Full Text Available A conceptual water balance model is presented to represent changes in monthly water balance following land use changes. Monthly rainfall–runoff, groundwater and soil moisture data from four experimental catchments in Western Australia have been analysed. Two of these catchments, 'Ernies' (control, fully forested and 'Lemon' (54% cleared are in a zone of mean annual rainfall of 725 mm, while 'Salmon' (control, fully forested and 'Wights' (100% cleared are in a zone with mean annual rainfall of 1125 mm. At the Salmon forested control catchment, streamflow comprises surface runoff, base flow and interflow components. In the Wights catchment, cleared of native forest for pasture development, all three components increased, groundwater levels rose significantly and stream zone saturated area increased from 1% to 15% of the catchment area. It took seven years after clearing for the rainfall–runoff generation process to stabilise in 1984. At the Ernies forested control catchment, the permanent groundwater system is 20 m below the stream bed and so does not contribute to streamflow. Following partial clearing of forest in the Lemon catchment, groundwater rose steadily and reached the stream bed by 1987. The streamflow increased in two phases: (i immediately after clearing due to reduced evapotranspiration, and (ii through an increase in the groundwater-induced stream zone saturated area after 1987. After analysing all the data available, a conceptual monthly model was created, comprising four inter-connecting stores: (i an upper zone unsaturated store, (ii a transient stream zone store, (ii a lower zone unsaturated store and (iv a saturated groundwater store. Data such as rooting depth, Leaf Area Index, soil porosity, profile thickness, depth to groundwater, stream length and surface slope were incorporated into the model as a priori defined attributes. The catchment average values for different stores were determined through matching observed and
Bari, M.; Smettem, K. R. J.
A conceptual water balance model is presented to represent changes in monthly water balance following land use changes. Monthly rainfall-runoff, groundwater and soil moisture data from four experimental catchments in Western Australia have been analysed. Two of these catchments, "Ernies" (control, fully forested) and "Lemon" (54% cleared) are in a zone of mean annual rainfall of 725 mm, while "Salmon" (control, fully forested) and "Wights" (100% cleared) are in a zone with mean annual rainfall of 1125 mm. At the Salmon forested control catchment, streamflow comprises surface runoff, base flow and interflow components. In the Wights catchment, cleared of native forest for pasture development, all three components increased, groundwater levels rose significantly and stream zone saturated area increased from 1% to 15% of the catchment area. It took seven years after clearing for the rainfall-runoff generation process to stabilise in 1984. At the Ernies forested control catchment, the permanent groundwater system is 20 m below the stream bed and so does not contribute to streamflow. Following partial clearing of forest in the Lemon catchment, groundwater rose steadily and reached the stream bed by 1987. The streamflow increased in two phases: (i) immediately after clearing due to reduced evapotranspiration, and (ii) through an increase in the groundwater-induced stream zone saturated area after 1987. After analysing all the data available, a conceptual monthly model was created, comprising four inter-connecting stores: (i) an upper zone unsaturated store, (ii) a transient stream zone store, (ii) a lower zone unsaturated store and (iv) a saturated groundwater store. Data such as rooting depth, Leaf Area Index, soil porosity, profile thickness, depth to groundwater, stream length and surface slope were incorporated into the model as a priori defined attributes. The catchment average values for different stores were determined through matching observed and predicted
Gao, H.; Birkel, C.; Hrachowitz, M.; Tetzlaff, D.; Soulsby, C.; Savenije, H. H. G.
Determining the amount of runoff generation from rainfall occupies a central place in rainfall-runoff modelling. Moreover, reading landscapes and developing calibration-free runoff generation models that adequately reflect land surface heterogeneities remains the focus of much hydrological research. In this study, we created a new method to estimate runoff generation - HAND-based Storage Capacity curve (HSC) which uses a topographic index (HAND, Height Above the Nearest Drainage) to identify hydrological similarity and partially the saturated areas of catchments. We then coupled the HSC model with the Mass Curve Technique (MCT) method to estimate root zone storage capacity (SuMax), and obtained the calibration-free runoff generation model HSC-MCT. Both the two models (HSC and HSC-MCT) allow us to estimate runoff generation and simultaneously visualize the spatial dynamic of saturated area. We tested the two models in the data-rich Bruntland Burn (BB) experimental catchment in Scotland with an unusual time series of the field-mapped saturation area extent. The models were subsequently tested in 323 MOPEX (Model Parameter Estimation Experiment) catchments in the United States. HBV and TOPMODEL were used as benchmarks. We found that the HSC performed better in reproducing the spatio-temporal pattern of the observed saturated areas in the BB catchment compared with TOPMODEL which is based on the topographic wetness index (TWI). The HSC also outperformed HBV and TOPMODEL in the MOPEX catchments for both calibration and validation. Despite having no calibrated parameters, the HSC-MCT model also performed comparably well with the calibrated HBV and TOPMODEL, highlighting the robustness of the HSC model to both describe the spatial distribution of the root zone storage capacity and the efficiency of the MCT method to estimate the SuMax. Moreover, the HSC-MCT model facilitated effective visualization of the saturated area, which has the potential to be used for broader
Chlumecký, Martin; Buchtele, Josef; Richta, Karel
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.
Kean, Jason W.; McCoy, Scott W.; Tucker, Gregory E.; Staley, Dennis M.; Coe, Jeffrey A.
Runoff during intense rainstorms plays a major role in generating debris flows in many alpine areas and burned steeplands. Yet compared to debris flow initiation from shallow landslides, the mechanics by which runoff generates a debris flow are less understood. To better understand debris flow initiation by surface water runoff, we monitored flow stage and rainfall associated with debris flows in the headwaters of two small catchments: a bedrock-dominated alpine basin in central Colorado (0.06 km2) and a recently burned area in southern California (0.01 km2). We also obtained video footage of debris flow initiation and flow dynamics from three cameras at the Colorado site. Stage observations at both sites display distinct patterns in debris flow surge characteristics relative to rainfall intensity (I). We observe small, quasiperiodic surges at low I; large, quasiperiodic surges at intermediate I; and a single large surge followed by small-amplitude fluctuations about a more steady high flow at high I. Video observations of surge formation lead us to the hypothesis that these flow patterns are controlled by upstream variations in channel slope, in which low-gradient sections act as “sediment capacitors,” temporarily storing incoming bed load transported by water flow and periodically releasing the accumulated sediment as a debris flow surge. To explore this hypothesis, we develop a simple one-dimensional morphodynamic model of a sediment capacitor that consists of a system of coupled equations for water flow, bed load transport, slope stability, and mass flow. This model reproduces the essential patterns in surge magnitude and frequency with rainfall intensity observed at the two field sites and provides a new framework for predicting the runoff threshold for debris flow initiation in a burned or alpine setting.
Chlumecký, M.; Buchtele, Josef; Richta, K.
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
Full Text Available Many hydrologic applications require reliable estimates of runoff in river basins to face the widespread lack of data, both in time and in space. A regional method for the reconstruction of monthly runoff series is here developed and applied to Sicily (Italy. A simple modeling structure is adopted, consisting of a regression-based rainfall–runoff model with four model parameters, calibrated through a two-step procedure. Monthly runoff estimates are based on precipitation, temperature, and exploiting the autocorrelation with runoff at the previous month. Model parameters are assessed by specific regional equations as a function of easily measurable physical and climate basin descriptors. The first calibration step is aimed at the identification of a set of parameters optimizing model performances at the level of single basin. Such “optimal” sets are used at the second step, part of a regional regression analysis, to establish the regional equations for model parameters assessment as a function of basin attributes. All the gauged watersheds across the region have been analyzed, selecting 53 basins for model calibration and using the other six basins exclusively for validation. Performances, quantitatively evaluated by different statistical indexes, demonstrate relevant model ability in reproducing the observed hydrological time-series at both the monthly and coarser time resolutions. The methodology, which is easily transferable to other arid and semi-arid areas, provides a reliable tool for filling/reconstructing runoff time series at any gauged or ungauged basin of a region.
van Dijk, A. I. J. M.; Bruijnzeel, L. A.; Vertessy, R. A.; Ruijter, J.
Despite widespread bench-terracing, stream sediment yields from agricultural hillsides in upland West Java remain high. We studied the causes of this lack of effect by combining measurements at different spatial scales using an erosion process model. Event runoff and sediment yield from two 4-ha terraced hillside subcatchments were measured and field surveys of land use, bench-terrace geometry and storage of sediment in the drainage network were conducted for two consecutive years. Runoff was 3.0-3.9% of rainfall and sediment yield was 11-30 t ha-1 yr-1 for different years, subcatchments and calculation techniques. Sediment storage changes in the subcatchment drainage network were less than 2 t ha-1, whereas an additional 0.3-1.5 t ha-1 was stored in the gully between the subcatchment flumes and the main stream. This suggests mean annual sediment delivery ratios of 86-125%, or 80-104% if this additional storage is included. The Terrace Erosion and Sediment Transport (TEST) model developed and validated for the studied environment was parameterized using erosion plot studies, land use surveys and digital terrain analysis to simulate runoff and sediment generation on the terraced hillsides. This resulted in over-estimates of runoff and under-estimates of runoff sediment concentration. Relatively poor model performance was attributed to sample bias in the six erosion plots used for model calibration and unaccounted covariance between important terrain attributes such as slope, infiltration capacity, soil conservation works and vegetation cover.
BERTHIER, E; ANDRIEU, H; CREUTIN, JD
A two-dimensional numerical model is developed to determine the role of soil in the formation of urban catchment runoff. The model is based on a modeling unit, called the Urban Hydrological Element (UHE), which corresponds to the cross-section of an urban cadastral parcel. Water flow in the soil of a UHE is explicitly simulated with a finite element code for solving the Richards' equation. Two runoff components, dependent on soil behavior, are represented: runoff from natural surfaces and dra...
New hydrological insights for the region: We examined the spatio-temporal variation of runoff generating mechanisms on the sub-basin level on seasonal basis. Our analysis reveals that the runoff generation in the Selke catchment is primarily dominated by shallow sub-surface flow and very rarely the contribution from Dunne overland flow exceeds sub-surface flow. Runoff generated by Hortonian mechanism is very infrequent and almost negligible. We also examined the spatio-temporal variation of runoff coefficients on seasonal basis as well as for individual storms. Due to higher precipitation and topographic relief in the upland catchment of Silberhutte, the runoff coefficients were consistently higher and its peak was found in winter months due to lower evapotranspiration.
Li, Y.; Chang, J.; Luo, L.
It is of great importance for water resources management to model the truly hydrological process under changing environment, especially under significant changes of underlying surfaces like the Wei River Bain (WRB) where the subsurface hydrology is highly influenced by human activities, and to systematically investigate the interactions among LULC change, streamflow variation and changes in runoff generation process. Therefore, we proposed the idea of evolving parameters in hydrological model (SWAT) to reflect the changes in physical environment with different LULC conditions. Then with these evolving parameters, the spatiotemporal impacts of LULC changes on streamflow were quantified, and qualitative analysis was conducted to further explore how LULC changes affect the streamflow from the perspective of runoff generation mechanism. Results indicate the following: 1) evolving parameter calibration is not only effective but necessary to ensure the validity of the model when dealing with significant changes in underlying surfaces due to human activities. 2) compared to the baseline period, the streamflow in wet seasons increased in the 1990s but decreased in the 2000s. While at yearly and dry seasonal scales, the streamflow decreased in both two decades; 3) the expansion of cropland is the major contributor to the reduction of surface water component, thus causing the decline in streamflow at yearly and dry seasonal scales. While compared to the 1990s, the expansions of woodland in the middle stream and grassland in the downstream are the main stressors that increased the soil water component, thus leading to the more decline of the streamflow in the 2000s.
Bronstert, Axel; Plate, Erich J.
The modelling of hillslope hydrology is of great importance not only for the reason that all non-plain, i.e. hilly or mountainous, landscapes can be considered as being composed of a mosaic of hillslopes. A hillslope model may also be used for both research purposes and for application-oriented, detailed, hillslope-scale hydrological studies in conjunction with related scientific disciplines such as geotechnics, geo-chemistry and environmental technology. Despite the current limited application of multi-process and multi-dimensional hydrological models (particularly at the hillslope scale), hardly any comprehensive model has been available for operational use. In this paper we introduce a model which considers most of the relevant hillslope hydrological processes. Some recent applications are described which demonstrate its ability to narrow the stated gap in hillslope hydrological modelling. The modelling system accounts for the hydrological processes of interception, evapotranspiration, infiltration, soil-moisture movement (where the flow processes can be modelled in three dimensions), surface runoff, subsurface stormflow and streamflow discharge. The relevant process interactions are also included. Special regard has been given to consideration of state-of-the-art knowledge concerning rapid soilwater flow processes during storm conditions (e.g. macropore infiltration, lateral subsurface stormflow, return flow) and to its transfer to and inclusion within an operational modelling scheme. The model is "physically based" in the sense that its parameters have a physical meaning and can be obtained or derived from field measurements. This somewhat weaker than usual definition of a physical basis implies that some of the sub-models (still) contain empirical components, that the effects of the high spatial and temporal variability found in nature cannot always be expressed within the various physical laws, i.e. that the laws are scale dependent, and that due to
Costa, Veber; Fernandes, Wilson
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
van Dijk, A.I.J.M.; Bruijnzeel, L.A.; Vertessy, R.A.; Ruijter, J.
Despite widespread bench-terracing, stream sediment yields from agricultural hillsides in upland West Java remain high. We studied the causes of this lack of effect by combining measurements at different spatial scales using an erosion process model. Event runoff and sediment yield from two 4-ha
Coles, Anna E.; Appels, Willemijn M.; McConkey, Brian G.; McDonnell, Jeffrey J.
Understanding and modeling snowmelt-runoff generation in seasonally-frozen regions is a major challenge in hydrology. Partly, this is because the controls on hillslope-scale snowmelt-runoff generation are potentially extensive and their hierarchy is poorly understood. Understanding the relative importance of controls (e.g. topography, vegetation, land use, soil characteristics, and precipitation dynamics) on runoff response is necessary for model development, spatial extrapolation, and runoff...
A. E. Van Beusekom; R. J. Viger
A module to simulate glacier runoff, PRMSglacier, was added to PRMS (Precipitation Runoff Modeling System), a distributed-parameter, physical-process hydrological simulation code. The extension does not require extensive on-glacier measurements or computational expense but still relies on physical principles over empirical relations as much as is feasible while...
Full Text Available Successful implementation of best management practices for reducing non-point source (NPS pollution requires knowledge of the location of saturated areas that produce runoff. A physically-based, fully-distributed, GIS-integrated model, the Soil Moisture Distribution and Routing (SMDR model was developed to simulate the hydrologic behavior of small rural upland watersheds with shallow soils and steep to moderate slopes. The model assumes that gravity is the only driving force of water and that most overland flow occurs as saturation excess. The model uses available soil and climatic data, and requires little calibration. The SMDR model was used to simulate runoff production on a 164-ha farm watershed in Delaware County, New York, in the headwaters of New York City water supply. Apart from land use, distributed input parameters were derived from readily available data. Simulated hydrographs compared reasonably with observed flows at the watershed outlet over a eight year simulation period, and peak timing and intensities were well reproduced. Using off-site weather input data produced occasional missed event peaks. Simulated soil moisture distribution agreed well with observed hydrological features and followed the same spatial trend as observed soil moisture contents sampled on four transects. Model accuracy improved when input variables were calibrated within the range of SSURGO-available parameters. The model will be a useful planning tool for reducing NPS pollution from farms in landscapes similar to the Northeastern US.
Ebel, Brian A.; Moody, John A.; Martin, Deborah A.
We investigated the control of postwildfire runoff by physical and hydraulic properties of soil, hydrologic states, and an ash layer immediately following wildfire. The field site is within the area burned by the 2010 Fourmile Canyon Fire in Colorado, USA. Physical and hydraulic property characterization included ash thickness, particle size distribution, hydraulic conductivity, and soil water retention curves. Soil water content and matric potential were measured indirectly at several depths below the soil surface to document hydrologic states underneath the ash layer in the unsaturated zone, whereas precipitation and surface runoff were measured directly. Measurements of soil water content showed that almost no water infiltrated below the ash layer into the near-surface soil in the burned site at the storm time scale (i.e., minutes to hours). Runoff generation processes were controlled by and highly sensitive to ash thickness and ash hydraulic properties. The ash layer stored from 97% to 99% of rainfall, which was critical for reducing runoff amounts. The hydrologic response to two rain storms with different rainfall amounts, rainfall intensity, and durations, only ten days apart, indicated that runoff generation was predominantly by the saturation-excess mechanism perched at the ash-soil interface during the first storm and predominantly by the infiltration-excess mechanism at the ash surface during the second storm. Contributing area was not static for the two storms and was 4% (saturation excess) to 68% (infiltration excess) of the catchment area. Our results showed the importance of including hydrologic conditions and hydraulic properties of the ash layer in postwildfire runoff generation models.
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...
Thorndahl, Søren; Johansen, C.; Schaarup-Jensen, Kjeld
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...
L. Gong; S. Halldin; C.-Y. Xu
World water resources have primarily been analysed by global-scale hydrological models in the last decades. Runoff generation in many of these models are based on process formulations developed at catchments scales. The division between slow runoff (baseflow) and fast runoff is primarily governed by slope and spatial distribution of effective water storage capacity, both acting a very small scales. Many hydrological models, e.g. VIC, account for the spatial storage variability in terms...
Cheng, Yanyan; Ogden, Fred L.; Zhu, Jianting
Preferential flow paths (PFPs) affect the hydrological response of humid tropical catchments but have not received sufficient attention. We consider PFPs created by tree roots and earthworms in a near-surface soil layer in steep, humid, tropical lowland catchments and hypothesize that observed hydrological behaviors can be better captured by reasonably considering PFPs in this layer. We test this hypothesis by evaluating the performance of four different physically based distributed model structures without and with PFPs in different configurations. Model structures are tested both quantitatively and qualitatively using hydrological, geophysical, and geochemical data both from the Smithsonian Tropical Research Institute Agua Salud Project experimental catchment(s) in Central Panama and other sources in the literature. The performance of different model structures is evaluated using runoff Volume Error and three Nash-Sutcliffe efficiency measures against observed total runoff, stormflows, and base flows along with visual comparison of simulated and observed hydrographs. Two of the four proposed model structures which include both lateral and vertical PFPs are plausible, but the one with explicit simulation of PFPs performs the best. A small number of vertical PFPs that fully extend below the root zone allow the model to reasonably simulate deep groundwater recharge, which plays a crucial role in base flow generation. Results also show that the shallow lateral PFPs are the main contributor to the observed high flow characteristics. Their number and size distribution are found to be more important than the depth distribution. Our model results are corroborated by geochemical and geophysical observations.
Kumar, P.; Tripathi, S.
The Gangetic Plain is among the most fertile and highly cultivated regions of the world. It supports a large agrarian population that is rapidly growing since the Green Revolution of 1960s. With increasing population, the average farm size is decreasing. Consequently, the density of cadastral boundaries, which are used for separating individual farm holdings, is increasing. The cadastral boundaries in the Gangetic Plains are typically 25 to 30 cm high and 30 to 60 cm wide. These boundaries segment the flat topography of the region, creating small artificial water storages, the effect of which on the hydrology of the region is not extensively investigated. The objective of this research is to develop a laboratory scale physical model for understanding the effect of cadastral boundaries and resulting artificial storages on runoff generation. Experiments were performed in a hydrological apparatus equipped for simulating rainfall-runoff processes under control conditions. The experiments were carried out for watersheds with no cadastral boundaries, and with cadastral boundaries of varying dimensions and densities. Changes in the observed runoff were used to develop a mathematical model for explaining and predicting the impact of cadastral boundaries on the hydrology of the Gangetic Plains.
Van Beusekom, Ashley E.; Viger, Roland
A module to simulate glacier runoff, PRMSglacier, was added to PRMS (Precipitation Runoff Modeling System), a distributed-parameter, physical-process hydrological simulation code. The extension does not require extensive on-glacier measurements or computational expense but still relies on physical principles over empirical relations as much as is feasible while maintaining model usability. PRMSglacier is validated on two basins in Alaska, Wolverine, and Gulkana Glacier basin, which have been studied since 1966 and have a substantial amount of data with which to test model performance over a long period of time covering a wide range of climatic and hydrologic conditions. When error in field measurements is considered, the Nash-Sutcliffe efficiencies of streamflow are 0.87 and 0.86, the absolute bias fractions of the winter mass balance simulations are 0.10 and 0.08, and the absolute bias fractions of the summer mass balances are 0.01 and 0.03, all computed over 42 years for the Wolverine and Gulkana Glacier basins, respectively. Without taking into account measurement error, the values are still within the range achieved by the more computationally expensive codes tested over shorter time periods.
In this study, the Regional Transportation District (RTD)s light rail tracks were modeled to determine the Rational Method : runoff coefficient, C, values corresponding to ballasted tracks. To accomplish this, a laboratory study utilizing a : rain...
P. Fiener; K. Auerswald; F. Winter; M. Disse
Surface runoff generation on arable fields is an important driver of (local) flooding, on-site and off-site damages by erosion, and of nutrient and agrochemical transport. In general, three different processes generate surface runoff (Hortonian runoff, saturation excess runoff, and return of subsurface flow). Despite the developments in our understanding of these processes it remains difficult to predict, which processes govern runoff generation during the course of an event or through...
Full Text Available The potential impact of future climate change on runoff generation processes in two southern British Columbia catchments was explored using the Canadian Centre for Climate Modelling Analysis General Circulation Model (CGCMa1 to estimate future changes in precipitation, temperature and cloud cover while the U.B.C. Watershed Model was used to simulate discharges and quantify the separate runoff components, i.e. rainfall, snowmelt, glacier melt and groundwater. Changes, not only in precipitation and temperature but also in the spatial distribution of precipitation with elevation, cloud cover, glacier extension, altitude distribution of vegetation, vegetation biomass production and plant physiology were considered. The future climate of the catchments would be wetter and warmer than the present. In the maritime rain-fed catchment of the Upper Campbell, runoff from rainfall is the most significant source of flow for present and future climatic conditions in the autumn and winter whereas runoff from groundwater generates the flow in spring and summer, especially for the future climate scenario. The total runoff, under the future climatic conditions, would increase in the autumn and winter and decrease in spring and summer. In contrast, in the interior snow-covered Illecillewaet catchment, groundwater is the most significant runoff generation mechanism in the autumn and winter although, at present, significant flow is generated from snowmelt in spring and from glacier runoff in summer. In the future scenario, the contribution to flow from snowmelt would increase in winter and diminish in spring while the runoff from the glacier would remain unchanged; groundwater would then become the most significant source of runoff, which would peak earlier in the season. Keywords: climatic change, hydrological simulation, rainfall, snowmelt, runoff processes
Fowler, Keirnan J. A.; Peel, Murray C.; Western, Andrew W.; Zhang, Lu; Peterson, Tim J.
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 cases of apparent model failure under the split sample test using the lower [higher] of two model performance criteria trialed, 155 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.
Li, Hong-Yi; Sivapalan, Murugesu; Tian, Fuqiang; Harman, Ciaran
Inspired by the Dunne diagram, the climatic and landscape controls on the partitioning of annual runoff into its various components (Hortonian and Dunne overland flow and subsurface stormflow) are assessed quantitatively, from a purely theoretical perspective. A simple distributed hydrologic model has been built sufficient to simulate the effects of different combinations of climate, soil, and topography on the runoff generation processes. The model is driven by a sequence of simple hypothetical precipitation events, for a large combination of climate and landscape properties, and hydrologic responses at the catchment scale are obtained through aggregation of grid-scale responses. It is found, first, that the water balance responses, including relative contributions of different runoff generation mechanisms, could be related to a small set of dimensionless similarity parameters. These capture the competition between the wetting, drying, storage, and drainage functions underlying the catchment responses, and in this way, provide a quantitative approximation of the conceptual Dunne diagram. Second, only a subset of all hypothetical catchment/climate combinations is found to be "behavioral," in terms of falling sufficiently close to the Budyko curve, describing mean annual runoff as a function of climate aridity. Furthermore, these behavioral combinations are mostly consistent with the qualitative picture presented in the Dunne diagram, indicating clearly the commonality between the Budyko curve and the Dunne diagram. These analyses also suggest clear interrelationships amongst the "behavioral" climate, soil, and topography parameter combinations, implying these catchment properties may be constrained to be codependent in order to satisfy the Budyko curve.
Hillslope hydrology is concerned with the partition of precipitation as it passes through the vegetation and soil between overland flow and subsurface flow. Flow follows routes which attenuate and delay the flow to different extents, so that a knowledge of the relevant mechanisms is important. In the 1960s and 1970s, hillslope hydrology developed as a distinct topic through the application of new field observations to develop a generation of physically based forecasting models. In its short history, theory has continually been overturned by field observation. Thus the current tendency, particularly among temperate zone hydrologists, to dismiss all Hortonian overland flow as a myth, is now being corrected by a number of significant field studies which reveal the great range in both climatic and hillslope conditions. Some recent models have generally attempted to simplify the processes acting, for example including only vertical unsaturated flow and lateral saturated flows. Others explicitly forecast partial or contributing areas. With hindsight, the most complete and distributed models have generally shown little forecasting advantage over simpler approaches, perhaps trending towards reliable models which can run on desk top microcomputers. The variety now being recognised in hillslope hydrological responses should also lead to models which take account of more complex interactions, even if initially with a less secure physical and mathematical basis than the Richards equation. In particular, there is a need to respond to the variety of climatic responses, and to spatial variability on and beneath the surface, including the role of seepage macropores and pipes which call into question whether the hillside can be treated as a Darcian flow system.
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.
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.
McCabe, G.J.; Wolock, D.M.
A monthly water balance model (WB model) is used with CRUTS2.1 monthly temperature and precipitation data to generate time series of monthly runoff for all land areas of the globe for the period 1905 through 2002. Even though annual precipitation accounts for most of the temporal and spatial variability in annual runoff, increases in temperature have had an increasingly negative effect on annual runoff after 1980. Although the effects of increasing temperature on runoff became more apparent after 1980, the relative magnitude of these effects are small compared to the effects of precipitation on global runoff. ?? 2010 Royal Meteorological Society.
Full Text Available Imperviousness associated with urbanization remains one of the biggest challenges in sustainable urban design. The replacement of forests, marshlands, buffers, and wetlands with impervious surfaces, strongly influences hydrological processes in urbanizing areas. This study analyzed the contribution of four constructed surfaces types – roofs, yards, roads, and an international airport – to surface runoff within a 21 km2 watershed, and presents the development over five decades (1977−2030. The land-cover model, used to assess watershed imperviousness in 2030, utilized coefficients between impervious areas generating surface runoff and the floor area, developed during the study. The conducted imperviousness analysis allowed the evaluation of land-use development impacts on the stream network, and the identification of hydrologically active areas for urban planning and stormwater management. Research revealed the importance of yard imperviousness related to suburban residential housing for stormwater runoff generation, and the impacts of transport-related imperviousness on stormwater runoff.
Thorndahl, Søren Liedtke; Johansen, C.; Schaarup-Jensen, Kjeld
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...
Gong, L.; Halldin, S.; Xu, C.-Y.
World water resources have primarily been analysed by global-scale hydrological models in the last decades. Runoff generation in many of these models are based on process formulations developed at catchments scales. The division between slow runoff (baseflow) and fast runoff is primarily governed by slope and spatial distribution of effective water storage capacity, both acting at very small scales. Many hydrological models, e.g. VIC, account for the spatial storage variability in terms of statistical distributions; such models are generally proven to perform well. The statistical approaches, however, use the same runoff-generation parameters everywhere in a basin. The TOPMODEL concept, on the other hand, links the effective maximum storage capacity with real-world topography. Recent availability of global high-quality, high-resolution topographic data makes TOPMODEL attractive as a basis for a physically-based runoff-generation algorithm at large scales, even if its assumptions are not valid in flat terrain or for deep groundwater systems. We present a new runoff-generation algorithm for large-scale hydrology based on TOPMODEL concepts intended to overcome these problems. The TRG (topography-derived runoff generation) algorithm relaxes the TOPMODEL equilibrium assumption so baseflow generation is not tied to topography. TRG only uses the topographic index to distribute average storage to each topographic index class. The maximum storage capacity is proportional to the range of topographic index and is scaled by one parameter. The distribution of storage capacity within large-scale grid cells is obtained numerically through topographic analysis. The new topography-derived distribution function is then inserted into a runoff-generation framework similar VIC's. Different basin parts are parameterised by different storage capacities, and different shapes of the storage-distribution curves depend on their topographic characteristics. The TRG algorithm is driven by the
Full Text Available World water resources have primarily been analysed by global-scale hydrological models in the last decades. Runoff generation in many of these models are based on process formulations developed at catchments scales. The division between slow runoff (baseflow and fast runoff is primarily governed by slope and spatial distribution of effective water storage capacity, both acting at very small scales. Many hydrological models, e.g. VIC, account for the spatial storage variability in terms of statistical distributions; such models are generally proven to perform well. The statistical approaches, however, use the same runoff-generation parameters everywhere in a basin. The TOPMODEL concept, on the other hand, links the effective maximum storage capacity with real-world topography. Recent availability of global high-quality, high-resolution topographic data makes TOPMODEL attractive as a basis for a physically-based runoff-generation algorithm at large scales, even if its assumptions are not valid in flat terrain or for deep groundwater systems. We present a new runoff-generation algorithm for large-scale hydrology based on TOPMODEL concepts intended to overcome these problems. The TRG (topography-derived runoff generation algorithm relaxes the TOPMODEL equilibrium assumption so baseflow generation is not tied to topography. TRG only uses the topographic index to distribute average storage to each topographic index class. The maximum storage capacity is proportional to the range of topographic index and is scaled by one parameter. The distribution of storage capacity within large-scale grid cells is obtained numerically through topographic analysis. The new topography-derived distribution function is then inserted into a runoff-generation framework similar VIC's. Different basin parts are parameterised by different storage capacities, and different shapes of the storage-distribution curves depend on their topographic characteristics. The TRG algorithm
MacLeod, C.; Binley, A.; Humphreys, M.; King, I. P.; O'Donovan, S.; Papadopoulos, A.; Turner, L. B.; Watts, C.; Whalley, W. R.; Haygarth, P.
