of global average temperature is influenced by the increasing of CO2 in the atmosphere, which caused climate change. Meanwhile, the forests as carbon sinks that help keep the carbon cycle and climate change mitigation. Climate change caused by rainfall intensity deviations can affect the economy of a region, and even countries. It encourages research on rainfall associated with an area of forest. In this study, the mathematics model that used is a model which describes the global temperatures, forest cover, and seasonal rainfall called the TFR (temperature, forest cover, and rainfall) model. The model will be discretized first, and then it will be estimated by the method of Ensemble Kalman Filter (EnKF). The result shows that the more ensembles used in estimation, the better the result is. Also, the accurateness of simulation result is influenced by measurement variable. If a variable is measurement data, the result of simulation is better.

  3. The role of interception in the hydrological cycle

    NARCIS (Netherlands)

    Gerrits, A.M.J.

    2010-01-01

    Interception is the part of the rainfall that is intercepted by the earth’s surface and which subsequently evaporates. In this definition the earth’s surface includes everything that becomes wet after a rainfall event and that dries out soon after. It includes: vegetation, soil surface, litter,

  4. Influence of radioactive contamination to agricultural products by rainfall during a nuclear accident

    International Nuclear Information System (INIS)

    Hwang, W. T.; Han, M. H.; Choi, Y. H.; Lee, H. S.; Lee, C. W.

    2001-01-01

    For the consideration of the effects on radioactive contamination of agricultural products by rainfall during a nuclear accident, the wet interception coefficients for the plants were derived, and the previous dynamic food chain model was also modified. From the results, radioactive contamination of agricultural products was greatly decreased by rainfall, and it decreased dramatically according to increase of rainfall amount. It means that the predictive contamination in agricultural products using the previous dynamic food chain model, in which dry interception to the plants is only considered, can be overestimated. Influence of rainfall on the contamination of agricultural products was the most sensitive for 131 I, and the least sensitive for 90 Sr

  5. Modeling Spatial Dependence of Rainfall Extremes Across Multiple Durations

    Science.gov (United States)

    Le, Phuong Dong; Leonard, Michael; Westra, Seth

    2018-03-01

    Determining the probability of a flood event in a catchment given that another flood has occurred in a nearby catchment is useful in the design of infrastructure such as road networks that have multiple river crossings. These conditional flood probabilities can be estimated by calculating conditional probabilities of extreme rainfall and then transforming rainfall to runoff through a hydrologic model. Each catchment's hydrological response times are unlikely to be the same, so in order to estimate these conditional probabilities one must consider the dependence of extreme rainfall both across space and across critical storm durations. To represent these types of dependence, this study proposes a new approach for combining extreme rainfall across different durations within a spatial extreme value model using max-stable process theory. This is achieved in a stepwise manner. The first step defines a set of common parameters for the marginal distributions across multiple durations. The parameters are then spatially interpolated to develop a spatial field. Storm-level dependence is represented through the max-stable process for rainfall extremes across different durations. The dependence model shows a reasonable fit between the observed pairwise extremal coefficients and the theoretical pairwise extremal coefficient function across all durations. The study demonstrates how the approach can be applied to develop conditional maps of the return period and return level across different durations.

  6. Regionalising Parameters of a Conceptual Rainfall-Runoff Model for ...

    African Journals Online (AJOL)

    IHACRES, a lumped conceptual rainfall-runoff model, was calibrated to six catchments ranging in size from 49km2 to 600 km2 within the upper Tana River basin to obtain a set of model parameters that characterise the hydrological behaviour within the region. Physical catchment attributes indexing topography, soil and ...

  7. Global estimate of lichen and bryophyte contributions to forest precipitation interception

    Science.gov (United States)

    Van Stan, John; Porada, Philipp; Kleidon, Axel

    2017-04-01

    Interception of precipitation by forest canopies plays an important role in its partitioning to evaporation, transpiration and runoff. Field observations show arboreal lichens and bryophytes can substantially enhance forests' precipitation storage and evaporation. However, representations of canopy interception in global land surface models currently ignore arboreal lichen and bryophyte contributions. This study uses the lichen and bryophyte model (LiBry) to provide the first process-based modelling approach estimating these organisms' contributions to canopy water storage and evaporation. The global mean value of forest water storage capacity increased significantly from 0.87 mm to 1.33 mm by the inclusion of arboreal poikilohydric organisms. Global forest canopy evaporation of intercepted precipitation was also greatly enhanced by 44%. Ratio of total versus bare canopy global evaporation exceeded 2 in many forested regions. This altered global patterns in canopy water storage, evaporation, and ultimately the proportion of rainfall evaporated. A sensitivity analysis was also performed. Results indicate rainfall interception is of larger magnitude than previously reported by global land surface modelling work because of the important role of lichen and bryophytes in rainfall interception.

  8. An Overview of Rainfall-Runoff Model Types

    Science.gov (United States)

    This report explores rainfall-runoff models, their generation methods, and the categories under which they fall. Runoff plays an important role in the hydrological cycle by returning excess precipitation to the oceans and controlling how much water flows into stream systems. Mode...

  9. DAILY RAINFALL-RUNOFF MODELLING BY NEURAL NETWORKS ...

    African Journals Online (AJOL)

    K. Benzineb, M. Remaoun

    2016-09-01

    Sep 1, 2016 ... The hydrologic behaviour modelling of w. Journal of ... i Ouahrane's basin from rainfall-runoff relation which is non-linea networks ... will allow checking efficiency of formal neural networks for flows simulation in semi-arid zone.

  10. Interpolation of daily rainfall using spatiotemporal models and clustering

    KAUST Repository

    Militino, A. F.

    2014-06-11

    Accumulated daily rainfall in non-observed locations on a particular day is frequently required as input to decision-making tools in precision agriculture or for hydrological or meteorological studies. Various solutions and estimation procedures have been proposed in the literature depending on the auxiliary information and the availability of data, but most such solutions are oriented to interpolating spatial data without incorporating temporal dependence. When data are available in space and time, spatiotemporal models usually provide better solutions. Here, we analyse the performance of three spatiotemporal models fitted to the whole sampled set and to clusters within the sampled set. The data consists of daily observations collected from 87 manual rainfall gauges from 1990 to 2010 in Navarre, Spain. The accuracy and precision of the interpolated data are compared with real data from 33 automated rainfall gauges in the same region, but placed in different locations than the manual rainfall gauges. Root mean squared error by months and by year are also provided. To illustrate these models, we also map interpolated daily precipitations and standard errors on a 1km2 grid in the whole region. © 2014 Royal Meteorological Society.

  11. Interpolation of daily rainfall using spatiotemporal models and clustering

    KAUST Repository

    Militino, A. F.; Ugarte, M. D.; Goicoa, T.; Genton, Marc G.

    2014-01-01

    Accumulated daily rainfall in non-observed locations on a particular day is frequently required as input to decision-making tools in precision agriculture or for hydrological or meteorological studies. Various solutions and estimation procedures have been proposed in the literature depending on the auxiliary information and the availability of data, but most such solutions are oriented to interpolating spatial data without incorporating temporal dependence. When data are available in space and time, spatiotemporal models usually provide better solutions. Here, we analyse the performance of three spatiotemporal models fitted to the whole sampled set and to clusters within the sampled set. The data consists of daily observations collected from 87 manual rainfall gauges from 1990 to 2010 in Navarre, Spain. The accuracy and precision of the interpolated data are compared with real data from 33 automated rainfall gauges in the same region, but placed in different locations than the manual rainfall gauges. Root mean squared error by months and by year are also provided. To illustrate these models, we also map interpolated daily precipitations and standard errors on a 1km2 grid in the whole region. © 2014 Royal Meteorological Society.

  12. modelling relationship between rainfall variability and yields

    African Journals Online (AJOL)

    , S. and ... factors to rice yield. Adebayo and Adebayo (1997) developed double log multiple regression model to predict rice yield in Adamawa State, Nigeria. The general form of .... the second are the crop yield/values for millet and sorghum ...

  13. Modeling rainfall-runoff process using soft computing techniques

    Science.gov (United States)

    Kisi, Ozgur; Shiri, Jalal; Tombul, Mustafa

    2013-02-01

    Rainfall-runoff process was modeled for a small catchment in Turkey, using 4 years (1987-1991) of measurements of independent variables of rainfall and runoff values. The models used in the study were Artificial Neural Networks (ANNs), Adaptive Neuro-Fuzzy Inference System (ANFIS) and Gene Expression Programming (GEP) which are Artificial Intelligence (AI) approaches. The applied models were trained and tested using various combinations of the independent variables. The goodness of fit for the model was evaluated in terms of the coefficient of determination (R2), root mean square error (RMSE), mean absolute error (MAE), coefficient of efficiency (CE) and scatter index (SI). A comparison was also made between these models and traditional Multi Linear Regression (MLR) model. The study provides evidence that GEP (with RMSE=17.82 l/s, MAE=6.61 l/s, CE=0.72 and R2=0.978) is capable of modeling rainfall-runoff process and is a viable alternative to other applied artificial intelligence and MLR time-series methods.

  14. Application of the Forhyd model to simulate net precipitation and intercepted water evaporation in forest canopies in Colombian amazonia

    International Nuclear Information System (INIS)

    Tellez Guio, Patricia; Boschell Villamarin, Francisco; Tobon Marin, Conrado

    2005-01-01

    Hydrologic simulation is a technique, which allows us to understand the relationships among hydrological, biological and ecological variables in an ecosystem. In this research, the FORHYD model is used to simulate the net precipitation and the water intercepted by the canopies of a mature forest, a 30-year old secondary forest, an 18-year old secondary forest, a 5-year old secondary forest, and a shifting cultivation plot, all located in Colombia's amazonia. The model calculates the water budget of the canopy by using the precipitation rates, canopy drainage and evaporation of the water intercepted by the canopy. This paper is the second one in a series of papers reporting the results of the research on the simulation of the hydrological fluxes in three different land use types of Colombian amazonia. The research was carried out in middle Caqueta of Colombian amazonia (northwest amazon basin). The FORHYD model was calibrated and validated by using field observations of the climate, net precipitation (PT), thoughtful (TH) and stem flow (ST), which were monitored during a period of 15 months from March 2001 to June 2002. These observations were used as both input variables and diagnostic variables to probe the model's precision to simulate field observations. Results showed that FORHYD simulates with a good precision the net precipitation and the evaporation of the water intercepted by the canopy. However, the model's precision depends on a good parameterization, which in turn depends on a good database of field observations. The model is a good tool for simulating the hydrological cycle and can be used to simulate critical scenarios of climate variability

  15. Modelling and assessment of urban flood hazards based on rainfall intensity-duration-frequency curves reformation

    OpenAIRE

    Ghazavi, Reza; Moafi Rabori, Ali; Ahadnejad Reveshty, Mohsen

    2016-01-01

    Estimate design storm based on rainfall intensity–duration–frequency (IDF) curves is an important parameter for hydrologic planning of urban areas. The main aim of this study was to estimate rainfall intensities of Zanjan city watershed based on overall relationship of rainfall IDF curves and appropriate model of hourly rainfall estimation (Sherman method, Ghahreman and Abkhezr method). Hydrologic and hydraulic impacts of rainfall IDF curves change in flood properties was evaluated via Stormw...

  16. Parameter estimation in stochastic rainfall-runoff models

    DEFF Research Database (Denmark)

    Jonsdottir, Harpa; Madsen, Henrik; Palsson, Olafur Petur

    2006-01-01

    A parameter estimation method for stochastic rainfall-runoff models is presented. The model considered in the paper is a conceptual stochastic model, formulated in continuous-discrete state space form. The model is small and a fully automatic optimization is, therefore, possible for estimating all...... the parameter values are optimal for simulation or prediction. The data originates from Iceland and the model is designed for Icelandic conditions, including a snow routine for mountainous areas. The model demands only two input data series, precipitation and temperature and one output data series...

  17. Evaluation of Weed Diversity and Modelling Light Interception and Distribution in Multiple and Sole Cropping of Millet (Setaria italica L. and Bean (Phaseolus vulgaris L.

    Directory of Open Access Journals (Sweden)

    A Koocheki

    2013-10-01

    Full Text Available In order to investigate the weed diversity and modeling light interception in sole and intercropping millet and bean an experiment was conducted as complete randomized block design with 4 treatments and 4 replications at the Agricultural Research Station, Ferdowsi University of Mashhad, Iran, during 2008. Treatments included monocultures, intercropping of millet and bean and a control treatment where weeds grew without crops. In this experiment Shannon diversity index and Sorensen similarity index was investigated at six stages. Results indicated that in each stage Shannon index was affected by treatments. In first stage intercropping had the lowest weed diversity but in another stages it has no significant with monocultures. Control treatment has highest weed diversity. For modeling light interception were used INTERCOM model. Results showed that in light interception plant height and leaf distribution was more effective than LAI (Leaf Area Index. Light interception in intercropping was more effective than monoculture.

  18. Interceptação das chuvas em um fragmento de floresta da Mata Atlântica na Bacia do Prata, Recife, PE Rainfall interception in an Atlantic Forest fragment in the Prata Basin, Recife, PE

    Directory of Open Access Journals (Sweden)

    Albert Einstein Spindola Saraiva de Moura

    2009-06-01

    Full Text Available A mata de Dois Irmãos é uma das poucas áreas remanescentes da Floresta Atlântica no Estado de Pernambuco. Nela estão inseridos os açudes do Meio, do Prata e Dois Irmãos que compõem a bacia hidrográfica do Prata. Este trabalho teve como objetivo estudar a partição das chuvas em um fragmento de Floresta Atlântica na Bacia do Prata em Recife, PE. Para obtenção dos dados de precipitação sob florestas, foram instalados 24 interceptômetros e selecionadas 20 árvores do estrato superior, e 10 árvores do sub-bosque foram escolhidas para obter os dados de escoamento pelo tronco. Encontraram-se perdas por interceptação de 208,3 mm, precipitação efetiva de 1.431,7 mm, precipitação interna de 1.392,4 mm, escoamento pelo tronco das árvores do estrato superior de 6,6 mm e escoamento pelo sub-bosque de 32,8 mm, correspondendo a 12,7%, 87,3%, 84,9%, 0,4% e 2%, respectivamente, do total precipitado de 1.464 mm.The Dois Irmãos forest is one of the few remaining areas of the Atlantic Forest in the State of Pernambuco. The dams of Meio, Prata and Dois Irmãos, which belong to the Prata Basin, are in it. The objective of this work was to study the rainfall partitioning in a fragment of the Atlantic forest in the Prata basin, in Recife, PE. 24 raingouges were installed in the interior of the forest to measure the throughfall and 20 trees of superior extract and 10 of the sub-forest were selected to determine the stemflow. The results showed values of loss interception of 208,3 mm, net precipitation of 1431,7 mm, throughfall of 1392,4 mm, stemflow by superior stratum of 6,6 mm and stemflow by sub-forest of 32,8 mm, corresponding to 12,7%, 87,3%, 84,9%, 0,4% and 2%, respectively.

  19. Random Modeling of Daily Rainfall and Runoff Using a Seasonal Model and Wavelet Denoising

    Directory of Open Access Journals (Sweden)

    Chien-ming Chou

    2014-01-01

    Full Text Available Instead of Fourier smoothing, this study applied wavelet denoising to acquire the smooth seasonal mean and corresponding perturbation term from daily rainfall and runoff data in traditional seasonal models, which use seasonal means for hydrological time series forecasting. The denoised rainfall and runoff time series data were regarded as the smooth seasonal mean. The probability distribution of the percentage coefficients can be obtained from calibrated daily rainfall and runoff data. For validated daily rainfall and runoff data, percentage coefficients were randomly generated according to the probability distribution and the law of linear proportion. Multiplying the generated percentage coefficient by the smooth seasonal mean resulted in the corresponding perturbation term. Random modeling of daily rainfall and runoff can be obtained by adding the perturbation term to the smooth seasonal mean. To verify the accuracy of the proposed method, daily rainfall and runoff data for the Wu-Tu watershed were analyzed. The analytical results demonstrate that wavelet denoising enhances the precision of daily rainfall and runoff modeling of the seasonal model. In addition, the wavelet denoising technique proposed in this study can obtain the smooth seasonal mean of rainfall and runoff processes and is suitable for modeling actual daily rainfall and runoff processes.

  20. Influence of rainfall observation network on model calibration and application

    Directory of Open Access Journals (Sweden)

    A. Bárdossy

    2008-01-01

    Full Text Available The objective in this study is to investigate the influence of the spatial resolution of the rainfall input on the model calibration and application. The analysis is carried out by varying the distribution of the raingauge network. A meso-scale catchment located in southwest Germany has been selected for this study. First, the semi-distributed HBV model is calibrated with the precipitation interpolated from the available observed rainfall of the different raingauge networks. An automatic calibration method based on the combinatorial optimization algorithm simulated annealing is applied. The performance of the hydrological model is analyzed as a function of the raingauge density. Secondly, the calibrated model is validated using interpolated precipitation from the same raingauge density used for the calibration as well as interpolated precipitation based on networks of reduced and increased raingauge density. Lastly, the effect of missing rainfall data is investigated by using a multiple linear regression approach for filling in the missing measurements. The model, calibrated with the complete set of observed data, is then run in the validation period using the above described precipitation field. The simulated hydrographs obtained in the above described three sets of experiments are analyzed through the comparisons of the computed Nash-Sutcliffe coefficient and several goodness-of-fit indexes. The results show that the model using different raingauge networks might need re-calibration of the model parameters, specifically model calibrated on relatively sparse precipitation information might perform well on dense precipitation information while model calibrated on dense precipitation information fails on sparse precipitation information. Also, the model calibrated with the complete set of observed precipitation and run with incomplete observed data associated with the data estimated using multiple linear regressions, at the locations treated as

  1. Warning Model for Shallow Landslides Induced by Extreme Rainfall

    Directory of Open Access Journals (Sweden)

    Lien-Kwei Chien

    2015-08-01

    Full Text Available In this study, the geophysical properties of the landslide-prone catchment of the Gaoping River in Taiwan were investigated using zones based on landslide history in conjunction with landslide analysis using a deterministic approach based on the TRIGRS (Transient Rainfall Infiltration and Grid-based Regional Slope-Stability model. Typhoon Morakot in 2009 was selected as a simulation scenario to calibrate the combination of geophysical parameters in each zone before analyzing changes in the factor of safety (FS. Considering the amount of response time required for typhoons, suitable FS thresholds for landslide warnings are proposed for each town in the catchment area. Typhoon Fanapi of 2010 was used as a test scenario to verify the applicability of the FS as well as the efficacy of the cumulative rainfall thresholds derived in this study. Finally, the amount of response time provided by the FS thresholds in cases of yellow and red alerts was determined. All five of the landslide events reported by the Soil and Water Conservation Bureau were listed among the unstable sites identified in the proposed model, thereby demonstrating its effectiveness and accuracy in determining unstable areas and areas that require evacuation. These cumulative rainfall thresholds provide a valuable reference to guide disaster prevention authorities in the issuance of yellow and red alerts with the ability to reduce losses and save lives.

  2. Fog interception by Ball moss (Tillandsia recurvata)

    Science.gov (United States)

    Guevara-Escobar, A.; Cervantes-Jiménez, M.; Suzán-Azpiri, H.; González-Sosa, E.; Hernández-Sandoval, L.; Malda-Barrera, G.; Martínez-Díaz, M.

    2011-08-01

    Interception losses are a major influence in the water yield of vegetated areas. For most storms, rain interception results in less water reaching the ground. However, fog interception can increase the overall water storage capacity of the vegetation and once the storage is exceeded, fog drip is a common hydrological input. Fog interception is disregarded in water budgets of semiarid regions, but for some plant communities, it could be a mechanism offsetting evaporation losses. Tillandsia recurvata is a cosmopolitan epiphyte adapted to arid habitats where fog may be an important water source. Therefore, the interception storage capacity by T. recurvata was measured in controlled conditions and applying simulated rain or fog. Juvenile, vegetative specimens were used to determine the potential upperbound storage capacities. The storage capacity was proportional to dry weight mass. Interception storage capacity (Cmin) was 0.19 and 0.56 mm for rainfall and fog respectively. The coefficients obtained in the laboratory were used together with biomass measurements for T. recurvata in a xeric scrub to calculate the depth of water intercepted by rain. T. recurvata contributed 20 % to the rain interception capacity of their shrub hosts: Acacia farnesiana and Prosopis laevigata and; also potentially intercepted 4.8 % of the annual rainfall. Nocturnal stomatic opening in T. recurvata is not only relevant for CO2 but for water vapor, as suggested by the higher weight change of specimens wetted with fog for 1 h at dark in comparison to those wetted during daylight (543 ± 77 vs. 325 ± 56 mg, p = 0.048). The storage capacity of T. recurvata leaf surfaces could increase the amount of water available for evaporation, but as this species colonise montane forests, the effect could be negative on water recharge, because potential storage capacity is very high, in the laboratory experiments it took up to 12 h at a rate of 0.26 l h-1 to reach saturation conditions when fog was applied.

  3. Fog interception by Ball moss (Tillandsia recurvata

    Directory of Open Access Journals (Sweden)

    G. Malda-Barrera

    2011-08-01

    Full Text Available Interception losses are a major influence in the water yield of vegetated areas. For most storms, rain interception results in less water reaching the ground. However, fog interception can increase the overall water storage capacity of the vegetation and once the storage is exceeded, fog drip is a common hydrological input. Fog interception is disregarded in water budgets of semiarid regions, but for some plant communities, it could be a mechanism offsetting evaporation losses. Tillandsia recurvata is a cosmopolitan epiphyte adapted to arid habitats where fog may be an important water source. Therefore, the interception storage capacity by T. recurvata was measured in controlled conditions and applying simulated rain or fog. Juvenile, vegetative specimens were used to determine the potential upperbound storage capacities. The storage capacity was proportional to dry weight mass. Interception storage capacity (Cmin was 0.19 and 0.56 mm for rainfall and fog respectively. The coefficients obtained in the laboratory were used together with biomass measurements for T. recurvata in a xeric scrub to calculate the depth of water intercepted by rain. T. recurvata contributed 20 % to the rain interception capacity of their shrub hosts: Acacia farnesiana and Prosopis laevigata and; also potentially intercepted 4.8 % of the annual rainfall. Nocturnal stomatic opening in T. recurvata is not only relevant for CO2 but for water vapor, as suggested by the higher weight change of specimens wetted with fog for 1 h at dark in comparison to those wetted during daylight (543 ± 77 vs. 325 ± 56 mg, p = 0.048. The storage capacity of T. recurvata leaf surfaces could increase the amount of water available for evaporation, but as this species colonise montane forests, the effect could be negative on water recharge, because potential storage capacity is very high, in the laboratory experiments it took up to 12 h at a rate of 0.26 l h−1 to reach saturation conditions

  4. Modelling rainfall amounts using mixed-gamma model for Kuantan district

    Science.gov (United States)

    Zakaria, Roslinazairimah; Moslim, Nor Hafizah

    2017-05-01

    An efficient design of flood mitigation and construction of crop growth models depend upon good understanding of the rainfall process and characteristics. Gamma distribution is usually used to model nonzero rainfall amounts. In this study, the mixed-gamma model is applied to accommodate both zero and nonzero rainfall amounts. The mixed-gamma model presented is for the independent case. The formulae of mean and variance are derived for the sum of two and three independent mixed-gamma variables, respectively. Firstly, the gamma distribution is used to model the nonzero rainfall amounts and the parameters of the distribution (shape and scale) are estimated using the maximum likelihood estimation method. Then, the mixed-gamma model is defined for both zero and nonzero rainfall amounts simultaneously. The formulae of mean and variance for the sum of two and three independent mixed-gamma variables derived are tested using the monthly rainfall amounts from rainfall stations within Kuantan district in Pahang Malaysia. Based on the Kolmogorov-Smirnov goodness of fit test, the results demonstrate that the descriptive statistics of the observed sum of rainfall amounts is not significantly different at 5% significance level from the generated sum of independent mixed-gamma variables. The methodology and formulae demonstrated can be applied to find the sum of more than three independent mixed-gamma variables.

  5. Real Time Updating in Distributed Urban Rainfall Runoff Modelling

    DEFF Research Database (Denmark)

    Borup, Morten; Madsen, Henrik

    that are being updated from system measurements was studied. The results showed that the fact alone that it takes time for rainfall data to travel the distance between gauges and catchments has such a big negative effect on the forecast skill of updated models, that it can justify the choice of even very...... as in a real data case study. The results confirmed that the method is indeed suitable for DUDMs and that it can be used to utilise upstream as well as downstream water level and flow observations to improve model estimates and forecasts. Due to upper and lower sensor limits many sensors in urban drainage...

  6. Impact of the Rainfall Duration and Temporal Rainfall Distribution Defined Using the Huff Curves on the Hydraulic Flood Modelling Results

    Directory of Open Access Journals (Sweden)

    Nejc Bezak

    2018-02-01

    Full Text Available In the case of ungauged catchments, different procedures can be used to derive the design hydrograph and design peak discharge, which are crucial input data for the design of different hydrotechnical engineering structures, or the production of flood hazard maps. One of the possible approaches involves using a hydrological model where one can calculate the design hydrograph through the design of a rainfall event. This study investigates the impact of the design rainfall on the combined one-dimensional/two-dimensional (1D/2D hydraulic modelling results. The Glinščica Stream catchment located in Slovenia (central Europe is used as a case study. Ten different design rainfall events were compared for 10 and 100-year return periods, where we used Huff curves for the design rainfall event definition. The results indicate that the selection of the design rainfall event should be regarded as an important step, since the hydraulic modelling results for different scenarios differ significantly. In the presented experimental case study, the maximum flooded area extent was twice as large as the minimum one, and the maximum water velocity over flooded areas was more than 10 times larger than the minimum one. This can lead to the production of very different flood hazard maps, and consequently planning very different flood protection schemes.

  7. High-resolution stochastic generation of extreme rainfall intensity for urban drainage modelling applications

    Science.gov (United States)

    Peleg, Nadav; Blumensaat, Frank; Molnar, Peter; Fatichi, Simone; Burlando, Paolo

    2016-04-01

    Urban drainage response is highly dependent on the spatial and temporal structure of rainfall. Therefore, measuring and simulating rainfall at a high spatial and temporal resolution is a fundamental step to fully assess urban drainage system reliability and related uncertainties. This is even more relevant when considering extreme rainfall events. However, the current space-time rainfall models have limitations in capturing extreme rainfall intensity statistics for short durations. Here, we use the STREAP (Space-Time Realizations of Areal Precipitation) model, which is a novel stochastic rainfall generator for simulating high-resolution rainfall fields that preserve the spatio-temporal structure of rainfall and its statistical characteristics. The model enables a generation of rain fields at 102 m and minute scales in a fast and computer-efficient way matching the requirements for hydrological analysis of urban drainage systems. The STREAP model was applied successfully in the past to generate high-resolution extreme rainfall intensities over a small domain. A sub-catchment in the city of Luzern (Switzerland) was chosen as a case study to: (i) evaluate the ability of STREAP to disaggregate extreme rainfall intensities for urban drainage applications; (ii) assessing the role of stochastic climate variability of rainfall in flow response and (iii) evaluate the degree of non-linearity between extreme rainfall intensity and system response (i.e. flow) for a small urban catchment. The channel flow at the catchment outlet is simulated by means of a calibrated hydrodynamic sewer model.

  8. Quantitative rainfall metrics for comparing volumetric rainfall retrievals to fine scale models

    Science.gov (United States)

    Collis, Scott; Tao, Wei-Kuo; Giangrande, Scott; Fridlind, Ann; Theisen, Adam; Jensen, Michael

    2013-04-01

    Precipitation processes play a significant role in the energy balance of convective systems for example, through latent heating and evaporative cooling. Heavy precipitation "cores" can also be a proxy for vigorous convection and vertical motions. However, comparisons between rainfall rate retrievals from volumetric remote sensors with forecast rain fields from high-resolution numerical weather prediction simulations are complicated by differences in the location and timing of storm morphological features. This presentation will outline a series of metrics for diagnosing the spatial variability and statistical properties of precipitation maps produced both from models and retrievals. We include existing metrics such as Contoured by Frequency Altitude Diagrams (Yuter and Houze 1995) and Statistical Coverage Products (May and Lane 2009) and propose new metrics based on morphology, cell and feature based statistics. Work presented focuses on observations from the ARM Southern Great Plains radar network consisting of three agile X-Band radar systems with a very dense coverage pattern and a C Band system providing site wide coverage. By combining multiple sensors resolutions of 250m2 can be achieved, allowing improved characterization of fine-scale features. Analyses compare data collected during the Midlattitude Continental Convective Clouds Experiment (MC3E) with simulations of observed systems using the NASA Unified Weather Research and Forecasting model. May, P. T., and T. P. Lane, 2009: A method for using weather radar data to test cloud resolving models. Meteorological Applications, 16, 425-425, doi:10.1002/met.150, 10.1002/met.150. Yuter, S. E., and R. A. Houze, 1995: Three-Dimensional Kinematic and Microphysical Evolution of Florida Cumulonimbus. Part II: Frequency Distributions of Vertical Velocity, Reflectivity, and Differential Reflectivity. Mon. Wea. Rev., 123, 1941-1963, doi:10.1175/1520-0493(1995)1232.0.CO;2.

  9. Modeling of the Monthly Rainfall-Runoff Process Through Regressions

    Directory of Open Access Journals (Sweden)

    Campos-Aranda Daniel Francisco

    2014-10-01

    Full Text Available To solve the problems associated with the assessment of water resources of a river, the modeling of the rainfall-runoff process (RRP allows the deduction of runoff missing data and to extend its record, since generally the information available on precipitation is larger. It also enables the estimation of inputs to reservoirs, when their building led to the suppression of the gauging station. The simplest mathematical model that can be set for the RRP is the linear regression or curve on a monthly basis. Such a model is described in detail and is calibrated with the simultaneous record of monthly rainfall and runoff in Ballesmi hydrometric station, which covers 35 years. Since the runoff of this station has an important contribution from the spring discharge, the record is corrected first by removing that contribution. In order to do this a procedure was developed based either on the monthly average regional runoff coefficients or on nearby and similar watershed; in this case the Tancuilín gauging station was used. Both stations belong to the Partial Hydrologic Region No. 26 (Lower Rio Panuco and are located within the state of San Luis Potosi, México. The study performed indicates that the monthly regression model, due to its conceptual approach, faithfully reproduces monthly average runoff volumes and achieves an excellent approximation in relation to the dispersion, proved by calculation of the means and standard deviations.

  10. A simple analytical infiltration model for short-duration rainfall

    Science.gov (United States)

    Wang, Kaiwen; Yang, Xiaohua; Liu, Xiaomang; Liu, Changming

    2017-12-01

    Many infiltration models have been proposed to simulate infiltration process. Different initial soil conditions and non-uniform initial water content can lead to infiltration simulation errors, especially for short-duration rainfall (SHR). Few infiltration models are specifically derived to eliminate the errors caused by the complex initial soil conditions. We present a simple analytical infiltration model for SHR infiltration simulation, i.e., Short-duration Infiltration Process model (SHIP model). The infiltration simulated by 5 models (i.e., SHIP (high) model, SHIP (middle) model, SHIP (low) model, Philip model and Parlange model) were compared based on numerical experiments and soil column experiments. In numerical experiments, SHIP (middle) and Parlange models had robust solutions for SHR infiltration simulation of 12 typical soils under different initial soil conditions. The absolute values of percent bias were less than 12% and the values of Nash and Sutcliffe efficiency were greater than 0.83. Additionally, in soil column experiments, infiltration rate fluctuated in a range because of non-uniform initial water content. SHIP (high) and SHIP (low) models can simulate an infiltration range, which successfully covered the fluctuation range of the observed infiltration rate. According to the robustness of solutions and the coverage of fluctuation range of infiltration rate, SHIP model can be integrated into hydrologic models to simulate SHR infiltration process and benefit the flood forecast.

  11. Coupling Radar Rainfall to Hydrological Models for Water Abstraction Management

    Science.gov (United States)

    Asfaw, Alemayehu; Shucksmith, James; Smith, Andrea; MacDonald, Ken

    2015-04-01

    The impacts of climate change and growing water use are likely to put considerable pressure on water resources and the environment. In the UK, a reform to surface water abstraction policy has recently been proposed which aims to increase the efficiency of using available water resources whilst minimising impacts on the aquatic environment. Key aspects to this reform include the consideration of dynamic rather than static abstraction licensing as well as introducing water trading concepts. Dynamic licensing will permit varying levels of abstraction dependent on environmental conditions (i.e. river flow and quality). The practical implementation of an effective dynamic abstraction strategy requires suitable flow forecasting techniques to inform abstraction asset management. Potentially the predicted availability of water resources within a catchment can be coupled to predicted demand and current storage to inform a cost effective water resource management strategy which minimises environmental impacts. The aim of this work is to use a historical analysis of UK case study catchment to compare potential water resource availability using modelled dynamic abstraction scenario informed by a flow forecasting model, against observed abstraction under a conventional abstraction regime. The work also demonstrates the impacts of modelling uncertainties on the accuracy of predicted water availability over range of forecast lead times. The study utilised a conceptual rainfall-runoff model PDM - Probability-Distributed Model developed by Centre for Ecology & Hydrology - set up in the Dove River catchment (UK) using 1km2 resolution radar rainfall as inputs and 15 min resolution gauged flow data for calibration and validation. Data assimilation procedures are implemented to improve flow predictions using observed flow data. Uncertainties in the radar rainfall data used in the model are quantified using artificial statistical error model described by Gaussian distribution and

  12. Bayesian estimation of extreme flood quantiles using a rainfall-runoff model and a stochastic daily rainfall generator

    Science.gov (United States)

    Costa, Veber; Fernandes, Wilson

    2017-11-01

    Extreme flood estimation has been a key research topic in hydrological sciences. Reliable estimates of such events are necessary as structures for flood conveyance are continuously evolving in size and complexity and, as a result, their failure-associated hazards become more and more pronounced. Due to this fact, several estimation techniques intended to improve flood frequency analysis and reducing uncertainty in extreme quantile estimation have been addressed in the literature in the last decades. In this paper, we develop a Bayesian framework for the indirect estimation of extreme flood quantiles from rainfall-runoff models. In the proposed approach, an ensemble of long daily rainfall series is simulated with a stochastic generator, which models extreme rainfall amounts with an upper-bounded distribution function, namely, the 4-parameter lognormal model. The rationale behind the generation model is that physical limits for rainfall amounts, and consequently for floods, exist and, by imposing an appropriate upper bound for the probabilistic model, more plausible estimates can be obtained for those rainfall quantiles with very low exceedance probabilities. Daily rainfall time series are converted into streamflows by routing each realization of the synthetic ensemble through a conceptual hydrologic model, the Rio Grande rainfall-runoff model. Calibration of parameters is performed through a nonlinear regression model, by means of the specification of a statistical model for the residuals that is able to accommodate autocorrelation, heteroscedasticity and nonnormality. By combining the outlined steps in a Bayesian structure of analysis, one is able to properly summarize the resulting uncertainty and estimating more accurate credible intervals for a set of flood quantiles of interest. The method for extreme flood indirect estimation was applied to the American river catchment, at the Folsom dam, in the state of California, USA. Results show that most floods

  13. Interannual Tropical Rainfall Variability in General Circulation Model Simulations Associated with the Atmospheric Model Intercomparison Project.

    Science.gov (United States)

    Sperber, K. R.; Palmer, T. N.

    1996-11-01

    The interannual variability of rainfall over the Indian subcontinent, the African Sahel, and the Nordeste region of Brazil have been evaluated in 32 models for the period 1979-88 as part of the Atmospheric Model Intercomparison Project (AMIP). The interannual variations of Nordeste rainfall are the most readily captured, owing to the intimate link with Pacific and Atlantic sea surface temperatures. The precipitation variations over India and the Sahel are less well simulated. Additionally, an Indian monsoon wind shear index was calculated for each model. Evaluation of the interannual variability of a wind shear index over the summer monsoon region indicates that the models exhibit greater fidelity in capturing the large-scale dynamic fluctuations than the regional-scale rainfall variations. A rainfall/SST teleconnection quality control was used to objectively stratify model performance. Skill scores improved for those models that qualitatively simulated the observed rainfall/El Niño- Southern Oscillation SST correlation pattern. This subset of models also had a rainfall climatology that was in better agreement with observations, indicating a link between systematic model error and the ability to simulate interannual variations.A suite of six European Centre for Medium-Range Weather Forecasts (ECMWF) AMIP runs (differing only in their initial conditions) have also been examined. As observed, all-India rainfall was enhanced in 1988 relative to 1987 in each of these realizations. All-India rainfall variability during other years showed little or no predictability, possibly due to internal chaotic dynamics associated with intraseasonal monsoon fluctuations and/or unpredictable land surface process interactions. The interannual variations of Nordeste rainfall were best represented. The State University of New York at Albany/National Center for Atmospheric Research Genesis model was run in five initial condition realizations. In this model, the Nordeste rainfall

  14. Visual perception and interception of falling objects: a review of evidence for an internal model of gravity.

    Science.gov (United States)

    Zago, Myrka; Lacquaniti, Francesco

    2005-09-01

    Prevailing views on how we time the interception of a moving object assume that the visual inputs are informationally sufficient to estimate the time-to-contact from the object's kinematics. However, there are limitations in the visual system that raise questions about the general validity of these theories. Most notably, vision is poorly sensitive to arbitrary accelerations. How then does the brain deal with the motion of objects accelerated by Earth's gravity? Here we review evidence in favor of the view that the brain makes the best estimate about target motion based on visually measured kinematics and an a priori guess about the causes of motion. According to this theory, a predictive model is used to extrapolate time-to-contact from the expected kinetics in the Earth's gravitational field.

  15. A Stochastic Fractional Dynamics Model of Rainfall Statistics

    Science.gov (United States)

    Kundu, Prasun; Travis, James

    2013-04-01

    Rainfall varies in space and time in a highly irregular manner and is described naturally in terms of a stochastic process. A characteristic feature of rainfall statistics is that they depend strongly on the space-time scales over which rain data are averaged. A spectral model of precipitation has been developed based on a stochastic differential equation of fractional order for the point rain rate, that allows a concise description of the second moment statistics of rain at any prescribed space-time averaging scale. The model is designed to faithfully reflect the scale dependence and is thus capable of providing a unified description of the statistics of both radar and rain gauge data. The underlying dynamical equation can be expressed in terms of space-time derivatives of fractional orders that are adjusted together with other model parameters to fit the data. The form of the resulting spectrum gives the model adequate flexibility to capture the subtle interplay between the spatial and temporal scales of variability of rain but strongly constrains the predicted statistical behavior as a function of the averaging length and times scales. The main restriction is the assumption that the statistics of the precipitation field is spatially homogeneous and isotropic and stationary in time. We test the model with radar and gauge data collected contemporaneously at the NASA TRMM ground validation sites located near Melbourne, Florida and in Kwajalein Atoll, Marshall Islands in the tropical Pacific. We estimate the parameters by tuning them to the second moment statistics of the radar data. The model predictions are then found to fit the second moment statistics of the gauge data reasonably well without any further adjustment. Some data sets containing periods of non-stationary behavior that involves occasional anomalously correlated rain events, present a challenge for the model.

  16. Evaluate Hydrologic Response on Spatiotemporal Characteristics of Rainfall Using High Resolution Radar Rainfall Data and WRF-Hydro Model

    Science.gov (United States)

    Gao, S.; Fang, N. Z.

    2017-12-01

    A previously developed Dynamic Moving Storm (DMS) generator is a multivariate rainfall model simulating the complex nature of precipitation field: spatial variability, temporal variability, and storm movement. Previous effort by the authors has investigated the sensitivity of DMS parameters on corresponding hydrologic responses by using synthetic storms. In this study, the DMS generator has been upgraded to generate more realistic precipitation field. The dependence of hydrologic responses on rainfall features was investigated by dissecting the precipitation field into rain cells and modifying their spatio-temporal specification individually. To retrieve DMS parameters from radar rainfall data, rain cell segmentation and tracking algorithms were respectively developed and applied on high resolution radar rainfall data (1) to spatially determine the rain cells within individual radar image and (2) to temporally analyze their dynamic behavior. Statistics of DMS parameters were established by processing a long record of rainfall data (10 years) to keep the modification on real storms within the limit of regional climatology. Empirical distributions of the DMS parameters were calculated to reveal any preferential pattern and seasonality. Subsequently, the WRF-Hydro model forced by the remodeled and modified precipitation was used for hydrologic simulation. The study area was the Upper Trinity River Basin (UTRB) watershed, Texas; and two kinds of high resolution radar data i.e. the Next-Generation Radar (NEXRAD) level III Digital Hybrid Reflectivity (DHR) product and Multi-Radar Multi-Sensor (MRMS) precipitation rate product, were utilized to establish parameter statistics and to recreate/remodel historical events respectively. The results demonstrated that rainfall duration is a significant linkage between DMS parameters and their hydrologic impacts—any combination of spatiotemporal characteristics that keep rain cells longer over the catchment will produce higher

  17. Applying Spatially Distributed Rainfall to a Hydrological Model in a Tropical Watershed, Manoa Watershed, in Hawaii

    Science.gov (United States)

    Huang, Y. F.; Tsang, Y. P.

    2017-12-01

    Rainfall in Hawaii is characterized with high spatial and temporal variability. In the south side of Oahu, the Manoa watershed, with an area of 11 km2, has the annual maximum rainfall of 3900mm and the minimum rainfall of 1000 mm. Despite this high spatial heterogeneity, the rain gage network seems insufficiently capture this pattern. When simulating stream flow and predicting floods with hydrological models in Hawaii, the model performance is often unsatisfactory because of inadequate representation of rainfall data. Longman et al. (in prep.) have developed the spatially distributed daily rainfall across the Hawaiian Islands by applying ordinary kriging, yet these data have not been applied to hydrological models. In this study, we used the Soil and Water Assessment Tool (SWAT) model to assess the streamflow simulation by applying spatially-distributed rainfall in the Manoa watershed. We first used point daily-rainfall at Lyon Arboretum from National Center of Environmental Information (NCEI) as the uniform rainfall input. Secondly, we summarized sub-watershed mean rainfall from the daily spatial-statistical rainfall. Both rainfall data are available from 1999 to 2014. The SWAT was set up for five-year warm-up, nine-year calibration, and two-year validation. The model parameters were calibrated and validated with four U.S. Geological Survey stream gages. We compared the calibrated watershed parameters, characteristics, and assess the streamflow hydrographs from these two rainfall inputs. The differences and improvement of using spatially distributed rainfall input in SWAT were discussed. In addition to improving the model by the representation of rainfall, this study helped us having a better understanding of the watershed hydrological response in Hawaii.

  18. Partitioning the impacts of spatial and climatological rainfall variability in urban drainage modeling

    Science.gov (United States)

    Peleg, Nadav; Blumensaat, Frank; Molnar, Peter; Fatichi, Simone; Burlando, Paolo

    2017-03-01

    The performance of urban drainage systems is typically examined using hydrological and hydrodynamic models where rainfall input is uniformly distributed, i.e., derived from a single or very few rain gauges. When models are fed with a single uniformly distributed rainfall realization, the response of the urban drainage system to the rainfall variability remains unexplored. The goal of this study was to understand how climate variability and spatial rainfall variability, jointly or individually considered, affect the response of a calibrated hydrodynamic urban drainage model. A stochastic spatially distributed rainfall generator (STREAP - Space-Time Realizations of Areal Precipitation) was used to simulate many realizations of rainfall for a 30-year period, accounting for both climate variability and spatial rainfall variability. The generated rainfall ensemble was used as input into a calibrated hydrodynamic model (EPA SWMM - the US EPA's Storm Water Management Model) to simulate surface runoff and channel flow in a small urban catchment in the city of Lucerne, Switzerland. The variability of peak flows in response to rainfall of different return periods was evaluated at three different locations in the urban drainage network and partitioned among its sources. The main contribution to the total flow variability was found to originate from the natural climate variability (on average over 74 %). In addition, the relative contribution of the spatial rainfall variability to the total flow variability was found to increase with longer return periods. This suggests that while the use of spatially distributed rainfall data can supply valuable information for sewer network design (typically based on rainfall with return periods from 5 to 15 years), there is a more pronounced relevance when conducting flood risk assessments for larger return periods. The results show the importance of using multiple distributed rainfall realizations in urban hydrology studies to capture the

  19. Internal model of gravity for hand interception: parametric adaptation to zero-gravity visual targets on Earth.

    Science.gov (United States)

    Zago, Myrka; Lacquaniti, Francesco

    2005-08-01

    Internal model is a neural mechanism that mimics the dynamics of an object for sensory motor or cognitive functions. Recent research focuses on the issue of whether multiple internal models are learned and switched to cope with a variety of conditions, or single general models are adapted by tuning the parameters. Here we addressed this issue by investigating how the manual interception of a moving target changes with changes of the visual environment. In our paradigm, a virtual target moves vertically downward on a screen with different laws of motion. Subjects are asked to punch a hidden ball that arrives in synchrony with the visual target. By using several different protocols, we systematically found that subjects do not develop a new internal model appropriate for constant speed targets, but they use the default gravity model and reduce the central processing time. The results imply that adaptation to zero-gravity targets involves a compression of temporal processing through the cortical and subcortical regions interconnected with the vestibular cortex, which has previously been shown to be the site of storage of the internal model of gravity.

  20. Exploring the potential of multivariate depth-damage and rainfall-damage models

    DEFF Research Database (Denmark)

    van Ootegem, Luc; van Herck, K.; Creten, T.

    2018-01-01

    In Europe, floods are among the natural catastrophes that cause the largest economic damage. This article explores the potential of two distinct types of multivariate flood damage models: ‘depth-damage’ models and ‘rainfall-damage’ models. We use survey data of 346 Flemish households that were...... victim of pluvial floods complemented with rainfall data from both rain gauges and weather radars. In the econometrical analysis, a Tobit estimation technique is used to deal with the issue of zero damage observations. The results show that in the ‘depth-damage’ models flood depth has a significant...... impact on the damage. In the ‘rainfall-damage’ models there is a significant impact of rainfall accumulation on the damage when using the gauge rainfall data as predictor, but not when using the radar rainfall data. Finally, non-hazard indicators are found to be important for explaining pluvial flood...

  1. Rainfall model investigation and scenario analyses of the effect of government reforestation policy on seasonal rainfalls: A case study from Northern Thailand

    Science.gov (United States)

    Duangdai, Eakkapong; Likasiri, Chulin

    2017-03-01

    In this work, 4 models for predicting rainfall amounts are investigated and compared using Northern Thailand's seasonal rainfall data for 1973-2008. Two models, global temperature, forest area and seasonal rainfall (TFR) and modified TFR based on a system of differential equations, give the relationships between global temperature, Northern Thailand's forest cover and seasonal rainfalls in the region. The other two models studied are time series and Autoregressive Moving Average (ARMA) models. All models are validated using the k-fold cross validation method with the resulting errors being 0.971233, 0.740891, 2.376415 and 2.430891 for time series, ARMA, TFR and modified TFR models, respectively. Under Business as Usual (BaU) scenario, seasonal rainfalls in Northern Thailand are projected through the year 2020 using all 4 models. TFR and modified TFR models are also used to further analyze how global temperature rise and government reforestation policy affect seasonal rainfalls in the region. Rainfall projections obtained via the two models are also compared with those from the International Panel on Climate Change (IPCC) under IS92a scenario. Results obtained through a mathematical model for global temperature, forest area and seasonal rainfall show that the higher the forest cover, the less fluctuation there is between rainy-season and summer rainfalls. Moreover, growth in forest cover also correlates with an increase in summer rainfalls. An investigation into the relationship between main crop productions and rainfalls in dry and rainy seasons indicates that if the rainy-season rainfall is high, that year's main-crop rice production will decrease but the second-crop rice, maize, sugarcane and soybean productions will increase in the following year.

  2. Rainfall-runoff modeling in the Turkey River using numerical and ...

    African Journals Online (AJOL)

    Modeling rainfall-runoff relationships in a watershed have an important role in water resources engineering. Researchers have used numerical models for modeling rainfall-runoff ... Also, by using SPSS software, the regression equations were developed and then the best equation was selected from regression analysis.

  3. Evaporation of impact water droplets in interception processes: Historical precedence of the hypothesis and a brief literature overview

    Science.gov (United States)

    Dunkerley, David L.

    2009-10-01

    SummaryIntra-storm evaporation depths exceed post-storm evaporation depths in the interception of rainfall on plant canopies. An important fraction of the intra-storm evaporation may involve the small impact (or splash) droplets produced when raindrops, and perhaps gravity drops (drips released from plant parts), collide with wet plant surfaces. This idea has been presented as a new conception by Murakami [Murakami, S., 2006. A proposal for a new forest canopy interception mechanism: splash droplet evaporation. Journal of Hydrology 319, 72-82; Murakami, S., 2007a. Application of three canopy interception models to a young stand of Japanese cypress and interpretation in terms of interception mechanism. Journal of Hydrology 342, 305-319; Murakami, S., 2007b. A follow-up for the splash droplet evaporation hypothesis of canopy interception and remaining problems: why is humidity unsaturated during rainfall? In: Proceedings of the 20th Annual Conference. Japan Society of Hydrology and Water Resources (in Japanese). ] but was in fact advanced by Dunin [Dunin, F.X., O'Loughlin, E.M., Reyenga, W., 1988. Interception loss from eucalypt forest: lysimeter determination of hourly rates for long term evaluation. Hydrological Processes 2, 315-329] more than 20 years ago. In addition, Dunin et al. considered that canopy ventilation might be enhanced in intense rain. This note draws attention to the historical precedence of the work of Dunin et al. and also presents a short review of literature on impact droplet production, highlighting areas where data are still required for the full exploration of the role of droplet evaporation in canopy interception. Droplet production needs to be properly parameterised and included in models of interception processes and landsurface-atmosphere interactions.

  4. Projections of West African summer monsoon rainfall extremes from two CORDEX models

    Science.gov (United States)

    Akinsanola, A. A.; Zhou, Wen

    2018-05-01

    Global warming has a profound impact on the vulnerable environment of West Africa; hence, robust climate projection, especially of rainfall extremes, is quite important. Based on two representative concentration pathway (RCP) scenarios, projected changes in extreme summer rainfall events over West Africa were investigated using data from the Coordinated Regional Climate Downscaling Experiment models. Eight (8) extreme rainfall indices (CDD, CWD, r10mm, r20mm, PRCPTOT, R95pTOT, rx5day, and sdii) defined by the Expert Team on Climate Change Detection and Indices were used in the study. The performance of the regional climate model (RCM) simulations was validated by comparing with GPCP and TRMM observation data sets. Results show that the RCMs reasonably reproduced the observed pattern of extreme rainfall over the region and further added significant value to the driven GCMs over some grids. Compared to the baseline period 1976-2005, future changes (2070-2099) in summer rainfall extremes under the RCP4.5 and RCP8.5 scenarios show statistically significant decreasing total rainfall (PRCPTOT), while consecutive dry days and extreme rainfall events (R95pTOT) are projected to increase significantly. There are obvious indications that simple rainfall intensity (sdii) will increase in the future. This does not amount to an increase in total rainfall but suggests a likelihood of greater intensity of rainfall events. Overall, our results project that West Africa may suffer more natural disasters such as droughts and floods in the future.

  5. Spatial Disaggregation of Areal Rainfall Using Two Different Artificial Neural Networks Models

    Directory of Open Access Journals (Sweden)

    Sungwon Kim

    2015-06-01

    Full Text Available The objective of this study is to develop artificial neural network (ANN models, including multilayer perceptron (MLP and Kohonen self-organizing feature map (KSOFM, for spatial disaggregation of areal rainfall in the Wi-stream catchment, an International Hydrological Program (IHP representative catchment, in South Korea. A three-layer MLP model, using three training algorithms, was used to estimate areal rainfall. The Levenberg–Marquardt training algorithm was found to be more sensitive to the number of hidden nodes than were the conjugate gradient and quickprop training algorithms using the MLP model. Results showed that the networks structures of 11-5-1 (conjugate gradient and quickprop and 11-3-1 (Levenberg-Marquardt were the best for estimating areal rainfall using the MLP model. The networks structures of 1-5-11 (conjugate gradient and quickprop and 1-3-11 (Levenberg–Marquardt, which are the inverse networks for estimating areal rainfall using the best MLP model, were identified for spatial disaggregation of areal rainfall using the MLP model. The KSOFM model was compared with the MLP model for spatial disaggregation of areal rainfall. The MLP and KSOFM models could disaggregate areal rainfall into individual point rainfall with spatial concepts.

  6. The sensitivity of catchment runoff models to rainfall data at different spatial scales

    Directory of Open Access Journals (Sweden)

    V. A. Bell

    2000-01-01

    Full Text Available The sensitivity of catchment runoff models to rainfall is investigated at a variety of spatial scales using data from a dense raingauge network and weather radar. These data form part of the HYREX (HYdrological Radar EXperiment dataset. They encompass records from 49 raingauges over the 135 km2 Brue catchment in south-west England together with 2 and 5 km grid-square radar data. Separate rainfall time-series for the radar and raingauge data are constructed on 2, 5 and 10 km grids, and as catchment average values, at a 15 minute time-step. The sensitivity of the catchment runoff models to these grid scales of input data is evaluated on selected convective and stratiform rainfall events. Each rainfall time-series is used to produce an ensemble of modelled hydrographs in order to investigate this sensitivity. The distributed model is shown to be sensitive to the locations of the raingauges within the catchment and hence to the spatial variability of rainfall over the catchment. Runoff sensitivity is strongest during convective rainfall when a broader spread of modelled hydrographs results, with twice the variability of that arising from stratiform rain. Sensitivity to rainfall data and model resolution is explored and, surprisingly, best performance is obtained using a lower resolution of rainfall data and model. Results from the distributed catchment model, the Simple Grid Model, are compared with those obtained from a lumped model, the PDM. Performance from the distributed model is found to be only marginally better during stratiform rain (R2 of 0.922 compared to 0.911 but significantly better during convective rain (R2 of 0.953 compared to 0.909. The improved performance from the distributed model can, in part, be accredited to the excellence of the dense raingauge network which would not be the norm for operational flood warning systems. In the final part of the paper, the effect of rainfall resolution on the performance of the 2 km distributed

  7. Characterization of the Sahelian-Sudan rainfall based on observations and regional climate models

    Science.gov (United States)

    Salih, Abubakr A. M.; Elagib, Nadir Ahmed; Tjernström, Michael; Zhang, Qiong

    2018-04-01

    The African Sahel region is known to be highly vulnerable to climate variability and change. We analyze rainfall in the Sahelian Sudan in terms of distribution of rain-days and amounts, and examine whether regional climate models can capture these rainfall features. Three regional models namely, Regional Model (REMO), Rossby Center Atmospheric Model (RCA) and Regional Climate Model (RegCM4), are evaluated against gridded observations (Climate Research Unit, Tropical Rainfall Measuring Mission, and ERA-interim reanalysis) and rain-gauge data from six arid and semi-arid weather stations across Sahelian Sudan over the period 1989 to 2008. Most of the observed rain-days are characterized by weak (0.1-1.0 mm/day) to moderate (> 1.0-10.0 mm/day) rainfall, with average frequencies of 18.5% and 48.0% of the total annual rain-days, respectively. Although very strong rainfall events (> 30.0 mm/day) occur rarely, they account for a large fraction of the total annual rainfall (28-42% across the stations). The performance of the models varies both spatially and temporally. RegCM4 most closely reproduces the observed annual rainfall cycle, especially for the more arid locations, but all of the three models fail to capture the strong rainfall events and hence underestimate its contribution to the total annual number of rain-days and rainfall amount. However, excessive moderate rainfall compensates this underestimation in the models in an annual average sense. The present study uncovers some of the models' limitations in skillfully reproducing the observed climate over dry regions, will aid model users in recognizing the uncertainties in the model output and will help climate and hydrological modeling communities in improving models.

  8. Hand interception of occluded motion in humans: a test of model-based vs. on-line control.

    Science.gov (United States)

    La Scaleia, Barbara; Zago, Myrka; Lacquaniti, Francesco

    2015-09-01

    Two control schemes have been hypothesized for the manual interception of fast visual targets. In the model-free on-line control, extrapolation of target motion is based on continuous visual information, without resorting to physical models. In the model-based control, instead, a prior model of target motion predicts the future spatiotemporal trajectory. To distinguish between the two hypotheses in the case of projectile motion, we asked participants to hit a ball that rolled down an incline at 0.2 g and then fell in air at 1 g along a parabola. By varying starting position, ball velocity and trajectory differed between trials. Motion on the incline was always visible, whereas parabolic motion was either visible or occluded. We found that participants were equally successful at hitting the falling ball in both visible and occluded conditions. Moreover, in different trials the intersection points were distributed along the parabolic trajectories of the ball, indicating that subjects were able to extrapolate an extended segment of the target trajectory. Remarkably, this trend was observed even at the very first repetition of movements. These results are consistent with the hypothesis of model-based control, but not with on-line control. Indeed, ball path and speed during the occlusion could not be extrapolated solely from the kinematic information obtained during the preceding visible phase. The only way to extrapolate ball motion correctly during the occlusion was to assume that the ball would fall under gravity and air drag when hidden from view. Such an assumption had to be derived from prior experience. Copyright © 2015 the American Physiological Society.

  9. Fast adaptation of the internal model of gravity for manual interceptions: evidence for event-dependent learning.

    Science.gov (United States)

    Zago, Myrka; Bosco, Gianfranco; Maffei, Vincenzo; Iosa, Marco; Ivanenko, Yuri P; Lacquaniti, Francesco

    2005-02-01

    We studied how subjects learn to deal with two conflicting sensory environments as a function of the probability of each environment and the temporal distance between repeated events. Subjects were asked to intercept a visual target moving downward on a screen with randomized laws of motion. We compared five protocols that differed in the probability of constant speed (0g) targets and accelerated (1g) targets. Probability ranged from 9 to 100%, and the time interval between consecutive repetitions of the same target ranged from about 1 to 20 min. We found that subjects systematically timed their responses consistent with the assumption of gravity effects, for both 1 and 0g trials. With training, subjects rapidly adapted to 0g targets by shifting the time of motor activation. Surprisingly, the adaptation rate was independent of both the probability of 0g targets and their temporal distance. Very few 0g trials sporadically interspersed as catch trials during immersive practice with 1g trials were sufficient for learning and consolidation in long-term memory, as verified by retesting after 24 h. We argue that the memory store for adapted states of the internal gravity model is triggered by individual events and can be sustained for prolonged periods of time separating sporadic repetitions. This form of event-related learning could depend on multiple-stage memory, with exponential rise and decay in the initial stages followed by a sample-and-hold module.

  10. An artificial neural network model for rainfall forecasting in Bangkok, Thailand

    Directory of Open Access Journals (Sweden)

    N. Q. Hung

    2009-08-01

    Full Text Available This paper presents a new approach using an Artificial Neural Network technique to improve rainfall forecast performance. A real world case study was set up in Bangkok; 4 years of hourly data from 75 rain gauge stations in the area were used to develop the ANN model. The developed ANN model is being applied for real time rainfall forecasting and flood management in Bangkok, Thailand. Aimed at providing forecasts in a near real time schedule, different network types were tested with different kinds of input information. Preliminary tests showed that a generalized feedforward ANN model using hyperbolic tangent transfer function achieved the best generalization of rainfall. Especially, the use of a combination of meteorological parameters (relative humidity, air pressure, wet bulb temperature and cloudiness, the rainfall at the point of forecasting and rainfall at the surrounding stations, as an input data, advanced ANN model to apply with continuous data containing rainy and non-rainy period, allowed model to issue forecast at any moment. Additionally, forecasts by ANN model were compared to the convenient approach namely simple persistent method. Results show that ANN forecasts have superiority over the ones obtained by the persistent model. Rainfall forecasts for Bangkok from 1 to 3 h ahead were highly satisfactory. Sensitivity analysis indicated that the most important input parameter besides rainfall itself is the wet bulb temperature in forecasting rainfall.

  11. Improved rainfall-runoff approach using lumped and conceptual modelling

    OpenAIRE

    Durán Barroso, Pablo

    2016-01-01

    Rainfall-runoff quantification is one of the most important tasks in both engineering and watershed management as it allows to identify, forecast and explain watershed response. The division of the rainfall depth between infiltration and runoff has a high level of complexity due to the spatial heterogeneity in real catchments and the temporal precipitation variability, which provide scale effects on the overall runoff volumes. The Natural Resources Conservation Service Curve Number (NRCS CN) ...

  12. Seasonal prediction of East Asian summer rainfall using a multi-model ensemble system

    Science.gov (United States)

    Ahn, Joong-Bae; Lee, Doo-Young; Yoo, Jin‑Ho

    2015-04-01

    Using the retrospective forecasts of seven state-of-the-art coupled models and their multi-model ensemble (MME) for boreal summers, the prediction skills of climate models in the western tropical Pacific (WTP) and East Asian region are assessed. The prediction of summer rainfall anomalies in East Asia is difficult, while the WTP has a strong correlation between model prediction and observation. We focus on developing a new approach to further enhance the seasonal prediction skill for summer rainfall in East Asia and investigate the influence of convective activity in the WTP on East Asian summer rainfall. By analyzing the characteristics of the WTP convection, two distinct patterns associated with El Niño-Southern Oscillation developing and decaying modes are identified. Based on the multiple linear regression method, the East Asia Rainfall Index (EARI) is developed by using the interannual variability of the normalized Maritime continent-WTP Indices (MPIs), as potentially useful predictors for rainfall prediction over East Asia, obtained from the above two main patterns. For East Asian summer rainfall, the EARI has superior performance to the East Asia summer monsoon index or each MPI. Therefore, the regressed rainfall from EARI also shows a strong relationship with the observed East Asian summer rainfall pattern. In addition, we evaluate the prediction skill of the East Asia reconstructed rainfall obtained by hybrid dynamical-statistical approach using the cross-validated EARI from the individual models and their MME. The results show that the rainfalls reconstructed from simulations capture the general features of observed precipitation in East Asia quite well. This study convincingly demonstrates that rainfall prediction skill is considerably improved by using a hybrid dynamical-statistical approach compared to the dynamical forecast alone. Acknowledgements This work was carried out with the support of Rural Development Administration Cooperative Research

  13. Research on the Relationship between Landslide of Farming Terraces and the Intensity of Rainfall and Slope Angle Based on the Indoor Rainfall Slide Slope Model

    Directory of Open Access Journals (Sweden)

    Dongqin Chen

    2016-03-01

    Full Text Available Due to the increase of geographical disaster in China, it is necessary to study the formation mechanism to make a preparation for the future prevention of geological disasters and effectively reduce the unnecessary financial loss and casualties. We found there is a powerful connection between heavy rainfall and landslide slope. Thus, this article takes the accumulation of gravel soil as the research material to set up indoor rainfall and landslide model test. By comparing the rules of pore water pressure and soil pressure responding to different rainfall intensity and slope angle, we discussed over the effects of rainfall intensity and slope angle on the sliding of accumulation gravelly soil.

  14. Large Pelagics Intercept Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Large Pelagics Intercept Survey (LPIS) is a dockside survey of private and charterboat captains who have just completed fishing trips directed at large pelagic...

  15. Spatial connections in regional climate model rainfall outputs at different temporal scales: Application of network theory

    Science.gov (United States)

    Naufan, Ihsan; Sivakumar, Bellie; Woldemeskel, Fitsum M.; Raghavan, Srivatsan V.; Vu, Minh Tue; Liong, Shie-Yui

    2018-01-01

    Understanding the spatial and temporal variability of rainfall has always been a great challenge, and the impacts of climate change further complicate this issue. The present study employs the concepts of complex networks to study the spatial connections in rainfall, with emphasis on climate change and rainfall scaling. Rainfall outputs (during 1961-1990) from a regional climate model (i.e. Weather Research and Forecasting (WRF) model that downscaled the European Centre for Medium-range Weather Forecasts, ECMWF ERA-40 reanalyses) over Southeast Asia are studied, and data corresponding to eight different temporal scales (6-hr, 12-hr, daily, 2-day, 4-day, weekly, biweekly, and monthly) are analyzed. Two network-based methods are applied to examine the connections in rainfall: clustering coefficient (a measure of the network's local density) and degree distribution (a measure of the network's spread). The influence of rainfall correlation threshold (T) on spatial connections is also investigated by considering seven different threshold levels (ranging from 0.5 to 0.8). The results indicate that: (1) rainfall networks corresponding to much coarser temporal scales exhibit properties similar to that of small-world networks, regardless of the threshold; (2) rainfall networks corresponding to much finer temporal scales may be classified as either small-world networks or scale-free networks, depending upon the threshold; and (3) rainfall spatial connections exhibit a transition phase at intermediate temporal scales, especially at high thresholds. These results suggest that the most appropriate model for studying spatial connections may often be different at different temporal scales, and that a combination of small-world and scale-free network models might be more appropriate for rainfall upscaling/downscaling across all scales, in the strict sense of scale-invariance. The results also suggest that spatial connections in the studied rainfall networks in Southeast Asia are

  16. A space-time hybrid hourly rainfall model for derived flood frequency analysis

    Directory of Open Access Journals (Sweden)

    U. Haberlandt

    2008-12-01

    Full Text Available For derived flood frequency analysis based on hydrological modelling long continuous precipitation time series with high temporal resolution are needed. Often, the observation network with recording rainfall gauges is poor, especially regarding the limited length of the available rainfall time series. Stochastic precipitation synthesis is a good alternative either to extend or to regionalise rainfall series to provide adequate input for long-term rainfall-runoff modelling with subsequent estimation of design floods. Here, a new two step procedure for stochastic synthesis of continuous hourly space-time rainfall is proposed and tested for the extension of short observed precipitation time series.

    First, a single-site alternating renewal model is presented to simulate independent hourly precipitation time series for several locations. The alternating renewal model describes wet spell durations, dry spell durations and wet spell intensities using univariate frequency distributions separately for two seasons. The dependence between wet spell intensity and duration is accounted for by 2-copulas. For disaggregation of the wet spells into hourly intensities a predefined profile is used. In the second step a multi-site resampling procedure is applied on the synthetic point rainfall event series to reproduce the spatial dependence structure of rainfall. Resampling is carried out successively on all synthetic event series using simulated annealing with an objective function considering three bivariate spatial rainfall characteristics. In a case study synthetic precipitation is generated for some locations with short observation records in two mesoscale catchments of the Bode river basin located in northern Germany. The synthetic rainfall data are then applied for derived flood frequency analysis using the hydrological model HEC-HMS. The results show good performance in reproducing average and extreme rainfall characteristics as well as in

  17. Quantifying interception associated with new urban vegetation canopies

    Science.gov (United States)

    Yerk, W.; Montalto, F. A.

    2013-12-01

    Interception of precipitation by vegetation canopies has long been recognized as an important component of the hydrologic cycle, though most research has been in closed or sparse canopy forests. Much less work has been published on interception by urban vegetation, and especially associated with the low growing shrubs commonly installed in green infrastructure program. To inform urban watershed model with vegetation-specific interception data, a field experiment was designed to directly measure canopy throughfall associated with two shrub species commonly included in urban greening programs. Data was collected at a high (e.g. five second) sampling frequency. A non-parametric Kruskal-Wallis test performed on data collected between August and October of 2012 demonstrated statistically significant (p= 0.0011) differences in recorded throughfall between two species (94% for Itea virginica, 86% for Cornus sericea). Additionally, the results suggested that the relationship of throughfall to rainfall intensity varied by species. For Itea, the ratio of throughfall to precipitation intensity was close to 1:1. However, for Cornus, the throughfall rate was on average slower (or 0.85 of the precipitation intensity). An improved and expanded set-up installed in 2013 added two additional species (Prunus laurocerasus and Hydrangea quercifolia). The 2013 results confirm interspecies differences in both throughfall amount, and in the relationship of throughfall rate to precipitation intensity. The results are discussed with respect to droplet splashing and enhanced evaporation within the canopy. Both years' findings suggest that the quantity of water intercepted by vegetation canopies exceeds the canopy storage capacity, as assumed in many conventional hydrologic models.

  18. Rainfall-runoff and hydraulic modelling integration in the Blatina River

    International Nuclear Information System (INIS)

    Timko, J.

    2017-01-01

    This paper investigates the use and integration of rainfall-runoff modelling and hydrologic modelling of Blatina river catchment. Characteristics of physical-geographical sphere and its components were created within the model, enhancing the robustness of input data for the mathematical modelling of landscape runoff. Rainfall-runoff model HEC-HMS utilised in this research allows using a wide range of methodologies to determine the movement of water in the riverbed, water losses in the basin, hydraulic and hydrological methods of transformation and base-flow. Loss and transformation of water in the basin were modeled with curve numbers method SCS-CN. The simulated hydrograph was calibrated using rainfall-runoff event from June 2009. The same event was also modelled after the deforestation of the focus area. Using hydraulic model MIKE 21, a flood of focus rainfall-runoff area was simulated under both current real and changed land cover scenarios. (authors)

  19. Gridded rainfall estimation for distributed modeling in western mountainous areas

    Science.gov (United States)

    Moreda, F.; Cong, S.; Schaake, J.; Smith, M.

    2006-05-01

    Estimation of precipitation in mountainous areas continues to be problematic. It is well known that radar-based methods are limited due to beam blockage. In these areas, in order to run a distributed model that accounts for spatially variable precipitation, we have generated hourly gridded rainfall estimates from gauge observations. These estimates will be used as basic data sets to support the second phase of the NWS-sponsored Distributed Hydrologic Model Intercomparison Project (DMIP 2). One of the major foci of DMIP 2 is to better understand the modeling and data issues in western mountainous areas in order to provide better water resources products and services to the Nation. We derive precipitation estimates using three data sources for the period of 1987-2002: 1) hourly cooperative observer (coop) gauges, 2) daily total coop gauges and 3) SNOw pack TELemetry (SNOTEL) daily gauges. The daily values are disaggregated using the hourly gauge values and then interpolated to approximately 4km grids using an inverse-distance method. Following this, the estimates are adjusted to match monthly mean values from the Parameter-elevation Regressions on Independent Slopes Model (PRISM). Several analyses are performed to evaluate the gridded estimates for DMIP 2 experiments. These gridded inputs are used to generate mean areal precipitation (MAPX) time series for comparison to the traditional mean areal precipitation (MAP) time series derived by the NWS' California-Nevada River Forecast Center for model calibration. We use two of the DMIP 2 basins in California and Nevada: the North Fork of the American River (catchment area 885 sq. km) and the East Fork of the Carson River (catchment area 922 sq. km) as test areas. The basins are sub-divided into elevation zones. The North Fork American basin is divided into two zones above and below an elevation threshold. Likewise, the Carson River basin is subdivided in to four zones. For each zone, the analyses include: a) overall

  20. Modelling of Multi Input Transfer Function for Rainfall Forecasting in Batu City

    Directory of Open Access Journals (Sweden)

    Priska Arindya Purnama

    2017-11-01

    Full Text Available The aim of this research is to model and forecast the rainfall in Batu City using multi input transfer function model based on air temperature, humidity, wind speed and cloud. Transfer function model is a multivariate time series model which consists of an output series (Yt sequence expected to be effected by an input series (Xt and other inputs in a group called a noise series (Nt. Multi input transfer function model obtained is (b1,s1,r1 (b2,s2,r2 (b3,s3,r3 (b4,s4,r4(pn,qn = (0,0,0 (23,0,0 (1,2,0 (0,0,0 ([5,8],2 and shows that air temperature on t-day affects rainfall on t-day, rainfall on t-day is influenced by air humidity in the previous 23 days, rainfall on t-day is affected by wind speed in the previous day , and rainfall on day t is affected by clouds on day t. The results of rainfall forecasting in Batu City with multi input transfer function model can be said to be accurate, because it produces relatively small RMSE value. The value of RMSE data forecasting training is 7.7921 while forecasting data testing is 4.2184. Multi-input transfer function model is suitable for rainfall in Batu City.

  1. Comparison of short term rainfall forecasts for model based flow prediction in urban drainage systems

    DEFF Research Database (Denmark)

    Thorndahl, Søren; Poulsen, Troels Sander; Bøvith, Thomas

    2012-01-01

    Forecast based flow prediction in drainage systems can be used to implement real time control of drainage systems. This study compares two different types of rainfall forecasts – a radar rainfall extrapolation based nowcast model and a numerical weather prediction model. The models are applied...... performance of the system is found using the radar nowcast for the short leadtimes and weather model for larger lead times....

  2. Further developments of the Neyman-Scott clustered point process for modeling rainfall

    Science.gov (United States)

    Cowpertwait, Paul S. P.

    1991-07-01

    This paper provides some useful results for modeling rainfall. It extends work on the Neyman-Scott cluster model for simulating rainfall time series. Several important properties have previously been found for the model, for example, the expectation and variance of the amount of rain captured in an arbitrary time interval (Rodriguez-Iturbe et al., 1987a), In this paper additional properties are derived, such as the probability of an arbitrary interval of any chosen length being dry. In applications this is a desirable property to have, and is often used for fitting stochastic rainfall models to field data. The model is currently being used in rainfall time series research directed toward improving sewage systems in the United Kingdom. To illustrate the model's performance an example is given, where the model is fitted to 10 years of hourly data taken from Blackpool, England.

  3. Assessment of Runoff Contributing Catchment Areas in Rainfall Runoff Modelling

    DEFF Research Database (Denmark)

    Thorndahl, Søren Liedtke; Johansen, C.; Schaarup-Jensen, Kjeld

    2005-01-01

    to determine with significant precision the hydrological reduction factor is implemented to account all hydrological losses except the initial loss. This paper presents an inconsistency between calculations of the hydrological reduction factor, based on measurements of rainfall and runoff, and till now...... recommended literary values for residential areas. It is proven by comparing rainfall-runoff measurements from four different residential catchments that the literary values of the hydrological reduction factor are over-estimated for this type of catchments. In addition, different catchment descriptions...

  4. A dependence modelling study of extreme rainfall in Madeira Island

    Science.gov (United States)

    Gouveia-Reis, Délia; Guerreiro Lopes, Luiz; Mendonça, Sandra

    2016-08-01

    The dependence between variables plays a central role in multivariate extremes. In this paper, spatial dependence of Madeira Island's rainfall data is addressed within an extreme value copula approach through an analysis of maximum annual data. The impact of altitude, slope orientation, distance between rain gauge stations and distance from the stations to the sea are investigated for two different periods of time. The results obtained highlight the influence of the island's complex topography on the spatial distribution of extreme rainfall in Madeira Island.

  5. Do we really use rainfall observations consistent with reality in hydrological modelling?

    Science.gov (United States)

    Ciampalini, Rossano; Follain, Stéphane; Raclot, Damien; Crabit, Armand; Pastor, Amandine; Moussa, Roger; Le Bissonnais, Yves

    2017-04-01

    Spatial and temporal patterns in rainfall control how water reaches soil surface and interacts with soil properties (i.e., soil wetting, infiltration, saturation). Once a hydrological event is defined by a rainfall with its spatiotemporal variability and by some environmental parameters such as soil properties (including land use, topographic and anthropic features), the evidence shows that each parameter variation produces different, specific outputs (e.g., runoff, flooding etc.). In this study, we focus on the effect of rainfall patterns because, due to the difficulty to dispose of detailed data, their influence in modelling is frequently underestimated or neglected. A rainfall event affects a catchment non uniformly, it is spatially localized and its pattern moves in space and time. The way and the time how the water reaches the soil and saturates it respect to the geometry of the catchment deeply influences soil saturation, runoff, and then sediment delivery. This research, approaching a hypothetical, simple case, aims to stimulate the debate on the reliability of the rainfall quality used in hydrological / soil erosion modelling. We test on a small catchment of the south of France (Roujan, Languedoc Roussillon) the influence of rainfall variability with the use of a HD hybrid hydrological - soil erosion model, combining a cinematic wave with the St. Venant equation and a simplified "bucket" conceptual model for ground water, able to quantify the effect of different spatiotemporal patterns of a very-high-definition synthetic rainfall. Results indicate that rainfall spatiotemporal patterns are crucial simulating an erosive event: differences between spatially uniform rainfalls, as frequently adopted in simulations, and some hypothetical rainfall patterns here applied, reveal that the outcome of a simulated event can be highly underestimated.

  6. Modelling solar radiation interception in row plantation. 3. Application to a traditional vineyard; Modélisation de l’interception des rayonnements solaires dans une culture en rangs. 3. Application à une vigne traditionnelle

    Energy Technology Data Exchange (ETDEWEB)

    Sinoquet, H. [Institut National de la Recherche Agronomique, Pointe a Pitre (France); Valancogne, C.; Lescure, A.; Bonhomme, R.

    1992-07-01

    A previously described model of solar radiation interception was applied to a spatially discontinuous canopy: that of a traditional vineyard in which the classical terms of the radiative balance and the spatial distribution of the radiation transmitted to the soil were measured. Comparison of measured and simulated data gave satisfactory agreement for reflected radiation (fig 4), but major discrepancies appeared for mean transmitted radiation (fig 5). The use of small stationary sensors for measuring the transmitted radiation explains the latter observation, since most of the time they measured radiation received on the ground in the sunflecks or in the shaded area rather than mean radiation. This was verified by comparing the measured and simulated spatial distribution of transmitted radiation (figs 7, 8). Finally, the influence of the woody parts which were not taken into consideration in the model was clearly identified : it significantly reduced the transmission of incident radiation (fig 9), and to a greater degrees the closer the sensor was to the vegetation row. (author) [French] Un modèle d’interception du rayonnement solaire décrit précédemment est appliqué à un couvert spatialement discontinu : une vigne traditionnelle sur laquelle ont été mesurés les termes classiques du bilan radiatif et la distribution spatiale du rayonnement transmis au sol. La comparaison des mesures au modèle révèle un ajustement satisfaisant pour le rayonnement réfléchi (fig 4), mais assez médiocre pour le rayonnement transmis moyen (fig 5). Ceci est expliqué par l’utilisation de capteurs ponctuels qui, en raison de leur taille, mesurent plus souvent le rayonnement reçu au sol dans les taches de soleil ou les zones d’ombre qu’un rayonnement moyen. Ceci est vérifié en comparant les distributions mesurées et calculées du rayonnement transmis au sol (figs 7 et 8). Enfin, l’influence des parties ligneuses, non prise en compte dans le modèle, est

  7. Prediction of early summer rainfall over South China by a physical-empirical model

    Science.gov (United States)

    Yim, So-Young; Wang, Bin; Xing, Wen

    2014-10-01

    In early summer (May-June, MJ) the strongest rainfall belt of the northern hemisphere occurs over the East Asian (EA) subtropical front. During this period the South China (SC) rainfall reaches its annual peak and represents the maximum rainfall variability over EA. Hence we establish an SC rainfall index, which is the MJ mean precipitation averaged over 72 stations over SC (south of 28°N and east of 110°E) and represents superbly the leading empirical orthogonal function mode of MJ precipitation variability over EA. In order to predict SC rainfall, we established a physical-empirical model. Analysis of 34-year observations (1979-2012) reveals three physically consequential predictors. A plentiful SC rainfall is preceded in the previous winter by (a) a dipole sea surface temperature (SST) tendency in the Indo-Pacific warm pool, (b) a tripolar SST tendency in North Atlantic Ocean, and (c) a warming tendency in northern Asia. These precursors foreshadow enhanced Philippine Sea subtropical High and Okhotsk High in early summer, which are controlling factors for enhanced subtropical frontal rainfall. The physical empirical model built on these predictors achieves a cross-validated forecast correlation skill of 0.75 for 1979-2012. Surprisingly, this skill is substantially higher than four-dynamical models' ensemble prediction for 1979-2010 period (0.15). The results here suggest that the low prediction skill of current dynamical models is largely due to models' deficiency and the dynamical prediction has large room to improve.

  8. Towards large scale stochastic rainfall models for flood risk assessment in trans-national basins

    Science.gov (United States)

    Serinaldi, F.; Kilsby, C. G.

    2012-04-01

    While extensive research has been devoted to rainfall-runoff modelling for risk assessment in small and medium size watersheds, less attention has been paid, so far, to large scale trans-national basins, where flood events have severe societal and economic impacts with magnitudes quantified in billions of Euros. As an example, in the April 2006 flood events along the Danube basin at least 10 people lost their lives and up to 30 000 people were displaced, with overall damages estimated at more than half a billion Euros. In this context, refined analytical methods are fundamental to improve the risk assessment and, then, the design of structural and non structural measures of protection, such as hydraulic works and insurance/reinsurance policies. Since flood events are mainly driven by exceptional rainfall events, suitable characterization and modelling of space-time properties of rainfall fields is a key issue to perform a reliable flood risk analysis based on alternative precipitation scenarios to be fed in a new generation of large scale rainfall-runoff models. Ultimately, this approach should be extended to a global flood risk model. However, as the need of rainfall models able to account for and simulate spatio-temporal properties of rainfall fields over large areas is rather new, the development of new rainfall simulation frameworks is a challenging task involving that faces with the problem of overcoming the drawbacks of the existing modelling schemes (devised for smaller spatial scales), but keeping the desirable properties. In this study, we critically summarize the most widely used approaches for rainfall simulation. Focusing on stochastic approaches, we stress the importance of introducing suitable climate forcings in these simulation schemes in order to account for the physical coherence of rainfall fields over wide areas. Based on preliminary considerations, we suggest a modelling framework relying on the Generalized Additive Models for Location, Scale

  9. A Statistical Model for Seasonal Rainfall Forecasting over the ...

    African Journals Online (AJOL)

    In a preliminary step, in order to identify the most influential rainfall predictor, a correlation matrix and step-wise regression of 10 predictors with different lags were analysed. The influence of the southern Indian Ocean Sea Surface Temperature was identified as the most influential predictor for the highland of Eritrea.

  10. assessment of neural networks performance in modeling rainfall ...

    African Journals Online (AJOL)

    Sholagberu

    neural network architecture for precipitation prediction of Myanmar, World Academy of. Science, Engineering and Technology, 48, pp. 130 – 134. Kumarasiri, A.D. and Sonnadara, D.U.J. (2006). Rainfall forecasting: an artificial neural network approach, Proceedings of the Technical Sessions,. 22, pp. 1-13 Institute of Physics ...

  11. Comparison of Satellite Rainfall Estimates and Rain Gauge Measurements in Italy, and Impact on Landslide Modeling

    Directory of Open Access Journals (Sweden)

    Mauro Rossi

    2017-12-01

    Full Text Available Landslides can be triggered by intense or prolonged rainfall. Rain gauge measurements are commonly used to predict landslides even if satellite rainfall estimates are available. Recent research focuses on the comparison of satellite estimates and gauge measurements. The rain gauge data from the Italian network (collected in the system database “Verifica Rischio Frana”, VRF are compared with the National Aeronautics and Space Administration (NASA Tropical Rainfall Measuring Mission (TRMM products. For the purpose, we couple point gauge and satellite rainfall estimates at individual grid cells, evaluating the correlation between gauge and satellite data in different morpho-climatological conditions. We then analyze the statistical distributions of both rainfall data types and the rainfall events derived from them. Results show that satellite data underestimates ground data, with the largest differences in mountainous areas. Power-law models, are more appropriate to correlate gauge and satellite data. The gauge and satellite-based products exhibit different statistical distributions and the rainfall events derived from them differ. In conclusion, satellite rainfall cannot be directly compared with ground data, requiring local investigation to account for specific morpho-climatological settings. Results suggest that satellite data can be used for forecasting landslides, only performing a local scaling between satellite and ground data.

  12. Ensemble averaging and stacking of ARIMA and GSTAR model for rainfall forecasting

    Science.gov (United States)

    Anggraeni, D.; Kurnia, I. F.; Hadi, A. F.

    2018-04-01

    Unpredictable rainfall changes can affect human activities, such as in agriculture, aviation, shipping which depend on weather forecasts. Therefore, we need forecasting tools with high accuracy in predicting the rainfall in the future. This research focus on local forcasting of the rainfall at Jember in 2005 until 2016, from 77 rainfall stations. The rainfall here was not only related to the occurrence of the previous of its stations, but also related to others, it’s called the spatial effect. The aim of this research is to apply the GSTAR model, to determine whether there are some correlations of spatial effect between one to another stations. The GSTAR model is an expansion of the space-time model that combines the time-related effects, the locations (stations) in a time series effects, and also the location it self. The GSTAR model will also be compared to the ARIMA model that completely ignores the independent variables. The forcested value of the ARIMA and of the GSTAR models then being combined using the ensemble forecasting technique. The averaging and stacking method of ensemble forecasting method here provide us the best model with higher acuracy model that has the smaller RMSE (Root Mean Square Error) value. Finally, with the best model we can offer a better local rainfall forecasting in Jember for the future.

  13. Where do forests influence rainfall?

    Science.gov (United States)

    Wang-Erlandsson, Lan; van der Ent, Ruud; Fetzer, Ingo; Keys, Patrick; Savenije, Hubert; Gordon, Line

    2017-04-01

    Forests play a major role in hydrology. Not only by immediate control of soil moisture and streamflow, but also by regulating climate through evaporation (i.e., transpiration, interception, and soil evaporation). The process of evaporation travelling through the atmosphere and returning as precipitation on land is known as moisture recycling. Whether evaporation is recycled depends on wind direction and geography. Moisture recycling and forest change studies have primarily focused on either one region (e.g. the Amazon), or one biome type (e.g. tropical humid forests). We will advance this via a systematic global inter-comparison of forest change impacts on precipitation depending on both biome type and geographic location. The rainfall effects are studied for three contemporary forest changes: afforestation, deforestation, and replacement of mature forest by forest plantations. Furthermore, as there are indications in the literature that moisture recycling in some places intensifies during dry years, we will also compare the rainfall impacts of forest change between wet and dry years. We model forest change effects on evaporation using the global hydrological model STEAM and trace precipitation changes using the atmospheric moisture tracking scheme WAM-2layers. This research elucidates the role of geographical location of forest change driven modifications on rainfall as a function of the type of forest change and climatic conditions. These knowledge gains are important at a time of both rapid forest and climate change. Our conclusions nuance our understanding of how forests regulate climate and pinpoint hotspot regions for forest-rainfall coupling.

  14. Understanding onsets of rainfall in Southern Africa using temporal probabilistic modelling

    CSIR Research Space (South Africa)

    Cheruiyot, D

    2010-12-01

    Full Text Available This research investigates an alternative approach to automatically evolve the hidden temporal distribution of onset of rainfall directly from multivariate time series (MTS) data in the absence of domain experts. Temporal probabilistic modelling...

  15. FLASH-FLOOD MODELLING WITH ARTIFICIAL NEURAL NETWORKS USING RADAR RAINFALL ESTIMATES

    Directory of Open Access Journals (Sweden)

    Dinu Cristian

    2017-09-01

    Full Text Available The use of artificial neural networks (ANNs in modelling the hydrological processes has become a common approach in the last two decades, among side the traditional methods. In regard to the rainfall-runoff modelling, in both traditional and ANN models the use of ground rainfall measurements is prevalent, which can be challenging in areas with low rain gauging station density, especially in catchments where strong focused rainfall can generate flash-floods. The weather radar technology can prove to be a solution for such areas by providing rain estimates with good time and space resolution. This paper presents a comparison between different ANN setups using as input both ground and radar observations for modelling the rainfall-runoff process for Bahluet catchment, with focus on a flash-flood observed in the catchment.

  16. Tropospheric biennial oscillation and south Asian summer monsoon rainfall in a coupled model

    Science.gov (United States)

    Konda, Gopinadh; Chowdary, J. S.; Srinivas, G.; Gnanaseelan, C.; Parekh, Anant; Attada, Raju; Rama Krishna, S. S. V. S.

    2018-06-01

    In this study Tropospheric Biennial Oscillation (TBO) and south Asian summer monsoon rainfall are examined in the National Centers for Environmental Prediction (NCEP) Climate Forecast System (CFSv2) hindcast. High correlation between the observations and model TBO index suggests that the model is able to capture most of the TBO years. Spatial patterns of rainfall anomalies associated with positive TBO over the south Asian region are better represented in the model as in the observations. However, the model predicted rainfall anomaly patterns associated with negative TBO years are improper and magnitudes are underestimated compared to the observations. It is noted that positive (negative) TBO is associated with La Niña (El Niño) like Sea surface temperature (SST) anomalies in the model. This leads to the fact that model TBO is El Niño-Southern Oscillation (ENSO) driven, while in the observations Indian Ocean Dipole (IOD) also plays a role in the negative TBO phase. Detailed analysis suggests that the negative TBO rainfall anomaly pattern in the model is highly influenced by improper teleconnections allied to IOD. Unlike in the observations, rainfall anomalies over the south Asian region are anti-correlated with IOD index in CFSv2. Further, summer monsoon rainfall over south Asian region is highly correlated with IOD western pole than eastern pole in CFSv2 in contrast to the observations. Altogether, the present study highlights the importance of improving Indian Ocean SST teleconnections to south Asian summer rainfall in the model by enhancing the predictability of TBO. This in turn would improve monsoon rainfall prediction skill of the model.

  17. Tropospheric biennial oscillation and south Asian summer monsoon rainfall in a coupled model

    KAUST Repository

    Konda, Gopinadh; Chowdary, Jasti S.; Srinivas, G; Gnanaseelan, C; Parekh, Anant; Attada, Raju; Rama Krishna, S S V S

    2018-01-01

    In this study Tropospheric Biennial Oscillation (TBO) and south Asian summer monsoon rainfall are examined in the National Centers for Environmental Prediction (NCEP) Climate Forecast System (CFSv2) hindcast. High correlation between the observations and model TBO index suggests that the model is able to capture most of the TBO years. Spatial patterns of rainfall anomalies associated with positive TBO over the south Asian region are better represented in the model as in the observations. However, the model predicted rainfall anomaly patterns associated with negative TBO years are improper and magnitudes are underestimated compared to the observations. It is noted that positive (negative) TBO is associated with La Niña (El Niño) like Sea surface temperature (SST) anomalies in the model. This leads to the fact that model TBO is El Niño-Southern Oscillation (ENSO) driven, while in the observations Indian Ocean Dipole (IOD) also plays a role in the negative TBO phase. Detailed analysis suggests that the negative TBO rainfall anomaly pattern in the model is highly influenced by improper teleconnections allied to IOD. Unlike in the observations, rainfall anomalies over the south Asian region are anti-correlated with IOD index in CFSv2. Further, summer monsoon rainfall over south Asian region is highly correlated with IOD western pole than eastern pole in CFSv2 in contrast to the observations. Altogether, the present study highlights the importance of improving Indian Ocean SST teleconnections to south Asian summer rainfall in the model by enhancing the predictability of TBO. This in turn would improve monsoon rainfall prediction skill of the model.

  18. Tropospheric biennial oscillation and south Asian summer monsoon rainfall in a coupled model

    KAUST Repository

    Konda, Gopinadh

    2018-05-22

    In this study Tropospheric Biennial Oscillation (TBO) and south Asian summer monsoon rainfall are examined in the National Centers for Environmental Prediction (NCEP) Climate Forecast System (CFSv2) hindcast. High correlation between the observations and model TBO index suggests that the model is able to capture most of the TBO years. Spatial patterns of rainfall anomalies associated with positive TBO over the south Asian region are better represented in the model as in the observations. However, the model predicted rainfall anomaly patterns associated with negative TBO years are improper and magnitudes are underestimated compared to the observations. It is noted that positive (negative) TBO is associated with La Niña (El Niño) like Sea surface temperature (SST) anomalies in the model. This leads to the fact that model TBO is El Niño-Southern Oscillation (ENSO) driven, while in the observations Indian Ocean Dipole (IOD) also plays a role in the negative TBO phase. Detailed analysis suggests that the negative TBO rainfall anomaly pattern in the model is highly influenced by improper teleconnections allied to IOD. Unlike in the observations, rainfall anomalies over the south Asian region are anti-correlated with IOD index in CFSv2. Further, summer monsoon rainfall over south Asian region is highly correlated with IOD western pole than eastern pole in CFSv2 in contrast to the observations. Altogether, the present study highlights the importance of improving Indian Ocean SST teleconnections to south Asian summer rainfall in the model by enhancing the predictability of TBO. This in turn would improve monsoon rainfall prediction skill of the model.

  19. Evaluation of Stochastic Rainfall Models in Capturing Climate Variability for Future Drought and Flood Risk Assessment

    Science.gov (United States)

    Chowdhury, A. F. M. K.; Lockart, N.; Willgoose, G. R.; Kuczera, G. A.; Kiem, A.; Nadeeka, P. M.

    2016-12-01

    One of the key objectives of stochastic rainfall modelling is to capture the full variability of climate system for future drought and flood risk assessment. However, it is not clear how well these models can capture the future climate variability when they are calibrated to Global/Regional Climate Model data (GCM/RCM) as these datasets are usually available for very short future period/s (e.g. 20 years). This study has assessed the ability of two stochastic daily rainfall models to capture climate variability by calibrating them to a dynamically downscaled RCM dataset in an east Australian catchment for 1990-2010, 2020-2040, and 2060-2080 epochs. The two stochastic models are: (1) a hierarchical Markov Chain (MC) model, which we developed in a previous study and (2) a semi-parametric MC model developed by Mehrotra and Sharma (2007). Our hierarchical model uses stochastic parameters of MC and Gamma distribution, while the semi-parametric model uses a modified MC process with memory of past periods and kernel density estimation. This study has generated multiple realizations of rainfall series by using parameters of each model calibrated to the RCM dataset for each epoch. The generated rainfall series are used to generate synthetic streamflow by using a SimHyd hydrology model. Assessing the synthetic rainfall and streamflow series, this study has found that both stochastic models can incorporate a range of variability in rainfall as well as streamflow generation for both current and future periods. However, the hierarchical model tends to overestimate the multiyear variability of wet spell lengths (therefore, is less likely to simulate long periods of drought and flood), while the semi-parametric model tends to overestimate the mean annual rainfall depths and streamflow volumes (hence, simulated droughts are likely to be less severe). Sensitivity of these limitations of both stochastic models in terms of future drought and flood risk assessment will be discussed.

  20. Weather model performance on extreme rainfall events simulation's over Western Iberian Peninsula

    Science.gov (United States)

    Pereira, S. C.; Carvalho, A. C.; Ferreira, J.; Nunes, J. P.; Kaiser, J. J.; Rocha, A.

    2012-08-01

    This study evaluates the performance of the WRF-ARW numerical weather model in simulating the spatial and temporal patterns of an extreme rainfall period over a complex orographic region in north-central Portugal. The analysis was performed for the December month of 2009, during the Portugal Mainland rainy season. The heavy rainfall to extreme heavy rainfall periods were due to several low surface pressure's systems associated with frontal surfaces. The total amount of precipitation for December exceeded, in average, the climatological mean for the 1971-2000 time period in +89 mm, varying from 190 mm (south part of the country) to 1175 mm (north part of the country). Three model runs were conducted to assess possible improvements in model performance: (1) the WRF-ARW is forced with the initial fields from a global domain model (RunRef); (2) data assimilation for a specific location (RunObsN) is included; (3) nudging is used to adjust the analysis field (RunGridN). Model performance was evaluated against an observed hourly precipitation dataset of 15 rainfall stations using several statistical parameters. The WRF-ARW model reproduced well the temporal rainfall patterns but tended to overestimate precipitation amounts. The RunGridN simulation provided the best results but model performance of the other two runs was good too, so that the selected extreme rainfall episode was successfully reproduced.

  1. Evaluation of rainfall simulations over West Africa in dynamically downscaled CMIP5 global circulation models

    Science.gov (United States)

    Akinsanola, A. A.; Ajayi, V. O.; Adejare, A. T.; Adeyeri, O. E.; Gbode, I. E.; Ogunjobi, K. O.; Nikulin, G.; Abolude, A. T.

    2018-04-01

    This study presents evaluation of the ability of Rossby Centre Regional Climate Model (RCA4) driven by nine global circulation models (GCMs), to skilfully reproduce the key features of rainfall climatology over West Africa for the period of 1980-2005. The seasonal climatology and annual cycle of the RCA4 simulations were assessed over three homogenous subregions of West Africa (Guinea coast, Savannah, and Sahel) and evaluated using observed precipitation data from the Global Precipitation Climatology Project (GPCP). Furthermore, the model output was evaluated using a wide range of statistical measures. The interseasonal and interannual variability of the RCA4 were further assessed over the subregions and the whole of the West Africa domain. Results indicate that the RCA4 captures the spatial and interseasonal rainfall pattern adequately but exhibits a weak performance over the Guinea coast. Findings from the interannual rainfall variability indicate that the model performance is better over the larger West Africa domain than the subregions. The largest difference across the RCA4 simulated annual rainfall was found in the Sahel. Result from the Mann-Kendall test showed no significant trend for the 1980-2005 period in annual rainfall either in GPCP observation data or in the model simulations over West Africa. In many aspects, the RCA4 simulation driven by the HadGEM2-ES perform best over the region. The use of the multimodel ensemble mean has resulted to the improved representation of rainfall characteristics over the study domain.

  2. Development and evaluation of a stochastic daily rainfall model with long-term variability

    Science.gov (United States)

    Kamal Chowdhury, A. F. M.; Lockart, Natalie; Willgoose, Garry; Kuczera, George; Kiem, Anthony S.; Parana Manage, Nadeeka

    2017-12-01

    The primary objective of this study is to develop a stochastic rainfall generation model that can match not only the short resolution (daily) variability but also the longer resolution (monthly to multiyear) variability of observed rainfall. This study has developed a Markov chain (MC) model, which uses a two-state MC process with two parameters (wet-to-wet and dry-to-dry transition probabilities) to simulate rainfall occurrence and a gamma distribution with two parameters (mean and standard deviation of wet day rainfall) to simulate wet day rainfall depths. Starting with the traditional MC-gamma model with deterministic parameters, this study has developed and assessed four other variants of the MC-gamma model with different parameterisations. The key finding is that if the parameters of the gamma distribution are randomly sampled each year from fitted distributions rather than fixed parameters with time, the variability of rainfall depths at both short and longer temporal resolutions can be preserved, while the variability of wet periods (i.e. number of wet days and mean length of wet spell) can be preserved by decadally varied MC parameters. This is a straightforward enhancement to the traditional simplest MC model and is both objective and parsimonious.

  3. Future climate change enhances rainfall seasonality in a regional model of western Maritime Continent

    Science.gov (United States)

    Kang, Suchul; Im, Eun-Soon; Eltahir, Elfatih A. B.

    2018-03-01

    In this study, future changes in rainfall due to global climate change are investigated over the western Maritime Continent based on dynamically downscaled climate projections using the MIT Regional Climate Model (MRCM) with 12 km horizontal resolution. A total of nine 30-year regional climate projections driven by multi-GCMs projections (CCSM4, MPI-ESM-MR and ACCESS1.0) under multi-scenarios of greenhouse gases emissions (Historical: 1976-2005, RCP4.5 and RCP8.5: 2071-2100) from phase 5 of the Coupled Model Inter-comparison Project (CMIP5) are analyzed. Focusing on dynamically downscaled rainfall fields, the associated systematic biases originating from GCM and MRCM are removed based on observations using Parametric Quantile Mapping method in order to enhance the reliability of future projections. The MRCM simulations with bias correction capture the spatial patterns of seasonal rainfall as well as the frequency distribution of daily rainfall. Based on projected rainfall changes under both RCP4.5 and RCP8.5 scenarios, the ensemble of MRCM simulations project a significant decrease in rainfall over the western Maritime Continent during the inter-monsoon periods while the change in rainfall is not relevant during wet season. The main mechanism behind the simulated decrease in rainfall is rooted in asymmetries of the projected changes in seasonal dynamics of the meridional circulation along different latitudes. The sinking motion, which is marginally positioned in the reference simulation, is enhanced and expanded under global climate change, particularly in RCP8.5 scenario during boreal fall season. The projected enhancement of rainfall seasonality over the western Maritime Continent suggests increased risk of water stress for natural ecosystems as well as man-made water resources reservoirs.

  4. Using multinomial and imprecise probability for non-parametric modelling of rainfall in Manizales (Colombia

    Directory of Open Access Journals (Sweden)

    Ibsen Chivatá Cárdenas

    2008-05-01

    Full Text Available This article presents a rainfall model constructed by applying non-parametric modelling and imprecise probabilities; these tools were used because there was not enough homogeneous information in the study area. The area’s hydro-logical information regarding rainfall was scarce and existing hydrological time series were not uniform. A distributed extended rainfall model was constructed from so-called probability boxes (p-boxes, multinomial probability distribu-tion and confidence intervals (a friendly algorithm was constructed for non-parametric modelling by combining the last two tools. This model confirmed the high level of uncertainty involved in local rainfall modelling. Uncertainty en-compassed the whole range (domain of probability values thereby showing the severe limitations on information, leading to the conclusion that a detailed estimation of probability would lead to significant error. Nevertheless, rele-vant information was extracted; it was estimated that maximum daily rainfall threshold (70 mm would be surpassed at least once every three years and the magnitude of uncertainty affecting hydrological parameter estimation. This paper’s conclusions may be of interest to non-parametric modellers and decisions-makers as such modelling and imprecise probability represents an alternative for hydrological variable assessment and maybe an obligatory proce-dure in the future. Its potential lies in treating scarce information and represents a robust modelling strategy for non-seasonal stochastic modelling conditions

  5. Event-based rainfall-runoff modelling of the Kelantan River Basin

    Science.gov (United States)

    Basarudin, Z.; Adnan, N. A.; Latif, A. R. A.; Tahir, W.; Syafiqah, N.

    2014-02-01

    Flood is one of the most common natural disasters in Malaysia. According to hydrologists there are many causes that contribute to flood events. The two most dominant factors are the meteorology factor (i.e climate change) and change in land use. These two factors contributed to floods in recent decade especially in the monsoonal catchment such as Malaysia. This paper intends to quantify the influence of rainfall during extreme rainfall events on the hydrological model in the Kelantan River catchment. Therefore, two dynamic inputs were used in the study: rainfall and river discharge. The extreme flood events in 2008 and 2004 were compared based on rainfall data for both years. The events were modeled via a semi-distributed HEC-HMS hydrological model. Land use change was not incorporated in the study because the study only tries to quantify rainfall changes during these two events to simulate the discharge and runoff value. Therefore, the land use data representing the year 2004 were used as inputs in the 2008 runoff model. The study managed to demonstrate that rainfall change has a significant impact to determine the peak discharge and runoff depth for the study area.

  6. Event-based rainfall-runoff modelling of the Kelantan River Basin

    International Nuclear Information System (INIS)

    Basarudin, Z; Adnan, N A; Latif, A R A; Syafiqah, N; Tahir, W

    2014-01-01

    Flood is one of the most common natural disasters in Malaysia. According to hydrologists there are many causes that contribute to flood events. The two most dominant factors are the meteorology factor (i.e climate change) and change in land use. These two factors contributed to floods in recent decade especially in the monsoonal catchment such as Malaysia. This paper intends to quantify the influence of rainfall during extreme rainfall events on the hydrological model in the Kelantan River catchment. Therefore, two dynamic inputs were used in the study: rainfall and river discharge. The extreme flood events in 2008 and 2004 were compared based on rainfall data for both years. The events were modeled via a semi-distributed HEC-HMS hydrological model. Land use change was not incorporated in the study because the study only tries to quantify rainfall changes during these two events to simulate the discharge and runoff value. Therefore, the land use data representing the year 2004 were used as inputs in the 2008 runoff model. The study managed to demonstrate that rainfall change has a significant impact to determine the peak discharge and runoff depth for the study area

  7. Effect of radar rainfall time resolution on the predictive capability of a distributed hydrologic model

    Science.gov (United States)

    Atencia, A.; Llasat, M. C.; Garrote, L.; Mediero, L.

    2010-10-01

    The performance of distributed hydrological models depends on the resolution, both spatial and temporal, of the rainfall surface data introduced. The estimation of quantitative precipitation from meteorological radar or satellite can improve hydrological model results, thanks to an indirect estimation at higher spatial and temporal resolution. In this work, composed radar data from a network of three C-band radars, with 6-minutal temporal and 2 × 2 km2 spatial resolution, provided by the Catalan Meteorological Service, is used to feed the RIBS distributed hydrological model. A Window Probability Matching Method (gage-adjustment method) is applied to four cases of heavy rainfall to improve the observed rainfall sub-estimation in both convective and stratiform Z/R relations used over Catalonia. Once the rainfall field has been adequately obtained, an advection correction, based on cross-correlation between two consecutive images, was introduced to get several time resolutions from 1 min to 30 min. Each different resolution is treated as an independent event, resulting in a probable range of input rainfall data. This ensemble of rainfall data is used, together with other sources of uncertainty, such as the initial basin state or the accuracy of discharge measurements, to calibrate the RIBS model using probabilistic methodology. A sensitivity analysis of time resolutions was implemented by comparing the various results with real values from stream-flow measurement stations.

  8. Centrifuge model tests of rainfall-induced slope failures for the investigation of the initiation conditions

    Science.gov (United States)

    Matziaris, Vasileios; Marshall, Alec; Yu, Hai-Sui

    2015-04-01

    Rainfall-induced landslides are very common natural disasters which cause damage to properties and infrastructure and may result in the loss of human lives. These phenomena often take place in unsaturated soil slopes and are triggered by the saturation of the soil profile, due to rain infiltration, which leads to a loss of shear strength. The aim of this study is to determine rainfall thresholds for the initiation of landslides under different initial conditions. Model tests of rainfall-induced landslides are conducted in the Nottingham Centre for Geomechanics 50g-T geotechnical centrifuge. Initially unsaturated plane-strain slope models made with fine silica sand are prepared at varying densities at 1g and accommodated within a climatic chamber which provides controlled environmental conditions. During the centrifuge flight at 60g, rainfall events of varying intensity and duration are applied to the slope models causing the initiation of slope failure. The impact of soil state properties and rainfall characteristics on the landslide initiation process are discussed. The variation of pore water pressures within the slope before, during and after simulated rainfall events is recorded using miniature pore pressure transducers buried in the soil model. Slope deformation is determined by using a high-speed camera and digital image analysis techniques.

  9. Rainfall height stochastic modelling as a support tool for landslides early warning

    Science.gov (United States)

    Capparelli, G.; Giorgio, M.; Greco, R.; Versace, P.

    2009-04-01

    Occurrence of landslides is uneasy to predict, since it is affected by a number of variables, such as mechanical and hydraulic soil properties, slope morphology, vegetation coverage, rainfall spatial and temporal variability. Although heavy landslides frequently occurred in Campania, southern Italy, during the last decade, no complete data sets are available for natural slopes where landslides occurred. As a consequence, landslide risk assessment procedures and early warning systems in Campania still rely on simple empirical models based on correlation between daily rainfall records and observed landslides, like FLAIR model [Versace et al., 2003]. Effectiveness of such systems could be improved by reliable quantitative rainfall prediction. In mountainous areas, rainfall spatial and temporal variability are very pronounced due to orographic effects, making predictions even more complicated. Existing rain gauge networks are not dense enough to resolve the small scale spatial variability, and the same limitation of spatial resolution affects rainfall height maps provided by radar sensors as well as by meteorological physically based models. Therefore, analysis of on-site recorded rainfall height time series still represents the most effective approach for a reliable prediction of local temporal evolution of rainfall. Hydrological time series analysis is a widely studied field in hydrology, often carried out by means of autoregressive models, such as AR and ARMA [Box and Jenkins, 1976]. Sometimes exogenous information coming from additional series of observations is also taken into account, and the models are called ARX and ARMAX (e.g. Salas [1992]). Such models gave the best results when applied to the analysis of autocorrelated hydrological time series, like river flow or level time series. Conversely, they are not able to model the behaviour of intermittent time series, like point rainfall height series usually are, especially when recorded with short sampling time

  10. Real Time Updating in Distributed Urban Rainfall Runoff Modelling

    OpenAIRE

    Borup, Morten; Mikkelsen, Peter Steen; Grum, Morten; Madsen, Henrik

    2014-01-01

    When it rains on urban areas the rainfall runoff is transported out of the city via the drainage system. Frequently, the drainage system cannot handle all the rain water, which results in problems like flooding or overflows into natural water bodies. To reduce these problems the systems are equipped with basins and automated structures that allow for a large degree of control of the systems, but in order to do this optimally it is required to know what is happening throughout the system. For ...

  11. Bayesian analysis of data and model error in rainfall-runoff hydrological models

    Science.gov (United States)

    Kavetski, D.; Franks, S. W.; Kuczera, G.

    2004-12-01

    A major unresolved issue in the identification and use of conceptual hydrologic models is realistic description of uncertainty in the data and model structure. In particular, hydrologic parameters often cannot be measured directly and must be inferred (calibrated) from observed forcing/response data (typically, rainfall and runoff). However, rainfall varies significantly in space and time, yet is often estimated from sparse gauge networks. Recent work showed that current calibration methods (e.g., standard least squares, multi-objective calibration, generalized likelihood uncertainty estimation) ignore forcing uncertainty and assume that the rainfall is known exactly. Consequently, they can yield strongly biased and misleading parameter estimates. This deficiency confounds attempts to reliably test model hypotheses, to generalize results across catchments (the regionalization problem) and to quantify predictive uncertainty when the hydrologic model is extrapolated. This paper continues the development of a Bayesian total error analysis (BATEA) methodology for the calibration and identification of hydrologic models, which explicitly incorporates the uncertainty in both the forcing and response data, and allows systematic model comparison based on residual model errors and formal Bayesian hypothesis testing (e.g., using Bayes factors). BATEA is based on explicit stochastic models for both forcing and response uncertainty, whereas current techniques focus solely on response errors. Hence, unlike existing methods, the BATEA parameter equations directly reflect the modeler's confidence in all the data. We compare several approaches to approximating the parameter distributions: a) full Markov Chain Monte Carlo methods and b) simplified approaches based on linear approximations. Studies using synthetic and real data from the US and Australia show that BATEA systematically reduces the parameter bias, leads to more meaningful model fits and allows model comparison taking

  12. Interception storage capacities of tropical rainforest canopy trees

    Science.gov (United States)

    Herwitz, Stanley R.

    1985-04-01

    The rainwater interception storage capacities of mature canopy trees in a tropical rainforest site in northeast Queensland, Australia, were approximated using a combination of field and laboratory measurements. The above-ground vegetative surfaces of five selected species (three flaky-barked; two smooth-barked) were saturated under laboratory conditions in order to establish their maximum interception storage capacities. Average leaf surface interception storages ranged from 112 to 161 ml m -2. The interception storages of bark ranged from 0.51 to 0.97 ml cm -3. These standardized interception storages were applied to estimates of leaf surface area and bark volume for 51 mature canopy trees representing the selected species in the field site. The average whole tree interception storage capacities of the five species ranged from 110 to 5281 per tree and 2.2 to 8.3 mm per unit projected crown area. The highly significant interspecific differences in interception storage capacity suggest that both floristic and demographic data are needed in order to accurately calculate a forest-wide interception storage capacity for species-rich tropical rainforest vegetation. Species with large woody surface areas and small projected crown areas are capable of storing the greatest depth equivalents of rainwater under heavy rainfall conditions. In the case of both the flaky-barked and the smooth-barked species, bark accounted for > 50% of the total interception storage capacity under still-air conditions, and > 80% under turbulent air conditions. The emphasis in past interception studies on the role of leaf surfaces in determining the interception storage capacity of a vegetative cover must be modified for tropical rainforests to include the storage capacity provided by the bark tissue on canopy trees.

  13. Modification of a rainfall-runoff model for distributed modeling in a GIS and its validation

    Science.gov (United States)

    Nyabeze, W. R.

    A rainfall-runoff model, which can be inter-faced with a Geographical Information System (GIS) to integrate definition, measurement, calculating parameter values for spatial features, presents considerable advantages. The modification of the GWBasic Wits Rainfall-Runoff Erosion Model (GWBRafler) to enable parameter value estimation in a GIS (GISRafler) is presented in this paper. Algorithms are applied to estimate parameter values reducing the number of input parameters and the effort to populate them. The use of a GIS makes the relationship between parameter estimates and cover characteristics more evident. This paper has been produced as part of research to generalize the GWBRafler on a spatially distributed basis. Modular data structures are assumed and parameter values are weighted relative to the module area and centroid properties. Modifications to the GWBRafler enable better estimation of low flows, which are typical in drought conditions.

  14. Global Warming Induced Changes in Rainfall Characteristics in IPCC AR5 Models

    Science.gov (United States)

    Lau, William K. M.; Wu, Jenny, H.-T.; Kim, Kyu-Myong

    2012-01-01

    Changes in rainfall characteristic induced by global warming are examined from outputs of IPCC AR5 models. Different scenarios of climate warming including a high emissions scenario (RCP 8.5), a medium mitigation scenario (RCP 4.5), and 1% per year CO2 increase are compared to 20th century simulations (historical). Results show that even though the spatial distribution of monthly rainfall anomalies vary greatly among models, the ensemble mean from a sizable sample (about 10) of AR5 models show a robust signal attributable to GHG warming featuring a shift in the global rainfall probability distribution function (PDF) with significant increase (>100%) in very heavy rain, reduction (10-20% ) in moderate rain and increase in light to very light rains. Changes in extreme rainfall as a function of seasons and latitudes are also examined, and are similar to the non-seasonal stratified data, but with more specific spatial dependence. These results are consistent from TRMM and GPCP rainfall observations suggesting that extreme rainfall events are occurring more frequently with wet areas getting wetter and dry-area-getting drier in a GHG induced warmer climate.

  15. The Impact of Model and Rainfall Forcing Errors on Characterizing Soil Moisture Uncertainty in Land Surface Modeling

    Science.gov (United States)

    Maggioni, V.; Anagnostou, E. N.; Reichle, R. H.

    2013-01-01

    The contribution of rainfall forcing errors relative to model (structural and parameter) uncertainty in the prediction of soil moisture is investigated by integrating the NASA Catchment Land Surface Model (CLSM), forced with hydro-meteorological data, in the Oklahoma region. Rainfall-forcing uncertainty is introduced using a stochastic error model that generates ensemble rainfall fields from satellite rainfall products. The ensemble satellite rain fields are propagated through CLSM to produce soil moisture ensembles. Errors in CLSM are modeled with two different approaches: either by perturbing model parameters (representing model parameter uncertainty) or by adding randomly generated noise (representing model structure and parameter uncertainty) to the model prognostic variables. Our findings highlight that the method currently used in the NASA GEOS-5 Land Data Assimilation System to perturb CLSM variables poorly describes the uncertainty in the predicted soil moisture, even when combined with rainfall model perturbations. On the other hand, by adding model parameter perturbations to rainfall forcing perturbations, a better characterization of uncertainty in soil moisture simulations is observed. Specifically, an analysis of the rank histograms shows that the most consistent ensemble of soil moisture is obtained by combining rainfall and model parameter perturbations. When rainfall forcing and model prognostic perturbations are added, the rank histogram shows a U-shape at the domain average scale, which corresponds to a lack of variability in the forecast ensemble. The more accurate estimation of the soil moisture prediction uncertainty obtained by combining rainfall and parameter perturbations is encouraging for the application of this approach in ensemble data assimilation systems.

  16. Spatio-temporal modelling of rainfall in the Murray-Darling Basin

    Science.gov (United States)

    Nowak, Gen; Welsh, A. H.; O'Neill, T. J.; Feng, Lingbing

    2018-02-01

    The Murray-Darling Basin (MDB) is a large geographical region in southeastern Australia that contains many rivers and creeks, including Australia's three longest rivers, the Murray, the Murrumbidgee and the Darling. Understanding rainfall patterns in the MDB is very important due to the significant impact major events such as droughts and floods have on agricultural and resource productivity. We propose a model for modelling a set of monthly rainfall data obtained from stations in the MDB and for producing predictions in both the spatial and temporal dimensions. The model is a hierarchical spatio-temporal model fitted to geographical data that utilises both deterministic and data-derived components. Specifically, rainfall data at a given location are modelled as a linear combination of these deterministic and data-derived components. A key advantage of the model is that it is fitted in a step-by-step fashion, enabling appropriate empirical choices to be made at each step.

  17. Rainfall variability over southern Africa: an overview of current research using satellite and climate model data

    Science.gov (United States)

    Williams, C.; Kniveton, D.; Layberry, R.