Sustainable management of water in landscapes requires balancing demands of agricultural production whilst moderating downstream effects like flooding. Pasture comprises 69% of global agricultural areas and is essential for producing food and fibre alongside environmental goods and services. Thus there is a need to breed forage grasses that deliver multiple benefits through increased levels of productivity whilst moderating fluxes of water. Here we show that a novel grass hybrid that combines the entire genomes of perennial ryegrass (Lolium perenne - the grass of choice for Europe’s forage agriculture) and meadow fescue (Festuca pratensis) has a significant role in flood prevention. Field plot experiments established differences in runoff generation with the hybrid cultivar reducing runoff by 50% compared to perennial ryegrass cultivar, and by 35% compared to a meadow fescue cultivar (34 events over two years, replicated randomized-block design, statistically significant differences). This important research outcome was the result of a project that combined plant genetics, soil physics and plot scale hydrology to identify novel grass genotypes that can reduce runoff from grassland systems. Through a coordinated series of experiments examining effects from the gene to plot scale, we have identified that the rapid growth and then turnover of roots in the L. perenne x F. pratensis hybrid is likely to be a key mechanism in reducing runoff generation. More broadly this is an exciting first step to realizing the potential to design grass genomes to achieve both food production, and to deliver flood control, a key ecosystem service.
Mohammady, Majid; Moradi, Hamid Reza; Zeinivand, Hossein; Temme, A.J.A.M.; Yazdani, Mohammad Reza; Pourghasemi, Hamid Reza
Land use change is an important determinant of hydrological processes and is known to affect hydrological parameters such as runoff volume, flood frequency, base flow, and the partitioning into surface flow and subsurface flow. The main objective of this research was to assess the magnitude of
Wooyeon Sunwoo; Minha Choi
Runoff prediction in limited-data areas is vital for hydrological applications, such as the design of infrastructure and flood defenses, runoff forecasting, and water management. Rainfall–runoff models may be useful for simulation of runoff generation, particularly event-based models, which offer a practical modeling scheme because of their simplicity. However, there is a need to reduce the uncertainties related to the estimation of the initial wetness condition (IWC) prior to a rainfall even...
Moody, John A.; Ebel, Brian A.
Post-wildfire runoff was investigated by combining field measurements and modelling of infiltration into fire-affected soils to predict time-to-start of runoff and peak runoff rate at the plot scale (1 m2). Time series of soil-water content, rainfall and runoff were measured on a hillslope burned by the 2010 Fourmile Canyon Fire west of Boulder, Colorado during cyclonic and convective rainstorms in the spring and summer of 2011. Some of the field measurements and measured soil physical properties were used to calibrate a one-dimensional post-wildfire numerical model, which was then used as a ‘virtual instrument’ to provide estimates of the saturated hydraulic conductivity and high-resolution (1 mm) estimates of the soil-water profile and water fluxes within the unsaturated zone.Field and model estimates of the wetting-front depth indicated that post-wildfire infiltration was on average confined to shallow depths less than 30 mm. Model estimates of the effective saturated hydraulic conductivity, Ks, near the soil surface ranged from 0.1 to 5.2 mm h−1. Because of the relatively small values of Ks, the time-to-start of runoff (measured from the start of rainfall), tp, was found to depend only on the initial soil-water saturation deficit (predicted by the model) and a measured characteristic of the rainfall profile (referred to as the average rainfall acceleration, equal to the initial rate of change in rainfall intensity). An analytical model was developed from the combined results and explained 92–97% of the variance of tp, and the numerical infiltration model explained 74–91% of the variance of the peak runoff rates. These results are from one burned site, but they strongly suggest that tp in fire-affected soils (which often have low values of Ks) is probably controlled more by the storm profile and the initial soil-water saturation deficit than by soil hydraulic properties.
Danáčová, Michaela; Valent, Peter; Výleta, Roman
Nowadays, rainfall simulators are being used by many researchers in field or laboratory experiments. The main objective of most of these experiments is to better understand the underlying runoff generation processes, and to use the results in the process of calibration and validation of hydrological models. Many research groups have assembled their own rainfall simulators, which comply with their understanding of rainfall processes, and the requirements of their experiments. Most often, the existing rainfall simulators differ mainly in the size of the irrigated area, and the way they generate rain drops. They can be characterized by the accuracy, with which they produce a rainfall of a given intensity, the size of the irrigated area, and the rain drop generating mechanism. Rainfall simulation experiments can provide valuable information about the genesis of surface runoff, infiltration of water into soil and rainfall erodibility. Apart from the impact of physical properties of soil, its moisture and compaction on the generation of surface runoff and the amount of eroded particles, some studies also investigate the impact of vegetation cover of the whole area of interest. In this study, the rainfall simulator was used to simulate the impact of the slope gradient of the irrigated area on the amount of generated runoff and sediment yield. In order to eliminate the impact of external factors and to improve the reproducibility of the initial conditions, the experiments were conducted in laboratory conditions. The laboratory experiments were carried out using a commercial rainfall simulator, which was connected to an external peristaltic pump. The pump maintained a constant and adjustable inflow of water, which enabled to overcome the maximum volume of simulated precipitation of 2.3 l, given by the construction of the rainfall simulator, while maintaining constant characteristics of the simulated precipitation. In this study a 12-minute rainfall with a constant intensity
Beck, Nicole G; Conley, Gary; Kanner, Lisa; Mathias, Margaret
We present an urban runoff model designed for stormwater managers to quantify runoff reduction benefits of mitigation actions that has lower input data and user expertise requirements than most commonly used models. The stormwater tool to estimate load reductions (TELR) employs a semi-distributed approach, where landscape characteristics and process representation are spatially-lumped within urban catchments on the order of 100 acres (40 ha). Hydrologic computations use a set of metrics that describe a 30-year rainfall distribution, combined with well-tested algorithms for rainfall-runoff transformation and routing to generate average annual runoff estimates for each catchment. User inputs include the locations and specifications for a range of structural best management practice (BMP) types. The model was tested in a set of urban catchments within the Lake Tahoe Basin of California, USA, where modeled annual flows matched that of the observed flows within 18% relative error for 5 of the 6 catchments and had good regional performance for a suite of performance metrics. Comparisons with continuous simulation models showed an average of 3% difference from TELR predicted runoff for a range of hypothetical urban catchments. The model usually identified the dominant BMP outflow components within 5% relative error of event-based measured flow data and simulated the correct proportionality between outflow components. TELR has been implemented as a web-based platform for use by municipal stormwater managers to inform prioritization, report program benefits and meet regulatory reporting requirements (www.swtelr.com). Copyright © 2017. Published by Elsevier Ltd.
R. H. Hawkins; A. Barreto-Munoz
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...
Ries, Fabian; Schmidt, Sebastian; Sauter, Martin; Lange, Jens
Surface runoff acts as an integrated response of catchment characteristics and hydrological processes. In the Eastern Mediterranean region, a lack of runoff data has hindered a better understanding of runoff generation processes on the catchment scale, despite the importance of surface runoff as a water resource or flood hazard. Our main aim was to identify and explain differences in catchment runoff reactions across a variety of scales. Over a period of five years, we observed runoff in ephemeral streams of seven watersheds with sizes between 3 and 129 km2. Landuse and surface cover types (share of vegetation, bare soil and rock outcrops) were derived from aerial images by objective classification techniques. Using data from a dense rainfall network we analysed the effects of scale, catchment properties and aridity on runoff generation. Thereby we extracted rainfall and corresponding runoff events from our time-series to calculate event based rainfall characteristics and catchment runoff coefficients. Soil moisture observations provided additional information on antecedent moisture conditions, infiltration characteristics and the evolution of saturated areas. In contrast to the prevailing opinion that the proportion of Hortonian overland flow increases with aridity, we found that in our area the largest share (> 95 %) of runoff is generated by saturation excess overland flow in response to long lasting, rainfall events of high amount. This was supported by a strong correlation between event runoff and precipitation totals. Similar rainfall thresholds (50 mm) for runoff generation were observed in all investigated catchments. No scale effects on runoff coefficients were found; instead we identified up to three-fold runoff coefficients in catchments with larger extension of arid areas, higher percentage of rock outcrops and urbanization. Comparing two headwater catchments with noticeable differences in extent of olive orchards, no difference in runoff generation was
Full Text Available Surface runoff generation on arable fields is an important driver of flooding, on-site and off-site damages by erosion, and of nutrient and agrochemical transport. In general, three different processes generate surface runoff (Hortonian runoff, saturation excess runoff, and return of subsurface flow. Despite the developments in our understanding of these processes it remains difficult to predict which processes govern runoff generation during the course of an event or throughout the year, when soil and vegetation on arable land are passing many states. We analysed the results from 317 rainfall simulations on 209 soils from different landscapes with a resolution of 14 286 runoff measurements to determine temporal and spatial differences in variables governing surface runoff, and to derive and test a statistical model of surface runoff generation independent from an a priori selection of modelled process types. Measured runoff was related to 20 time-invariant soil properties, three variable soil properties, four rain properties, three land use properties and many derived variables describing interactions and curvilinear behaviour. In an iterative multiple regression procedure, six of these properties/variables best described initial abstraction and the hydrograph. To estimate initial abstraction, the percentages of stone cover above 10% and of sand content in the bulk soil were needed, while the hydrograph could be predicted best from rain depth exceeding initial abstraction, rainfall intensity, soil organic carbon content, and time since last tillage. Combining the multiple regressions to estimate initial abstraction and surface runoff allowed modelling of event-specific hydrographs without an a priori assumption of the underlying process. The statistical model described the measured data well and performed equally well during validation. In both cases, the model explained 71 and 58% of variability in accumulated runoff volume and instantaneous
Full Text Available Processes of runoff and erosion are one of the main research subjects in hydrological science. Based on the field and laboratory measurements, and analogous with development of computational techniques, runoff and erosion models based on equations which describe the physics of the process are also developed. Several models of runoff and erosion which describes entire process of genesis and sediment transport on the catchment are described and compared.
Gelati, Emiliano; Madsen, H.; Rosbjerg, Dan
We define a Markov-modulated autoregressive model with exogenous input (MARX) to generate runoff scenarios using climatic information. Runoff parameterization is assumed to be conditioned on a hidden climate state following a Markov chain, where state transition probabilities are functions...... of the climatic input. MARX allows stochastic modeling of nonstationary runoff, as runoff anomalies are described by a mixture of autoregressive models with exogenous input, each one corresponding to a climate state. We apply MARX to inflow time series of the Daule Peripa reservoir (Ecuador). El Nino Southern...... Oscillation (ENSO) information is used to condition runoff parameterization. Among the investigated ENSO indexes, the NINO 1+2 sea surface temperature anomalies and the trans-Nino index perform best as predictors. In the perspective of reservoir optimization at various time scales, MARX produces realistic...
van Dijk, A.I.J.M.; Bruijnzeel, L.A.
Overland flow resulting from an excess of rain over infiltration is an essential component of many models of runoff and erosion from fields or catchments. The spatially variable infiltration (SVI) model and a set of associated equations relating depth of runoff and maximum rate of 'effective' runoff
Zhan, X.; Huang, M.-L.
The development and the application of ArcCN-Runoff tool, an extension of ESRI@ ArcGIS software, are reported. This tool can be applied to determine curve numbers and to calculate runoff or infiltration for a rainfall event in a watershed. Implementation of GIS techniques such as dissolving, intersecting, and a curve-number reference table improve efficiency. Technical processing time may be reduced from days, if not weeks, to hours for producing spatially varied curve number and runoff maps. An application example for a watershed in Lyon County and Osage County, Kansas, USA, is presented. ?? 2004 Elsevier Ltd. All rights reserved.
Yiming Si; Xiaowei Liu
The change trend of water cycle factors such as rainfall, runoff and flood events etc. in the Luohe River basin are analysed based on hydrological data since 1950s. The analysis shows that rainfall has been decreasing, but not much, while runoff has been decreasing remarkably. Under the same rainfall conditions, runoff and peak discharge have dropped considerably, runoff coefficient has become much smaller, and the frequency of flood occurrence has been decreasing. It is considered that environmental variation caused by human activities accounts for the change, in characteristics of runoff generation and confluence in the basin.(Author)
Full Text Available Apart from direct measurements, modelling of runoff from green roofs is valuable source of information about effectiveness of this type of structure from hydrological point of view. Among different type of models, the most frequently used are numerical models. They allow to assess the impact of green roofs on decrease and attenuation of runoff, reduction of peak runoff and value of water retention. This paper presents preliminary results of research on computing the rate of runoff from green roofs using GARDENIA model. The analysis has been carried out for selected rainfall events registered during measuring campaign on pilot-scale green roofs. Obtained results are promising and show good fit between observed and simulated runoff.
Full Text Available Based on the field and laboratory measurements, and analogous with development of computational techniques, runoff and erosion models based on equations which describe the physics of the process are also developed. Based on the KINEROS2 model, this paper presents basic modelling principles of runoff and erosion processes based on the St. Venant's equations. Alternative equations for friction calculation, calculation of source and deposition elements and transport capacity are also shown. Numerical models based on original and alternative equations are calibrated and verified on laboratory scale model. According to the results, friction calculation based on the analytic solution of laminar flow must be included in all runoff and erosion models.
Vaezi, A. R.; Bahrami, H. A.; Sadeghi, S. H. R.; Mahdian, M. H.
The process of transformation of rainfall into runoff over a catchment is very complex and exhibits both temporal and spatial variability. However, in a semi-arid area this variability is mainly controlled by the physical and chemical properties of the soil surface. Developing an accurate and easily-used model that can appropriately determine the runoff generation value is of strong demand. In this study a simple, an empirically based model developed to explore effect of soil properties on ru...
exponential model was developed between the rainfall and the run-off that predicted the run-off with an R2 of ... precipitation and other climate parameters is well documented ...... Sen P K 1968 Estimates of the regression coefficient based.
Rafael Pires Fernandes
Full Text Available Since an understanding of how runoff is generated is of great importance to soil conservation, to water availability and to the management of a watershed, the objective of this study was to understand the generation of surface runoff in a watershed covered by sugarcane and riparian forest. Nine surface runoff plots were set up, evenly distributed on the lower, middle and upper slopes. The lower portion was covered by riparian forest. We showed that the average surface runoff coefficient along the slope in the present study was higher than in other studies under different land uses. Furthermore, the surface runoff was higher under sugarcane compared to the riparian forest, especially after sugarcane harvesting. Besides land cover, other factors such as the characteristics of rainfall events, relief and physical soil characteristics such as soil bulk density and saturated hydraulic conductivity influenced the surface runoff generation.
Marques da Silva, Richarde; Guimarães Santos, Celso Augusto; Carneiro de Lima Silva, Valeriano; Pereira e Silva, Leonardo
This study evaluates erosivity, surface runoff generation, and soil erosion rates for Mamuaba catchment, sub-catchment of Gramame River basin (Brazil) by using the ArcView Soil and Water Assessment Tool (AvSWAT) model. Calibration and validation of the model was performed on monthly basis, and it could simulate surface runoff and soil erosion to a good level of accuracy. Daily rainfall data between 1969 and 1989 from six rain gauges were used, and the monthly rainfall erosivity of each station was computed for all the studied years. In order to evaluate the calibration and validation of the model, monthly runoff data between January 1978 and April 1982 from one runoff gauge were used as well. The estimated soil loss rates were also realistic when compared to what can be observed in the field and to results from previous studies around of catchment. The long-term average soil loss was estimated at 9.4 t ha(-1) year(-1); most of the area of the catchment (60%) was predicted to suffer from a low- to moderate-erosion risk (soil erosion was estimated to exceed > 12 t ha(-1) year(-1). Expectedly, estimated soil loss was significantly correlated with measured rainfall and simulated surface runoff. Based on the estimated soil loss rates, the catchment was divided into four priority categories (low, moderate, high and very high) for conservation intervention. The study demonstrates that the AvSWAT model provides a useful tool for soil erosion assessment from catchments and facilitates the planning for a sustainable land management in northeastern Brazil.
Evelpidou, Niki (Ed.); Cordier, Stephane (Ed.); Merino, Agustin (Ed.); Figueiredo, Tomás de (Ed.); Centeri, Csaba (Ed.)
Table of Contents PART I – THEORY OF RUNOFF EROSION CHAPTER 1 - RUNOFF EROSION – THE MECHANISMS CHAPTER 2 - LARGE SCALE APPROACHES OF RUNOFF EROSION CHAPTER 3 - MEASURING PRESENT RUNOFF EROSION CHAPTER 4 - MODELLING RUNOFF EROSION CHAPTER 5 - RUNOFF EROSION AND HUMAN SOCIETIES: THE INFLUENCE OF LAND USE AND MANAGEMENT PRACTICES ON SOIL EROSION PART II - CASE STUDIES CASE STUDIES – INTRODUCTION: RUNOFF EROSION IN MEDITERRANEAN AREA CASE STUDY 1: Soil Erosion Risk...
Appels, W.M.; Bogaart, P.W.; Bogaart, P.W.; Zee, van der S.E.A.T.M.
In flat lowland agricultural catchments in temperate climate zones with highly permeable sandy soils, surface runoff is a rare process with a large impact on the redistribution of sediments and solutes and stream water quality. We examine hydrological data obtained on two field sites in the
Full Text Available Runoff is one of most important hydrological variables that are used in many civil works, planning for optimal use of reservoirs, organizing rivers and warning flood. The runoff curve number (CN is a key factor in determining runoff in the SCS (Soil Conservation Service based hydrologic modeling method. The traditional SCS-CN method for calculating the composite curve number consumes a major portion of the hydrologic modeling time. Therefore, geographic information systems (GIS are now being used in combination with the SCS-CN method. This work uses a methodology of determining surface runoff by Geographic Information System model and applying SCS-CN method that needs the necessary parameters such as land use map, hydrologic soil groups, rainfall data, DEM, physiographic characteristic of the basin. The model is built by implementing some well known hydrologic methods in GIS like as ArcHydro, ArcCN-Runoff for modeling of Zilberchai basin runoff. The results show that the high average weighted of curve number indicate that permeability of the basin is low and therefore likelihood of flooding is high. So the fundamental works is essential in order to increase water infiltration in Zilberchai basin and to avoid wasting surface water resources. Also comparing the results of the computed and observed runoff value show that use of GIS tools in addition to accelerate the calculation of the runoff also increase the accuracy of the results. This paper clearly demonstrates that the integration of GIS with the SCS-CN method provides a powerful tool for estimating runoff volumes in large basins.
Malekani, L.; Khaleghi, S.; Mahmoodi, M.
Runoff is one of most important hydrological variables that are used in many civil works, planning for optimal use of reservoirs, organizing rivers and warning flood. The runoff curve number (CN) is a key factor in determining runoff in the SCS (Soil Conservation Service) based hydrologic modeling method. The traditional SCS-CN method for calculating the composite curve number consumes a major portion of the hydrologic modeling time. Therefore, geographic information systems (GIS) are now being used in combination with the SCS-CN method. This work uses a methodology of determining surface runoff by Geographic Information System model and applying SCS-CN method that needs the necessary parameters such as land use map, hydrologic soil groups, rainfall data, DEM, physiographic characteristic of the basin. The model is built by implementing some well known hydrologic methods in GIS like as ArcHydro, ArcCN-Runoff for modeling of Zilberchai basin runoff. The results show that the high average weighted of curve number indicate that permeability of the basin is low and therefore likelihood of flooding is high. So the fundamental works is essential in order to increase water infiltration in Zilberchai basin and to avoid wasting surface water resources. Also comparing the results of the computed and observed runoff value show that use of GIS tools in addition to accelerate the calculation of the runoff also increase the accuracy of the results. This paper clearly demonstrates that the integration of GIS with the SCS-CN method provides a powerful tool for estimating runoff volumes in large basins.
Birch, A. L.; Stallard, R. F.; Barnard, H. R.
While relationships between land use/land cover and hydrology are well studied and understood in temperate parts of the world, little research exists in the humid tropics, where hydrologic research is often decades behind. Specifically, quantitative information on how physical and biological differences across varying land covers influence runoff generation and hydrologic flowpaths in the humid tropics is scarce; frequently leading to poorly informed hydrologic modelling and water policy decision making. This research effort seeks to quantify how tropical land cover change may alter physical hydrologic processes in the economically important Panama Canal Watershed (Republic of Panama) by separating streamflow into its different runoff components using end member mixing analysis. The samples collected for this project come from small headwater catchments of four varying land covers (mature tropical forest, young secondary forest, active pasture, recently clear-cut tropical forest) within the Smithsonian Tropical Research Institute's Agua Salud Project. During the past three years, samples have been collected at the four study catchments from streamflow and from a number of water sources within hillslope transects, and have been analyzed for stable water isotopes, major cations, and major anions. Major ion analysis of these samples has shown distinct geochemical differences for the potential runoff generating end members sampled (soil moisture/ preferential flow, groundwater, overland flow, throughfall, and precipitation). Based on this finding, an effort was made from May-August 2017 to intensively sample streamflow during wet season storm events, yielding a total of 5 events of varying intensity in each land cover/catchment, with sampling intensity ranging from sub-hourly to sub-daily. The focus of this poster presentation will be to present the result of hydrograph separation's done using end member mixing analysis from this May-August 2017 storm dataset. Expected
This study proposes an application of two techniques of artificial intelligence (AI) ... (2006) applied rainfall–runoff modeling using ANN ... in artificial intelligence, engineering and science .... usually be estimated from a sample of observations.
... 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 ...
Zhang, Xuyang; Goh, Kean S
Three models were evaluated for their accuracy in simulating pesticide runoff at the edge of agricultural fields: Pesticide Root Zone Model (PRZM), Root Zone Water Quality Model (RZWQM), and OpusCZ. Modeling results on runoff volume, sediment erosion, and pesticide loss were compared with measurements taken from field studies. Models were also compared on their theoretical foundations and ease of use. For runoff events generated by sprinkler irrigation and rainfall, all models performed equally well with small errors in simulating water, sediment, and pesticide runoff. The mean absolute percentage errors (MAPEs) were between 3 and 161%. For flood irrigation, OpusCZ simulated runoff and pesticide mass with the highest accuracy, followed by RZWQM and PRZM, likely owning to its unique hydrological algorithm for runoff simulations during flood irrigation. Simulation results from cold model runs by OpusCZ and RZWQM using measured values for model inputs matched closely to the observed values. The MAPE ranged from 28 to 384 and 42 to 168% for OpusCZ and RZWQM, respectively. These satisfactory model outputs showed the models' abilities in mimicking reality. Theoretical evaluations indicated that OpusCZ and RZWQM use mechanistic approaches for hydrology simulation, output data on a subdaily time-step, and were able to simulate management practices and subsurface flow via tile drainage. In contrast, PRZM operates at daily time-step and simulates surface runoff using the USDA Soil Conservation Service's curve number method. Among the three models, OpusCZ and RZWQM were suitable for simulating pesticide runoff in semiarid areas where agriculture is heavily dependent on irrigation. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.
Modarres, R.; Ouarda, T. B. M. J.
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.
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.
Campos-Aranda Daniel Francisco
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.
Szolgay, J.; Kubes, R.
The component part of atmospheric precipitations-runoff model of Hron River is a individual model of transformation of flows in river network, too, which transforms runoff from separate partial catchment basin into terminal profile. This component of precipitations-runoff model can also be used as individual hydrologic transformation model of runoff waves in river-basin. Identification and calibration of this model is realised independently on precipitations-runoff model of Hron River, which is described in this chapter in detail.
Krein, A.; Pailler, J.; Guignard, C.; Iffly, J.; Pfister, L.; Hoffmann, L.
In the experimental Mess basin (35 km2, Luxembourg) dissolved xenobiotics in surface water are used to study the influences of anthropogenic sources like separated sewer systems on runoff generation. Emerging contaminants like pharmaceuticals are of growing interest because of their use in large quantities in human and veterinary medicine. The amounts reaching surface waters depend on rainfall patterns, hydraulic conditions, consumption, metabolism, degradation, and disposal. The behaviour of endocrine disruptors including pharmaceuticals in the aquatic environment is widely unknown. The twelve molecules analyzed belong to three families: the estrogens, the antibiotics (sulfonamides, tetracyclines), and the painkillers (ibuprofen, diclofenac). Xenobiotics can be used as potential environmental tracers for untreated sewerage. Our results show that the concentrations are highly variable during flood events. The highest concentrations are reached in the first flush period, mainly during the rising limb of the flood hydrographs. As a result of the kinematic wave effect the concentration peak occurs in some cases a few hours after the discharge maximum. In floodwater (eleven floods, 66 samples) the highest concentrations were measured for ibuprofen (g/l range), estrone, and diclofenac (all ng/l range). From the tetracycline group, essentially tetracycline itself is of relevance, while the sulfonamides are mainly represented by sulfamethoxazole (all in ng/l range). In the Mess River the pharmaceuticals fluxes during flood events proved to be influenced by hydrological conditions. Different pharmaceuticals showed their concentration peaks during different times of a flood event. An example is the estrone peak that - during summer flash floods - often occurred one to two hours prior to the largest concentrations of the painkillers. This suggests for more sources than the sole storm drainage through the spillway of the single sewage water treatment plant, different
Winter, Benjamin; Schneeberger, Klaus; Dung Nguyen, Viet; Vorogushyn, Sergiy; Huttenlau, Matthias; Merz, Bruno; Stötter, Johann
The evaluation of potential monetary damage of flooding is an essential part of flood risk management. One possibility to estimate the monetary risk is to analyze long time series of observed flood events and their corresponding damages. In reality, however, only few flood events are documented. This limitation can be overcome by the generation of a set of synthetic, physically and spatial plausible flood events and subsequently the estimation of the resulting monetary damages. In the present work, a set of synthetic flood events is generated by a continuous rainfall-runoff simulation in combination with a coupled weather generator and temporal disaggregation procedure for the study area of Vorarlberg (Austria). Most flood risk studies focus on daily time steps, however, the mesoscale alpine study area is characterized by short concentration times, leading to large differences between daily mean and daily maximum discharge. Accordingly, an hourly time step is needed for the simulations. The hourly metrological input for the rainfall-runoff model is generated in a two-step approach. A synthetic daily dataset is generated by a multivariate and multisite weather generator and subsequently disaggregated to hourly time steps with a k-Nearest-Neighbor model. Following the event generation procedure, the negative consequences of flooding are analyzed. The corresponding flood damage for each synthetic event is estimated by combining the synthetic discharge at representative points of the river network with a loss probability relation for each community in the study area. The loss probability relation is based on exposure and susceptibility analyses on a single object basis (residential buildings) for certain return periods. For these impact analyses official inundation maps of the study area are used. Finally, by analyzing the total event time series of damages, the expected annual damage or losses associated with a certain probability of occurrence can be estimated for
Horat, Christoph; Antonetti, Manuel; Wernli, Heini; Zappa, Massimiliano
Flash floods evolve rapidly during and after heavy precipitation events and represent a risk for society, especially in mountainous areas. Knowledge on meteorological variables and their temporal development is often not sufficient to predict their occurrence. Therefore, information about the state of the hydrological system derived from hydrological models is used. These models rely however on strong simplifying assumptions and need therefore to be calibrated. This prevents their application on catchments, where no runoff data is available. Here we present a flash-flood forecasting chain including: (i) a nowcasting product which combines radar and rain gauge rainfall data (CombiPrecip), (ii) meteorological data from numerical weather prediction models at currently finest available resolution (COSMO-1, COSMO-E), (iii) operationally available soil moisture estimations from the PREVAH hydrological model, and (iv) a process-based runoff generation module with no need for calibration (RGM-PRO). This last component uses information on the spatial distribution of dominant runoff processes (DRPs) which can be derived with different mapping approaches, and is parameterised a priori based on expert knowledge. First, we compared the performance of RGM-PRO with the one of a traditional conceptual runoff generation module for several events on Swiss Emme catchment, as well as on their nested catchments. Different DRP-maps are furthermore tested to evaluate the sensitivity of the forecasting chain to the mapping approaches. Then, we benchmarked the new forecasting chain with the traditional chain used on the Swiss Verzasca catchment. The results show that RGM-PRO performs similarly or even better than the traditional calibrated conceptual module on the investigated catchments. The use of strongly simplified DRP mapping approaches still leads to satisfying results, due mainly to the fact that the largest uncertainty source is represented by the meteorological input data. On the
Crow, W. T.; Chen, F.; Reichle, R. H.; Xia, Y.; Liu, Q.
Accurate partitioning of precipitation into infiltration and runoff is a fundamental objective of land surface models tasked with characterizing the surface water and energy balance. Temporal variability in this partitioning is due, in part, to changes in prestorm soil moisture, which determine soil infiltration capacity and unsaturated storage. Utilizing the National Aeronautics and Space Administration Soil Moisture Active Passive Level-4 soil moisture product in combination with streamflow and precipitation observations, we demonstrate that land surface models (LSMs) generally underestimate the strength of the positive rank correlation between prestorm soil moisture and event runoff coefficients (i.e., the fraction of rainfall accumulation volume converted into stormflow runoff during a storm event). Underestimation is largest for LSMs employing an infiltration-excess approach for stormflow runoff generation. More accurate coupling strength is found in LSMs that explicitly represent subsurface stormflow or saturation-excess runoff generation processes.
Sun, Y.; Hou, Z.; Huang, M.; Tian, F.; Leung, L. Ruby
This study demonstrates the possibility of inverting hydrologic parameters using surface flux and runoff observations in version 4 of the Community Land Model (CLM4). Previous studies showed that surface flux and runoff calculations are sensitive to major hydrologic parameters in CLM4 over different watersheds, and illustrated the necessity and possibility of parameter calibration. Both deterministic least-square fitting and stochastic Markov-chain Monte Carlo (MCMC)-Bayesian inversion approaches are evaluated by applying them to CLM4 at selected sites with different climate and soil conditions. The unknowns to be estimated include surface and subsurface runoff generation parameters and vadose zone soil water parameters. We find that using model parameters calibrated by the sampling-based stochastic inversion approaches provides significant improvements in the model simulations compared to using default CLM4 parameter values, and that as more information comes in, the predictive intervals (ranges of posterior distributions) of the calibrated parameters become narrower. In general, parameters that are identified to be significant through sensitivity analyses and statistical tests are better calibrated than those with weak or nonlinear impacts on flux or runoff observations. Temporal resolution of observations has larger impacts on the results of inverse modeling using heat flux data than runoff data. Soil and vegetation cover have important impacts on parameter sensitivities, leading to different patterns of posterior distributions of parameters at different sites. Overall, the MCMC-Bayesian inversion approach effectively and reliably improves the simulation of CLM under different climates and environmental conditions. Bayesian model averaging of the posterior estimates with different reference acceptance probabilities can smooth the posterior distribution and provide more reliable parameter estimates, but at the expense of wider uncertainty bounds.
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 ...
The subject of an article is the mathematical modeling of the rainwater runoff along the surface catchment taking account the transport of pollution which permeates into the water flow from a porous media of soil at the certain areas of this surface. The developed mathematical model consists of two types of equations: the ...
Department of Civil Engineering, National Pingtung University of Science and Technology, Neipu Hsiang,. Pingtung ... study, a model for estimating runoff by using rainfall data from a river basin is developed and a neural ... For example, 2009 typhoon Morakot in Pingtung ... Tokar and Markus (2000) applied ANN to predict.
K. Benzineb, M. Remaoun
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.