    2009-04-01

    It is increasingly accepted that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. A change in the distribution and magnitude of extreme rainfall events (associated with changing variability), such as droughts or flooding, may have a far greater impact on human and natural systems than a changing mean. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The subcontinent is considered especially vulnerable to and ill-equipped (in terms of adaptation) for extreme events, due to a number of factors including extensive poverty, famine, disease and political instability. Rainfall variability is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. In this research, satellite-derived rainfall data are used as a basis for undertaking model experiments using a state-of-the-art climate model, run at both high and low spatial resolution. Once the model's ability to reproduce extremes has been assessed, idealised regions of sea surface temperature (SST) anomalies are used to force the model, with the overall aim of investigating the ways in which SST anomalies influence rainfall extremes over southern Africa. In this paper, a brief overview is given of the authors' research to date, pertaining to southern African rainfall. This covers (i) a description of present-day rainfall variability over southern Africa; (ii) a comparison of model simulated daily rainfall with the satellite-derived dataset; (iii) results from sensitivity testing of the model's domain size; and (iv) results from the idealised SST experiments.

  18. Modeling Daily Rainfall Conditional on Atmospheric Predictors: An application to Western Greece

    Science.gov (United States)

    Langousis, Andreas; Kaleris, Vassilios

    2013-04-01

    Due to its intermittent and highly variable character, daily precipitation is the least well reproduced hydrologic variable by both General Circulation Models (GCMs) and Limited Area Models (LAMs). To that extent, several statistical procedures (usually referred to as downscaling schemes) have been suggested to generate synthetic rainfall time series conditional on predictor variables that are descriptive of the atmospheric circulation at the mesoscale. In addition to be more accurately simulated by GCMs and LAMs, large-scale atmospheric predictors are important indicators of the local weather. Currently used downscaling methods simulate rainfall series using either stable statistical relationships (usually referred to as transfer functions) between certain characteristics of the rainfall process and mesoscale atmospheric predictor variables, or simple stochastic schemes (e.g. properly transformed autoregressive models) with parameters that depend on the large-scale atmospheric conditions. The latter are determined by classifying large-scale circulation patterns into broad categories of weather states, using empirical or theoretically based classification schemes, and modeled by resampling from those categories; a process usually referred to as weather generation. In this work we propose a statistical framework to generate synthetic rainfall timeseries at a daily level, conditional on large scale atmospheric predictors. The latter include the mean sea level pressure (MSLP), the magnitude and direction of upper level geostrophic winds, and the 500 hPa geopotential height, relative vorticity and divergence. The suggested framework operates in continuous time, avoiding the use of transfer functions, and weather classification schemes. The suggested downscaling approach is validated using atmospheric data from the ERA-Interim archive (see http://www.ecmwf.int/research/era/do/get/index), and daily rainfall data from Western Greece, for the 14-year period from 01 October

  19. Modeling rainfall infiltration on hillslopes using Flux-concentration relation and time compression approximation

    Science.gov (United States)

    Wang, Jie; Chen, Li; Yu, Zhongbo

    2018-02-01

    Rainfall infiltration on hillslopes is an important issue in hydrology, which is related to many environmental problems, such as flood, soil erosion, and nutrient and contaminant transport. This study aimed to improve the quantification of infiltration on hillslopes under both steady and unsteady rainfalls. Starting from Darcy's law, an analytical integral infiltrability equation was derived for hillslope infiltration by use of the flux-concentration relation. Based on this equation, a simple scaling relation linking the infiltration times on hillslopes and horizontal planes was obtained which is applicable for both small and large times and can be used to simplify the solution procedure of hillslope infiltration. The infiltrability equation also improved the estimation of ponding time for infiltration under rainfall conditions. For infiltration after ponding, the time compression approximation (TCA) was applied together with the infiltrability equation. To improve the computational efficiency, the analytical integral infiltrability equation was approximated with a two-term power-like function by nonlinear regression. Procedures of applying this approach to both steady and unsteady rainfall conditions were proposed. To evaluate the performance of the new approach, it was compared with the Green-Ampt model for sloping surfaces by Chen and Young (2006) and Richards' equation. The proposed model outperformed the sloping Green-Ampt, and both ponding time and infiltration predictions agreed well with the solutions of Richards' equation for various soil textures, slope angles, initial water contents, and rainfall intensities for both steady and unsteady rainfalls.

  20. Areal rainfall estimation using moving cars - computer experiments including hydrological modeling

    Science.gov (United States)

    Rabiei, Ehsan; Haberlandt, Uwe; Sester, Monika; Fitzner, Daniel; Wallner, Markus

    2016-09-01

    The need for high temporal and spatial resolution precipitation data for hydrological analyses has been discussed in several studies. Although rain gauges provide valuable information, a very dense rain gauge network is costly. As a result, several new ideas have emerged to help estimating areal rainfall with higher temporal and spatial resolution. Rabiei et al. (2013) observed that moving cars, called RainCars (RCs), can potentially be a new source of data for measuring rain rate. The optical sensors used in that study are designed for operating the windscreen wipers and showed promising results for rainfall measurement purposes. Their measurement accuracy has been quantified in laboratory experiments. Considering explicitly those errors, the main objective of this study is to investigate the benefit of using RCs for estimating areal rainfall. For that, computer experiments are carried out, where radar rainfall is considered as the reference and the other sources of data, i.e., RCs and rain gauges, are extracted from radar data. Comparing the quality of areal rainfall estimation by RCs with rain gauges and reference data helps to investigate the benefit of the RCs. The value of this additional source of data is not only assessed for areal rainfall estimation performance but also for use in hydrological modeling. Considering measurement errors derived from laboratory experiments, the result shows that the RCs provide useful additional information for areal rainfall estimation as well as for hydrological modeling. Moreover, by testing larger uncertainties for RCs, they observed to be useful up to a certain level for areal rainfall estimation and discharge simulation.

  1. Modelling of extreme minimum rainfall using generalised extreme value distribution for Zimbabwe

    Directory of Open Access Journals (Sweden)

    Delson Chikobvu

    2015-09-01

    Full Text Available We modelled the mean annual rainfall for data recorded in Zimbabwe from 1901 to 2009. Extreme value theory was used to estimate the probabilities of meteorological droughts. Droughts can be viewed as extreme events which go beyond and/or below normal rainfall occurrences, such as exceptionally low mean annual rainfall. The duality between the distribution of the minima and maxima was exploited and used to fit the generalised extreme value distribution (GEVD to the data and hence find probabilities of extreme low levels of mean annual rainfall. The augmented Dickey Fuller test confirmed that rainfall data were stationary, while the normal quantile-quantile plot indicated that rainfall data deviated from the normality assumption at both ends of the tails of the distribution. The maximum likelihood estimation method and the Bayesian approach were used to find the parameters of the GEVD. The Kolmogorov-Smirnov and Anderson-Darling goodnessof- fit tests showed that the Weibull class of distributions was a good fit to the minima mean annual rainfall using the maximum likelihood estimation method. The mean return period estimate of a meteorological drought using the threshold value of mean annual rainfall of 473 mm was 8 years. This implies that if in the year there is a meteorological drought then another drought of the same intensity or greater is expected after 8 years. It is expected that the use of Bayesian inference may better quantify the level of uncertainty associated with the GEVD parameter estimates than with the maximum likelihood estimation method. The Markov chain Monte Carlo algorithm for the GEVD was applied to construct the model parameter estimates using the Bayesian approach. These findings are significant because results based on non-informative priors (Bayesian method and the maximum likelihood method approach are expected to be similar.

  2. Estimation of Stormwater Interception Rate for various LID Facilities

    Science.gov (United States)

    Kim, S.; Lee, O.; Choi, J.

    2017-12-01

    In this study, the stormwater interception rate is proposed to apply in the design of LID facilities. For this purpose, EPA-SWMM is built with some areas of Noksan National Industrial Complex where long-term observed stormwater data were monitored and stormwater interception rates for various design capacities of various LID facilities are estimated. While the sensitivity of stormwater interception rate according to design specifications of bio-retention and infiltration trench facilities is not large, the sensitivity of stormwater interception rate according to local rainfall characteristics is relatively big. As a result of comparing the present rainfall interception rate estimation method which is officially operated in Korea with the one proposed in this study, it will be presented that the present method is highly likely to overestimate the performance of the bio-retention and infiltration trench facilities. Finally, a new stormwater interception rate formulas for the bio-retention and infiltration trench LID facilities will be proposed. Acknowledgement This research was supported by a grant (2016000200002) from Public Welfare Technology Development Program funded by Ministry of Environment of Korean government.

  3. Rainfall Erosivity in Europe

    DEFF Research Database (Denmark)

    Panagos, Panos; Ballabio, Cristiano; Borrelli, Pasquale

    2015-01-01

    Rainfall is one the main drivers of soil erosion. The erosive force of rainfall is expressed as rainfall erosivity. Rainfall erosivity considers the rainfall amount and intensity, and is most commonly expressed as the Rfactor in the USLE model and its revised version, RUSLE. At national...... and continental levels, the scarce availability of data obliges soil erosion modellers to estimate this factor based on rainfall data with only low temporal resolution (daily, monthly, annual averages). The purpose of this study is to assess rainfall erosivity in Europe in the form of the RUSLE R-factor, based...

  4. Nonstationary modeling of a long record of rainfall and temperature over Rome

    Science.gov (United States)

    Villarini, Gabriele; Smith, James A.; Napolitano, Francesco

    2010-10-01

    A long record (1862-2004) of seasonal rainfall and temperature from the Rome observatory of Collegio Romano are modeled in a nonstationary framework by means of the Generalized Additive Models in Location, Scale and Shape (GAMLSS). Modeling analyses are used to characterize nonstationarities in rainfall and related climate variables. It is shown that the GAMLSS models are able to represent the magnitude and spread in the seasonal time series with parameters which are a smooth function of time. Covariate analyses highlight the role of seasonal and interannual variability of large-scale climate forcing, as reflected in three teleconnection indexes (Atlantic Multidecadal Oscillation, North Atlantic Oscillation, and Mediterranean Index), for modeling seasonal rainfall and temperature over Rome. In particular, the North Atlantic Oscillation is a significant predictor during the winter, while the Mediterranean Index is a significant predictor for almost all seasons.

  5. Simulation of the Indian summer monsoon onset-phase rainfall using a regional model

    KAUST Repository

    Srinivas, C. V.

    2015-09-11

    This study examines the ability of the Advanced Research WRF (ARW) regional model to simulate Indian summer monsoon (ISM) rainfall climatology in different climate zones during the monsoon onset phase in the decade 2000–2009. The initial and boundary conditions for ARW are provided from the NCEP/NCAR Reanalysis Project (NNRP) global reanalysis. Seasonal onset-phase rainfall is compared with corresponding values from 0.25° IMD (India Meteorological Department) rainfall and NNRP precipitation data over seven climate zones (perhumid, humid, dry/moist, subhumid, dry/moist, semiarid and arid) of India to see whether dynamical downscaling using a regional model yields advantages over just using large-scale model predictions. Results show that the model could simulate the onset phase in terms of progression and distribution of rainfall in most zones (except over the northeast) with good correlations and low error metrics. The observed mean onset dates and their variability over different zones are well reproduced by the regional model over most climate zones. It has been found that the ARW performed similarly to the reanalysis in most zones and improves the onset time by 1 to 3 days in zones 4 and 7, in which the NNRP shows a delayed onset compared to the actual IMD onset times. The variations in the onset-phase rainfall during the below-normal onset (June negative) and above-normal onset (June positive) phases are well simulated. The slight underestimation of onset-phase rainfall in the northeast zone could be due to failure in resolving the wide extent of topographic variations and the associated multiscale interactions in that zone. Spatial comparisons showed improvement of pentad rainfall in both space and quantity in ARW simulations over NNRP data, as evident from a wider eastward distribution of pentad rainfall over the Western Ghats, central and eastern India, as in IMD observations. While NNRP under-represented the high pentad rainfall over northeast, east and

  6. Simulation of the Indian summer monsoon onset-phase rainfall using a regional model

    Directory of Open Access Journals (Sweden)

    C. V. Srinivas

    2015-09-01

    Full Text Available This study examines the ability of the Advanced Research WRF (ARW regional model to simulate Indian summer monsoon (ISM rainfall climatology in different climate zones during the monsoon onset phase in the decade 2000–2009. The initial and boundary conditions for ARW are provided from the NCEP/NCAR Reanalysis Project (NNRP global reanalysis. Seasonal onset-phase rainfall is compared with corresponding values from 0.25° IMD (India Meteorological Department rainfall and NNRP precipitation data over seven climate zones (perhumid, humid, dry/moist, subhumid, dry/moist, semiarid and arid of India to see whether dynamical downscaling using a regional model yields advantages over just using large-scale model predictions. Results show that the model could simulate the onset phase in terms of progression and distribution of rainfall in most zones (except over the northeast with good correlations and low error metrics. The observed mean onset dates and their variability over different zones are well reproduced by the regional model over most climate zones. It has been found that the ARW performed similarly to the reanalysis in most zones and improves the onset time by 1 to 3 days in zones 4 and 7, in which the NNRP shows a delayed onset compared to the actual IMD onset times. The variations in the onset-phase rainfall during the below-normal onset (June negative and above-normal onset (June positive phases are well simulated. The slight underestimation of onset-phase rainfall in the northeast zone could be due to failure in resolving the wide extent of topographic variations and the associated multiscale interactions in that zone. Spatial comparisons showed improvement of pentad rainfall in both space and quantity in ARW simulations over NNRP data, as evident from a wider eastward distribution of pentad rainfall over the Western Ghats, central and eastern India, as in IMD observations. While NNRP under-represented the high pentad rainfall over

  7. A geomorphology-based ANFIS model for multi-station modeling of rainfall-runoff process

    Science.gov (United States)

    Nourani, Vahid; Komasi, Mehdi

    2013-05-01

    This paper demonstrates the potential use of Artificial Intelligence (AI) techniques for predicting daily runoff at multiple gauging stations. Uncertainty and complexity of the rainfall-runoff process due to its variability in space and time in one hand and lack of historical data on the other hand, cause difficulties in the spatiotemporal modeling of the process. In this paper, an Integrated Geomorphological Adaptive Neuro-Fuzzy Inference System (IGANFIS) model conjugated with C-means clustering algorithm was used for rainfall-runoff modeling at multiple stations of the Eel River watershed, California. The proposed model could be used for predicting runoff in the stations with lack of data or any sub-basin within the watershed because of employing the spatial and temporal variables of the sub-basins as the model inputs. This ability of the integrated model for spatiotemporal modeling of the process was examined through the cross validation technique for a station. In this way, different ANFIS structures were trained using Sugeno algorithm in order to estimate daily discharge values at different stations. In order to improve the model efficiency, the input data were then classified into some clusters by the means of fuzzy C-means (FCMs) method. The goodness-of-fit measures support the gainful use of the IGANFIS and FCM methods in spatiotemporal modeling of hydrological processes.

  8. Forecasting and Analysis of Monthly Rainfalls in Ardabil Province by Arima, Autoregrressive, and Winters Models

    Directory of Open Access Journals (Sweden)

    B. Salahi

    2017-01-01

    Full Text Available Introduction: Rainfall has the highest variability at time and place scale. Rainfall fluctuation in different geographical areas reveals the necessity of investigating this climate element and suitable models to forecast the rate of precipitation for regional planning. Ardabil province has always faced rainfall fluctuations and shortage of water supply. Precipitation is one of the most important features of the environment. The amount of precipitation over time and in different places is subject to large fluctuations which may be periodical. Studies show that, due to the certain complexities of rainfall, the models which used to predict future values will also need greater accuracy and less error. Among the forecasting models, Arima has more applications and it has replaced with other models. Materials and Methods: In this research, through order 2 Autoregrressive, Winters, and Arima models, monthly rainfalls of Ardabil synoptic station (representing Ardabil province for a 31-year period (1977-2007 were investigated. To assess the presence or absence of significant changes in mean precipitation of Ardabil synoptic station, rainfall of this station was divided into two periods: 1977-1993 and 1994-2010. T-test was used to statistically examine the difference between the two periods. After adjusting the data, descriptive statistics were applied. In order to model the total monthly precipitation of Ardabil synoptic station, Winters, Autoregressive, and Arima models were used. Among different models, the best options were chosen to predict the time series including the mean absolute deviation (MAD, the mean squared errors (MSE, root mean square errors (RMSE and mean absolute percentage errors (MAPE. In order to select the best model among the available options under investigation, the predicted value of the deviation of the actual value was utilized for the months of 2006-2010. Results and Discussion: Statistical characteristics of the total monthly

  9. A spatial and nonstationary model for the frequency of extreme rainfall events

    DEFF Research Database (Denmark)

    Gregersen, Ida Bülow; Madsen, Henrik; Rosbjerg, Dan

    2013-01-01

    of extreme rainfall events, a statistical model is tested for this purpose. The model is built on the theory of generalized linear models and uses Poisson regression solved by generalized estimation equations. Spatial and temporal explanatory variables can be included simultaneously, and their relative...

  10. Daily rainfall-runoff modelling by neural networks in semi-arid zone ...

    African Journals Online (AJOL)

    This research work will allow checking efficiency of formal neural networks for flows' modelling of wadi Ouahrane's basin from rainfall-runoff relation which is non-linear. Two models of neural networks were optimized through supervised learning and compared in order to achieve this goal, the first model with input rain, and ...

  11. Relationships between southeastern Australian rainfall and sea surface temperatures examined using a climate model

    Science.gov (United States)

    Watterson, I. G.

    2010-05-01

    Rainfall in southeastern Australia has declined in recent years, particularly during austral autumn over the state of Victoria. A recent study suggests that sea surface temperature (SST) variations in both the Indonesian Throughflow (ITF) region and in a meridional dipole in the central Indian Ocean have influenced Victorian late autumn rainfall since 1950. However, it remains unclear to what extent SSTs in these and other regions force such a teleconnection. Analysis of a 1080 year simulation by the climate model CSIRO Mk3.5 shows that the model Victorian rainfall is correlated rather realistically with SSTs but that part of the above relationships is due to the model ENSO. Furthermore, the remote patterns of pressure, rainfall, and land temperature greatly diminish when the data are lagged by 1 month, suggesting that the true forcing by the persisting SSTs is weak. In a series of simulations of the atmospheric Mk3.5 with idealized SST anomalies, raised SSTs to the east of Indonesia lower the simulated Australian rainfall, while those to the west raise it. A positive ITF anomaly lowers pressure over Australia, but with little effect on Victorian rainfall. The meridional dipole and SSTs to the west and southeast of Australia have little direct effect on southeastern Australia in the model. The results suggest that tropical SSTs predominate as an influence on Victorian rainfall. However, the SST indices appear to explain only a fraction of the observed trend, which in the case of decadal means remains within the range of unforced variability simulated by Mk3.5.

  12. Prediction of Meiyu rainfall in Taiwan by multi-lead physical-empirical models

    Science.gov (United States)

    Yim, So-Young; Wang, Bin; Xing, Wen; Lu, Mong-Ming

    2015-06-01

    Taiwan is located at the dividing point of the tropical and subtropical monsoons over East Asia. Taiwan has double rainy seasons, the Meiyu in May-June and the Typhoon rains in August-September. To predict the amount of Meiyu rainfall is of profound importance to disaster preparedness and water resource management. The seasonal forecast of May-June Meiyu rainfall has been a challenge to current dynamical models and the factors controlling Taiwan Meiyu variability has eluded climate scientists for decades. Here we investigate the physical processes that are possibly important for leading to significant fluctuation of the Taiwan Meiyu rainfall. Based on this understanding, we develop a physical-empirical model to predict Taiwan Meiyu rainfall at a lead time of 0- (end of April), 1-, and 2-month, respectively. Three physically consequential and complementary predictors are used: (1) a contrasting sea surface temperature (SST) tendency in the Indo-Pacific warm pool, (2) the tripolar SST tendency in North Atlantic that is associated with North Atlantic Oscillation, and (3) a surface warming tendency in northeast Asia. These precursors foreshadow an enhanced Philippine Sea anticyclonic anomalies and the anomalous cyclone near the southeastern China in the ensuing summer, which together favor increasing Taiwan Meiyu rainfall. Note that the identified precursors at various lead-times represent essentially the same physical processes, suggesting the robustness of the predictors. The physical empirical model made by these predictors is capable of capturing the Taiwan rainfall variability with a significant cross-validated temporal correlation coefficient skill of 0.75, 0.64, and 0.61 for 1979-2012 at the 0-, 1-, and 2-month lead time, respectively. The physical-empirical model concept used here can be extended to summer monsoon rainfall prediction over the Southeast Asia and other regions.

  13. Regionalization of the Modified Bartlett-Lewis Rectangular Pulse Stochastic Rainfall Model

    Directory of Open Access Journals (Sweden)

    Dongkyun Kim

    2013-01-01

    Full Text Available Parameters of the Modified Bartlett-Lewis Rectangular Pulse (MBLRP stochastic rainfall simulation model were regionalized across the contiguous United States. Three thousand four hundred forty-four National Climate Data Center (NCDC rain gauges were used to obtain spatial and seasonal patterns of the model parameters. The MBLRP model was calibrated to minimize the discrepancy between the precipitation depth statistics between the observed and MBLRP-generated precipitation time series. These statistics included the mean, variance, probability of zero rainfall and autocorrelation at 1-, 3-, 12- and 24-hour accumulation intervals. The Ordinary Kriging interpolation technique was used to generate maps of the six MBLRP model parameters for each of the 12 months of the year. All parameters had clear to discernible regional tendencies; except for one related to rain cell duration distribution. Parameter seasonality was not obvious and it was more apparent in some locations than in others, depending on the seasonality of the rainfall statistics. Cross-validation was used to assess the validity of the parameter maps. The results indicate that the suggested maps reproduce well the observed rainfall statistics for different accumulation intervals, except for the lag-1 autocorrelation coefficient. The boundaries of the expected residual, with 95% confidence, between the observed rainfall statistics and the simulated rainfall statistics based on the map parameters were approximately ±0.064 mm hr-1, ±1.63 mm2 hr-2, ±0.16, and ±0.030 for the mean, variance, lag-1 autocorrelation and probability of zero rainfall at hourly accumulation levels, respectively. The estimated parameter values were also used to estimate the storm and rain cell characteristics.

  14. The modified turning bands (MTB) model for space-time rainfall. I. Model definition and properties

    Science.gov (United States)

    Mellor, Dale

    1996-02-01

    A new stochastic model of space-time rainfall, the Modified Turning Bands (MTB) model, is proposed which reproduces, in particular, the movements and developments of rainbands, cluster potential regions and raincells, as well as their respective interactions. The ensemble correlation structure is unsuitable for practical estimation of the model parameters because the model is not ergodic in this statistic, and hence it cannot easily be measured from a single real storm. Thus, some general theory on the internal covariance structure of a class of stochastic models is presented, of which the MTB model is an example. It is noted that, for the MTB model, the internal covariance structure may be measured from a single storm, and can thus be used for model identification.

  15. Integrating Artificial Neural Networks into the VIC Model for Rainfall-Runoff Modeling

    Directory of Open Access Journals (Sweden)

    Changqing Meng

    2016-09-01

    Full Text Available A hybrid rainfall-runoff model was developed in this study by integrating the variable infiltration capacity (VIC model with artificial neural networks (ANNs. In the proposed model, the prediction interval of the ANN replaces separate, individual simulation (i.e., single simulation. The spatial heterogeneity of horizontal resolution, subgrid-scale features and their influence on the streamflow can be assessed according to the VIC model. In the routing module, instead of a simple linear superposition of the streamflow generated from each subbasin, ANNs facilitate nonlinear mappings of the streamflow produced from each subbasin into the total streamflow at the basin outlet. A total of three subbasins were delineated and calibrated independently via the VIC model; daily runoff errors were simulated for each subbasin, then corrected by an ANN bias-correction model. The initial streamflow and corrected runoff from the simulation for individual subbasins serve as inputs to the ANN routing model. The feasibility of this proposed method was confirmed according to the performance of its application to a case study on rainfall-runoff prediction in the Jinshajiang River Basin, the headwater area of the Yangtze River.

  16. Stochastic Modeling of Rainfall in Peninsular Malaysia Using Bartlett Lewis Rectangular Pulses Models

    Directory of Open Access Journals (Sweden)

    Ibrahim Suliman Hanaish

    2011-01-01

    Full Text Available Three versions of Bartlett Lewis rectangular pulse rainfall models, namely, the Original Bartlett Lewis (OBL, Modified Bartlett Lewis (MBL, and 2N-cell-type Bartlett Lewis model (BL2n, are considered. These models are fitted to the hourly rainfall data from 1970 to 2008 obtained from Petaling Jaya rain gauge station, located in Peninsular Malaysia. The generalized method of moments is used to estimate the model parameters. Under this method, minimization of two different objective functions which involve different weight functions, one weight is inversely proportional to the variance and another one is inversely proportional to the mean squared, is carried out using Nelder-Mead optimization technique. For the purpose of comparison of the performance of the three different models, the results found for the months of July and November are used for illustration. This performance is assessed based on the goodness of fit of the models. In addition, the sensitivity of the parameter estimates to the choice of the objective function is also investigated. It is found that BL2n slightly outperforms OBL. However, the best model is the Modified Bartlett Lewis MBL, particularly when the objective function considered involves weight which is inversely proportional to the variance.

  17. The use of geostationary satellite based rainfall estimation and rainfall-runoff modelling for regional flash flood assessment

    OpenAIRE

    Suseno, Dwi Prabowo Yuga

    2013-01-01

    The availability of rainfall triggered hazard information such as flash flood is crucial in the flood disaster management and mitigation. However, providing that information is mainly hampered by the shortage of data because of the sparse, uneven or absence the hydrological or meteorological observation. Remote sensing techniques that make frequent observations with continuous spatial coverage provide useful information for detecting the hydrometeorological phenomena such as rainfall and floo...

  18. Statistical bias correction modelling for seasonal rainfall forecast for the case of Bali island

    Science.gov (United States)

    Lealdi, D.; Nurdiati, S.; Sopaheluwakan, A.

    2018-04-01

    Rainfall is an element of climate which is highly influential to the agricultural sector. Rain pattern and distribution highly determines the sustainability of agricultural activities. Therefore, information on rainfall is very useful for agriculture sector and farmers in anticipating the possibility of extreme events which often cause failures of agricultural production. This research aims to identify the biases from seasonal forecast products from ECMWF (European Centre for Medium-Range Weather Forecasts) rainfall forecast and to build a transfer function in order to correct the distribution biases as a new prediction model using quantile mapping approach. We apply this approach to the case of Bali Island, and as a result, the use of bias correction methods in correcting systematic biases from the model gives better results. The new prediction model obtained with this approach is better than ever. We found generally that during rainy season, the bias correction approach performs better than in dry season.

  19. Intense rainfalls prediction models for the state of Mato Grosso, Brazil

    Directory of Open Access Journals (Sweden)

    Sidney Pereira

    2011-12-01

    Full Text Available Rain intensity data are necessary to increase security of hydraulic projects. The objective of this study was to determine the relationships among intensity-duration-frequency (IDF and Bell’s model for the State of Mato Grosso, Brazil. The equations were obtained by disaggregation of 24 h rainfall data from 136 rain stations available in the National Water Agency (ANA data base. Employing Gumbel distribution, the rainfalls were estimated for each time duration and for the return periods of 2, 5, 10, 25, 50 and 100 years, and thereafter for each season. The coefficients of IDF relationships and Bell’s models were adjusted by the minimum square method, for all seasons evaluated. The coefficients of determination and Willmott agreement index exceeded 0.98 and 0.85, respectively, for all stations, which classifies the adjustment of the rainfall models as great.

  20. The potential of detecting intermediate-scale biomass and canopy interception in a coniferous forest using cosmic-ray neutron intensity measurements and neutron transport modeling

    Science.gov (United States)

    Andreasen, M.; Looms, M. C.; Bogena, H. R.; Desilets, D.; Zreda, M. G.; Sonnenborg, T. O.; Jensen, K. H.

    2014-12-01

    . Additionally, neutron transport modeling, using the extended version of the Monte Carlo N-Particle Transport Code, was conducted. The responses of the reference condition, different amounts of biomass, soil moisture and canopy interception on the cosmic-ray neutron intensity were simulated and compared to the measurements.

  1. Introducing a rainfall compound distribution model based on weather patterns sub-sampling

    Directory of Open Access Journals (Sweden)

    F. Garavaglia

    2010-06-01

    Full Text Available This paper presents a probabilistic model for daily rainfall, using sub-sampling based on meteorological circulation. We classified eight typical but contrasted synoptic situations (weather patterns for France and surrounding areas, using a "bottom-up" approach, i.e. from the shape of the rain field to the synoptic situations described by geopotential fields. These weather patterns (WP provide a discriminating variable that is consistent with French climatology, and allows seasonal rainfall records to be split into more homogeneous sub-samples, in term of meteorological genesis.

    First results show how the combination of seasonal and WP sub-sampling strongly influences the identification of the asymptotic behaviour of rainfall probabilistic models. Furthermore, with this level of stratification, an asymptotic exponential behaviour of each sub-sample appears as a reasonable hypothesis. This first part is illustrated with two daily rainfall records from SE of France.

    The distribution of the multi-exponential weather patterns (MEWP is then defined as the composition, for a given season, of all WP sub-sample marginal distributions, weighted by the relative frequency of occurrence of each WP. This model is finally compared to Exponential and Generalized Pareto distributions, showing good features in terms of robustness and accuracy. These final statistical results are computed from a wide dataset of 478 rainfall chronicles spread on the southern half of France. All these data cover the 1953–2005 period.

  2. Analysis and modelling of spatio-temporal properties of daily rainfall over the Danube basin

    Science.gov (United States)

    Serinaldi, F.; Kilsby, C. G.

    2012-04-01

    Central and Eastern Europe are prone to severe floods due to heavy rainfall that cause societal and economic damages, ranging from agriculture to water resources, from the insurance/reinsurance sector to the energy industry. To improve the flood risk analysis, a better characterisation and modelling of the rainfall patterns over this area, which involves the Danube river watershed, is strategically important. In this study, we analyse the spatio-temporal properties of a large data set of daily rainfall time series from 15 countries in the Central Eastern Europe through different lagged and non-lagged indices of associations that quantify both the overall dependence and extreme dependence of pairwise observations. We also show that these measures are linked to each other and can be written in a unique and coherent notation within the copula framework. Moreover, the lagged version of these measures allows exploring some important spatio-temporal properties of the rainfall fields. The exploratory analysis is complemented by the preliminary results of a spatio-temporal rainfall simulation performed via a compound model based upon the Generalized Additive Models for Location, Scale and Shape (GAMLSS) and meta-elliptical multivariate distributions.

  3. The Unsaturated Hydromechanical Coupling Model of Rock Slope Considering Rainfall Infiltration Using DDA

    Directory of Open Access Journals (Sweden)

    Xianshan Liu

    2017-01-01

    Full Text Available Water flow and hydromechanical coupling process in fractured rocks is more different from that in general porous media because of heterogeneous spatial fractures and possible fracture-dominated flow; a saturated-unsaturated hydromechanical coupling model using a discontinuous deformation analysis (DDA similar to FEM and DEM was employed to analyze water movement in saturated-unsaturated deformed rocks, in which the Van-Genuchten model differently treated the rock and fractures permeable properties to describe the constitutive relationships. The calibrating results for the dam foundation indicated the validation and feasibility of the proposed model and are also in good agreement with the calculations based on DEM still demonstrating its superiority. And then, the rainfall infiltration in a reservoir rock slope was detailedly investigated to describe the water pressure on the fault surface and inside the rocks, displacement, and stress distribution under hydromechanical coupling conditions and uncoupling conditions. It was observed that greater rainfall intensity and longer rainfall time resulted in lower stability of the rock slope, and larger difference was very obvious between the hydromechanical coupling condition and uncoupling condition, demonstrating that rainfall intensity, rainfall time, and hydromechanical coupling effect had great influence on the saturated-unsaturated water flow behavior and mechanical response of the fractured rock slopes.

  4. Simulated transient thermal infrared emissions of forest canopies during rainfall events

    Science.gov (United States)

    Ballard, Jerrell R.; Hawkins, William R.; Howington, Stacy E.; Kala, Raju V.

    2017-05-01

    We describe the development of a centimeter-scale resolution simulation framework for a theoretical tree canopy that includes rainfall deposition, evaporation, and thermal infrared emittance. Rainfall is simulated as discrete raindrops with specified rate. The individual droplets will either fall through the canopy and intersect the ground; adhere to a leaf; bounce or shatter on impact with a leaf resulting in smaller droplets that are propagated through the canopy. Surface physical temperatures are individually determined by surface water evaporation, spatially varying within canopy wind velocities, solar radiation, and water vapor pressure. Results are validated by theoretical canopy gap and gross rainfall interception models.

  5. Application of a probabilistic model of rainfall-induced shallow landslides to complex hollows

    NARCIS (Netherlands)

    Talebi, A.; Uijlenhoet, R.; Troch, P.A.

    2008-01-01

    Recently, D'Odorico and Fagherazzi (2003) proposed "A probabilistic model of rainfall-triggered shallow landslides in hollows" (Water Resour. Res., 39, 2003). Their model describes the long-term evolution of colluvial deposits through a probabilistic soil mass balance at a point. Further building

  6. a multi-period markov model for monthly rainfall in lagos, nigeria

    African Journals Online (AJOL)

    PUBLICATIONS1

    A twelve-period. Markov model has been developed for the monthly rainfall data for Lagos, along the coast of .... autoregressive process to model river flow; Deo et al. (2015) utilized an ...... quences for the analysis of river basins by simulation.

  7. A mathematical model for soil solute transfer into surface runoff as influenced by rainfall detachment.

    Science.gov (United States)

    Yang, Ting; Wang, Quanjiu; Wu, Laosheng; Zhao, Guangxu; Liu, Yanli; Zhang, Pengyu

    2016-07-01

    Nutrients transport is a main source of water pollution. Several models describing transport of soil nutrients such as potassium, phosphate and nitrate in runoff water have been developed. The objectives of this research were to describe the nutrients transport processes by considering the effect of rainfall detachment, and to evaluate the factors that have greatest influence on nutrients transport into runoff. In this study, an existing mass-conservation equation and rainfall detachment process were combined and augmented to predict runoff of nutrients in surface water in a Loess Plateau soil in Northwestern Yangling, China. The mixing depth is a function of time as a result of rainfall impact, not a constant as described in previous models. The new model was tested using two different sub-models of complete-mixing and incomplete-mixing. The complete-mixing model is more popular to use for its simplicity. It captured the runoff trends of those high adsorption nutrients, and of nutrients transport along steep slopes. While the incomplete-mixing model predicted well for the highest observed concentrations of the test nutrients. Parameters inversely estimated by the models were applied to simulate nutrients transport, results suggested that both models can be adopted to describe nutrients transport in runoff under the impact of rainfall. Copyright © 2016 Elsevier B.V. All rights reserved.

  8. Weather models as virtual sensors to data-driven rainfall predictions in urban watersheds

    Science.gov (United States)

    Cozzi, Lorenzo; Galelli, Stefano; Pascal, Samuel Jolivet De Marc; Castelletti, Andrea

    2013-04-01

    Weather and climate predictions are a key element of urban hydrology where they are used to inform water management and assist in flood warning delivering. Indeed, the modelling of the very fast dynamics of urbanized catchments can be substantially improved by the use of weather/rainfall predictions. For example, in Singapore Marina Reservoir catchment runoff processes have a very short time of concentration (roughly one hour) and observational data are thus nearly useless for runoff predictions and weather prediction are required. Unfortunately, radar nowcasting methods do not allow to carrying out long - term weather predictions, whereas numerical models are limited by their coarse spatial scale. Moreover, numerical models are usually poorly reliable because of the fast motion and limited spatial extension of rainfall events. In this study we investigate the combined use of data-driven modelling techniques and weather variables observed/simulated with a numerical model as a way to improve rainfall prediction accuracy and lead time in the Singapore metropolitan area. To explore the feasibility of the approach, we use a Weather Research and Forecast (WRF) model as a virtual sensor network for the input variables (the states of the WRF model) to a machine learning rainfall prediction model. More precisely, we combine an input variable selection method and a non-parametric tree-based model to characterize the empirical relation between the rainfall measured at the catchment level and all possible weather input variables provided by WRF model. We explore different lead time to evaluate the model reliability for different long - term predictions, as well as different time lags to see how past information could improve results. Results show that the proposed approach allow a significant improvement of the prediction accuracy of the WRF model on the Singapore urban area.

  9. Improving predictive power of physically based rainfall-induced shallow landslide models: a probabilistic approach

    Directory of Open Access Journals (Sweden)

    S. Raia

    2014-03-01

    Full Text Available Distributed models to forecast the spatial and temporal occurrence of rainfall-induced shallow landslides are based on deterministic laws. These models extend spatially the static stability models adopted in geotechnical engineering, and adopt an infinite-slope geometry to balance the resisting and the driving forces acting on the sliding mass. An infiltration model is used to determine how rainfall changes pore-water conditions, modulating the local stability/instability conditions. A problem with the operation of the existing models lays in the difficulty in obtaining accurate values for the several variables that describe the material properties of the slopes. The problem is particularly severe when the models are applied over large areas, for which sufficient information on the geotechnical and hydrological conditions of the slopes is not generally available. To help solve the problem, we propose a probabilistic Monte Carlo approach to the distributed modeling of rainfall-induced shallow landslides. For this purpose, we have modified the transient rainfall infiltration and grid-based regional slope-stability analysis (TRIGRS code. The new code (TRIGRS-P adopts a probabilistic approach to compute, on a cell-by-cell basis, transient pore-pressure changes and related changes in the factor of safety due to rainfall infiltration. Infiltration is modeled using analytical solutions of partial differential equations describing one-dimensional vertical flow in isotropic, homogeneous materials. Both saturated and unsaturated soil conditions can be considered. TRIGRS-P copes with the natural variability inherent to the mechanical and hydrological properties of the slope materials by allowing values of the TRIGRS model input parameters to be sampled randomly from a given probability distribution. The range of variation and the mean value of the parameters can be determined by the usual methods used for preparing the TRIGRS input parameters. The outputs

  10. Improving predictive power of physically based rainfall-induced shallow landslide models: a probablistic approach

    Science.gov (United States)

    Raia, S.; Alvioli, M.; Rossi, M.; Baum, R.L.; Godt, J.W.; Guzzetti, F.

    2013-01-01

    Distributed models to forecast the spatial and temporal occurrence of rainfall-induced shallow landslides are deterministic. These models extend spatially the static stability models adopted in geotechnical engineering and adopt an infinite-slope geometry to balance the resisting and the driving forces acting on the sliding mass. An infiltration model is used to determine how rainfall changes pore-water conditions, modulating the local stability/instability conditions. A problem with the existing models is the difficulty in obtaining accurate values for the several variables that describe the material properties of the slopes. The problem is particularly severe when the models are applied over large areas, for which sufficient information on the geotechnical and hydrological conditions of the slopes is not generally available. To help solve the problem, we propose a probabilistic Monte Carlo approach to the distributed modeling of shallow rainfall-induced landslides. For the purpose, we have modified the Transient Rainfall Infiltration and Grid-Based Regional Slope-Stability Analysis (TRIGRS) code. The new code (TRIGRS-P) adopts a stochastic approach to compute, on a cell-by-cell basis, transient pore-pressure changes and related changes in the factor of safety due to rainfall infiltration. Infiltration is modeled using analytical solutions of partial differential equations describing one-dimensional vertical flow in isotropic, homogeneous materials. Both saturated and unsaturated soil conditions can be considered. TRIGRS-P copes with the natural variability inherent to the mechanical and hydrological properties of the slope materials by allowing values of the TRIGRS model input parameters to be sampled randomly from a given probability distribution. The range of variation and the mean value of the parameters can be determined by the usual methods used for preparing the TRIGRS input parameters. The outputs of several model runs obtained varying the input parameters

  11. Future rainfall variations reduce abundances of aboveground arthropods in model agroecosystems with different soil types

    Directory of Open Access Journals (Sweden)

    Johann G. Zaller

    2014-10-01

    Full Text Available Climate change scenarios for Central Europe predict less frequent but heavier rainfalls and longer drought periods during the growing season. This is expected to alter arthropods in agroecosystems that are important as biocontrol agents, herbivores or food for predators (e.g. farmland birds. In a lysimeter facility (totally 18 3-m2-plots, we experimentally tested the effects of long-term past vs. prognosticated future rainfall variations (15% increased rainfall per event, 25% more dry days according to regionalized climate change models from the Intergovernmental Panel on Climate Change (IPCC on aboveground arthropods in winter wheat (Triticum aestivum L. cultivated at three different soil types (calcaric phaeozem, calcic chernozem and gleyic phaeozem. Soil types were established 17 years and rainfall treatments one month before arthropod sampling; treatments were fully crossed and replicated three times. Aboveground arthropods were assessed by suction sampling, their mean abundances (± SD differed between April, May and June with 20 ± 3 m-2, 90 ± 35 m-2 and 289 ± 93 individuals m-2, respectively. Averaged across sampling dates, future rainfall reduced the abundance of spiders (Araneae, -47%, cicadas and leafhoppers (Auchenorrhyncha, -39%, beetles (Coleoptera, -52%, ground beetles (Carabidae, -41%, leaf beetles (Chrysomelidae, -64%, spring tails (Collembola, -58%, flies (Diptera, -73% and lacewings (Neuroptera, -73% but increased the abundance of snails (Gastropoda, +69%. Across sampling dates, soil types had no effects on arthropod abundances. Arthropod diversity was neither affected by rainfall nor soil types. Arthropod abundance was positively correlated with weed biomass for almost all taxa; abundance of Hemiptera and of total arthropods was positively correlated with weed density. These detrimental effects of future rainfall varieties on arthropod taxa in wheat fields can potentially alter arthropod-associated agroecosystem services.

  12. Climate downscaling over South America for 1971-2000: application in SMAP rainfall-runoff model for Grande River Basin

    Science.gov (United States)

    da Silva, Felipe das Neves Roque; Alves, José Luis Drummond; Cataldi, Marcio

    2018-03-01

    This paper aims to validate inflow simulations concerning the present-day climate at Água Vermelha Hydroelectric Plant (AVHP—located on the Grande River Basin) based on the Soil Moisture Accounting Procedure (SMAP) hydrological model. In order to provide rainfall data to the SMAP model, the RegCM regional climate model was also used working with boundary conditions from the MIROC model. Initially, present-day climate simulation performed by RegCM model was analyzed. It was found that, in terms of rainfall, the model was able to simulate the main patterns observed over South America. A bias correction technique was also used and it was essential to reduce mistakes related to rainfall simulation. Comparison between rainfall simulations from RegCM and MIROC showed improvements when the dynamical downscaling was performed. Then, SMAP, a rainfall-runoff hydrological model, was used to simulate inflows at Água Vermelha Hydroelectric Plant. After calibration with observed rainfall, SMAP simulations were evaluated in two different periods from the one used in calibration. During calibration, SMAP captures the inflow variability observed at AVHP. During validation periods, the hydrological model obtained better results and statistics with observed rainfall. However, in spite of some discrepancies, the use of simulated rainfall without bias correction captured the interannual flow variability. However, the use of bias removal in the simulated rainfall performed by RegCM brought significant improvements to the simulation of natural inflows performed by SMAP. Not only the curve of simulated inflow became more similar to the observed inflow, but also the statistics improved their values. Improvements were also noticed in the inflow simulation when the rainfall was provided by the regional climate model compared to the global model. In general, results obtained so far prove that there was an added value in rainfall when regional climate model was compared to global climate

  13. Analysis and Modeling of Time-Correlated Characteristics of Rainfall-Runoff Similarity in the Upstream Red River Basin

    Directory of Open Access Journals (Sweden)

    Xiuli Sang

    2012-01-01

    Full Text Available We constructed a similarity model (based on Euclidean distance between rainfall and runoff to study time-correlated characteristics of rainfall-runoff similar patterns in the upstream Red River Basin and presented a detailed evaluation of the time correlation of rainfall-runoff similarity. The rainfall-runoff similarity was used to determine the optimum similarity. The results showed that a time-correlated model was found to be capable of predicting the rainfall-runoff similarity in the upstream Red River Basin in a satisfactory way. Both noised and denoised time series by thresholding the wavelet coefficients were applied to verify the accuracy of model. And the corresponding optimum similar sets obtained as the equation solution conditions showed an interesting and stable trend. On the whole, the annual mean similarity presented a gradually rising trend, for quantitatively estimating comprehensive influence of climate change and of human activities on rainfall-runoff similarity.

  14. Incorporating rainfall uncertainty in a SWAT model: the river Zenne basin (Belgium) case study

    Science.gov (United States)

    Tolessa Leta, Olkeba; Nossent, Jiri; van Griensven, Ann; Bauwens, Willy

    2013-04-01

    The European Union Water Framework Directive (EU-WFD) called its member countries to achieve a good ecological status for all inland and coastal water bodies by 2015. According to recent studies, the river Zenne (Belgium) is far from this objective. Therefore, an interuniversity and multidisciplinary project "Towards a Good Ecological Status in the river Zenne (GESZ)" was launched to evaluate the effects of wastewater management plans on the river. In this project, different models have been developed and integrated using the Open Modelling Interface (OpenMI). The hydrologic, semi-distributed Soil and Water Assessment Tool (SWAT) is hereby used as one of the model components in the integrated modelling chain in order to model the upland catchment processes. The assessment of the uncertainty of SWAT is an essential aspect of the decision making process, in order to design robust management strategies that take the predicted uncertainties into account. Model uncertainty stems from the uncertainties on the model parameters, the input data (e.g, rainfall), the calibration data (e.g., stream flows) and on the model structure itself. The objective of this paper is to assess the first three sources of uncertainty in a SWAT model of the river Zenne basin. For the assessment of rainfall measurement uncertainty, first, we identified independent rainfall periods, based on the daily precipitation and stream flow observations and using the Water Engineering Time Series PROcessing tool (WETSPRO). Secondly, we assigned a rainfall multiplier parameter for each of the independent rainfall periods, which serves as a multiplicative input error corruption. Finally, we treated these multipliers as latent parameters in the model optimization and uncertainty analysis (UA). For parameter uncertainty assessment, due to the high number of parameters of the SWAT model, first, we screened out its most sensitive parameters using the Latin Hypercube One-factor-At-a-Time (LH-OAT) technique

  15. Simulating runoff under changing climatic conditions: Revisiting an apparent deficiency of conceptual rainfall-runoff models

    Science.gov (United States)

    Fowler, Keirnan J. A.; Peel, Murray C.; Western, Andrew W.; Zhang, Lu; Peterson, Tim J.

    2016-03-01

    Hydrologic models have potential to be useful tools in planning for future climate variability. However, recent literature suggests that the current generation of conceptual rainfall runoff models tend to underestimate the sensitivity of runoff to a given change in rainfall, leading to poor performance when evaluated over multiyear droughts. This research revisited this conclusion, investigating whether the observed poor performance could be due to insufficient model calibration and evaluation techniques. We applied an approach based on Pareto optimality to explore trade-offs between model performance in different climatic conditions. Five conceptual rainfall runoff model structures were tested in 86 catchments in Australia, for a total of 430 Pareto analyses. The Pareto results were then compared with results from a commonly used model calibration and evaluation method, the Differential Split Sample Test. We found that the latter often missed potentially promising parameter sets within a given model structure, giving a false negative impression of the capabilities of the model. This suggests that models may be more capable under changing climatic conditions than previously thought. Of the 282[347] cases of apparent model failure under the split sample test using the lower [higher] of two model performance criteria trialed, 155[120] were false negatives. We discuss potential causes of remaining model failures, including the role of data errors. Although the Pareto approach proved useful, our aim was not to suggest an alternative calibration strategy, but to critically assess existing methods of model calibration and evaluation. We recommend caution when interpreting split sample results.

  16. Initial conditions of urban permeable surfaces in rainfall-runoff models using Horton’s infiltration

    DEFF Research Database (Denmark)

    Davidsen, Steffen; Löwe, Roland; Høegh Ravn, Nanna

    2017-01-01

    Infiltration is a key process controlling runoff, but varies depending on antecedent conditions. This study provides estimates on initial conditions for urban permeable surfaces via continuous simulation of the infiltration capacity using historical rain data. An analysis of historical rainfall...... records show that accumulated rainfall prior to large rain events does not depend on the return period of the event. Using an infiltration-runoff model we found that for a typical large rain storm, antecedent conditions in general lead to reduced infiltration capacity both for sandy and clayey soils...... and that there is substantial runoff for return periods above 1–10 years....

  17. Mapping extreme rainfall in the Northwest Portugal region: statistical analysis and spatial modelling

    Science.gov (United States)

    Santos, Monica; Fragoso, Marcelo

    2010-05-01

    Extreme precipitation events are one of the causes of natural hazards, such as floods and landslides, making its investigation so important, and this research aims to contribute to the study of the extreme rainfall patterns in a Portuguese mountainous area. The study area is centred on the Arcos de Valdevez county, located in the northwest region of Portugal, the rainiest of the country, with more than 3000 mm of annual rainfall at the Peneda-Gerês mountain system. This work focus on two main subjects related with the precipitation variability on the study area. First, a statistical analysis of several precipitation parameters is carried out, using daily data from 17 rain-gauges with a complete record for the 1960-1995 period. This approach aims to evaluate the main spatial contrasts regarding different aspects of the rainfall regime, described by ten parameters and indices of precipitation extremes (e.g. mean annual precipitation, the annual frequency of precipitation days, wet spells durations, maximum daily precipitation, maximum of precipitation in 30 days, number of days with rainfall exceeding 100 mm and estimated maximum daily rainfall for a return period of 100 years). The results show that the highest precipitation amounts (from annual to daily scales) and the higher frequency of very abundant rainfall events occur in the Serra da Peneda and Gerês mountains, opposing to the valleys of the Lima, Minho and Vez rivers, with lower precipitation amounts and less frequent heavy storms. The second purpose of this work is to find a method of mapping extreme rainfall in this mountainous region, investigating the complex influence of the relief (e.g. elevation, topography) on the precipitation patterns, as well others geographical variables (e.g. distance from coast, latitude), applying tested geo-statistical techniques (Goovaerts, 2000; Diodato, 2005). Models of linear regression were applied to evaluate the influence of different geographical variables (altitude

  18. Modelling the embedded rainfall process using tipping bucket data

    DEFF Research Database (Denmark)

    Thyregod, Peter; Arnbjerg-Nielsen, Karsten; Madsen, Henrik

    1998-01-01

    A new method for modelling the dynamics of rain measurement processes is suggested. The method takes the discrete nature and autocorrelation of measurements from the tipping bucket rain gauge into consideration. The considered model is a state space model with a Poisson marginal distribution....... In the model there is only one parameter, a thinning parameter. The model is tested on 39 rain events. The estimated value for the various rain events is reflecting a subjective classification of rain events into frontal and convective rain. Finally, it is demonstrated how the model can be used for simulation...

  19. A Canonical Response in Rainfall Characteristics to Global Warming: Projections by IPCC CMIP5 Models

    Science.gov (United States)

    Lau, William K. M.; Wu, H. T.; Kim, K. M.

    2012-01-01

    Changes in rainfall characteristics induced by global warming are examined based on probability distribution function (PDF) analysis, from outputs of 14 IPCC (Intergovernmental Panel on Climate Change), CMIP (5th Coupled Model Intercomparison Project) models under various scenarios of increased CO2 emissions. Results show that collectively CMIP5 models project a robust and consistent global and regional rainfall response to CO2 warming. Globally, the models show a 1-3% increase in rainfall per degree rise in temperature, with a canonical response featuring large increase (100-250 %) in frequency of occurrence of very heavy rain, a reduction (5-10%) of moderate rain, and an increase (10-15%) of light rain events. Regionally, even though details vary among models, a majority of the models (>10 out of 14) project a consistent large scale response with more heavy rain events in climatologically wet regions, most pronounced in the Pacific ITCZ and the Asian monsoon. Moderate rain events are found to decrease over extensive regions of the subtropical and extratropical oceans, but increases over the extratropical land regions, and the Southern Oceans. The spatial distribution of light rain resembles that of moderate rain, but mostly with opposite polarity. The majority of the models also show increase in the number of dry events (absence or only trace amount of rain) over subtropical and tropical land regions in both hemispheres. These results suggest that rainfall characteristics are changing and that increased extreme rainfall events and droughts occurrences are connected, as a consequent of a global adjustment of the large scale circulation to global warming.

  20. Wildcat5 for Windows, a rainfall-runoff hydrograph model: user manual and documentation

    Science.gov (United States)

    R. H. Hawkins; A. Barreto-Munoz

    2016-01-01

    Wildcat5 for Windows (Wildcat5) is an interactive Windows Excel-based software package designed to assist watershed specialists in analyzing rainfall runoff events to predict peak flow and runoff volumes generated by single-event rainstorms for a variety of watershed soil and vegetation conditions. Model inputs are: (1) rainstorm characteristics, (2) parameters related...

  1. Added value of distribution in rainfall-runoff models for the Meuse basin

    NARCIS (Netherlands)

    de Boer, T.

    2017-01-01

    Why do equal precipitation events not lead to equal discharge events across space and time? The easy answer would be because catchments are different, which then leads to the second question: Why do hydrologists often use the same rainfall-runoff model for different catchments? Probably because

  2. Prediction of Monthly Summer Monsoon Rainfall Using Global Climate Models Through Artificial Neural Network Technique

    Science.gov (United States)

    Nair, Archana; Singh, Gurjeet; Mohanty, U. C.

    2018-01-01

    The monthly prediction of summer monsoon rainfall is very challenging because of its complex and chaotic nature. In this study, a non-linear technique known as Artificial Neural Network (ANN) has been employed on the outputs of Global Climate Models (GCMs) to bring out the vagaries inherent in monthly rainfall prediction. The GCMs that are considered in the study are from the International Research Institute (IRI) (2-tier CCM3v6) and the National Centre for Environmental Prediction (Coupled-CFSv2). The ANN technique is applied on different ensemble members of the individual GCMs to obtain monthly scale prediction over India as a whole and over its spatial grid points. In the present study, a double-cross-validation and simple randomization technique was used to avoid the over-fitting during training process of the ANN model. The performance of the ANN-predicted rainfall from GCMs is judged by analysing the absolute error, box plots, percentile and difference in linear error in probability space. Results suggest that there is significant improvement in prediction skill of these GCMs after applying the ANN technique. The performance analysis reveals that the ANN model is able to capture the year to year variations in monsoon months with fairly good accuracy in extreme years as well. ANN model is also able to simulate the correct signs of rainfall anomalies over different spatial points of the Indian domain.

  3. Stochastic rainfall modeling in West Africa: Parsimonious approaches for domestic rainwater harvesting assessment

    Science.gov (United States)

    Cowden, Joshua R.; Watkins, David W., Jr.; Mihelcic, James R.

    2008-10-01

    SummarySeveral parsimonious stochastic rainfall models are developed and compared for application to domestic rainwater harvesting (DRWH) assessment in West Africa. Worldwide, improved water access rates are lowest for Sub-Saharan Africa, including the West African region, and these low rates have important implications on the health and economy of the region. Domestic rainwater harvesting (DRWH) is proposed as a potential mechanism for water supply enhancement, especially for the poor urban households in the region, which is essential for development planning and poverty alleviation initiatives. The stochastic rainfall models examined are Markov models and LARS-WG, selected due to availability and ease of use for water planners in the developing world. A first-order Markov occurrence model with a mixed exponential amount model is selected as the best option for unconditioned Markov models. However, there is no clear advantage in selecting Markov models over the LARS-WG model for DRWH in West Africa, with each model having distinct strengths and weaknesses. A multi-model approach is used in assessing DRWH in the region to illustrate the variability associated with the rainfall models. It is clear DRWH can be successfully used as a water enhancement mechanism in West Africa for certain times of the year. A 200 L drum storage capacity could potentially optimize these simple, small roof area systems for many locations in the region.

  4. Radionuclide interception and loss processes in vegetation

    International Nuclear Information System (INIS)

    Proehl, G.; Hoffman, F.O.

    1996-01-01

    Data available since the Chernobyl accident have strengthened the view that the transfer of radionuclides from air to vegetation is a primary area of uncertainty in the estimation of the contamination of food chains leading to human exposure. The processes affecting the overall transfer from air to vegetation involve wet and dry deposition, interception and initial retention, and post-deposition retention of radioactive substances by vegetation. During the growing season, the time-integrated concentrations of radionuclides on vegetation in the first few months after initial deposition are dominated by the direct foliar interception of deposited material. Chapter 2 contains a review of data for modelling the direct foliar interception and initial retention of radioactivity deposited by dry and wet processes, together with data on the factors affecting post-deposition retention of radioactivity on the vegetation. 82 refs, 9 figs, 11 tabs

  5. Hydrological Modelling Using a Rainfall Simulator over an Experimental Hillslope Plot

    Directory of Open Access Journals (Sweden)

    Arpit Chouksey

    2017-03-01

    Full Text Available Hydrological processes are complex to compute in hilly areas when compared to plain areas. The governing processes behind runoff generation on hillslopes are subsurface storm flow, saturation excess flow, overland flow, return flow and pipe storage. The simulations of the above processes in the soil matrix require detailed hillslope hydrological modelling. In the present study, a hillslope experimental plot has been designed to study the runoff generation processes on the plot scale. The setup is designed keeping in view the natural hillslope conditions prevailing in the Northwestern Himalayas, India where high intensity rainfall events occur frequently. A rainfall simulator was installed over the experimental hillslope plot to generate rainfall with an intensity of 100 mm/h, which represents the dominating rainfall intensity range in the region. Soil moisture sensors were also installed at variable depths from 100 to 1000 mm at different locations of the plot to observe the soil moisture regime. From the experimental observations it was found that once the soil is saturated, it remains at field capacity for the next 24–36 h. Such antecedent moisture conditions are most favorable for the generation of rapid stormflow from hillslopes. A dye infiltration test was performed on the undisturbed soil column to observe the macropore fraction variability over the vegetated hillslopes. The estimated macropore fractions are used as essential input for the hillslope hydrological model. The main objective of the present study was to develop and test a method for estimating runoff responses from natural rainfall over hillslopes of the Northwestern Himalayas using a portable rainfall simulator. Using the experimental data and the developed conceptual model, the overland flow and the subsurface flow through a macropore-dominated area have been estimated/analyzed. The surface and subsurface runoff estimated using the developed hillslope hydrological model

  6. Effect of raingage density, position and interpolation on rainfall-discharge modelling

    Science.gov (United States)

    Ly, S.; Sohier, C.; Charles, C.; Degré, A.

    2012-04-01

    Precipitation traditionally observed using raingages or weather stations, is one of the main parameters that have direct impact on runoff production. Precipitation data require a preliminary spatial interpolation prior to hydrological modeling. The accuracy of modelling result depends on the accuracy of the interpolated spatial rainfall which differs according to different interpolation methods. The accuracy of the interpolated spatial rainfall is usually determined by cross-validation method. The objective of this study is to assess the different interpolation methods of daily rainfall at the watershed scale through hydrological modelling and to explore the best methods that provide a good long term simulation. Four versions of geostatistics: Ordinary Kriging (ORK), Universal Kriging (UNK), Kriging with External Dridft (KED) and Ordinary Cokriging (OCK) and two types of deterministic methods: Thiessen polygon (THI) and Inverse Distance Weighting (IDW) are used to produce 30-year daily rainfall inputs for a distributed physically-based hydrological model (EPIC-GRID). This work is conducted in the Ourthe and Ambleve nested catchments, located in the Ardennes hilly landscape in the Walloon region, Belgium. The total catchment area is 2908 km2, lies between 67 and 693 m in elevation. The multivariate geostatistics (KED and OCK) are also used by incorporating elevation as external data to improve the rainfall prediction. This work also aims at analysing the effect of different raingage densities and position used for interpolation, on the stream flow modelled to get insight in terms of the capability and limitation of the geostatistical methods. The number of raingage varies from 70, 60, 50, 40, 30, 20, 8 to 4 stations located in and surrounding the catchment area. In the latter case, we try to use different positions: around the catchment and only a part of the catchment. The result shows that the simple method like THI fails to capture the rainfall and to produce

  7. A Physically—Based Geometry Model for Transport Distance Estimation of Rainfall-Eroded Soil Sediment

    Directory of Open Access Journals (Sweden)

    Qian-Gui Zhang

    2016-01-01

    Full Text Available Estimations of rainfall-induced soil erosion are mostly derived from the weight of sediment measured in natural runoff. The transport distance of eroded soil is important for evaluating landscape evolution but is difficult to estimate, mainly because it cannot be linked directly to the eroded sediment weight. The volume of eroded soil is easier to calculate visually using popular imaging tools, which can aid in estimating the transport distance of eroded soil through geometry relationships. In this study, we present a straightforward geometry model to predict the maximum sediment transport distance incurred by rainfall events of various intensity and duration. In order to verify our geometry prediction model, a series of experiments are reported in the form of a sediment volume. The results show that cumulative rainfall has a linear relationship with the total volume of eroded soil. The geometry model can accurately estimate the maximum transport distance of eroded soil by cumulative rainfall, with a low root-mean-square error (4.7–4.8 and a strong linear correlation (0.74–0.86.

  8. Using satellite-based rainfall estimates for streamflow modelling: Bagmati Basin

    Science.gov (United States)

    Shrestha, M.S.; Artan, Guleid A.; Bajracharya, S.R.; Sharma, R. R.

    2008-01-01

    In this study, we have described a hydrologic modelling system that uses satellite-based rainfall estimates and weather forecast data for the Bagmati River Basin of Nepal. The hydrologic model described is the US Geological Survey (USGS) Geospatial Stream Flow Model (GeoSFM). The GeoSFM is a spatially semidistributed, physically based hydrologic model. We have used the GeoSFM to estimate the streamflow of the Bagmati Basin at Pandhera Dovan hydrometric station. To determine the hydrologic connectivity, we have used the USGS Hydro1k DEM dataset. The model was forced by daily estimates of rainfall and evapotranspiration derived from weather model data. The rainfall estimates used for the modelling are those produced by the National Oceanic and Atmospheric Administration Climate Prediction Centre and observed at ground rain gauge stations. The model parameters were estimated from globally available soil and land cover datasets – the Digital Soil Map of the World by FAO and the USGS Global Land Cover dataset. The model predicted the daily streamflow at Pandhera Dovan gauging station. The comparison of the simulated and observed flows at Pandhera Dovan showed that the GeoSFM model performed well in simulating the flows of the Bagmati Basin.

  9. Regionalization of the Modified Bartlett-Lewis Rectangular Pulse Stochastic Rainfall Model

    OpenAIRE

    Dongkyun Kim; Francisco Olivera; Huidae Cho; Scott A. Socolofsky

    2013-01-01

    Parameters of the Modified Bartlett-Lewis Rectangular Pulse (MBLRP) stochastic rainfall simulation model were regionalized across the contiguous United States. Three thousand four hundred forty-four National Climate Data Center (NCDC) rain gauges were used to obtain spatial and seasonal patterns of the model parameters. The MBLRP model was calibrated to minimize the discrepancy between the precipitation depth statistics between the observed and MBLRP-generated precipitation time series. These...

  10. Simulation of infiltration and redistribution of intense rainfall using Land Surface Models

    Science.gov (United States)

    Mueller, Anna; Verhoef, Anne; Cloke, Hannah

    2016-04-01

    Flooding from intense rainfall (FFIR) can cause widespread damage and disruption. Numerical Weather Prediction (NWP) models provide distributed information about atmospheric conditions, such as precipitation, that can lead to a flooding event. Short duration, high intensity rainfall events are generally poorly predicted by NWP models, because of the high spatiotemporal resolution required and because of the way the convective rainfall is described in the model. The resolution of NWP models is ever increasing. Better understanding of complex hydrological processes and the effect of scale is important in order to improve the prediction of magnitude and duration of such events, in the context of disaster management. Working as part of the NERC SINATRA project, we evaluated how the Land Surface Model (LSM) components of NWP models cope with high intensity rainfall input and subsequent infiltration problems. Both in terms of the amount of water infiltrated in the soil store, as well as the timing and the amount of surface and subsurface runoff generated. The models investigated are SWAP (Soil Water Air Plant, Alterra, the Netherlands, van Dam 1997), JULES (Joint UK Land Environment Simulator a component of Unified Model in UK Met Office, Best et al. 2011) and CHTESSEL (Carbon and Hydrology- Tiled ECMWF Scheme for Surface Exchanges over Land, Balsamo et al. 2009) We analysed the numerical aspects arising from discontinuities (or sharp gradients) in forcing and/or the model solution. These types of infiltration configurations were tested in the laboratory (Vachaud 1971), for some there are semi-analytical solutions (Philip 1957, Parlange 1972, Vanderborght 2005) or reference numerical solutions (Haverkamp 1977, van Dam 2000, Vanderborght 2005). The maximum infiltration by the surface, Imax, is in general dependent on atmospheric conditions, surface type, soil type, soil moisture content θ, and surface orographic factor σ. The models used differ in their approach to

  11. Mathematical model for the contribution of individual organs to non-zero y-intercepts in single and multi-compartment linear models of whole-body energy expenditure.

    Science.gov (United States)

    Kaiyala, Karl J

    2014-01-01

    Mathematical models for the dependence of energy expenditure (EE) on body mass and composition are essential tools in metabolic phenotyping. EE scales over broad ranges of body mass as a non-linear allometric function. When considered within restricted ranges of body mass, however, allometric EE curves exhibit 'local linearity.' Indeed, modern EE analysis makes extensive use of linear models. Such models typically involve one or two body mass compartments (e.g., fat free mass and fat mass). Importantly, linear EE models typically involve a non-zero (usually positive) y-intercept term of uncertain origin, a recurring theme in discussions of EE analysis and a source of confounding in traditional ratio-based EE normalization. Emerging linear model approaches quantify whole-body resting EE (REE) in terms of individual organ masses (e.g., liver, kidneys, heart, brain). Proponents of individual organ REE modeling hypothesize that multi-organ linear models may eliminate non-zero y-intercepts. This could have advantages in adjusting REE for body mass and composition. Studies reveal that individual organ REE is an allometric function of total body mass. I exploit first-order Taylor linearization of individual organ REEs to model the manner in which individual organs contribute to whole-body REE and to the non-zero y-intercept in linear REE models. The model predicts that REE analysis at the individual organ-tissue level will not eliminate intercept terms. I demonstrate that the parameters of a linear EE equation can be transformed into the parameters of the underlying 'latent' allometric equation. This permits estimates of the allometric scaling of EE in a diverse variety of physiological states that are not represented in the allometric EE literature but are well represented by published linear EE analyses.

  12. Application of random number generators in genetic algorithms to improve rainfall-runoff modelling

    Science.gov (United States)

    Chlumecký, Martin; Buchtele, Josef; Richta, Karel

    2017-10-01

    The efficient calibration of rainfall-runoff models is a difficult issue, even for experienced hydrologists. Therefore, fast and high-quality model calibration is a valuable improvement. This paper describes a novel methodology and software for the optimisation of a rainfall-runoff modelling using a genetic algorithm (GA) with a newly prepared concept of a random number generator (HRNG), which is the core of the optimisation. The GA estimates model parameters using evolutionary principles, which requires a quality number generator. The new HRNG generates random numbers based on hydrological information and it provides better numbers compared to pure software generators. The GA enhances the model calibration very well and the goal is to optimise the calibration of the model with a minimum of user interaction. This article focuses on improving the internal structure of the GA, which is shielded from the user. The results that we obtained indicate that the HRNG provides a stable trend in the output quality of the model, despite various configurations of the GA. In contrast to previous research, the HRNG speeds up the calibration of the model and offers an improvement of rainfall-runoff modelling.

  13. Ensemble flood simulation for a small dam catchment in Japan using 10 and 2 km resolution nonhydrostatic model rainfalls

    Science.gov (United States)

    Kobayashi, Kenichiro; Otsuka, Shigenori; Apip; Saito, Kazuo

    2016-08-01

    This paper presents a study on short-term ensemble flood forecasting specifically for small dam catchments in Japan. Numerical ensemble simulations of rainfall from the Japan Meteorological Agency nonhydrostatic model (JMA-NHM) are used as the input data to a rainfall-runoff model for predicting river discharge into a dam. The ensemble weather simulations use a conventional 10 km and a high-resolution 2 km spatial resolutions. A distributed rainfall-runoff model is constructed for the Kasahori dam catchment (approx. 70 km2) and applied with the ensemble rainfalls. The results show that the hourly maximum and cumulative catchment-average rainfalls of the 2 km resolution JMA-NHM ensemble simulation are more appropriate than the 10 km resolution rainfalls. All the simulated inflows based on the 2 and 10 km rainfalls become larger than the flood discharge of 140 m3 s-1, a threshold value for flood control. The inflows with the 10 km resolution ensemble rainfall are all considerably smaller than the observations, while at least one simulated discharge out of 11 ensemble members with the 2 km resolution rainfalls reproduces the first peak of the inflow at the Kasahori dam with similar amplitude to observations, although there are spatiotemporal lags between simulation and observation. To take positional lags into account of the ensemble discharge simulation, the rainfall distribution in each ensemble member is shifted so that the catchment-averaged cumulative rainfall of the Kasahori dam maximizes. The runoff simulation with the position-shifted rainfalls shows much better results than the original ensemble discharge simulations.

  14. Modelling the complex dynamics of vegetation, livestock and rainfall ...

    African Journals Online (AJOL)

    Open Access DOWNLOAD FULL TEXT ... In this paper, we present mathematical models that incorporate ideas from complex systems theory to integrate several strands of rangeland theory in a hierarchical framework. ... Keywords: catastrophe theory; complexity theory; disequilibrium; hysteresis; moving attractors

  15. Application of the rainfall infiltration breakthrough (RIB) model for ...

    African Journals Online (AJOL)

    2012-05-23

    May 23, 2012 ... In this paper, the physical meaning of parameters in the CRD and previous ... ity; the utility of the RIB model for application in different climatic areas under ...... TMG Aquifer feasibility study and pilot project ecological and.

  16. Seasonal variability of interception evaporation from the canopy of a mixed deciduous forest

    DEFF Research Database (Denmark)

    Herbst, Mathias; Rosier, Paul T.W.; McNeil, David D.

    2008-01-01

    and the different aerodynamic properties of the canopy. Together with the lower average rainfall rate this counterbalanced the reduced storage capacity of the leafless canopy and maintained a relatively high interception loss throughout the year being 29% of the gross rainfall in the leafed period and 20...

  17. Improving rainfall representation for large-scale hydrological modelling of tropical mountain basins

    Science.gov (United States)

    Zulkafli, Zed; Buytaert, Wouter; Onof, Christian; Lavado, Waldo; Guyot, Jean-Loup

    2013-04-01

    Errors in the forcing data are sometimes overlooked in hydrological studies even when they could be the most important source of uncertainty. The latter particularly holds true in tropical countries with short historical records of rainfall monitoring and remote areas with sparse rain gauge network. In such instances, alternative data such as the remotely sensed precipitation from the TRMM (Tropical Rainfall Measuring Mission) satellite have been used. These provide a good spatial representation of rainfall processes but have been established in the literature to contain volumetric biases that may impair the results of hydrological modelling or worse, are compensated during model calibration. In this study, we analysed precipitation time series from the TMPA (TRMM Multiple Precipitation Algorithm, version 6) against measurements from over 300 gauges in the Andes and Amazon regions of Peru and Ecuador. We found moderately good monthly correlation between the pixel and gauge pairs but a severe underestimation of rainfall amounts and wet days. The discrepancy between the time series pairs is particularly visible over the east side of the Andes and may be attributed to localized and orographic-driven high intensity rainfall, which the satellite product may have limited skills at capturing due to technical and scale issues. This consequently results in a low bias in the simulated streamflow volumes further downstream. In comparison, with the recently released TMPA, version 7, the biases reduce. This work further explores several approaches to merge the two sources of rainfall measurements, each of a different spatial and temporal support, with the objective of improving the representation of rainfall in hydrological simulations. The methods used are (1) mean bias correction (2) data assimilation using Kalman filter Bayesian updating. The results are evaluated by means of (1) a comparison of runoff ratios (the ratio of the total runoff and the total precipitation over an

  18. Convective-stratiform rainfall separation of Typhoon Fitow (2013: A 3D WRF modeling study

    Directory of Open Access Journals (Sweden)

    Huiyan Xu

    2018-01-01

    Full Text Available Surface precipitation budget equation in a three-dimensional (3D WRF model framework is derived. By applying the convective-stratiform partition method to the surface precipitation budget equation in the 3D model, this study separated convective and stratiform rainfall of typhoon Fitow (2013. The separations are further verified by examining statistics of vertical velocity, surface precipitation budget, and cloud microphysical budget. Results show that water vapor convergence moistens local atmosphere and offsets hydrometeor divergence, and producing convective rainfall, while hydrometeor convergence primarily supports stratiform rainfall, since water vapor divergence and local atmospheric drying generally cancelled out. Mean ascending motions are prevailing in the entire troposphere in the convective region, whereas mean descending motions occur below 5 km and mean ascending motions occur above in the stratiform region. The frequency distribution of vertical velocity shows vertical velocity has wide distribution with the maximum values up to 13 m s-1 in the convective regions, whereas it has narrow distribution with absolute values confined within 7 m s-1 in the stratiform region. Liquid cloud microphysics is dominant in convective regions and ice cloud microphysics is dominant in stratiform regions. These indicate that the statistics results are generally consistent with the corresponding physical characteristics of the convective-stratiform rainfall structures generalized by previous studies.

  19. Rainfall and crop modeling-based water stress assessment for rainfed maize cultivation in peninsular India

    Science.gov (United States)

    Manivasagam, V. S.; Nagarajan, R.

    2018-04-01

    Water stress due to uneven rainfall distribution causes a significant impact on the agricultural production of monsoon-dependent peninsular India. In the present study, water stress assessment for rainfed maize crop is carried out for kharif (June-October) and rabi (October-February) cropping seasons which coincide with two major Indian monsoons. Rainfall analysis (1976-2010) shows that the kharif season receives sufficient weekly rainfall (28 ± 32 mm) during 26th-39th standard meteorological weeks (SMWs) from southwest monsoon, whereas the rabi season experiences a major portion of its weekly rainfall due to northeast monsoon between the 42nd and 51st SMW (31 ± 42 mm). The later weeks experience minimal rainfall (5.5 ± 15 mm) and thus expose the late sown maize crops to a severe water stress during its maturity stage. Wet and dry spell analyses reveal a substantial increase in the rainfall intensity over the last few decades. However, the distribution of rainfall shows a striking decrease in the number of wet spells, with prolonged dry spells in both seasons. Weekly rainfall classification shows that the flowering and maturity stages of kharif maize (33rd-39th SMWs) can suffer around 30-40% of the total water stress. In the case of rabi maize, the analysis reveals that a shift in the sowing time from the existing 42nd SMW (16-22 October) to the 40th SMW (1-7 October) can avoid terminal water stress. Further, AquaCrop modeling results show that one or two minimal irrigations during the flowering and maturity stages (33rd-39th SMWs) of kharif maize positively avoid the mild water stress exposure. Similarly, rabi maize requires an additional two or three lifesaving irrigations during its flowering and maturity stages (48th-53rd SMWs) to improve productivity. Effective crop planning with appropriate sowing time, short duration crop, and high yielding drought-resistant varieties will allow for better utilization of the monsoon rain, thus reducing water stress with

  20. Analysis of the sensitivity to rainfall spatio-temporal variability of an operational urban rainfall-runoff model in a multifractal framework

    Science.gov (United States)

    Gires, A.; Tchiguirinskaia, I.; Schertzer, D. J.; Lovejoy, S.

    2011-12-01

    In large urban areas, storm water management is a challenge with enlarging impervious areas. Many cities have implemented real time control (RTC) of their urban drainage system to either reduce overflow or limit urban contamination. A basic component of RTC is hydraulic/hydrologic model. In this paper we use the multifractal framework to suggest an innovative way to test the sensitivity of such a model to the spatio-temporal variability of its rainfall input. Indeed the rainfall variability is often neglected in urban context, being considered as a non-relevant issue at the scales involve. Our results show that on the contrary the rainfall variability should be taken into account. Universal multifractals (UM) rely on the concept of multiplicative cascade and are a standard tool to analyze and simulate with a reduced number of parameters geophysical processes that are extremely variable over a wide range of scales. This study is conducted on a 3 400 ha urban area located in Seine-Saint-Denis, in the North of Paris (France). We use the operational semi-distributed model that was calibrated by the local authority (Direction Eau et Assainnissement du 93) that is in charge of urban drainage. The rainfall data comes from the C-Band radar of Trappes operated by Météo-France. The rainfall event of February 9th, 2009 was used. A stochastic ensemble approach was implemented to quantify the uncertainty on discharge associated to the rainfall variability occurring at scales smaller than 1 km x 1 km x 5 min that is usually available with C-band radar networks. An analysis of the quantiles of the simulated peak flow showed that the uncertainty exceeds 20 % for upstream links. To evaluate a potential gain from a direct use of the rainfall data available at the resolution of X-band radar, we performed similar analysis of the rainfall fields of the degraded resolution of 9 km x 9 km x 20 min. The results show a clear decrease in uncertainty when the original resolution of C

  1. Derivation of flood frequency curves in poorly gauged Mediterranean catchments using a simple stochastic hydrological rainfall-runoff model

    Science.gov (United States)

    Aronica, G. T.; Candela, A.

    2007-12-01

    SummaryIn this paper a Monte Carlo procedure for deriving frequency distributions of peak flows using a semi-distributed stochastic rainfall-runoff model is presented. The rainfall-runoff model here used is very simple one, with a limited number of parameters and practically does not require any calibration, resulting in a robust tool for those catchments which are partially or poorly gauged. The procedure is based on three modules: a stochastic rainfall generator module, a hydrologic loss module and a flood routing module. In the rainfall generator module the rainfall storm, i.e. the maximum rainfall depth for a fixed duration, is assumed to follow the two components extreme value (TCEV) distribution whose parameters have been estimated at regional scale for Sicily. The catchment response has been modelled by using the Soil Conservation Service-Curve Number (SCS-CN) method, in a semi-distributed form, for the transformation of total rainfall to effective rainfall and simple form of IUH for the flood routing. Here, SCS-CN method is implemented in probabilistic form with respect to prior-to-storm conditions, allowing to relax the classical iso-frequency assumption between rainfall and peak flow. The procedure is tested on six practical case studies where synthetic FFC (flood frequency curve) were obtained starting from model variables distributions by simulating 5000 flood events combining 5000 values of total rainfall depth for the storm duration and AMC (antecedent moisture conditions) conditions. The application of this procedure showed how Monte Carlo simulation technique can reproduce the observed flood frequency curves with reasonable accuracy over a wide range of return periods using a simple and parsimonious approach, limited data input and without any calibration of the rainfall-runoff model.

  2. A regional and nonstationary model for partial duration series of extreme rainfall

    DEFF Research Database (Denmark)

    Gregersen, Ida Bülow; Madsen, Henrik; Rosbjerg, Dan

    2017-01-01

    as the explanatory variables in the regional and temporal domain, respectively. Further analysis of partial duration series with nonstationary and regional thresholds shows that the mean exceedances also exhibit a significant variation in space and time for some rainfall durations, while the shape parameter is found...... of extreme rainfall. The framework is built on a partial duration series approach with a nonstationary, regional threshold value. The model is based on generalized linear regression solved by generalized estimation equations. It allows a spatial correlation between the stations in the network and accounts...... furthermore for variable observation periods at each station and in each year. Marginal regional and temporal regression models solved by generalized least squares are used to validate and discuss the results of the full spatiotemporal model. The model is applied on data from a large Danish rain gauge network...

  3. Modelling the effects of spatial and temporal resolution of rainfall and basin model on extreme river discharge

    NARCIS (Netherlands)

    Booij, Martijn J.

    2002-01-01

    Important characteristics of an appropriate river basin model, intended to study the effect of climate change on basin response, are the spatial and temporal resolution of the model and the rainfall input. The effects of input and model resolution on extreme discharge of a large river basin are

  4. Event-based model diagnosis of rainfall-runoff model structures

    International Nuclear Information System (INIS)

    Stanzel, P.

    2012-01-01

    The objective of this research is a comparative evaluation of different rainfall-runoff model structures. Comparative model diagnostics facilitate the assessment of strengths and weaknesses of each model. The application of multiple models allows an analysis of simulation uncertainties arising from the selection of model structure, as compared with effects of uncertain parameters and precipitation input. Four different model structures, including conceptual and physically based approaches, are compared. In addition to runoff simulations, results for soil moisture and the runoff components of overland flow, interflow and base flow are analysed. Catchment runoff is simulated satisfactorily by all four model structures and shows only minor differences. Systematic deviations from runoff observations provide insight into model structural deficiencies. While physically based model structures capture some single runoff events better, they do not generally outperform conceptual model structures. Contributions to uncertainty in runoff simulations stemming from the choice of model structure show similar dimensions to those arising from parameter selection and the representation of precipitation input. Variations in precipitation mainly affect the general level and peaks of runoff, while different model structures lead to different simulated runoff dynamics. Large differences between the four analysed models are detected for simulations of soil moisture and, even more pronounced, runoff components. Soil moisture changes are more dynamical in the physically based model structures, which is in better agreement with observations. Streamflow contributions of overland flow are considerably lower in these models than in the more conceptual approaches. Observations of runoff components are rarely made and are not available in this study, but are shown to have high potential for an effective selection of appropriate model structures (author) [de

  5. Influence of Superparameterization and a Higher-Order Turbulence Closure on Rainfall Bias Over Amazonia in Community Atmosphere Model Version 5: How Parameterization Changes Rainfall

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Kai [Jackson School of Geosciences, University of Texas at Austin, Austin TX USA; Fu, Rong [Jackson School of Geosciences, University of Texas at Austin, Austin TX USA; Department of Atmospheric and Oceanic Sciences, University of California, Los Angeles CA USA; Shaikh, Muhammad J. [Jackson School of Geosciences, University of Texas at Austin, Austin TX USA; Ghan, Steven [Pacific Northwest National Laboratory, Richland WA USA; Wang, Minghuai [Institute for Climate and Global Change Research and School of Atmospheric Sciences, Nanjing University, Nanjing China; Collaborative Innovation Center of Climate Change, Nanjing China; Leung, L. Ruby [Pacific Northwest National Laboratory, Richland WA USA; Dickinson, Robert E. [Jackson School of Geosciences, University of Texas at Austin, Austin TX USA; Marengo, Jose [Centro Nacional de Monitoramento e Alertas aos Desastres Naturais, São Jose dos Campos Brazil

    2017-09-21

    We evaluate the Community Atmosphere Model Version 5 (CAM5) with a higher-order turbulence closure scheme, named Cloud Layers Unified By Binomials (CLUBB), and a Multiscale Modeling Framework (MMF) with two different microphysics configurations to investigate their influences on rainfall simulations over Southern Amazonia. The two different microphysics configurations in MMF are the one-moment cloud microphysics without aerosol treatment (SAM1MOM) and two-moment cloud microphysics coupled with aerosol treatment (SAM2MOM). Results show that both MMF-SAM2MOM and CLUBB effectively reduce the low biases of rainfall, mainly during the wet season. The CLUBB reduces low biases of humidity in the lower troposphere with further reduced shallow clouds. The latter enables more surface solar flux, leading to stronger convection and more rainfall. MMF, especially MMF-SAM2MOM, unstablizes the atmosphere with more moisture and higher atmospheric temperatures in the atmospheric boundary layer, allowing the growth of more extreme convection and further generating more deep convection. MMF-SAM2MOM significantly increases rainfall in the afternoon, but it does not reduce the early bias of the diurnal rainfall peak; LUBB, on the other hand, delays the afternoon peak time and produces more precipitation in the early morning, due to more realistic gradual transition between shallow and deep convection. MMF appears to be able to realistically capture the observed increase of relative humidity prior to deep convection, especially with its two-moment configuration. In contrast, in CAM5 and CAM5 with CLUBB, occurrence of deep convection in these models appears to be a result of stronger heating rather than higher relative humidity.

  6. Arima modelling of annual rainfalls in the Bregalnica River basin

    OpenAIRE

    Jovanovski, Vlatko; Delipetrov, Todor

    2007-01-01

    Changes in the hydrological characteristics have an impact on the environment. The reasons for the impact in the Bregalnica river basin are heavy rains and long droughts. Monitoring the undenstanding of hydrological impacts may provide useful assessment ingand forecast in several fields. This paper analysis hydrological processes, and offeres data processing of the monitor with ARIMA Modelling in STATISTICA packet like good techniques for estimation forecast of the hydrological caracterist...

  7. An architectural analysis of the elongation of field-grown sunflower root systems. Elements for modelling the effects of temperature and intercepted radiation

    International Nuclear Information System (INIS)

    Aguirrezabal, L.A.N.; Tardieu, F.

    1996-01-01

    The effects of photosynthetic photon flux density (PPFD) and soil temperature on root system elongation rate have been analysed by using an architectural framework. Root elongation rate was analysed by considering three terms, (i) the branch appearance rate, (ii) the individual elongation rates of the taproot and branches and (iii) the proportion of branches which stop elongating. Large ranges of PPFD and soil temperature were obtained in a series of field and growth chamber experiments. In the field, the growth of root systems experiencing day-to-day natural fluctuation of PPFD and temperature was followed, and some of the plants under study were shaded. In the growth chamber, plants experienced contrasting and constant PPFDs and root temperatures. The direct effect of apex temperature on individual root elongation rate was surprisingly low in the range 13–25°C, except for the first days after germination. Root elongation rate was essentially related to intercepted PPFD and to distance to the source, both in the field and in the growth chamber. Branch appearance rate substantially varied among days and environmental conditions. It was essentially linked to taproot elongation rate, as the profile of branch density along the taproot was quite stable. The length of the taproot segment carrying newly appeared branches on a given day was equal to taproot elongation on this day, plus a 'buffering term' which transiently increased if taproot elongation rate slowed down. The proportion of branches which stopped elongating a short distance from the taproot ranged from 50–80% and was, therefore, a major architectural variable, although it is not taken into account in current architectural models. A set of equations accounting for the variabilities in elongation rate, branch appearance rate and proportion of branches which stop elongating, as a function of intercepted PPFD and apex temperature is proposed. These equations apply for both field and growth

  8. Assessment of initial soil moisture conditions for event-based rainfall-runoff modelling

    OpenAIRE

    Tramblay, Yves; Bouvier, Christophe; Martin, C.; Didon-Lescot, J. F.; Todorovik, D.; Domergue, J. M.

    2010-01-01

    Flash floods are the most destructive natural hazards that occur in the Mediterranean region. Rainfall-runoff models can be very useful for flash flood forecasting and prediction. Event-based models are very popular for operational purposes, but there is a need to reduce the uncertainties related to the initial moisture conditions estimation prior to a flood event. This paper aims to compare several soil moisture indicators: local Time Domain Reflectometry (TDR) measurements of soil moisture,...

  9. Desert locust populations, rainfall and climate change: insights from phenomenological models using gridded monthly data

    OpenAIRE

    Tratalos, Jamie A.; Cheke, Robert A.; Healey, Richard G.; Stenseth, Nils Chr.

    2010-01-01

    Using autocorrelation analysis and autoregressive integrated moving average (ARIMA)modelling, we analysed a time series of the monthly number of 1° grid squares infested with desert locust Schistocerca gregaria swarms throughout the geographical range of the species from 1930–1987. Statistically significant first- and higher-order autocorrelations were found in the series. Although endogenous components captured much of the variance, adding rainfall data improved endogenous ARIMA models and r...

  10. Establish susceptibility and risk assessment models for rainfall-induced landslide: A case in Central Taiwan

    Science.gov (United States)

    Wu, Chunhung; Huang, Jyuntai

    2017-04-01

    Most of the landslide cases in Taiwan were triggered by rainfall or earthquake events. The heavy rainfall in the typhoon seasons, from June to October, causes the landslide hazard more serious. Renai Towhship is of the most large landslide cases after 2009 Typhoon Morakot (from Aug. 5 to Aug. 10, 2009) in Taiwan. Around 2,744 landslides cases with the total landslide area of 21.5 km2 (landslide ratio =1.8%), including 26 large landslide cases, induced after 2009 Typhoon Morakot in Renai Towhship. The area of each large landslides case is more than 0.1 km2, and the area of the largest case is around 0.96 km2. 58% of large landslide cases locate in the area with metamorphosed sandstone. The mean slope of 26 large landslide cases ranges from 15 degree to 56 degree, and the accumulated rainfall during 2009 Typhoon Morakot ranges from 530 mm to 937 mm. Three methods, including frequency ratio method (abbreviated as FR), weights of evidence method (abbreviated as WOE), and logistic regression method (abbreviated as LR), are used in this study to establish the landslides susceptibility in the Renai Township, Nantou County, Taiwan. Eight landslide related-factors, including elevation, slope, aspect, geology, land use, distance to drainage, distance to fault, accumulation rainfall during 2009 Typhoon Morakot, are used to establish the landslide susceptibility models in this study. The landslide inventory after 2009 Typhoon Morakot is also used to test the model performance in this study. The mean accumulated rainfall in Renai Township during 2009 typhoon Morakot was around 735 mm with the maximum 1-hr, 3-hrs, and 6-hrs rainfall intensity of 44 mm/1-hr, 106 mm/3-hrs and 204 mm/6-hrs, respectively. The range of original susceptibility values established by three methods are 4.0 to 20.9 for FR, -33.8 to -16.1 for WOE, and -41.7 to 5.7 for LR, and the mean landslide susceptibility value are 8.0, -24.6 and 0.38, respectively. The AUC values are 0.815 for FR, 0.816 for WOE, and 0

  11. Estimation and prediction of maximum daily rainfall at Sagar Island using best fit probability models

    Science.gov (United States)

    Mandal, S.; Choudhury, B. U.

    2015-07-01

    Sagar Island, setting on the continental shelf of Bay of Bengal, is one of the most vulnerable deltas to the occurrence of extreme rainfall-driven climatic hazards. Information on probability of occurrence of maximum daily rainfall will be useful in devising risk management for sustaining rainfed agrarian economy vis-a-vis food and livelihood security. Using six probability distribution models and long-term (1982-2010) daily rainfall data, we studied the probability of occurrence of annual, seasonal and monthly maximum daily rainfall (MDR) in the island. To select the best fit distribution models for annual, seasonal and monthly time series based on maximum rank with minimum value of test statistics, three statistical goodness of fit tests, viz. Kolmogorove-Smirnov test (K-S), Anderson Darling test ( A 2 ) and Chi-Square test ( X 2) were employed. The fourth probability distribution was identified from the highest overall score obtained from the three goodness of fit tests. Results revealed that normal probability distribution was best fitted for annual, post-monsoon and summer seasons MDR, while Lognormal, Weibull and Pearson 5 were best fitted for pre-monsoon, monsoon and winter seasons, respectively. The estimated annual MDR were 50, 69, 86, 106 and 114 mm for return periods of 2, 5, 10, 20 and 25 years, respectively. The probability of getting an annual MDR of >50, >100, >150, >200 and >250 mm were estimated as 99, 85, 40, 12 and 03 % level of exceedance, respectively. The monsoon, summer and winter seasons exhibited comparatively higher probabilities (78 to 85 %) for MDR of >100 mm and moderate probabilities (37 to 46 %) for >150 mm. For different recurrence intervals, the percent probability of MDR varied widely across intra- and inter-annual periods. In the island, rainfall anomaly can pose a climatic threat to the sustainability of agricultural production and thus needs adequate adaptation and mitigation measures.

  12. Satellite-based Flood Modeling Using TRMM-based Rainfall Products

    Directory of Open Access Journals (Sweden)

    Greg Easson

    2007-12-01

    Full Text Available Increasingly available and a virtually uninterrupted supply of satellite-estimatedrainfall data is gradually becoming a cost-effective source of input for flood predictionunder a variety of circumstances. However, most real-time and quasi-global satelliterainfall products are currently available at spatial scales ranging from 0.25o to 0.50o andhence, are considered somewhat coarse for dynamic hydrologic modeling of basin-scaleflood events. This study assesses the question: what are the hydrologic implications ofuncertainty of satellite rainfall data at the coarse scale? We investigated this question onthe 970 km2 Upper Cumberland river basin of Kentucky. The satellite rainfall productassessed was NASA’s Tropical Rainfall Measuring Mission (TRMM Multi-satellitePrecipitation Analysis (TMPA product called 3B41RT that is available in pseudo real timewith a latency of 6-10 hours. We observed that bias adjustment of satellite rainfall data canimprove application in flood prediction to some extent with the trade-off of more falsealarms in peak flow. However, a more rational and regime-based adjustment procedureneeds to be identified before the use of satellite data can be institutionalized among floodmodelers.

  13. Sampling design optimisation for rainfall prediction using a non-stationary geostatistical model

    Science.gov (United States)

    Wadoux, Alexandre M. J.-C.; Brus, Dick J.; Rico-Ramirez, Miguel A.; Heuvelink, Gerard B. M.

    2017-09-01

    The accuracy of spatial predictions of rainfall by merging rain-gauge and radar data is partly determined by the sampling design of the rain-gauge network. Optimising the locations of the rain-gauges may increase the accuracy of the predictions. Existing spatial sampling design optimisation methods are based on minimisation of the spatially averaged prediction error variance under the assumption of intrinsic stationarity. Over the past years, substantial progress has been made to deal with non-stationary spatial processes in kriging. Various well-documented geostatistical models relax the assumption of stationarity in the mean, while recent studies show the importance of considering non-stationarity in the variance for environmental processes occurring in complex landscapes. We optimised the sampling locations of rain-gauges using an extension of the Kriging with External Drift (KED) model for prediction of rainfall fields. The model incorporates both non-stationarity in the mean and in the variance, which are modelled as functions of external covariates such as radar imagery, distance to radar station and radar beam blockage. Spatial predictions are made repeatedly over time, each time recalibrating the model. The space-time averaged KED variance was minimised by Spatial Simulated Annealing (SSA). The methodology was tested using a case study predicting daily rainfall in the north of England for a one-year period. Results show that (i) the proposed non-stationary variance model outperforms the stationary variance model, and (ii) a small but significant decrease of the rainfall prediction error variance is obtained with the optimised rain-gauge network. In particular, it pays off to place rain-gauges at locations where the radar imagery is inaccurate, while keeping the distribution over the study area sufficiently uniform.

  14. Estimating methane emissions from landfills based on rainfall, ambient temperature, and waste composition: The CLEEN model.

    Science.gov (United States)

    Karanjekar, Richa V; Bhatt, Arpita; Altouqui, Said; Jangikhatoonabad, Neda; Durai, Vennila; Sattler, Melanie L; Hossain, M D Sahadat; Chen, Victoria

    2015-12-01

    Accurately estimating landfill methane emissions is important for quantifying a landfill's greenhouse gas emissions and power generation potential. Current models, including LandGEM and IPCC, often greatly simplify treatment of factors like rainfall and ambient temperature, which can substantially impact gas production. The newly developed Capturing Landfill Emissions for Energy Needs (CLEEN) model aims to improve landfill methane generation estimates, but still require inputs that are fairly easy to obtain: waste composition, annual rainfall, and ambient temperature. To develop the model, methane generation was measured from 27 laboratory scale landfill reactors, with varying waste compositions (ranging from 0% to 100%); average rainfall rates of 2, 6, and 12 mm/day; and temperatures of 20, 30, and 37°C, according to a statistical experimental design. Refuse components considered were the major biodegradable wastes, food, paper, yard/wood, and textile, as well as inert inorganic waste. Based on the data collected, a multiple linear regression equation (R(2)=0.75) was developed to predict first-order methane generation rate constant values k as functions of waste composition, annual rainfall, and temperature. Because, laboratory methane generation rates exceed field rates, a second scale-up regression equation for k was developed using actual gas-recovery data from 11 landfills in high-income countries with conventional operation. The Capturing Landfill Emissions for Energy Needs (CLEEN) model was developed by incorporating both regression equations into the first-order decay based model for estimating methane generation rates from landfills. CLEEN model values were compared to actual field data from 6 US landfills, and to estimates from LandGEM and IPCC. For 4 of the 6 cases, CLEEN model estimates were the closest to actual. Copyright © 2015 Elsevier Ltd. All rights reserved.

  15. Urban flood return period assessment through rainfall-flood response modelling

    Science.gov (United States)

    Murla Tuyls, Damian; Thorndahl, Søren

    2017-04-01

    Intense rainfall can often cause severe floods, especially in urbanized areas, where population density or large impermeable areas are found. In this context, floods can generate a direct impact in a social-environmental-economic viewpoint. Traditionally, in design of Urban Drainage Systems (UDS), correlation between return period (RP) of a given rainfall and RP of its consequent flood has been assumed to be linear (e.g. DS/EN752 (2008)). However, this is not always the case. Complex UDS, where diverse hydraulic infrastructures are often found, increase the heterogeneity of system response, which may cause an alteration of the mentioned correlation. Consequently, reliability on future urban planning, design and resilience against floods may be also affected by this misassumption. In this study, an assessment of surface flood RP across rainfall RP has been carried out at Lystrup, a urbanized catchment area of 440ha and 10.400inhab. located in Jutland (Denmark), which has received the impact of several pluvial flooding in the last recent years. A historical rainfall dataset from the last 35 years from two different rain gauges located at 2 and 10 km from the study area has been provided by the Danish Wastewater Pollution Committee and the Danish Meteorological Institute (DMI). The most extreme 25 rainfall events have been selected through a two-step multi-criteria procedure, ensuring an adequate variability of rainfall, from extreme high peak storms with a short duration to moderate rainfall with longer duration. In addition, a coupled 1D/2D surface and network UDS model of the catchment area developed in an integrated MIKE URBAN and MIKE Flood model (DHI 2014), considering both permeable and impermeable areas, in combination with a DTM (2x2m res.) has been used to study and assess in detail flood RP. Results show an ambiguous relation between rainfall RP and flood response. Local flood levels, flood area and volume RP estimates should therefore not be neglected in

  16. INVESTIGATION OF QUANTIFICATION OF FLOOD CONTROL AND WATER UTILIZATION EFFECT OF RAINFALL INFILTRATION FACILITY BY USING WATER BALANCE ANALYSIS MODEL

    OpenAIRE

    文, 勇起; BUN, Yuki

    2013-01-01

    In recent years, many flood damage and drought attributed to urbanization has occurred. At present infiltration facility is suggested for the solution of these problems. Based on this background, the purpose of this study is investigation of quantification of flood control and water utilization effect of rainfall infiltration facility by using water balance analysis model. Key Words : flood control, water utilization , rainfall infiltration facility

  17. Disaggregating radar-derived rainfall measurements in East Azarbaijan, Iran, using a spatial random-cascade model

    Science.gov (United States)

    Fouladi Osgouei, Hojjatollah; Zarghami, Mahdi; Ashouri, Hamed

    2017-07-01

    The availability of spatial, high-resolution rainfall data is one of the most essential needs in the study of water resources. These data are extremely valuable in providing flood awareness for dense urban and industrial areas. The first part of this paper applies an optimization-based method to the calibration of radar data based on ground rainfall gauges. Then, the climatological Z-R relationship for the Sahand radar, located in the East Azarbaijan province of Iran, with the help of three adjacent rainfall stations, is obtained. The new climatological Z-R relationship with a power-law form shows acceptable statistical performance, making it suitable for radar-rainfall estimation by the Sahand radar outputs. The second part of the study develops a new heterogeneous random-cascade model for spatially disaggregating the rainfall data resulting from the power-law model. This model is applied to the radar-rainfall image data to disaggregate rainfall data with coverage area of 512 × 512 km2 to a resolution of 32 × 32 km2. Results show that the proposed model has a good ability to disaggregate rainfall data, which may lead to improvement in precipitation forecasting, and ultimately better water-resources management in this arid region, including Urmia Lake.

  18. A coupled stochastic rainfall-evapotranspiration model for hydrological impact analysis

    Science.gov (United States)

    Pham, Minh Tu; Vernieuwe, Hilde; De Baets, Bernard; Verhoest, Niko E. C.

    2018-02-01

    A hydrological impact analysis concerns the study of the consequences of certain scenarios on one or more variables or fluxes in the hydrological cycle. In such an exercise, discharge is often considered, as floods originating from extremely high discharges often cause damage. Investigating the impact of extreme discharges generally requires long time series of precipitation and evapotranspiration to be used to force a rainfall-runoff model. However, such kinds of data may not be available and one should resort to stochastically generated time series, even though the impact of using such data on the overall discharge, and especially on the extreme discharge events, is not well studied. In this paper, stochastically generated rainfall and corresponding evapotranspiration time series, generated by means of vine copulas, are used to force a simple conceptual hydrological model. The results obtained are comparable to the modelled discharge using observed forcing data. Yet, uncertainties in the modelled discharge increase with an increasing number of stochastically generated time series used. Notwithstanding this finding, it can be concluded that using a coupled stochastic rainfall-evapotranspiration model has great potential for hydrological impact analysis.

  19. Skill of Predicting Heavy Rainfall Over India: Improvement in Recent Years Using UKMO Global Model

    Science.gov (United States)

    Sharma, Kuldeep; Ashrit, Raghavendra; Bhatla, R.; Mitra, A. K.; Iyengar, G. R.; Rajagopal, E. N.

    2017-11-01

    The quantitative precipitation forecast (QPF) performance for heavy rains is still a challenge, even for the most advanced state-of-art high-resolution Numerical Weather Prediction (NWP) modeling systems. This study aims to evaluate the performance of UK Met Office Unified Model (UKMO) over India for prediction of high rainfall amounts (>2 and >5 cm/day) during the monsoon period (JJAS) from 2007 to 2015 in short range forecast up to Day 3. Among the various modeling upgrades and improvements in the parameterizations during this period, the model horizontal resolution has seen an improvement from 40 km in 2007 to 17 km in 2015. Skill of short range rainfall forecast has improved in UKMO model in recent years mainly due to increased horizontal and vertical resolution along with improved physics schemes. Categorical verification carried out using the four verification metrics, namely, probability of detection (POD), false alarm ratio (FAR), frequency bias (Bias) and Critical Success Index, indicates that QPF has improved by >29 and >24% in case of POD and FAR. Additionally, verification scores like EDS (Extreme Dependency Score), EDI (Extremal Dependence Index) and SEDI (Symmetric EDI) are used with special emphasis on verification of extreme and rare rainfall events. These scores also show an improvement by 60% (EDS) and >34% (EDI and SEDI) during the period of study, suggesting an improved skill of predicting heavy rains.

  20. Testing the Beta-Lognormal Model in Amazonian Rainfall Fields Using the Generalized Space q-Entropy

    Directory of Open Access Journals (Sweden)

    Hernán D. Salas

    2017-12-01

    Full Text Available We study spatial scaling and complexity properties of Amazonian radar rainfall fields using the Beta-Lognormal Model (BL-Model with the aim to characterize and model the process at a broad range of spatial scales. The Generalized Space q-Entropy Function (GSEF, an entropic measure defined as a continuous set of power laws covering a broad range of spatial scales, S q ( λ ∼ λ Ω ( q , is used as a tool to check the ability of the BL-Model to represent observed 2-D radar rainfall fields. In addition, we evaluate the effect of the amount of zeros, the variability of rainfall intensity, the number of bins used to estimate the probability mass function, and the record length on the GSFE estimation. Our results show that: (i the BL-Model adequately represents the scaling properties of the q-entropy, S q, for Amazonian rainfall fields across a range of spatial scales λ from 2 km to 64 km; (ii the q-entropy in rainfall fields can be characterized by a non-additivity value, q s a t, at which rainfall reaches a maximum scaling exponent, Ω s a t; (iii the maximum scaling exponent Ω s a t is directly related to the amount of zeros in rainfall fields and is not sensitive to either the number of bins to estimate the probability mass function or the variability of rainfall intensity; and (iv for small-samples, the GSEF of rainfall fields may incur in considerable bias. Finally, for synthetic 2-D rainfall fields from the BL-Model, we look for a connection between intermittency using a metric based on generalized Hurst exponents, M ( q 1 , q 2 , and the non-extensive order (q-order of a system, Θ q, which relates to the GSEF. Our results do not exhibit evidence of such relationship.

  1. Vegetation Variability And Its Effect On Monsoon Rainfall Over South East Asia: Observational and Modeling Results

    Science.gov (United States)

    Sarkar, S.; Peters-Lidard, C.; Chiu, L.; Kafatos, M.

    2005-12-01

    Increasing population and urbanization have created stress on developing nations. The quickly shifting patterns of vegetation change in different parts of the world have given rise to the pertinent question of feedback on the climate prevailing on local to regional scales. It is now known with some certainty, that vegetation changes can affect the climate by influencing the heat and water balance. The hydrological cycle particularly is susceptible to changes in vegetation. The Monsoon rainfall forms a vital link in the hydrological cycle prevailing over South East Asia This work examines the variability of vegetation over South East Asia and assesses its impact on the monsoon rainfall. We explain the role of changing vegetation and show how this change has affected the heat and energy balance. We demonstrate the role of vegetation one season earlier in influencing rainfall intensity over specific areas in South East Asia and show the ramification of vegetation change on the summer rainfall behavior. The vegetation variability study specifically focuses on India and China, two of the largest and most populous nations. We have done an assessment to find out the key meteorological and human induced parameters affecting vegetation over the study area through a spatial analysis of monthly NDVI values. This study highlights the role of monsoon rainfall, regional climate dynamics and large scale human induced pollution to be the crucial factors governing the vegetation and vegetation distribution. The vegetation is seen to follow distinct spatial patterns that have been found to be crucial in its eventual impact on monsoon rainfall. We have carried out a series of sensitivity experiments using a land surface hydrologic modeling scheme. The vital energy and water balance parameters are identified and the daily climatological cycles are examined for possible change in behavior for different boundary conditions. It is found that the change from native deciduous forest

  2. Prediction of Rainfall-Induced Landslides in Tegucigalpa, Honduras, Using a Hydro-Geotechnical Model

    Science.gov (United States)

    Garcia Urquia, Elias; Axelsson, K.

    2010-05-01

    Central America is constantly being affected by natural hazards. Among these events are hurricanes and earthquakes, capable of triggering landslides that can alter the natural landscape, destroy infrastructure and cause the death of people in the most important settlements of the region. Hurricane Mitch in October of 1998 was of particular interest for the region, since it provoked hundreds of rainfall-induced landslides, mainly in 4 different countries. Studies carried out after Hurricane Mitch have allowed researchers to identify the factors that contribute to slope instability in many vulnerable areas. As Tegucigalpa, Honduras was partially destroyed due to the various landslide and flooding events triggered by this devastating hurricane, various research teams have deepened in their investigations and have proposed measures to mitigate the effects of similar future incidents. A model coupling an infinite-slope analysis and a simple groundwater flow approach can serve as a basis to predict the occurrence of landslides in Tegucigalpa, Honduras as a function of topographic, hydrological and soil variables. A safety map showing the rainfall-triggered landslide risk zones for Tegucigalpa, Honduras is to be created. As opposed to previous safety maps in which only steady-state conditions are studied, this analysis is extended and different steady-state and quasi-dynamic scenarios are considered for comparison. For the purpose of the latter settings, a hydrological analysis that determines the rainfall extreme values and their return periods in Tegucigalpa will account for the influence of rainfall on the groundwater flow and strength of soils. It is known that the spatial distribution of various factors that contribute to the risk of landslides (i.e. soil thickness, conductivity and strength properties; rainfall intensity and duration; root strength; subsurface flow orientation) is hard to determine. However, an effort is done to derive correlations for these

  3. Modelling of Multi Input Transfer Function for Rainfall Forecasting in Batu City

    OpenAIRE

    Priska Arindya Purnama

    2017-01-01

    The aim of this research is to model and forecast the rainfall in Batu City using multi input transfer function model based on air temperature, humidity, wind speed and cloud. Transfer function model is a multivariate time series model which consists of an output series (Yt) sequence expected to be effected by an input series (Xt) and other inputs in a group called a noise series (Nt). Multi input transfer function model obtained is (b1,s1,r1) (b2,s2,r2) (b3,s3,r3) (b4,s4,r4)(pn,qn) = (0,0,0)...

  4. Assessment of the Weather Research and Forecasting (WRF) model for simulation of extreme rainfall events in the upper Ganga Basin

    Science.gov (United States)

    Chawla, Ila; Osuri, Krishna K.; Mujumdar, Pradeep P.; Niyogi, Dev

    2018-02-01

    Reliable estimates of extreme rainfall events are necessary for an accurate prediction of floods. Most of the global rainfall products are available at a coarse resolution, rendering them less desirable for extreme rainfall analysis. Therefore, regional mesoscale models such as the advanced research version of the Weather Research and Forecasting (WRF) model are often used to provide rainfall estimates at fine grid spacing. Modelling heavy rainfall events is an enduring challenge, as such events depend on multi-scale interactions, and the model configurations such as grid spacing, physical parameterization and initialization. With this background, the WRF model is implemented in this study to investigate the impact of different processes on extreme rainfall simulation, by considering a representative event that occurred during 15-18 June 2013 over the Ganga Basin in India, which is located at the foothills of the Himalayas. This event is simulated with ensembles involving four different microphysics (MP), two cumulus (CU) parameterizations, two planetary boundary layers (PBLs) and two land surface physics options, as well as different resolutions (grid spacing) within the WRF model. The simulated rainfall is evaluated against the observations from 18 rain gauges and the Tropical Rainfall Measuring Mission Multi-Satellite Precipitation Analysis (TMPA) 3B42RT version 7 data. From the analysis, it should be noted that the choice of MP scheme influences the spatial pattern of rainfall, while the choice of PBL and CU parameterizations influences the magnitude of rainfall in the model simulations. Further, the WRF run with Goddard MP, Mellor-Yamada-Janjic PBL and Betts-Miller-Janjic CU scheme is found to perform best in simulating this heavy rain event. The selected configuration is evaluated for several heavy to extremely heavy rainfall events that occurred across different months of the monsoon season in the region. The model performance improved through incorporation

  5. Projections of Rainfall and Temperature from CMIP5 Models over BIMSTEC Countries

    Science.gov (United States)

    Pattnayak, K. C.; Kar, S. C.; Ragi, A. R.

    2014-12-01

    Rainfall and surface temperature are the most important climatic variables in the context of climate change. Thus, these variables simulated from fifth phase of the Climate Model Inter-comparison Project (CMIP5) models have been compared against Climatic Research Unit (CRU) observed data and projected for the twenty first century under the Representative Concentration Pathways (RCPs) 4.5 and 8.5 emission scenarios. Results for the seven countries under Bay of Bengal Initiative for Multi-Sectoral Technical and Economic Cooperation (BIMSTEC) such as Bangladesh, Bhutan, India, Myanmar, Nepal, Sri Lanka and Thailand have been examined. Six CMIP5 models namely GFDL-CM3, GFDL-ESM2M, GFDL-ESM2G, HadGEM2-AO, HadGEM2-CC and HadGEM2-ES have been chosen for this study. The study period has been considered is from 1861 to 2100. From this period, initial 145 years i.e. 1861 to 2005 is reference or historical period and the later 95 years i.e. 2005 to 2100 is projected period. The climate change in the projected period has been examined with respect to the reference period. In order to validate the models, the mean annual rainfall and temperature has been compared with CRU over the reference period 1901 to 2005. Comparison reveals that most of the models are able to capture the spatial distribution of rainfall and temperature over most of the regions of BIMSTEC countries. Therefore these model data can be used to study the future changes in the 21st Century. Four out six models shows that the rainfall over Central and North India, Thailand and eastern part of Myanmar shows decreasing trend and Bangladesh, Bhutan, Nepal and Sri Lanka shows an increasing trend in both RCP 4.5 and 8.5 scenarios. In case of temperature, all of the models show an increasing trend over all the BIMSTEC countries in both scenarios, however, the rate of increase is relatively less over Sri Lanka than the other countries. Annual cycles of rainfall and temperature over Bangladesh, Myanmar and Thailand

  6. Simulation skill of APCC set of global climate models for Asian summer monsoon rainfall variability

    Science.gov (United States)

    Singh, U. K.; Singh, G. P.; Singh, Vikas

    2015-04-01

    The performance of 11 Asia-Pacific Economic Cooperation Climate Center (APCC) global climate models (coupled and uncoupled both) in simulating the seasonal summer (June-August) monsoon rainfall variability over Asia (especially over India and East Asia) has been evaluated in detail using hind-cast data (3 months advance) generated from APCC which provides the regional climate information product services based on multi-model ensemble dynamical seasonal prediction systems. The skill of each global climate model over Asia was tested separately in detail for the period of 21 years (1983-2003), and simulated Asian summer monsoon rainfall (ASMR) has been verified using various statistical measures for Indian and East Asian land masses separately. The analysis found a large variation in spatial ASMR simulated with uncoupled model compared to coupled models (like Predictive Ocean Atmosphere Model for Australia, National Centers for Environmental Prediction and Japan Meteorological Agency). The simulated ASMR in coupled model was closer to Climate Prediction Centre Merged Analysis of Precipitation (CMAP) compared to uncoupled models although the amount of ASMR was underestimated in both models. Analysis also found a high spread in simulated ASMR among the ensemble members (suggesting that the model's performance is highly dependent on its initial conditions). The correlation analysis between sea surface temperature (SST) and ASMR shows that that the coupled models are strongly associated with ASMR compared to the uncoupled models (suggesting that air-sea interaction is well cared in coupled models). The analysis of rainfall using various statistical measures suggests that the multi-model ensemble (MME) performed better compared to individual model and also separate study indicate that Indian and East Asian land masses are more useful compared to Asia monsoon rainfall as a whole. The results of various statistical measures like skill of multi-model ensemble, large spread

  7. Interannual Rainfall Variability in North-East Brazil: Observation and Model Simulation

    Science.gov (United States)

    Harzallah, A.; Rocha de Aragão, J. O.; Sadourny, R.

    1996-08-01

    The relationship between interannual variability of rainfall in north-east Brazil and tropical sea-surface temperature is studied using observations and model simulations. The simulated precipitation is the average of seven independent realizations performed using the Laboratoire de Météorologie Dynamique atmospheric general model forced by the 1970-1988 observed sea-surface temperature. The model reproduces very well the rainfall anomalies (correlation of 091 between observed and modelled anomalies). The study confirms that precipitation in north-east Brazil is highly correlated to the sea-surface temperature in the tropical Atlantic and Pacific oceans. Using the singular value decomposition method, we find that Nordeste rainfall is modulated by two independent oscillations, both governed by the Atlantic dipole, but one involving only the Pacific, the other one having a period of about 10 years. Correlations between precipitation in north-east Brazil during February-May and the sea-surface temperature 6 months earlier indicate that both modes are essential to estimate the quality of the rainy season.

  8. Regionalised spatiotemporal rainfall and temperature models for flood studies in the Basque Country, Spain

    Directory of Open Access Journals (Sweden)

    P. Cowpertwait

    2013-02-01

    Full Text Available A spatiotemporal point process model of rainfall is fitted to data taken from three homogeneous regions in the Basque Country, Spain. The model is the superposition of two spatiotemporal Neyman–Scott processes, in which rain cells are modelled as discs with radii that follow exponential distributions. In addition, the model includes a parameter for the radius of storm discs, so that rain only occurs when both a cell and a storm disc overlap a point. The model is fitted to data for each month, taken from each of the three homogeneous regions, using a modified method of moments procedure that ensures a smooth seasonal variation in the parameter estimates.

    Daily temperature data from 23 sites are used to fit a stochastic temperature model. A principal component analysis of the maximum daily temperatures across the sites indicates that 92% of the variance is explained by the first component, implying that this component can be used to account for spatial variation. A harmonic equation with autoregressive error terms is fitted to the first principal component. The temperature model is obtained by regressing the maximum daily temperature on the first principal component, an indicator variable for the region, and altitude. This, together with scaling and a regression model of temperature range, enables hourly temperatures to be predicted. Rainfall is included as an explanatory variable but has only a marginal influence when predicting temperatures.