This study proposes an application of two techniques of artificial intelligence (AI) for rainfall–runoff modeling: the artificial neural networks (ANN) and the evolutionary computation (EC). Two diff- erent ANN techniques, the feed forward back propagation (FFBP) and generalized regression neural network (GRNN) methods ...
Liu, H.; Liu, J.; Peng, A.; Gu, W.; Wang, W.; Gao, F.
In order to learn more about the critical zone ecohydrological dynamics at the Qinghai-Tibet Plateau, a research on the identification of runoff components using tracers was carried out in the Niyang River upstream, a tributary of the Yalung Zangbo River. In this study, four basins with the areas of 182, 216, 243, 213 km2 which are embed in a larger basin were sampled at altitudes between 3667 to 6140 m. The types of land use in the basins mainly include forest land, grassland and glacier. River water and precipitation were sampled monthly, while spring water, glacial ice, soil, and plants were sampled seasonally. Soil and plant samples were taken along the valleys with spatial interval of about 5 km. Soil and plant waters were extracted via cryogenic vacuum distillation method, and then analyzed for isotopes and ions. Preliminary results show that the δD and δ18O of the precipitation water spread approximately along the LMWL of the Namucuo Lake near Lasa city, which varied according to altitude. Stem water δD and δ18O from different elevations and tree species also varied regularly, albeit with no apparent relationship to recent precipitation. It appears that trees utilized fissure water and soil water formed by precipitation. Future efforts will involve (1) an expanded sampling strategy across basins, and (2) a series of experiments on the Hydrohill catchment in the Chuzhou Experimental Facility, whereby an improved understanding of K+, Na+, Ca2+ and Mg2+ export dynamics could aid in much better description and modeling of Niyang River runoff composition and generation. This research is funded by the NSFC project 91647111 and 91647203, which are included in the Runoff Change and its Adaptive Management in the Major Rivers in Southwestern China Major Research Plan.
Faber, Claas; Wu, Naicheng; Ulrich, Uta; Fohrer, Nicola
Since lowlands are characterised by flat topography and low hydraulic gradients, groundwater inflow has a large influence to streamflow generation in such catchments. In catchments with intense agricultural land use, artificial drainages are often another major contributor to streamflow. They shorten the soil passage and thus change the matter retention potential as well as runoff dynamics of a catchment. Contribution of surface runoff to streamflow is usually less important in volume. However, due to high concentrations of agrochemicals, surface runoff can constitute an important entry pathway into water bodies, especially if strong precipitation events coincide with fertilizer or pesticide application. The DFG funded project "Separating surface runoff from tile drainage flow in agricultural lowland catchments based on diatoms to improve modelled runoff components and phosphorous transport" investigates prevalent processes in this context in a 50 km² lowland catchment (Kielstau, Schleswig-Holstein, Germany) with the goal of improving existing models. End Member Mixing Analysis (EMMA) is used in the project to determine the relative importance of groundwater, tile drainage and surface runoff to streamflow at daily time steps. It became apparent that geochemical tracers are suitable for distinguishing surface runoff, but are weak for the separation of tile drainage and groundwater influence. We attribute this to the strong and complex interaction between soil water and shallow groundwater tables in the catchment. Recent studies (e.g. Pfister et al. 2011, Tauro et al. 2013) show the potential of diatoms as indicators for hydrological processes. Since we found diatoms to be suitable for the separation of tile drainage and stream samples (Wu et al., unpublished data) in our catchment, we are able to include diatom derived indices (e.g. density, species moisture indices, diversity indices) as traces in EMMA. Our results show that the inclusion of diatom data in the
Full Text Available The neighbouring river systems Cubango and Cuito drain the southeastern part of the Angolan Highlands and form the Okavango River after their confluence, thus providing 95% of the Okavango River discharge. Although they are characterised by similar environmental conditions, runoff records indicate remarkable differences regarding the hydrological dynamics. The Cubango River is known for rapid discharges with high peaks and low baseflow whereas the Cuito runoff appears more balanced. These differences are mainly caused by heterogeneous geological conditions or terrain features. The Cubango headwaters are dominated by crystalline bedrock and steeper, v-shaped valleys while the Cuito system is characterised by wide, swampy valleys and thick sand layers, thus attenuating runoff. This study presents model exercises which have been performed to assess and quantify these effects by applying the distributive model J2000g for each sub-basin. The models provide reasonable results representing the spatio-temporal runoff pattern, although some peaks are over- or underestimated, particularly in the Cuito catchment. This is explained by the scarce information on extent and structure of storages, such as aquifers or swamps, in the Cuito system. However, the model results aid understanding of the differences of both tributaries in runoff generation and underpin the importance of floodplains regarding the control of runoff peaks and low flows in the Cuito system. Model exercises reveal that basin heterogeneity needs to be taken into account and must be parameterised appropriately for reliable modelling and assessment of the entire Okavango River basin for managing the water resources of the transboundary Okavango River in a harmonious way.
Birkel, C.; Broder, T.; Biester, H.
We used a relatively simple two-layer, coupled hydrology-biogeochemistry model to simultaneously simulate streamflow and stream dissolved organic carbon (DOC) concentrations in a small lead and arsenic contaminated upland peat catchment in northwestern Germany. The model procedure was informed by an initial data mining analysis, in combination with regression relationships of discharge, DOC, and element export. We assessed the internal model DOC processing based on stream DOC hysteresis patterns and 3-hourly time step groundwater level and soil DOC data for two consecutive summer periods in 2013 and 2014. The parsimonious model (i.e., few calibrated parameters) showed the importance of nonlinear and rapid near-surface runoff generation mechanisms that caused around 60% of simulated DOC load. The total load was high even though these pathways were only activated during storm events on average 30% of the monitoring time—as also shown by the experimental data. Overall, the drier period 2013 resulted in increased nonlinearity but exported less DOC (115 kg C ha-1 yr-1 ± 11 kg C ha-1 yr-1) compared to the equivalent but wetter period in 2014 (189 kg C ha-1 yr-1 ± 38 kg C ha-1 yr-1). The exceedance of a critical water table threshold (-10 cm) triggered a rapid near-surface runoff response with associated higher DOC transport connecting all available DOC pools and subsequent dilution. We conclude that the combination of detailed experimental work with relatively simple, coupled hydrology-biogeochemistry models not only allowed the model to be internally constrained but also provided important insight into how DOC and tightly coupled pollutants or trace elements are mobilized.
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
Kisi, Ozgur; Shiri, Jalal; Tombul, Mustafa
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.
Achieng, K. O.; Zhu, J.
There are a number of North American Regional Climate Change Assessment Program (NARCCAP) climatic models that have been used to project surface runoff in the mid-21st century. Statistical model selection techniques are often used to select the model that best fits data. However, model selection techniques often lead to different conclusions. In this study, ten models are averaged in Bayesian paradigm to project runoff. Bayesian Model Averaging (BMA) is used to project and identify effect of model uncertainty on future runoff projections. Baseflow separation - a two-digital filter which is also called Eckhardt filter - is used to separate USGS streamflow (total runoff) into two components: baseflow and surface runoff. We use this surface runoff as the a priori runoff when conducting BMA of runoff simulated from the ten RCM models. The primary objective of this study is to evaluate how well RCM multi-model ensembles simulate surface runoff, in a Bayesian framework. Specifically, we investigate and discuss the following questions: How well do ten RCM models ensemble jointly simulate surface runoff by averaging over all the models using BMA, given a priori surface runoff? What are the effects of model uncertainty on surface runoff simulation?
Aquatic Buffers serve as natural boundaries between local waterways and existing development. The model and example ordinaces below provide suggested language or technical guidance designed to create the most effective stream buffer zones possible.
Jonsdottir, Harpa; Madsen, Henrik; Palsson, Olafur Petur
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...
Birch, Heidi; Vezzaro, Luca; Mikkelsen, Peter Steen
the information obtained about MPs discharged from the monitored system. A dynamic stormwater quality model was calibrated using MP data collected by volume-proportional and passive sampling in a storm drainage system in the outskirts of Copenhagen (Denmark) and a 10-year rain series was used to find annual...... average and maximum event mean concentrations. Use of this model reduced the uncertainty of predicted annual average concentrations compared to a simple stochastic method based solely on data. The predicted annual average obtained by using passive sampler measurements (one month installation...
Lindblom, Erik Ulfson; Ahlman, S.; Mikkelsen, Peter Steen
(runoff volumes and pollutant masses). We use the generalized likelihood uncertainty estimation (GLUE) methodology and generate posterior parameter distributions that result in model outputs encompassing a significant number of the highly variable measurements. Given the applied pollution accumulation......In this paper, we conduct a systematic analysis of the uncertainty related with estimating the total load of pollution (copper) from a separate stormwater drainage system, conditioned on a specific combination of input data, a dynamic conceptual pollutant accumulation-washout model and measurements...
A. I. J. M. van Dijk
Full Text Available An appropriately simple event runoff model for catchment hydrological studies was derived. The model was selected from several variants as having the optimum balance between simplicity and the ability to explain daily observations of streamflow from 260 Australian catchments (23–1902 km2. Event rainfall and runoff were estimated from the observations through a combination of baseflow separation and storm flow recession analysis, producing a storm flow recession coefficient (kQF. Various model structures with up to six free parameters were investigated, covering most of the equations applied in existing lumped catchment models. The performance of alternative structures and free parameters were expressed in Aikake's Final Prediction Error Criterion (FPEC and corresponding Nash-Sutcliffe model efficiencies (NSME for event runoff totals. For each model variant, the number of free parameters was reduced in steps based on calculated parameter sensitivity. The resulting optimal model structure had two or three free parameters; the first describing the non-linear relationship between event rainfall and runoff (Smax, the second relating runoff to antecedent groundwater storage (CSg, and a third that described initial rainfall losses (Li, but which could be set at 8 mm without affecting model performance too much. The best three parameter model produced a median NSME of 0.64 and outperformed, for example, the Soil Conservation Service Curve Number technique (median NSME 0.30–0.41. Parameter estimation in ungauged catchments is likely to be challenging: 64% of the variance in kQF among stations could be explained by catchment climate indicators and spatial correlation, but corresponding numbers were a modest 45% for CSg, 21% for Smax and none for Li, respectively. In gauged catchments, better
Donker, N. H. W.
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.
Full Text Available Runoff prediction in limited-data areas is vital for hydrological applications, such as the design of infrastructure and flood defenses, runoff forecasting, and water management. Rainfall–runoff models may be useful for simulation of runoff generation, particularly event-based models, which offer a practical modeling scheme because of their simplicity. However, there is a need to reduce the uncertainties related to the estimation of the initial wetness condition (IWC prior to a rainfall event. Soil moisture is one of the most important variables in rainfall–runoff modeling, and remotely sensed soil moisture is recognized as an effective way to improve the accuracy of runoff prediction. In this study, the IWC was evaluated based on remotely sensed soil moisture by using the Soil Conservation Service-Curve Number (SCS-CN method, which is one of the representative event-based models used for reducing the uncertainty of runoff prediction. Four proxy variables for the IWC were determined from the measurements of total rainfall depth (API5, ground-based soil moisture (SSMinsitu, remotely sensed surface soil moisture (SSM, and soil water index (SWI provided by the advanced scatterometer (ASCAT. To obtain a robust IWC framework, this study consists of two main parts: the validation of remotely sensed soil moisture, and the evaluation of runoff prediction using four proxy variables with a set of rainfall–runoff events in the East Asian monsoon region. The results showed an acceptable agreement between remotely sensed soil moisture (SSM and SWI and ground based soil moisture data (SSMinsitu. In the proxy variable analysis, the SWI indicated the optimal value among the proposed proxy variables. In the runoff prediction analysis considering various infiltration conditions, the SSM and SWI proxy variables significantly reduced the runoff prediction error as compared with API5 by 60% and 66%, respectively. Moreover, the proposed IWC framework with
Soulis, K. X.; Valiantzas, J. D.; Dercas, N.; Londra, P. A.
The Soil Conservation Service Curve Number (SCS-CN) method is widely used for predicting direct runoff volume for a given rainfall event. The applicability of the SCS-CN method and the runoff generation mechanism were thoroughly analysed in a Mediterranean experimental watershed in Greece. The region is characterized by a Mediterranean semi-arid climate. A detailed land cover and soil survey using remote sensing and GIS techniques, showed that the watershed is dominated by coarse soils with high hydraulic conductivities, whereas a smaller part is covered with medium textured soils and impervious surfaces. The analysis indicated that the SCS-CN method fails to predict runoff for the storm events studied, and that there is a strong correlation between the CN values obtained from measured runoff and the rainfall depth. The hypothesis that this correlation could be attributed to the existence of an impermeable part in a very permeable watershed was examined in depth, by developing a numerical simulation water flow model for predicting surface runoff generated from each of the three soil types of the watershed. Numerical runs were performed using the HYDRUS-1D code. The results support the validity of this hypothesis for most of the events examined where the linear runoff formula provides better results than the SCS-CN method. The runoff coefficient of this formula can be taken equal to the percentage of the impervious area. However, the linear formula should be applied with caution in case of extreme events with very high rainfall intensities. In this case, the medium textured soils may significantly contribute to the total runoff and the linear formula may significantly underestimate the runoff produced.
Soulis, K. X.; Valiantzas, J. D.; Dercas, N.; Londra, P. A.
The Soil Conservation Service Curve Number (SCS-CN) method is widely used for predicting direct runoff volume for a given rainfall event. The applicability of the SCS-CN method and the direct runoff generation mechanism were thoroughly analysed in a Mediterranean experimental watershed in Greece. The region is characterized by a Mediterranean semi-arid climate. A detailed land cover and soil survey using remote sensing and GIS techniques, showed that the watershed is dominated by coarse soils with high hydraulic conductivities, whereas a smaller part is covered with medium textured soils and impervious surfaces. The analysis indicated that the SCS-CN method fails to predict runoff for the storm events studied, and that there is a strong correlation between the CN values obtained from measured runoff and the rainfall depth. The hypothesis that this correlation could be attributed to the existence of an impermeable part in a very permeable watershed was examined in depth, by developing a numerical simulation water flow model for predicting surface runoff generated from each of the three soil types of the watershed. Numerical runs were performed using the HYDRUS-1D code. The results support the validity of this hypothesis for most of the events examined where the linear runoff formula provides better results than the SCS-CN method. The runoff coefficient of this formula can be taken equal to the percentage of the impervious area. However, the linear formula should be applied with caution in case of extreme events with very high rainfall intensities. In this case, the medium textured soils may significantly contribute to the total runoff and the linear formula may significantly underestimate the runoff produced.
K. X. Soulis
Full Text Available The Soil Conservation Service Curve Number (SCS-CN method is widely used for predicting direct runoff volume for a given rainfall event. The applicability of the SCS-CN method and the direct runoff generation mechanism were thoroughly analysed in a Mediterranean experimental watershed in Greece. The region is characterized by a Mediterranean semi-arid climate. A detailed land cover and soil survey using remote sensing and GIS techniques, showed that the watershed is dominated by coarse soils with high hydraulic conductivities, whereas a smaller part is covered with medium textured soils and impervious surfaces. The analysis indicated that the SCS-CN method fails to predict runoff for the storm events studied, and that there is a strong correlation between the CN values obtained from measured runoff and the rainfall depth. The hypothesis that this correlation could be attributed to the existence of an impermeable part in a very permeable watershed was examined in depth, by developing a numerical simulation water flow model for predicting surface runoff generated from each of the three soil types of the watershed. Numerical runs were performed using the HYDRUS-1D code. The results support the validity of this hypothesis for most of the events examined where the linear runoff formula provides better results than the SCS-CN method. The runoff coefficient of this formula can be taken equal to the percentage of the impervious area. However, the linear formula should be applied with caution in case of extreme events with very high rainfall intensities. In this case, the medium textured soils may significantly contribute to the total runoff and the linear formula may significantly underestimate the runoff produced.
Loáiciga, Hugo A.; Johnson, J. Michael
A modified Green-and-Ampt model is formulated to quantify infiltration on sloping terrain underlain by homogeneous soil wetted by surficial water application. This paper's theory for quantifying infiltration relies on the mathematical statement of the coupled partial differential equations (pdes) governing infiltration and runoff. These pdes are solved by employing an explicit finite-difference numerical method that yields the infiltration, the infiltration rate, the depth to the wetting front, the rate of runoff, and the depth of runoff everywhere on the slope during external wetting. Data inputs consist of a water application rate or the rainfall hyetograph of a storm of arbitrary duration, soil hydraulic characteristics and antecedent moisture, and the slope's hydraulic and geometric characteristics. The presented theory predicts the effect an advancing wetting front has on slope stability with respect to translational sliding. This paper's theory also develops the 1D pde governing suspended sediment transport and slope degradation caused by runoff influenced by infiltration. Three examples illustrate the application of the developed theory to calculate infiltration and runoff on a slope and their role on the stability of cohesive and cohesionless soils forming sloping terrain.
Chin, W.Q.; Salmon, G.M.; Luo, W.
The need to accurately forecast precipitation and water runoff is essential to the operations of hydroelectric power plants. In 1993, BC Hydro established a program to develop, test and improve new and existing atmospheric and hydrologic models that would be suitable for application over the mountainous terrain of British Columbia. The objective was to improve the reliability and accuracy of hydrological models that simulate and forecast precipitation and runoff. Another objective was to develop a modelling system for hydrologic risk assessment in dam safety evaluation. This paper describes progress made in implementing timely measures to resolve problems of reservoir operation in balancing the need for generation of hydroelectric power with conflicting requirements for flood control, fisheries, recreation and other environmental concerns. 23 refs., 11 figs
Meshram, S. Gajbhiye; Sharma, S. K.; Tignath, S.
Watershed is an ideal unit for planning and management of land and water resources (Gajbhiye et al., IEEE international conference on advances in technology and engineering (ICATE), Bombay, vol 1, issue 9, pp 23-25, 2013a; Gajbhiye et al., Appl Water Sci 4(1):51-61, 2014a; Gajbhiye et al., J Geol Soc India (SCI-IF 0.596) 84(2):192-196, 2014b). This study aims to generate the curve number, using remote sensing and geographical information system (GIS) and the effect of slope on curve number values. The study was carried out in Kanhaiya Nala watershed located in Satna district of Madhya Pradesh. Soil map, Land Use/Land cover and slope map were generated in GIS Environment. The CN parameter values corresponding to various soil, land cover, and land management conditions were selected from Natural Resource Conservation Service (NRCS) standard table. Curve number (CN) is an index developed by the NRCS, to represent the potential for storm water runoff within a drainage area. The CN for a drainage basin is estimated using a combination of land use, soil, and antecedent soil moisture condition (AMC). In present study effect of slope on CN values were determined. The result showed that the CN unadjusted value are higher in comparison to CN adjusted with slope. Remote sensing and GIS is very reliable technique for the preparation of most of the input data required by the SCS curve number model.
Full Text Available Analyses of runoff- sediment measurement and evaluation using automated and convectional runoff-meters was carried out at Meteorological and Hydrological Station of Auchi Polytechnic, Auchi using two runoff plots (ABCDa and EFGHm of area 2m 2 each, depth 0.26 m and driven into the soil to the depth of 0.13m. Runoff depths and intensities were measured from each of the positioned runoff plot. Automated runoff-meter has a measuring accuracy of ±0.001l/±0.025 mm and rainfall depth-intensity was measured using tipping-bucket rainguage during the period of 14-month of experimentation. Minimum and maximum rainfall depths of 1.2 and 190.3 mm correspond to measured runoff depths (MRo of 0.0 mm for both measurement approaches and 60.4 mm and 48.9 mm respectively. Automated runoffmeter provides precise, accurate and instantaneous result over the convectional measurement of surface runoff. Runoff measuring accuracy for automated runoff-meter from the plot (ABCDa produces R 2 = 0.99; while R 2 = 0.96 for manual evaluation in plot (EFGHm. WEPP and SWAT models were used to simulate the obtained hydrological variables from the applied measurement mechanisms. The outputs of sensitivity simulation analysis indicate that data from automated measuring systems gives a better modelling index and such could be used for running robust runoff-sediment predictive modelling technique under different reservoir sedimentation and water management scenarios.
Cuhaciyan, C.; Luce, C.; Voisin, N.; Lettenmaier, D.; Black, T.
Roads can have a substantial effect on hydrologic patterns of forested watersheds; the most noteworthy being the resurfacing of shallow groundwater at roadcuts. The influence of roads on hydrology has compelled hydrologists to include water routing and storage routines in rainfall-runoff models, such as those in the Distributed Hydrologic Soil Vegetation Model (DHSVM). We tested the ability of DHSVM to match observed runoff in roadcuts of a watershed in the Coast Range of Oregon. Eight roadcuts were instrumented using large tipping bucket gauges designed to capture only the water entering the roadside ditch from an 80-m long roadcut. The roadcuts were categorized by the topography of the upstream hillside as either swale, planar, or ridge. The simulation was run from December 2002 to December 2003 at a relatively fine spatial resolution (10-m). Average observed soil depths are 1.8-m across the watershed, below which there lies deep and highly weathered sandstone. DHSVM was designed for relatively impermeable bedrock and shallow soils; therefore it does not provide a mechanism for deep groundwater movement and storage. In the geologic setting of the study basin, however, water is routed through the sandstone allowing water to pass under roads through the parent material. For this reason a uniformly deep soil of 6.5-m with a decreased decay in conductivity with depth was used in the model to allow water to be routed beneath roadcuts that are up to 5.5-m in height. Up to three, typically shallow, soil layers can be modeled in DHSVM. We used the lowest of the three soil layers to mimic the hydraulically-well-connected sandstone exposed at deeper roadcuts. The model was calibrated against observed discharge at the outlet of the watershed. While model results closely matched the observed hydrograph at the watershed outlet, simulated runoff at an upstream gauge and the roadside ditches were varied and often higher than those observed in the field. The timing of the field
Bhandari, Ammar B; Nelson, Nathan O; Sweeney, Daniel W; Baffaut, Claire; Lory, John A; Senaviratne, Anomaa; Pierzynski, Gary M; Janssen, Keith A; Barnes, Philip L
Process-based computer models have been proposed as a tool to generate data for Phosphorus (P) Index assessment and development. Although models are commonly used to simulate P loss from agriculture using managements that are different from the calibration data, this use of models has not been fully tested. The objective of this study is to determine if the Agricultural Policy Environmental eXtender (APEX) model can accurately simulate runoff, sediment, total P, and dissolved P loss from 0.4 to 1.5 ha of agricultural fields with managements that are different from the calibration data. The APEX model was calibrated with field-scale data from eight different managements at two locations (management-specific models). The calibrated models were then validated, either with the same management used for calibration or with different managements. Location models were also developed by calibrating APEX with data from all managements. The management-specific models resulted in satisfactory performance when used to simulate runoff, total P, and dissolved P within their respective systems, with > 0.50, Nash-Sutcliffe efficiency > 0.30, and percent bias within ±35% for runoff and ±70% for total and dissolved P. When applied outside the calibration management, the management-specific models only met the minimum performance criteria in one-third of the tests. The location models had better model performance when applied across all managements compared with management-specific models. Our results suggest that models only be applied within the managements used for calibration and that data be included from multiple management systems for calibration when using models to assess management effects on P loss or evaluate P Indices. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.
Rasmussen, Michael R.; Brorsen, Michael; Schaarup-Jensen, Kjeld
A neural network is used to simulate folw and water levels in a sewer system. The calibration of th neural network is based on a few measured events and the network is validated against measureed events as well as flow simulated with the MOUSE model (Lindberg and Joergensen, 1986). The neural...... network is used to compute flow or water level at selected points in the sewer system, and to forecast the flow from a small residential area. The main advantages of the neural network are the build-in self calibration procedure and high speed performance, but the neural network cannot be used to extract...... knowledge of the runoff process. The neural network was found to simulate 150 times faster than e.g. the MOUSE model....
Nicolau, J.M. [Universidad de Alcala de Henares, Alcala de Henares (Spain)
The aim of the study was to identify the mechanisms of runoff generation and routing and their controlling factors at the hillslope scale, on artificial slopes derived from surface coal mining reclamation in a Mediterranean-continental area. Rainfall and runoff at interrill and microcatchment scales were recorded for a year on two slopes with different substrata: topsoil cover and overburden cover. Runoff coefficient and runoff routing from interrill areas to microcatchment outlets were higher in the overburden substratum than in topsoil, and greater in the most developed rill network. Rainfall volume is the major parameter responsible for runoff response on overburden, suggesting that this substratum is very impermeable - at least during the main rainfall periods of the year (late spring and autumn) when the soil surface is sealed. In such conditions, most rainfall input is converted into runoff, regardless of its intensity. Results from artificial rainfall experiments, conducted 3 and 7 years after seeding, confirm the low infiltration capacity of overburden when sealed. The hydrological response shows great seasonal variability on the overburden slope in accordance with soil surface changes over the year. Rainfall volume and intensities explain runoff at the inter-rill scale on the topsoil slope, where rainfall experiments demonstrated a typical Hortonian infiltration curve. However, no correlation was found at the microcatchment level, probably because of the loss of functionality of the only rill as ecological succession proceeded. The runoff generation mechanism on the topsoil slope is more homogeneous throughout the year. The dense rill networks of the overburden slope guarantee very effective runoff drainage, regardless of rainfall magnitude. Runoff generation and routing on topsoil slopes are controlled by grass cover and soil moisture content, whereas on overburden slopes rill network density and soil moisture content are the main controlling factors.
Durán Barroso, Pablo
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) ...
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.
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)
Ferreira, C. S. S.; Soares, D.; Soares, A. J. D.; Coelho, C. O. A.; Steenhuis, T. S.; Keizer, J. J.; Walsh, R. P. D.
Forests play an important role in the water cycle, particularly through their influence on infiltration and evapotranspiration processes. Removing forest for urban growth will affect the hydrological cycle, but to what degree is not known. To improve the knowledge about the role of forest areas in the catchment surface runoff, a total of nine runoff plots (16m2) was installed in the three predominant woodland types found in the small Ribeira dos Covões catchment (620ha), located in a rapid urbanizing area in central Portugal. The three representative study sites comprised: (i) a dense eucalyptus stand on a sandy-loam soil overlying sandstone; (ii) a open eucalyptus stand dominated by dense shrub vegetation, also on a sandy-loam soil overlying sandstone; (iii) a Mediterranean oak stand on a loamy soil overlying limestone. The three plots at each site were bounded by metal sheets and their outlets were connected to a modified Gerlach through for sediments retention and, subsequently, a tipping-bucket device and a tank for recording and collecting the runoff. The overland flow generated by the plots was monitored for almost one year. In addition, soil moisture content was measured automatically at 0-2, 5-10 and 15-20cm soil depth using 5 sensors per plot. Furthermore, soil water repellency was repeatedly measured on the field, through ethanol percentage method. In the dense eucalyptus forest the soil is hydrophobic during most of the year, just vanished after severe rainfall events. This reflects on low soil moisture content that reached 37% during wet periods. In this area, with an average slope of 20°±5°, the runoff coefficient ranged between 0.0% (for a 3mm rainfall event) and 2.2% (for a 23mm rainfall during hydrophobic conditions). In general, the runoff was higher when the soil was extremely repellent, but it also increased with soil moisture rise when the repellence was absent (reaching 0.6%). In the open eucalyptus forest, hydrophobicity is also presented
Vannametee, E.; Karssenberg, D.; Hendriks, M. R.; de Jong, S. M.; Bierkens, M. F. P.
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
Hailegeorgis, Teklu T.; Alfredsen, Knut
useful for better computation of runoff generated from different land cover, for assessments of stormwater management techniques (e.g. the Low Impact Development or LID) and the impacts of land cover and climate change. There are some simplifications or limitations such as the runoff routing does not involve detailed sewer hydraulics, effects of leakages from water supply systems and faulty/illegal connections from sanitary sewer are not considered, the model cannot identify actual locations of the interactions between the subsurface runoff and sewer pipes and lacks parsimony.
Tyler Jon Smith; Lucy Amanda Marshall
Model selection is an extremely important aspect of many hydrologic modeling studies because of the complexity, variability, and uncertainty that surrounds the current understanding of watershed-scale systems. However, development and implementation of a complete precipitation-runoff modeling framework, from model selection to calibration and uncertainty analysis, are...
Brandt, M.; Bergström, S.
Conceptual runoff models have become standard tools for operational hydrological forecasting in Scandinavia. These models are normally based on observations from the national climatological networks, but in mountainous areas the stations are few and sometimes not representative. Due to the great economic importance of good hydrological forecasts for the hydro-power industry attempts have been made to improve the model simulations by support from field observations of the snowpack. The snowpack has been mapped by several methods; airborne gamma-spectrometry, airborne georadars, satellites and by conventional snow courses. The studies cover more than ten years of work in Sweden. The conclusion is that field observations of the snow cover have a potential for improvement of the forecasts of inflow to the reservoirs in the mountainous part of the country, where the climatological data coverages is poor. This is pronounced during years with unusual snow distribution. The potential for model improvement is smaller in the climatologically more homogeneous forested lowlands, where the climatological network is denser. The costs of introduction of airborne observations into the modelling procedure are high and can only be justified in areas of great hydropower potential. (author)
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.
In hydrology a basic task is the estimation of design discharges and runoff changes in ungauged catchments. However, traditional empirical rules of thumb as well as regionalization of measured discharges are subject to uncertainty. It seems that precipitation-runoff modelling is the only comprehensible way to predict discharge alterations due to changes in ungauged basins, even though the results are perhaps not less uncertain. In order to minimize this uncertainty this work presents a new methodology for discharge estimation in ungauged basins by introducing runoff coefficients derived from field assessment, by a new adapted precipitation-runoff model (ZEMOKOST) and routines for a plausibility check. Subsequently ten gauged Austrian catchments were used as hypothetical ungauged catchments for application and verification of this method. Except for special questions in karst- and glacier-hydrology the procedure showed satisfying results. (author) [de
Zhang Wei; Ye Youbin; Tong Yindong; Ou Langbo; Hu Dan; Wang Xuejun
Understanding of the magnitude of urban runoff toxicity to aquatic organisms is important for effective management of runoff quality. In this paper, the aquatic toxicity of polycyclic aromatic hydrocarbons (PAHs) in urban road runoff was evaluated through a damage assessment model. Mortality probability of the organisms representative in aquatic environment was calculated using the monitored PAHs concentration in road runoff. The result showed that the toxicity of runoff in spring was higher than those in summer. Analysis of the time-dependent toxicity of series of runoff water samples illustrated that the toxicity of runoff water in the final phase of a runoff event may be as high as those in the initial phase. Therefore, the storm runoff treatment systems or strategies designed for capture and treatment of the initial portion of runoff may be inappropriate for control of runoff toxicity. - Research highlights: → Toxicity resulting from realistic exposure patterns of urban runoff is evaluated. → Toxicity of runoff water in the final phase is as high as the initial phase. → Treatment of the initial runoff portion is inappropriate to abate runoff toxicity. - Toxicity to aquatic organisms after sequential pulsed exposure to PAHs in urban road runoff is evaluated.