    A distributed model (TETIS; Francés et al., 2007 is calibrated for a selected catchment. Five hundred years of data are simulated using the rainfall and temperature models and used as input to the calibrated TETIS model to obtain simulated discharges to compare with observed discharges. Kolmogorov–Smirnov tests indicate that there is no significant difference in the distributions of observed and simulated maximum flows at the same sites, thus supporting the use of the spatiotemporal

  9. Multi-Site Calibration of Linear Reservoir Based Geomorphologic Rainfall-Runoff Models

    Directory of Open Access Journals (Sweden)

    Bahram Saeidifarzad

    2014-09-01

    Full Text Available Multi-site optimization of two adapted event-based geomorphologic rainfall-runoff models was presented using Non-dominated Sorting Genetic Algorithm (NSGA-II method for the South Fork Eel River watershed, California. The first model was developed based on Unequal Cascade of Reservoirs (UECR and the second model was presented as a modified version of Geomorphological Unit Hydrograph based on Nash’s model (GUHN. Two calibration strategies were considered as semi-lumped and semi-distributed for imposing (or unimposing the geomorphology relations in the models. The results of models were compared with Nash’s model. Obtained results using the observed data of two stations in the multi-site optimization framework showed reasonable efficiency values in both the calibration and the verification steps. The outcomes also showed that semi-distributed calibration of the modified GUHN model slightly outperformed other models in both upstream and downstream stations during calibration. Both calibration strategies for the developed UECR model during the verification phase showed slightly better performance in the downstream station, but in the upstream station, the modified GUHN model in the semi-lumped strategy slightly outperformed the other models. The semi-lumped calibration strategy could lead to logical lag time parameters related to the basin geomorphology and may be more suitable for data-based statistical analyses of the rainfall-runoff process.

  10. Effects of climate model interdependency on the uncertainty quantification of extreme rainfall projections

    DEFF Research Database (Denmark)

    Sunyer Pinya, Maria Antonia; Madsen, H.; Rosbjerg, Dan

    Climate Models (RCMs) and General Circulation Models (GCMs). These multi-model ensembles provide the information needed to estimate probabilistic climate change projections. Several probabilistic methods have been suggested. One common assumption in most of these methods is that the climate models...... are independent. The effects of this assumption on the uncertainty quantification of extreme rainfall projections are addressed in this study. First, the interdependency of the 95% quantile of wet days in the ENSEMBLES RCMs is estimated. For this statistic and the region studied, the RCMs cannot be assumed...

  11. A Physically-based Model For Rainfall-triggered Landslides At A Regional Scale

    Science.gov (United States)

    Teles, V.; Capolongo, D.; Bras, R. L.

    Rainfall has long been recognized as a major cause of landslides. Historical records have shown that large rainfall can generate hundreds of landslides over hundreds of square kilometers. Although a great body of work has documented the morphology and mechanics of individual slope failure, few studies have considered the process at basin and regional scale. A landslide model is integrated in the landscape evolution model CHILD and simulates rainfall-triggered events based on a geotechnical index, the factor of safety, which takes into account the slope, the soil effective cohesion and weight, the friction angle, the regolith thickness and the saturated thickness. The stat- urated thickness is represented by the wetness index developed in the TOPMODEL. The topography is represented by a Triangulated Irregular Network (TIN). The factor of safety is computed at each node of the TIN. If the factor of safety is lower than 1, a landslide is intiated at this node. The regolith is then moved downstream. We applied the model to the Fortore basin whose valley cuts the flysch terrain that constitute the framework of the so called "sub-Apennines" chain that is the most eastern part of the Southern Apennines (Italy). We will discuss its value according to its sensitivity to the used parameters and compare it to the actual data available for this basin.

  12. Different methods for spatial interpolation of rainfall data for operational hydrology and hydrological modeling at watershed scale: a review

    Directory of Open Access Journals (Sweden)

    Ly, S.

    2013-01-01

    Full Text Available Watershed management and hydrological modeling require data related to the very important matter of precipitation, often measured using raingages or weather stations. Hydrological models often require a preliminary spatial interpolation as part of the modeling process. The success of spatial interpolation varies according to the type of model chosen, its mode of geographical management and the resolution used. The quality of a result is determined by the quality of the continuous spatial rainfall, which ensues from the interpolation method used. The objective of this article is to review the existing methods for interpolation of rainfall data that are usually required in hydrological modeling. We review the basis for the application of certain common methods and geostatistical approaches used in interpolation of rainfall. Previous studies have highlighted the need for new research to investigate ways of improving the quality of rainfall data and ultimately, the quality of hydrological modeling.

  13. Estimation of Rainfall Associated with Typhoons over the Ocean Using TRMM/TMI and Numerical Models

    Directory of Open Access Journals (Sweden)

    Nan-Ching Yeh

    2015-11-01

    Full Text Available This study quantitatively estimated the precipitation associated with a typhoon in the northwestern Pacific Ocean by using a physical algorithm which included the Weather Research and Forecasting model, Radiative Transfer for TIROS Operational Vertical Sounder model, and data from the Tropical Rainfall Measuring Mission (TRMM/TRMM Microwave Imager (TMI and TRMM/Precipitation Radar (PR. First, a prior probability distribution function (PDF was constructed using over three million rain rate retrievals from the TRMM/PR data for the period 2002–2010 over the northwestern Pacific Ocean. Subsequently, brightness temperatures for 15 typhoons that occurred over the northwestern Pacific Ocean were simulated using a microwave radiative transfer model and a conditional PDF was obtained for these typhoons. The aforementioned physical algorithm involved using a posterior PDF. A posterior PDF was obtained by combining the prior and conditional PDFs. Finally, the rain rate associated with a typhoon was estimated by inputting the observations of the TMI (attenuation indices at 10, 19, 37 GHz into the posterior PDF (lookup table. Results based on rain rate retrievals indicated that rainband locations with the heaviest rainfall showed qualitatively similar horizontal distributions. The correlation coefficient and root-mean-square error of the rain rate estimation were 0.63 and 4.45 mm·h−1, respectively. Furthermore, the correlation coefficient and root-mean-square error for convective rainfall were 0.78 and 7.25 mm·h−1, respectively, and those for stratiform rainfall were 0.58 and 9.60 mm·h−1, respectively. The main contribution of this study is introducing an approach to quickly and accurately estimate the typhoon precipitation, and remove the need for complex calculations.

  14. Modeling of dengue occurrences early warning involving temperature and rainfall factors

    Directory of Open Access Journals (Sweden)

    Prama Setia Putra

    2017-07-01

    Full Text Available Objective: To understand dengue transmission process and its vector dynamics and to develop early warning model of dengue occurrences based on mosquito population and host-vector threshold values considering temperature and rainfall. Methods: To obtain the early warning model, mosquito population and host-vector models are developed initially. Both are developed using differential equations. Basic offspring number (R0m and basic reproductive ratio (R0d which are the threshold values are derived from the models under constant parameters assumption. Temperature and rainfall effects on mosquito and dengue are performed in entomological and disease transmission parameters. Some of parameters are set as functions of temperature or rainfall while other parameters are set to be constant. Hereafter, both threshold values are computed using those parameters. Monthly dengue occurrences data are categorized as zero and one values which one means the outbreak does occur in that month. Logistics regression is chosen to bridge the threshold values and categorized data. Threshold values are considered as the input of early warning model. Semarang city is selected as the sample to develop this early waning model. Results: The derived threshold values which are R 0 m and R 0 d show to have relation that mosquito as dengue vector affects transmission of the disease. Result of the early warning model will be a value between zero and one. It is categorized as outbreak does occur when the value is larger than 0.5 while other is categorized as outbreak does not occur. By using single predictor, the model can perform 68% accuracy approximately. Conclusions: The extinction of mosquitoes will be followed by disease disappearance while mosquitoes existence can lead to disease free or endemic states. Model simulations show that mosquito population are more affected by weather factors than human. Involving weather factors implicitly in the threshold value and linking them

  15. Geo-statistical model of Rainfall erosivity by using high temporal resolution precipitation data in Europe

    Science.gov (United States)

    Panagos, Panos; Ballabio, Cristiano; Borrelli, Pasquale; Meusburger, Katrin; Alewell, Christine

    2015-04-01

    Rainfall erosivity (R-factor) is among the 6 input factors in estimating soil erosion risk by using the empirical Revised Universal Soil Loss Equation (RUSLE). R-factor is a driving force for soil erosion modelling and potentially can be used in flood risk assessments, landslides susceptibility, post-fire damage assessment, application of agricultural management practices and climate change modelling. The rainfall erosivity is extremely difficult to model at large scale (national, European) due to lack of high temporal resolution precipitation data which cover long-time series. In most cases, R-factor is estimated based on empirical equations which take into account precipitation volume. The Rainfall Erosivity Database on the European Scale (REDES) is the output of an extensive data collection of high resolution precipitation data in the 28 Member States of the European Union plus Switzerland taking place during 2013-2014 in collaboration with national meteorological/environmental services. Due to different temporal resolutions of the data (5, 10, 15, 30, 60 minutes), conversion equations have been applied in order to homogenise the database at 30-minutes interval. The 1,541 stations included in REDES have been interpolated using the Gaussian Process Regression (GPR) model using as covariates the climatic data (monthly precipitation, monthly temperature, wettest/driest month) from WorldClim Database, Digital Elevation Model and latitude/longitude. GPR has been selected among other candidate models (GAM, Regression Kriging) due the best performance both in cross validation (R2=0.63) and in fitting dataset (R2=0.72). The highest uncertainty has been noticed in North-western Scotland, North Sweden and Finland due to limited number of stations in REDES. Also, in highlands such as Alpine arch and Pyrenees the diversity of environmental features forced relatively high uncertainty. The rainfall erosivity map of Europe available at 500m resolution plus the standard error

  16. On the possibility of calibrating urban storm-water drainage models using gauge-based adjusted radar rainfall estimates

    OpenAIRE

    Ochoa-Rodriguez, S; Wang, L; Simoes, N; Onof, C; Maksimovi?, ?

    2013-01-01

    24/07/14 meb. Authors did not sign CTA. Traditionally, urban storm water drainage models have been calibrated using only raingauge data, which may result in overly conservative models due to the lack of spatial description of rainfall. With the advent of weather radars, radar rainfall estimates with higher temporal and spatial resolution have become increasingly available and have started to be used operationally for urban storm water model calibration and real time operation. Nonetheless,...

  17. Challenges to Rainfall-Runoff and Transit Time Distribution Modeling Within the Southeastern Coastal Plain, USA

    Science.gov (United States)

    Decker, P.; Cohen, M. J.; Jawitz, J. W.

    2017-12-01

    Previous hydrologic studies primarily focus on processes related to montane catchments with significant runoff ratios, low evapotranspiration rates, and reasonably short travel times. There is a significant lack of research for hydrologic processes occurring within the United States Southeastern Coastal Plain landscape where low-relief and high rates of evapotranspiration impact water fluxes. Hydrologic modeling efforts within this region may elucidate possible interactions and timescales of solute travel where much of the landscape is managed for agricultural crops, namely plantation forestry. A long-term paired watershed study carried out in northern Florida monitored two second-order blackwater streams for five years. Rainfall-runoff models for both catchments were created using daily discharge, precipitation, and modeled evapotranspiration as input parameters. Best fit occurred (NSE = 0.8) when the catchments were modeled as two-storage (shallow and deep) reservoirs in parallel and overland flow was allowed to contribute to streamflow in periods were shallow groundwater storage was at capacity. In addition, streamflow and rainfall chloride concentrations were used to model in-variable transit time distributions using spectral methods. In both catchments this transit time was unresolvable because output spectral power exceeded input spectral power, a result assumed to be driven by the evaporative demand of the region. A modeled chloride time series from random input concentration and modeled output through the rainfall-runoff model was used to alter the evaporation ratio. Once evaporation rates equaled known rates found in cool, high-relief catchments, spectral analysis illustrated higher input spectral power and therefore resolvable transit times. Findings from this study illustrate significant effects from evaporation within the catchment - often exceeding the signal from the background catchment process itself. Calculations illustrate a proposed mean transit

  18. HYDROSCAPE: A SCAlable and ParallelizablE Rainfall Runoff Model for Hydrological Applications

    Science.gov (United States)

    Piccolroaz, S.; Di Lazzaro, M.; Zarlenga, A.; Majone, B.; Bellin, A.; Fiori, A.

    2015-12-01

    In this work we present HYDROSCAPE, an innovative streamflow routing method based on the travel time approach, and modeled through a fine-scale geomorphological description of hydrological flow paths. The model is designed aimed at being easily coupled with weather forecast or climate models providing the hydrological forcing, and at the same time preserving the geomorphological dispersion of the river network, which is kept unchanged independently on the grid size of rainfall input. This makes HYDROSCAPE particularly suitable for multi-scale applications, ranging from medium size catchments up to the continental scale, and to investigate the effects of extreme rainfall events that require an accurate description of basin response timing. Key feature of the model is its computational efficiency, which allows performing a large number of simulations for sensitivity/uncertainty analyses in a Monte Carlo framework. Further, the model is highly parsimonious, involving the calibration of only three parameters: one defining the residence time of hillslope response, one for channel velocity, and a multiplicative factor accounting for uncertainties in the identification of the potential maximum soil moisture retention in the SCS-CN method. HYDROSCAPE is designed with a simple and flexible modular structure, which makes it particularly prone to massive parallelization, customization according to the specific user needs and preferences (e.g., rainfall-runoff model), and continuous development and improvement. Finally, the possibility to specify the desired computational time step and evaluate streamflow at any location in the domain, makes HYDROSCAPE an attractive tool for many hydrological applications, and a valuable alternative to more complex and highly parametrized large scale hydrological models. Together with model development and features, we present an application to the Upper Tiber River basin (Italy), providing a practical example of model performance and

  19. Comparison of Spatial Interpolation Schemes for Rainfall Data and Application in Hydrological Modeling

    Directory of Open Access Journals (Sweden)

    Tao Chen

    2017-05-01

    Full Text Available The spatial distribution of precipitation is an important aspect of water-related research. The use of different interpolation schemes in the same catchment may cause large differences and deviations from the actual spatial distribution of rainfall. Our study analyzes different methods of spatial rainfall interpolation at annual, daily, and hourly time scales to provide a comprehensive evaluation. An improved regression-based scheme is proposed using principal component regression with residual correction (PCRR and is compared with inverse distance weighting (IDW and multiple linear regression (MLR interpolation methods. In this study, the meso-scale catchment of the Fuhe River in southeastern China was selected as a typical region. Furthermore, a hydrological model HEC-HMS was used to calculate streamflow and to evaluate the impact of rainfall interpolation methods on the results of the hydrological model. Results show that the PCRR method performed better than the other methods tested in the study and can effectively eliminate the interpolation anomalies caused by terrain differences between observation points and surrounding areas. Simulated streamflow showed different characteristics based on the mean, maximum, minimum, and peak flows. The results simulated by PCRR exhibited the lowest streamflow error and highest correlation with measured values at the daily time scale. The application of the PCRR method is found to be promising because it considers multicollinearity among variables.

  20. Calculation of intercepted runoff depth based on stormwater quality and environmental capacity of receiving waters for initial stormwater pollution management.

    Science.gov (United States)

    Peng, Hai-Qin; Liu, Yan; Gao, Xue-Long; Wang, Hong-Wu; Chen, Yi; Cai, Hui-Yi

    2017-11-01

    While point source pollutions have gradually been controlled in recent years, the non-point source pollution problem has become increasingly prominent. The receiving waters are frequently polluted by the initial stormwater from the separate stormwater system and the wastewater from sewage pipes through stormwater pipes. Consequently, calculating the intercepted runoff depth has become a problem that must be resolved immediately for initial stormwater pollution management. The accurate calculation of intercepted runoff depth provides a solid foundation for selecting the appropriate size of intercepting facilities in drainage and interception projects. This study establishes a separate stormwater system for the Yishan Building watershed of Fuzhou City using the InfoWorks Integrated Catchment Management (InfoWorks ICM), which can predict the stormwater flow velocity and the flow of discharge outlet after each rainfall. The intercepted runoff depth is calculated from the stormwater quality and environmental capacity of the receiving waters. The average intercepted runoff depth from six rainfall events is calculated as 4.1 mm based on stormwater quality. The average intercepted runoff depth from six rainfall events is calculated as 4.4 mm based on the environmental capacity of the receiving waters. The intercepted runoff depth differs when calculated from various aspects. The selection of the intercepted runoff depth depends on the goal of water quality control, the self-purification capacity of the water bodies, and other factors of the region.

  1. How might Australian rainforest cloud interception respond to climate change?

    Science.gov (United States)

    Wallace, Jim; McJannet, Dave

    2013-02-01

    SummaryThe lower and upper montane rainforests in northern Queensland receive significant amounts of cloud interception that affect both in situ canopy wetness and downstream runoff. Cloud interception contributes 5-30% of the annual water input to the canopy and this increases to 40-70% of the monthly water input during the dry season. This occult water is therefore an important input to the canopy, sustaining the epiphytes, mosses and other species that depend on wet canopy conditions. The potential effect of climate change on cloud interception was examined using the relationship between cloud interception and cloud frequency derived from measurements made at four different rainforest locations. Any given change in cloud frequency produces a greater change in cloud interception and this 'amplification' increases from 1.1 to 1.7 as cloud frequency increases from 5% to 70%. This means that any changes in cloud frequency will have the greatest relative effects at the higher altitude sites where cloud interception is greatest. As cloud frequency is also a major factor affecting canopy wetness, any given change in cloud frequency will therefore have a greater impact on canopy wetness at the higher altitude sites. These changes in wetness duration will augment those due to changes in rainfall and may have important implications for the fauna and flora that depend on wet canopy conditions. We also found that the Australian rainforests may be more efficient (by ˜50% on average) in intercepting cloud water than American coniferous forests, which may be due to differences in canopy structure and exposure at the different sites.

  2. How would peak rainfall intensity affect runoff predictions using conceptual water balance models?

    Directory of Open Access Journals (Sweden)

    B. Yu

    2015-06-01

    Full Text Available Most hydrological models use continuous daily precipitation and potential evapotranspiration for streamflow estimation. With the projected increase in mean surface temperature, hydrological processes are set to intensify irrespective of the underlying changes to the mean precipitation. The effect of an increase in rainfall intensity on the long-term water balance is, however, not adequately accounted for in the commonly used hydrological models. This study follows from a previous comparative analysis of a non-stationary daily series of stream flow of a forested watershed (River Rimbaud in the French Alps (area = 1.478 km2 (1966–2006. Non-stationarity in the recorded stream flow occurred as a result of a severe wild fire in 1990. Two daily models (AWBM and SimHyd were initially calibrated for each of three distinct phases in relation to the well documented land disturbance. At the daily and monthly time scales, both models performed satisfactorily with the Nash–Sutcliffe coefficient of efficiency (NSE varying from 0.77 to 0.92. When aggregated to the annual time scale, both models underestimated the flow by about 22% with a reduced NSE at about 0.71. Exploratory data analysis was undertaken to relate daily peak hourly rainfall intensity to the discrepancy between the observed and modelled daily runoff amount. Preliminary results show that the effect of peak hourly rainfall intensity on runoff prediction is insignificant, and model performance is unlikely to improve when peak daily precipitation is included. Trend analysis indicated that the large decrease of precipitation when daily precipitation amount exceeded 10–20 mm may have contributed greatly to the decrease in stream flow of this forested watershed.

  3. Introducing uncertainty of radar-rainfall estimates to the verification of mesoscale model precipitation forecasts

    Directory of Open Access Journals (Sweden)

    M. P. Mittermaier

    2008-05-01

    Full Text Available A simple measure of the uncertainty associated with using radar-derived rainfall estimates as "truth" has been introduced to the Numerical Weather Prediction (NWP verification process to assess the effect on forecast skill and errors. Deterministic precipitation forecasts from the mesoscale version of the UK Met Office Unified Model for a two-day high-impact event and for a month were verified at the daily and six-hourly time scale using a spatially-based intensity-scale method and various traditional skill scores such as the Equitable Threat Score (ETS and log-odds ratio. Radar-rainfall accumulations from the UK Nimrod radar-composite were used.

    The results show that the inclusion of uncertainty has some effect, shifting the forecast errors and skill. The study also allowed for the comparison of results from the intensity-scale method and traditional skill scores. It showed that the two methods complement each other, one detailing the scale and rainfall accumulation thresholds where the errors occur, the other showing how skillful the forecast is. It was also found that for the six-hourly forecasts the error distributions remain similar with forecast lead time but skill decreases. This highlights the difference between forecast error and forecast skill, and that they are not necessarily the same.

  4. Modeling urban storm rainfall runoff from diverse underlying surfaces and application for control design in Beijing.

    Science.gov (United States)

    Ouyang, Wei; Guo, Bobo; Hao, Fanghua; Huang, Haobo; Li, Junqi; Gong, Yongwei

    2012-12-30

    Managing storm rainfall runoff is paramount in semi-arid regions with urban development. In Beijing, pollution prevention in urban storm runoff and storm water utilization has been identified as the primary strategy for urban water management. In this paper, we sampled runoff during storm rainfall events and analyzed the concentration of chemical oxygen demand (COD), total suspended solids (TSS) and total phosphorus (TP) in the runoff. Furthermore, the first flush effect of storm rainfall from diverse underlying surfaces was also analyzed. With the Storm Water Management Model (SWMM), the different impervious rates of underlying surfaces during the storm runoff process were expressed. The removal rates of three typical pollutants and their interactions with precipitation and underlying surfaces were identified. From these rates, the scenarios regarding the urban storm runoff pollution loading from different designs of underlying previous rates were assessed with the SWMM. First flush effect analysis showed that the first 20% of the storm runoff should be discarded, which can help in utilizing the storm water resource. The results of this study suggest that the SWMM can express in detail the storm water pollution patterns from diverse underlying surfaces in Beijing, which significantly affected water quality. The scenario analysis demonstrated that impervious rate adjustment has the potential to reduce runoff peak and decrease pollution loading. Copyright © 2012 Elsevier Ltd. All rights reserved.

  5. Mechanism of ENSO influence on the South Asian monsoon rainfall in global model simulations

    Science.gov (United States)

    Joshi, Sneh; Kar, Sarat C.

    2018-02-01

    Coupled ocean atmosphere global climate models are increasingly being used for seasonal scale simulation of the South Asian monsoon. In these models, sea surface temperatures (SSTs) evolve as coupled air-sea interaction process. However, sensitivity experiments with various SST forcing can only be done in an atmosphere-only model. In this study, the Global Forecast System (GFS) model at T126 horizontal resolution has been used to examine the mechanism of El Niño-Southern Oscillation (ENSO) forcing on the monsoon circulation and rainfall. The model has been integrated (ensemble) with observed, climatological and ENSO SST forcing to document the mechanism on how the South Asian monsoon responds to basin-wide SST variations in the Indian and Pacific Oceans. The model simulations indicate that the internal variability gets modulated by the SSTs with warming in the Pacific enhancing the ensemble spread over the monsoon region as compared to cooling conditions. Anomalous easterly wind anomalies cover the Indian region both at 850 and 200 hPa levels during El Niño years. The locations and intensity of Walker and Hadley circulations are altered due to ENSO SST forcing. These lead to reduction of monsoon rainfall over most parts of India during El Niño events compared to La Niña conditions. However, internally generated variability is a major source of uncertainty in the model-simulated climate.

  6. Transfer function modeling of the monthly accumulated rainfall series over the Iberian Peninsula

    Energy Technology Data Exchange (ETDEWEB)

    Mateos, Vidal L.; Garcia, Jose A.; Serrano, Antonio; De la Cruz Gallego, Maria [Departamento de Fisica, Universidad de Extremadura, Badajoz (Spain)

    2002-10-01

    In order to improve the results given by Autoregressive Moving-Average (ARMA) modeling for the monthly accumulated rainfall series taken at 19 observatories of the Iberian Peninsula, a Discrete Linear Transfer Function Noise (DLTFN) model was applied taking the local pressure series (LP), North Atlantic sea level pressure series (SLP) and North Atlantic sea surface temperature (SST) as input variables, and the rainfall series as the output series. In all cases, the performance of the DLTFN models, measured by the explained variance of the rainfall series, is better than the performance given by the ARMA modeling. The best performance is given by the models that take the local pressure as the input variable, followed by the sea level pressure models and the sea surface temperature models. Geographically speaking, the models fitted to those observatories located in the west of the Iberian Peninsula work better than those on the north and east of the Peninsula. Also, it was found that there is a region located between 0 N and 20 N, which shows the highest cross-correlation between SST and the peninsula rainfalls. This region moves to the west and northwest off the Peninsula when the SLP series are used. [Spanish] Con el objeto de mejorar los resultados porporcionados por los modelos Autorregresivo Media Movil (ARMA) ajustados a las precipitaciones mensuales acumuladas registradas en 19 observatorios de la Peninsula Iberica se han usado modelos de funcion de transferencia (DLTFN) en los que se han empleado como variable independiente la presion local (LP), la presion a nivel del mar (SLP) o la temperatura de agua del mar (SST) en el Atlantico Norte. En todos los casos analizados, los resultados obtenidos con los modelos DLTFN, medidos mediante la varianza explicada por el modelo, han sido mejores que los resultados proporcionados por los modelos ARMA. Los mejores resultados han sido dados por aquellos modelos que usan la presion local como variable de entrada, seguidos

  7. A rainfall disaggregation scheme for sub-hourly time scales: Coupling a Bartlett-Lewis based model with adjusting procedures

    Science.gov (United States)

    Kossieris, Panagiotis; Makropoulos, Christos; Onof, Christian; Koutsoyiannis, Demetris

    2018-01-01

    Many hydrological applications, such as flood studies, require the use of long rainfall data at fine time scales varying from daily down to 1 min time step. However, in the real world there is limited availability of data at sub-hourly scales. To cope with this issue, stochastic disaggregation techniques are typically employed to produce possible, statistically consistent, rainfall events that aggregate up to the field data collected at coarser scales. A methodology for the stochastic disaggregation of rainfall at fine time scales was recently introduced, combining the Bartlett-Lewis process to generate rainfall events along with adjusting procedures to modify the lower-level variables (i.e., hourly) so as to be consistent with the higher-level one (i.e., daily). In the present paper, we extend the aforementioned scheme, initially designed and tested for the disaggregation of daily rainfall into hourly depths, for any sub-hourly time scale. In addition, we take advantage of the recent developments in Poisson-cluster processes incorporating in the methodology a Bartlett-Lewis model variant that introduces dependence between cell intensity and duration in order to capture the variability of rainfall at sub-hourly time scales. The disaggregation scheme is implemented in an R package, named HyetosMinute, to support disaggregation from daily down to 1-min time scale. The applicability of the methodology was assessed on a 5-min rainfall records collected in Bochum, Germany, comparing the performance of the above mentioned model variant against the original Bartlett-Lewis process (non-random with 5 parameters). The analysis shows that the disaggregation process reproduces adequately the most important statistical characteristics of rainfall at wide range of time scales, while the introduction of the model with dependent intensity-duration results in a better performance in terms of skewness, rainfall extremes and dry proportions.

  8. Modeling and forecasting rainfall patterns of southwest monsoons in North-East India as a SARIMA process

    Science.gov (United States)

    Narasimha Murthy, K. V.; Saravana, R.; Vijaya Kumar, K.

    2018-02-01

    Weather forecasting is an important issue in the field of meteorology all over the world. The pattern and amount of rainfall are the essential factors that affect agricultural systems. India experiences the precious Southwest monsoon season for four months from June to September. The present paper describes an empirical study for modeling and forecasting the time series of Southwest monsoon rainfall patterns in the North-East India. The Box-Jenkins Seasonal Autoregressive Integrated Moving Average (SARIMA) methodology has been adopted for model identification, diagnostic checking and forecasting for this region. The study has shown that the SARIMA (0, 1, 1) (1, 0, 1)4 model is appropriate for analyzing and forecasting the future rainfall patterns. The Analysis of Means (ANOM) is a useful alternative to the analysis of variance (ANOVA) for comparing the group of treatments to study the variations and critical comparisons of rainfall patterns in different months of the season.

  9. Development of a transient, lumped hydrologic model for geomorphologic units in a geomorphology based rainfall-runoff modelling framework

    Science.gov (United States)

    Vannametee, E.; Karssenberg, D.; Hendriks, M. R.; de Jong, S. M.; Bierkens, M. F. P.

    2010-05-01

    We propose a modelling framework for distributed hydrological modelling of 103-105 km2 catchments by discretizing the catchment in geomorphologic units. Each of these units is modelled using a lumped model representative for the processes in the unit. Here, we focus on the development and parameterization of this lumped model as a component of our framework. The development of the lumped model requires rainfall-runoff data for an extensive set of geomorphological units. Because such large observational data sets do not exist, we create artificial data. With a high-resolution, physically-based, rainfall-runoff model, we create artificial rainfall events and resulting hydrographs for an extensive set of different geomorphological units. This data set is used to identify the lumped model of geomorphologic units. The advantage of this approach is that it results in a lumped model with a physical basis, with representative parameters that can be derived from point-scale measurable physical parameters. The approach starts with the development of the high-resolution rainfall-runoff model that generates an artificial discharge dataset from rainfall inputs as a surrogate of a real-world dataset. The model is run for approximately 105 scenarios that describe different characteristics of rainfall, properties of the geomorphologic units (i.e. slope gradient, unit length and regolith properties), antecedent moisture conditions and flow patterns. For each scenario-run, the results of the high-resolution model (i.e. runoff and state variables) at selected simulation time steps are stored in a database. The second step is to develop the lumped model of a geomorphological unit. This forward model consists of a set of simple equations that calculate Hortonian runoff and state variables of the geomorphologic unit over time. The lumped model contains only three parameters: a ponding factor, a linear reservoir parameter, and a lag time. The model is capable of giving an appropriate

  10. Effects of land cover change on temperature and rainfall extremes in multi-model ensemble simulations

    Directory of Open Access Journals (Sweden)

    A. J. Pitman

    2012-11-01

    Full Text Available The impact of historical land use induced land cover change (LULCC on regional-scale climate extremes is examined using four climate models within the Land Use and Climate, IDentification of robust impacts project. To assess those impacts, multiple indices based on daily maximum and minimum temperatures and daily precipitation were used. We contrast the impact of LULCC on extremes with the impact of an increase in atmospheric CO2 from 280 ppmv to 375 ppmv. In general, consistent changes in both high and low temperature extremes are similar to the simulated change in mean temperature caused by LULCC and are restricted to regions of intense modification. The impact of LULCC on both means and on most temperature extremes is statistically significant. While the magnitude of the LULCC-induced change in the extremes can be of similar magnitude to the response to the change in CO2, the impacts of LULCC are much more geographically isolated. For most models, the impacts of LULCC oppose the impact of the increase in CO2 except for one model where the CO2-caused changes in the extremes are amplified. While we find some evidence that individual models respond consistently to LULCC in the simulation of changes in rainfall and rainfall extremes, LULCC's role in affecting rainfall is much less clear and less commonly statistically significant, with the exception of a consistent impact over South East Asia. Since the simulated response of mean and extreme temperatures to LULCC is relatively large, we conclude that unless this forcing is included, we risk erroneous conclusions regarding the drivers of temperature changes over regions of intense LULCC.

  11. A Merging Framework for Rainfall Estimation at High Spatiotemporal Resolution for Distributed Hydrological Modeling in a Data-Scarce Area

    Directory of Open Access Journals (Sweden)

    Yinping Long

    2016-07-01

    Full Text Available Merging satellite and rain gauge data by combining accurate quantitative rainfall from stations with spatial continuous information from remote sensing observations provides a practical method of estimating rainfall. However, generating high spatiotemporal rainfall fields for catchment-distributed hydrological modeling is a problem when only a sparse rain gauge network and coarse spatial resolution of satellite data are available. The objective of the study is to present a satellite and rain gauge data-merging framework adapting for coarse resolution and data-sparse designs. In the framework, a statistical spatial downscaling method based on the relationships among precipitation, topographical features, and weather conditions was used to downscale the 0.25° daily rainfall field derived from the Tropical Rainfall Measuring Mission (TRMM Multisatellite Precipitation Analysis (TMPA precipitation product version 7. The nonparametric merging technique of double kernel smoothing, adapting for data-sparse design, was combined with the global optimization method of shuffled complex evolution, to merge the downscaled TRMM and gauged rainfall with minimum cross-validation error. An indicator field representing the presence and absence of rainfall was generated using the indicator kriging technique and applied to the previously merged result to consider the spatial intermittency of daily rainfall. The framework was applied to estimate daily precipitation at a 1 km resolution in the Qinghai Lake Basin, a data-scarce area in the northeast of the Qinghai-Tibet Plateau. The final estimates not only captured the spatial pattern of daily and annual precipitation with a relatively small estimation error, but also performed very well in stream flow simulation when applied to force the geomorphology-based hydrological model (GBHM. The proposed framework thus appears feasible for rainfall estimation at high spatiotemporal resolution in data-scarce areas.

  12. Future climate scenarios and rainfall-runoff modelling in the Upper Gallego catchment (Spain)

    International Nuclear Information System (INIS)

    Buerger, C.M.; Kolditz, O.; Fowler, H.J.; Blenkinsop, S.

    2007-01-01

    Global climate change may have large impacts on water supplies, drought or flood frequencies and magnitudes in local and regional hydrologic systems. Water authorities therefore rely on computer models for quantitative impact prediction. In this study we present kernel-based learning machine river flow models for the Upper Gallego catchment of the Ebro basin. Different learning machines were calibrated using daily gauge data. The models posed two major challenges: (1) estimation of the rainfall-runoff transfer function from the available time series is complicated by anthropogenic regulation and mountainous terrain and (2) the river flow model is weak when only climate data are used, but additional antecedent flow data seemed to lead to delayed peak flow estimation. These types of models, together with the presented downscaled climate scenarios, can be used for climate change impact assessment in the Gallego, which is important for the future management of the system. - Future climate change and data-based rainfall-runoff predictions are presented for the Upper Gallego

  13. Numerical simulation of rainfall and temperature over Kenya using weather research and forecasting-environmental modelling system (WRF-EMS

    Directory of Open Access Journals (Sweden)

    Sagero Obaigwa Philip

    2016-01-01

    Full Text Available This paper focuses on one of the high resolution models used for weather forecasting at Kenya Meteorological Department (KMD. It reviews the skill and accuracy of the Weather Research and Forecasting (WRF - Environmental Modeling System (EMS model, in simulating weather over Kenya. The study period was March to May 2011, during the rainy season over Kenya. The model output was compared with the observed data from 27 synoptic stations spread over the study area, to determine the performance of the model in terms of its skill and accuracy in forecasting. The spatial distribution of rainfall and temperature showed that the WRF model was capable of reproducing the observed general pattern especially for temperature. The model has skill in forecasting both rainfall and temperature over the study area. However, the model may underestimate rainfall of more than 10 mm/day and displace its location and overestimate rainfall of less than 1 mm/day. Therefore, during the period of enhanced rainfall especially in the month of April and part of May the model forecast needs to be complemented by other models or forecasting methods before giving a forecast. There is need to improve its performance over the domain through review of the parameterization of small scale physical processes and more observed data need to be simulated into the model.

  14. The use of Mediterranean shrub to flight against the land degradation. The rainfall partitioning fluxes

    Science.gov (United States)

    García-Estringana, Pablo; Nieves Alonso-Blazquez, M.; Alegre, Jesús; Cerdà, Artemi

    2014-05-01

    Desertification can be triggered by the lost of vegetation (Izzo et al., 2013). One of the impacts of the lack of vegetation is the increase in the effective rainfall and then higher soil and water losses. Vegetation can reduce the effective rainfall by interception. To recover the land that is affected by Desertification we must select plant species that will intercept the rainfall, but will not avoid the rainfall to reach the soil. This is why, studies on the plant rainfall interception are relevant to flight Land Degradation processes. Soil erosion is highly dependent on the effective rainfall (Cerdà and Lasanta, 2005; Haile and Fetene; 2012; Miao et al., 2012, Prokop and Poręba, 2012). The amount of rainfall that reaches the soil surface and can contribute to detach and transport material is determined by the interception of plants. Interception is also a key factor of the watershed hydrology (Zema et al., 2012). The importance of the rainfall partitioning fluxes is related to the climatic conditions, as climate control the plant cover and the soil properties, and then the soil losses (Cerdà, 1998). Although the shrubs has been seen as a key vegetation cover in semiarid lands to control the soil and water losses (Cerdà and Doerr, 2007) little information is available about rainfall interception in Mediterranean shrub vegetation, due to technical difficulties to measure them in such small-sized vegetation (Belmonte Serrato and Romero Diaz, 1998). The aim of this work was to assess the influence of different Mediterranean shrubs (Retama sphaerocarpa, Colutea arborescens, Dorycnium pentaphyllum, Medicago strasseri, Pistacia Lentiscus and Quercus coccifera) on rainfall partitioning fluxes (interception losses, throughfall and stemflow) in semiarid environments. The experiment was carried out under natural rainfall conditions with live specimens during two years, with automatic measurement of rainfall partitioning fluxes. In order to assess the influence of

  15. Computer-aided mathematical analysis of probability of intercept for ground-based communication intercept system

    Science.gov (United States)

    Park, Sang Chul

    1989-09-01

    We develop a mathematical analysis model to calculate the probability of intercept (POI) for the ground-based communication intercept (COMINT) system. The POI is a measure of the effectiveness of the intercept system. We define the POI as the product of the probability of detection and the probability of coincidence. The probability of detection is a measure of the receiver's capability to detect a signal in the presence of noise. The probability of coincidence is the probability that an intercept system is available, actively listening in the proper frequency band, in the right direction and at the same time that the signal is received. We investigate the behavior of the POI with respect to the observation time, the separation distance, antenna elevations, the frequency of the signal, and the receiver bandwidths. We observe that the coincidence characteristic between the receiver scanning parameters and the signal parameters is the key factor to determine the time to obtain a given POI. This model can be used to find the optimal parameter combination to maximize the POI in a given scenario. We expand this model to a multiple system. This analysis is conducted on a personal computer to provide the portability. The model is also flexible and can be easily implemented under different situations.

  16. Adequacy of TRMM satellite rainfall data in driving the SWAT modeling of Tiaoxi catchment (Taihu lake basin, China)

    Science.gov (United States)

    Li, Dan; Christakos, George; Ding, Xinxin; Wu, Jiaping

    2018-01-01

    Spatial rainfall data is an essential input to Distributed Hydrological Models (DHM), and a significant contributor to hydrological model uncertainty. Model uncertainty is higher when rain gauges are sparse, as is often the case in practice. Currently, satellite-based precipitation products increasingly provide an alternative means to ground-based rainfall estimates, in which case a rigorous product assessment is required before implementation. Accordingly, the twofold objective of this work paper was the real-world assessment of both (a) the Tropical Rainfall Measuring Mission (TRMM) rainfall product using gauge data, and (b) the TRMM product's role in forcing data for hydrologic simulations in the area of the Tiaoxi catchment (Taihu lake basin, China). The TRMM rainfall products used in this study are the Version-7 real-time 3B42RT and the post-real-time 3B42. It was found that the TRMM rainfall data showed a superior performance at the monthly and annual scales, fitting well with surface observation-based frequency rainfall distributions. The Nash-Sutcliffe Coefficient of Efficiency (NSCE) and the relative bias ratio (BIAS) were used to evaluate hydrologic model performance. The satisfactory performance of the monthly runoff simulations in the Tiaoxi study supports the view that the implementation of real-time 3B42RT allows considerable room for improvement. At the same time, post-real-time 3B42 can be a valuable tool of hydrologic modeling, water balance analysis, and basin water resource management, especially in developing countries or at remote locations in which rainfall gauges are scarce.

  17. Drought Early Warning and Agro-Meteorological Risk Assessment using Earth Observation Rainfall Datasets and Crop Water Budget Modelling

    Science.gov (United States)

    Tarnavsky, E.

    2016-12-01

    The water resources satisfaction index (WRSI) model is widely used in drought early warning and food security analyses, as well as in agro-meteorological risk management through weather index-based insurance. Key driving data for the model is provided from satellite-based rainfall estimates such as ARC2 and TAMSAT over Africa and CHIRPS globally. We evaluate the performance of these rainfall datasets for detecting onset and cessation of rainfall and estimating crop production conditions for the WRSI model. We also examine the sensitivity of the WRSI model to different satellite-based rainfall products over maize growing regions in Tanzania. Our study considers planting scenarios for short-, medium-, and long-growing cycle maize, and we apply these for 'regular' and drought-resistant maize, as well as with two different methods for defining the start of season (SOS). Simulated maize production estimates are compared against available reported production figures at the national and sub-national (province) levels. Strengths and weaknesses of the driving rainfall data, insights into the role of the SOS definition method, and phenology-based crop yield coefficient and crop yield reduction functions are discussed in the context of space-time drought characteristics. We propose a way forward for selecting skilled rainfall datasets and discuss their implication for crop production monitoring and the design and structure of weather index-based insurance products as risk transfer mechanisms implemented across scales for smallholder farmers to national programmes.

  18. Estimation of Areal Mean Rainfall in Remote Areas Using B-SHADE Model

    Directory of Open Access Journals (Sweden)

    Tao Zhang

    2016-01-01

    Full Text Available This study presented a method to estimate areal mean rainfall (AMR using a Biased Sentinel Hospital Based Area Disease Estimation (B-SHADE model, together with biased rain gauge observations and Tropical Rainfall Measuring Mission (TRMM data, for remote areas with a sparse and uneven distribution of rain gauges. Based on the B-SHADE model, the best linear unbiased estimation of AMR could be obtained. A case study was conducted for the Three-River Headwaters region in the Tibetan Plateau of China, and its performance was compared with traditional methods. The results indicated that B-SHADE obtained the least estimation biases, with a mean error and root mean square error of −0.63 and 3.48 mm, respectively. For the traditional methods including arithmetic average, Thiessen polygon, and ordinary kriging, the mean errors were 7.11, −1.43, and 2.89 mm, which were up to 1027.1%, 127.0%, and 358.3%, respectively, greater than for the B-SHADE model. The root mean square errors were 10.31, 4.02, and 6.27 mm, which were up to 196.1%, 15.5%, and 80.0%, respectively, higher than for the B-SHADE model. The proposed technique can be used to extend the AMR record to the presatellite observation period, when only the gauge data are available.

  19. Comparing Satellite Rainfall Estimates with Rain-Gauge Data: Optimal Strategies Suggested by a Spectral Model

    Science.gov (United States)

    Bell, Thomas L.; Kundu, Prasun K.; Lau, William K. M. (Technical Monitor)

    2002-01-01

    Validation of satellite remote-sensing methods for estimating rainfall against rain-gauge data is attractive because of the direct nature of the rain-gauge measurements. Comparisons of satellite estimates to rain-gauge data are difficult, however, because of the extreme variability of rain and the fact that satellites view large areas over a short time while rain gauges monitor small areas continuously. In this paper, a statistical model of rainfall variability developed for studies of sampling error in averages of satellite data is used to examine the impact of spatial and temporal averaging of satellite and gauge data on intercomparison results. The model parameters were derived from radar observations of rain, but the model appears to capture many of the characteristics of rain-gauge data as well. The model predicts that many months of data from areas containing a few gauges are required to validate satellite estimates over the areas, and that the areas should be of the order of several hundred km in diameter. Over gauge arrays of sufficiently high density, the optimal areas and averaging times are reduced. The possibility of using time-weighted averages of gauge data is explored.

  20. An investigation of the effect of hysteresis in a simple rainfall-runoff model

    Science.gov (United States)

    Flynn, D. P.; O'Kane, J. P.

    2009-04-01

    Multiphase porous media such as soils are known to exhibit hysteresis, e.g. in soils there is a strong hysteretic relationship between the moisture content and the matric potential and to date the Preisach model has been successful in modelling this relationship. Subsequently ODEs with Preisach hysteresis have been developed, such as a hysteretic version of Darcy's law and a hysteretic version of the linear reservoir known as the Preisach reservoir. In this paper we combine the above Hysteretic Differential Equations (HDEs) with three linear reservoirs so as to develop a simple rainfall runoff model. The model can be represented by a block diagram: Rainfall q(t) enters the soil component and either infiltrates and/or runs off when it exceeds the maximum rate of infiltration. The runoff part is fed into two linear reservoirs in series. Next, the drainage from the soil to groundwater is represented by a single linear reservoir, where the output from the soil becomes the input to the ground reservoir and vice-versa for capillary rise. Finally the groundwater and surface runoff are combined at some point and contribute to the total outflow from the catchment. Finally we investigate the effects of hysteresis in this system and compare it to the non-hysteretic case.

  1. Application of a probabilistic model of rainfall-induced shallow landslides to complex hollows

    Directory of Open Access Journals (Sweden)

    A. Talebi

    2008-07-01

    Full Text Available Recently, D'Odorico and Fagherazzi (2003 proposed "A probabilistic model of rainfall-triggered shallow landslides in hollows" (Water Resour. Res., 39, 2003. Their model describes the long-term evolution of colluvial deposits through a probabilistic soil mass balance at a point. Further building blocks of the model are: an infinite-slope stability analysis; a steady-state kinematic wave model (KW of hollow groundwater hydrology; and a statistical model relating intensity, duration, and frequency of extreme precipitation. Here we extend the work of D'Odorico and Fagherazzi (2003 by incorporating a more realistic description of hollow hydrology (hillslope storage Boussinesq model, HSB such that this model can also be applied to more gentle slopes and hollows with different plan shapes. We show that results obtained using the KW and HSB models are significantly different as in the KW model the diffusion term is ignored. We generalize our results by examining the stability of several hollow types with different plan shapes (different convergence degree. For each hollow type, the minimum value of the landslide-triggering saturated depth corresponding to the triggering precipitation (critical recharge rate is computed for steep and gentle hollows. Long term analysis of shallow landslides by the presented model illustrates that all hollows show a quite different behavior from the stability view point. In hollows with more convergence, landslide occurrence is limited by the supply of deposits (supply limited regime or rainfall events (event limited regime while hollows with low convergence degree are unconditionally stable regardless of the soil thickness or rainfall intensity. Overall, our results show that in addition to the effect of slope angle, plan shape (convergence degree also controls the subsurface flow and this process affects the probability distribution of landslide occurrence in different hollows. Finally, we conclude that

  2. Application of random number generators in genetic algorithms to improve rainfall-runoff modelling

    Czech Academy of Sciences Publication Activity Database

    Chlumecký, M.; Buchtele, Josef; Richta, K.

    2017-01-01

    Roč. 553, October (2017), s. 350-355 ISSN 0022-1694 Institutional support: RVO:67985874 Keywords : genetic algorithm * optimisation * rainfall-runoff modeling * random generator Subject RIV: DA - Hydrology ; Limnology OBOR OECD: Hydrology Impact factor: 3.483, year: 2016 https://ac.els-cdn.com/S0022169417305516/1-s2.0-S0022169417305516-main.pdf?_tid=fa1bad8a-bd6a-11e7-8567-00000aab0f27&acdnat=1509365462_a1335d3d997e9eab19e23b1eee977705

  3. Applying volumetric weather radar data for rainfall runoff modeling: The importance of error correction.

    Science.gov (United States)

    Hazenberg, P.; Leijnse, H.; Uijlenhoet, R.; Delobbe, L.; Weerts, A.; Reggiani, P.

    2009-04-01

    In the current study half a year of volumetric radar data for the period October 1, 2002 until March 31, 2003 is being analyzed which was sampled at 5 minutes intervals by C-band Doppler radar situated at an elevation of 600 m in the southern Ardennes region, Belgium. During this winter half year most of the rainfall has a stratiform character. Though radar and raingauge will never sample the same amount of rainfall due to differences in sampling strategies, for these stratiform situations differences between both measuring devices become even larger due to the occurrence of a bright band (the point where ice particles start to melt intensifying the radar reflectivity measurement). For these circumstances the radar overestimates the amount of precipitation and because in the Ardennes bright bands occur within 1000 meter from the surface, it's detrimental effects on the performance of the radar can already be observed at relatively close range (e.g. within 50 km). Although the radar is situated at one of the highest points in the region, very close to the radar clutter is a serious problem. As a result both nearby and farther away, using uncorrected radar results in serious errors when estimating the amount of precipitation. This study shows the effect of carefully correcting for these radar errors using volumetric radar data, taking into account the vertical reflectivity profile of the atmosphere, the effects of attenuation and trying to limit the amount of clutter. After applying these correction algorithms, the overall differences between radar and raingauge are much smaller which emphasizes the importance of carefully correcting radar rainfall measurements. The next step is to assess the effect of using uncorrected and corrected radar measurements on rainfall-runoff modeling. The 1597 km2 Ourthe catchment lies within 60 km of the radar. Using a lumped hydrological model serious improvement in simulating observed discharges is found when using corrected radar

  4. Rainfall-induced fecal indicator organisms transport from manured fields: model sensitivity analysis.

    Science.gov (United States)

    Martinez, Gonzalo; Pachepsky, Yakov A; Whelan, Gene; Yakirevich, Alexander M; Guber, Andrey; Gish, Timothy J

    2014-02-01

    Microbial quality of surface waters attracts attention due to food- and waterborne disease outbreaks. Fecal indicator organisms (FIOs) are commonly used for the microbial pollution level evaluation. Models predicting the fate and transport of FIOs are required to design and evaluate best management practices that reduce the microbial pollution in ecosystems and water sources and thus help to predict the risk of food and waterborne diseases. In this study we performed a sensitivity analysis for the KINEROS/STWIR model developed to predict the FIOs transport out of manured fields to other fields and water bodies in order to identify input variables that control the transport uncertainty. The distributions of model input parameters were set to encompass values found from three-year experiments at the USDA-ARS OPE3 experimental site in Beltsville and publicly available information. Sobol' indices and complementary regression trees were used to perform the global sensitivity analysis of the model and to explore the interactions between model input parameters on the proportion of FIO removed from fields. Regression trees provided a useful visualization of the differences in sensitivity of the model output in different parts of the input variable domain. Environmental controls such as soil saturation, rainfall duration and rainfall intensity had the largest influence in the model behavior, whereas soil and manure properties ranked lower. The field length had only moderate effect on the model output sensitivity to the model inputs. Among the manure-related properties the parameter determining the shape of the FIO release kinetic curve had the largest influence on the removal of FIOs from the fields. That underscored the need to better characterize the FIO release kinetics. Since the most sensitive model inputs are available in soil and weather databases or can be obtained using soil water models, results indicate the opportunity of obtaining large-scale estimates of FIO

  5. Verification of the skill of numerical weather prediction models in forecasting rainfall from U.S. landfalling tropical cyclones

    Science.gov (United States)

    Luitel, Beda; Villarini, Gabriele; Vecchi, Gabriel A.

    2018-01-01

    The goal of this study is the evaluation of the skill of five state-of-the-art numerical weather prediction (NWP) systems [European Centre for Medium-Range Weather Forecasts (ECMWF), UK Met Office (UKMO), National Centers for Environmental Prediction (NCEP), China Meteorological Administration (CMA), and Canadian Meteorological Center (CMC)] in forecasting rainfall from North Atlantic tropical cyclones (TCs). Analyses focus on 15 North Atlantic TCs that made landfall along the U.S. coast over the 2007-2012 period. As reference data we use gridded rainfall provided by the Climate Prediction Center (CPC). We consider forecast lead-times up to five days. To benchmark the skill of these models, we consider rainfall estimates from one radar-based (Stage IV) and four satellite-based [Tropical Rainfall Measuring Mission - Multi-satellite Precipitation Analysis (TMPA, both real-time and research version); Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN); the CPC MORPHing Technique (CMORPH)] rainfall products. Daily and storm total rainfall fields from each of these remote sensing products are compared to the reference data to obtain information about the range of errors we can expect from "observational data." The skill of the NWP models is quantified: (1) by visual examination of the distribution of the errors in storm total rainfall for the different lead-times, and numerical examination of the first three moments of the error distribution; (2) relative to climatology at the daily scale. Considering these skill metrics, we conclude that the NWP models can provide skillful forecasts of TC rainfall with lead-times up to 48 h, without a consistently best or worst NWP model.

  6. Assimilating satellite soil moisture into rainfall-runoff modelling: towards a systematic study

    Science.gov (United States)

    Massari, Christian; Tarpanelli, Angelica; Brocca, Luca; Moramarco, Tommaso

    2015-04-01

    Soil moisture is the main factor for the repartition of the mass and energy fluxes between the land surface and the atmosphere thus playing a fundamental role in the hydrological cycle. Indeed, soil moisture represents the initial condition of rainfall-runoff modelling that determines the flood response of a catchment. Different initial soil moisture conditions can discriminate between catastrophic and minor effects of a given rainfall event. Therefore, improving the estimation of initial soil moisture conditions will reduce uncertainties in early warning flood forecasting models addressing the mitigation of flood hazard. In recent years, satellite soil moisture products have become available with fine spatial-temporal resolution and a good accuracy. Therefore, a number of studies have been published in which the impact of the assimilation of satellite soil moisture data into rainfall-runoff modelling is investigated. Unfortunately, data assimilation involves a series of assumptions and choices that significantly affect the final result. Given a satellite soil moisture observation, a rainfall-runoff model and a data assimilation technique, an improvement or a deterioration of discharge predictions can be obtained depending on the choices made in the data assimilation procedure. Consequently, large discrepancies have been obtained in the studies published so far likely due to the differences in the implementation of the data assimilation technique. On this basis, a comprehensive and robust procedure for the assimilation of satellite soil moisture data into rainfall-runoff modelling is developed here and applied to six subcatchment of the Upper Tiber River Basin for which high-quality hydrometeorological hourly observations are available in the period 1989-2013. The satellite soil moisture product used in this study is obtained from the Advanced SCATterometer (ASCAT) onboard Metop-A satellite and it is available since 2007. The MISDc ("Modello Idrologico Semi

  7. Copula-based model for rainfall and El- Niño in Banyuwangi Indonesia

    Science.gov (United States)

    Caraka, R. E.; Supari; Tahmid, M.

    2018-04-01

    Modelling, describing and measuring the structure dependences between different random events is at the very heart of statistics. Therefore, a broad variety of varying dependence concepts has been developed in the past. Most often, practitioners rely only on the linear correlation to describe the degree of dependence between two or more variables; an approach that can lead to quite misleading conclusions as this measure is only capable of capturing linear relationships. Copulas go beyond dependence measures and provide a sound framework for general dependence modelling. This paper will introduce an application of Copula to estimate, understand, and interpret the dependence structure in a given set of data El-Niño in Banyuwangi, Indonesia. In a nutshell, we proved the flexibility of Copulas Archimedean in rainfall modelling and catching phenomena of El Niño in Banyuwangi, East Java, Indonesia. Also, it was found that SST of nino3, nino4, and nino3.4 are most appropriate ENSO indicators in identifying the relationship of El Nino and rainfall.

  8. A hybrid hydrologically complemented warning model for shallow landslides induced by extreme rainfall in Korean Mountain

    Science.gov (United States)

    Singh Pradhan, Ananta Man; Kang, Hyo-Sub; Kim, Yun-Tae

    2016-04-01

    This study uses a physically based approach to evaluate the factor of safety of the hillslope for different hydrological conditions, in Mt Umyeon, south of Seoul. The hydrological conditions were determined using intensity and duration of whole Korea of known landslide inventory data. Quantile regression statistical method was used to ascertain different probability warning levels on the basis of rainfall thresholds. Physically based models are easily interpreted and have high predictive capabilities but rely on spatially explicit and accurate parameterization, which is commonly not possible. Statistical probabilistic methods can include other causative factors which influence the slope stability such as forest, soil and geology, but rely on good landslide inventories of the site. In this study a hybrid approach has described that combines the physically-based landslide susceptibility for different hydrological conditions. A presence-only based maximum entropy model was used to hybrid and analyze relation of landslide with conditioning factors. About 80% of the landslides were listed among the unstable sites identified in the proposed model, thereby presenting its effectiveness and accuracy in determining unstable areas and areas that require evacuation. These cumulative rainfall thresholds provide a valuable reference to guide disaster prevention authorities in the issuance of warning levels with the ability to reduce losses and save lives.

  9. Integrating a Linear Signal Model with Groundwater and Rainfall time-series on the Characteristic Identification of Groundwater Systems

    Science.gov (United States)

    Chen, Yu-Wen; Wang, Yetmen; Chang, Liang-Cheng

    2017-04-01

    Groundwater resources play a vital role on regional supply. To avoid irreversible environmental impact such as land subsidence, the characteristic identification of groundwater system is crucial before sustainable management of groundwater resource. This study proposes a signal process approach to identify the character of groundwater systems based on long-time hydrologic observations include groundwater level and rainfall. The study process contains two steps. First, a linear signal model (LSM) is constructed and calibrated to simulate the variation of underground hydrology based on the time series of groundwater levels and rainfall. The mass balance equation of the proposed LSM contains three major terms contain net rate of horizontal exchange, rate of rainfall recharge and rate of pumpage and four parameters are required to calibrate. Because reliable records of pumpage is rare, the time-variant groundwater amplitudes of daily frequency (P ) calculated by STFT are assumed as linear indicators of puamage instead of pumpage records. Time series obtained from 39 observation wells and 50 rainfall stations in and around the study area, Pintung Plain, are paired for model construction. Second, the well-calibrated parameters of the linear signal model can be used to interpret the characteristic of groundwater system. For example, the rainfall recharge coefficient (γ) means the transform ratio between rainfall intention and groundwater level raise. The area around the observation well with higher γ means that the saturated zone here is easily affected by rainfall events and the material of unsaturated zone might be gravel or coarse sand with high infiltration ratio. Considering the spatial distribution of γ, the values of γ decrease from the upstream to the downstream of major rivers and also are correlated to the spatial distribution of grain size of surface soil. Via the time-series of groundwater levels and rainfall, the well-calibrated parameters of LSM have

  10. A physics-based probabilistic forecasting model for rainfall-induced shallow landslides at regional scale

    Directory of Open Access Journals (Sweden)

    S. Zhang

    2018-03-01

    Full Text Available Conventional outputs of physics-based landslide forecasting models are presented as deterministic warnings by calculating the safety factor (Fs of potentially dangerous slopes. However, these models are highly dependent on variables such as cohesion force and internal friction angle which are affected by a high degree of uncertainty especially at a regional scale, resulting in unacceptable uncertainties of Fs. Under such circumstances, the outputs of physical models are more suitable if presented in the form of landslide probability values. In order to develop such models, a method to link the uncertainty of soil parameter values with landslide probability is devised. This paper proposes the use of Monte Carlo methods to quantitatively express uncertainty by assigning random values to physical variables inside a defined interval. The inequality Fs < 1 is tested for each pixel in n simulations which are integrated in a unique parameter. This parameter links the landslide probability to the uncertainties of soil mechanical parameters and is used to create a physics-based probabilistic forecasting model for rainfall-induced shallow landslides. The prediction ability of this model was tested in a case study, in which simulated forecasting of landslide disasters associated with heavy rainfalls on 9 July 2013 in the Wenchuan earthquake region of Sichuan province, China, was performed. The proposed model successfully forecasted landslides in 159 of the 176 disaster points registered by the geo-environmental monitoring station of Sichuan province. Such testing results indicate that the new model can be operated in a highly efficient way and show more reliable results, attributable to its high prediction accuracy. Accordingly, the new model can be potentially packaged into a forecasting system for shallow landslides providing technological support for the mitigation of these disasters at regional scale.

  11. A physics-based probabilistic forecasting model for rainfall-induced shallow landslides at regional scale

    Science.gov (United States)

    Zhang, Shaojie; Zhao, Luqiang; Delgado-Tellez, Ricardo; Bao, Hongjun

    2018-03-01

    Conventional outputs of physics-based landslide forecasting models are presented as deterministic warnings by calculating the safety factor (Fs) of potentially dangerous slopes. However, these models are highly dependent on variables such as cohesion force and internal friction angle which are affected by a high degree of uncertainty especially at a regional scale, resulting in unacceptable uncertainties of Fs. Under such circumstances, the outputs of physical models are more suitable if presented in the form of landslide probability values. In order to develop such models, a method to link the uncertainty of soil parameter values with landslide probability is devised. This paper proposes the use of Monte Carlo methods to quantitatively express uncertainty by assigning random values to physical variables inside a defined interval. The inequality Fs soil mechanical parameters and is used to create a physics-based probabilistic forecasting model for rainfall-induced shallow landslides. The prediction ability of this model was tested in a case study, in which simulated forecasting of landslide disasters associated with heavy rainfalls on 9 July 2013 in the Wenchuan earthquake region of Sichuan province, China, was performed. The proposed model successfully forecasted landslides in 159 of the 176 disaster points registered by the geo-environmental monitoring station of Sichuan province. Such testing results indicate that the new model can be operated in a highly efficient way and show more reliable results, attributable to its high prediction accuracy. Accordingly, the new model can be potentially packaged into a forecasting system for shallow landslides providing technological support for the mitigation of these disasters at regional scale.

  12. A Stochastic Model of Space-Time Variability of Tropical Rainfall: I. Statistics of Spatial Averages

    Science.gov (United States)

    Kundu, Prasun K.; Bell, Thomas L.; Lau, William K. M. (Technical Monitor)

    2002-01-01

    Global maps of rainfall are of great importance in connection with modeling of the earth s climate. Comparison between the maps of rainfall predicted by computer-generated climate models with observation provides a sensitive test for these models. To make such a comparison, one typically needs the total precipitation amount over a large area, which could be hundreds of kilometers in size over extended periods of time of order days or months. This presents a difficult problem since rain varies greatly from place to place as well as in time. Remote sensing methods using ground radar or satellites detect rain over a large area by essentially taking a series of snapshots at infrequent intervals and indirectly deriving the average rain intensity within a collection of pixels , usually several kilometers in size. They measure area average of rain at a particular instant. Rain gauges, on the other hand, record rain accumulation continuously in time but only over a very small area tens of centimeters across, say, the size of a dinner plate. They measure only a time average at a single location. In making use of either method one needs to fill in the gaps in the observation - either the gaps in the area covered or the gaps in time of observation. This involves using statistical models to obtain information about the rain that is missed from what is actually detected. This paper investigates such a statistical model and validates it with rain data collected over the tropical Western Pacific from ship borne radars during TOGA COARE (Tropical Oceans Global Atmosphere Coupled Ocean-Atmosphere Response Experiment). The model incorporates a number of commonly observed features of rain. While rain varies rapidly with location and time, the variability diminishes when averaged over larger areas or longer periods of time. Moreover, rain is patchy in nature - at any instant on the average only a certain fraction of the observed pixels contain rain. The fraction of area covered by

  13. Multifractality, imperfect scaling and hydrological properties of rainfall time series simulated by continuous universal multifractal and discrete random cascade models

    Directory of Open Access Journals (Sweden)

    F. Serinaldi

    2010-12-01

    Full Text Available Discrete multiplicative random cascade (MRC models were extensively studied and applied to disaggregate rainfall data, thanks to their formal simplicity and the small number of involved parameters. Focusing on temporal disaggregation, the rationale of these models is based on multiplying the value assumed by a physical attribute (e.g., rainfall intensity at a given time scale L, by a suitable number b of random weights, to obtain b attribute values corresponding to statistically plausible observations at a smaller L/b time resolution. In the original formulation of the MRC models, the random weights were assumed to be independent and identically distributed. However, for several studies this hypothesis did not appear to be realistic for the observed rainfall series as the distribution of the weights was shown to depend on the space-time scale and rainfall intensity. Since these findings contrast with the scale invariance assumption behind the MRC models and impact on the applicability of these models, it is worth studying their nature. This study explores the possible presence of dependence of the parameters of two discrete MRC models on rainfall intensity and time scale, by analyzing point rainfall series with 5-min time resolution. Taking into account a discrete microcanonical (MC model based on beta distribution and a discrete canonical beta-logstable (BLS, the analysis points out that the relations between the parameters and rainfall intensity across the time scales are detectable and can be modeled by a set of simple functions accounting for the parameter-rainfall intensity relationship, and another set describing the link between the parameters and the time scale. Therefore, MC and BLS models were modified to explicitly account for these relationships and compared with the continuous in scale universal multifractal (CUM model, which is used as a physically based benchmark model. Monte Carlo simulations point out

  14. Bayesian uncertainty assessment of flood predictions in ungauged urban basins for conceptual rainfall-runoff models

    Directory of Open Access Journals (Sweden)

    A. E. Sikorska

    2012-04-01

    Full Text Available Urbanization and the resulting land-use change strongly affect the water cycle and runoff-processes in watersheds. Unfortunately, small urban watersheds, which are most affected by urban sprawl, are mostly ungauged. This makes it intrinsically difficult to assess the consequences of urbanization. Most of all, it is unclear how to reliably assess the predictive uncertainty given the structural deficits of the applied models. In this study, we therefore investigate the uncertainty of flood predictions in ungauged urban basins from structurally uncertain rainfall-runoff models. To this end, we suggest a procedure to explicitly account for input uncertainty and model structure deficits using Bayesian statistics with a continuous-time autoregressive error model. In addition, we propose a concise procedure to derive prior parameter distributions from base data and successfully apply the methodology to an urban catchment in Warsaw, Poland. Based on our results, we are able to demonstrate that the autoregressive error model greatly helps to meet the statistical assumptions and to compute reliable prediction intervals. In our study, we found that predicted peak flows were up to 7 times higher than observations. This was reduced to 5 times with Bayesian updating, using only few discharge measurements. In addition, our analysis suggests that imprecise rainfall information and model structure deficits contribute mostly to the total prediction uncertainty. In the future, flood predictions in ungauged basins will become more important due to ongoing urbanization as well as anthropogenic and climatic changes. Thus, providing reliable measures of uncertainty is crucial to support decision making.

  15. Modeling regional initiation of rainfall-induced shallow landslides in the eastern Umbria Region of central Italy

    Science.gov (United States)

    Salciarini, D.; Godt, J.W.; Savage, W.Z.; Conversini, P.; Baum, R.L.; Michael, J.A.

    2006-01-01

    We model the rainfall-induced initiation of shallow landslides over a broad region using a deterministic approach, the Transient Rainfall Infiltration and Grid-based Slope-stability (TRIGRS) model that couples an infinite-slope stability analysis with a one-dimensional analytical solution for transient pore pressure response to rainfall infiltration. This model permits the evaluation of regional shallow landslide susceptibility in a Geographic Information System framework, and we use it to analyze susceptibility to shallow landslides in an area in the eastern Umbria Region of central Italy. As shown on a landslide inventory map produced by the Italian National Research Council, the area has been affected in the past by shallow landslides, many of which have transformed into debris flows. Input data for the TRIGRS model include time-varying rainfall, topographic slope, colluvial thickness, initial water table depth, and material strength and hydraulic properties. Because of a paucity of input data, we focus on parametric analyses to calibrate and test the model and show the effect of variation in material properties and initial water table conditions on the distribution of simulated instability in the study area in response to realistic rainfall. Comparing the results with the shallow landslide inventory map, we find more than 80% agreement between predicted shallow landslide susceptibility and the inventory, despite the paucity of input data.

  16. Application of a satellite based rainfall - runoff model : a case study of the Trans Boundary Cuvelai Basin in Southern Africa

    NARCIS (Netherlands)

    Mufeti, P.; Rientjes, T.H.M.; Mabande, P.; Maathuis, B.H.P.

    2013-01-01

    Applications of distributed hydrological models are often constrained by poor data availability. Models rely on distributed inputs for meteorological forcing and land surface parameterization. In this pilot the rainfall runoff model LISFLOOD for large scale streamflow simulation is tested for the

  17. Indian Summer Monsoon Sub-seasonal Low-Level Circulation Predictability and its Association with Rainfall in a Coupled Model

    KAUST Repository

    Sagalgile, Archana P.

    2017-10-26

    This study investigates predictability of the sub-seasonal Indian summer monsoon (ISM) circulation and its relation with rainfall variations in the coupled model National Centers for Environmental Prediction (NCEP) Climate Forecast System version 2 (CFSv2). Hindcasts based on CFSv2 for the period of 1982–2009 are used for detailed analysis. Though the model is capable of predicting the seasonal ISM rainfall at long lead months, the predication skill of the model for sub-seasonal rainfall in general is poor for short and long lead except for September. Rainfall over the ISM region/Indian Subcontinent is highly correlated with the low-level jet (LLJ) or Somali jet both in the observations and the model. The model displays improved skill in predicting LLJ as compared to precipitation in seasonal mean and September, whereas the model skill is poor for June and August. Detailed analysis reveals that the model LLJ variations throughout the season are overdependent on the El Niño-Southern Oscillation (ENSO) unlike in the observations. This is mainly responsible for the model’s low skill in predicting LLJ especially in July and August, which is the primary cause for the poor rainfall skill. Though LLJ is weak in September, the model skill is reasonably good because of its ENSO dependency both in model and the observations and which is contributed to the seasonal mean skill. Thus, to improve the skill of seasonal mean monsoon forecast, it is essential to improve the skill of individual months/sub-seasonal circulation and rainfall skill.

  18. Indian Summer Monsoon Sub-seasonal Low-Level Circulation Predictability and its Association with Rainfall in a Coupled Model

    KAUST Repository

    Sagalgile, Archana P.; Chowdary, Jasti S.; Srinivas, G.; Gnanaseelan, C.; Parekh, Anant; Attada, Raju; Singh, Prem

    2017-01-01

    This study investigates predictability of the sub-seasonal Indian summer monsoon (ISM) circulation and its relation with rainfall variations in the coupled model National Centers for Environmental Prediction (NCEP) Climate Forecast System version 2 (CFSv2). Hindcasts based on CFSv2 for the period of 1982–2009 are used for detailed analysis. Though the model is capable of predicting the seasonal ISM rainfall at long lead months, the predication skill of the model for sub-seasonal rainfall in general is poor for short and long lead except for September. Rainfall over the ISM region/Indian Subcontinent is highly correlated with the low-level jet (LLJ) or Somali jet both in the observations and the model. The model displays improved skill in predicting LLJ as compared to precipitation in seasonal mean and September, whereas the model skill is poor for June and August. Detailed analysis reveals that the model LLJ variations throughout the season are overdependent on the El Niño-Southern Oscillation (ENSO) unlike in the observations. This is mainly responsible for the model’s low skill in predicting LLJ especially in July and August, which is the primary cause for the poor rainfall skill. Though LLJ is weak in September, the model skill is reasonably good because of its ENSO dependency both in model and the observations and which is contributed to the seasonal mean skill. Thus, to improve the skill of seasonal mean monsoon forecast, it is essential to improve the skill of individual months/sub-seasonal circulation and rainfall skill.

  19. Flood modelling with a distributed event-based parsimonious rainfall-runoff model: case of the karstic Lez river catchment

    Directory of Open Access Journals (Sweden)

    M. Coustau

    2012-04-01

    Full Text Available Rainfall-runoff models are crucial tools for the statistical prediction of flash floods and real-time forecasting. This paper focuses on a karstic basin in the South of France and proposes a distributed parsimonious event-based rainfall-runoff model, coherent with the poor knowledge of both evaporative and underground fluxes. The model combines a SCS runoff model and a Lag and Route routing model for each cell of a regular grid mesh. The efficiency of the model is discussed not only to satisfactorily simulate floods but also to get powerful relationships between the initial condition of the model and various predictors of the initial wetness state of the basin, such as the base flow, the Hu2 index from the Meteo-France SIM model and the piezometric levels of the aquifer. The advantage of using meteorological radar rainfall in flood modelling is also assessed. Model calibration proved to be satisfactory by using an hourly time step with Nash criterion values, ranging between 0.66 and 0.94 for eighteen of the twenty-one selected events. The radar rainfall inputs significantly improved the simulations or the assessment of the initial condition of the model for 5 events at the beginning of autumn, mostly in September–October (mean improvement of Nash is 0.09; correction in the initial condition ranges from −205 to 124 mm, but were less efficient for the events at the end of autumn. In this period, the weak vertical extension of the precipitation system and the low altitude of the 0 °C isotherm could affect the efficiency of radar measurements due to the distance between the basin and the radar (~60 km. The model initial condition S is correlated with the three tested predictors (R2 > 0.6. The interpretation of the model suggests that groundwater does not affect the first peaks of the flood, but can strongly impact subsequent peaks in the case of a multi-storm event. Because this kind of model is based on a limited

  20. Rainfall-runoff model for prediction of waterborne viral contamination in a small river catchment

    Science.gov (United States)

    Gelati, E.; Dommar, C.; Lowe, R.; Polcher, J.; Rodó, X.

    2013-12-01

    We present a lumped rainfall-runoff model aimed at providing useful information for the prediction of waterborne viral contamination in small rivers. Viral contamination of water bodies may occur because of the discharge of sewage effluents and of surface runoff over areas affected by animal waste loads. Surface runoff is caused by precipitation that cannot infiltrate due to its intensity and to antecedent soil water content. It may transport animal feces to adjacent water bodies and cause viral contamination. We model streamflow by separating it into two components: subsurface flow, which is produced by infiltrated precipitation; and surface runoff. The model estimates infiltrated and non-infiltrated precipitation and uses impulse-response functions to compute the corresponding fractions of streamflow. The developed methodologies are applied to the Glafkos river, whose catchment extends for 102 km2 and includes the city of Patra. Streamflow and precipitation observations are available at a daily time resolution. Waterborne virus concentration measurements were performed approximately every second week from the beginning of 2011 to mid 2012. Samples were taken at several locations: in river water upstream of Patras and in the urban area; in sea water at the river outlet and approximately 2 km south-west of Patras; in sewage effluents before and after treatment. The rainfall-runoff model was calibrated and validated using observed streamflow and precipitation data. The model contribution to waterborne viral contamination prediction was benchmarked by analyzing the virus concentration measurements together with the estimated surface runoff values. The presented methodology may be a first step towards the development of waterborne viral contamination alert systems. Predicting viral contamination of water bodies would benefit sectors such as water supply and tourism.

  1. Causes and Model Skill of the Persistent Intense Rainfall and Flooding in Paraguay during the Austral Summer 2015-2016

    Science.gov (United States)

    Doss-Gollin, J.; Munoz, A. G.; Pastén, M.

    2017-12-01

    During the austral summer 2015-16 severe flooding displaced over 150,000 people on the Paraguay River system in Paraguay, Argentina, and Southern Brazil. This flooding was out of phase with the typical seasonal cycle of the Paraguay River, and was driven by repeated intense rainfall events in the Lower Paraguay River basin. Using a weather typing approach within a diagnostic framework, we show that enhanced moisture inflow from the low-level jet and local convergence associated with baroclinic systems favored the development of mesoscale convective activity and enhanced precipitation. The observed circulation patterns were made more likely by the cross-timescale interactions of multiple climate mechanisms including the strong, mature El Niño event and an active Madden-Julien Oscillation in phases four and five. We also perform a comparison of the rainfall predictability using seasonal forecasts from the Latin American Observatory of Climate Events (OLE2) and sub-seasonal forecasts produced by the ECMWF. We find that the model output precipitation field exhibited limited skill at lead times beyond the synoptic timescale, but that a Model Output Statistics (MOS) approach, in which the leading principal components of the observed rainfall field are regressed on the leading principal components of model-simulated rainfall fields, substantially improves spatial representation of rainfall forecasts. Possible implications for flood preparedness are briefly discussed.

  2. Impact of Assimilation on Heavy Rainfall Simulations Using WRF Model: Sensitivity of Assimilation Results to Background Error Statistics

    Science.gov (United States)

    Rakesh, V.; Kantharao, B.

    2017-03-01

    Data assimilation is considered as one of the effective tools for improving forecast skill of mesoscale models. However, for optimum utilization and effective assimilation of observations, many factors need to be taken into account while designing data assimilation methodology. One of the critical components that determines the amount and propagation observation information into the analysis, is model background error statistics (BES). The objective of this study is to quantify how BES in data assimilation impacts on simulation of heavy rainfall events over a southern state in India, Karnataka. Simulations of 40 heavy rainfall events were carried out using Weather Research and Forecasting Model with and without data assimilation. The assimilation experiments were conducted using global and regional BES while the experiment with no assimilation was used as the baseline for assessing the impact of data assimilation. The simulated rainfall is verified against high-resolution rain-gage observations over Karnataka. Statistical evaluation using several accuracy and skill measures shows that data assimilation has improved the heavy rainfall simulation. Our results showed that the experiment using regional BES outperformed the one which used global BES. Critical thermo-dynamic variables conducive for heavy rainfall like convective available potential energy simulated using regional BES is more realistic compared to global BES. It is pointed out that these results have important practical implications in design of forecast platforms while decision-making during extreme weather events

  3. Sensitivity analysis of Takagi-Sugeno-Kang rainfall-runoff fuzzy models

    Directory of Open Access Journals (Sweden)

    A. P. Jacquin

    2009-01-01

    Full Text Available This paper is concerned with the sensitivity analysis of the model parameters of the Takagi-Sugeno-Kang fuzzy rainfall-runoff models previously developed by the authors. These models are classified in two types of fuzzy models, where the first type is intended to account for the effect of changes in catchment wetness and the second type incorporates seasonality as a source of non-linearity. The sensitivity analysis is performed using two global sensitivity analysis methods, namely Regional Sensitivity Analysis and Sobol's variance decomposition. The data of six catchments from different geographical locations and sizes are used in the sensitivity analysis. The sensitivity of the model parameters is analysed in terms of several measures of goodness of fit, assessing the model performance from different points of view. These measures include the Nash-Sutcliffe criteria, volumetric errors and peak errors. The results show that the sensitivity of the model parameters depends on both the catchment type and the measure used to assess the model performance.

  4. RRAWFLOW: Rainfall-Response Aquifer and Watershed Flow Model (v1.15)

    Science.gov (United States)

    Long, Andrew J.

    2015-01-01

    The Rainfall-Response Aquifer and Watershed Flow Model (RRAWFLOW) is a lumped-parameter model that simulates streamflow, spring flow, groundwater level, or solute transport for a measurement point in response to a system input of precipitation, recharge, or solute injection. I introduce the first version of RRAWFLOW available for download and public use and describe additional options. The open-source code is written in the R language and is available at http://sd.water.usgs.gov/projects/RRAWFLOW/RRAWFLOW.html along with an example model of streamflow. RRAWFLOW includes a time-series process to estimate recharge from precipitation and simulates the response to recharge by convolution, i.e., the unit-hydrograph approach. Gamma functions are used for estimation of parametric impulse-response functions (IRFs); a combination of two gamma functions results in a double-peaked IRF. A spline fit to a set of control points is introduced as a new method for estimation of nonparametric IRFs. Several options are included to simulate time-variant systems. For many applications, lumped models simulate the system response with equal accuracy to that of distributed models, but moreover, the ease of model construction and calibration of lumped models makes them a good choice for many applications (e.g., estimating missing periods in a hydrologic record). RRAWFLOW provides professional hydrologists and students with an accessible and versatile tool for lumped-parameter modeling.

  5. RRAWFLOW: Rainfall-Response Aquifer and Watershed Flow Model (v1.11)

    Science.gov (United States)

    Long, A. J.

    2014-09-01

    The Rainfall-Response Aquifer and Watershed Flow Model (RRAWFLOW) is a lumped-parameter model that simulates streamflow, springflow, groundwater level, solute transport, or cave drip for a measurement point in response to a system input of precipitation, recharge, or solute injection. The RRAWFLOW open-source code is written in the R language and is included in the Supplement to this article along with an example model of springflow. RRAWFLOW includes a time-series process to estimate recharge from precipitation and simulates the response to recharge by convolution; i.e., the unit hydrograph approach. Gamma functions are used for estimation of parametric impulse-response functions (IRFs); a combination of two gamma functions results in a double-peaked IRF. A spline fit to a set of control points is introduced as a new method for estimation of nonparametric IRFs. Other options include the use of user-defined IRFs and different methods to simulate time-variant systems. For many applications, lumped models simulate the system response with equal accuracy to that of distributed models, but moreover, the ease of model construction and calibration of lumped models makes them a good choice for many applications. RRAWFLOW provides professional hydrologists and students with an accessible and versatile tool for lumped-parameter modeling.

  6. Addressing the mischaracterization of extreme rainfall in regional climate model simulations - A synoptic pattern based bias correction approach

    Science.gov (United States)

    Li, Jingwan; Sharma, Ashish; Evans, Jason; Johnson, Fiona

    2018-01-01

    Addressing systematic biases in regional climate model simulations of extreme rainfall is a necessary first step before assessing changes in future rainfall extremes. Commonly used bias correction methods are designed to match statistics of the overall simulated rainfall with observations. This assumes that change in the mix of different types of extreme rainfall events (i.e. convective and non-convective) in a warmer climate is of little relevance in the estimation of overall change, an assumption that is not supported by empirical or physical evidence. This study proposes an alternative approach to account for the potential change of alternate rainfall types, characterized here by synoptic weather patterns (SPs) using self-organizing maps classification. The objective of this study is to evaluate the added influence of SPs on the bias correction, which is achieved by comparing the corrected distribution of future extreme rainfall with that using conventional quantile mapping. A comprehensive synthetic experiment is first defined to investigate the conditions under which the additional information of SPs makes a significant difference to the bias correction. Using over 600,000 synthetic cases, statistically significant differences are found to be present in 46% cases. This is followed by a case study over the Sydney region using a high-resolution run of the Weather Research and Forecasting (WRF) regional climate model, which indicates a small change in the proportions of the SPs and a statistically significant change in the extreme rainfall over the region, although the differences between the changes obtained from the two bias correction methods are not statistically significant.

  7. Assessing Intelligent Models in Forecasting Monthly Rainfall by Means of Teleconnection Patterns (Case Study: Khorasan Razavi Province

    Directory of Open Access Journals (Sweden)

    Farzaneh Nazarieh

    2016-02-01

    Full Text Available Introduction: Rainfall is affected by changes in the global sea level change, especially changes in sea surface temperature SST Sea Surface Temperature and sea level pressure SLP Sea level Pressure. Climate anomalies being related to each other at large distance is called teleconnection. As physical relationships between rainfall and teleconnection patterns are not defined clearly, we used intelligent models for forecasting rainfall. The intelligent models used in this study included Fuzzy Inference Systems, neural network and Neuro-fuzzy. In this study, first the teleconnection indices that could affect rainfall in the study area were identified. Then intelligent models were trained for rainfall forecasting. Finally, the most capable model for forecasting rainfall was presented. The study area for this research is the Khorasan Razavi Province. In order to present a model for rainfall forecasting, rainfall data of seven synoptic stations including Mashhad, Golmakan, Nishapur, Sabzevar, Kashmar, Torbate and Sharks since 1991 to 2010 were used. Materials and Methods: Based on previous studies about Teleconnection Patterns in the study area, effective Teleconnection indexes were identified. After calculating the correlation between the identified teleconnection indices and rainfall in one, two and three months ahead for all stations, fourteen teleconnection indices were chosen as inputs for intelligent models. These indices include, SLP Adriatic , SLP northern Red Sea, SLP Mediterranean Sea, SLP Aral sea, SST Sea surface temperature Labrador sea, SST Oman Sea, SST Caspian Sea, SST Persian Gulf, North Pacific pattern, SST Tropical Pacific in NINO12 and NINO3 regions, North Pacific Oscillation, Trans-Nino Index, Multivariable Enso Index. Inputs of the intelligent models include fourteen teleconnection indices, latitude and altitude of each station and their outputs are the prediction of rainfall for one, two and three months ahead. For calibration of

  8. Application of the rainfall infiltration breakthrough (RIB) model for groundwater recharge estimation in west coastal South Africa

    CSIR Research Space (South Africa)

    Sun, X

    2013-04-01

    Full Text Available level fluctuations (WLF) on a monthly basis was proposed in the rainfall infiltration breakthrough (RIB) model for the purpose of groundwater recharge estimation. In this paper, the physical meaning of parameters in the CRD and previous RIB models...

  9. Hydrological model calibration for derived flood frequency analysis using stochastic rainfall and probability distributions of peak flows

    Science.gov (United States)

    Haberlandt, U.; Radtke, I.

    2014-01-01

    Derived flood frequency analysis allows the estimation of design floods with hydrological modeling for poorly observed basins considering change and taking into account flood protection measures. There are several possible choices regarding precipitation input, discharge output and consequently the calibration of the model. The objective of this study is to compare different calibration strategies for a hydrological model considering various types of rainfall input and runoff output data sets and to propose the most suitable approach. Event based and continuous, observed hourly rainfall data as well as disaggregated daily rainfall and stochastically generated hourly rainfall data are used as input for the model. As output, short hourly and longer daily continuous flow time series as well as probability distributions of annual maximum peak flow series are employed. The performance of the strategies is evaluated using the obtained different model parameter sets for continuous simulation of discharge in an independent validation period and by comparing the model derived flood frequency distributions with the observed one. The investigations are carried out for three mesoscale catchments in northern Germany with the hydrological model HEC-HMS (Hydrologic Engineering Center's Hydrologic Modeling System). The results show that (I) the same type of precipitation input data should be used for calibration and application of the hydrological model, (II) a model calibrated using a small sample of extreme values works quite well for the simulation of continuous time series with moderate length but not vice versa, and (III) the best performance with small uncertainty is obtained when stochastic precipitation data and the observed probability distribution of peak flows are used for model calibration. This outcome suggests to calibrate a hydrological model directly on probability distributions of observed peak flows using stochastic rainfall as input if its purpose is the

  10. Interception of LPI radar signals

    Science.gov (United States)

    Lee, Jim P.

    1991-11-01

    Most current radars are designed to transmit short duration pulses with relatively high peak power. These radars can be detected easily by the use of relatively modest EW intercept receivers. Three radar functions (search, anti-ship missile (ASM) seeker, and navigation) are examined to evaluate the effectiveness of potential low probability of intercept (LPI) techniques, such as waveform coding, antenna profile control, and power management that a radar may employ against current Electronic Warfare (EW) receivers. The general conclusion is that it is possible to design a LPI radar which is effective against current intercept EW receivers. LPI operation is most easily achieved at close ranges and against a target with a large radar cross section. The general system sensitivity requirement for the detection of current and projected LPI radars is found to be on the order of -100 dBmi which cannot be met by current EW receivers. Finally, three potential LPI receiver architectures, using channelized, superhet, and acousto-optic receivers with narrow RF and video bandwidths are discussed. They have shown some potential in terms of providing the sensitivity and capability in an environment where both conventional and LPI signals are present.

  11. Derived flood frequency analysis using different model calibration strategies based on various types of rainfall-runoff data - a comparison

    Science.gov (United States)

    Haberlandt, U.; Radtke, I.

    2013-08-01

    Derived flood frequency analysis allows to estimate design floods with hydrological modelling for poorly observed basins considering change and taking into account flood protection measures. There are several possible choices about precipitation input, discharge output and consequently regarding the calibration of the model. The objective of this study is to compare different calibration strategies for a hydrological model considering various types of rainfall input and runoff output data sets. Event based and continuous observed hourly rainfall data as well as disaggregated daily rainfall and stochastically generated hourly rainfall data are used as input for the model. As output short hourly and longer daily continuous flow time series as well as probability distributions of annual maximum peak flow series are employed. The performance of the strategies is evaluated using the obtained different model parameter sets for continuous simulation of discharge in an independent validation period and by comparing the model derived flood frequency distributions with the observed one. The investigations are carried out for three mesoscale catchments in Northern Germany with the hydrological model HEC-HMS. The results show that: (i) the same type of precipitation input data should be used for calibration and application of the hydrological model, (ii) a model calibrated using a small sample of extreme values works quite well for the simulation of continuous time series with moderate length but not vice versa, (iii) the best performance with small uncertainty is obtained when stochastic precipitation data and the observed probability distribution of peak flows are used for model calibration. This outcome suggests to calibrate a hydrological model directly on probability distributions of observed peak flows using stochastic rainfall as input if its purpose is the application for derived flood frequency analysis.

  12. The influence of visual motion on interceptive actions and perception.

    Science.gov (United States)

    Marinovic, Welber; Plooy, Annaliese M; Arnold, Derek H

    2012-05-01

    Visual information is an essential guide when interacting with moving objects, yet it can also be deceiving. For instance, motion can induce illusory position shifts, such that a moving ball can seem to have bounced past its true point of contact with the ground. Some evidence suggests illusory motion-induced position shifts bias pointing tasks to a greater extent than they do perceptual judgments. This, however, appears at odds with other findings and with our success when intercepting moving objects. Here we examined the accuracy of interceptive movements and of perceptual judgments in relation to simulated bounces. Participants were asked to intercept a moving disc at its bounce location by positioning a virtual paddle, and then to report where the disc had landed. Results showed that interceptive actions were accurate whereas perceptual judgments were inaccurate, biased in the direction of motion. Successful interceptions necessitated accurate information concerning both the location and timing of the bounce, so motor planning evidently had privileged access to an accurate forward model of bounce timing and location. This would explain why people can be accurate when intercepting a moving object, but lack insight into the accurate information that had guided their actions when asked to make a perceptual judgment. Copyright © 2012 Elsevier Ltd. All rights reserved.

  13. Incorporation of groundwater losses and well level data in rainfall-runoff models illustrated using the PDM

    Directory of Open Access Journals (Sweden)

    R. J. Moore

    2002-01-01

    Full Text Available Intermittent streamflow is a common occurrence in permeable catchments, especially where there are pumped abstractions to water supply. Many rainfall-runoff models are not formulated so as to represent ephemeral streamflow behaviour or to allow for the possibility of negative recharge arising from groundwater pumping. A groundwater model component is formulated here for use in extending existing rainfall-runoff models to accommodate such ephemeral behaviour. Solutions to the Horton-Izzard equation resulting from the conceptual model of groundwater storage are adapted and the form of nonlinear storage extended to accommodate negative inputs, water storage below which outflow ceases, and losses to external springs and underflows below the gauged catchment outlet. The groundwater model component is demonstrated through using it as an extension of the PDM rainfall-runoff model. It is applied to the River Lavant, a catchment in Southern England on the English Chalk, where it successfully simulates the ephemeral streamflow behaviour and flood response together with well level variations. Keywords: groundwater, rainfall-runoff model, ephemeral stream, well level, spring, abstraction

  14. A comparative study of mixed exponential and Weibull distributions in a stochastic model replicating a tropical rainfall process

    Science.gov (United States)

    Abas, Norzaida; Daud, Zalina M.; Yusof, Fadhilah

    2014-11-01

    A stochastic rainfall model is presented for the generation of hourly rainfall data in an urban area in Malaysia. In view of the high temporal and spatial variability of rainfall within the tropical rain belt, the Spatial-Temporal Neyman-Scott Rectangular Pulse model was used. The model, which is governed by the Neyman-Scott process, employs a reasonable number of parameters to represent the physical attributes of rainfall. A common approach is to attach each attribute to a mathematical distribution. With respect to rain cell intensity, this study proposes the use of a mixed exponential distribution. The performance of the proposed model was compared to a model that employs the Weibull distribution. Hourly and daily rainfall data from four stations in the Damansara River basin in Malaysia were used as input to the models, and simulations of hourly series were performed for an independent site within the basin. The performance of the models was assessed based on how closely the statistical characteristics of the simulated series resembled the statistics of the observed series. The findings obtained based on graphical representation revealed that the statistical characteristics of the simulated series for both models compared reasonably well with the observed series. However, a further assessment using the AIC, BIC and RMSE showed that the proposed model yields better results. The results of this study indicate that for tropical climates, the proposed model, using a mixed exponential distribution, is the best choice for generation of synthetic data for ungauged sites or for sites with insufficient data within the limit of the fitted region.

  15. Projection of spatial and temporal changes of rainfall in Sarawak of Borneo Island using statistical downscaling of CMIP5 models

    Science.gov (United States)

    Sa'adi, Zulfaqar; Shahid, Shamsuddin; Chung, Eun-Sung; Ismail, Tarmizi bin

    2017-11-01

    This study assesses the possible changes in rainfall patterns of Sarawak in Borneo Island due to climate change through statistical downscaling of General Circulation Models (GCM) projections. Available in-situ observed rainfall data were used to downscale the future rainfall from ensembles of 20 GCMs of Coupled Model Intercomparison Project phase 5 (CMIP5) for four Representative Concentration Pathways (RCP) scenarios, namely, RCP2.6, RCP4.5, RCP6.0 and RCP8.5. Model Output Statistics (MOS) based downscaling models were developed using two data mining approaches known as Random Forest (RF) and Support Vector Machine (SVM). The SVM was found to downscale all GCMs with normalized mean square error (NMSE) of 48.2-75.2 and skill score (SS) of 0.94-0.98 during validation. The results show that the future projection of the annual rainfalls is increasing and decreasing on the region-based and catchment-based basis due to the influence of the monsoon season affecting the coast of Sarawak. The ensemble mean of GCMs projections reveals the increased and decreased mean of annual precipitations at 33 stations with the rate of 0.1% to 19.6% and one station with the rate of - 7.9% to - 3.1%, respectively under all RCP scenarios. The remaining 15 stations showed inconsistency neither increasing nor decreasing at the rate of - 5.6% to 5.2%, but mainly showing a trend of decreasing rainfall during the first period (2010-2039) followed by increasing rainfall for the period of 2070-2099.

  16. Calibration of a rainfall-runoff hydrological model and flood simulation using data assimilation

    Science.gov (United States)

    Piacentini, A.; Ricci, S. M.; Thual, O.; Coustau, M.; Marchandise, A.

    2010-12-01

    Rainfall-runoff models are crucial tools for long-term assessment of flash floods or real-time forecasting. This work focuses on the calibration of a distributed parsimonious event-based rainfall-runoff model using data assimilation. The model combines a SCS-derived runoff model and a Lag and Route routing model for each cell of a regular grid mesh. The SCS-derived runoff model is parametrized by the initial water deficit, the discharge coefficient for the soil reservoir and a lagged discharge coefficient. The Lag and Route routing model is parametrized by the velocity of travel and the lag parameter. These parameters are assumed to be constant for a given catchment except for the initial water deficit and the velocity travel that are event-dependent (landuse, soil type and moisture initial conditions). In the present work, a BLUE filtering technique was used to calibrate the initial water deficit and the velocity travel for each flood event assimilating the first available discharge measurements at the catchment outlet. The advantages of the BLUE algorithm are its low computational cost and its convenient implementation, especially in the context of the calibration of a reduced number of parameters. The assimilation algorithm was applied on two Mediterranean catchment areas of different size and dynamics: Gardon d'Anduze and Lez. The Lez catchment, of 114 km2 drainage area, is located upstream Montpellier. It is a karstic catchment mainly affected by floods in autumn during intense rainstorms with short Lag-times and high discharge peaks (up to 480 m3.s-1 in September 2005). The Gardon d'Anduze catchment, mostly granite and schistose, of 545 km2 drainage area, lies over the departements of Lozère and Gard. It is often affected by flash and devasting floods (up to 3000 m3.s-1 in September 2002). The discharge observations at the beginning of the flood event are assimilated so that the BLUE algorithm provides optimal values for the initial water deficit and the

  17. Effect of Incident Rainfall Redistribution by Maize Canopy on Soil Moisture at the Crop Row Scale

    Directory of Open Access Journals (Sweden)

    Marco Martello

    2015-05-01

    Full Text Available The optimization of irrigation use in agriculture is a key challenge to increase farm profitability and reduce its ecological footprint. To this context, an understanding of more efficient irrigation systems includes the assessment of water redistribution at the microscale. This study aimed to investigate rainfall interception by maize canopy and to model the soil water dynamics at row scale as a result of rain and sprinkler irrigation with HYDRUS 2D/3D. On average, 78% of rainfall below the maize canopy was intercepted by the leaves and transferred along the stem (stemflow, while only 22% reached the ground directly (throughfall. In addition, redistribution of the water with respect to the amount (both rain and irrigation showed that the stemflow/throughfall ratio decreased logarithmically at increasing values of incident rainfall, suggesting the plant capacity to confine the water close to the roots and diminish water stress conditions. This was also underlined by higher soil moisture values observed in the row than in the inter-row at decreasing rainfall events. Modelled data highlighted different behavior in terms of soil water dynamics between simulated irrigation water distributions, although they did not show significant changes in terms of crop water use efficiency. These results were most likely affected by the soil type (silty-loam where the experiment was conducted, as it had unfavorable physical conditions for the rapid vertical water movement that would have increased infiltration and drainage.

  18. Applicability of Zero-Inflated Models to Fit the Torrential Rainfall Count Data with Extra Zeros in South Korea

    Directory of Open Access Journals (Sweden)

    Cheol-Eung Lee

    2017-02-01

    Full Text Available Several natural disasters occur because of torrential rainfalls. The change in global climate most likely increases the occurrences of such downpours. Hence, it is necessary to investigate the characteristics of the torrential rainfall events in order to introduce effective measures for mitigating disasters such as urban floods and landslides. However, one of the major problems is evaluating the number of torrential rainfall events from a statistical viewpoint. If the number of torrential rainfall occurrences during a month is considered as count data, their frequency distribution could be identified using a probability distribution. Generally, the number of torrential rainfall occurrences has been analyzed using the Poisson distribution (POI or the Generalized Poisson Distribution (GPD. However, it was reported that POI and GPD often overestimated or underestimated the observed count data when additional or fewer zeros were included. Hence, in this study, a zero-inflated model concept was applied to solve this problem existing in the conventional models. Zero-Inflated Poisson (ZIP model, Zero-Inflated Generalized Poisson (ZIGP model, and the Bayesian ZIGP model have often been applied to fit the count data having additional or fewer zeros. However, the applications of these models in water resource management have been very limited despite their efficiency and accuracy. The five models, namely, POI, GPD, ZIP, ZIGP, and Bayesian ZIGP, were applied to the torrential rainfall data having additional zeros obtained from two rain gauges in South Korea, and their applicability was examined in this study. In particular, the informative prior distributions evaluated via the empirical Bayes method using ten rain gauges were developed in the Bayesian ZIGP model. Finally, it was suggested to avoid using the POI and GPD models to fit the frequency of torrential rainfall data. In addition, it was concluded that the Bayesian ZIGP model used in this study

  19. Modelling the impacts of deforestation on monsoon rainfall in West Africa

    International Nuclear Information System (INIS)

    Abiodun, B J; Pal, J S; Afiesimama, E A; Gutowski, W J; Adedoyin, A

    2010-01-01

    The study found that deforestation causes more monsoon moisture to be retained in the mid-troposphere, thereby reducing the northward transport of moisture needed for rainfall over West Africa. Hence, deforestation has dynamical impacts on the West African monsoon and rainfall.

  20. Continuous Sub-daily Rainfall Simulation for Regional Flood Risk Assessment - Modelling of Spatio-temporal Correlation Structure of Extreme Precipitation in the Austrian Alps

    Science.gov (United States)

    Salinas, J. L.; Nester, T.; Komma, J.; Bloeschl, G.

    2017-12-01

    Generation of realistic synthetic spatial rainfall is of pivotal importance for assessing regional hydroclimatic hazard as the input for long term rainfall-runoff simulations. The correct reproduction of observed rainfall characteristics, such as regional intensity-duration-frequency curves, and spatial and temporal correlations is necessary to adequately model the magnitude and frequency of the flood peaks, by reproducing antecedent soil moisture conditions before extreme rainfall events, and joint probability of flood waves at confluences. In this work, a modification of the model presented by Bardossy and Platte (1992), where precipitation is first modeled on a station basis as a multivariate autoregressive model (mAr) in a Normal space. The spatial and temporal correlation structures are imposed in the Normal space, allowing for a different temporal autocorrelation parameter for each station, and simultaneously ensuring the positive-definiteness of the correlation matrix of the mAr errors. The Normal rainfall is then transformed to a Gamma-distributed space, with parameters varying monthly according to a sinusoidal function, in order to adapt to the observed rainfall seasonality. One of the main differences with the original model is the simulation time-step, reduced from 24h to 6h. Due to a larger availability of daily rainfall data, as opposite to sub-daily (e.g. hourly), the parameters of the Gamma distributions are calibrated to reproduce simultaneously a series of daily rainfall characteristics (mean daily rainfall, standard deviations of daily rainfall, and 24h intensity-duration-frequency [IDF] curves), as well as other aggregated rainfall measures (mean annual rainfall, and monthly rainfall). The calibration of the spatial and temporal correlation parameters is performed in a way that the catchment-averaged IDF curves aggregated at different temporal scales fit the measured ones. The rainfall model is used to generate 10.000 years of synthetic

  1. Green roof rainfall-runoff modelling: is the comparison between conceptual and physically based approaches relevant?

    Science.gov (United States)

    Versini, Pierre-Antoine; Tchiguirinskaia, Ioulia; Schertzer, Daniel

    2017-04-01

    Green roofs are commonly considered as efficient tools to mitigate urban runoff as they can store precipitation, and consequently provide retention and detention performances. Designed as a compromise between water holding capacity, weight and hydraulic conductivity, their substrate is usually an artificial media differentiating significantly from a traditional soil. In order to assess green roofs hydrological performances, many models have been developed. Classified into two categories (conceptual and physically based), they are usually applied to reproduce the discharge of a particular monitored green roof considered as homogeneous. Although the resulted simulations could be satisfactory, the question of robustness and consistency of the calibrated parameters is often not addressed. Here, a modeling framework has been developed to assess the efficiency and the robustness of both modelling approaches (conceptual and physically based) in reproducing green roof hydrological behaviour. SWMM and VS2DT models have been used for this purpose. This work also benefits from an experimental setup where several green roofs differentiated by their substrate thickness and vegetation cover are monitored. Based on the data collected for several rainfall events, it has been studied how the calibrated parameters are effectively linked to their physical properties and how they can vary from one green roof configuration to another. Although both models reproduce correctly the observed discharges in most of the cases, their calibrated parameters exhibit a high inconsistency. For a same green roof configuration, these parameters can vary significantly from one rainfall event to another, even if they are supposed to be linked to the green roof characteristics (roughness, residual moisture content for instance). They can also be different from one green roof configuration to another although the implemented substrate is the same. Finally, it appears very difficult to find any

  2. Canopy rainfall partitioning across an urbanization gradient in forest structure as characterized by terrestrial LiDAR

    Science.gov (United States)

    Mesta, D. C.; Van Stan, J. T., II; Yankine, S. A.; Cote, J. F.; Jarvis, M. T.; Hildebrandt, A.; Friesen, J.; Maldonado, G.

    2017-12-01

    As urbanization expands, greater forest area is shifting from natural stand structures to urban stand structures, like forest fragments and landscaped tree rows. Changes in forest canopy structure have been found to drastically alter the amount of rainwater reaching the surface. However, stormwater management models generally treat all forest structures (beyond needle versus broadleaved) similarly. This study examines the rainfall partitioning of Pinus spp. canopies along a natural-to-urban forest gradient and compares these to canopy structural measurements using terrestrial LiDAR. Throughfall and meteorological observations were also used to estimate parameters of the commonly-used Gash interception model. Preliminary findings indicate that as forest structure changed from natural, closed canopy conditions to semi-closed canopy fragments and, ultimately, to exposed urban landscaping tree rows, the interchange between throughfall and rainfall interception also changed. This shift in partitioning between throughfall and rainfall interception may be linked to intuitive parameters, like canopy closure and density, as well as more complex metrics, like the fine-scale patterning of gaps (ie, lacunarity). Thus, results indicate that not all forests of the same species should be treated the same by stormwater models. Rather, their canopy structural characteristics should be used to vary their hydrometeorological interactions.

  3. A model for estimating time-variant rainfall infiltration as a function of antecedent surface moisture and hydrologic soil type

    Science.gov (United States)

    Wilkening, H. A.; Ragan, R. M.

    1982-01-01

    Recent research indicates that the use of remote sensing techniques for the measurement of near surface soil moisture could be practical in the not too distant future. Other research shows that infiltration rates, especially for average or frequent rainfall events, are extremely sensitive to the proper definition and consideration of the role of the soil moisture at the beginning of the rainfall. Thus, it is important that an easy to use, but theoretically sound, rainfall infiltration model be available if the anticipated remotely sensed soil moisture data is to be optimally utilized for hydrologic simulation. A series of numerical experiments with the Richards' equation for an array of conditions anticipated in watershed hydrology were used to develop functional relationships that describe temporal infiltration rates as a function of soil type and initial moisture conditions.

  4. Forecast generation for real-time control of urban drainage systems using greybox modelling and radar rainfall

    DEFF Research Database (Denmark)

    Löwe, Roland; Mikkelsen, Peter Steen; Madsen, Henrik

    2012-01-01

    We present stochastic flow forecasts to be used in a real-time control setup for urban drainage systems. The forecasts are generated using greybox models with rain gauge and radar rainfall observations as input. Predictions are evaluated as intervals rather than just mean values. We obtain...

  5. Subgrid Parameterization of the Soil Moisture Storage Capacity for a Distributed Rainfall-Runoff Model

    Directory of Open Access Journals (Sweden)

    Weijian Guo

    2015-05-01

    Full Text Available Spatial variability plays an important role in nonlinear hydrologic processes. Due to the limitation of computational efficiency and data resolution, subgrid variability is usually assumed to be uniform for most grid-based rainfall-runoff models, which leads to the scale-dependence of model performances. In this paper, the scale effect on the Grid-Xinanjiang model was examined. The bias of the estimation of precipitation, runoff, evapotranspiration and soil moisture at the different grid scales, along with the scale-dependence of the effective parameters, highlights the importance of well representing the subgrid variability. This paper presents a subgrid parameterization method to incorporate the subgrid variability of the soil storage capacity, which is a key variable that controls runoff generation and partitioning in the Grid-Xinanjiang model. In light of the similar spatial pattern and physical basis, the soil storage capacity is correlated with the topographic index, whose spatial distribution can more readily be measured. A beta distribution is introduced to represent the spatial distribution of the soil storage capacity within the grid. The results derived from the Yanduhe Basin show that the proposed subgrid parameterization method can effectively correct the watershed soil storage capacity curve. Compared to the original Grid-Xinanjiang model, the model performances are quite consistent at the different grid scales when the subgrid variability is incorporated. This subgrid parameterization method reduces the recalibration necessity when the Digital Elevation Model (DEM resolution is changed. Moreover, it improves the potential for the application of the distributed model in the ungauged basin.

  6. Aspect of ECMWF downscaled Regional Climate Modeling in simulating Indian summer monsoon rainfall and dependencies on lateral boundary conditions

    Science.gov (United States)

    Ghosh, Soumik; Bhatla, R.; Mall, R. K.; Srivastava, Prashant K.; Sahai, A. K.

    2018-03-01

    Climate model faces considerable difficulties in simulating the rainfall characteristics of southwest summer monsoon. In this study, the dynamical downscaling of European Centre for Medium-Range Weather Forecast's (ECMWF's) ERA-Interim (EIN15) has been utilized for the simulation of Indian summer monsoon (ISM) through the Regional Climate Model version 4.3 (RegCM-4.3) over the South Asia Co-Ordinated Regional Climate Downscaling EXperiment (CORDEX) domain. The complexities of model simulation over a particular terrain are generally influenced by factors such as complex topography, coastal boundary, and lack of unbiased initial and lateral boundary conditions. In order to overcome some of these limitations, the RegCM-4.3 is employed for simulating the rainfall characteristics over the complex topographical conditions. For reliable rainfall simulation, implementations of numerous lower boundary conditions are forced in the RegCM-4.3 with specific horizontal grid resolution of 50 km over South Asia CORDEX domain. The analysis is considered for 30 years of climatological simulation of rainfall, outgoing longwave radiation (OLR), mean sea level pressure (MSLP), and wind with different vertical levels over the specified region. The dependency of model simulation with the forcing of EIN15 initial and lateral boundary conditions is used to understand the impact of simulated rainfall characteristics during different phases of summer monsoon. The results obtained from this study are used to evaluate the activity of initial conditions of zonal wind circulation speed, which causes an increase in the uncertainty of regional model output over the region under investigation. Further, the results showed that the EIN15 zonal wind circulation lacks sufficient speed over the specified region in a particular time, which was carried forward by the RegCM output and leads to a disrupted regional simulation in the climate model.

  7. Modeling jointly low, moderate, and heavy rainfall intensities without a threshold selection

    KAUST Repository

    Naveau, Philippe

    2016-04-09

    In statistics, extreme events are often defined as excesses above a given large threshold. This definition allows hydrologists and flood planners to apply Extreme-Value Theory (EVT) to their time series of interest. Even in the stationary univariate context, this approach has at least two main drawbacks. First, working with excesses implies that a lot of observations (those below the chosen threshold) are completely disregarded. The range of precipitation is artificially shopped down into two pieces, namely large intensities and the rest, which necessarily imposes different statistical models for each piece. Second, this strategy raises a nontrivial and very practical difficultly: how to choose the optimal threshold which correctly discriminates between low and heavy rainfall intensities. To address these issues, we propose a statistical model in which EVT results apply not only to heavy, but also to low precipitation amounts (zeros excluded). Our model is in compliance with EVT on both ends of the spectrum and allows a smooth transition between the two tails, while keeping a low number of parameters. In terms of inference, we have implemented and tested two classical methods of estimation: likelihood maximization and probability weighed moments. Last but not least, there is no need to choose a threshold to define low and high excesses. The performance and flexibility of this approach are illustrated on simulated and hourly precipitation recorded in Lyon, France.

  8. Effect of increasing greenhouse gases on Indian monsoon rainfall as downscaled from the ECHAM coupled model

    International Nuclear Information System (INIS)

    Singh, S.V.; Storch, H.V.

    1994-01-01

    It is more or less accepted that the increasing anthropogenic gases will result in global warming through the greenhouse effect. The major influence of this will be felt in the form of ice melts and rising sea levels. The influence on regional climates like monsoons is not very clear. Since the monsoons arise due to surface heating, one would expect that global warming will lead to more vigorous monsoons. The expected change in a climate parameter can be studied by analyzing the historical data and then extrapolating in time. Alternatively, one can use the state-of-the-art coupled GCMs which are able to simulate the earth's climate with reasonable accuracy. Both methods have some limitations. The first method cannot adequately consider the nonlinearity, and the second method may not be efficient for regional scales. So that the projections can be trusted, the regional features should be well simulated. None of the current models are able to simulate the Indian monsoon satisfactorily. Therefore it is desirable to infer the expected change in monsoons from other large and near global scale features which are better simulated. This approach, which depends on the concurrent association between a large-scale modeled feature and a regional scale, is known as downscaling, after Storch et al., and is adopted here to project the Indian monsoon rainfall for the next 100 years from the ECHAM T21 coupled model

  9. STEP-TRAMM - A modeling interface for simulating localized rainfall induced shallow landslides and debris flow runout pathways

    Science.gov (United States)

    Or, D.; von Ruette, J.; Lehmann, P.

    2017-12-01

    Landslides and subsequent debris-flows initiated by rainfall represent a common natural hazard in mountainous regions. We integrated a landslide hydro-mechanical triggering model with a simple model for debris flow runout pathways and developed a graphical user interface (GUI) to represent these natural hazards at catchment scale at any location. The STEP-TRAMM GUI provides process-based estimates of the initiation locations and sizes of landslides patterns based on digital elevation models (SRTM) linked with high resolution global soil maps (SoilGrids 250 m resolution) and satellite based information on rainfall statistics for the selected region. In the preprocessing phase the STEP-TRAMM model estimates soil depth distribution to supplement other soil information for delineating key hydrological and mechanical properties relevant to representing local soil failure. We will illustrate this publicly available GUI and modeling platform to simulate effects of deforestation on landslide hazards in several regions and compare model outcome with satellite based information.

  10. A combined triggering-propagation modeling approach for the assessment of rainfall induced debris flow susceptibility

    Science.gov (United States)

    Stancanelli, Laura Maria; Peres, David Johnny; Cancelliere, Antonino; Foti, Enrico

    2017-07-01

    Rainfall-induced shallow slides can evolve into debris flows that move rapidly downstream with devastating consequences. Mapping the susceptibility to debris flow is an important aid for risk mitigation. We propose a novel practical approach to derive debris flow inundation maps useful for susceptibility assessment, that is based on the integrated use of DEM-based spatially-distributed hydrological and slope stability models with debris flow propagation models. More specifically, the TRIGRS infiltration and infinite slope stability model and the FLO-2D model for the simulation of the related debris flow propagation and deposition are combined. An empirical instability-to-debris flow triggering threshold calibrated on the basis of observed events, is applied to link the two models and to accomplish the task of determining the amount of unstable mass that develops as a debris flow. Calibration of the proposed methodology is carried out based on real data of the debris flow event occurred on 1 October 2009, in the Peloritani mountains area (Italy). Model performance, assessed by receiver-operating-characteristics (ROC) indexes, evidences fairly good reproduction of the observed event. Comparison with the performance of the traditional debris flow modeling procedure, in which sediment and water hydrographs are inputed as lumped at selected points on top of the streams, is also performed, in order to assess quantitatively the limitations of such commonly applied approach. Results show that the proposed method, besides of being more process-consistent than the traditional hydrograph-based approach, can potentially provide a more accurate simulation of debris-flow phenomena, in terms of spatial patterns of erosion and deposition as well on the quantification of mobilized volumes and depths, avoiding overestimation of debris flow triggering volume and, thus, of maximum inundation flow depths.

  11. Empirical model for estimating dengue incidence using temperature, rainfall, and relative humidity: a 19-year retrospective analysis in East Delhi.

    Science.gov (United States)

    Ramachandran, Vishnampettai G; Roy, Priyamvada; Das, Shukla; Mogha, Narendra Singh; Bansal, Ajay Kumar

    2016-01-01

    Aedes mosquitoes are responsible for transmitting the dengue virus. The mosquito lifecycle is known to be influenced by temperature, rainfall, and relative humidity. This retrospective study was planned to investigate whether climatic factors could be used to predict the occurrence of dengue in East Delhi. The number of monthly dengue cases reported over 19 years was obtained from the laboratory records of our institution. Monthly data of rainfall, temperature, and humidity collected from a local weather station were correlated with the number of monthly reported dengue cases. One-way analysis of variance was used to analyse whether the climatic parameters differed significantly among seasons. Four models were developed using negative binomial generalized linear model analysis. Monthly rainfall, temperature, humidity, were used as independent variables, and the number of dengue cases reported monthly was used as the dependent variable. The first model considered data from the same month, while the other three models involved incorporating data with a lag phase of 1, 2, and 3 months, respectively. The greatest number of cases was reported during the post-monsoon period each year. Temperature, rainfall, and humidity varied significantly across the pre-monsoon, monsoon, and post-monsoon periods. The best correlation between these three climatic factors and dengue occurrence was at a time lag of 2 months. This study found that temperature, rainfall, and relative humidity significantly affected dengue occurrence in East Delhi. This weather-based dengue empirical model can forecast potential outbreaks 2-month in advance, providing an early warning system for intensifying dengue control measures.

  12. Coupling Radar Rainfall Estimation and Hydrological Modelling For Flash-flood Hazard Mitigation

    Science.gov (United States)

    Borga, M.; Creutin, J. D.

    issues are examined: advantages and caveats of using radar rainfall estimates in operational flash flood forecasting, methodological problems as- sociated to the use of hydrological models for distributed flash flood forecasting with rainfall input estimated from radar.

  13. Impact of Urbanization on Spatial Variability of Rainfall-A case study of Mumbai city with WRF Model

    Science.gov (United States)

    Mathew, M.; Paul, S.; Devanand, A.; Ghosh, S.

    2015-12-01

    Urban precipitation enhancement has been identified over many cities in India by previous studies conducted. Anthropogenic effects such as change in land cover from hilly forest areas to flat topography with solid concrete infrastructures has certain effect on the local weather, the same way the greenhouse gas has on climate change. Urbanization could alter the large scale forcings to such an extent that it may bring about temporal and spatial changes in the urban weather. The present study investigate the physical processes involved in urban forcings, such as the effect of sudden increase in wind velocity travelling through the channel space in between the dense array of buildings, which give rise to turbulence and air mass instability in urban boundary layer and in return alters the rainfall distribution as well as rainfall initiation. A numerical model study is conducted over Mumbai metropolitan city which lies on the west coast of India, to assess the effect of urban morphology on the increase in number of extreme rainfall events in specific locations. An attempt has been made to simulate twenty extreme rainfall events that occurred over the summer monsoon period of the year 2014 using high resolution WRF-ARW (Weather Research and Forecasting-Advanced Research WRF) model to assess the urban land cover mechanisms that influences precipitation variability over this spatially varying urbanized region. The result is tested against simulations with altered land use. The correlation of precipitation with spatial variability of land use is found using a detailed urban land use classification. The initial and boundary conditions for running the model were obtained from the global model ECMWF(European Centre for Medium Range Weather Forecast) reanalysis data having a horizontal resolution of 0.75 °x 0.75°. The high resolution simulations show significant spatial variability in the accumulated rainfall, within a few kilometers itself. Understanding the spatial

  14. Areal rainfall estimation using moving cars - computer experiments including hydrological modeling

    OpenAIRE

    Rabiei, Ehsan; Haberlandt, Uwe; Sester, Monika; Fitzner, Daniel; Wallner, Markus

    2016-01-01

    The need for high temporal and spatial resolution precipitation data for hydrological analyses has been discussed in several studies. Although rain gauges provide valuable information, a very dense rain gauge network is costly. As a result, several new ideas have been emerged to help estimating areal rainfall with higher temporal and spatial resolution. Rabiei et al. (2013) observed that moving cars, called RainCars (RCs), can potentially be a new source of data for measuring rainfall amounts...