Full Text Available River runoff is not only a crucial part of the global water cycle, but it is also an important source for hydropower and an essential element of water balance. This study presents a system-theory-based model for river runoff forecasting taking the Hailiutu River as a case study. The forecasting model, designed for the Hailiutu watershed, was calibrated and verified by long-term precipitation observation data and groundwater exploitation data from the study area. Additionally, frequency analysis, taken as an optimization technique, was applied to improve prediction accuracy. Following model optimization, the overall relative prediction errors are below 10%. The system-theory-based prediction model is applicable to river runoff forecasting, and following optimization by frequency analysis, the prediction error is acceptable.
For surface runoff estimation in the Soil and Water Assessment Tool (SWAT) model, the curve number (CN) procedure is commonly adopted to calculate surface runoff by utilizing antecedent soil moisture condition (SCSI) in field. In the recent version of SWAT (SWAT2005), an alternative approach is ava...
Nourani, Vahid; Komasi, Mehdi
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.
Mallard, J. M.; McGlynn, B. L.; Richter, D. D., Jr.
Our understanding of runoff generation in regions characterized by deep, highly weathered soils is incomplete, despite the prevalence occupation of these landscapes worldwide. To address this, we instrumented a first-order watershed in the Piedmont of South Carolina, USA, a region that extends east of the Appalachians from Maryland to Alabama, and home to some of the most rapid population growth in the country. Although regionally the relief is modest, the landscape is often highly dissected and local slopes can be steep and highly varied. The typical soils of the region are kaolinite dominated ultisols, with hydrologic properties controlled by argillic Bt horizons, often with >50% clay-size fraction. The humid subtropical climate creates relatively consistent precipitation intra-annually and seasonally variable energy availability. Consequently, the mixed deciduous and coniferous tree cover creates a strong evapotranspiration-mediated hydrologic dynamic. While moist soils and extended stream networks are typical from late fall through spring, relatively dry soils and contracting stream networks emerge in the summer and early fall. Here, we seek to elucidate the relative influence of the vertical soil and spatial terrain structure of this region on watershed hillslope hydrology and subsequent runoff generation. We installed a network of nested, shallow groundwater wells and soil water content probes within an ephemeral to first-order watershed to continuously measure soil and groundwater dynamics across soil horizons and landscape position. We also recorded local precipitation and discharge from this watershed. Most landscape positions exhibited minimal water table response to precipitation throughout dry summer periods, with infrequently observed responses rarely coincident with streamflow generation. In contrast, during the wetter late fall through early spring period, streamflow was driven by the interaction between transient perched water tables and
This paper analyzed the impacts of foret stand volume and precipitation on annual erosion modulus, mean sediment, maximum sediment, mean runoff, maximum runoff, minimum runoff, mean water level, maximum water level and minimum water level in Tianshui watershed, and also analyzed the effect of the variation of forest stand volume on monthly mean runoff, minimum runoff and mean water level. The dynamic models of grey system GM(1, N) were constructed to simulate the changes of these hydrological elements. The dynamic GM models on the impact of stand volumes of different forest types(Chinese fir, masson pine and broad-leaved forests) with different age classes(young, middle-aged, mature and over-mature) and that of precipitation on the hydrological elements were also constructed, and their changes with time were analyzed.
McCabe, G.J.; Wolock, D.M.
A water-balance model is used to simulate time series of water-year runoff for 4 km ?? 4 km grid cells for the conterminous United States during the 1900-2008 period. Model outputs are used to examine the separate effects of precipitation and temperature on runoff variability. Overall, water-year runoff has increased in the conterminous United States and precipitation has accounted for almost all of the variability in water-year runoff during the past century. In contrast, temperature effects on runoff have been small for most locations in the United States even during periods when temperatures for most of the United States increased significantly. Copyright 2011 by the American Geophysical Union.
Ross, C Wade; Prihodko, Lara; Anchang, Julius; Kumar, Sanath; Ji, Wenjie; Hanan, Niall P
Hydrologic soil groups (HSGs) are a fundamental component of the USDA curve-number (CN) method for estimation of rainfall runoff; yet these data are not readily available in a format or spatial-resolution suitable for regional- and global-scale modeling applications. We developed a globally consistent, gridded dataset defining HSGs from soil texture, bedrock depth, and groundwater. The resulting data product-HYSOGs250m-represents runoff potential at 250 m spatial resolution. Our analysis indicates that the global distribution of soil is dominated by moderately high runoff potential, followed by moderately low, high, and low runoff potential. Low runoff potential, sandy soils are found primarily in parts of the Sahara and Arabian Deserts. High runoff potential soils occur predominantly within tropical and sub-tropical regions. No clear pattern could be discerned for moderately low runoff potential soils, as they occur in arid and humid environments and at both high and low elevations. Potential applications of this data include CN-based runoff modeling, flood risk assessment, and as a covariate for biogeographical analysis of vegetation distributions.
Tanaka, T.; Yasuhara, M.; Sakai, H.; Marui, A.
The study discusses storm runoff processes and the mechanism of its generation in relation to dynamic responses of subsurface water in a small forested drainage basin located in the western suburbs of Tokyo, Japan. Intensive field observations were carried out for the period 1980-1983. In the drainage basin overland flow occurred from restricted areas on the valley floor. No significant overland flow was produced on the steep hillside slopes even during a heavy storm event. The maximum extent of the saturated area occupied only 1-4% of the total basin area. The main source of storm runoff was groundwater flow. More than 90% of the total discharge was due to groundwater flow and the surface flow component contributed less than 10%. The rapid and large amounts of groundwater discharge during a storm event could not be explained solely by the traditional concept of Darcian matrix flow. These phenomena were mainly attributed to rapid flow such as pipe flow which has velocities about as high as those of surface flows. The pulsating flow phenomenon was observed as a characteristic of pipe flow.
van Wesenbeeck, I J; Peacock, A L; Havens, P L
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.
Borup, Morten; Grum, M.; Mikkelsen, Peter Steen
In many urban runoff systems infiltrating water contributes with a substantial part of the total inflow and therefore most urban runoff modelling packages include hydrological models for simulating the infiltrating inflow. This paper presents a method for deterministic updating of the hydrological...... improvements for regular simulations as well as up to 10 hour forecasts. The updating method reduces the impact of non-representative precipitation estimates as well as model structural errors and leads to better overall modelling results....
Vischel, Théo; Lebel, Thierry
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...
Oeverland, H.; Kleeberg, H.B.
The movement of water in a given region is determined by a number of regional factors, e.g. land use and topography. However, the available precipitation-runoff models take little account of this regional information. Geological information systems, on the other hand, are instruments for efficient management, presentation and evaluation of local information, so the best approach would be a combination of the two types of models. The requirements to be met by such a system are listed; they result from the processes to be modelled (continuous runoff, high-water runoff, mass transfer) but also from the available data and their acquisition and processing. Ten of the best-known precipitation-runoff models are presented and evaluated on the basis of the requirements listed. The basic concept of an integrated model is outlined, and additional modulus required for modelling are defined. (orig./BBR) [de
Ouyang, Wei; Guo, Bobo; Hao, Fanghua; Huang, Haobo; Li, Junqi; Gong, Yongwei
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.
Soulsby, C.; Rodgers, P.; Malcolm, I. A.; Dunn, S.
Geochemical and isotopic tracers have been shown to have widespread utility in catch- ment hydrology in terms of identifying hydrological source areas and characterising residence time distributions. In many cases application of tracer techniques has pro- vided insights into catchment functioning that could not be obtained from hydromet- ric and/or modelling studies alone. This paper will show how the use of tracers has contributed to an evolving perceptual model of hydrological pathways and runoff gen- eration processes in catchments in the Scottish highlands. In particular the paper will focus on the different insights that are gained at three different scales of analysis; (a) nested sub-catchments within a mesoscale (ca. 200 square kilometers) experimen- tal catchment; (b) hillslope-riparian interactions and (c) stream bed fluxes. Nested hydrometric and hydrochemical monitoring within the mesoscale Feugh catchment identified three main hydrological response units: (i) plateau peatlands which gener- ated saturation overland flow in the catchment headwaters, (ii) steep valley hillslopes which drain from the plateaux into (iii) alluvial and drift aquifers in the valley bottoms. End Member Mixing Analysis (EMMA) in 8 nested sub-catchments indicated that that stream water tracer concentrations can be modelled in terms of 2 dominant runoff pro- cesses; overland flow from the peat and groundwater from the drift aquifers. Ground- water contributions generally increased with catchment size, though this was moder- ated by the characteristics of individual sub-basins, with drift cover being particularly important. Hillslope riparian interactions were also examined using tracers, hydromet- ric data and a semi-distributed hydrological model. This revealed that in the glaciated, drift covered terrain of the Scottish highlands, extensive valley bottom aquifers effec- tively de-couple hillslope waters from the river channel. Thus, riparian groundwater appears to significantly
Hong, Mei; Wang, Dong; Wang, Yuankun; Zeng, Xiankui; Ge, Shanshan; Yan, Hengqian; Singh, Vijay P.
In recent years, the phase-space reconstruction method has usually been used for mid- and long-term runoff predictions. However, the traditional phase-space reconstruction method is still needs to be improved. Using the genetic algorithm to improve the phase-space reconstruction method, a new nonlinear model of monthly runoff is constructed. The new model does not rely heavily on embedding dimensions. Recognizing that the rainfall–runoff process is complex, affected by a number of factors, more variables (e.g. temperature and rainfall) are incorporated in the model. In order to detect the possible presence of chaos in the runoff dynamics, chaotic characteristics of the model are also analyzed, which shows the model can represent the nonlinear and chaotic characteristics of the runoff. The model is tested for its forecasting performance in four types of experiments using data from six hydrological stations on the Yellow River and the Yangtze River. Results show that the medium-and long-term runoff is satisfactorily forecasted at the hydrological stations. Not only is the forecasting trend accurate, but also the mean absolute percentage error is no more than 15%. Moreover, the forecast results of wet years and dry years are both good, which means that the improved model can overcome the traditional ‘‘wet years and dry years predictability barrier,’’ to some extent. The model forecasts for different regions are all good, showing the universality of the approach. Compared with selected conceptual and empirical methods, the model exhibits greater reliability and stability in the long-term runoff prediction. Our study provides a new thinking for research on the association between the monthly runoff and other hydrological factors, and also provides a new method for the prediction of the monthly runoff. - Highlights: • The improved phase-space reconstruction model of monthly runoff is established. • Two variables (temperature and rainfall) are incorporated
Hong, Mei [Research Center of Ocean Environment Numerical Simulation, Institute of Meteorology and oceanography, PLA University of Science and Technology, Nanjing (China); Wang, Dong, E-mail: email@example.com [Key Laboratory of Surficial Geochemistry, Ministry of Education, Department of Hydrosciences, School of Earth Sciences and Engineering, Collaborative Innovation Center of South China Sea Studies, State Key Laboratory of Pollution Control and Resource Reuse, Nanjing University, Nanjing 210093 (China); Wang, Yuankun; Zeng, Xiankui [Key Laboratory of Surficial Geochemistry, Ministry of Education, Department of Hydrosciences, School of Earth Sciences and Engineering, Collaborative Innovation Center of South China Sea Studies, State Key Laboratory of Pollution Control and Resource Reuse, Nanjing University, Nanjing 210093 (China); Ge, Shanshan; Yan, Hengqian [Research Center of Ocean Environment Numerical Simulation, Institute of Meteorology and oceanography, PLA University of Science and Technology, Nanjing (China); Singh, Vijay P. [Department of Biological and Agricultural Engineering Zachry Department of Civil Engineering, Texas A & M University, College Station, TX 77843 (United States)
In recent years, the phase-space reconstruction method has usually been used for mid- and long-term runoff predictions. However, the traditional phase-space reconstruction method is still needs to be improved. Using the genetic algorithm to improve the phase-space reconstruction method, a new nonlinear model of monthly runoff is constructed. The new model does not rely heavily on embedding dimensions. Recognizing that the rainfall–runoff process is complex, affected by a number of factors, more variables (e.g. temperature and rainfall) are incorporated in the model. In order to detect the possible presence of chaos in the runoff dynamics, chaotic characteristics of the model are also analyzed, which shows the model can represent the nonlinear and chaotic characteristics of the runoff. The model is tested for its forecasting performance in four types of experiments using data from six hydrological stations on the Yellow River and the Yangtze River. Results show that the medium-and long-term runoff is satisfactorily forecasted at the hydrological stations. Not only is the forecasting trend accurate, but also the mean absolute percentage error is no more than 15%. Moreover, the forecast results of wet years and dry years are both good, which means that the improved model can overcome the traditional ‘‘wet years and dry years predictability barrier,’’ to some extent. The model forecasts for different regions are all good, showing the universality of the approach. Compared with selected conceptual and empirical methods, the model exhibits greater reliability and stability in the long-term runoff prediction. Our study provides a new thinking for research on the association between the monthly runoff and other hydrological factors, and also provides a new method for the prediction of the monthly runoff. - Highlights: • The improved phase-space reconstruction model of monthly runoff is established. • Two variables (temperature and rainfall) are incorporated
Pomeroy, J. W.; Carey, S. K.; Granger, R. J.; Hedstrom, N. R.; Janowicz, R.; Pietroniro, A.; Quinton, W. L.
The supply of water to large northern catchments such as the Mackenzie and Yukon Rivers is dominated by snowmelt runoff from first order mountain catchments. In order to understand the timing, peak and duration of the snowmelt freshet at larger scale it is important to appreciate the spatial and temporal variability of snowmelt and runoff processes at the source. For this reason a comprehensive hydrology study of a Yukon River headwaters catchment, Wolf Creek Research Basin, near Whitehorse, has focussed on the spatial variability of snow ablation and snowmelt runoff generation and the consequences for the water balance in a mountain tundra zone. In northern mountain tundra, surface energetics vary with receipt of solar radiation, shrub vegetation cover and initial snow accumulation. Therefore the timing of snowmelt is controlled by aspect, in that south facing slopes become snow-free 4-5 weeks before the north facing. Runoff generation differs widely between the slopes; there is normally no spring runoff generated from the south facing slope as all meltwater evaporates or infiltrates. On the north facing slope, snowmelt provides substantial runoff to hillside macropores which rapidly route water to the stream channel. Macropore distribution is associated with organic terrain and discontinuous permafrost, which in turn result from the summer surface energetics. Therefore the influence of small-scale snow redistribution and energetics as controlled by topography must be accounted for when calculating contributing areas to larger scale catchments, and estimating the effectiveness of snowfall in generating streamflow. This concept is quite distinct from the drainage controlled contributing area that has been found useful in temperate-zone hydrology.
Votrubová, J.; Dohnal, M.; Vogel, T.; Šanda, M.; Tesař, Miroslav
Roč. 65, č. 2 (2017), s. 114-122 ISSN 0042-790X Grant - others:Grantová agentura České republiky (GA ČR)(CZ) GC14-15201J Institutional support: RVO:67985874 Keywords : O isotope * headwater catchment runoff * subsurface runoff * tracer * rainfall-runoff episodes Subject RIV: DA - Hydrology ; Limnology OBOR OECD: Hydrology Impact factor: 1.654, year: 2016
This study is aimed to investigate the possibility of three lumped hydrological models to predict daily runoff of large-scale Arctic basins for the modern period (1979-2014) in the case of substantial data scarcity. All models were driven only by meteorological forcing reanalysis dataset without any additional information about landscape, soil or vegetation cover properties of studied basins. We found limitations of model parameters calibration in ungauged basins using global optimization alg...
Davidsen, Steffen; Löwe, Roland; Høegh Ravn, Nanna
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....
Steele, Caitriana; Dialesandro, John; James, Darren; Elias, Emile; Rango, Albert; Bleiweiss, Max
Snow-covered area (SCA) is a key variable in the Snowmelt-Runoff Model (SRM) and in other models for simulating discharge from snowmelt. Landsat Thematic Mapper (TM), Enhanced Thematic Mapper (ETM +) or Operational Land Imager (OLI) provide remotely sensed data at an appropriate spatial resolution for mapping SCA in small headwater basins, but the temporal resolution of the data is low and may not always provide sufficient cloud-free dates. The coarser spatial resolution Moderate Resolution Imaging Spectroradiometer (MODIS) offers better temporal resolution and in cloudy years, MODIS data offer the best alternative for mapping snow cover when finer spatial resolution data are unavailable. However, MODIS' coarse spatial resolution (500 m) can obscure fine spatial patterning in snow cover and some MODIS products are not sensitive to end-of-season snow cover. In this study, we aimed to test MODIS snow products for use in simulating snowmelt runoff from smaller headwater basins by a) comparing maps of TM and MODIS-based SCA and b) determining how SRM streamflow simulations are changed by the different estimates of seasonal snow depletion. We compared gridded MODIS snow products (Collection 5 MOD10A1 fractional and binary SCA; SCA derived from Collection 6 MOD10A1 Normalised Difference Snow Index (NDSI) Snow Cover), and the MODIS Snow Covered-Area and Grain size retrieval (MODSCAG) canopy-corrected fractional SCA (SCAMG), with reference SCA maps (SCAREF) generated from binary classification of TM imagery. SCAMG showed strong agreement with SCAREF; excluding true negatives (where both methods agreed no snow was present) the median percent difference between SCAREF and SCAMG ranged between -2.4% and 4.7%. We simulated runoff for each of the four study years using SRM populated with and calibrated for snow depletion curves derived from SCAREF. We then substituted in each of the MODIS-derived depletion curves. With efficiency coefficients ranging between 0.73 and 0.93, SRM
This study used Soil Water Assessment Tool (SWAT) to simulate temporal-spatial distribution of surface water runoff (river flow), sediment and nutrient generation in Sondu watershed, and to identify soil erosion and nutrient source hot spots. Annual sediment generation to the lake is 80,000 t/yr composed of mainly silt while ...
Full Text Available To understand changes in global mean and extreme streamflow volumes over recent decades, we statistically analyzed runoff and streamflow simulated by the WBM-plus hydrological model using either observational-based meteorological inputs from WATCH Forcing Data (WFD, or bias-corrected inputs from five global climate models (GCMs provided by the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP. Results show that the bias-corrected GCM inputs yield very good agreement with the observation-based inputs in average magnitude of runoff and streamflow. On global average, the observation-based simulated mean runoff and streamflow both decreased about 1.3% from 1971 to 2001. However, GCM-based simulations yield increasing trends over that period, with an inter-model global average of 1% for mean runoff and 0.9% for mean streamflow. In the GCM-based simulations, relative changes in extreme runoff and extreme streamflow (annual maximum daily values and annual-maximum seven-day streamflow are slightly greater than those of mean runoff and streamflow, in terms of global and continental averages. Observation-based simulations show increasing trend in mean runoff and streamflow for about one-half of the land areas and decreasing trend for the other half. However, mean and extreme runoff and streamflow based on the GCMs show increasing trend for approximately two-thirds of the global land area and decreasing trend for the other one-third. Further work is needed to understand why GCM simulations appear to indicate trends in streamflow that are more positive than those suggested by climate observations, even where, as in ISI-MIP, bias correction has been applied so that their streamflow climatology is realistic.
Wu, Xiaoling; Xiang, Xiaohua; Qiu, Chao; Li, Li
In cold regions, precipitation, air temperature and snow cover significantly influence soil water, heat transfer, the freezing-thawing processes of the active soil layer, and runoff generation. Hydrological regimes of the world's major rivers in cold regions have changed remarkably since the 1960s, but the mechanisms underlying the changes have not yet been fully understood. Using the basic physical processes for water and heat balances and transfers in snow covered soil, a water-heat coupling model for snow cover and its underlying soil layers was established. We found that freezing-thawing processes can affect the thickness of the active layer, storage capacity for liquid water, and subsequent surface runoffs. Based on calculations of thawing-freezing processes, we investigated hydrological processes at Qumalai. The results show that the water-heat coupling model can be used in this region to provide an understanding of the local movement of hydrological regimes.
Yang, Ting; Wang, Quanjiu; Wu, Laosheng; Zhao, Guangxu; Liu, Yanli; Zhang, Pengyu
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.
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.
Borup, Morten; Mikkelsen, Peter Steen; Grum, Morten; Madsen, Henrik
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 ...
Full Text Available The snowmelt runoff model (SRM has been widely used in simulation and forecast of streamflow in snow-dominated mountainous basins around the world. This paper presents an overall review of worldwide applications of SRM in mountainous watersheds, particularly in data-sparse watersheds of northwestern China. Issues related to proper selection of input climate variables and parameters, and determination of the snow cover area (SCA using remote sensing data in snowmelt runoff modeling are discussed through extensive review of literature. Preliminary applications of SRM in northwestern China have shown that the model accuracies are relatively acceptable although most of the watersheds lack measured hydro-meteorological data. Future research could explore the feasibility of modeling snowmelt runoff in data-sparse mountainous watersheds in northwestern China by utilizing snow and glacier cover remote sensing data, geographic information system (GIS tools, field measurements, and innovative ways of model parameterization.
Verbree, E.; de Vries, M.; Gorte, B.; Oude Elberink, S.; Karimlou, G.
Water run-off modelling applied within urban areas requires an appropriate detailed surface model represented by a raster height grid. Accurate simulations at this scale level have to take into account small but important water barriers and flow channels given by the large-scale map definitions of buildings, street infrastructure, and other terrain objects. Thus, these 3D features have to be rasterised such that each cell represents the height of the object class as good as possible given the cell size limitations. Small grid cells will result in realistic run-off modelling but with unacceptable computation times; larger grid cells with averaged height values will result in less realistic run-off modelling but fast computation times. This paper introduces a height grid generalisation approach in which the surface characteristics that most influence the water run-off flow are preserved. The first step is to create a detailed surface model (1:1.000), combining high-density laser data with a detailed topographic base map. The topographic map objects are triangulated to a set of TIN-objects by taking into account the semantics of the different map object classes. These TIN objects are then rasterised to two grids with a 0.5m cell-spacing: one grid for the object class labels and the other for the TIN-interpolated height values. The next step is to generalise both raster grids to a lower resolution using a procedure that considers the class label of each cell and that of its neighbours. The results of this approach are tested and validated by water run-off model runs for different cellspaced height grids at a pilot area in Amersfoort (the Netherlands). Two national datasets were used in this study: the large scale Topographic Base map (BGT, map scale 1:1.000), and the National height model of the Netherlands AHN2 (10 points per square meter on average). Comparison between the original AHN2 height grid and the semantically enriched and then generalised height grids shows
Full Text Available Given the substantial impacts that are expected due to climate change, it is crucial that accurate rainfall–runoff results are provided for various decision-making purposes. However, these modeling results often generate uncertainty or bias due to the imperfect character of individual models. In this paper, a genetic algorithm together with a Bayesian model averaging method are employed to provide a multi-model ensemble (MME and combined runoff prediction under climate change scenarios produced from eight rainfall–runoff models for the Yellow River Basin. The results show that the multi-model ensemble method, especially the genetic algorithm method, can produce more reliable predictions than the other considered rainfall–runoff models. These results show that it is possible to reduce the uncertainty and thus improve the accuracy for future projections using different models because an MME approach evens out the bias involved in the individual model. For the study area, the final combined predictions reveal that less runoff is expected under most climatic scenarios, which will threaten water security of the basin.
Massari, Christian; Tarpanelli, Angelica; Brocca, Luca; Moramarco, Tommaso
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
Gallegos, A.F.; Wenzel, W.J.
The environmental risk simulation model BIOTRAN was interfaced with a series of new subroutines (RUNOFF, GEOFLX, EROSON, and AQUIFER) to predict the movement of nuclides, elements, and pertinent chemical compounds in association with sediments through lateral and channel flow of runoff water. In addition, the movement of water into and out of segmented portions of runoff channels was modeled to simulate the dynamics of moisture flow through specified aquifers within the watershed. The BIOTRAN soil water flux subroutine, WATFLX, was modified to interface the relationships found in the SPUR model for runoff and sediment transport into channels with the particle sorting relationships to predict radionuclide enrichment and movement in watersheds. The new subroutines were applied specifically to Mortandad Canyon within Los Alamos National Laboratory by simultaneous simulation of eight surface vegetational subdivisions and associated channel and aquifer segments of this watershed. This report focuses on descriptions of the construction and rationale for the new subroutines and on discussing both input characteristics and output relationships to known runoff events from Mortandad Canyon. Limitations of the simplified input on model behavior are also discussed. Uranium-238 was selected as the nuclide for demonstration of the model because it could be assumed to be homogeneously distributed over the watershed surface. 22 refs., 18 figs., 9 tabs.
Applying a regional hydrology model to evaluate locations for groundwater replenishment with hillslope runoff under different climate and land use scenarios in an agricultural basin, central coastal California
Beganskas, S.; Young, K. S.; Fisher, A. T.; Lozano, S.; Harmon, R. E.; Teo, E. K.
We are applying a regional hydrology model, Precipitation-Runoff Modeling System (PRMS), to evaluate locations for groundwater replenishment with hillslope runoff in the Pajaro Valley Groundwater Basin (PVGB), central coastal California. Stormwater managed aquifer recharge (MAR) projects collect hillslope runoff before it reaches a stream and infiltrate it into underlying aquifers, improving groundwater supply. The PVGB is a developed agricultural basin where groundwater provides >85% of water for irrigation and municipal needs; stormwater-MAR projects are being considered to address chronic overdraft and saltwater intrusion. We are applying PRMS to assess on a subwatershed scale (10-100 ha; 25-250 acres) where adequate runoff is generated to supply stormwater-MAR in coincidence with suitable conditions for infiltration and recharge. Data from active stormwater-MAR projects in the PVGB provide ground truth for model results. We are also examining how basinwide hydrology responds to changing land use and climate, and the potential implications for future water management. To prepare extensive input files for PRMS models, we developed ArcGIS and Python tools to delineate a topographic model grid and incorporate high-resolution soil, vegetation, and other physical data into each grid region; we also developed tools to analyze and visualize model output. Using historic climate records, we generated dry, normal, and wet climate scenarios, defined as having approximately 25th, 50th, and 75th percentile annual rainfall, respectively. We also generated multiple land use scenarios by replacing developed areas with native vegetation. Preliminary results indicate that many parts of the PVGB generate significant runoff and have suitable infiltration/recharge conditions. Reducing basinwide overdraft by 10% would require collecting less than 5% of total hillslope runoff, even during the dry scenario; this demonstrates that stormwater-MAR could be an effective water management
Zhang, Xuyang; Luo, Yuzhou; Goh, Kean S
Pesticides move to surface water via various pathways including surface runoff, spray drift and subsurface flow. Little is known about the relative contributions of surface runoff and spray drift in agricultural watersheds. This study develops a modeling framework to address the contribution of spray drift to the total loadings of pesticides in receiving water bodies. The modeling framework consists of a GIS module for identifying drift potential, the AgDRIFT model for simulating spray drift, and the Soil and Water Assessment Tool (SWAT) for simulating various hydrological and landscape processes including surface runoff and transport of pesticides. The modeling framework was applied on the Orestimba Creek Watershed, California. Monitoring data collected from daily samples were used for model evaluation. Pesticide mass deposition on the Orestimba Creek ranged from 0.08 to 6.09% of applied mass. Monitoring data suggests that surface runoff was the major pathway for pesticide entering water bodies, accounting for 76% of the annual loading; the rest 24% from spray drift. The results from the modeling framework showed 81 and 19%, respectively, for runoff and spray drift. Spray drift contributed over half of the mass loading during summer months. The slightly lower spray drift contribution as predicted by the modeling framework was mainly due to SWAT's under-prediction of pesticide mass loading during summer and over-prediction of the loading during winter. Although model simulations were associated with various sources of uncertainties, the overall performance of the modeling framework was satisfactory as evaluated by multiple statistics: for simulation of daily flow, the Nash-Sutcliffe Efficiency Coefficient (NSE) ranged from 0.61 to 0.74 and the percent bias (PBIAS) runoff in receiving waters and the design of management practices for mitigating pesticide exposure within a watershed. Published by Elsevier Ltd.
Comoretto, Laetitia; Arfib, Bruno; Talva, Romain; Chauvelon, Philippe; Pichaud, Marc; Chiron, Serge; Hoehener, Patrick
A field study on the runoff of pesticides was conducted during the cultivation period in 2004 on a hydraulically isolated rice farm of 120 ha surface with one central water outlet. Four pesticides were studied: Alphamethrin, MCPA, Oxadiazon, and Pretilachlor. Alphamethrin concentrations in runoff never exceeded 0.001 μg L -1 . The three other pesticides were found in concentrations between 5.2 and 28.2 μg L -1 in the runoff water shortly after the application and decreased thereafter. The data for MCPA compared reasonably well with predictions by an analytical runoff model, accounting for volatilization, degradation, leaching to groundwater, and sorption to soil. The runoff model estimated that runoff accounted for as much as 18-42% of mass loss for MCPA. Less runoff is observed and predicted for Oxadiazon and Pretilachlor. It was concluded that runoff from rice paddies carries important loads of dissolved pesticides to the wetlands in the Ile de Camargue, and that the model can be used to predict this runoff. - Runoff of dissolved pesticides was measured on a rice farm in the Camargue (France) and modeled with an analytical model
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 ...
Zhang, Jun; Han, Dawei
Runoff prediction in ungauged catchments has been one of the major challenges in the past decades. However, due to the tremendous heterogeneity of the catchments, obstacles exist in deducing model parameters for ungauged catchments from gauged ones. We propose a novel approach to predict ungauged runoff with Catchment Morphing (CM) using a fully distributed model. CM is defined as by changing the catchment characteristics (area and slope here) from the baseline model built with a gauged catchment to model the ungauged ones. As a proof of concept, a case study on seven catchments in the UK has been used to demonstrate the proposed scheme. Comparing the predicted with measured runoff, the Nash-Sutcliffe efficiency (NSE) varies from 0.03 to 0.69 in six catchments. Moreover, NSEs are significantly improved (up to 0.81) when considering the discrepancy of percentage runoff between the target and baseline catchments. A distinct advantage has been experienced by comparing the CM with a traditional method for ungauged catchments. The advantages are: (a) less demand of the similarity between the baseline catchment and the ungauged catchment, (b) less demand of available data, and (c) potentially widely applicable in varied catchments. This study demonstrates the feasibility of the proposed scheme as a potentially powerful alternative to the conventional methods in runoff predictions of ungauged catchments. Clearly, more work beyond this pilot study is needed to explore and develop this new approach further to maturity by the hydrological community.