  15. Assessing the capability of CORDEX models in simulating onset of rainfall in West Africa

    Science.gov (United States)

    Mounkaila, Moussa S.; Abiodun, Babatunde J.; `Bayo Omotosho, J.

    2015-01-01

    Reliable forecasts of rainfall-onset dates (RODs) are crucial for agricultural planning and food security in West Africa. This study evaluates the ability of nine CORDEX regional climate models (RCMs: ARPEGE, CRCM5, RACMO, RCA35, REMO, RegCM3, PRECIS, CCLM and WRF) in simulating RODs over the region. Four definitions are used to compute RODs, and two observation datasets (GPCP and TRMM) are used in the model evaluation. The evaluation considers how well the RCMs, driven by ERA-Interim reanalysis (ERAIN), simulate the observed mean, standard deviation and inter-annual variability of RODs over West Africa. It also investigates how well the models link RODs with the northward movement of the monsoon system over the region. The model performances are compared to that of the driving reanalysis—ERAIN. Observations show that the mean RODs in West Africa have a zonal distribution, and the dates increase from the Guinea coast northward. ERAIN fails to reproduce the spatial distribution of the RODs as observed. The performance of some RCMs in simulating the RODs depends on the ROD definition used. For instance, ARPEGE, RACMO, PRECIS and CCLM produce a better ROD distribution than that of ERAIN when three of the ROD definitions are used, but give a worse ROD distribution than that of ERAIN when the fourth definition is used. However, regardless of the definition used, CCRM5, RCA35, REMO, RegCM3 and WRF show a remarkable improvement over ERAIN. The study shows that the ability of the RCMs in simulating RODs over West Africa strongly depends on how well the models reproduce the northward movement of the monsoon system and the associated features. The results show that there are some differences in the RODs obtained between the two observation datasets and RCMs, and the differences are magnified by differences in the ROD definitions. However, the study shows that most CORDEX RCMs have remarkable skills in predicting the RODs in West Africa.

  16. Assessment of summer rainfall forecast skill in the Intra-Americas in GFDL high and low-resolution models

    Science.gov (United States)

    Krishnamurthy, Lakshmi; Muñoz, Ángel G.; Vecchi, Gabriel A.; Msadek, Rym; Wittenberg, Andrew T.; Stern, Bill; Gudgel, Rich; Zeng, Fanrong

    2018-05-01

    The Caribbean low-level jet (CLLJ) is an important component of the atmospheric circulation over the Intra-Americas Sea (IAS) which impacts the weather and climate both locally and remotely. It influences the rainfall variability in the Caribbean, Central America, northern South America, the tropical Pacific and the continental Unites States through the transport of moisture. We make use of high-resolution coupled and uncoupled models from the Geophysical Fluid Dynamics Laboratory (GFDL) to investigate the simulation of the CLLJ and its teleconnections and further compare with low-resolution models. The high-resolution coupled model FLOR shows improvements in the simulation of the CLLJ and its teleconnections with rainfall and SST over the IAS compared to the low-resolution coupled model CM2.1. The CLLJ is better represented in uncoupled models (AM2.1 and AM2.5) forced with observed sea-surface temperatures (SSTs), emphasizing the role of SSTs in the simulation of the CLLJ. Further, we determine the forecast skill for observed rainfall using both high- and low-resolution predictions of rainfall and SSTs for the July-August-September season. We determine the role of statistical correction of model biases, coupling and horizontal resolution on the forecast skill. Statistical correction dramatically improves area-averaged forecast skill. But the analysis of spatial distribution in skill indicates that the improvement in skill after statistical correction is region dependent. Forecast skill is sensitive to coupling in parts of the Caribbean, Central and northern South America, and it is mostly insensitive over North America. Comparison of forecast skill between high and low-resolution coupled models does not show any dramatic difference. However, uncoupled models show improvement in the area-averaged skill in the high-resolution atmospheric model compared to lower resolution model. Understanding and improving the forecast skill over the IAS has important implications

  17. Rainfall and its seasonality over the Amazon in the 21st century as assessed by the coupled models for the IPCC AR4

    Science.gov (United States)

    Li, Wenhong; Fu, Rong; Dickinson, Robert E.

    2006-01-01

    The global climate models for the Intergovernmental Panel on Climate Change Fourth Assessment Report (IPCC AR4) predict very different changes of rainfall over the Amazon under the SRES A1B scenario for global climate change. Five of the eleven models predict an increase of annual rainfall, three models predict a decrease of rainfall, and the other three models predict no significant changes in the Amazon rainfall. We have further examined two models. The UKMO-HadCM3 model predicts an El Niño-like sea surface temperature (SST) change and warming in the northern tropical Atlantic which appear to enhance atmospheric subsidence and consequently reduce clouds over the Amazon. The resultant increase of surface solar absorption causes a stronger surface sensible heat flux and thus reduces relative humidity of the surface air. These changes decrease the rate and length of wet season rainfall and surface latent heat flux. This decreased wet season rainfall leads to drier soil during the subsequent dry season, which in turn can delay the transition from the dry to wet season. GISS-ER predicts a weaker SST warming in the western Pacific and the southern tropical Atlantic which increases moisture transport and hence rainfall in the Amazon. In the southern Amazon and Nordeste where the strongest rainfall increase occurs, the resultant higher soil moisture supports a higher surface latent heat flux during the dry and transition season and leads to an earlier wet season onset.

  18. Use of Machine Learning Techniques for Iidentification of Robust Teleconnections to East African Rainfall Variability in Observations and Models

    Science.gov (United States)

    Roberts, J. Brent; Robertson, Franklin R.; Funk, Chris

    2014-01-01

    Providing advance warning of East African rainfall variations is a particular focus of several groups including those participating in the Famine Early Warming Systems Network. Both seasonal and long-term model projections of climate variability are being used to examine the societal impacts of hydrometeorological variability on seasonal to interannual and longer time scales. The NASA / USAID SERVIR project, which leverages satellite and modeling-based resources for environmental decision making in developing nations, is focusing on the evaluation of both seasonal and climate model projections to develop downscaled scenarios for using in impact modeling. The utility of these projections is reliant on the ability of current models to capture the embedded relationships between East African rainfall and evolving forcing within the coupled ocean-atmosphere-land climate system. Previous studies have posited relationships between variations in El Niño, the Walker circulation, Pacific decadal variability (PDV), and anthropogenic forcing. This study applies machine learning methods (e.g. clustering, probabilistic graphical model, nonlinear PCA) to observational datasets in an attempt to expose the importance of local and remote forcing mechanisms of East African rainfall variability. The ability of the NASA Goddard Earth Observing System (GEOS5) coupled model to capture the associated relationships will be evaluated using Coupled Model Intercomparison Project Phase 5 (CMIP5) simulations.

  19. Effect of the spatiotemporal variability of rainfall inputs in water quality integrated catchment modelling for dissolved oxygen concentrations

    Science.gov (United States)

    Moreno Ródenas, Antonio Manuel; Cecinati, Francesca; ten Veldhuis, Marie-Claire; Langeveld, Jeroen; Clemens, Francois

    2016-04-01

    Maintaining water quality standards in highly urbanised hydrological catchments is a worldwide challenge. Water management authorities struggle to cope with changing climate and an increase in pollution pressures. Water quality modelling has been used as a decision support tool for investment and regulatory developments. This approach led to the development of integrated catchment models (ICM), which account for the link between the urban/rural hydrology and the in-river pollutant dynamics. In the modelled system, rainfall triggers the drainage systems of urban areas scattered along a river. When flow exceeds the sewer infrastructure capacity, untreated wastewater enters the natural system by combined sewer overflows. This results in a degradation of the river water quality, depending on the magnitude of the emission and river conditions. Thus, being capable of representing these dynamics in the modelling process is key for a correct assessment of the water quality. In many urbanised hydrological systems the distances between draining sewer infrastructures go beyond the de-correlation length of rainfall processes, especially, for convective summer storms. Hence, spatial and temporal scales of selected rainfall inputs are expected to affect water quality dynamics. The objective of this work is to evaluate how the use of rainfall data from different sources and with different space-time characteristics affects modelled output concentrations of dissolved oxygen in a simplified ICM. The study area is located at the Dommel, a relatively small and sensitive river flowing through the city of Eindhoven (The Netherlands). This river stretch receives the discharge of the 750,000 p.e. WWTP of Eindhoven and from over 200 combined sewer overflows scattered along its length. A pseudo-distributed water quality model has been developed in WEST (mikedhi.com); this is a lumped-physically based model that accounts for urban drainage processes, WWTP and river dynamics for several

  20. Scale effect challenges in urban hydrology highlighted with a Fully Distributed Model and High-resolution rainfall data

    Science.gov (United States)

    Ichiba, Abdellah; Gires, Auguste; Tchiguirinskaia, Ioulia; Schertzer, Daniel; Bompard, Philippe; Ten Veldhuis, Marie-Claire

    2017-04-01

    Nowadays, there is a growing interest on small-scale rainfall information, provided by weather radars, to be used in urban water management and decision-making. Therefore, an increasing interest is in parallel devoted to the development of fully distributed and grid-based models following the increase of computation capabilities, the availability of high-resolution GIS information needed for such models implementation. However, the choice of an appropriate implementation scale to integrate the catchment heterogeneity and the whole measured rainfall variability provided by High-resolution radar technologies still issues. This work proposes a two steps investigation of scale effects in urban hydrology and its effects on modeling works. In the first step fractal tools are used to highlight the scale dependency observed within distributed data used to describe the catchment heterogeneity, both the structure of the sewer network and the distribution of impervious areas are analyzed. Then an intensive multi-scale modeling work is carried out to understand scaling effects on hydrological model performance. Investigations were conducted using a fully distributed and physically based model, Multi-Hydro, developed at Ecole des Ponts ParisTech. The model was implemented at 17 spatial resolutions ranging from 100 m to 5 m and modeling investigations were performed using both rain gauge rainfall information as well as high resolution X band radar data in order to assess the sensitivity of the model to small scale rainfall variability. Results coming out from this work demonstrate scale effect challenges in urban hydrology modeling. In fact, fractal concept highlights the scale dependency observed within distributed data used to implement hydrological models. Patterns of geophysical data change when we change the observation pixel size. The multi-scale modeling investigation performed with Multi-Hydro model at 17 spatial resolutions confirms scaling effect on hydrological model

  1. Construction of a Risk Assessment Model for Rainfall-Induced Landslides

    Science.gov (United States)

    Chen, Yie-Ruey; Tsai, Kuang-Jung; Chen, Jing-Wen; Lin, Wei-Chung

    2013-04-01

    The unstable geology and steep terrain in the mountainous regions of Taiwan make these areas vulnerable to landslides and debris flow during typhoons and heavy rains. According to the Water Resources Agency, Ministry of Economic Affairs of Taiwan, there were 500 typhoons and over one thousand storms in Taiwan between 1897 and 2011. Natural disasters caused 3.5 billion USD of damage between 1983 and 2011. Thus, the construction of risk assessment model for landslides is essential to disaster prevention. This study employed genetic adaptive neural networks (GANN) with texture analysis in the classification of high-resolution satellite images from which data related to surface conditions in mountainous areas of Taiwan were derived. Ten landslide hazard potential factors are included: slope, geology, elevation, distance from the fault, distance from water, terrain roughness, slope roughness, effective accumulated rainfall and developing situation. By using correlation test, GANN, weight analysis and dangerous value method, levels and probabilities of landslide of the research areas are presented. Then, through geographic information system the landslide potential map is plotted to distinguish high potential regions from low potential regions. Through field surveys, interviews with district officials and a review of relevant literature, the probability of a sediment disaster was estimated as well as the vulnerability of the villages concerned and the degree to which these villages were prepared, to construct a risk evaluation model. The regional risk map was plotted with the help of GIS and the landslide assessment model. The risk assessment model can be used by authorities to make provisions for high-risk areas, to reduce the number of casualties and social costs of sediment disasters.

  2. Evaluation TRMM Rainfall Data In Hydrological Modeling For An Ungaged In Lhasa River Basin

    Science.gov (United States)

    Ji, H. J.; Liu, J.

    2017-12-01

    Evaluation TRMM Rainfall Data In Hydrological Modeling For An Ungaged In Lhasa River BasinHaijuan Ji1* Jintao Liu1,2 Shanshan Xu1___________________ 1College of Hydrology and Water Resources, Hohai University, Nanjing 210098, People's Republic of China 2State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing 210098, People's Republic of China ___________________ * Corresponding author. Tel.: +86-025-83786973; Fax: +86-025-83786606. E-mail address: Hhu201510@163.com (H.J. Ji). Abstract: The Tibetan Plateau plays an important role in regulating the regional hydrological processes due to its high elevations and being the headwaters of many major Asian river basins. If familiar with the distribution of hydrological characteristics, will help us improve the level of development and utilization the water resources. However, there exist glaciers and snow with few sites. It is significance for us to understand the glacier and snow hydrological process in order to recognize the evolution of water resources in the Tibetan. This manuscript takes Lhasa River as the study area, taking use of ground, remote sensing and assimilation data, taking advantage of high precision TRMM precipitation data and MODIS snow cover data, first, according to the data from ground station evaluation of TRMM data in the application of the accuracy of the Lhasa River, and based on MODIS data fusion of multi source microwave snow making cloudless snow products, which are used for discriminant and analysis glacier and snow regulation mechanism on day scale, add snow and glacier unit into xinanjing model, this model can simulate the study region's runoff evolution, parameter sensitivity even spatial variation of hydrological characteristics the next ten years on region grid scale. The results of hydrological model in Lhasa River can simulate the glacier and snow runoff variation in high cold region better, to enhance the predictive ability of the spring

  3. Measurement and modeling of diclosulam runoff under the influence of simulated severe rainfall.

    Science.gov (United States)

    van Wesenbeeck, I J; Peacock, A L; Havens, P L

    2001-01-01

    A runoff study was conducted near Tifton, GA to measure the losses of water, sediment, and diclosulam (N-(2,6-dichlorophenyl)-5-ethoxy-7-fluoro-[1,2,4]triazolo-[1,5c]-pyrimidine- 2-sulfonamide), a new broadleaf herbicide, under a 50-mm-in-3-h simulated rainfall event on three separate 0.05-ha plots. Results of a runoff study were used to validate the Pesticide Root Zone Model (PRZM, v. 3.12) using field-measured soil, chemical, and weather inputs. The model-predicted edge-of-field diclosulam loading was within 1% of the average observed diclosulam runoff from the field study; however, partitioning between phases was not as well predicted. The model was subsequently used with worst-case agricultural practice inputs and a 41-yr weather record from Dublin, GA to simulate edge-of-field runoff losses for the two most prevalent soils (Tifton and Bibb) in the southeastern U.S. peanut (Arachis hypogaea L.) market for 328 simulation years, and showed that the 90th percentile runoff amounts, expressed as percent of applied diclosulam, were 1.8, 0.6, and 5.2% for the runoff study plots and Tifton and Bibb soils, respectively. The runoff study and modeling indicated that more than 97% of the total diclosulam runoff was transported off the field by water, with < 3% associated with the sediment. Diclosulam losses due to runoff can be further reduced by lower application rates, tillage and crop residue management practices that reduce edge-of-field runoff, and conservation practices such as vegetated filter strips.

  4. Eye movement accuracy determines natural interception strategies.

    Science.gov (United States)

    Fooken, Jolande; Yeo, Sang-Hoon; Pai, Dinesh K; Spering, Miriam

    2016-11-01

    Eye movements aid visual perception and guide actions such as reaching or grasping. Most previous work on eye-hand coordination has focused on saccadic eye movements. Here we show that smooth pursuit eye movement accuracy strongly predicts both interception accuracy and the strategy used to intercept a moving object. We developed a naturalistic task in which participants (n = 42 varsity baseball players) intercepted a moving dot (a "2D fly ball") with their index finger in a designated "hit zone." Participants were instructed to track the ball with their eyes, but were only shown its initial launch (100-300 ms). Better smooth pursuit resulted in more accurate interceptions and determined the strategy used for interception, i.e., whether interception was early or late in the hit zone. Even though early and late interceptors showed equally accurate interceptions, they may have relied on distinct tactics: early interceptors used cognitive heuristics, whereas late interceptors' performance was best predicted by pursuit accuracy. Late interception may be beneficial in real-world tasks as it provides more time for decision and adjustment. Supporting this view, baseball players who were more senior were more likely to be late interceptors. Our findings suggest that interception strategies are optimally adapted to the proficiency of the pursuit system.

  5. Forced response of the East Asian summer rainfall over the past millennium: results from a coupled model simulation

    Energy Technology Data Exchange (ETDEWEB)

    Liu, Jian; Wang, Hongli; Ti, Ruyuan [Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, State Key Laboratory of Lake Science and Environment, Nanjing (China); Wang, Bin [University of Hawaii at Manoa, Department of Meteorology and IPRC, Honolulu, HI (United States); Kuang, Xueyuan [Nanjing University, School of Atmospheric Sciences, Nanjing (China)

    2011-01-15

    The centennial-millennial variation of the East Asian summer monsoon (EASM) precipitation over the past 1000 years was investigated through the analysis of a millennium simulation of the coupled ECHO-G model. The model results indicate that the centennial-millennial variation of the EASM is essentially a forced response to the external radiative forcing (insolation, volcanic aerosol, and green house gases). The strength of the response depends on latitude; and the spatial structure of the centennial-millennial variation differs from the interannual variability that arises primarily from the internal feedback processes within the climate system. On millennial time scale, the extratropical and subtropical precipitation was generally strong during Medieval Warm Period (MWP) and weak during Little Ice Age (LIA). The tropical rainfall is insensitive to the effective solar radiation forcing (insolation plus radiative effect of volcanic aerosols) but significantly responds to the modern anthropogenic radiative forcing. On centennial time scale, the variation of the extratropical and subtropical rainfall also tends to follow the effective solar radiation forcing closely. The forced response features in-phase rainfall variability between the extratropics and subtropics, which is in contrast to the anti-correlation on the interannual time scale. Further, the behavior of the interannual-decadal variation in the extratropics is effectively modulated by change of the mean states on the millennial time scale, suggesting that the structure of the internal mode may vary with significant changes in the external forcing. These findings imply that on the millennial time scale, (a) the proxy data in the extratropical EA may more sensitively reflect the EASM rainfall variations, and (b) the Meiyu and the northern China rainfall provide a consistent measure for the EASM strength. (orig.)

  6. Physically based modeling of rainfall-triggered landslides: a case study in the Luquillo forest, Puerto Rico

    Science.gov (United States)

    Lepore, C.; Arnone, E.; Noto, L. V.; Sivandran, G.; Bras, R. L.

    2013-09-01

    This paper presents the development of a rainfall-triggered landslide module within an existing physically based spatially distributed ecohydrologic model. The model, tRIBS-VEGGIE (Triangulated Irregular Networks-based Real-time Integrated Basin Simulator and Vegetation Generator for Interactive Evolution), is capable of a sophisticated description of many hydrological processes; in particular, the soil moisture dynamics are resolved at a temporal and spatial resolution required to examine the triggering mechanisms of rainfall-induced landslides. The validity of the tRIBS-VEGGIE model to a tropical environment is shown with an evaluation of its performance against direct observations made within the study area of Luquillo Forest. The newly developed landslide module builds upon the previous version of the tRIBS landslide component. This new module utilizes a numerical solution to the Richards' equation (present in tRIBS-VEGGIE but not in tRIBS), which better represents the time evolution of soil moisture transport through the soil column. Moreover, the new landslide module utilizes an extended formulation of the factor of safety (FS) to correctly quantify the role of matric suction in slope stability and to account for unsaturated conditions in the evaluation of FS. The new modeling framework couples the capabilities of the detailed hydrologic model to describe soil moisture dynamics with the infinite slope model, creating a powerful tool for the assessment of rainfall-triggered landslide risk.

  7. Modeling seasonal leptospirosis transmission and its association with rainfall and temperature in Thailand using time-series and ARIMAX analyses.

    Science.gov (United States)

    Chadsuthi, Sudarat; Modchang, Charin; Lenbury, Yongwimon; Iamsirithaworn, Sopon; Triampo, Wannapong

    2012-07-01

    To study the number of leptospirosis cases in relations to the seasonal pattern, and its association with climate factors. Time series analysis was used to study the time variations in the number of leptospirosis cases. The Autoregressive Integrated Moving Average (ARIMA) model was used in data curve fitting and predicting the next leptospirosis cases. We found that the amount of rainfall was correlated to leptospirosis cases in both regions of interest, namely the northern and northeastern region of Thailand, while the temperature played a role in the northeastern region only. The use of multivariate ARIMA (ARIMAX) model showed that factoring in rainfall (with an 8 months lag) yields the best model for the northern region while the model, which factors in rainfall (with a 10 months lag) and temperature (with an 8 months lag) was the best for the northeastern region. The models are able to show the trend in leptospirosis cases and closely fit the recorded data in both regions. The models can also be used to predict the next seasonal peak quite accurately. Copyright © 2012 Hainan Medical College. Published by Elsevier B.V. All rights reserved.

  8. Physically based modeling of rainfall-triggered landslides: a case study in the Luquillo forest, Puerto Rico

    Directory of Open Access Journals (Sweden)

    C. Lepore

    2013-09-01

    Full Text Available This paper presents the development of a rainfall-triggered landslide module within an existing physically based spatially distributed ecohydrologic model. The model, tRIBS-VEGGIE (Triangulated Irregular Networks-based Real-time Integrated Basin Simulator and Vegetation Generator for Interactive Evolution, is capable of a sophisticated description of many hydrological processes; in particular, the soil moisture dynamics are resolved at a temporal and spatial resolution required to examine the triggering mechanisms of rainfall-induced landslides. The validity of the tRIBS-VEGGIE model to a tropical environment is shown with an evaluation of its performance against direct observations made within the study area of Luquillo Forest. The newly developed landslide module builds upon the previous version of the tRIBS landslide component. This new module utilizes a numerical solution to the Richards' equation (present in tRIBS-VEGGIE but not in tRIBS, which better represents the time evolution of soil moisture transport through the soil column. Moreover, the new landslide module utilizes an extended formulation of the factor of safety (FS to correctly quantify the role of matric suction in slope stability and to account for unsaturated conditions in the evaluation of FS. The new modeling framework couples the capabilities of the detailed hydrologic model to describe soil moisture dynamics with the infinite slope model, creating a powerful tool for the assessment of rainfall-triggered landslide risk.

  9. Instrumental record of debris flow initiation during natural rainfall: Implications for modeling slope stability

    Science.gov (United States)

    Montgomery, D.R.; Schmidt, K.M.; Dietrich, W.E.; McKean, J.

    2009-01-01

    The middle of a hillslope hollow in the Oregon Coast Range failed and mobilized as a debris flow during heavy rainfall in November 1996. Automated pressure transducers recorded high spatial variability of pore water pressure within the area that mobilized as a debris flow, which initiated where local upward flow from bedrock developed into overlying colluvium. Postfailure observations of the bedrock surface exposed in the debris flow scar reveal a strong spatial correspondence between elevated piezometric response and water discharging from bedrock fractures. Measurements of apparent root cohesion on the basal (Cb) and lateral (Cl) scarp demonstrate substantial local variability, with areally weighted values of Cb = 0.1 and Cl = 4.6 kPa. Using measured soil properties and basal root strength, the widely used infinite slope model, employed assuming slope parallel groundwater flow, provides a poor prediction of hydrologie conditions at failure. In contrast, a model including lateral root strength (but neglecting lateral frictional strength) gave a predicted critical value of relative soil saturation that fell within the range defined by the arithmetic and geometric mean values at the time of failure. The 3-D slope stability model CLARA-W, used with locally observed pore water pressure, predicted small areas with lower factors of safety within the overall slide mass at sites consistent with field observations of where the failure initiated. This highly variable and localized nature of small areas of high pore pressure that can trigger slope failure means, however, that substantial uncertainty appears inevitable for estimating hydrologie conditions within incipient debris flows under natural conditions. Copyright 2009 by the American Geophysical Union.

  10. Assimilation of flood extent data with 2D flood inundation models for localised intense rainfall events

    Science.gov (United States)

    Neal, J. C.; Wood, M.; Bermúdez, M.; Hostache, R.; Freer, J. E.; Bates, P. D.; Coxon, G.

    2017-12-01

    Remote sensing of flood inundation extent has long been a potential source of data for constraining and correcting simulations of floodplain inundation. Hydrodynamic models and the computing resources to run them have developed to the extent that simulation of flood inundation in two-dimensional space is now feasible over large river basins in near real-time. However, despite substantial evidence that there is useful information content within inundation extent data, even from low resolution SAR such as that gathered by Envisat ASAR in wide swath mode, making use of the information in a data assimilation system has proved difficult. He we review recent applications of the Ensemble Kalman Filter (EnKF) and Particle Filter for assimilating SAR data, with a focus on the River Severn UK and compare these with complementary research that has looked at the internal error sources and boundary condition errors using detailed terrestrial data that is not available in most locations. Previous applications of the EnKF to this reach have focused on upstream boundary conditions as the source of flow error, however this description of errors was too simplistic for the simulation of summer flood events where localised intense rainfall can be substantial. Therefore, we evaluate the introduction of uncertain lateral inflows to the ensemble. A further limitation of the existing EnKF based methods is the need to convert flood extent to water surface elevations by intersecting the shoreline location with a high quality digital elevation model (e.g. LiDAR). To simplify this data processing step, we evaluate a method to directly assimilate inundation extent as a EnKF model state rather than assimilating water heights, potentially allowing the scheme to be used where high-quality terrain data are sparse.

  11. Multiple data fusion for rainfall estimation using a NARX-based recurrent neural network – the development of the REIINN model

    International Nuclear Information System (INIS)

    Ang, M R C O; Gonzalez, R M; Castro, P P M

    2014-01-01

    Rainfall, one of the important elements of the hydrologic cycle, is also the most difficult to model. Thus, accurate rainfall estimation is necessary especially in localized catchment areas where variability of rainfall is extremely high. Moreover, early warning of severe rainfall through timely and accurate estimation and forecasting could help prevent disasters from flooding. This paper presents the development of two rainfall estimation models that utilize a NARX-based neural network architecture namely: REIINN 1 and REIINN 2. These REIINN models, or Rainfall Estimation by Information Integration using Neural Networks, were trained using MTSAT cloud-top temperature (CTT) images and rainfall rates from the combined rain gauge and TMPA 3B40RT datasets. Model performance was assessed using two metrics – root mean square error (RMSE) and correlation coefficient (R). REIINN 1 yielded an RMSE of 8.1423 mm/3h and an overall R of 0.74652 while REIINN 2 yielded an RMSE of 5.2303 and an overall R of 0.90373. The results, especially that of REIINN 2, are very promising for satellite-based rainfall estimation in a catchment scale. It is believed that model performance and accuracy will greatly improve with a denser and more spatially distributed in-situ rainfall measurements to calibrate the model with. The models proved the viability of using remote sensing images, with their good spatial coverage, near real time availability, and relatively inexpensive to acquire, as an alternative source for rainfall estimation to complement existing ground-based measurements

  12. Assessing the Impacts of Flooding Caused by Extreme Rainfall Events Through a Combined Geospatial and Numerical Modeling Approach

    Science.gov (United States)

    Santillan, J. R.; Amora, A. M.; Makinano-Santillan, M.; Marqueso, J. T.; Cutamora, L. C.; Serviano, J. L.; Makinano, R. M.

    2016-06-01

    In this paper, we present a combined geospatial and two dimensional (2D) flood modeling approach to assess the impacts of flooding due to extreme rainfall events. We developed and implemented this approach to the Tago River Basin in the province of Surigao del Sur in Mindanao, Philippines, an area which suffered great damage due to flooding caused by Tropical Storms Lingling and Jangmi in the year 2014. The geospatial component of the approach involves extraction of several layers of information such as detailed topography/terrain, man-made features (buildings, roads, bridges) from 1-m spatial resolution LiDAR Digital Surface and Terrain Models (DTM/DSMs), and recent land-cover from Landsat 7 ETM+ and Landsat 8 OLI images. We then used these layers as inputs in developing a Hydrologic Engineering Center Hydrologic Modeling System (HEC HMS)-based hydrologic model, and a hydraulic model based on the 2D module of the latest version of HEC River Analysis System (RAS) to dynamically simulate and map the depth and extent of flooding due to extreme rainfall events. The extreme rainfall events used in the simulation represent 6 hypothetical rainfall events with return periods of 2, 5, 10, 25, 50, and 100 years. For each event, maximum flood depth maps were generated from the simulations, and these maps were further transformed into hazard maps by categorizing the flood depth into low, medium and high hazard levels. Using both the flood hazard maps and the layers of information extracted from remotely-sensed datasets in spatial overlay analysis, we were then able to estimate and assess the impacts of these flooding events to buildings, roads, bridges and landcover. Results of the assessments revealed increase in number of buildings, roads and bridges; and increase in areas of land-cover exposed to various flood hazards as rainfall events become more extreme. The wealth of information generated from the flood impact assessment using the approach can be very useful to the

  13. Impact of the calibration period on the conceptual rainfall-runoff model parameter estimates

    Science.gov (United States)

    Todorovic, Andrijana; Plavsic, Jasna

    2015-04-01

    A conceptual rainfall-runoff model is defined by its structure and parameters, which are commonly inferred through model calibration. Parameter estimates depend on objective function(s), optimisation method, and calibration period. Model calibration over different periods may result in dissimilar parameter estimates, while model efficiency decreases outside calibration period. Problem of model (parameter) transferability, which conditions reliability of hydrologic simulations, has been investigated for decades. In this paper, dependence of the parameter estimates and model performance on calibration period is analysed. The main question that is addressed is: are there any changes in optimised parameters and model efficiency that can be linked to the changes in hydrologic or meteorological variables (flow, precipitation and temperature)? Conceptual, semi-distributed HBV-light model is calibrated over five-year periods shifted by a year (sliding time windows). Length of the calibration periods is selected to enable identification of all parameters. One water year of model warm-up precedes every simulation, which starts with the beginning of a water year. The model is calibrated using the built-in GAP optimisation algorithm. The objective function used for calibration is composed of Nash-Sutcliffe coefficient for flows and logarithms of flows, and volumetric error, all of which participate in the composite objective function with approximately equal weights. Same prior parameter ranges are used in all simulations. The model is calibrated against flows observed at the Slovac stream gauge on the Kolubara River in Serbia (records from 1954 to 2013). There are no trends in precipitation nor in flows, however, there is a statistically significant increasing trend in temperatures at this catchment. Parameter variability across the calibration periods is quantified in terms of standard deviations of normalised parameters, enabling detection of the most variable parameters

  14. Model testing on rainfall-induced landslide of loose soil in Wenchuan earthquake region

    Directory of Open Access Journals (Sweden)

    H. Fang

    2012-03-01

    Full Text Available This study investigates the formation process of rainfall-induced landslide for slopes composed of loose soil in the Wenchuan earthquake region. Experimental investigations have been performed on the landslide's formation and the variation of the controlling soil parameters under various artificial rainfall conditions. The landslide triggering mechanisms can be described in the following way. Firstly, the large porosity of the loose soil facilitated the infiltration of water, which increased the pore water pressure and reduced the shear strength of the soil significantly. In addition, the rainfalls probably caused the concentration of finer particles at a certain depth of the valley slopes. This concentration within the soil increased the pore water pressure significantly, and consequently reduced both the porosity ratio and permeability. Therefore, when the pore water pressure reached a critical state, the effective shear strength of the soil diminished, inducing the landslide's formation.

  15. Urban flood return period assessment through rainfall-flood response modelling

    DEFF Research Database (Denmark)

    Murla, Damian; Thorndahl, Søren Liedtke

    Intense rainfall can often cause severe floods, especially in urbanized areas, where population density or large impermeable areas are found. In this context, floods can generate a direct impact in a social-environmental-economic viewpoint. Traditionally, in design of Urban Drainage Systems (UDS......), correlation between return period (RP) of a given rainfall and RP of its consequent flood has been assumed to be linear (e.g.DS/EN752 (2008)). However, this is not always the case. Complex UDS, where diverse hydraulic infrastructures are often found, increase the heterogeneity of system response, which may...... cause an alteration of the mentioned correlation. Consequently, reliability on future urban planning, design and resilience against floods may be also affected by this misassumption. In this study, an assessment of surface flood RP across rainfall RP has been carried out at Lystrup, a urbanized...

  16. Exploring the potential of the cosmic-ray neutron method to measure interception storage dynamics

    Science.gov (United States)

    Jakobi, Jannis; Bogena, Heye; Huisman, Johan Alexander; Diekkrüger, Bernd; Vereecken, Harry

    2017-04-01

    Cosmic-ray neutron soil moisture probes are an emerging technology that relies on the negative correlation between near-surface fast neutron counts and soil moisture content. Hydrogen atoms in the soil, which are mainly present as water, moderate the secondary neutrons on the way back to the surface. Any application of this method needs to consider the sensitivity of the neutron counts to additional sources of hydrogen (e.g. above- and below-ground biomass, humidity of the lower atmosphere, lattice water of the soil minerals, organic matter and water in the litter layer, intercepted water in the canopy, and soil organic matter). In this study, we analyzed the effects of canopy-intercepted water on the cosmic-ray neutron counts. For this, an arable field cropped with sugar beet was instrumented with several cosmic-ray neutron probes and a wireless sensor network with more than 140 in-situ soil moisture sensors. Additionally rainfall interception was estimated using a new approach coupling throughfall measurements and leaf wetness sensors. The derived interception storage was used to correct for interception effects on cosmic ray neutrons to enhance soil water content prediction. Furthermore, the potential for a simultaneous prediction of above- and below-ground biomass, soil moisture and interception was tested.

  17. Projected rainfall and temperature changes over Malaysia at the end of the 21st century based on PRECIS modelling system

    Science.gov (United States)

    Loh, Jui Le; Tangang, Fredolin; Juneng, Liew; Hein, David; Lee, Dong-In

    2016-05-01

    This study investigates projected changes in rainfall and temperature over Malaysia by the end of the 21st century based on the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emission Scenarios (SRES) A2, A1B and B2 emission scenarios using the Providing Regional Climates for Impacts Studies (PRECIS). The PRECIS regional climate model (HadRM3P) is configured in 0.22° × 0.22° horizontal grid resolution and is forced at the lateral boundaries by the UKMO-HadAM3P and UKMOHadCM3Q0 global models. The model performance in simulating the present-day climate was assessed by comparing the modelsimulated results to the Asian Precipitation - Highly-Resolved Observational Data Integration Towards Evaluation (APHRODITE) dataset. Generally, the HadAM3P/PRECIS and HadCM3Q0/PRECIS simulated the spatio-temporal variability structure of both temperature and rainfall reasonably well, albeit with the presence of cold biases. The cold biases appear to be associated with the systematic error in the HadRM3P. The future projection of temperature indicates widespread warming over the entire country by the end of the 21st century. The projected temperature increment ranges from 2.5 to 3.9°C, 2.7 to 4.2°C and 1.7 to 3.1°C for A2, A1B and B2 scenarios, respectively. However, the projection of rainfall at the end of the 21st century indicates substantial spatio-temporal variation with a tendency for drier condition in boreal winter and spring seasons while wetter condition in summer and fall seasons. During the months of December to May, ~20-40% decrease of rainfall is projected over Peninsular Malaysia and Borneo, particularly for the A2 and B2 emission scenarios. During the summer months, rainfall is projected to increase by ~20-40% across most regions in Malaysia, especially for A2 and A1B scenarios. The spatio-temporal variations in the projected rainfall can be related to the changes in the weakening monsoon circulations, which in turn alter the patterns of

  18. Planning of an interceptive movement in children

    NARCIS (Netherlands)

    van Kampen, P.M.; Ledebt, A.; Savelsbergh, G.J.P.

    2010-01-01

    In the present study, we examined the spatio-temporal organization of the walking and reaching behaviour during an interception task in younger (6-9 years old) and older (10-13 years old) children. To this end, eighteen children had to walk towards an interception point to grasp a moving ball under

  19. Intercepting virtual balls approaching under different gravity conditions: evidence for spatial prediction.

    Science.gov (United States)

    Russo, Marta; Cesqui, Benedetta; La Scaleia, Barbara; Ceccarelli, Francesca; Maselli, Antonella; Moscatelli, Alessandro; Zago, Myrka; Lacquaniti, Francesco; d'Avella, Andrea

    2017-10-01

    To accurately time motor responses when intercepting falling balls we rely on an internal model of gravity. However, whether and how such a model is also used to estimate the spatial location of interception is still an open question. Here we addressed this issue by asking 25 participants to intercept balls projected from a fixed location 6 m in front of them and approaching along trajectories with different arrival locations, flight durations, and gravity accelerations (0 g and 1 g ). The trajectories were displayed in an immersive virtual reality system with a wide field of view. Participants intercepted approaching balls with a racket, and they were free to choose the time and place of interception. We found that participants often achieved a better performance with 1 g than 0 g balls. Moreover, the interception points were distributed along the direction of a 1 g path for both 1 g and 0 g balls. In the latter case, interceptions tended to cluster on the upper half of the racket, indicating that participants aimed at a lower position than the actual 0 g path. These results suggest that an internal model of gravity was probably used in predicting the interception locations. However, we found that the difference in performance between 1 g and 0 g balls was modulated by flight duration, the difference being larger for faster balls. In addition, the number of peaks in the hand speed profiles increased with flight duration, suggesting that visual information was used to adjust the motor response, correcting the prediction to some extent. NEW & NOTEWORTHY Here we show that an internal model of gravity plays a key role in predicting where to intercept a fast-moving target. Participants also assumed an accelerated motion when intercepting balls approaching in a virtual environment at constant velocity. We also show that the role of visual information in guiding interceptive movement increases when more time is available. Copyright © 2017 the American Physiological

  20. Including local rainfall dynamics and uncertain boundary conditions into a 2-D regional-local flood modelling cascade

    Science.gov (United States)

    Bermúdez, María; Neal, Jeffrey C.; Bates, Paul D.; Coxon, Gemma; Freer, Jim E.; Cea, Luis; Puertas, Jerónimo

    2016-04-01

    Flood inundation models require appropriate boundary conditions to be specified at the limits of the domain, which commonly consist of upstream flow rate and downstream water level. These data are usually acquired from gauging stations on the river network where measured water levels are converted to discharge via a rating curve. Derived streamflow estimates are therefore subject to uncertainties in this rating curve, including extrapolating beyond the maximum observed ratings magnitude. In addition, the limited number of gauges in reach-scale studies often requires flow to be routed from the nearest upstream gauge to the boundary of the model domain. This introduces additional uncertainty, derived not only from the flow routing method used, but also from the additional lateral rainfall-runoff contributions downstream of the gauging point. Although generally assumed to have a minor impact on discharge in fluvial flood modeling, this local hydrological input may become important in a sparse gauge network or in events with significant local rainfall. In this study, a method to incorporate rating curve uncertainty and the local rainfall-runoff dynamics into the predictions of a reach-scale flood inundation model is proposed. Discharge uncertainty bounds are generated by applying a non-parametric local weighted regression approach to stage-discharge measurements for two gauging stations, while measured rainfall downstream from these locations is cascaded into a hydrological model to quantify additional inflows along the main channel. A regional simplified-physics hydraulic model is then applied to combine these inputs and generate an ensemble of discharge and water elevation time series at the boundaries of a local-scale high complexity hydraulic model. Finally, the effect of these rainfall dynamics and uncertain boundary conditions are evaluated on the local-scale model. Improvements in model performance when incorporating these processes are quantified using observed

  1. Stability analysis of unsaturated soil slope during rainfall infiltration using coupled liquid-gas-solid three-phase model

    Directory of Open Access Journals (Sweden)

    Dong-mei Sun

    2016-07-01

    Full Text Available Generally, most soil slope failures are induced by rainfall infiltration, a process that involves interactions between the liquid phase, gas phase, and solid skeleton in an unsaturated soil slope. In this study, a loosely coupled liquid-gas-solid three-phase model, linking two numerical codes, TOUGH2/EOS3, which is used for water-air two-phase flow analysis, and FLAC3D, which is used for mechanical analysis, was established. The model was validated through a documented water drainage experiment over a sandy column and a comparison of the results with measured data and simulated results from other researchers. The proposed model was used to investigate the features of water-air two-phase flow and stress fields in an unsaturated soil slope during rainfall infiltration. The slope stability analysis was then performed based on the simulated water-air two-phase seepage and stress fields on a given slip surface. The results show that the safety factor for the given slip surface decreases first, then increases, and later decreases until the rainfall stops. Subsequently, a sudden rise occurs. After that, the safety factor decreases continually and reaches its lowest value, and then increases slowly to a steady value. The lowest value does not occur when the rainfall stops, indicating a delayed effect of the safety factor. The variations of the safety factor for the given slip surface are therefore caused by a combination of pore-air pressure, matric suction, normal stress, and net normal stress.

  2. Does internal variability change in response to global warming? A large ensemble modelling study of tropical rainfall

    Science.gov (United States)

    Milinski, S.; Bader, J.; Jungclaus, J. H.; Marotzke, J.

    2017-12-01

    There is some consensus on mean state changes of rainfall under global warming; changes of the internal variability, on the other hand, are more difficult to analyse and have not been discussed as much despite their importance for understanding changes in extreme events, such as droughts or floodings. We analyse changes in the rainfall variability in the tropical Atlantic region. We use a 100-member ensemble of historical (1850-2005) model simulations with the Max Planck Institute for Meteorology Earth System Model (MPI-ESM1) to identify changes of internal rainfall variability. To investigate the effects of global warming on the internal variability, we employ an additional ensemble of model simulations with stronger external forcing (1% CO2-increase per year, same integration length as the historical simulations) with 68 ensemble members. The focus of our study is on the oceanic Atlantic ITCZ. We find that the internal variability of rainfall over the tropical Atlantic does change due to global warming and that these changes in variability are larger than changes in the mean state in some regions. From splitting the total variance into patterns of variability, we see that the variability on the southern flank of the ITCZ becomes more dominant, i.e. explaining a larger fraction of the total variance in a warmer climate. In agreement with previous studies, we find that changes in the mean state show an increase and narrowing of the ITCZ. The large ensembles allow us to do a statistically robust differentiation between the changes in variability that can be explained by internal variability and those that can be attributed to the external forcing. Furthermore, we argue that internal variability in a transient climate is only well defined in the ensemble domain and not in the temporal domain, which requires the use of a large ensemble.

  3. A simulation-optimization model for Stone column-supported embankment stability considering rainfall effect

    International Nuclear Information System (INIS)

    Deb, Kousik; Dhar, Anirban; Purohit, Sandip

    2016-01-01

    Landslide due to rainfall has been and continues to be one of the most important concerns of geotechnical engineering. The paper presents the variation of factor of safety of stone column-supported embankment constructed over soft soil due to change in water level for an incessant period of rainfall. A combined simulation-optimization based methodology has been proposed to predict the critical surface of failure of the embankment and to optimize the corresponding factor of safety under rainfall conditions using an evolutionary genetic algorithm NSGA-II (Non-Dominated Sorted Genetic Algorithm-II). It has been observed that the position of water table can be reliably estimated with varying periods of infiltration using developed numerical method. The parametric study is presented to study the optimum factor of safety of the embankment and its corresponding critical failure surface under the steady-state infiltration condition. Results show that in case of floating stone columns, period of infiltration has no effect on factor of safety. Even critical failure surfaces for a particular floating column length remain same irrespective of rainfall duration

  4. Comparison of radar and numerical weather model rainfall forecasts in the perspective of urban flood prediction

    DEFF Research Database (Denmark)

    Lovring, Maite Monica; Löwe, Roland; Courdent, Vianney Augustin Thomas

    An early flood warning system has been developed for urban catchments and is currently running in online operation in Copenhagen. The system is highly dependent on the quality of rainfall forecast inputs. An investigation of precipitation inputs from Radar Nowcast (RN), Numerical Weather Prediction...

  5. Evaluation of remote-sensing-based rainfall products through predictive capability in hydrological runoff modelling

    DEFF Research Database (Denmark)

    Stisen, Simon; Sandholt, Inge

    2010-01-01

    SRFEs, Climate Prediction Center MORPHing technique (CMORPH), Tropical Rainfall Measuring Mission (TRMM) and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN). The best performing SRFE, CPC-FEWS, produced good results with values of R2NS between 0...

  6. South African mid-summer seasonal rainfall prediction performance by a coupled ocean-atmosphere model

    CSIR Research Space (South Africa)

    Landman, WA

    2011-01-01

    Full Text Available . 2000; Goddard and Mason, 2002). Such a so-called two-tiered procedure to predict the outcome of the rainfall season has been employed in South Africa for a number of years already (e.g., Landman et al., 2001). The advent of fully coupled ocean...

  7. A simulation-optimization model for Stone column-supported embankment stability considering rainfall effect

    Energy Technology Data Exchange (ETDEWEB)

    Deb, Kousik, E-mail: kousik@civil.iitkgp.ernet.in [Associate Professor, Department of Civil Engineering, IIT Kharagpur, Kharagpur-721302 (India); Dhar, Anirban, E-mail: anirban@civil.iitkgp.ernet.in [Assistant Professor, Department of Civil Engineering, IIT Kharagpur, Kharagpur-721302 (India); Purohit, Sandip, E-mail: sandip.purohit91@gmail.com [Former B.Tech Student, Department of Civil Engineering, NIT Rourkela, Rourkela (India)

    2016-02-01

    Landslide due to rainfall has been and continues to be one of the most important concerns of geotechnical engineering. The paper presents the variation of factor of safety of stone column-supported embankment constructed over soft soil due to change in water level for an incessant period of rainfall. A combined simulation-optimization based methodology has been proposed to predict the critical surface of failure of the embankment and to optimize the corresponding factor of safety under rainfall conditions using an evolutionary genetic algorithm NSGA-II (Non-Dominated Sorted Genetic Algorithm-II). It has been observed that the position of water table can be reliably estimated with varying periods of infiltration using developed numerical method. The parametric study is presented to study the optimum factor of safety of the embankment and its corresponding critical failure surface under the steady-state infiltration condition. Results show that in case of floating stone columns, period of infiltration has no effect on factor of safety. Even critical failure surfaces for a particular floating column length remain same irrespective of rainfall duration.

  8. How much complexity is warranted in a rainfall-runoff model? Findings obtained from symbolic regression, using Eureqa

    Science.gov (United States)

    Abrahart, R. J.; Beriro, D. J.

    2012-04-01

    The information content in a rainfall-runoff record is sufficient to support models of only very limited complexity (Jakeman and Hornberger, 1993). This begs the question of what limits should observed data place on the allowable complexity of rainfall-runoff models? Eureqa1 (Schmidt and Lipson, 2009) - pronounced "eureka" - is a software tool for finding equations and detecting mathematical relationships in a dataset. The challenge, for both software and modeller, is to identify, by means of symbolic regression, the simplest mathematical formulas which describe the underlying mechanisms that produced the data. It actually delivers, however, a series of preferred modelling solutions comprising one champion for each specific level of complexity i.e. related to solution enlargement involving the progressive incorporation of additional permitted factors (internal operators/ external drivers). The potential benefit of increased complexity can as a result be assessed in a rational manner. Eureqa is free to download and use; and, in the current study, has been employed to construct a set of rainfall-runoff transfer function models for the Annapolis River at Wilmot, in north-western Nova Scotia, Canada. The climatic conditions in this catchment present an interesting set of modelling challenges; daily variations and seasonal changes in temperature, snowfall and retention result in great difficulty for runoff prediction by means of a data-driven approach. Data from 10 years of daily observations are used in the present study (01/01/2000-31/12/2009): comprising [i] discharge, [ii] total rainfall (excluding snowfall), [iii] total snowfall, [iv] thickness of snow cover, and [v] maximum and [vi] minimum temperature. Precipitation occurs throughout the whole year being slightly lower during summer. Snowfall is common from November until April and rare hurricane weather may occur in autumn. The average maximum temperature is below 0 0C in January and February, but significant

  9. Estimating the timing and location of shallow rainfall-induced landslides using a model for transient, unsaturated infiltration

    Science.gov (United States)

    Baum, Rex L.; Godt, Jonathan W.; Savage, William Z.

    2010-01-01

    Shallow rainfall-induced landslides commonly occur under conditions of transient infiltration into initially unsaturated soils. In an effort to predict the timing and location of such landslides, we developed a model of the infiltration process using a two-layer system that consists of an unsaturated zone above a saturated zone and implemented this model in a geographic information system (GIS) framework. The model links analytical solutions for transient, unsaturated, vertical infiltration above the water table to pressure-diffusion solutions for pressure changes below the water table. The solutions are coupled through a transient water table that rises as water accumulates at the base of the unsaturated zone. This scheme, though limited to simplified soil-water characteristics and moist initial conditions, greatly improves computational efficiency over numerical models in spatially distributed modeling applications. Pore pressures computed by these coupled models are subsequently used in one-dimensional slope-stability computations to estimate the timing and locations of slope failures. Applied over a digital landscape near Seattle, Washington, for an hourly rainfall history known to trigger shallow landslides, the model computes a factor of safety for each grid cell at any time during a rainstorm. The unsaturated layer attenuates and delays the rainfall-induced pore-pressure response of the model at depth, consistent with observations at an instrumented hillside near Edmonds, Washington. This attenuation results in realistic estimates of timing for the onset of slope instability (7 h earlier than observed landslides, on average). By considering the spatial distribution of physical properties, the model predicts the primary source areas of landslides.

  10. Fractional-Order Information in the Visual Control of Lateral Locomotor Interception

    NARCIS (Netherlands)

    Bootsma, Reinoud J.; Ledouit, Simon; Casanova, Remy; Zaal, Frank T. J. M.

    Previous work on locomotor interception of a target moving in the transverse plane has suggested that interception is achieved by maintaining the target's bearing angle (often inadvertently confused and/or confounded with the target heading angle) at a constant value. However, dynamics-based model

  11. Estimation of groundwater recharge via percolation outputs from a rainfall/runoff model for the Verlorenvlei estuarine system, west coast, South Africa

    Science.gov (United States)

    Watson, Andrew; Miller, Jodie; Fleischer, Melanie; de Clercq, Willem

    2018-03-01

    Wetlands are conservation priorities worldwide, due to their high biodiversity and productivity, but are under threat from agricultural and climate change stresses. To improve the water management practices and resource allocation in these complex systems, a modelling approach has been developed to estimate potential recharge for data poor catchments using rainfall data and basic assumptions regarding soil and aquifer properties. The Verlorenvlei estuarine lake (RAMSAR #525) on the west coast of South Africa is a data poor catchment where rainfall records have been supplemented with farmer's rainfall records. The catchment has multiple competing users. To determine the ecological reserve for the wetlands, the spatial and temporal distribution of recharge had to be well constrained using the J2000 rainfall/runoff model. The majority of rainfall occurs in the mountains (±650 mm/yr) and considerably less in the valley (±280 mm/yr). Percolation was modelled as ∼3.6% of rainfall in the driest parts of the catchment, ∼10% of rainfall in the moderately wet parts of the catchment and ∼8.4% but up to 28.9% of rainfall in the wettest parts of the catchment. The model results are representative of rainfall and water level measurements in the catchment, and compare well with water table fluctuation technique, although estimates are dissimilar to previous estimates within the catchment. This is most likely due to the daily timestep nature of the model, in comparison to other yearly average methods. These results go some way in understanding the fact that although most semi-arid catchments have very low yearly recharge estimates, they are still capable of sustaining high biodiversity levels. This demonstrates the importance of incorporating shorter term recharge event modeling for improving recharge estimates.

  12. A framework of integrated hydrological and hydrodynamic models using synthetic rainfall for flash flood hazard mapping of ungauged catchments in tropical zones

    Directory of Open Access Journals (Sweden)

    W. Lohpaisankrit

    2016-05-01

    Full Text Available Flash flood hazard maps provide a scientific support to mitigate flash flood risk. The present study develops a practical framework with the help of integrated hydrological and hydrodynamic modelling in order to estimate the potential flash floods. We selected a small pilot catchment which has already suffered from flash floods in the past. This catchment is located in the Nan River basin, northern Thailand. Reliable meteorological and hydrometric data are missing in the catchment. Consequently, the entire upper basin of the main river was modelled with the help of the hydrological modelling system PANTA RHEI. In this basin, three monitoring stations are located along the main river. PANTA RHEI was calibrated and validated with the extreme flood events in June 2011 and July 2008, respectively. The results show a good agreement with the observed discharge data. In order to create potential flash flood scenarios, synthetic rainfall series were derived from temporal rainfall patterns based on the radar-rainfall observation and different rainfall depths from regional rainfall frequency analysis. The temporal rainfall patterns were characterized by catchment-averaged rainfall series selected from 13 rainstorms in 2008 and 2011 within the region. For regional rainfall frequency analysis, the well-known L-moments approach and related criteria were used to examine extremely climatic homogeneity of the region. According to the L-moments approach, Generalized Pareto distribution was recognized as the regional frequency distribution. The synthetic rainfall series were fed into the PANTA RHEI model. The simulated results from PANTA RHEI were provided to a 2-D hydrodynamic model (MEADFLOW, and various simulations were performed. Results from the integrated modelling framework are used in the ongoing study to regionalize and map the spatial distribution of flash flood hazards with four levels of flood severities. As an overall outcome, the presented framework

  13. Seasonality in cholera dynamics: A rainfall-driven model explains the wide range of patterns in endemic areas

    Science.gov (United States)

    Baracchini, Theo; King, Aaron A.; Bouma, Menno J.; Rodó, Xavier; Bertuzzo, Enrico; Pascual, Mercedes

    2017-10-01

    Seasonal patterns in cholera dynamics exhibit pronounced variability across geographical regions, showing single or multiple peaks at different times of the year. Although multiple hypotheses related to local climate variables have been proposed, an understanding of this seasonal variation remains incomplete. The historical Bengal region, which encompasses the full range of cholera's seasonality observed worldwide, provides a unique opportunity to gain insights on underlying environmental drivers. Here, we propose a mechanistic, rainfall-temperature driven, stochastic epidemiological model which explicitly accounts for the fluctuations of the aquatic reservoir, and analyze with this model the historical dataset of cholera mortality in the Bengal region. Parameters are inferred with a recently developed sequential Monte Carlo method for likelihood maximization in partially observed Markov processes. Results indicate that the hydrological regime is a major driver of the seasonal dynamics of cholera. Rainfall tends to buffer the propagation of the disease in wet regions due to the longer residence times of water in the environment and an associated dilution effect, whereas it enhances cholera resurgence in dry regions. Moreover, the dynamics of the environmental water reservoir determine whether the seasonality is unimodal or bimodal, as well as its phase relative to the monsoon. Thus, the full range of seasonal patterns can be explained based solely on the local variation of rainfall and temperature. Given the close connection between cholera seasonality and environmental conditions, a deeper understanding of the underlying mechanisms would allow the better management and planning of public health policies with respect to climate variability and climate change.

  14. Flood modelling with global precipitation measurement (GPM) satellite rainfall data: a case study of Dehradun, Uttarakhand, India

    Science.gov (United States)

    Sai Krishna, V. V.; Dikshit, Anil Kumar; Pandey, Kamal

    2016-05-01

    Urban expansion, water bodies and climate change are inextricably linked with each other. The macro and micro level climate changes are leading to extreme precipitation events which have severe consequences on flooding in urban areas. Flood simulations shall be helpful in demarcation of flooded areas and effective flood planning and preparedness. The temporal availability of satellite rainfall data at varying spatial scale of 0.10 to 0.50 is helpful in near real time flood simulations. The present research aims at analysing stream flow and runoff to monitor flood condition using satellite rainfall data in a hydrologic model. The satellite rainfall data used in the research was NASA's Integrated Multi-satellite Retrievals for Global Precipitation Measurement (IMERG), which is available at 30 minutes temporal resolution. Landsat data was used for mapping the water bodies in the study area. Land use land cover (LULC) data was prepared using Landsat 8 data with maximum likelihood technique that was provided as an input to the HEC-HMS hydrological model. The research was applied to one of the urbanized cities of India, viz. Dehradun, which is the capital of Uttarakhand State. The research helped in identifying the flood vulnerability at the basin level on the basis of the runoff and various socio economic parameters using multi criteria analysis.