Forecasting the runoff over longer periods, such as months and years, is one of the important tasks for hydrologists and water resource managers to maximize the potential of the limited water. However, due to the nonlinear and nonstationary characteristic of the natural runoff, it is hard to forecast the middle and long-term runoff with a satisfactory accuracy. It has been proven that the forecast performance can be improved by using signal decomposition techniques to product more cleaner signals as model inputs. In this study, a new conjunction model (EEMD-neuro-fuzzy) with adaptive ability is proposed. The ensemble empirical model decomposition (EEMD) is used to decompose the runoff time series into several components, which are with different frequencies and more cleaner than the original time series. Then the neuro-fuzzy model is developed for each component. The final forecast results can be obtained by summing the outputs of all neuro-fuzzy models. Unlike the conventional forecast model, the decomposition and forecast models in this study are adjusted adaptively as long as new runoff information is added. The proposed models are applied to forecast the monthly runoff of Yichang station, located in Yangtze River of China. The results show that the performance of adaptive forecast model we proposed outperforms than the conventional forecast model, the Nash-Sutcliffe efficiency coefficient can reach to 0.9392. Due to its ability to process the nonstationary data, the forecast accuracy, especially in flood season, is improved significantly.
Full Text Available A fully integrated Atmospheric-Ocean-Hydrology Model (BALTIMOS = Baltic Integrated Model System has been developed using existing model components. Experiment and model design has been adapted to the Baltic basin with a catchment area of approximately 1 750 000 km2. A comprehensive model validation has been completed using large meteorological and hydrological measurement database. Comparing the calculated runoff from the integrated and non-integrated model system with measurements for three different representative subbasins and the entire Baltic basin, the effect of the integrated model is described. The results display a good agreement between measured and calculated runoff. The effect of the integrated model is rather negligible looking at computed mean values: There is no significant difference between mean monthly runoff of the integrated and non-integrated model during the year with the exception of spring. There is a delay of one month with regard to peak runoff for the non-integrated model in spring caused by different interactive processes during the melting period.
Vesuviano, Gianni; Sonnenwald, Fred; Stovin, Virginia
Green roofs have been adopted in urban drainage systems to control the total quantity and volumetric flow rate of runoff. Modern green roof designs are multi-layered, their main components being vegetation, substrate and, in almost all cases, a separate drainage layer. Most current hydrological models of green roofs combine the modelling of the separate layers into a single process; these models have limited predictive capability for roofs not sharing the same design. An adaptable, generic, two-stage model for a system consisting of a granular substrate over a hard plastic 'egg box'-style drainage layer and fibrous protection mat is presented. The substrate and drainage layer/protection mat are modelled separately by previously verified sub-models. Controlled storm events are applied to a green roof system in a rainfall simulator. The time-series modelled runoff is compared to the monitored runoff for each storm event. The modelled runoff profiles are accurate (mean Rt(2) = 0.971), but further characterization of the substrate component is required for the model to be generically applicable to other roof configurations with different substrate.
Zarriello, Philip J.; Barlow, P.M.; Duda, P.B.
Precipitation-runoff models are used to assess the effects of water use and management alternatives on streamflow. Often, ground-water withdrawals are a major water-use component that affect streamflow, but the ability of surface-water models to simulate ground-water withdrawals is limited. As part of a Hydrologic Simulation Program-FORTRAN (HSPF) precipitation-runoff model developed to analyze the effect of ground-water and surface-water withdrawals on streamflow in the Ipswich River in northeastern Massachusetts, an analytical technique (STRMDEPL) was developed for calculating the effects of pumped wells on streamflow. STRMDEPL is a FORTRAN program based on two analytical solutions that solve equations for ground-water flow to a well completed in a semi-infinite, homogeneous, and isotropic aquifer in direct hydraulic connection to a fully penetrating stream. One analytical method calculates unimpeded flow at the stream-aquifer boundary and the other method calculates the resistance to flow caused by semipervious streambed and streambank material. The principle of superposition is used with these analytical equations to calculate time-varying streamflow depletions due to daily pumping. The HSPF model can readily incorporate streamflow depletions caused by a well or surface-water withdrawal, or by multiple wells or surface-water withdrawals, or both, as a combined time-varying outflow demand from affected channel reaches. These demands are stored as a time series in the Watershed Data Management (WDM) file. This time-series data is read into the model as an external source used to specify flow from the first outflow gate in the reach where these withdrawals are located. Although the STRMDEPL program can be run independently of the HSPF model, an extension was developed to run this program within GenScn, a scenario generator and graphical user interface developed for use with the HSPF model. This extension requires that actual pumping rates for each well be stored
Gash, J.H.C.; Rosier, P.T.W.; Ragab, R.
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
Assefa S. Desta
A stochastic precipitation-runoff modeling is used to estimate a cold and warm-seasons water yield from a ponderosa pine forested watershed in the north-central Arizona. The model consists of two parts namely, simulation of the temporal and spatial distribution of precipitation using a stochastic, event-based approach and estimation of water yield from the watershed...
Gelati, E.; Dommar, C.; Lowe, R.; Polcher, J.; Rodó, X.
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.
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.
Davood Davoodi Moghadam
Full Text Available Introduction: It is vital to control land degradation, for conserving precious natural treasures. Quantification of runoff production and soil and nutrient loss from wild lands under different managerial systems is one of the scientific and optimal management in agriculture and natural resources, as a major component of sustainable development. Many researches have been conducted to assess the effects of different land uses on soil erosion and runoff generation throughout the globe. Most of which, mainly verified the detrimental effects of human intervention on land degradation. However, limited comprehensive and comparative studies have been conducted to consider the amount of surface runoff generation, and soil and nutrient loss from watersheds with different management patterns viz. untreated and treated small watersheds. Materials and Methods: The present study aimed to compare surface runoff generation,soil and nutrient loss in Kakhk treated and untreated watersheds with an area ca. 222 ha and precipitation of some 243 mm per annum. Other physical and geological characteristics of the paired watersheds were also similar to allow assessing the effects of study measures on soil, water and nutrient losses. The area under consideration has been located in Khorasan Razavi Province in northeastern Iran. The present study was performed in plots with standard size of 22.1 × 1.8 m in treating and representative areas, with three replicates and on the storm basis occurred during early 2011 and mid-2014. The treated plots were covered by biological measures viz. seeding, bunching and exclusre. The study plots have been situated on eastern,western and northern aspects with respective slope of 55, 40 and 40 %. The entire runoff from study plots were collected in a container in 0.5×1×1 m. The sediment concentration was also measured in 2-liter samples taken from the container after a complete mixing of the entire collected runoff. The sample was
Liu, Yaoze; Ahiablame, Laurent M; Bralts, Vincent F; Engel, Bernard A
Best management practices (BMPs) and low impact development (LID) practices are increasingly being used as stormwater management techniques to reduce the impacts of urban development on hydrology and water quality. To assist planners and decision-makers at various stages of development projects (planning, implementation, and evaluation), user-friendly tools are needed to assess the effectiveness of BMPs and LID practices. This study describes a simple tool, the Long-Term Hydrologic Impact Assessment-LID (L-THIA-LID), which is enhanced with additional BMPs and LID practices, improved approaches to estimate hydrology and water quality, and representation of practices in series (meaning combined implementation). The tool was used to evaluate the performance of BMPs and LID practices individually and in series with 30 years of daily rainfall data in four types of idealized land use units and watersheds (low density residential, high density residential, industrial, and commercial). Simulation results were compared with the results of other published studies. The simulated results showed that reductions in runoff volume and pollutant loads after implementing BMPs and LID practices, both individually and in series, were comparable with the observed impacts of these practices. The L-THIA-LID 2.0 model is capable of assisting decision makers in evaluating environmental impacts of BMPs and LID practices, thereby improving the effectiveness of stormwater management decisions. Copyright © 2014 Elsevier Ltd. All rights reserved.
Yang, Q.; Shao, J.; Zhang, H.; Wang, G.
Runoff simulation is of great significance for water engineering design, water disaster control, water resources planning and management in a catchment or region. A large number of methods including concept-based process-driven models and statistic-based data-driven models, have been proposed and widely used in worldwide during past decades. Most existing models assume that the relationship among runoff and its impacting factors is stationary. However, in the changing environment (e.g., climate change, human disturbance), their relationship usually evolves over time. In this study, we propose a data stream model for runoff simulation in a changing environment. Specifically, the proposed model works in three steps: learning a rule set, expansion of a rule, and simulation. The first step is to initialize a rule set. When a new observation arrives, the model will check which rule covers it and then use the rule for simulation. Meanwhile, Page-Hinckley (PH) change detection test is used to monitor the online simulation error of each rule. If a change is detected, the corresponding rule is removed from the rule set. In the second step, for each rule, if it covers more than a given number of instance, the rule is expected to expand. In the third step, a simulation model of each leaf node is learnt with a perceptron without activation function, and is updated with adding a newly incoming observation. Taking Fuxi River catchment as a case study, we applied the model to simulate the monthly runoff in the catchment. Results show that abrupt change is detected in the year of 1997 by using the Page-Hinckley change detection test method, which is consistent with the historic record of flooding. In addition, the model achieves good simulation results with the RMSE of 13.326, and outperforms many established methods. The findings demonstrated that the proposed data stream model provides a promising way to simulate runoff in a changing environment.
Full Text Available We describe and evaluate a dynamical continental runoff routing model for the Northern Hemisphere that calculates the runoff pathways in response to topographic modifications due to changes in ice thickness and isostatic adjustment. The algorithm is based on the steepest gradient method and takes as simplifying assumption that depressions are filled at all times and water drains through the lowest outlet points. It also considers changes in water storage and lake drainage in post-processing mode that become important in the presence of large ice dammed proglacial lakes. Although applicable to other scenarios as well, the model was conceived to study the routing of freshwater fluxes during the last Northern Hemisphere deglaciation. For that specific application we simulated the Northern Hemisphere ice sheets with an existing 3-D thermomechanical ice sheet model, which calculates changes in topography due to changes in ice cover and isostatic adjustment, as well as the evolution of freshwater fluxes resulting from surface ablation, iceberg calving and basal melt. The continental runoff model takes this input, calculates the drainage pathways and routes the freshwater fluxes to the surface grid points of an existing ocean model. This results in a chronology of temporally and spatially varying freshwater fluxes from the Last Glacial Maximum to the present day. We analyse the dependence of the runoff routing to grid resolution and parameters of the isostatic adjustment module of the ice sheet model.
Full Text Available A major structural inconsistency of the traditional curve number (CN model is its dependence on an unstable fixed initial abstraction, which normally results in sudden jumps in runoff estimation. Likewise, the lack of pre-storm soil moisture accounting (PSMA procedure is another inherent limitation of the model. To circumvent those problems, we used a variable initial abstraction after ensembling the traditional CN model and a French four-parameter (GR4J model to better quantify direct runoff from ungauged watersheds. To mimic the natural rainfall-runoff transformation at the watershed scale, our new parameterization designates intrinsic parameters and uses a simple structure. It exhibited more accurate and consistent results than earlier methods in evaluating data from 39 forest-dominated watersheds, both for small and large watersheds. In addition, based on different performance evaluation indicators, the runoff reproduction results show that the proposed model produced more consistent results for dry, normal, and wet watershed conditions than the other models used in this study.
Mortatti, Jefferson; Victoria, Reynaldo L.; Moraes, Jorge M.; Rodrigues Junior, Jose C.; Matsumoto, Otavio M.
Using the δO 18 O content of natural waters as a conservative tracer, a runoff modelling of the Amazon river basin was carried out in order to study the hydrological characteristics of the precipitation-runoff relationship. Measurements of the δ 18 O in rainfall waters made in the high Solimoes region at Benjamin Constant, in the central part of basin at Manaus, and at the mouth near the Marajo Island, while the river waters were measured at Obidos only, as a proxy for the mouth, during the 1973-1974 hydrological years. The hydrography separation of the Amazon river was performed using the isotopic method to estimate the contributions of the surface runoff (event water) and baseflow (pre-event water) components to the total river flow. At peak discharge, the average contribution of the baseflow was 57% of the total river flow. The annual average contributions for surface runoff and baseflow were 30.3 and 69.7%, respectively. The residence time of the subsurface water in the basin was estimated as being 7 months, by fitting a sinusoidal function to the isotopic values of rainfall and river waters. The low values of the amplitude damping in the basin suggest high mixing waters during the runoff process. (author). 21 refs., 4 figs., 1 tab
Z. M. Easton
Full Text Available A multi basin analysis of runoff and erosion in the Blue Nile Basin, Ethiopia was conducted to elucidate sources of runoff and sediment. Erosion is arguably the most critical problem in the Blue Nile Basin, as it limits agricultural productivity in Ethiopia, degrades benthos in the Nile, and results in sedimentation of dams in downstream countries. A modified version of the Soil and Water Assessment Tool (SWAT model was developed to predict runoff and sediment losses from the Ethiopian Blue Nile Basin. The model simulates saturation excess runoff from the landscape using a simple daily water balance coupled to a topographic wetness index in ways that are consistent with observed runoff processes in the basin. The spatial distribution of landscape erosion is thus simulated more correctly. The model was parameterized in a nested design for flow at eight and sediment at three locations in the basin. Subbasins ranged in size from 1.3 to 174 000 km2, and interestingly, the partitioning of runoff and infiltrating flow could be predicted by topographic information. Model predictions showed reasonable accuracy (Nash Sutcliffe Efficiencies ranged from 0.53–0.92 with measured data across all sites except Kessie, where the water budget could not be closed; however, the timing of flow was well captured. Runoff losses increased with rainfall during the monsoonal season and were greatest from areas with shallow soils and large contributing areas. Analysis of model results indicate that upland landscape erosion dominated sediment delivery to the main stem of the Blue Nile in the early part of the growing season when tillage occurs and before the soil was wetted up and plant cover was established. Once plant cover was established in mid August landscape erosion was negligible and sediment export was dominated by channel processes and re-suspension of landscape sediment deposited early in the growing season. These results imply that targeting small
Verbist, K.; Cronelis, W. M.; McLaren, R.; Gabriels, D.; Soto, G.
In arid and semi-arid zones runoff harvesting techniques are often applied to increase the water retention and infiltration on steep slopes. Additionally, they act as an erosion control measure to reduce land degradation hazards. Both in literature and in the field, a large variety of runoff collecting systems are found, as well as large variations in design and dimensions. Therefore, detailed measurements were performed on a semi-arid slope in central Chile to allow identification of the effect of a simple water harvesting technique on soil water availability. For this purpose, twenty two TDR-probes were installed and were monitored continuously during and after a simulated rainfall event. These data were used to calibrate the 3D distributed flow model HydroGeoSphere, to assess the runoff components and soil water retention as influenced by the water harvesting technique, both under simulated and natural rainfall conditions. (Author) 6 refs.
Hanninen, J.; Vuorinen, I. [Turku Univ. (Finland). Archipelaco Research Inst.], e-mail: firstname.lastname@example.org
Using Transfer function (TF) models, we have earlier presented a chain of events between changes in the North Atlantic Oscillation (NAO) and their oceanographical and ecological consequences in the Baltic Sea. Here we tested whether other climate indices as inputs would improve TF models, and our understanding of the Baltic Sea ecosystem. Besides NAO, the predictors were the Arctic Oscillation (AO), sea-level air pressures at Iceland (SLP), and wind speeds at Hoburg (Gotland). All indices produced good TF models when the total riverine runoff to the Baltic Sea was used as a modelling basis. AO was not applicable in all study areas, showing a delay of about half a year between climate and runoff events, connected with freezing and melting time of ice and snow in the northern catchment area of the Baltic Sea. NAO appeared to be most useful modelling tool as its area of applicability was the widest of the tested indices, and the time lag between climate and runoff events was the shortest. SLP and Hoburg wind speeds showed largely same results as NAO, but with smaller areal applicability. Thus AO and NAO were both mostly contributing to the general understanding of climate control of runoff events in the Baltic Sea ecosystem. (orig.)
Aronica, G. T.; Candela, A.
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.
Vezzaro, Luca; Mikkelsen, Peter Steen
of uncertainty in a conceptual lumped dynamic stormwater runoff quality model that is used in a study catchment to estimate (i) copper loads, (ii) compliance with dissolved Cu concentration limits on stormwater discharge and (iii) the fraction of Cu loads potentially intercepted by a planned treatment facility...
Borup, Morten; Mikkelsen, Peter Steen; Borup, Morten
When an online runoff model is updated from system measurements, the requirements of the precipitation input change. Using rain gauge data as precipitation input there will be a displacement between the time when the rain hits the gauge and the time where the rain hits the actual catchment, due...
de Boer, T.
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
Runoff from manured fields is often considered to be the source of microorganisms in the surface water used for irrigation, recreation, and household needs. Concerns about microbial safety of this water resulted in development of predictive models for estimating the concentrations and total numbers ...
The Virginia Department of Transportation (VDOT) collects millions of gallons of runoff at its nearly 300 salt storage : facilities each year, with some portion of this water being reused for the generation of salt brine. Storing this collected storm...
Behrens, H.; Moser, H.; Oerter, H.; Rauert, W.; Stichler, W.; Ambach, W.; Kirchlechner, P.
For several years, in the glaciated catchment area of the Rofenache (Oetztal Alps, Austria), measurements have been made of the environmental isotopes 2 H, 18 O and 3 H in precipitation, snow and ice samples and in the runoff. Furthermore, the electrolytic conductivity of runoff samples was measured and tracing experiments were made with fluorescent dyes. From core samples drilled in the accumulation area of the Vernagtferner, the gross beta activity was investigated and compared with the data from 2 H, 3 H and 18 O analyses and the data from mass balance studies. It is shown that the annual net balance from previous years can be recovered on temperate glaciers using environmental isotope techniques. From the diurnal variations of the 2 H and 3 H contents and the electrolytic conductivity, the following proportions in the runoff of the Vernagtferner catchment area were obtained during a 24-hour interval at a time of strong ablation (August 1976): about 50% ice meltwater, 25% direct runoff of firn and snow meltwater, and 7% of mineralized groundwater. The rest of the runoff consists of non-mineralized meltwater seeping from the glacier body. The annual variations of the 2 H and 3 H contents in the runoff of the glaciated catchment area permit conclusions on the time sequence of the individual ablation periods, and on the residence time, on the basis of model concepts. The residence times of approximately 100 days or four years, respectively, are obtained from the decrease in the 2 H content at the end of the ablation period and from the variation of the 3 H content in the winter discharge. (author)
Behrens, H.; Moser, H.; Oerter, H.; Rauert, W.; Stichler, W.; Ambach, W.; Kirchlechner, P.
In the glacierized catchment area of the Rofenache (Oetztal Alps, Austria) during several years measurements have been made of the environmental isotopes 2 H, 18 O and 3 H in the precipitation, in snow and ice samples and in the runoff. Furthermore the electrolytic conductivity of runoff samples was measured and tracing experiments were made with fluorescent dyes. From core samples drilled in the accumulation area of the Vernagtferner, the gross beta activity was investigated and compared with both, the data from 2 H, 3 H und 18 O analyses and the data from mass balance studies. It is shown that the annual net balance from previous years can be recovered on temperate glaciers using environmental isotope techniques. From the diurnal variations of the 2 H and 3 H contents and the electrolytic conductivity the following proportions in the runoff of the Vernagtferner catchment area were obtained during a 24-hour interval at a time of strong ablation (August 1976): about 50% of ice melt water, 25% of direct runoff fo firn- and snow melt water, and 7% of mineralized groundwater. The rest of the runoff consists of not mineralized melt water seeping from the glacier body. The annual variations of the 2 H and 3 H contents in the runoff of the glacierized catchment area permit conclusions on the time sequence of the individual ablation periods and on the residence time on the basis of model concepts. The residence times of approximately 100 days or 4 years, respectively, are obtained from the decrease in the 2 H content at the end of the ablation period and from the variation of the 3 H content in the winter discharge. (orig.) [de
Bradford, S. A.; Liang, J.; Li, W.; Murata, T.; Simunek, J.
Contaminants can be rapidly transported at the soil surface by runoff to surface water bodies. Physically-based models, which are based on the mathematical description of main hydrological processes, are key tools for predicting surface water impairment. Along with physically-based models, data-driven models are becoming increasingly popular for describing the behavior of hydrological and water resources systems since these models can be used to complement or even replace physically based-models. In this presentation we propose a new data-driven model as an alternative to a physically-based overland flow and transport model. First, we have developed a physically-based numerical model to simulate overland flow and contaminant transport (the HYDRUS-1D overland flow module). A large number of numerical simulations were carried out to develop a database containing information about the impact of various input parameters (weather patterns, surface topography, vegetation, soil conditions, contaminants, and best management practices) on runoff water quantity and quality outputs. This database was used to train data-driven models. Three different methods (Neural Networks, Support Vector Machines, and Recurrence Neural Networks) were explored to prepare input- output functional relations. Results demonstrate the ability and limitations of machine learning and deep learning models to predict runoff water quantity and quality.
Poole, Sandra; Vis, Marc; Knight, Rodney; Seibert, Jan
Ecologically relevant streamflow characteristics (SFCs) of ungauged catchments are often estimated from simulated runoff of hydrologic models that were originally calibrated on gauged catchments. However, SFC estimates of the gauged donor catchments and subsequently the ungauged catchments can be substantially uncertain when models are calibrated using traditional approaches based on optimization of statistical performance metrics (e.g., Nash–Sutcliffe model efficiency). An improved calibration strategy for gauged catchments is therefore crucial to help reduce the uncertainties of estimated SFCs for ungauged catchments. The aim of this study was to improve SFC estimates from modeled runoff time series in gauged catchments by explicitly including one or several SFCs in the calibration process. Different types of objective functions were defined consisting of the Nash–Sutcliffe model efficiency, single SFCs, or combinations thereof. We calibrated a bucket-type runoff model (HBV – Hydrologiska Byråns Vattenavdelning – model) for 25 catchments in the Tennessee River basin and evaluated the proposed calibration approach on 13 ecologically relevant SFCs representing major flow regime components and different flow conditions. While the model generally tended to underestimate the tested SFCs related to mean and high-flow conditions, SFCs related to low flow were generally overestimated. The highest estimation accuracies were achieved by a SFC-specific model calibration. Estimates of SFCs not included in the calibration process were of similar quality when comparing a multi-SFC calibration approach to a traditional model efficiency calibration. For practical applications, this implies that SFCs should preferably be estimated from targeted runoff model calibration, and modeled estimates need to be carefully interpreted.
Maaløe, Lars; Sønderby, Casper Kaae; Sønderby, Søren Kaae
Deep generative models parameterized by neural networks have recently achieved state-of-the-art performance in unsupervised and semi-supervised learning. We extend deep generative models with auxiliary variables which improves the variational approximation. The auxiliary variables leave...... the generative model unchanged but make the variational distribution more expressive. Inspired by the structure of the auxiliary variable we also propose a model with two stochastic layers and skip connections. Our findings suggest that more expressive and properly specified deep generative models converge...... faster with better results. We show state-of-the-art performance within semi-supervised learning on MNIST (0.96%), SVHN (16.61%) and NORB (9.40%) datasets....
Trenouth, William R.; Gharabaghi, Bahram
This paper presents novel highway runoff quality models using artificial neural networks (ANN) which take into account site-specific highway traffic and seasonal storm event meteorological factors to predict the event mean concentration (EMC) statistics and mean daily unit area load (MDUAL) statistics of common highway pollutants for the design of roadside ditch treatment systems (RDTS) to protect sensitive receiving environs. A dataset of 940 monitored highway runoff events from fourteen sites located in five countries (Canada, USA, Australia, New Zealand, and China) was compiled and used to develop ANN models for the prediction of highway runoff suspended solids (TSS) seasonal EMC statistical distribution parameters, as well as the MDUAL statistics for four different heavy metal species (Cu, Zn, Cr and Pb). TSS EMCs are needed to estimate the minimum required removal efficiency of the RDTS needed in order to improve highway runoff quality to meet applicable standards and MDUALs are needed to calculate the minimum required capacity of the RDTS to ensure performance longevity.
Prosdocimi, Massimo; Jordán, Antonio; Tarolli, Paolo; Keesstra, Saskia; Novara, Agata; Cerdà, Artemi
Soil and water loss in agriculture is a major problem throughout the world, and especially in Mediterranean areas. Non-conservation agricultural practices have further aggravated the situation, especially in vineyards, which are affected by one of the highest rates of soil loss among cultivated lands. Therefore, it is necessary to find the right soil practices for more sustainable viticulture. In this regard, straw mulching has proven to be effective in other crop and fire affected soils, but, nonetheless, little research has been carried out in vineyards. This research tests the effect of barley straw mulching on soil erosion and surface runoff on vineyards in Eastern Spain where the soil and water losses are non-sustainable. An experiment was setup using rainfall simulation tests at 55 mm h(-1) over 1h on forty paired plots of 0.24 m(2): twenty bare and twenty straw covered. Straw cover varied from 48 to 90% with a median value of 59% as a result of the application of 75 g of straw per m(2). The use of straw mulch resulted in delayed ponding and runoff generation and, as a consequence, the median water loss decreased from 52.59 to 39.27% of the total rainfall. The straw cover reduced the median sediment concentration in runoff from 9.8 to 3.0 g L(-1) and the median total sediment detached from 70.34 to 15.62 g per experiment. The median soil erosion rate decreased from 2.81 to 0.63 Mg ha(-1)h(-1) due to the straw mulch protection. Straw mulch is very effective in reducing soil erodibility and surface runoff, and this benefit was achieved immediately after the application of the straw. Copyright © 2015 Elsevier B.V. All rights reserved.
Del Giudice, Dario; Löwe, Roland; Madsen, Henrik
from different fields and have not yet been compared in environmental modeling. To compare the two approaches, we develop a unifying terminology, evaluate them theoretically, and apply them to conceptual rainfall-runoff modeling in the same drainage system. Our results show that both approaches can......In urban rainfall-runoff, commonly applied statistical techniques for uncertainty quantification mostly ignore systematic output errors originating from simplified models and erroneous inputs. Consequently, the resulting predictive uncertainty is often unreliable. Our objective is to present two...... approaches which use stochastic processes to describe systematic deviations and to discuss their advantages and drawbacks for urban drainage modeling. The two methodologies are an external bias description (EBD) and an internal noise description (IND, also known as stochastic gray-box modeling). They emerge...
Lesschen, J.P.; Schoorl, J.M.; Cammeraat, L.H.
Runoff and erosion processes are often non-linear and scale dependent, which complicate runoff and erosion modelling at the catchment scale. One of the reasons for scale dependency is the influence of sinks, i.e. areas of infiltration and sedimentation, which lower hydrological connectivity and
Albaradeyia, Issa; Hani, Azzedine; Shahrour, Isam
This paper presents the use of both the Water Erosion Prediction Project (WEPP) and the artificial neural network (ANN) for the prediction of runoff and soil loss in the central highland mountainous of the Palestinian territories. Analyses show that the soil erosion is highly dependent on both the rainfall depth and the rainfall event duration rather than on the rainfall intensity as mostly mentioned in the literature. The results obtained from the WEPP model for the soil loss and runoff disagree with the field data. The WEPP underestimates both the runoff and soil loss. Analyses conducted with the ANN agree well with the observation. In addition, the global network models developed using the data of all the land use type show a relatively unbiased estimation for both runoff and soil loss. The study showed that the ANN model could be used as a management tool for predicting runoff and soil loss.
V. A. Bell
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
Troutman, Brent M.
Errors in complex conceptual precipitation-runoff models may be analyzed by placing them into a statistical framework. This amounts to treating the errors as random variables and defining the probabilistic structure of the errors. By using such a framework, a large array of techniques, many of which have been presented in the statistical literature, becomes available to the modeler for quantifying and analyzing the various sources of error. A number of these techniques are reviewed in this paper, with special attention to the peculiarities of hydrologic models. Known methodologies for parameter estimation (calibration) are particularly applicable for obtaining physically meaningful estimates and for explaining how bias in runoff prediction caused by model error and input error may contribute to bias in parameter estimation.
Wood, A. W.; Restrepo, P. J.; Clark, M. P.
In the western US, the snow accumulation and melt cycle of winter and spring plays a critical role in the region's water management strategies. Consequently, the ability to predict snowmelt runoff at time scales from days to seasons is a key input for decisions in reservoir management, whether for avoiding flood hazards or supporting environmental flows through the scheduling of releases in spring, or for allocating releases for multi-state water distribution in dry seasons of year (using reservoir systems to provide an invaluable buffer for many sectors against drought). Runoff forecasts thus have important benefits at both wet and dry extremes of the climatological spectrum. The importance of the prediction of the snow cycle motivates an assessment of the strengths and weaknesses of the US's central operational snow model, SNOW17, in contrast to process-modeling alternatives, as they relate to simulating observed snowmelt variability and extremes. To this end, we use a flexible modeling approach that enables an investigation of different choices in model structure, including model physics, parameterization and degree of spatiotemporal discretization. We draw from examples of recent extreme events in western US watersheds and an overall assessment of retrospective model performance to identify fruitful avenues for advancing the modeling basis for the operational prediction of snow-related runoff extremes.
Zhang, J.; Han, D.
Runoff prediction in ungauged catchments has been one of the major challenges in the past decades. However, due to the tremendous heterogeneity of hydrological catchments, obstacles exist in deducing model parameters for ungauged catchments from gauged ones. We propose a novel approach to predict ungauged runoff with Catchment Morphing (CM) using a fully distributed model. CM is defined as by changing the catchment characteristics (area and slope here) from the baseline model built with a gauged catchment to model the ungauged ones. The advantages of CM are: (a) less demand of the similarity between the baseline catchment and the ungauged catchment, (b) less demand of available data, and (c) potentially applicable in varied catchments. A case study on seven catchments in the UK has been used to demonstrate the proposed scheme. To comprehensively examine the CM approach, distributed rainfall inputs are utilised in the model, and fractal landscapes are used to morph the land surface from the baseline model to the target model. The preliminary results demonstrate the feasibility of the approach, which is promising in runoff simulation for ungauged catchments. Clearly, more work beyond this pilot study is needed to explore and develop this new approach further to maturity by the hydrological community.
Tramblay, Yves; Bouvier, Christophe; Martin, C.; Didon-Lescot, J. F.; Todorovik, D.; Domergue, J. M.
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,...
van Emmerik, Tim; Eilander, Dirk; Piet, Marijn; Mulder, Gert
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.
The general objective of this study was to investigate the possibility of providing spatially distributed soil moisture data for event-based hydrological models close before a rainfall event. The study area is known as "Catsop", a small catchmment in south Limburg. The models used are: LISEM and
Zheng, Yi; Lin, Zhongrong; Li, Hao; Ge, Yan; Zhang, Wei; Ye, Youbin; Wang, Xuejun
Urban stormwater runoff delivers a significant amount of polycyclic aromatic hydrocarbons (PAHs), mostly of atmospheric origin, to receiving water bodies. The PAH pollution of urban stormwater runoff poses serious risk to aquatic life and human health, but has been overlooked by environmental modeling and management. This study proposed a dynamic modeling approach for assessing the PAH pollution and its associated environmental risk. A variable time-step model was developed to simulate the continuous cycles of pollutant buildup and washoff. To reflect the complex interaction among different environmental media (i.e. atmosphere, dust and stormwater), the dependence of the pollution level on antecedent weather conditions was investigated and embodied in the model. Long-term simulations of the model can be efficiently performed, and probabilistic features of the pollution level and its risk can be easily determined. The applicability of this approach and its value to environmental management was demonstrated by a case study in Beijing, China. The results showed that Beijing's PAH pollution of road runoff is relatively severe, and its associated risk exhibits notable seasonal variation. The current sweeping practice is effective in mitigating the pollution, but the effectiveness is both weather-dependent and compound-dependent. The proposed modeling approach can help identify critical timing and major pollutants for monitoring, assessing and controlling efforts to be focused on. The approach is extendable to other urban areas, as well as to other contaminants with similar fate and transport as PAHs. Copyright © 2014 Elsevier B.V. All rights reserved.
Jacobsen, Judith L.
In this thesis, models for the dynamics of oxygen and organic matter in receiving waters (such as rivers and creeks), which are affected by rain, are developed. A time series analysis framework is used, but presented with special emphasis on continuous time state space models. Also, the concept o....... In most models, precipitation in the form of rain have been included to study the impact from this. Finally, the future and industrial perspectives are presented, along with a list of suggestions for future research related to the subjects considered in this thesis....
The model ordinance in this section borrows language from the erosion and sediment control ordinance features that might help prevent erosion and sedimentation and protect natural resources more fully.
Regan, R. Steven; Markstrom, Steven L.; Hay, Lauren E.; Viger, Roland J.; Norton, Parker A.; Driscoll, Jessica M.; LaFontaine, Jacob H.
This report documents several components of the U.S. Geological Survey National Hydrologic Model of the conterminous United States for use with the Precipitation-Runoff Modeling System (PRMS). It provides descriptions of the (1) National Hydrologic Model, (2) Geospatial Fabric for National Hydrologic Modeling, (3) PRMS hydrologic simulation code, (4) parameters and estimation methods used to compute spatially and temporally distributed default values as required by PRMS, (5) National Hydrologic Model Parameter Database, and (6) model extraction tool named Bandit. The National Hydrologic Model Parameter Database contains values for all PRMS parameters used in the National Hydrologic Model. The methods and national datasets used to estimate all the PRMS parameters are described. Some parameter values are derived from characteristics of topography, land cover, soils, geology, and hydrography using traditional Geographic Information System methods. Other parameters are set to long-established default values and computation of initial values. Additionally, methods (statistical, sensitivity, calibration, and algebraic) were developed to compute parameter values on the basis of a variety of nationally-consistent datasets. Values in the National Hydrologic Model Parameter Database can periodically be updated on the basis of new parameter estimation methods and as additional national datasets become available. A companion ScienceBase resource provides a set of static parameter values as well as images of spatially-distributed parameters associated with PRMS states and fluxes for each Hydrologic Response Unit across the conterminuous United States.
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...
Soulis, K. X.; Valiantzas, J. D.; Dercas, N.; Londra, P. A.
The Soil Conservation Service Curve Number (SCS-CN) method is widely used for predicting direct runoff volume for a given rainfall event. The applicability of the SCS-CN method and the direct runoff generation mechanism were thoroughly analysed in a Mediterranean experimental watershed in Greece. The region is characterized by a Mediterranean semi-arid climate. A detailed land cover and soil survey using remote sensing and GIS techniques, showed that the watershed is dominated by coarse soils...
Birch, Heidi; Vezzaro, Luca; Mikkelsen, Peter Steen
Monitoring of micropollutants (MP) in stormwater is essential to evaluate the impacts of stormwater on the receiving aquatic environment. The aim of this study was to investigate how different strategies for monitoring of stormwater quality (combining a model with field sampling) affect the infor...
Rodrigo Comino, J; Iserloh, T; Lassu, T; Cerdà, A; Keestra, S D; Prosdocimi, M; Brings, C; Marzen, M; Ramos, M C; Senciales, J M; Ruiz Sinoga, J D; Seeger, M; Ries, J B
The aim of this study was to enable a quantitative comparison of initial soil erosion processes in European vineyards using the same methodology and equipment. The study was conducted in four viticultural areas with different characteristics (Valencia and Málaga in Spain, Ruwer-Mosel valley and Saar-Mosel valley in Germany). Old and young vineyards, with conventional and ecological planting and management systems were compared. The same portable rainfall simulator with identical rainfall intensity (40mmh(-1)) and sampling intervals (30min of test duration, collecting the samples at 5-min-intervals) was used over a circular test plot with 0.28m(2). The results of 83 simulations have been analysed and correlation coefficients were calculated for each study area to identify the relationship between environmental plot characteristics, soil texture, soil erosion, runoff and infiltration. The results allow for identification of the main factors related to soil properties, topography and management, which control soil erosion processes in vineyards. The most important factors influencing soil erosion and runoff were the vegetation cover for the ecological German vineyards (with 97.6±8% infiltration coefficients) and stone cover, soil moisture and slope steepness for the conventional land uses. Copyright © 2016 Elsevier B.V. All rights reserved.
Basarudin, Z.; Adnan, N. A.; Latif, A. R. A.; Tahir, W.; Syafiqah, N.
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.
Basarudin, Z; Adnan, N A; Latif, A R A; Syafiqah, N; Tahir, W
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
Flynn, D. P.; O'Kane, J. P.
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.
Wood, Eric F.
The effects of small-scale heterogeneity in land surface characteristics on the large-scale fluxes of water and energy in the land-atmosphere system has become a central focus of many of the climatology research experiments. The acquisition of high resolution land surface data through remote sensing and intensive land-climatology field experiments (like HAPEX and FIFE) has provided data to investigate the interactions between microscale land-atmosphere interactions and macroscale models. One essential research question is how to account for the small scale heterogeneities and whether 'effective' parameters can be used in the macroscale models. To address this question of scaling, the probability distribution for evaporation is derived which illustrates the conditions for which scaling should work. A correction algorithm that may appropriate for the land parameterization of a GCM is derived using a 2nd order linearization scheme. The performance of the algorithm is evaluated.
Kavetski, D.; Franks, S. W.; Kuczera, G.
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
Full Text Available This study assessed the performances of the traditional temperature-index snowmelt runoff model (SRM and an SRM model with a finer zonation based on aspect and slope (SRM + AS model in a data-scarce mountain watershed in the Urumqi River Basin, in Northwest China. The proposed SRM + AS model was used to estimate the melt rate with the degree-day factor (DDF through the division of watershed elevation zones based on aspect and slope. The simulation results of the SRM + AS model were compared with those of the traditional SRM model to identify the improvements of the SRM + AS model's performance with consideration of topographic features of the watershed. The results show that the performance of the SRM + AS model has improved slightly compared to that of the SRM model. The coefficients of determination increased from 0.73, 0.69, and 0.79 with the SRM model to 0.76, 0.76, and 0.81 with the SRM + AS model during the simulation and validation periods in 2005, 2006, and 2007, respectively. The proposed SRM + AS model that considers aspect and slope can improve the accuracy of snowmelt runoff simulation compared to the traditional SRM model in mountain watersheds in arid regions by proper parameterization, careful input data selection, and data preparation.
Locatelli, Luca; Mark, Ole; Mikkelsen, Peter Steen
Green roofs are being widely implemented for storm water control and runoff reduction. There is need for incorporating green roofs into urban drainage models in order to evaluate their impact. These models must have low computational costs and fine time resolution. This paper aims to develop...... a model of green roof hydrological performance. A simple conceptual model for the long term and single event hydrological performance of green roofs, shows to be capable of reproducing observed runoff measurements. The model has surface and subsurface storage components representing the overall retention...... capacity of the green roof. The runoff from the system is described by the non-linear reservoir method and the storage capacity of the green roof is continuously re-established by evapotranspiration. Runoff data from a green roof in Denmark are collected and used for parameter calibration....
The Lower Middle Zambezi Basin is sandwiched between three hydropower ... This study applied a rainfall-runoff model (HEC-HMS) and GIS techniques to ... Missing data were generated using the mean value infilling method. ... A hydrological model, HEC- HMS, was used to simulate runoff from the ungauged catchments.
Griessinger, Nena; Seibert, Jan; Magnusson, Jan; Jonas, Tobias
In Alpine catchments, snowmelt is often a major contribution to runoff. Therefore, modeling snow processes is important when concerned with flood or drought forecasting, reservoir operation and inland waterway management. In this study, we address the question of how sensitive hydrological models are to the representation of snow cover dynamics and whether the performance of a hydrological model can be enhanced by integrating data from a dedicated external snow monitoring system. As a framework for our tests we have used the hydrological model HBV (Hydrologiska Byråns Vattenbalansavdelning) in the version HBV-light, which has been applied in many hydrological studies and is also in use for operational purposes. While HBV originally follows a temperature-index approach with time-invariant calibrated degree-day factors to represent snowmelt, in this study the HBV model was modified to use snowmelt time series from an external and spatially distributed snow model as model input. The external snow model integrates three-dimensional sequential assimilation of snow monitoring data with a snowmelt model, which is also based on the temperature-index approach but uses a time-variant degree-day factor. The following three variations of this external snow model were applied: (a) the full model with assimilation of observational snow data from a dense monitoring network, (b) the same snow model but with data assimilation switched off and (c) a downgraded version of the same snow model representing snowmelt with a time-invariant degree-day factor. Model runs were conducted for 20 catchments at different elevations within Switzerland for 15 years. Our results show that at low and mid-elevations the performance of the runoff simulations did not vary considerably with the snow model version chosen. At higher elevations, however, best performance in terms of simulated runoff was obtained when using the snowmelt time series from the snow model, which utilized data assimilation
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.
Full Text Available This study assesses future change of surface runoff due to climate change over Korea using a regional climate model (RCM, namely, the Global/Regional Integrated Model System (GRIMs, Regional Model Program (RMP. The RMP is forced by future climate scenario, namely, A1B of Intergovernmental Panel on Climate Change (IPCC Fourth Assessment Report (AR4. The RMP satisfactorily reproduces the observed seasonal mean and variation of surface runoff for the current climate simulation. The distribution of monsoonal precipitation-related runoff is adequately captured by the RMP. In the future (2040–2070 simulation, it is shown that the increasing trend of temperature has significant impacts on the intra-annual runoff variation. The variability of runoff is increased in summer; moreover, the strengthened possibility of extreme occurrence is detected in the future climate. This study indicates that future climate projection, including surface runoff and its variability over Korea, can be adequately addressed on the RMP testbed. Furthermore, this study reflects that global warming affects local hydrological cycle by changing major water budget components. This study adduces that the importance of runoff should not be overlooked in regional climate studies, and more elaborate presentation of fresh-water cycle is needed to close hydrological circulation in RCMs.
Silveira, Alexandre; Abrantes, João; de Lima, João; Lira, Lincoln
Rainwater harvesting is a water saving alternative strategy that presents many advantages and can provide solutions to address major water resources problems, such as fresh water scarcity, urban stream degradation and flooding. In recent years, these problems have become global challenges, due to climatic change, population growth and increasing urbanisation. Generally, roofs are the first to come into contact with rainwater; thus, they are the best candidates for rainwater harvesting. In this context, the correct evaluation of roof runoff quantity and quality is essential to effectively design rainwater harvesting systems. Despite this, many studies usually focus on the qualitative aspects in detriment of the quantitative aspects. Laboratory studies using rainfall simulators have been widely used to investigate rainfall-runoff processes. These studies enabled a detailed exploration and systematic replication of a large range of hydrologic conditions, such as rainfall spatial and temporal characteristics, providing for a fast way to obtain precise and consistent data that can be used to calibrate and validate numerical models. This study aims to evaluate the performance of a kinematic wave based numerical model in simulating runoff on sloping roofs, by comparing the numerical results with the ones obtained from laboratory rainfall simulations on a real-scale ceramic tile roof (Lusa tiles). For all studied slopes, simulated discharge hydrographs had a good adjust to observed ones. Coefficient of determination and Nash-Sutcliffe efficiency values were close to 1.0. Particularly, peak discharges, times to peak and peak durations were very well simulated.
Concepción Ramos, Maria; Martínez-Casasnovas, José A.
The magnitude of erosion processes, widespread throughout the Mediterranean areas, may be enhanced due to changes in seasonal precipitation regimes and an increase of extreme events. The present research shows the results of possible effects of climate change on runoff and soil loss in a rainfed catchment located in the Barcelona province (NE Spain).In the study area, vines are the main land use, cultivated under the Penedès designation of origin. The present research shows the results of runoff and soil loss simulated using SWAT for a small basin with vines as main land use. Input data included detailed soil and land use maps, and daily climate data of the period 1998-2012. The analysis compared simulated results for years with different climatic conditions during that period and the average with predictions for the scenario 2020, 2050 and 2080 based on the HadCM3 GCM under A2 scenario and the trends observed in the area related to maximum rainfall intensity. The model was calibrated and validated using data recorded at different subbasins, using soil water and runoff samples. Taking into account the predicted changes in temperature and precipitation, the model simulated a decrease in soil loss associated with a decrease in runoff, mainly driven by an increase in evapotranspiration. However, the trend in soil losses varied when the changes in precipitation could balance the increase of evapotranspiration and also due to the increase of rainfall intensity. An increase in maximum rainfall intensity in spring and autumn (main rainy seasons) produced significant increases in soil loss: by up to 12% for the 2020 scenario and up to 57% for the 2050 scenario, although high differences may exists depending on rainfall characteristics. The research confirmed the difficulty of predicting future soil loss in this region, which has a very high climate inter-annual variability.
Gregoretti, C.; Degetto, M.; Bernard, M.; Crucil, G.; Pimazzoni, A.; De Vido, G.; Berti, M.; Simoni, A.; Lanzoni, S.
In dolomitic headwater catchments, intense rainstorms of short duration produce runoff discharges that often trigger debris flows on the scree slopes at the base of rock cliffs. In order to measure these discharges, we placed a measuring facility at the outlet (elevation 1770 m a.s.l.) of a small, rocky headwater catchment (area ˜0.032 km2, average slope ˜320%) located in the Venetian Dolomites (North Eastern Italian Alps). The facility consists of an approximately rectangular basin, ending with a sharp-crested weir. Six runoff events were recorded in the period 2011-2014, providing a unique opportunity for characterizing the hydrological response of the catchment. The measured hydrographs display impulsive shapes, with an abrupt raise up to the peak, followed by a rapidly decreasing tail, until a nearly constant plateau is eventually reached. This behavior can be simulated by means of a distributed hydrological model if the excess rainfall is determined accurately. We show that using the Soil Conservation Service Curve-Number (SCS-CN) method and assuming a constant routing velocity invariably results in an underestimated peak flow and a delayed peak time. A satisfactory prediction of the impulsive hydrograph shape, including peak value and timing, is obtained only by combining the SCS-CN procedure with a simplified version of the Horton equation, and simulating runoff routing along the channel network through a matched diffusivity kinematic wave model. The robustness of the proposed methodology is tested through a comparison between simulated and observed timings of runoff or debris flow occurrence in two neighboring alpine basins.
Decker, P.; Cohen, M. J.; Jawitz, J. W.
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
Full Text Available Soil sealing is the permanent covering of the land surface by buildings, infrastructures or any impermeable artificial material. Beside the loss of fertile soils with a direct impact on food security, soil sealing modifies the hydrological cycle. This can cause an increased flooding risk, due to urban development in potential risk areas and to the increased volumes of runoff. This work estimates the increase of runoff due to sealing following urbanization and land take in the plain of Emilia Romagna (Italy, using the Green and Ampt infiltration model for two rainfall return periods (20 and 200 years in two different years, 1976 and 2008. To this goal a hydropedological approach was adopted in order to characterize soil hydraulic properties via locally calibrated pedotransfer functions (PTF. PTF inputs were estimated via sequential Gaussian simulations coupled with a simple kriging with varying local means, taking into account soil type and dominant land use. Results show that in the study area an average increment of 8.4% in sealed areas due to urbanization and sprawl induces an average increment in surface runoff equal to 3.5 and 2.7% respectively for 20 and 200-years return periods, with a maximum > 20% for highly sealed coast areas.
Full Text Available Landsat MSS and ETM+ images were analyzed to detect 25-year land-cover change (1976–2001 in the critical Taguibo Watershed in Mindanao Island, Southern Philippines. This watershed has experienced historical modifications of its land-cover due to the presence of logging industries in the 1950s, and continuous deforestation due to illegal logging and slash-and-burn agriculture in the present time. To estimate the impacts of land-cover change on watershed runoff, land-cover information derived from the Landsat images was utilized to parameterize a GIS-based hydrologic model. The model was then calibrated with field-measured discharge data and used to simulate the responses of the watershed in its year 2001 and year 1976 land-cover conditions. The availability of land-cover information on the most recent state of the watershed from the Landsat ETM+ image made it possible to locate areas for rehabilitation such as barren and logged-over areas. We then created a “rehabilitated” land-cover condition map of the watershed (re-forestation of logged-over areas and agro-forestation of barren areas and used it to parameterize the model and predict the runoff responses of the watershed. Model results showed that changes in land-cover from 1976 to 2001 were directly related to the significant increase in surface runoff. Runoff predictions showed that a full rehabilitation of the watershed, especially in barren and logged-over areas, will be likely to reduce the generation of a huge volume of runoff during rainfall events. The results of this study have demonstrated the usefulness of multi-temporal Landsat images in detecting land-cover change, in identifying areas for rehabilitation, and in evaluating rehabilitation strategies for management of tropical watersheds through its use in hydrologic modeling.
Beck, Hylke; de Roo, Ad; van Dijk, Albert; Schellekens, Jaap; Dutra, Emanuel; Fink, Gabriel; Orth, Rene
Observed streamflow data from 966 medium sized catchments (1000 to 5000 km2) around the globe were used to comprehensively evaluate the daily runoff estimates (1979-2012) of six global hydrological models (GHMs) and four land surface models (LSMs) produced as part of Tier-1 of the eartH2Observe project. The models were all driven by the WATCH Forcing Data ERA-Interim (WFDEI) meteorological dataset, but used different datasets for non-meteorologic inputs and were run at various spatial and temporal resolutions, although all data were re-sampled to a common 0.5° spatial and daily temporal resolution. For the evaluation, we used a broad range of performance metrics related to important aspects of the hydrograph. We found pronounced inter-model performance differences, underscoring the importance of hydrological model uncertainty in addition to climate input uncertainty, for example in studies assessing the hydrological impacts of climate change. The (uncalibrated) GHMs were found to perform better than the LSMs in snow-dominated regions, and the ensemble mean was found to perform only slightly worse than the best (calibrated) model. The models generally showed an early bias in the spring snowmelt peak. We further found that, despite adjustments using gauge observations, the WFDEI precipitation data still contain substantial biases which propagate in the simulated runoff. Overall, more effort should be devoted to calibrating and regionalizing the parameters of macro-scale models.
''The Disposal Criticality Analysis Methodology Topical Report'' prescribes an approach to the methodology for performing postclosure criticality analyses within the monitored geologic repository at Yucca Mountain, Nevada. An essential component of the methodology is the ''Configuration Generator Model for In-Package Criticality'' that provides a tool to evaluate the probabilities of degraded configurations achieving a critical state. The configuration generator model is a risk-informed, performance-based process for evaluating the criticality potential of degraded configurations in the monitored geologic repository. The method uses event tree methods to define configuration classes derived from criticality scenarios and to identify configuration class characteristics (parameters, ranges, etc.). The probabilities of achieving the various configuration classes are derived in part from probability density functions for degradation parameters. The NRC has issued ''Safety Evaluation Report for Disposal Criticality Analysis Methodology Topical Report, Revision 0''. That report contained 28 open items that required resolution through additional documentation. Of the 28 open items, numbers 5, 6, 9, 10, 18, and 19 were concerned with a previously proposed software approach to the configuration generator methodology and, in particular, the k eff regression analysis associated with the methodology. However, the use of a k eff regression analysis is not part of the current configuration generator methodology and, thus, the referenced open items are no longer considered applicable and will not be further addressed
Zimmerman, Marc J.; Waldron, Marcus C.; Barbaro, Jeffrey R.; Sorenson, Jason R.
Low-impact-development (LID) approaches are intended to create, retain, or restore natural hydrologic and water-quality conditions that may be affected by human alterations. Wide-scale implementation of LID techniques may offer the possibility of improving conditions in river basins, such as the Ipswich River Basin in Massachusetts, that have run dry during the summer because of groundwater withdrawals and drought. From 2005 to 2008, the U.S. Geological Survey, in a cooperative funding agreement with the Massachusetts Department of Conservation and Recreation, monitored small-scale installations of LID enhancements designed to diminish the effects of storm runoff on the quantity and quality of surface water and groundwater. Funding for the studies also was contributed by the U.S. Environmental Protection Agency's Targeted Watersheds Grant Program through a financial assistance agreement with Massachusetts Department of Conservation and Recreation. The monitoring studies examined the effects of * replacing an impervious parking-lot surface with a porous surface on groundwater quality, * installing rain gardens and porous pavement in a neighborhood of 3 acres on the quantity and quality of stormwater runoff, and * installing a 3,000-ft2 (square-foot) green roof on the quantity and quality of rainfall-generated roof runoff. In addition to these small-scale installations, the U.S. Geological Survey's Ipswich River Basin model was used to simulate the basin-wide effects on streamflow of several changes: broad-scale implementation of LID techniques, reduced water-supply withdrawals, and water-conservation measures. Water-supply and conservation scenarios for application in model simulations were developed with the assistance of two technical advisory committees that included representatives of State agencies responsible for water resources, the U.S. Environmental Protection Agency, the U.S. Geological Survey, water suppliers, and non-governmental organizations. From June
Full Text Available For the Greenland Ice Sheet (GrIS, large-scale melt area has increased in recent years and is detectable via remote sensing, but its relation to runoff is not known. Historical, modeled melt area and runoff from Modern-Era Retrospective Analysis for Research and Applications (MERRA-Replay, the Interim Re-Analysis of the European Centre for Medium Range Weather Forecasts (ERA-I, the Climate Forecast System Reanalysis (CFSR, the Modèle Atmosphérique Régional (MAR, and the Arctic System Reanalysis (ASR are examined. These sources compare favorably with satellite-derived estimates of surface melt area for the period 2000-2012. Spatially, the models markedly disagree on the number of melt days in the interior of the southern part of the ice sheet, and on the extent of persistent melt areas in the northeastern GrIS. Temporally, the models agree on the mean seasonality of daily surface melt and on the timing of large-scale melt events in 2012. In contrast, the models disagree on the amount, seasonality, spatial distribution, and temporal variability of runoff. As compared to global reanalyses, time series from MAR indicate a lower correlation between runoff and melt area (r2 = 0.805. Runoff in MAR is much larger in the second half of the melt season for all drainage basins, while the ASR indicates larger runoff in the first half of the year. This difference in seasonality for the MAR and to an extent for the ASR provide a hysteresis in the relation between runoff and melt area, which is not found in the other models. The comparison points to a need for reliable observations of surface runoff.
Full Text Available In planning of water resource projects, the estimation of the availability of water plays an important role. The first step in the water availability estimation is the computation of runoff resulting from the precipitation on river catchments. The length of the runoff measured in a stream may be of short period or long period depending upon the catchment characteristics. Keeping this in mind the present work is focused on two different model generation. In the first phase of this study, runoff rating curves are developed considering present day water level (H(t as input and present day runoff (Q(t as the model output. In the second phase of the study runoff prediction models are developed considering 1 day lag water level (H(t − 1, 2 day lag water level (H(t − 2 and 1 day lag runoff (Q(t − 1 as inputs and 1 day ahead runoff (Q(t + 1 as the output of the model. Models developed and used for prediction of runoff are Non-Linear Multiple Regression (NLMR and Adaptive Neuro-Fuzzy Inference System (ANFIS. Both the models were trained and tested to predict the performance of models. Genetic Algorithm (GA is then coupled with NLMR model to obtain the condition of hydrological parameter for which the runoff is maximum.
Yang, Ting; Wang, Quanjiu; Wu, Laosheng; Zhang, Pengyu; Zhao, Guangxu; Liu, Yanli
The transfer of nutrients from soil to runoff often causes unexpected pollution in water bodies. In this study, a mathematical model that relates to the detachment of soil particles by water flow and the degree of mixing between overland flow and soil nutrients was proposed. The model assumes that the mixing depth is an integral of average water flow depth, and it was evaluated by experiments with three water inflow rates to bare soil surfaces and to surfaces with eight treatments of different stone coverages. The model predicted outflow rates were compared with the experimentally observed data to test the accuracy of the infiltration parameters obtained by curve fitting the models to the data. Further analysis showed that the comprehensive mixing coefficient (ke) was linearly correlated with Reynolds' number Re (R(2)>0.9), and this relationship was verified by comparing the simulated potassium concentration and cumulative mass with observed data, respectively. The best performance with the bias error analysis (Nash Sutcliffe coefficient of efficiency (NS), relative error (RE) and the coefficient of determination (R(2))) showed that the predicted data by the proposed model was in good agreement with the measured data. Thus the model can be used to guide soil-water and fertilization management to minimize nutrient runoff from cropland. Copyright © 2016 Elsevier B.V. All rights reserved.
Garcia Galiano, S. G.; Olmos, P.; Giraldo Osorio, J. D.
In the Mediterranean area, significant changes on temperature and precipitation are expected throughout the century. These trends could exacerbate the existing conditions in regions already vulnerable to climatic variability, reducing the water availability. Improving knowledge about plausible impacts of climate change on water cycle processes at basin scale, is an important step for building adaptive capacity to the impacts in this region, where severe water shortages are expected for the next decades. RCMs ensemble in combination with distributed hydrological models with few parameters, constitutes a valid and robust methodology to increase the reliability of climate and hydrological projections. For reaching this objective, a novel methodology for building Regional Climate Models (RCMs) ensembles of meteorological variables (rainfall an temperatures), was applied. RCMs ensembles are justified for increasing the reliability of climate and hydrological projections. The evaluation of RCMs goodness-of-fit to build the ensemble is based on empirical probability density functions (PDF) extracted from both RCMs dataset and a highly resolution gridded observational dataset, for the time period 1961-1990. The applied method is considering the seasonal and annual variability of the rainfall and temperatures. The RCMs ensembles constitute the input to a distributed hydrological model at basin scale, for assessing the runoff projections. The selected hydrological model is presenting few parameters in order to reduce the uncertainties involved. The study basin corresponds to a head basin of Segura River Basin, located in the South East of Spain. The impacts on runoff and its trend from observational dataset and climate projections, were assessed. Considering the control period 1961-1990, plausible significant decreases in runoff for the time period 2021-2050, were identified.
Because water goes into storage when it rains, perhaps the entire concept of a direct rainfall-runoff process is erroneous and misleading. Perhaps the runoff generation process is merely the conversion of storage to runoff. Using this perspective as a foundation, it then becomes important to understand how catchments retain water, where this storage is distributed and what controls the distribution of this storage. There is a growing body of observational evidence that the idiosyncrasies of storage in the catchment are crucial for runoff generation. These idiosyncrasies are important enough that some hydrologists are questioning assumptions of steady state, linearity, and topographic control in existing theories and algorithms of runoff generation. For instance, thresholds that control the release of water have been identified at many scales and in many landscapes. Hysteresis in storage-runoff relationships at all scales manifest because of these thresholds. Because storage thresholds at a range of scales are now known to be important for runoff response, connectivity has become an important concept crucial to interpreting catchment runoff response. There appears to be growing acceptance of such ideas as thresholds, hysteresis and connectivity in the hydrological literature. Theoretical development and model parameterization have begun, but there remains much work to resolve these field observations. In particular, our community should strive to investigate the relevance of storage-runoff relationships partly through innovative measurement techniques and the development of model structures appropriate for the requisite testing of these theories in a diversity of landscapes.
Full Text Available An integrated modeling system has been developed for analyzing the impact of climate change on snowmelt runoff in Kaidu Watershed, Northwest China. The system couples Hadley Centre Coupled Model version 3 (HadCM3 outputs with Snowmelt Runoff Model (SRM. The SRM was verified against observed discharge for outlet hydrological station of the watershed during the period from April to September in 2001 and generally performed well for Nash-Sutcliffe coefficient (EF and water balance coefficient (RE. The EF is approximately over 0.8, and the water balance error is lower than ± 10%, indicating reasonable prediction accuracy. The Statistical Downscaling Model (SDSM was used to downscale coarse outputs of HadCM3, and then the downscaled future climate data were used as inputs of the SRM. Four scenarios were considered for analyzing the climate change impact on snowmelt flow in the Kaidu Watershed. And the results indicated that watershed hydrology would alter under different climate change scenarios. The stream flow in spring is likely to increase with the increased mean temperature; the discharge and peck flow in summer decrease with the decreased precipitation under Scenarios 1 and 2. Moreover, the consideration of the change in cryosphere area would intensify the variability of stream flow under Scenarios 3 and 4. The modeling results provide useful decision support for water resources management.
Buerger, C.M.; Kolditz, O.; Fowler, H.J.; Blenkinsop, S.
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
Ritchie, L.T.; Brown, W.D.; Wayland, J.R.