  15. Hydrological control of large hurricane-induced lahars: evidence from rainfall-runoff modeling, seismic and video monitoring

    Science.gov (United States)

    Capra, Lucia; Coviello, Velio; Borselli, Lorenzo; Márquez-Ramírez, Víctor-Hugo; Arámbula-Mendoza, Raul

    2018-03-01

    The Volcán de Colima, one of the most active volcanoes in Mexico, is commonly affected by tropical rains related to hurricanes that form over the Pacific Ocean. In 2011, 2013 and 2015 hurricanes Jova, Manuel and Patricia, respectively, triggered tropical storms that deposited up to 400 mm of rain in 36 h, with maximum intensities of 50 mm h -1. The effects were devastating, with the formation of multiple lahars along La Lumbre and Montegrande ravines, which are the most active channels in sediment delivery on the south-southwest flank of the volcano. Deep erosion along the river channels and several marginal landslides were observed, and the arrival of block-rich flow fronts resulted in damages to bridges and paved roads in the distal reaches of the ravines. The temporal sequence of these flow events is reconstructed and analyzed using monitoring data (including video images, seismic records and rainfall data) with respect to the rainfall characteristics and the hydrologic response of the watersheds based on rainfall-runoff numerical simulation. For the studied events, lahars occurred 5-6 h after the onset of rainfall, lasted several hours and were characterized by several pulses with block-rich fronts and a maximum flow discharge of 900 m3 s -1. Rainfall-runoff simulations were performer using the SCS-curve number and the Green-Ampt infiltration models, providing a similar result in the detection of simulated maximum watershed peaks discharge. Results show different behavior for the arrival times of the first lahar pulses that correlate with the simulated catchment's peak discharge for La Lumbre ravine and with the peaks in rainfall intensity for Montegrande ravine. This different behavior is related to the area and shape of the two watersheds. Nevertheless, in all analyzed cases, the largest lahar pulse always corresponds with the last one and correlates with the simulated maximum peak discharge of these catchments. Data presented here show that flow pulses

  16. Evaluation of sub daily satellite rainfall estimates through flash flood modelling in the Lower Middle Zambezi Basin

    Directory of Open Access Journals (Sweden)

    T. Matingo

    2018-05-01

    Full Text Available Flash floods are experienced almost annually in the ungauged Mbire District of the Middle Zambezi Basin. Studies related to hydrological modelling (rainfall-runoff and flood forecasting require major inputs such as precipitation which, due to shortage of observed data, are increasingly using indirect methods for estimating precipitation. This study therefore evaluated performance of CMORPH and TRMM satellite rainfall estimates (SREs for 30 min, 1 h, 3 h and daily intensities through hydrologic and flash flood modelling in the Lower Middle Zambezi Basin for the period 2013–2016. On a daily timestep, uncorrected CMORPH and TRMM show Probability of Detection (POD of 61 and 59 %, respectively, when compared to rain gauge observations. The best performance using Correlation Coefficient (CC was 70 and 60 % on daily timesteps for CMORPH and TRMM, respectively. The best RMSE for CMORPH was 0.81 % for 30 min timestep and for TRMM was 2, 11 % on 3 h timestep. For the year 2014 to 2015, the HEC-HMS (Hydrological Engineering Centre-Hydrological Modelling System daily model calibration Nash Sutcliffe efficiency (NSE for Musengezi sub catchment was 59 % whilst for Angwa it was 55 %. Angwa sub-catchment daily NSE results for the period 2015–2016 was 61 %. HEC-RAS flash flood modeling at 100, 50 and 25 year return periods for Angwa sub catchment, inundated 811 and 867 ha for TRMM rainfall simulated discharge at 3 h and daily timesteps, respectively. For CMORPH generated rainfall, the inundation was 818, 876, 890 and 891 ha at daily, 3 h, 1 h and 30 min timesteps. The 30 min time step for CMORPH effectively captures flash floods with the measure of agreement between simulated flood extent and ground control points of 69 %. For TRMM, the 3 h timestep effectively captures flash floods with coefficient of 67 %. The study therefore concludes that satellite products are most effective in capturing localized

  17. Analysis and prediction of rainfall trends over Bangladesh using Mann-Kendall, Spearman's rho tests and ARIMA model

    Science.gov (United States)

    Rahman, Mohammad Atiqur; Yunsheng, Lou; Sultana, Nahid

    2017-08-01

    In this study, 60-year monthly rainfall data of Bangladesh were analysed to detect trends. Modified Mann-Kendall, Spearman's rho tests and Sen's slope estimators were applied to find the long-term annual, dry season and monthly trends. Sequential Mann-Kendall analysis was applied to detect the potential trend turning points. Spatial variations of the trends were examined using inverse distance weighting (IDW) interpolation. AutoRegressive integrated moving average (ARIMA) model was used for the country mean rainfall and for other two stations data which depicted the highest and the lowest trend in the Mann-Kendall and Spearman's rho tests. Results showed that there is no significant trend in annual rainfall pattern except increasing trends for Cox's Bazar, Khulna, Satkhira and decreasing trend for Srimagal areas. For the dry season, only Bogra area represented significant decreasing trend. Long-term monthly trends demonstrated a mixed pattern; both negative and positive changes were found from February to September. Comilla area showed a significant decreasing trend for consecutive 3 months while Rangpur and Khulna stations confirmed the significant rising trends for three different months in month-wise trends analysis. Rangpur station data gave a maximum increasing trend in April whereas a maximum decreasing trend was found in August for Comilla station. ARIMA models predict +3.26, +8.6 and -2.30 mm rainfall per year for the country, Cox's Bazar and Srimangal areas, respectively. However, all the test results and predictions revealed a good agreement among them in the study.

  18. Spatial dependence of extreme rainfall

    Science.gov (United States)

    Radi, Noor Fadhilah Ahmad; Zakaria, Roslinazairimah; Satari, Siti Zanariah; Azman, Muhammad Az-zuhri

    2017-05-01

    This study aims to model the spatial extreme daily rainfall process using the max-stable model. The max-stable model is used to capture the dependence structure of spatial properties of extreme rainfall. Three models from max-stable are considered namely Smith, Schlather and Brown-Resnick models. The methods are applied on 12 selected rainfall stations in Kelantan, Malaysia. Most of the extreme rainfall data occur during wet season from October to December of 1971 to 2012. This period is chosen to assure the available data is enough to satisfy the assumption of stationarity. The dependence parameters including the range and smoothness, are estimated using composite likelihood approach. Then, the bootstrap approach is applied to generate synthetic extreme rainfall data for all models using the estimated dependence parameters. The goodness of fit between the observed extreme rainfall and the synthetic data is assessed using the composite likelihood information criterion (CLIC). Results show that Schlather model is the best followed by Brown-Resnick and Smith models based on the smallest CLIC's value. Thus, the max-stable model is suitable to be used to model extreme rainfall in Kelantan. The study on spatial dependence in extreme rainfall modelling is important to reduce the uncertainties of the point estimates for the tail index. If the spatial dependency is estimated individually, the uncertainties will be large. Furthermore, in the case of joint return level is of interest, taking into accounts the spatial dependence properties will improve the estimation process.

  19. Mixing the Green-Ampt model and Curve Number method as an empirical tool for rainfall excess estimation in small ungauged catchments.

    Science.gov (United States)

    Grimaldi, S.; Petroselli, A.; Romano, N.

    2012-04-01

    The Soil Conservation Service - Curve Number (SCS-CN) method is a popular rainfall-runoff model that is widely used to estimate direct runoff from small and ungauged basins. The SCS-CN is a simple and valuable approach to estimate the total stream-flow volume generated by a storm rainfall, but it was developed to be used with daily rainfall data. To overcome this drawback, we propose to include the Green-Ampt (GA) infiltration model into a mixed procedure, which is referred to as CN4GA (Curve Number for Green-Ampt), aiming to distribute in time the information provided by the SCS-CN method so as to provide estimation of sub-daily incremental rainfall excess. For a given storm, the computed SCS-CN total net rainfall amount is used to calibrate the soil hydraulic conductivity parameter of the Green-Ampt model. The proposed procedure was evaluated by analyzing 100 rainfall-runoff events observed in four small catchments of varying size. CN4GA appears an encouraging tool for predicting the net rainfall peak and duration values and has shown, at least for the test cases considered in this study, a better agreement with observed hydrographs than that of the classic SCS-CN method.

  20. Simulation of boreal Summer Monsoon Rainfall using CFSV2_SSiB model: sensitivity to Land Use Land Cover (LULC)

    Science.gov (United States)

    Chilukoti, N.; Xue, Y.

    2016-12-01

    The land surface play a vital role in determining the surface energy budget, accurate representation of land use and land cover (LULC) is necessary to improve forecast. In this study, we have investigated the influence of surface vegetation maps with different LULC on simulating the boreal summer monsoon rainfall. Using a National Centres for Environmental Prediction (NCEP) Coupled Forecast System version 2(CFSv2) model coupled with Simplified Simple Biosphere (SSiB) model, two experiments were conducted: one with old vegetation map and one with new vegetation map. The significant differences between new and old vegetation map were in semi-arid and arid areas. For example, in old map Tibetan plateau classified as desert, which is not appropriate, while in new map it was classified as grasslands or shrubs with bare soil. Old map classified the Sahara desert as a bare soil and shrubs with bare soil, whereas in new map it was classified as bare ground. In addition to central Asia and the Sahara desert, in new vegetation map, Europe had more cropped area and India's vegetation cover was changed from crops and forests to wooded grassland and small areas of grassland and shrubs. The simulated surface air temperature with new map shows a significant improvement over Asia, South Africa, and northern America by some 1 to 2ºC and 2 to 3ºC over north east China and these are consistent with the reduced rainfall biases over Africa, near Somali coast, north east India, Bangladesh, east China sea, eastern Pacific and northern USA. Over Indian continent and bay of Bengal dry rainfall anomalies that is the only area showing large dry rainfall bias, however, they were unchanged with new map simulation. Overall the CFSv2(coupled with SSiB) model with new vegetation map show a promising result in improving the monsoon forecast by improving the Land -Atmosphere interactions. To compare with the LULC forcing, experiment was conducted using the Global Forecast System (GFS) simulations

  1. Similarity-based multi-model ensemble approach for 1-15-day advance prediction of monsoon rainfall over India

    Science.gov (United States)

    Jaiswal, Neeru; Kishtawal, C. M.; Bhomia, Swati

    2018-04-01

    The southwest (SW) monsoon season (June, July, August and September) is the major period of rainfall over the Indian region. The present study focuses on the development of a new multi-model ensemble approach based on the similarity criterion (SMME) for the prediction of SW monsoon rainfall in the extended range. This approach is based on the assumption that training with the similar type of conditions may provide the better forecasts in spite of the sequential training which is being used in the conventional MME approaches. In this approach, the training dataset has been selected by matching the present day condition to the archived dataset and days with the most similar conditions were identified and used for training the model. The coefficients thus generated were used for the rainfall prediction. The precipitation forecasts from four general circulation models (GCMs), viz. European Centre for Medium-Range Weather Forecasts (ECMWF), United Kingdom Meteorological Office (UKMO), National Centre for Environment Prediction (NCEP) and China Meteorological Administration (CMA) have been used for developing the SMME forecasts. The forecasts of 1-5, 6-10 and 11-15 days were generated using the newly developed approach for each pentad of June-September during the years 2008-2013 and the skill of the model was analysed using verification scores, viz. equitable skill score (ETS), mean absolute error (MAE), Pearson's correlation coefficient and Nash-Sutcliffe model efficiency index. Statistical analysis of SMME forecasts shows superior forecast skill compared to the conventional MME and the individual models for all the pentads, viz. 1-5, 6-10 and 11-15 days.

  2. Throughfall and temporal trends of rainfall redistribution in an open tropical rainforest, south-western Amazonia (Rondônia, Brazil

    Directory of Open Access Journals (Sweden)

    S. Germer

    2006-01-01

    Full Text Available Throughfall volumes and incident rainfall were measured between 23 August and 2 December 2004 as well as from 6 January to 15 April 2005 for individual rain events of differing intensities and magnitudes in an open tropical rainforest in Rondônia, Brazil. Temporal patterns of throughfall spatial variability were examined. Estimated interception was compared to modeled interception obtained by applying the revised Gash model in order to identify sources of throughfall variability in open tropical rainforests. Gross precipitation of 97 events amounted to 1309 mm, 89±5.6% (S.E. of which reached the forest floor as throughfall. The redistribution of water within the canopy was highly variable in time, which we attribute to the high density of babassu palms (Orbignya phalerata, their seasonal leaf growth, and their conducive morphology. We identified a 10-min rainfall intensity threshold of 30 mmh-1 above which interception was highly variable. This variability is amplified by funneling and shading effects of palms. This interaction between a rainfall variable and vegetation characteristics is relevant for understanding the hydrology of all tropical rainforests with a high palm density.

  3. Areal rainfall estimation using moving cars – computer experiments including hydrological modeling

    OpenAIRE

    E. Rabiei; U. Haberlandt; M. Sester; D. Fitzner; M. Wallner

    2016-01-01

    The need for high temporal and spatial resolution precipitation data for hydrological analyses has been discussed in several studies. Although rain gauges provide valuable information, a very dense rain gauge network is costly. As a result, several new ideas have emerged to help estimating areal rainfall with higher temporal and spatial resolution. Rabiei et al. (2013) observed that moving cars, called RainCars (RCs), can potentially be a new source of data for measuring rai...

  4. Catchment area-based evaluation of the AMC-dependent SCS-CN-based rainfall-runoff models

    Science.gov (United States)

    Mishra, S. K.; Jain, M. K.; Pandey, R. P.; Singh, V. P.

    2005-09-01

    Using a large set of rainfall-runoff data from 234 watersheds in the USA, a catchment area-based evaluation of the modified version of the Mishra and Singh (2002a) model was performed. The model is based on the Soil Conservation Service Curve Number (SCS-CN) methodology and incorporates the antecedent moisture in computation of direct surface runoff. Comparison with the existing SCS-CN method showed that the modified version performed better than did the existing one on the data of all seven area-based groups of watersheds ranging from 0.01 to 310.3 km2.

  5. Modelling of extreme rainfall events in Peninsular Malaysia based on annual maximum and partial duration series

    Science.gov (United States)

    Zin, Wan Zawiah Wan; Shinyie, Wendy Ling; Jemain, Abdul Aziz

    2015-02-01

    In this study, two series of data for extreme rainfall events are generated based on Annual Maximum and Partial Duration Methods, derived from 102 rain-gauge stations in Peninsular from 1982-2012. To determine the optimal threshold for each station, several requirements must be satisfied and Adapted Hill estimator is employed for this purpose. A semi-parametric bootstrap is then used to estimate the mean square error (MSE) of the estimator at each threshold and the optimal threshold is selected based on the smallest MSE. The mean annual frequency is also checked to ensure that it lies in the range of one to five and the resulting data is also de-clustered to ensure independence. The two data series are then fitted to Generalized Extreme Value and Generalized Pareto distributions for annual maximum and partial duration series, respectively. The parameter estimation methods used are the Maximum Likelihood and the L-moment methods. Two goodness of fit tests are then used to evaluate the best-fitted distribution. The results showed that the Partial Duration series with Generalized Pareto distribution and Maximum Likelihood parameter estimation provides the best representation for extreme rainfall events in Peninsular Malaysia for majority of the stations studied. Based on these findings, several return values are also derived and spatial mapping are constructed to identify the distribution characteristic of extreme rainfall in Peninsular Malaysia.

  6. Radar rainfall estimation in a hilly environment and implications for runoff modeling

    Science.gov (United States)

    Hazenberg, Pieter; Leijnse, Hidde; Uijlenhoet, Remko

    2010-05-01

    Radars are known for their ability to obtain a wealth of information about the spatial stormfield characteristics. Unfortunately, rainfall estimates obtained by this instrument are known to be affected by multiple sources of error. Especially for stratiform precipitation systems, the quality of radar rainfall estimates starts to decrease at relatively close ranges. In the current study the hydrological potential of weather radar is analyzed during a winter half-year for the hilly region of the Belgian Ardennes. A correction algorithm is proposed taking into account attenuation, ground clutter, anomalous propagation, the vertical profile of reflectivity (VPR) and advection. No final bias correction with respect to rain gauge data were implemented, because that does not add to a better understanding of the quality of the radar. Largest quality improvements in the radar data are obtained by ground clutter removal. The influence of VPR correction and advection depends on the precipitation system observed. Overall, the radar shows an underestimation as compared to the rain gauges, which becomes smaller after averaging at the scale of the medium-sized Ourthe catchment. Remaining differences between both devices can mainly be attributed to an improper choice of the Z-R relationship. Conceptual rainfall-runoff simulations show similar results using either catchment average radar or rain gauge data, although the largest discharge peak observed, is seriously underestimated when applying radar data. Overall, for hydrological applications corrected weather radar information in a hilly environment can be used up to 70 km during a winter half-year.

  7. Characterizing rainfall of hot arid region by using time-series modeling and sustainability approaches: a case study from Gujarat, India

    Science.gov (United States)

    Machiwal, Deepesh; Kumar, Sanjay; Dayal, Devi

    2016-05-01

    This study aimed at characterization of rainfall dynamics in a hot arid region of Gujarat, India by employing time-series modeling techniques and sustainability approach. Five characteristics, i.e., normality, stationarity, homogeneity, presence/absence of trend, and persistence of 34-year (1980-2013) period annual rainfall time series of ten stations were identified/detected by applying multiple parametric and non-parametric statistical tests. Furthermore, the study involves novelty of proposing sustainability concept for evaluating rainfall time series and demonstrated the concept, for the first time, by identifying the most sustainable rainfall series following reliability ( R y), resilience ( R e), and vulnerability ( V y) approach. Box-whisker plots, normal probability plots, and histograms indicated that the annual rainfall of Mandvi and Dayapar stations is relatively more positively skewed and non-normal compared with that of other stations, which is due to the presence of severe outlier and extreme. Results of Shapiro-Wilk test and Lilliefors test revealed that annual rainfall series of all stations significantly deviated from normal distribution. Two parametric t tests and the non-parametric Mann-Whitney test indicated significant non-stationarity in annual rainfall of Rapar station, where the rainfall was also found to be non-homogeneous based on the results of four parametric homogeneity tests. Four trend tests indicated significantly increasing rainfall trends at Rapar and Gandhidham stations. The autocorrelation analysis suggested the presence of persistence of statistically significant nature in rainfall series of Bhachau (3-year time lag), Mundra (1- and 9-year time lag), Nakhatrana (9-year time lag), and Rapar (3- and 4-year time lag). Results of sustainability approach indicated that annual rainfall of Mundra and Naliya stations ( R y = 0.50 and 0.44; R e = 0.47 and 0.47; V y = 0.49 and 0.46, respectively) are the most sustainable and dependable

  8. Application of a modified conceptual rainfall-runoff model to simulation of groundwater level in an undefined watershed.

    Science.gov (United States)

    Hong, Nian; Hama, Takehide; Suenaga, Yuichi; Aqili, Sayed Waliullah; Huang, Xiaowu; Wei, Qiaoyan; Kawagoshi, Yasunori

    2016-01-15

    Groundwater level simulation models can help ensure the proper management and use of urban and rural water supply. In this paper, we propose a groundwater level tank model (GLTM) based on a conceptual rainfall-runoff model (tank model) to simulate fluctuations in groundwater level. The variables used in the simulations consist of daily rainfall and daily groundwater level, which were recorded between April 2011 and March 2015 at two representative observation wells in Kumamoto City, Japan. We determined the best-fit model parameters by root-mean-square error through use of the Shuffled Complex Evolution-University of Arizona algorithm on a simulated data set. Calibration and validation results were evaluated by their coefficients of determination, Nash-Sutcliffe efficiency coefficients, and root-mean-square error values. The GLTM provided accurate results in both the calibration and validation of fluctuations in groundwater level. The split sample test results indicate a good reliability. These results indicate that this model can provide a simple approach to the accurate simulation of groundwater levels. Copyright © 2015 Elsevier B.V. All rights reserved.

  9. A binary genetic programing model for teleconnection identification between global sea surface temperature and local maximum monthly rainfall events

    Science.gov (United States)

    Danandeh Mehr, Ali; Nourani, Vahid; Hrnjica, Bahrudin; Molajou, Amir

    2017-12-01

    The effectiveness of genetic programming (GP) for solving regression problems in hydrology has been recognized in recent studies. However, its capability to solve classification problems has not been sufficiently explored so far. This study develops and applies a novel classification-forecasting model, namely Binary GP (BGP), for teleconnection studies between sea surface temperature (SST) variations and maximum monthly rainfall (MMR) events. The BGP integrates certain types of data pre-processing and post-processing methods with conventional GP engine to enhance its ability to solve both regression and classification problems simultaneously. The model was trained and tested using SST series of Black Sea, Mediterranean Sea, and Red Sea as potential predictors as well as classified MMR events at two locations in Iran as predictand. Skill of the model was measured in regard to different rainfall thresholds and SST lags and compared to that of the hybrid decision tree-association rule (DTAR) model available in the literature. The results indicated that the proposed model can identify potential teleconnection signals of surrounding seas beneficial to long-term forecasting of the occurrence of the classified MMR events.

  10. A simple rainfall-runoff model based on hydrological units applied to the Teba catchment (south-east Spain)

    Science.gov (United States)

    Donker, N. H. W.

    2001-01-01

    A hydrological model (YWB, yearly water balance) has been developed to model the daily rainfall-runoff relationship of the 202 km2 Teba river catchment, located in semi-arid south-eastern Spain. The period of available data (1976-1993) includes some very rainy years with intensive storms (responsible for flooding parts of the town of Malaga) and also some very dry years.The YWB model is in essence a simple tank model in which the catchment is subdivided into a limited number of meaningful hydrological units. Instead of generating per unit surface runoff resulting from infiltration excess, runoff has been made the result of storage excess. Actual evapotranspiration is obtained by means of curves, included in the software, representing the relationship between the ratio of actual to potential evapotranspiration as a function of soil moisture content for three soil texture classes.The total runoff generated is split between base flow and surface runoff according to a given baseflow index. The two components are routed separately and subsequently joined. A large number of sequential years can be processed, and the results of each year are summarized by a water balance table and a daily based rainfall runoff time series. An attempt has been made to restrict the amount of input data to the minimum.Interactive manual calibration is advocated in order to allow better incorporation of field evidence and the experience of the model user. Field observations allowed for an approximate calibration at the hydrological unit level.

  11. Innovative use of soft data for the validation of a rainfall-runoff model forced by remote sensing data

    Science.gov (United States)

    van Emmerik, Tim; Eilander, Dirk; Piet, Marijn; Mulder, Gert

    2013-04-01

    The Chamcar Bei catchment in southern Cambodia is a typical ungauged basin. Neither meteorological data or discharge measurements are available. In this catchment, local farmers are highly dependent on the irrigation system. However, due to the unreliability of the water supply, it was required to make a hydrological model, with which further improvements of the irrigation system could be planned. First, we used knowledge generated in the IAHS decade on Predictions in Ungauged Basins (PUB) to estimate the annual water balance of the Chamcar Bei catchment. Next, using remotely sensed precipitation, vegetation, elevation and transpiration data, a monthly rainfall-runoff model has been developed. The rainfall-runoff model was linked to the irrigation system reservoir, which allowed to validate the model based on soft data such as historical knowledge of the reservoir water level and groundwater levels visible in wells. This study shows that combining existing remote sensing data and soft ground data can lead to useful modeling results. The approach presented in this study can be applied in other ungauged basins, which can be extremely helpful in managing water resources in developing countries.

  12. WHEN DEATH INTERCEPTS LIFE IN IMAGINATIVE WRITING

    OpenAIRE

    washington, gene

    2014-01-01

    The representation of death in imaginative writing is a "virtual" (as opposed to) an actual death. It always occurs in the context of a "virtual" (represented) life. In this text the author examines some of the ways death "intercepts" life in such writing. The subject is a vast, perhaps inexhaustible, one. The richest source, one the author dos not mine, is Shakespeare's interceptions of life by death.

  13. Water Isotope Proxy-Proxy and Proxy-Model Convergence for Late Pleistocene East Asian Monsoon Rainfall Reconstructions

    Science.gov (United States)

    Clemens, S. C.; Holbourn, A.; Kubota, Y.; Lee, K. E.; Liu, Z.; Chen, G.

    2017-12-01

    Confidence in reconstruction of East Asian paleomonsoon rainfall using precipitation isotope proxies is a matter of considerable debate, largely due to the lack of correlation between precipitation amount and isotopic composition in the present climate. We present four new, very highly resolved records spanning the past 300,000 years ( 200 year sample spacing) from IODP Site U1429 in the East China Sea. We demonstrate that all the orbital- and millennial-scale variance in the onshore Yangtze River Valley speleothem δ18O record1 is also embedded in the offshore Site U1429 seawater δ18O record (derived from the planktonic foraminifer Globigerinoides ruber and sea surface temperature reconstructions). Signal replication in these two independent terrestrial and marine archives, both controlled by the same monsoon system, uniquely identifies δ18O of precipitation as the primary driver of the precession-band variance in both records. This proxy-proxy convergence also eliminates a wide array of other drivers that have been called upon as potential contaminants to the precipitation δ18O signal recorded by these proxies. We compare East Asian precipitation isotope proxy records to precipitation amount from a CCSM3 transient climate model simulation of the past 300,000 years using realistic insolation, ice volume, greenhouse gasses, and sea level boundary conditions. This model-proxy comparison suggests that both Yangtze River Valley precipitation isotope proxies (seawater and speleothem δ18O) track changes in summer-monsoon rainfall amount at orbital time scales, as do precipitation isotope records from the Pearl River Valley2 (leaf wax δ2H) and Borneo3 (speleothem δ18O). Notably, these proxy records all have significantly different spectral structure indicating strongly regional rainfall patterns that are also consistent with model results. Transient, isotope-enabled model simulations will be necessary to more thoroughly evaluate these promising results, and to

  14. Integration of Spatially Hydrological Modelling on Bentong Catchment, Pahang, Peninsular Malaysia Using Distributed GIS-based Rainfall Runoff Model

    Directory of Open Access Journals (Sweden)

    Rosli, M.H.

    2017-07-01

    Full Text Available With the advance of GIS technology, hydrology model can simulated at catchment wide scale. The objective is to integrate National Resource Conservation Service (NRCS Curve Number (CN with kinematic wave and manning’s equation using GIS to develop a simple GIS-based distributed model to simulate rainfall runoff in Bentong catchment. Model was built using Spatial Distributed Direct Hydrograph (SDDH concept and applying the time area (TA approach in presenting the predicted discharge hydrograph. The effective precipitation estimation was first calculated using the NRCS CN method. Then, the core maps that consists of digital elevation model (DEM, soil and land use map in grid. DEM was used to derive slope, flow direction and flow accumulation while soil and land use map used to derive roughness coefficient and CN. The overland velocity and channel velocity estimation derived from combination of kinematic wave theory with Manning’s equation. To capture the time frame, the travel time map was divided into isochrones in order to generate the TA histogram and finally. The creation of SDDH using the TA histogram which will lead to the estimation of travel time for the catchment. Simulated hydrograph was plotted together with the observed discharge for comparison. Six storm events used for model performance evaluation using statistical measure such as Nash-Sutcliffe efficiency (NSE, percent bias (PBIAS and coefficient of determination (R2;. SDDH model performed quite well as NSE gave result ranging from 0.55 to 0.68 with mean of 0.6. PBIAS indicate that the model slightly over predicted compared to observed hydrograph with result ranges from -46.71 (the most over predicted to +4.83 (the most under predicted with average of -20.73%. R2; ranges between 0.55 to 0.82 with mean of 0.67. When comparing the time to peak, (tp, min, and peak discharge, (pd, m3/s, results gave NSEtp 0.82, PBIAStp 0.65, R2tp 0.32, NSEpd 0.95, PBIASpd 14.49 and R2pd 0

  15. Analysis and stochastic modelling of Intensity-Duration-Frequency relationship from 88 years of 10 min rainfall data in North Spain

    Science.gov (United States)

    Delgado, Oihane; Campo-Bescós, Miguel A.; López, J. Javier

    2017-04-01

    Frequently, when we are trying to solve certain hydrological engineering problems, it is often necessary to know rain intensity values related to a specific probability or return period, T. Based on analyses of extreme rainfall events at different time scale aggregation, we can deduce the relationships among Intensity-Duration-Frequency (IDF), that are widely used in hydraulic infrastructure design. However, the lack of long time series of rainfall intensities for smaller time periods, minutes or hours, leads to use mathematical expressions to characterize and extend these curves. One way to deduce them is through the development of synthetic rainfall time series generated from stochastic models, which is evaluated in this work. From recorded accumulated rainfall time series every 10 min in the pluviograph of Igueldo (San Sebastian, Spain) for the time period between 1927-2005, their homogeneity has been checked and possible statistically significant increasing or decreasing trends have also been shown. Subsequently, two models have been calibrated: Bartlett-Lewis and Markov chains models, which are based on the successions of storms, composed for a series of rainfall events, separated by a short interval of time each. Finally, synthetic ten-minute rainfall time series are generated, which allow to estimate detailed IDF curves and compare them with the estimated IDF based on the recorded data.

  16. Hydraulic Geometry, GIS and Remote Sensing, Techniques against Rainfall-Runoff Models for Estimating Flood Magnitude in Ephemeral Fluvial Systems

    Directory of Open Access Journals (Sweden)

    Rafael Garcia-Lorenzo

    2010-11-01

    Full Text Available This paper shows the combined use of remotely sensed data and hydraulic geometry methods as an alternative to rainfall-runoff models. Hydraulic geometric data and boolean images of water sheets obtained from satellite images after storm events were integrated in a Geographical Information System. Channel cross-sections were extracted from a high resolution Digital Terrain Model (DTM and superimposed on the image cover to estimate the peak flow using HEC-RAS. The proposed methodology has been tested in ephemeral channels (ramblas on the coastal zone in south-eastern Spain. These fluvial systems constitute an important natural hazard due to their high discharges and sediment loads. In particular, different areas affected by floods during the period 1997 to 2009 were delimited through HEC-GeoRAs from hydraulic geometry data and Landsat images of these floods (Landsat‑TM5 and Landsat-ETM+7. Such an approach has been validated against rainfall-surface runoff models (SCS Dimensionless Unit Hydrograph, SCSD, Témez gamma HU Tγ and the Modified Rational method, MRM comparing their results with flood hydrographs of the Automatic Hydrologic Information System (AHIS in several ephemeral channels in the Murcia Region. The results obtained from the method providing a better fit were used to calculate different hydraulic geometry parameters, especially in residual flood areas.

  17. Estimating impact of rainfall change on hydrological processes in Jianfengling rainforest watershed, China using BASINS-HSPF-CAT modeling system

    Science.gov (United States)

    Zhang Zhou; Ying Ouyang; Yide Li; Zhijun Qiu; Matt Moran

    2017-01-01

    Climate change over the past several decades has resulted in shifting rainfall pattern and modifying rain-fall intensity, which has exacerbated hydrological processes and added the uncertainty and instability tothese processes. This study ascertained impacts of potential future rainfall change on hydrological pro-cesses at the Jianfengling (JFL) tropical mountain...

  18. prediction of rainfall in the southern highlands of tanzania

    African Journals Online (AJOL)

    User

    distribution at different places in the world. A study to ... climate indices influence rainfall. It has been observed .... Table 4: Summary of Predictors entered MLR and PCR models for MAM and OND rainfalls. .... from the cumulus clouds; rainfall is.

  19. Chance-constrained overland flow modeling for improving conceptual distributed hydrologic simulations based on scaling representation of sub-daily rainfall variability

    International Nuclear Information System (INIS)

    Han, Jing-Cheng; Huang, Guohe; Huang, Yuefei; Zhang, Hua; Li, Zhong; Chen, Qiuwen

    2015-01-01

    Lack of hydrologic process representation at the short time-scale would lead to inadequate simulations in distributed hydrological modeling. Especially for complex mountainous watersheds, surface runoff simulations are significantly affected by the overland flow generation, which is closely related to the rainfall characteristics at a sub-time step. In this paper, the sub-daily variability of rainfall intensity was considered using a probability distribution, and a chance-constrained overland flow modeling approach was proposed to capture the generation of overland flow within conceptual distributed hydrologic simulations. The integrated modeling procedures were further demonstrated through a watershed of China Three Gorges Reservoir area, leading to an improved SLURP-TGR hydrologic model based on SLURP. Combined with rainfall thresholds determined to distinguish various magnitudes of daily rainfall totals, three levels of significance were simultaneously employed to examine the hydrologic-response simulation. Results showed that SLURP-TGR could enhance the model performance, and the deviation of runoff simulations was effectively controlled. However, rainfall thresholds were so crucial for reflecting the scaling effect of rainfall intensity that optimal levels of significance and rainfall threshold were 0.05 and 10 mm, respectively. As for the Xiangxi River watershed, the main runoff contribution came from interflow of the fast store. Although slight differences of overland flow simulations between SLURP and SLURP-TGR were derived, SLURP-TGR was found to help improve the simulation of peak flows, and would improve the overall modeling efficiency through adjusting runoff component simulations. Consequently, the developed modeling approach favors efficient representation of hydrological processes and would be expected to have a potential for wide applications. - Highlights: • We develop an improved hydrologic model considering the scaling effect of rainfall. • A

  20. Chance-constrained overland flow modeling for improving conceptual distributed hydrologic simulations based on scaling representation of sub-daily rainfall variability

    Energy Technology Data Exchange (ETDEWEB)

    Han, Jing-Cheng [State Key Laboratory of Hydroscience & Engineering, Department of Hydraulic Engineering, Tsinghua University, Beijing 100084 (China); Huang, Guohe, E-mail: huang@iseis.org [Institute for Energy, Environment and Sustainable Communities, University of Regina, Regina, Saskatchewan S4S 0A2 (Canada); Huang, Yuefei [State Key Laboratory of Hydroscience & Engineering, Department of Hydraulic Engineering, Tsinghua University, Beijing 100084 (China); Zhang, Hua [College of Science and Engineering, Texas A& M University — Corpus Christi, Corpus Christi, TX 78412-5797 (United States); Li, Zhong [Institute for Energy, Environment and Sustainable Communities, University of Regina, Regina, Saskatchewan S4S 0A2 (Canada); Chen, Qiuwen [Center for Eco-Environmental Research, Nanjing Hydraulics Research Institute, Nanjing 210029 (China)

    2015-08-15

    Lack of hydrologic process representation at the short time-scale would lead to inadequate simulations in distributed hydrological modeling. Especially for complex mountainous watersheds, surface runoff simulations are significantly affected by the overland flow generation, which is closely related to the rainfall characteristics at a sub-time step. In this paper, the sub-daily variability of rainfall intensity was considered using a probability distribution, and a chance-constrained overland flow modeling approach was proposed to capture the generation of overland flow within conceptual distributed hydrologic simulations. The integrated modeling procedures were further demonstrated through a watershed of China Three Gorges Reservoir area, leading to an improved SLURP-TGR hydrologic model based on SLURP. Combined with rainfall thresholds determined to distinguish various magnitudes of daily rainfall totals, three levels of significance were simultaneously employed to examine the hydrologic-response simulation. Results showed that SLURP-TGR could enhance the model performance, and the deviation of runoff simulations was effectively controlled. However, rainfall thresholds were so crucial for reflecting the scaling effect of rainfall intensity that optimal levels of significance and rainfall threshold were 0.05 and 10 mm, respectively. As for the Xiangxi River watershed, the main runoff contribution came from interflow of the fast store. Although slight differences of overland flow simulations between SLURP and SLURP-TGR were derived, SLURP-TGR was found to help improve the simulation of peak flows, and would improve the overall modeling efficiency through adjusting runoff component simulations. Consequently, the developed modeling approach favors efficient representation of hydrological processes and would be expected to have a potential for wide applications. - Highlights: • We develop an improved hydrologic model considering the scaling effect of rainfall. • A

  1. Rainfall erosivity in Europe.

    Science.gov (United States)

    Panagos, Panos; Ballabio, Cristiano; Borrelli, Pasquale; Meusburger, Katrin; Klik, Andreas; Rousseva, Svetla; Tadić, Melita Perčec; Michaelides, Silas; Hrabalíková, Michaela; Olsen, Preben; Aalto, Juha; Lakatos, Mónika; Rymszewicz, Anna; Dumitrescu, Alexandru; Beguería, Santiago; Alewell, Christine

    2015-04-01

    Rainfall is one the main drivers of soil erosion. The erosive force of rainfall is expressed as rainfall erosivity. Rainfall erosivity considers the rainfall amount and intensity, and is most commonly expressed as the R-factor in the USLE model and its revised version, RUSLE. At national and continental levels, the scarce availability of data obliges soil erosion modellers to estimate this factor based on rainfall data with only low temporal resolution (daily, monthly, annual averages). The purpose of this study is to assess rainfall erosivity in Europe in the form of the RUSLE R-factor, based on the best available datasets. Data have been collected from 1541 precipitation stations in all European Union (EU) Member States and Switzerland, with temporal resolutions of 5 to 60 min. The R-factor values calculated from precipitation data of different temporal resolutions were normalised to R-factor values with temporal resolutions of 30 min using linear regression functions. Precipitation time series ranged from a minimum of 5 years to a maximum of 40 years. The average time series per precipitation station is around 17.1 years, the most datasets including the first decade of the 21st century. Gaussian Process Regression (GPR) has been used to interpolate the R-factor station values to a European rainfall erosivity map at 1 km resolution. The covariates used for the R-factor interpolation were climatic data (total precipitation, seasonal precipitation, precipitation of driest/wettest months, average temperature), elevation and latitude/longitude. The mean R-factor for the EU plus Switzerland is 722 MJ mm ha(-1) h(-1) yr(-1), with the highest values (>1000 MJ mm ha(-1) h(-1) yr(-1)) in the Mediterranean and alpine regions and the lowest (<500 MJ mm ha(-1) h(-1) yr(-1)) in the Nordic countries. The erosivity density (erosivity normalised to annual precipitation amounts) was also the highest in Mediterranean regions which implies high risk for erosive events and floods

  2. Inferring the flood frequency distribution for an ungauged basin using a spatially distributed rainfall-runoff model

    Directory of Open Access Journals (Sweden)

    G. Moretti

    2008-08-01

    Full Text Available The estimation of the peak river flow for ungauged river sections is a topical issue in applied hydrology. Spatially distributed rainfall-runoff models can be a useful tool to this end, since they are potentially able to simulate the river flow at any location of the watershed drainage network. However, it is not fully clear to what extent these models can provide reliable simulations over a wide range of spatial scales. This issue is investigated here by applying a spatially distributed, continuous simulation rainfall-runoff model to infer the flood frequency distribution of the Riarbero River. This is an ungauged mountain creek located in northern Italy, whose drainage area is 17 km2. The hydrological model is first calibrated by using a 1-year record of hourly meteorological data and river flows observed at the outlet of the 1294 km2 wide Secchia River basin, of which the Riarbero is a tributary. The model is then validated by performing a 100-year long simulation of synthetic river flow data, which allowed us to compare the simulated and observed flood frequency distributions at the Secchia River outlet and the internal cross river section of Cavola Bridge, where the basin area is 337 km2. Finally, another simulation of hourly river flows was performed by referring to the outlet of the Riarbero River, therefore allowing us to estimate the related flood frequency distribution. The results were validated by using estimates of peak river flow obtained by applying hydrological similarity principles and a regional method. The results show that the flood flow estimated through the application of the distributed model is consistent with the estimate provided by the regional procedure as well as the behaviors of the river banks. Conversely, the method based on hydrological similarity delivers an estimate that seems to be not as reliable. The analysis highlights interesting perspectives for the application of

  3. A note on estimating urban roof runoff with a forest evaporation model

    NARCIS (Netherlands)

    Gash, J.H.C.; Rosier, P.T.W.; Ragab, R.

    2008-01-01

    A model developed for estimating the evaporation of rainfall intercepted by forest canopies is applied to estimate measurements of the average runoff from the roofs of six houses made in a previous study of hydrological processes in an urban environment. The model is applied using values of the mean

  4. Hydrological real-time modelling in the Zambezi river basin using satellite-based soil moisture and rainfall data

    Directory of Open Access Journals (Sweden)

    P. Meier

    2011-03-01

    Full Text Available Reliable real-time forecasts of the discharge can provide valuable information for the management of a river basin system. For the management of ecological releases even discharge forecasts with moderate accuracy can be beneficial. Sequential data assimilation using the Ensemble Kalman Filter provides a tool that is both efficient and robust for a real-time modelling framework. One key parameter in a hydrological system is the soil moisture, which recently can be characterized by satellite based measurements. A forecasting framework for the prediction of discharges is developed and applied to three different sub-basins of the Zambezi River Basin. The model is solely based on remote sensing data providing soil moisture and rainfall estimates. The soil moisture product used is based on the back-scattering intensity of a radar signal measured by a radar scatterometer. These soil moisture data correlate well with the measured discharge of the corresponding watershed if the data are shifted by a time lag which is dependent on the size and the dominant runoff process in the catchment. This time lag is the basis for the applicability of the soil moisture data for hydrological forecasts. The conceptual model developed is based on two storage compartments. The processes modeled include evaporation losses, infiltration and percolation. The application of this model in a real-time modelling framework yields good results in watersheds where soil storage is an important factor. The lead time of the forecast is dependent on the size and the retention capacity of the watershed. For the largest watershed a forecast over 40 days can be provided. However, the quality of the forecast increases significantly with decreasing prediction time. In a watershed with little soil storage and a quick response to rainfall events, the performance is relatively poor and the lead time is as short as 10 days only.

  5. Modelling dimensional growth of three street tree species in the ...

    African Journals Online (AJOL)

    The results could also be used in the process of modelling energy use reduction, air pollution uptake, rainfall interception, carbon sequestration and microclimate modification of urban forests such as those found in the City of Tshwane. Keywords: allometry; regression; size relationships; tree growth; urban forests. Southern ...

  6. Hydrological model parameterization using NDVI values to account for the effects of land-cover change on the rainfall-runoff response

    Science.gov (United States)

    Classic rainfall-runoff models usually use historical data to estimate model parameters and mean values of parameters are considered for predictions. However, due to climate changes and human effects, the parameters of model change temporally. To overcome this problem, Normalized Difference Vegetati...

  7. Urban Flooding Analysis Using Radar Rainfall Data and 2-D Hydrodynamic Model: A Pilot Study of Back Cover Area, Portland, Maine

    Energy Technology Data Exchange (ETDEWEB)

    Yan, Eugene [Argonne National Lab. (ANL), Argonne, IL (United States); Pierce, Julia [Argonne National Lab. (ANL), Argonne, IL (United States); Mahat, Vinod [Argonne National Lab. (ANL), Argonne, IL (United States); Jared, Alissa [Argonne National Lab. (ANL), Argonne, IL (United States); Collis, Scott [Argonne National Lab. (ANL), Argonne, IL (United States); Verner, Duane [Argonne National Lab. (ANL), Argonne, IL (United States); Wall, Thomas [Argonne National Lab. (ANL), Argonne, IL (United States)

    2016-11-01

    This project is a part of the Regional Resiliency Assessment Program, led by the Department of Homeland Security, to address flooding hazards of regional significance for Portland, Maine. The pilot study was performed by Argonne National Laboratory to identify differences in spatial rainfall distributions between the radar-derived and rain-gauge rainfall datasets and to evaluate their impacts on urban flooding. The flooding impact analysis utilized a high-resolution 2-dimensional (2-D) hydrodynamic model (15 ft by 15 ft) incorporating the buildings, streets, stream channels, hydraulic structures, an existing city storm drain system, and assuming a storm surge along the coast coincident with a heavy rainfall event. Two historical storm events from April 16, 2007, and September 29, 2015, were selected for evaluation. The radar-derived rainfall data at a 200-m resolution provide spatially-varied rainfall patterns with a wide range of intensities for each event. The resultant maximum flood depth using data from a single rain gauge within the study area could be off (either under- or over-estimated) by more than 10% in the 2007 storm and more than 60% in the 2015 storm compared to the radar-derived rainfall data. The model results also suggest that the inundation area with a flow depth at or greater than 0.5 ft could reach 11% (2007 storm) and 17% (2015 storm) of the total study area, respectively. The lowland areas within the neighborhoods of North Deering, East Deering, East and West Baysides and northeastern Parkside, appear to be more vulnerable to the flood hazard in both storm events. The high-resolution 2-D hydrodynamic model with high-resolution radar-derived rainfall data provides an excellent tool for detailed urban flood analysis and vulnerability assessment. The model developed in this study could be potentially used to evaluate any proposed mitigation measures and optimize their effects in the future for Portland, ME.

  8. Hydrological model calibration for flood prediction in current and future climates using probability distributions of observed peak flows and model based rainfall

    Science.gov (United States)

    Haberlandt, Uwe; Wallner, Markus; Radtke, Imke

    2013-04-01

    Derived flood frequency analysis based on continuous hydrological modelling is very demanding regarding the required length and temporal resolution of precipitation input data. Often such flood predictions are obtained using long precipitation time series from stochastic approaches or from regional climate models as input. However, the calibration of the hydrological model is usually done using short time series of observed data. This inconsistent employment of different data types for calibration and application of a hydrological model increases its uncertainty. Here, it is proposed to calibrate a hydrological model directly on probability distributions of observed peak flows using model based rainfall in line with its later application. Two examples are given to illustrate the idea. The first one deals with classical derived flood frequency analysis using input data from an hourly stochastic rainfall model. The second one concerns a climate impact analysis using hourly precipitation from a regional climate model. The results show that: (I) the same type of precipitation input data should be used for calibration and application of the hydrological model, (II) a model calibrated on extreme conditions works quite well for average conditions but not vice versa, (III) the calibration of the hydrological model using regional climate model data works as an implicit bias correction method and (IV) the best performance for flood estimation is usually obtained when model based precipitation and observed probability distribution of peak flows are used for model calibration.

  9. Heterogeneity of Dutch rainfall

    NARCIS (Netherlands)

    Witter, J.V.

    1984-01-01

    Rainfall data for the Netherlands have been used in this study to investigate aspects of heterogeneity of rainfall, in particular local differences in rainfall levels, time trends in rainfall, and local differences in rainfall trend. The possible effect of urbanization and industrialization on the

  10. Assessing the water balance in the Sahel : Impact of small scale rainfall variability on runoff. Part 2 : Idealized modeling of runoff sensitivity

    OpenAIRE

    Vischel, Théo; Lebel, Thierry

    2007-01-01

    As in many other semi-arid regions in the world, the Sahelian hydrological environment is characterized by a mosaic of small endoreic catchments with dry soil surface conditions producing mostly Hortonian runoff. Using an SCS-type event based rainfall-runoff model, an idealized modeling experiment of a Sahelian environment is set up to study the sensitivity of runoff to small scale rainfall variability. A set of 548 observed rain events is used to force the hydrological model to study the sen...

  11. Embedded Systems - Missile Detection/Interception

    Directory of Open Access Journals (Sweden)

    Luis Cintron

    2010-01-01

    Full Text Available Missile defense systems are often related to major military resources aimed at shielding a specific region from incoming attacks. They are intended to detect, track, intercept, and destruct incoming enemy missiles. These systems vary in cost, efficiency, dependability, and technology. In present times, the possession of these types of systems is associated with large capacity military countries. Demonstrated here are the mathematical techniques behind missile systems which calculate trajectories of incoming missiles and potential intercept positions after initial missile detection. This procedure involved the use of vector-valued functions, systems of equations, and knowledge of projectile motion concepts.

  12. Application of Volumetric Weather Radar Data and the Distributed Rainfall Runoff Model REW in the Ourthe Catchment

    Science.gov (United States)

    Hazenberg, P.; Leijnse, H.; Torfs, P.; Uijlenhoet, R.; Weerts, A.; Reggiani, P.; Delobbe, L.

    2008-12-01

    In the southern Ardennes region of Belgium near the border with Luxembourg, the Royal Meteorological Institute of Belgium (RMI) installed a C-band Doppler weather radar at an elevation of 600 m in the year 2001. This volumetric weather radar scans over multiple elevations at a temporal resolution of 5 minutes. The current study explores the possibility of using the volumetric information of the precipitation field to correct for the effects of the Vertical Profile of Reflectivity (VPR) over the period October 1, 2002 until March 31, 2003. During this winter half year storm events are mainly stratiform, giving rise to bright band effects which can decrease the performance of the radar. Previous studies have shown multiple drawbacks in applying a single estimated VPR profile to correct such reflectivity data. Therefore, the focus here is on the temporal variability of the VPR as measured by the radar and its variability over different spatial scales. This information is applied to generate a number of possible rainfall fields. These realizations are employed to try to quantify some of the discrepancies in precipitation intensities as estimated by the weather radar and those measured by a raingauge network. The final step then is to assess their potential within a distributed rainfall runoff model. The 1597 km2 Ourthe catchment lies within 60 km of the radar. Over this medium sized watershed ten raingauges measuring at an hourly interval are more or less equally distributed. Near the outlet discharge data are collected at the same time step. The distributed hydrological Representative Elementary Watershed (REW) model is applied to model the hydrological behavior of the Ourthe over the six month period. The benefits of the high spatial and temporal resolution of weather radar data compared to a conventional raingauge network plus the possibility of generating multiple realizations of the precipitation field are expected to yield more information about the hydrological

  13. Yield accumulation in irrigated sugarcane. II. Utilization of intercepted radiation

    International Nuclear Information System (INIS)

    Muchow, R.C.; Evensen, C.I.; Osgood, R.V.; Robertson, M.J.

    1997-01-01

    Intercepted radiation is a major driving variable of crop production under high-input irrigated conditions. Quantitative information on the utilization of radiation in yield accumulation allows extrapolation beyond the current season and location, and when this information is incorporated into crop growth simulation models, the effect of crop age on the productivity of different cultivars can be examined under different climatic conditions. This paper examines the differential performance of high-yielding sugarcane (Saccharum spp. hybrids) crops in terms of the amount of short-wave solar radiation intercepted (Si) and the efficiency of use of intercepted radiation (RUE) in biomass production. Biomass accumulation during the 12- to 24-mo crop cycle was examined for two experiments conducted in Hawaii, and three experiments conducted in tropical Australia from 1991 to 1993. The analysis showed that (i) RUE was much less for growth after 12 mo than in the first 12 mo; (ii) maximum RUE of sugarcane approaches 2.0 g MJ(-1); (iii) biomass accumulation beyond 12 mo was not related directly to radiation utilization; and (iv) cultivars differed in Si, but differences in RUE could not be unequivocally assessed due to the confounding effect of variable recovery of trash in biomass estimates. It is concluded that stalk death and consequent biomass loss are important factors contributing to yield variation in sugarcane crops growing for 12 to 24 mo, with a yield plateau occurring at variable crop ages during the second year of growth

  14. Modelo de armadilha etanólica de interceptação de voo para captura de escolitíneos (Curculionidae: Scolytinae Ethanolic model of flight interception trap to capture scolytine (Curculionidae: Scolytinae

    Directory of Open Access Journals (Sweden)

    Augusto Bolson Murari

    2012-03-01

    Full Text Available

    Este estudo teve por objetivo desenvolver um modelo alternativo de armadilha etanólica de interceptação de insetos voadores, visando à redução dos custos relacionados aos levantamentos de insetos da subfamília Scolytinae (Curculionidae, realizados em ecossistemas florestais. O modelo de armadilha, denominado de PET-SM, foi confeccionado com materiais recicláveis: prato plástico, garrafa de polietileno (PET de dois litros, garrafa PET de 600 mL, e mangueira com álcool 96° GL empregado como atrativo. Em comparação a outros modelos utilizados para monitoramento de Scolytinae, o modelo PET-SM mostrou-se eficiente na captura, apresentando um maior número de espécies coletadas e oferecendo um menor custo de confecção.

     

    doi: 10.4336/2012.pfb.32.69.115

    This study aimed to develop an alternative model of trap for interception with ethanol for flying insects, in order to reduce the costs related to surveys of insects of the subfamily Scolytinae (Curculionidae, conducted in forest ecosystems. The model of trap, called PET-SM, was manufactured with recyclable materials: plastic plate, polyethylene (PET bottle of two liters, PET bottle of 600 mL, and a hose with alcohol 96 GL used as attractive. Compared to other models used to monitor Scolytinae, the PET-SM model proved to be effective for capture, presenting a greater number of species and offering a lower cost of manufacture.

     

    doi: 10.4336/2012.pfb.32.69.115

  15. Identifying multiple timescale rainfall controls on Mojave Desert ecohydrology using an integrated data and modeling approach for Larrea tridentata

    Science.gov (United States)

    Ng, Gene-Hua Crystal; Bedford, David R.; Miller, David M.

    2015-01-01

    The perennial shrub Larrea tridentata is widely successful in North American warm deserts but is also susceptible to climatic perturbations. Understanding its response to rainfall variability requires consideration of multiple timescales. We examine intra-annual to multi-year relationships using model simulations of soil moisture and vegetation growth over 50 years in the Mojave National Preserve in southeastern California (USA). Ecohydrological model parameters are conditioned on field and remote sensing data using an ensemble Kalman filter. Although no specific periodicities were detected in the rainfall record, simulated leaf-area-index exhibits multi-year dynamics that are driven by multi-year (∼3-years) rains, but with up to a 1-year delay in peak response. Within a multi-year period, Larrea tridentata is more sensitive to winter rains than summer. In the most active part of the root zone (above ∼80 cm), >1-year average soil moisture drives vegetation growth, but monthly average soil moisture is controlled by root uptake. Moisture inputs reach the lower part of the root zone (below ∼80 cm) infrequently, but once there they can persist over a year to help sustain plant growth. Parameter estimates highlight efficient plant physiological properties facilitating persistent growth and high soil hydraulic conductivity allowing deep soil moisture stores. We show that soil moisture as an ecological indicator is complicated by bidirectional interactions with vegetation that depend on timescale and depth. Under changing climate, Larrea tridentata will likely be relatively resilient to shorter-term moisture variability but will exhibit higher sensitivity to shifts in seasonal to multi-year moisture inputs.

  16. Effects of sea surface temperature, cloud radiative and microphysical processes, and diurnal variations on rainfall in equilibrium cloud-resolving model simulations

    International Nuclear Information System (INIS)

    Jiang Zhe; Li Xiao-Fan; Zhou Yu-Shu; Gao Shou-Ting

    2012-01-01

    The effects of sea surface temperature (SST), cloud radiative and microphysical processes, and diurnal variations on rainfall statistics are documented with grid data from the two-dimensional equilibrium cloud-resolving model simulations. For a rain rate of higher than 3 mm·h −1 , water vapor convergence prevails. The rainfall amount decreases with the decrease of SST from 29 °C to 27 °C, the inclusion of diurnal variation of SST, or the exclusion of microphysical effects of ice clouds and radiative effects of water clouds, which are primarily associated with the decreases in water vapor convergence. However, the amount of rainfall increases with the increase of SST from 29 °C to 31 °C, the exclusion of diurnal variation of solar zenith angle, and the exclusion of the radiative effects of ice clouds, which are primarily related to increases in water vapor convergence. For a rain rate of less than 3 mm·h −1 , water vapor divergence prevails. Unlike rainfall statistics for rain rates of higher than 3 mm·h −1 , the decrease of SST from 29 °C to 27 °C and the exclusion of radiative effects of water clouds in the presence of radiative effects of ice clouds increase the rainfall amount, which corresponds to the suppression in water vapor divergence. The exclusion of microphysical effects of ice clouds decreases the amount of rainfall, which corresponds to the enhancement in water vapor divergence. The amount of rainfall is less sensitive to the increase of SST from 29 °C to 31 °C and to the radiative effects of water clouds in the absence of the radiative effects of ice clouds. (electromagnetism, optics, acoustics, heat transfer, classical mechanics, and fluid dynamics)

  17. A multi-decadal assessment of the performance of gauge- and model-based rainfall products over Saudi Arabia: Climatology, anomalies and trends

    KAUST Repository

    El Kenawy, Ahmed M.

    2015-05-15

    Many arid and semi-arid regions have sparse precipitation observing networks, which limits the capacity for detailed hydrological modelling, water resources management and flood forecasting efforts. The objective of this work is to evaluate the utility of relatively high-spatial resolution rainfall products to reproduce observed multi-decadal rainfall characteristics such as climatologies, anomalies and trends over Saudi Arabia. Our study compares the statistical characteristics of rainfall from 53 observatories over the reference period 1965-2005, with rainfall data from six widely used gauge-based products, including APHRODITE, GPCC, PRINCETON, UDEL, CRU and PREC/L. In addition, the performance of three global climate models (GCMs), including CCSM4, EC-EARTH and MRI-I-CGCM3, integrated as part of the Fifth Coupled Model Intercomparison Project (CMIP5), was also evaluated. Results indicate that the gauge-based products were generally skillful in reproducing rainfall characteristics in Saudi Arabia. In most cases, the gauge-based products were also able to capture the annual cycle, anomalies and climatologies of observed data, although significant inter-product variability was observed, depending on the assessment metric being used. In comparison, the GCM-based products generally exhibited poor performance, with larger biases and very weak correlations, particularly during the summertime. Importantly, all products generally failed to reproduce the observed long-term seasonal and annual trends in the region, particularly during the dry seasons (summer and autumn). Overall, this work suggests that selected gauge-based products with daily (APHRODITE and PRINCETON) and monthly (GPCC and CRU) resolutions show superior performance relative to other products, implying that they may be the most appropriate data source from which multi-decadal variations of rainfall can be investigated at the regional scale over Saudi Arabia. Discriminating these skillful products is

  18. Modeling Rainfall-Runoff Response to Land Use and Land Cover Change in Rwanda (1990–2016

    Directory of Open Access Journals (Sweden)

    Fidele Karamage

    2017-02-01

    Full Text Available Stormwater runoff poses serious environmental problems and public health issues in Rwanda, a tropical country that is increasingly suffering from severe floods, landslides, soil erosion and water pollution. Using the WetSpa Extension model, this study assessed the changes in rainfall runoff depth in Rwanda from 1990 to 2016 in response to precipitation and land use changes. Our results show that Rwanda has experienced a significant conversion of natural forest and grassland to cropland and built-up areas. During the period 1990–2016, 7090.02 km2 (64.5% and 1715.26 km2 (32.1% of forest and grassland covers were lost, respectively, while the cropland and built-up areas increased by 135.3% (8503.75 km2 and 304.3% (355.02 km2, respectively. According to our estimates, the land use change effect resulted in a national mean runoff depth increase of 2.33 mm/year (0.38%. Although precipitation change affected the inter-annual fluctuation of runoff, the long-term trend of runoff was dominated by land use change. The top five districts that experienced the annual runoff depth increase (all >3.8 mm/year are Rubavu, Nyabihu, Ngororero, Gakenke, and Musanze. Their annual runoff depths increased at a rate of >3.8 mm/year during the past 27 years, due to severe deforestation (ranging from 62% to 85% and cropland expansion (ranging from 123% to 293%. These areas require high priority in runoff control using terracing in croplands and rainwater harvesting systems such as dam/reservoirs, percolation tanks, storage tanks, etc. The wet season runoff was three times higher than the dry season runoff in Rwanda; appropriate rainwater management and reservation could provide valuable irrigation water for the dry season or drought years (late rainfall onsets or early rainfall cessations. It was estimated that a reservation of 30.5% (3.99 km3 of the runoff in the wet season could meet the cropland irrigation water gap during the dry season in 2016.

  19. South African seasonal rainfall prediction performance by a coupled ocean-atmosphere model

    CSIR Research Space (South Africa)

    Landman, WA

    2010-12-01

    Full Text Available Evidence is presented that coupled ocean-atmosphere models can already outscore computationally less expensive atmospheric models. However, if the atmospheric models are forced with highly skillful SST predictions, they may still be a very strong...

  20. Quantification of the interception and initial ret