A general temperate latitude cyclonic rainstorm model is presented which describes the effects of washout and runoff on consequences of atmospheric releases of radioactive material from potential nuclear reactor accidents. The model treats the temporal and spatial variability of precipitation processes. Predicted air and ground concentrations of radioactive material and resultant health consequences for the new model are compared to those of the original WASH-1400 model under invariant meteorological conditions and for realistic weather events using observed meteorological sequences. For a specific accident under a particular set of meteorological conditions, the new model can give significantly different results from those predicted by the WASH-1400 model, but the aggregate consequences produced for a large number of meteorological conditions are similar
Milzow, Christian; Bauer-Gottwein, Peter
The competition between human water use and ecosystem water use is one of the major challenges for water resources management at the global scale. We analyse the situation for the Okavango River basin of southern Africa. The Okavango River is representative for many large rivers throughout the developing world in that it is ungauged and poorly studied. The Okavango basin - spanning over Angola, Namibia and Botswana - represents a multi-objective problem in an international setting. Economic benefits of agricultural development and conservation of ecosystem services call for opposed actions. A semi-distributed rainfall-runoff model of the Okavango catchment is set up using the Soil and Water Assessment Tool (SWAT). The model is sufficiently physically based to simulate the impact on runoff of extent of agricultural use, crop types and management practices. Precipitation and temperature inputs are taken from datasets covering large parts of the globe. The methodology can thus easily be applied for other ungauged catchments. For temperature we use the ERA-Interim reanalysis product of the European Centre for Medium-Range Weather Forecasts and for precipitation the Famine Early Warning Systems Network data (FEWS-Net). Tropical Rainfall Measurement Mission (TRMM) data resulted in poor model performance compared to the FEWS-Net data. Presently, the upstream catchment in Angola is largely pristine and agriculture is basically restricted to dry land subsistence farming. But economic growth in Angola is likely to result in agricultural development and consequent impacts on catchment runoff. Land use scenarios that are simulated include large scale irrigated agriculture with water extractions from the river and the shallow aquifer. Climate change impacts are also studied and compared to land use change impacts. The downstream part of the basin consists of the large Okavango Wetlands, which are a biodiversity hotspot of global importance and, through tourism, an important
Pool, Sandra; Viviroli, Daniel; Seibert, Jan
Applications of runoff models usually rely on long and continuous runoff time series for model calibration. However, many catchments around the world are ungauged and estimating runoff for these catchments is challenging. One approach is to perform a few runoff measurements in a previously fully ungauged catchment and to constrain a runoff model by these measurements. In this study we investigated the value of such individual runoff measurements when taken at strategic points in time for applying a bucket-type runoff model (HBV) in ungauged catchments. Based on the assumption that a limited number of runoff measurements can be taken, we sought the optimal sampling strategy (i.e. when to measure the streamflow) to obtain the most informative data for constraining the runoff model. We used twenty gauged catchments across the eastern US, made the assumption that these catchments were ungauged, and applied different runoff sampling strategies. All tested strategies consisted of twelve runoff measurements within one year and ranged from simply using monthly flow maxima to a more complex selection of observation times. In each case the twelve runoff measurements were used to select 100 best parameter sets using a Monte Carlo calibration approach. Runoff simulations using these 'informed' parameter sets were then evaluated for an independent validation period in terms of the Nash-Sutcliffe efficiency of the hydrograph and the mean absolute relative error of the flow-duration curve. Model performance measures were normalized by relating them to an upper and a lower benchmark representing a well-informed and an uninformed model calibration. The hydrographs were best simulated with strategies including high runoff magnitudes as opposed to the flow-duration curves that were generally better estimated with strategies that captured low and mean flows. The choice of a sampling strategy covering the full range of runoff magnitudes enabled hydrograph and flow-duration curve
Wang Long; Wei Jiahua; Huang Yuefei; Wang Guangqian; Maqsood, Imran
Many urban nonpoint source pollution models utilize pollutant buildup and washoff functions to simulate storm runoff quality of urban catchments. In this paper, two urban pollutant washoff load models are derived using pollutant buildup and washoff functions. The first model assumes that there is no residual pollutant after a storm event while the second one assumes that there is always residual pollutant after each storm event. The developed models are calibrated and verified with observed data from an urban catchment in the Los Angeles County. The application results show that the developed model with consideration of residual pollutant is more capable of simulating nonpoint source pollution from urban storm runoff than that without consideration of residual pollutant. For the study area, residual pollutant should be considered in pollutant buildup and washoff functions for simulating urban nonpoint source pollution when the total runoff volume is less than 30 mm. - Highlights: → An improved urban NPS model was developed. → It performs well in areas where storm events have great temporal variation. → Threshold of total runoff volume for ignoring residual pollutant was determined. - An improved urban NPS model was developed. Threshold of total runoff volume for ignoring residual pollutant was determined.
Georgievsky, M V
This paper analyses an opportunity to integrate remote sensing data in a forecasting scheme of river inflow to the Krasnodar reservoir. MODIS MOD10A2 eight-day composite snow cover data was selected as the basic remote sensing information. Based on these data, a database which consists of maximal snow extent maps covering the Kuban river basin over the period from March 2000 to the present, along with the technique of operative monitoring of the maximal snow covered area for the main basins of the rivers flowing into the Krasnodar reservoir were developed. It was revealed that the snow cover distribution data could be useful in the prediction of flooding in the basin. In addition, the Snowmelt Runoff model, application of which is based on snow cover remote sensing data as the input information, was tested as a short-term forecasting model. The obtained results enable us to conclude that the model can be used for short-term runoff forecasts in the mountain and foothill areas of the Krasnodar reservoir basin.
Georgievsky, M V, E-mail: email@example.com [State Hydrological Institute, St Petersburg (Russian Federation)
This paper analyses an opportunity to integrate remote sensing data in a forecasting scheme of river inflow to the Krasnodar reservoir. MODIS MOD10A2 eight-day composite snow cover data was selected as the basic remote sensing information. Based on these data, a database which consists of maximal snow extent maps covering the Kuban river basin over the period from March 2000 to the present, along with the technique of operative monitoring of the maximal snow covered area for the main basins of the rivers flowing into the Krasnodar reservoir were developed. It was revealed that the snow cover distribution data could be useful in the prediction of flooding in the basin. In addition, the Snowmelt Runoff model, application of which is based on snow cover remote sensing data as the input information, was tested as a short-term forecasting model. The obtained results enable us to conclude that the model can be used for short-term runoff forecasts in the mountain and foothill areas of the Krasnodar reservoir basin.
Schattan, Paul; Bellinger, Johannes; Förster, Kristian; Schöber, Johannes; Huttenlau, Matthias; Kirnbauer, Robert; Achleitner, Stefan
Modelling water resources in snow-dominated mountainous catchments is challenging due to both, short concentration times and a highly variable contribution of snow melt in space and time from complex terrain. A number of model setups exist ranging from physically based models to conceptional models which do not attempt to represent the natural processes in a physically meaningful way. Within the flood forecasting system for the Tyrolean Inn River two serially linked hydrological models with differing process representation are used. Non- glacierized catchments are modelled by a semi-distributed, water balance model (HQsim) based on the HRU-approach. A fully-distributed energy and mass balance model (SES), purpose-built for snow- and icemelt, is used for highly glacierized headwater catchments. Previous work revealed uncertainties and limitations within the models' structures regarding (i) the representation of snow processes in HQsim, (ii) the runoff routing of SES, and (iii) the spatial resolution of the meteorological input data in both models. To overcome these limitations, a "strengths driven" model coupling is applied. Instead of linking the models serially, a vertical one-way coupling of models has been implemented. The fully-distributed snow modelling of SES is combined with the semi-distributed HQsim structure, allowing to benefit from soil and runoff routing schemes in HQsim. A monte-carlo based modelling experiment was set up to evaluate the resulting differences in the runoff prediction due to the improved model coupling and a refined spatial resolution of the meteorological forcing. The experiment design follows a gradient of spatial discretisation of hydrological processes and meteorological forcing data with a total of six different model setups for the alpine headwater basin of the Fagge River in the Tyrolean Alps. In general, all setups show a good performance for this particular basin. It is therefore planned to include other basins with differing
Peel, M. C.; Srikanthan, R.; McMahon, T. A.; Karoly, D. J.
Two key sources of uncertainty in projections of future runoff for climate change impact assessments are uncertainty between global climate models (GCMs) and within a GCM. Within-GCM uncertainty is the variability in GCM output that occurs when running a scenario multiple times but each run has slightly different, but equally plausible, initial conditions. The limited number of runs available for each GCM and scenario combination within the Coupled Model Intercomparison Project phase 3 (CMIP3) and phase 5 (CMIP5) data sets, limits the assessment of within-GCM uncertainty. In this second of two companion papers, the primary aim is to present a proof-of-concept approximation of within-GCM uncertainty for monthly precipitation and temperature projections and to assess the impact of within-GCM uncertainty on modelled runoff for climate change impact assessments. A secondary aim is to assess the impact of between-GCM uncertainty on modelled runoff. Here we approximate within-GCM uncertainty by developing non-stationary stochastic replicates of GCM monthly precipitation and temperature data. These replicates are input to an off-line hydrologic model to assess the impact of within-GCM uncertainty on projected annual runoff and reservoir yield. We adopt stochastic replicates of available GCM runs to approximate within-GCM uncertainty because large ensembles, hundreds of runs, for a given GCM and scenario are unavailable, other than the Climateprediction.net data set for the Hadley Centre GCM. To date within-GCM uncertainty has received little attention in the hydrologic climate change impact literature and this analysis provides an approximation of the uncertainty in projected runoff, and reservoir yield, due to within- and between-GCM uncertainty of precipitation and temperature projections. In the companion paper, McMahon et al. (2015) sought to reduce between-GCM uncertainty by removing poorly performing GCMs, resulting in a selection of five better performing GCMs from
Wang, Long; Wei, Jiahua; Huang, Yuefei; Wang, Guangqian; Maqsood, Imran
Many urban nonpoint source pollution models utilize pollutant buildup and washoff functions to simulate storm runoff quality of urban catchments. In this paper, two urban pollutant washoff load models are derived using pollutant buildup and washoff functions. The first model assumes that there is no residual pollutant after a storm event while the second one assumes that there is always residual pollutant after each storm event. The developed models are calibrated and verified with observed data from an urban catchment in the Los Angeles County. The application results show that the developed model with consideration of residual pollutant is more capable of simulating nonpoint source pollution from urban storm runoff than that without consideration of residual pollutant. For the study area, residual pollutant should be considered in pollutant buildup and washoff functions for simulating urban nonpoint source pollution when the total runoff volume is less than 30 mm. Copyright © 2011 Elsevier Ltd. All rights reserved.
Beck, Hylke E.; van Dijk, Albert I. J. M.; de Roo, Ad; Dutra, Emanuel; Fink, Gabriel; Orth, Rene; Schellekens, Jaap
Observed streamflow data from 966 medium sized catchments (1000-5000 km2) around the globe were used to comprehensively evaluate the daily runoff estimates (1979-2012) of six global hydrological models (GHMs) and four land surface models (LSMs) produced as part of tier-1 of the eartH2Observe project. The models were all driven by the WATCH Forcing Data ERA-Interim (WFDEI) meteorological dataset, but used different datasets for non-meteorologic inputs and were run at various spatial and temporal resolutions, although all data were re-sampled to a common 0. 5° spatial and daily temporal resolution. For the evaluation, we used a broad range of performance metrics related to important aspects of the hydrograph. We found pronounced inter-model performance differences, underscoring the importance of hydrological model uncertainty in addition to climate input uncertainty, for example in studies assessing the hydrological impacts of climate change. The uncalibrated GHMs were found to perform, on average, better than the uncalibrated LSMs in snow-dominated regions, while the ensemble mean was found to perform only slightly worse than the best (calibrated) model. The inclusion of less-accurate models did not appreciably degrade the ensemble performance. Overall, we argue that more effort should be devoted on calibrating and regionalizing the parameters of macro-scale models. We further found that, despite adjustments using gauge observations, the WFDEI precipitation data still contain substantial biases that propagate into the simulated runoff. The early bias in the spring snowmelt peak exhibited by most models is probably primarily due to the widespread precipitation underestimation at high northern latitudes.
H. E. Beck
Full Text Available Observed streamflow data from 966 medium sized catchments (1000–5000 km2 around the globe were used to comprehensively evaluate the daily runoff estimates (1979–2012 of six global hydrological models (GHMs and four land surface models (LSMs produced as part of tier-1 of the eartH2Observe project. The models were all driven by the WATCH Forcing Data ERA-Interim (WFDEI meteorological dataset, but used different datasets for non-meteorologic inputs and were run at various spatial and temporal resolutions, although all data were re-sampled to a common 0. 5° spatial and daily temporal resolution. For the evaluation, we used a broad range of performance metrics related to important aspects of the hydrograph. We found pronounced inter-model performance differences, underscoring the importance of hydrological model uncertainty in addition to climate input uncertainty, for example in studies assessing the hydrological impacts of climate change. The uncalibrated GHMs were found to perform, on average, better than the uncalibrated LSMs in snow-dominated regions, while the ensemble mean was found to perform only slightly worse than the best (calibrated model. The inclusion of less-accurate models did not appreciably degrade the ensemble performance. Overall, we argue that more effort should be devoted on calibrating and regionalizing the parameters of macro-scale models. We further found that, despite adjustments using gauge observations, the WFDEI precipitation data still contain substantial biases that propagate into the simulated runoff. The early bias in the spring snowmelt peak exhibited by most models is probably primarily due to the widespread precipitation underestimation at high northern latitudes.
Full Text Available Drought assessment is essential for coping with frequent droughts nowadays. Owing to the large spatio-temporal variations in hydrometeorology in most regions in China, it is very necessary to use a physically-based hydrological model to produce rational spatial and temporal distributions of hydro-meteorological variables for drought assessment. In this study, the large-scale distributed hydrological model Variable Infiltration Capacity (VIC was coupled with a modified standardized runoff index (SRI for drought assessment in the Weihe River basin, northwest China. The result indicates that the coupled model is capable of reasonably reproducing the spatial distribution of drought occurrence. It reflected the spatial heterogeneity of regional drought and improved the physical mechanism of SRI. This model also has potential for drought forecasting, early warning and mitigation, given that accurate meteorological forcing data are available.
Emerson, Douglas G.
A model that simulates heat and water transfer in soils during freezing and thawing periods was developed and incorporated into the U.S. Geological Survey's Precipitation-Runoff Modeling System. The transfer of heat 1s based on an equation developed from Fourier's equation for heat flux. Field capacity and infiltration rate can vary throughout the freezing and thawing period, depending on soil conditions and rate and timing of snowmelt. The transfer of water within the soil profile is based on the concept of capillary forces. The model can be used to determine the effects of seasonally frozen soils on ground-water recharge and surface-water runoff. Data collected for two winters, 1985-86 and 1986-87, on three runoff plots were used to calibrate and verify the model. The winter of 1985-86 was colder than normal and snow cover was continuous throughout the winter. The winter of 1986-87 was wanner than normal and snow accumulated for only short periods of several days.Runoff, snowmelt, and frost depths were used as the criteria for determining the degree of agreement between simulated and measured data. The model was calibrated using the 1985-86 data for plot 2. The calibration simulation agreed closely with the measured data. The verification simulations for plots 1 and 3 using the 1985-86 data and for plots 1 and 2 using the 1986-87 data agreed closely with the measured data. The verification simulation for plot 3 using the 1986-87 data did not agree closely. The recalibratlon simulations for plots 1 and 3 using the 1985-86 data Indicated small improvement because the verification simulations for plots 1 and 3 already agreed closely with the measured data.
Gosling, S. N.; Taylor, R. G.; Arnell, N. W.; Todd, M. C.
We present a comparative analysis of projected impacts of climate change on river runoff from two types of distributed hydrological model, a global hydrological model (GHM) and catchment-scale hydrological models (CHM). Analyses are conducted for six catchments that are global in coverage and feature strong contrasts in spatial scale as well as climatic and developmental conditions. These include the Liard (Canada), Mekong (SE Asia), Okavango (SW Africa), Rio Grande (Brazil), Xiangxi (China) and Harper's Brook (UK). A single GHM (Mac-PDM.09) is applied to all catchments whilst different CHMs are applied for each catchment. The CHMs include SLURP v. 12.2 (Liard), SLURP v. 12.7 (Mekong), Pitman (Okavango), MGB-IPH (Rio Grande), AV-SWAT-X 2005 (Xiangxi) and Cat-PDM (Harper's Brook). The CHMs typically simulate water resource impacts based on a more explicit representation of catchment water resources than that available from the GHM and the CHMs include river routing, whereas the GHM does not. Simulations of mean annual runoff, mean monthly runoff and high (Q5) and low (Q95) monthly runoff under baseline (1961-1990) and climate change scenarios are presented. We compare the simulated runoff response of each hydrological model to (1) prescribed increases in global-mean air temperature of 1.0, 2.0, 3.0, 4.0, 5.0 and 6.0 °C relative to baseline from the UKMO HadCM3 Global Climate Model (GCM) to explore response to different amounts of climate forcing, and (2) a prescribed increase in global-mean air temperature of 2.0 °C relative to baseline for seven GCMs to explore response to climate model structural uncertainty. We find that the differences in projected changes of mean annual runoff between the two types of hydrological model can be substantial for a given GCM (e.g. an absolute GHM-CHM difference in mean annual runoff percentage change for UKMO HadCM3 2 °C warming of up to 25%), and they are generally larger for indicators of high and low monthly runoff. However
S. N. Gosling
Full Text Available We present a comparative analysis of projected impacts of climate change on river runoff from two types of distributed hydrological model, a global hydrological model (GHM and catchment-scale hydrological models (CHM. Analyses are conducted for six catchments that are global in coverage and feature strong contrasts in spatial scale as well as climatic and developmental conditions. These include the Liard (Canada, Mekong (SE Asia, Okavango (SW Africa, Rio Grande (Brazil, Xiangxi (China and Harper's Brook (UK. A single GHM (Mac-PDM.09 is applied to all catchments whilst different CHMs are applied for each catchment. The CHMs include SLURP v. 12.2 (Liard, SLURP v. 12.7 (Mekong, Pitman (Okavango, MGB-IPH (Rio Grande, AV-SWAT-X 2005 (Xiangxi and Cat-PDM (Harper's Brook. The CHMs typically simulate water resource impacts based on a more explicit representation of catchment water resources than that available from the GHM and the CHMs include river routing, whereas the GHM does not. Simulations of mean annual runoff, mean monthly runoff and high (Q5 and low (Q95 monthly runoff under baseline (1961–1990 and climate change scenarios are presented. We compare the simulated runoff response of each hydrological model to (1 prescribed increases in global-mean air temperature of 1.0, 2.0, 3.0, 4.0, 5.0 and 6.0 °C relative to baseline from the UKMO HadCM3 Global Climate Model (GCM to explore response to different amounts of climate forcing, and (2 a prescribed increase in global-mean air temperature of 2.0 °C relative to baseline for seven GCMs to explore response to climate model structural uncertainty.
We find that the differences in projected changes of mean annual runoff between the two types of hydrological model can be substantial for a given GCM (e.g. an absolute GHM-CHM difference in mean annual runoff percentage change for UKMO HadCM3 2 °C warming of up to 25%, and they are generally larger for indicators of high and low monthly runoff
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.
Cai, Mingyong; Yang, Shengtian; Zhao, Changsen; Zhou, Qiuwen; Hou, Lipeng
Regional hydrological modeling in ungauged regions has attracted growing attention in water resources research. The southern Tibetan Plateau often suffers from data scarcity in watershed hydrological simulation and water resources assessment. This hinders further research characterizing the water cycle and solving international water resource issues in the area. In this study, a multi-spatial data based Distributed Time-Variant Gain Model (MS-DTVGM) is applied to the Yarlung Zangbo River basin, an important international river basin in the southern Tibetan Plateau with limited meteorological data. This model is driven purely by spatial data from multiple sources and is independent of traditional meteorological data. Based on the methods presented in this study, daily snow cover and potential evapotranspiration data in the Yarlung Zangbo River basin in 2050 are obtained. Future (2050) climatic data (precipitation and air temperature) from the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR5) are used to study the hydrological response to climate change. The result shows that river runoff will increase due to precipitation and air temperature changes by 2050. Few differences are found between daily runoff simulations from different Representative Concentration Pathway (RCP) scenarios (RCP2.6, RCP4.5 and RCP8.5) for 2050. Historical station observations (1960-2000) at Nuxia and model simulations for two periods (2006-2009 and 2050) are combined to study inter-annual and intra-annual runoff distribution and variability. The inter-annual runoff variation is stable and the coefficient of variation (CV) varies from 0.21 to 0.27. In contrast, the intra-annual runoff varies significantly with runoff in summer and autumn accounting for more than 80% of the total amount. Compared to the historical period (1960-2000), the present period (2006-2009) has a slightly uneven intra-annual runoff temporal distribution, and becomes more balanced in
Full Text Available Regional hydrological modeling in ungauged regions has attracted growing attention in water resources research. The southern Tibetan Plateau often suffers from data scarcity in watershed hydrological simulation and water resources assessment. This hinders further research characterizing the water cycle and solving international water resource issues in the area. In this study, a multi-spatial data based Distributed Time-Variant Gain Model (MS-DTVGM is applied to the Yarlung Zangbo River basin, an important international river basin in the southern Tibetan Plateau with limited meteorological data. This model is driven purely by spatial data from multiple sources and is independent of traditional meteorological data. Based on the methods presented in this study, daily snow cover and potential evapotranspiration data in the Yarlung Zangbo River basin in 2050 are obtained. Future (2050 climatic data (precipitation and air temperature from the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR5 are used to study the hydrological response to climate change. The result shows that river runoff will increase due to precipitation and air temperature changes by 2050. Few differences are found between daily runoff simulations from different Representative Concentration Pathway (RCP scenarios (RCP2.6, RCP4.5 and RCP8.5 for 2050. Historical station observations (1960-2000 at Nuxia and model simulations for two periods (2006-2009 and 2050 are combined to study inter-annual and intra-annual runoff distribution and variability. The inter-annual runoff variation is stable and the coefficient of variation (CV varies from 0.21 to 0.27. In contrast, the intra-annual runoff varies significantly with runoff in summer and autumn accounting for more than 80% of the total amount. Compared to the historical period (1960-2000, the present period (2006-2009 has a slightly uneven intra-annual runoff temporal distribution, and becomes more
Christiansen, Daniel E.
The U.S. Geological Survey, in cooperation with the Iowa Department of Natural Resources, conducted a study to examine techniques for estimation of daily streamflows using hydrological models and statistical methods. This report focuses on the use of a hydrologic model, the U.S. Geological Survey's Precipitation-Runoff Modeling System, to estimate daily streamflows at gaged and ungaged locations. The Precipitation-Runoff Modeling System is a modular, physically based, distributed-parameter modeling system developed to evaluate the impacts of various combinations of precipitation, climate, and land use on surface-water runoff and general basin hydrology. The Cedar River Basin was selected to construct a Precipitation-Runoff Modeling System model that simulates the period from January 1, 2000, to December 31, 2010. The calibration period was from January 1, 2000, to December 31, 2004, and the validation periods were from January 1, 2005, to December 31, 2010 and January 1, 2000 to December 31, 2010. A Geographic Information System tool was used to delineate the Cedar River Basin and subbasins for the Precipitation-Runoff Modeling System model and to derive parameters based on the physical geographical features. Calibration of the Precipitation-Runoff Modeling System model was completed using a U.S. Geological Survey calibration software tool. The main objective of the calibration was to match the daily streamflow simulated by the Precipitation-Runoff Modeling System model with streamflow measured at U.S. Geological Survey streamflow gages. The Cedar River Basin daily streamflow model performed with a Nash-Sutcliffe efficiency ranged from 0.82 to 0.33 during the calibration period, and a Nash-Sutcliffe efficiency ranged from 0.77 to -0.04 during the validation period. The Cedar River Basin model is meeting the criteria of greater than 0.50 Nash-Sutcliffe and is a good fit for streamflow conditions for the calibration period at all but one location, Austin, Minnesota
Ely, D. Matthew
Recharge is a vital component of the ground-water budget and methods for estimating it range from extremely complex to relatively simple. The most commonly used techniques, however, are limited by the scale of application. One method that can be used to estimate ground-water recharge includes process-based models that compute distributed water budgets on a watershed scale. These models should be evaluated to determine which model parameters are the dominant controls in determining ground-water recharge. Seven existing watershed models from different humid regions of the United States were chosen to analyze the sensitivity of simulated recharge to model parameters. Parameter sensitivities were determined using a nonlinear regression computer program to generate a suite of diagnostic statistics. The statistics identify model parameters that have the greatest effect on simulated ground-water recharge and that compare and contrast the hydrologic system responses to those parameters. Simulated recharge in the Lost River and Big Creek watersheds in Washington State was sensitive to small changes in air temperature. The Hamden watershed model in west-central Minnesota was developed to investigate the relations that wetlands and other landscape features have with runoff processes. Excess soil moisture in the Hamden watershed simulation was preferentially routed to wetlands, instead of to the ground-water system, resulting in little sensitivity of any parameters to recharge. Simulated recharge in the North Fork Pheasant Branch watershed, Wisconsin, demonstrated the greatest sensitivity to parameters related to evapotranspiration. Three watersheds were simulated as part of the Model Parameter Estimation Experiment (MOPEX). Parameter sensitivities for the MOPEX watersheds, Amite River, Louisiana and Mississippi, English River, Iowa, and South Branch Potomac River, West Virginia, were similar and most sensitive to small changes in air temperature and a user-defined flow
Hur, Sungchul; Nam, Kisung; Kim, Jungsoo; Kwak, Changjae
An urban runoff model that is able to compute the runoff, the pollutant loadings, and the concentrations of water-quality constituents in urban drainages during the first flush was developed. This model, which is referred to as FFC-QUAL, was modified from the existing ILLUDAS model and added for use during the water-quality analysis process for dry and rainy periods. For the dry period, the specifications of the coefficients for the discharge and water quality were used. During rainfall, we used the Clark and time-area methods for the runoff analyses of pervious and impervious areas to consider the effects of the subbasin shape; moreover, four pollutant accumulation methods and the washoff equation for computing the water quality each time were used. According to the verification results, FFC-QUAL provides generally similar output as the measured data for the peak flow, total runoff volume, total loadings, peak concentration, and time of peak concentration for three rainfall events in the Gunja subbasin. In comparison with the ILLUDAS, SWMM, and MOUSE models, there is little difference between these models and the model developed in this study. The proposed model should be useful in urban watersheds because of its simplicity and its capacity to model common pollutants (e.g., biological oxygen demand, chemical oxygen demand, Escherichia coli, suspended solids, and total nitrogen and phosphorous) in runoff. The proposed model can also be used in design studies to determine how changes in infrastructure will affect the runoff and pollution loads. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.
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.
Mufeti, P.; Rientjes, T.H.M.; Mabande, P.; Maathuis, B.H.P.
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
A. E. Sikorska
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.
The glaciers in western Karakoram are important for freshwater supply in the rivers of Pakistan. Global warming influences the future water supply from glaciers. In order to study the hydrological conditions and possible impacts of climate change, runoff simulations are performed for the Hunza basin. The hydrological modelling system SRM (Snowmelt Runoff Model) is customized and applied to the Hunza basin. Various data obtained from satellite remote sensing imagery and meteorological stations in the study area are processed, prepared and used as input to SRM. For runoff simulations the basin is divided into five sub-basins. The (sub-) basins are defined by the hydrological response units (HRU) based on the elevation zones and land-cover types. The spatially distributed data are aggregated HRU-wise as input for the model simulations. The energy available for snow and glacier melt is parameterized in SRM by degree day factors which are defined separately for seasonal snow, ice and debris covered glaciers. The model is calibrated for the Hunza basin using the meteorological and remote sensing data from years 2002 and 2003. The daily runoff is simulated and compared with the measured discharge data obtained from the power company. The Nash-Sutcliffe correlation coefficient of simulated versus measured runoff data is 0.87 for year 2002 and 0.96 for year 2003 which indicates a good agreement. An estimation of mass balance of Baltoro glacier is made using the meteorological data from Shigar station applying the hydrological method to estimate accumulation and melt. Based on these data is found that Baltoro glacier has slightly negative mass balance. The ablation rates of debris covered parts of Baltoro glacier at 4150 m elevation are estimated to be between 3 and 4 cm per day. However, the uncertainty in mass balance modelling is high due to poor knowledge of accumulation inferred by spatial extrapolation from station data.Keeping the glacier area unchanged, for the 2002
Assessment of CREAMS [Chemicals, Runoff, and Erosion from Agricultural Management Systems] and ERHYM-II [Ekalaka Rangeland Hydrology and Yield Model] computer models for simulating soil water movement on the Idaho National Engineering Laboratory
The major goal of radioactive waste management is long-term containment of radioactive waste. Long-term containment is dependent on understanding water movement on, into, and through trench caps. Several computer simulation models are available for predicting water movement. Of the several computer models available, CREAMS (Chemicals, Runoff, and Erosion from Agricultural Management Systems) and ERHYM-II (Ekalaka Rangeland Hydrology and Yield Model) were tested for use on the Idaho National Engineering Laboratory (INEL). The models were calibrated, tested for sensitivity, and used to evaluate some basic trench cap designs. Each model was used to postdict soil moisture, evapotranspiration, and runoff of two watersheds for which such data were already available. Sensitivity of the models was tested by adjusting various input parameters from high to low values and then comparing model outputs to those generated from average values. Ten input parameters of the CREAMS model were tested for sensitivity. 17 refs., 23 figs., 20 tabs
Barbaro, Jeffrey R.; Zarriello, Phillip J.
A Hydrological Simulation Program-FORTRAN (HSPF) precipitation-runoff model of the Blackstone River Basin was developed and calibrated to study the effects of changing land- and water-use patterns on water resources. The 474.5 mi2 Blackstone River Basin in southeastern Massachusetts and northern Rhode Island is experiencing rapid population and commercial growth throughout much of its area. This growth and the corresponding changes in land-use patterns are increasing stress on water resources and raising concerns about the future availability of water to meet residential and commercial needs. Increased withdrawals and wastewater-return flows also could adversely affect aquatic habitat, water quality, and the recreational value of the streams in the basin. The Blackstone River Basin was represented by 19 hydrologic response units (HRUs): 17 types of pervious areas (PERLNDs) established from combinations of surficial geology, land-use categories, and the distribution of public water and public sewer systems, and two types of impervious areas (IMPLNDs). Wetlands were combined with open water and simulated as stream reaches that receive runoff from surrounding pervious and impervious areas. This approach was taken to achieve greater flexibility in calibrating evapotranspiration losses from wetlands during the growing season. The basin was segmented into 50 reaches (RCHRES) to represent junctions at tributaries, major lakes and reservoirs, and drainage areas to streamflow-gaging stations. Climatological, streamflow, water-withdrawal, and wastewater-return data were collected during the study to develop the HSPF model. Climatological data collected at Worcester Regional Airport in Worcester, Massachusetts and T.F. Green Airport in Warwick, Rhode Island, were used for model calibration. A total of 15 streamflow-gaging stations were used in the calibration. Streamflow was measured at eight continuous-record streamflow-gaging stations that are part of the U.S. Geological
Talei, Amin; Chua, Lloyd Hock Chye; Quek, Chai; Jansson, Per-Erik
SummaryA study using local learning Neuro-Fuzzy System (NFS) was undertaken for a rainfall-runoff modeling application. The local learning model was first tested on three different catchments: an outdoor experimental catchment measuring 25 m2 (Catchment 1), a small urban catchment 5.6 km2 in size (Catchment 2), and a large rural watershed with area of 241.3 km2 (Catchment 3). The results obtained from the local learning model were comparable or better than results obtained from physically-based, i.e. Kinematic Wave Model (KWM), Storm Water Management Model (SWMM), and Hydrologiska Byråns Vattenbalansavdelning (HBV) model. The local learning algorithm also required a shorter training time compared to a global learning NFS model. The local learning model was next tested in real-time mode, where the model was continuously adapted when presented with current information in real time. The real-time implementation of the local learning model gave better results, without the need for retraining, when compared to a batch NFS model, where it was found that the batch model had to be retrained periodically in order to achieve similar results.
Dams, J.; Nossent, J.; Senbeta, T. B.; Willems, P.; Batelaan, O.
The assessment of climate change impacts on hydrology is subject to uncertainties related to the climate change scenarios, stochastic uncertainties of the hydrological model and structural uncertainties of the hydrological model. This paper focuses on the contribution of structural uncertainty of hydrological models to the overall uncertainty of the climate change impact assessment. To quantify the structural uncertainty of hydrological models, four physically based hydrological models (SWAT, PRMS and a semi- and fully distributed version of the WetSpa model) are set up for a catchment in Belgium. Each model is calibrated using four different objective functions. Three climate change scenarios with a high, mean and low hydrological impact are statistically perturbed from a large ensemble of climate change scenarios and are used to force the hydrological models. This methodology allows assessing and comparing the uncertainty introduced by the climate change scenarios with the uncertainty introduced by the hydrological model structure. Results show that the hydrological model structure introduces a large uncertainty on both the average monthly discharge and the extreme peak and low flow predictions under the climate change scenarios. For the low impact climate change scenario, the uncertainty range of the mean monthly runoff is comparable to the range of these runoff values in the reference period. However, for the mean and high impact scenarios, this range is significantly larger. The uncertainty introduced by the climate change scenarios is larger than the uncertainty due to the hydrological model structure for the low and mean hydrological impact scenarios, but the reverse is true for the high impact climate change scenario. The mean and high impact scenarios project increasing peak discharges, while the low impact scenario projects increasing peak discharges only for peak events with return periods larger than 1.6 years. All models suggest for all scenarios a
Tong, Juxiu; Hu, Bill X; Yang, Jinzhong; Zhu, Yan
The mixing layer theory is not suitable for predicting solute transfer from initially saturated soil to surface runoff water under controlled drainage conditions. By coupling the mixing layer theory model with the numerical model Hydrus-1D, a hybrid solute transfer model has been proposed to predict soil solute transfer from an initially saturated soil into surface water, under controlled drainage water conditions. The model can also consider the increasing ponding water conditions on soil surface before surface runoff. The data of solute concentration in surface runoff and drainage water from a sand experiment is used as the reference experiment. The parameters for the water flow and solute transfer model and mixing layer depth under controlled drainage water condition are identified. Based on these identified parameters, the model is applied to another initially saturated sand experiment with constant and time-increasing mixing layer depth after surface runoff, under the controlled drainage water condition with lower drainage height at the bottom. The simulation results agree well with the observed data. Study results suggest that the hybrid model can accurately simulate the solute transfer from initially saturated soil into surface runoff under controlled drainage water condition. And it has been found that the prediction with increasing mixing layer depth is better than that with the constant one in the experiment with lower drainage condition. Since lower drainage condition and deeper ponded water depth result in later runoff start time, more solute sources in the mixing layer are needed for the surface water, and larger change rate results in the increasing mixing layer depth.
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
Piacentini, A.; Ricci, S. M.; Thual, O.; Coustau, M.; Marchandise, A.
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
Models exist for calculating overland flow on hillsides but no models have been found which explicitly deal with runoff from armored slopes. Flow on armored slopes differs from overland flow, because substantial flow occurs beneath the surface of the rock layer at low runnoff, and both above and below the surface for high runoff. In addition to the lack of a suitable model, no estimates of the PMP exist for such small areas and for very short durations. This paper develops a model for calculating runoff from armored embankments. The model considers the effect of slope, drainage area and ''flow concentration'' caused by irregular grading or slumping. A rainfall-duration curve based on the PMP is presented which is suitable for very small drainage areas. The development of the runoff model and rainfall-duration curve is presented below, along with a demonstration of the model on the design of a hypothetical tailings embankment
Birkel, Christian; Broder, Tanja; Biester, Harald
Peat soils act as important carbon sinks, but they also release large amounts of dissolved organic carbon (DOC) to the aquatic system. The DOC export is strongly tied to the export of soluble heavy metals. The accumulation of potentially toxic substances due to anthropogenic activities, and their natural export from peat soils to the aquatic system is an important health and environmental issue. However, limited knowledge exists as to how much of these substances are mobilized, how they are mobilized in terms of flow pathways and under which hydrometeorological conditions. In this study, we report from a combined experimental and modelling effort to provide greater process understanding from a small, lead (Pb) and arsenic (As) contaminated upland peat catchment in northwestern Germany. We developed a minimally parameterized, but process-based, coupled hydrology-biogeochemistry model applied to simulate detailed hydrometric and biogeochemical data. The model was based on an initial data mining analysis, in combination with regression relationships of discharge, DOC and element export. We assessed the internal model DOC-processing based on stream-DOC hysteresis patterns and 3-hourly time step groundwater level and soil DOC data (not used for calibration as an independent model test) for two consecutive summer periods in 2013 and 2014. We found that Pb and As mobilization can be efficiently predicted from DOC transport alone, but Pb showed a significant non-linear relationship with DOC, while As was linearly related to DOC. The relatively parsimonious model (nine calibrated parameters in total) showed the importance of non-linear and rapid near-surface runoff-generation mechanisms that caused around 60% of simulated DOC load. The total load was high even though these pathways were only activated during storm events on average 30% of the monitoring time - as also shown by the experimental data. Overall, the drier period 2013 resulted in increased nonlinearity, but
Yuan, Yu-zhi; Zhang, Zheng-dong; Meng, Jin-hua
SWAT model, an extensively used distributed hydrological model, was used to quantitatively analyze the influences of changes in land use and climate on the runoff at watershed scale. Liuxihe Watershed' s SWAT model was established and three scenarios were set. The calibration and validation at three hydrological stations of Wenquan, Taipingchang and Nangang showed that the three factors of Wenquan station just only reached the standard in validated period, and the other two stations had relative error (RE) 0.8 and Nash-Sutcliffe efficiency valve (Ens) > 0.75, suggesting that SWAT model was appropriate for simulating runoff response to land use change and climate variability in Liuxihe watershed. According to the integrated scenario simulation, the annual runoff increased by 11.23 m3 x s(-1) from 2001 to 2010 compared with the baseline period from 1991 to 2000, among which, the land use change caused an annual runoff reduction of 0.62 m3 x s(-1), whereas climate variability caused an annual runoff increase of 11.85 m3 x s(-1). Apparently, the impact of climate variability was stronger than that of land use change. On the other hand, the scenario simulation of extreme land use showed that compared with the land use in 2000, the annual runoff of the farmland scenario and the grassland scenario increased by 2.7% and 0.5% respectively, while that of the forest land scenario were reduced by 0.7%, which suggested that forest land had an ability of diversion closure. Furthermore, the scenario simulation of climatic variability indicated that the change of river runoff correlated positively with precipitation change (increase of 11.6% in annual runoff with increase of 10% in annual precipitation) , but negatively with air temperature change (reduction of 0.8% in annual runoff with increase of 1 degrees C in annual mean air temperature), which showed that the impact of precipitation variability was stronger than that of air temperature change. Therefore, in face of climate
Garcia Leal, Julio A.; Lopez-Baeza, Ernesto; Khodayar, Samiro; Estrela, Teodoro; Fidalgo, Arancha; Gabaldo, Onofre; Kuligowski, Robert; Herrera, Eddy
Surface runoff is defined as the amount of water that originates from precipitation, does not infiltrates due to soil saturation and therefore circulates over the surface. A good estimation of runoff is useful for the design of draining systems, structures for flood control and soil utilisation. For runoff estimation there exist different methods such as (i) rational method, (ii) isochrone method, (iii) triangular hydrograph, (iv) non-dimensional SCS hydrograph, (v) Temez hydrograph, (vi) kinematic wave model, represented by the dynamics and kinematics equations for a uniforme precipitation regime, and (vii) SCS-CN (Soil Conservation Service Curve Number) model. This work presents a way of estimating precipitation runoff through the SCS-CN model, using SMOS (Soil Moisture and Ocean Salinity) mission soil moisture observations and rain-gauge measurements, as well as satellite precipitation estimations. The area of application is the Jucar River Basin Authority area where one of the objectives is to develop the SCS-CN model in a spatial way. The results were compared to simulations performed with the 7-km COSMO-CLM (COnsortium for Small-scale MOdelling, COSMO model in CLimate Mode) model. The use of SMOS soil moisture as input to the COSMO-CLM model will certainly improve model simulations.
Todorovic, Andrijana; Plavsic, Jasna
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
Mishra, S. K.; Jain, M. K.; Pandey, R. P.; Singh, V. P.
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.
Locatelli, Luca; Gabriel, Søren; Mark, Ole; Mikkelsen, Peter Steen; Arnbjerg-Nielsen, Karsten; Taylor, Heidi; Bockhorn, Britta; Larsen, Hauge; Kjølby, Morten Just; Blicher, Anne Steensen; Binning, Philip John
Stormwater management using water sensitive urban design is expected to be part of future drainage systems. This paper aims to model the combination of local retention units, such as soakaways, with subsurface detention units. Soakaways are employed to reduce (by storage and infiltration) peak and volume stormwater runoff; however, large retention volumes are required for a significant peak reduction. Peak runoff can therefore be handled by combining detention units with soakaways. This paper models the impact of retrofitting retention-detention units for an existing urbanized catchment in Denmark. The impact of retrofitting a retention-detention unit of 3.3 m³/100 m² (volume/impervious area) was simulated for a small catchment in Copenhagen using MIKE URBAN. The retention-detention unit was shown to prevent flooding from the sewer for a 10-year rainfall event. Statistical analysis of continuous simulations covering 22 years showed that annual stormwater runoff was reduced by 68-87%, and that the retention volume was on average 53% full at the beginning of rain events. The effect of different retention-detention volume combinations was simulated, and results showed that allocating 20-40% of a soakaway volume to detention would significantly increase peak runoff reduction with a small reduction in the annual runoff.
Buch, A. M.; Narain, A.; Pandey, P. C.
The simulation of runoff from a Himalayan Glacier basin using an Artificial Neural Network (ANN) is presented. The performance of the ANN model is found to be superior to the Energy Balance Model and the Multiple Regression model. The RMS Error is used as the figure of merit for judging the performance of the three models, and the RMS Error for the ANN model is the latest of the three models. The ANN is faster in learning and exhibits excellent system generalization characteristics.
Emerson, Douglas G.
A model that simulates heat and water transfer in soils during freezing and thawing periods was developed and incorporated into the U.S. Geological Survey's Precipitation-Runoff Modeling System. The model's transfer of heat is based on an equation developed from Fourier's equation for heat flux. The model's transfer of water within the soil profile is based on the concept of capillary forces. Field capacity and infiltration rate can vary throughout the freezing and thawing period, depending on soil conditions and rate and timing of snowmelt. The model can be used to determine the effects of seasonally frozen soils on ground-water recharge and surface-water runoff. Data collected for two winters, 1985-86 and 1986-87, on three runoff plots were used to calibrate and verify the model. The winter of 1985-86 was colder than normal, and snow cover was continuous throughout the winter. The winter of 1986-87 was warmer than normal, and snow accumulated for only short periods of several days. as the criteria for determining the degree of agreement between simulated and measured data. The model was calibrated using the 1985-86 data for plot 2. The calibration simulation agreed closely with the measured data. The verification simulations for plots 1 and 3 using the 1985-86 data and for plots 1 and 2 using the 1986-87 data agreed closely with the measured data. The verification simulation for plot 3 using the 1986-87 data did not agree closely. The recalibration simulations for plots 1 and 3 using the 1985-86 data indicated little improvement because the verification simulations for plots 1 and 3 already agreed closely with the measured data.
R. J. Moore
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
Marçais, J.; Gupta, H. V.; De Dreuzy, J. R.; Troch, P. A. A.
Geomorphological structure and geological heterogeneity of hillslopes are major controls on runoff responses. The diversity of hillslopes (morphological shapes and geological structures) on one hand, and the highly non linear runoff mechanism response on the other hand, make it difficult to transpose what has been learnt at one specific hillslope to another. Therefore, making reliable predictions on runoff appearance or river flow for a given hillslope is a challenge. Applying a classic model calibration (based on inverse problems technique) requires doing it for each specific hillslope and having some data available for calibration. When applied to thousands of cases it cannot always be promoted. Here we propose a novel modeling framework based on coupling process based models with data based approach. First we develop a mechanistic model, based on hillslope storage Boussinesq equations (Troch et al. 2003), able to model non linear runoff responses to rainfall at the hillslope scale. Second we set up a model database, representing thousands of non calibrated simulations. These simulations investigate different hillslope shapes (real ones obtained by analyzing 5m digital elevation model of Brittany and synthetic ones), different hillslope geological structures (i.e. different parametrizations) and different hydrologic forcing terms (i.e. different infiltration chronicles). Then, we use this model library to train a machine learning model on this physically based database. Machine learning model performance is then assessed by a classic validating phase (testing it on new hillslopes and comparing machine learning with mechanistic outputs). Finally we use this machine learning model to learn what are the hillslope properties controlling runoffs. This methodology will be further tested combining synthetic datasets with real ones.
A. P. Jacquin
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.
Im, Sangjun; Brannan, Kevin M; Mostaghimi, Saied; Kim, Sang Min
A watershed model can be used to better understand the relationship between land use activities and hydrologic/water quality processes that occur within a watershed. The physically based, distributed parameter model (SWAT) and a conceptual, lumped parameter model (HSPF), were selected and their performance were compared in simulating runoff and sediment yields from the Polecat Creek watershed in Virginia, which is 12,048 ha in size. A monitoring project was conducted in Polecat Creek watershed during the period of October 1994 to June 2000. The observed data (stream flow and sediment yield) from the monitoring project was used in the calibration/validations of the models. The period of September 1996 to June 2000 was used for the calibration and October 1994 to December 1995 was used for the validation of the models. The outputs from the models were compared to the observed data at several sub-watershed outlets and at the watershed outlet of the Polecat Creek watershed. The results indicated that both models were generally able to simulate stream flow and sediment yields well during both the calibration/validation periods. For annual and monthly loads, HSPF simulated hydrologic and sediment yield more accurately than SWAT at all monitoring sites within the watershed. The results of this study indicate that both the SWAT and HSPF watershed models performed sufficiently well in the simulation of stream flow and sediment yield with HSPF performing moderately better than SWAT for simulation time-steps greater than a month.
Haberlandt, U.; Radtke, I.
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.
Liu, Dongdong; She, Dongli
Current physically based erosion models do not carefully consider the dynamic variations of soil properties during rainfall and are unable to simulate saline-sodic soil slope erosion processes. The aim of this work was to build upon a complete model framework, SSEM, to simulate runoff and erosion processes for saline-sodic soils by coupling dynamic saturated hydraulic conductivity Ks and soil erodibility Kτ. Sixty rainfall simulation rainfall experiments (2 soil textures × 5 sodicity levels × 2 slope gradients × 3 duplicates) provided data for model calibration and validation. SSEM worked very well for simulating the runoff and erosion processes of saline-sodic silty clay. The runoff and erosion processes of saline-sodic silt loam were more complex than those of non-saline soils or soils with higher clay contents; thus, SSEM did not perform very well for some validation events. We further examined the model performances of four concepts: Dynamic Ks and Kτ (Case 1, SSEM), Dynamic Ks and Constant Kτ (Case 2), Constant Ks and Dynamic Kτ (Case 3) and Constant Ks and Constant Kτ (Case 4). The results demonstrated that the model, which considers dynamic variations in soil saturated hydraulic conductivity and soil erodibility, can provide more reasonable runoff and erosion prediction results for saline-sodic soils.
Giesen, van de N.C.; Stomph, T.J.; Ridder, de N.
Measurements of surface runoff from uniform slopes of different lengths in West Africa have shown that longer slopes tend to have less runoff per unit of length than short slopes. The main reason for this scale effect is that once the rain stops, water on long slopes has more opportunity time to
Borup, Morten; Grum, Morten; Mikkelsen, Peter Steen
When an online runoff model is updated from system measurements, the requirements of the precipitation input change. Using rain gauge data as precipitation input there will be a displacement between the time when the rain hits the gauge and the time where the rain hits the actual catchment, due to the time it takes for the rain cell to travel from the rain gauge to the catchment. Since this time displacement is not present for system measurements the data assimilation scheme might already have updated the model to include the impact from the particular rain cell when the rain data is forced upon the model, which therefore will end up including the same rain twice in the model run. This paper compares forecast accuracy of updated models when using time displaced rain input to that of rain input with constant biases. This is done using a simple time-area model and historic rain series that are either displaced in time or affected with a bias. The results show that for a 10 minute forecast, time displacements of 5 and 10 minutes compare to biases of 60 and 100%, respectively, independent of the catchments time of concentration.
Connolly, R D; Kennedy, I R; Silburn, D M; Simpson, B W; Freebairn, D M
Endosulfan (6,7,8,9,10,10-hexachloro-1,5,5a,6,9,9a-hexahydro-6,9methano-2,4,3-benzodioxathiepin 3-oxide), a pesticide that is highly toxic to aquatic organisms, is widely used in the cotton (Gossypium hirsutum L.) industry in Australia and is a risk to the downstream riverine environment. We used the GLEAMS model to evaluate the effectiveness of a range of management scenarios aimed at minimizing endosulfan transport in runoff at the field scale. The field management scenarios simulated were (i) Conventional, bare soil at the beginning of the cotton season and seven irrigations per season; (ii) Improved Irrigation, irrigation amounts reduced and frequency increased to reduce runoff from excess irrigation; (iii) Dryland, no irrigation; (iv) Stubble Retained, increased soil cover created by retaining residue from the previous crop or a specially planted winter cover crop; and (v) Reduced Sprays, a fewer number of sprays. Stubble Retained was the most effective scenario for minimizing endosulfan transport because infiltration was increased and erosion reduced, and the stubble intercepted and neutralized a proportion of the applied endosulfan. Reducing excess irrigation reduced annual export rates by 80 to 90%, but transport in larger storm events was still high. Reducing the number of pesticide applications only reduced transport when three or fewer sprays were applied. We conclude that endosulfan transport from cotton farms can be minimized with a combination of field management practices that reduce excess irrigation and concentration of pesticide on the soil at any point in time; however, discharges, probably with endosulfan concentrations exceeding guideline values, will still occur in storm events.
Zhao, Chen; Wang, Chong-Chen; Li, Jun-Qi; Wang, Peng; Ou, Jia-Qi; Cui, Jing-Rui
Dissolved organic matter (DOM) can strongly interact with both organic and inorganic contaminants to influence their transportation, transformation, bioavailability, toxicity and even their ultimate fate. Within this work, DOM was extracted from urban stormwater runoff samples collected from a regular sampling site of a typical residential area in Beijing, China. Copper(II) ions were selected as model to investigate the interactions between DOM and typical heavy metals. Both ultraviolet (UV) absorbance and fluorescence titration methods were introduced to determine the complex capacities (C L ) and conditional stability constants (log K M ) of bonding between DOM and copper (II) ions, which revealed that the values of C L were 85.62 and 87.23 μmol mg -1 and the log K M values were 5.37 and 5.48, respectively. The results suggested the successful complexation between DOM and copper(II) ions. Furthermore, morphology of the DOM binding to copper(II) ions was confirmed by both energy-dispersive X-ray spectroscopy (EDX) and X-ray photoelectron spectroscopy (XPS), which can facilitate to clarify the corresponding mechanism. The Cu 2p 3/2 peak at 933.7 eV and the characteristic shake-up peaks of Cu-O were found in the XPS spectra, implying that copper(II) ions might coordinate with hydroxyl (aliphatic or phenolic) or carboxyl groups. With these profitable results, it can be concluded that DOM in urban stormwater runoff has a strong binding affinity with copper(II) ions, which may further lead to potentially significant influence on their migration and transformation.
Eck, Van Christel M.; Nunes, Joao P.; Vieira, Diana C.S.; Keesstra, Saskia; Keizer, Jan Jacob
Forest fires are a recurrent phenomenon in Mediterranean forests, with impacts for human landscapes and communities, which must be understood before they can be managed. This study used the physically based Limburg Soil Erosion Model (LISEM) to simulate rainfall–runoff response, under soil water
Singh, N. K.; Emanuel, R. E.; McGlynn, B. L.
The combined influence of topography and vegetation on runoff generation and streamflow in headwater catchments remains unclear. We aim to understand how spatial, hydrological and climate variables affect runoff generation and streamflow at hillslope and watershed scales at the Coweeta Hydrologic Laboratory (CHL) in the southern Appalachian Mountains by analyzing stable isotopes of hydrogen (2H) and oxygen (18O) coupled with measurements of hydrological variables (stream discharge, soil moisture, shallow groundwater) and landscape variables (upslope accumulated area, vegetation density slope, and aspect). We investigated four small catchments, two of which contained broadleaf deciduous vegetation and two of which contained evergreen coniferous vegetation. Beginning in June 2011, we collected monthly water samples at 25 m intervals along each stream, monthly samples from 24 shallow groundwater wells, and weekly to monthly samples from 10 rain gauges distributed across CHL. Water samples were analyzed for 2H and 18O using cavity ring-down spectroscopy. During the same time period we recorded shallow groundwater stage at 30 min intervals from each well, and beginning in fall 2011 we collected volumetric soil moisture data at 30 min intervals from multiple depths at 16 landscape positions. Results show high spatial and temporal variability in δ2H and δ18O within and among streams, but in general we found isotopic enrichment with increasing contributing area along each stream. We used a combination of hydrometric observations and geospatial analyses to understand why stream isotope patterns varied during the year and among watersheds, and we used complementary measurements of δ2H and δ18O from other pools within the watersheds to understand the movement and mixing of precipitation that precedes runoff formation. This combination of high resolution stable isotope data and hydrometric observations facilitates a clearer understanding of spatial controls on streamflow
One of today's challenges in the field of modeling and simulation is to model increasingly larger and more complex systems. Complex models take long to develop and incur high costs. With the advances in data collection technologies and more popular use of computer-aided systems, more data has become
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
Piccolroaz, S.; Di Lazzaro, M.; Zarlenga, A.; Majone, B.; Bellin, A.; Fiori, A.
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
Haj, Adel E.; Christiansen, Daniel E.; Hutchinson, Kasey J.
The U.S. Geological Survey, in cooperation with the Iowa Department of Natural Resources, constructed Precipitation-Runoff Modeling System models to estimate daily streamflow for nine river basins in eastern Iowa that drain into the Mississippi River. The models are part of a suite of methods for estimating daily streamflow at ungaged sites. The Precipitation-Runoff Modeling System is a deterministic, distributed- parameter, physical-process-based modeling system developed to evaluate the response of streamflow and general drainage basin hydrology to various combinations of climate and land use. Calibration and validation periods used in each basin mostly were October 1, 2002, through September 30, 2012, but differed depending on the period of record available for daily mean streamflow measurements at U.S. Geological Survey streamflow-gaging stations.
Hazenberg, P.; Leijnse, H.; Torfs, P.; Uijlenhoet, R.; Weerts, A.; Reggiani, P.; Delobbe, L.
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
Zhou, J.; Zeng, X.; Mo, L.; Chen, L.; Jiang, Z.; Feng, Z.; Yuan, L.; He, Z.
Generally, the adaptive utilization and regulation of runoff in the source region of China's southwest rivers is classified as a typical multi-objective collaborative optimization problem. There are grim competitions and incidence relation in the subsystems of water supply, electricity generation and environment, which leads to a series of complex problems represented by hydrological process variation, blocked electricity output and water environment risk. Mathematically, the difficulties of multi-objective collaborative optimization focus on the description of reciprocal relationships and the establishment of evolving model of adaptive systems. Thus, based on the theory of complex systems science, this project tries to carry out the research from the following aspects: the changing trend of coupled water resource, the covariant factor and driving mechanism, the dynamic evolution law of mutual feedback dynamic process in the supply-generation-environment coupled system, the environmental response and influence mechanism of coupled mutual feedback water resource system, the relationship between leading risk factor and multiple risk based on evolutionary stability and dynamic balance, the transfer mechanism of multiple risk response with the variation of the leading risk factor, the multidimensional coupled feedback system of multiple risk assessment index system and optimized decision theory. Based on the above-mentioned research results, the dynamic method balancing the efficiency of multiple objectives in the coupled feedback system and optimized regulation model of water resources is proposed, and the adaptive scheduling mode considering the internal characteristics and external response of coupled mutual feedback system of water resource is established. In this way, the project can make a contribution to the optimal scheduling theory and methodology of water resource management under uncertainty in the source region of Southwest River.
Byrne, J.; Kienzle, S.W.; MacDonald, R.J.
An understanding of local variability in climatic conditions over complex terrain is imperative to making accurate assessments of impacts from climate change on fresh water ecosystems (Daly, 2006). The derivation of representative spatial data in diverse environments poses a significant challenge to the modelling community. This presentation describes the current status of a long term ongoing hydro-climate model development program. We are developing a gridded hydroclimate dataset for diverse watersheds using SimGrid (Larson, 2008; Lapp et al., 2005; Sheppard, 1996), a model that applies the Mountain Climate Model (MTCLIM; Hungerford et al., 1989) to simulate hydro-climatic conditions over diverse terrain. The model uses GIS based terrain categories (TC) classified by slope, aspect, elevation, and soil water storage. SimGrid provides daily estimates of solar radiation, air temperature, relative humidity, precipitation, snowpack and soil water storage over space. Earlier versions of the model have been applied in the St. Mary (Larson, 2008) and upper Oldman basins (Lapp et al., 2005), giving realistic estimates of hydro-climatic variables. The current study demonstrates improvements to the estimation of temperature, precipitation, snowpack, soil water storage and runoff from the basin. Soil water storage data for the upper drainage were derived with GIS and included in SimGrid to estimate soil water flux over the time period. These changes help improve the estimation of spatial climatic variability over the basin while accounting for topographical influence. In further work we will apply spatial hydro-climatic surfaces from the SimGrid model to assess the hydrologic response to environmental change for watersheds in Canada and beyond. (author)
.... The approach assumes that soil moisture and saturated groundwater storage serve as essential state variables in the rainfall-runoff process and that natural variations in topography, drainage area...
Myo Lin, Nay; Rutten, Martine
The Sittaung River is one of four major rivers in Myanmar. This river basin is developing fast and facing problems with flood, sedimentation, river bank erosion and salt intrusion. At present, more than 20 numbers of reservoirs have already been constructed for multiple purposes such as irrigation, domestic water supply, hydro-power generation, and flood control. The rainfall runoff models are required for the operational management of this reservoir system. In this study, the river basin is divided into (64) sub-catchments and the Sacramento Soil Moisture Accounting (SAC-SMA) models are developed by using satellite rainfall and Geographic Information System (GIS) data. The SAC-SMA model has sixteen calibration parameters, and also uses a unit hydrograph for surface flow routing. The Sobek software package is used for SAC-SMA modelling and simulation of river system. The models are calibrated and tested by using observed discharge and water level data. The statistical results show that the model is applicable to use for data scarce region. Keywords: Sacramento, Sobek, rainfall runoff, reservoir
Hoos, Anne B.; Patel, Anant R.
Model-adjustment procedures were applied to the combined data bases of storm-runoff quality for Chattanooga, Knoxville, and Nashville, Tennessee, to improve predictive accuracy for storm-runoff quality for urban watersheds in these three cities and throughout Middle and East Tennessee. Data for 45 storms at 15 different sites (five sites in each city) constitute the data base. Comparison of observed values of storm-runoff load and event-mean concentration to the predicted values from the regional regression models for 10 constituents shows prediction errors, as large as 806,000 percent. Model-adjustment procedures, which combine the regional model predictions with local data, are applied to improve predictive accuracy. Standard error of estimate after model adjustment ranges from 67 to 322 percent. Calibration results may be biased due to sampling error in the Tennessee data base. The relatively large values of standard error of estimate for some of the constituent models, although representing significant reduction (at least 50 percent) in prediction error compared to estimation with unadjusted regional models, may be unacceptable for some applications. The user may wish to collect additional local data for these constituents and repeat the analysis, or calibrate an independent local regression model.
Chung, S W; Lee, H S
In monsoon climate area, turbidity flows typically induced by flood runoffs cause numerous environmental impacts such as impairment of fish habitat and river attraction, and degradation of water supply efficiency. This study was aimed to characterize the physical dynamics of turbidity plume induced into a stratified reservoir using field monitoring and numerical simulations, and to assess the effect of different withdrawal scenarios on the control of downstream water quality. Three different turbidity models (RUN1, RUN2, RUN3) were developed based on a two-dimensional laterally averaged hydrodynamic and transport model, and validated against field data. RUN1 assumed constant settling velocity of suspended sediment, while RUN2 estimated the settling velocity as a function of particle size, density, and water temperature to consider vertical stratification. RUN3 included a lumped first-order turbidity attenuation rate taking into account the effects of particles aggregation and degradable organic particles. RUN3 showed best performance in replicating the observed variations of in-reservoir and release turbidity. Numerical experiments implemented to assess the effectiveness of different withdrawal depths showed that the alterations of withdrawal depth can modify the pathway and flow regimes of the turbidity plume, but its effect on the control of release water quality could be trivial.
Hanzer, Florian; Förster, Kristian; Marke, Thomas; Strasser, Ulrich
Assessing the amount of water resources stored in mountain catchments as snow and ice as well as the timing of meltwater production and the resulting streamflow runoff is of high interest for glaciohydrological investigations and hydropower production. Climate change induced seasonal shifts in snow and ice melt will alter the hydrological regimes in glacierized catchments in terms of both timing and magnitude of discharge. We present the setup of the hydroclimatological model AMUNDSEN for a highly glacierized (24 %) 558 km2 large study area (1760-3768 m a.s.l.) in the Ötztal Alps (Austria), and first results of simulated future runoff conditions. The study region comprises the headwater catchments of the valleys Ötztal, Pitztal, and Kaunertal, which contribute to the streamflow of the river Inn. AMUNDSEN is a fully distributed physically based model designed to quantify the energy and mass balance of snow and ice surfaces in complex topography as well as streamflow generation for a given catchment. The model has been extensively validated for past conditions and has been extended by an empirical glacier evolution model (Δh approach) for the present study. Statistically downscaled EURO-CORDEX climate simulations covering the RCP4.5 and RCP8.5 scenarios are used as the meteorological forcing for the period 2006-2050. Model results are evaluated in terms of magnitude and change of the contributions of the individual runoff components (snowmelt, ice melt, rain) in the subcatchments as well as the change in glacier volume and area.
Auvet, B.; Lidon, B.; Kartiwa, B.; Le Bissonnais, Y.; Poussin, J.-C.
This paper presents an approach to model runoff and erosion risk in a context of data scarcity, whereas the majority of available models require large quantities of physical data that are frequently not accessible. To overcome this problem, our approach uses different sources of data, particularly on agricultural practices (tillage and land cover) and farmers' perceptions of runoff and erosion. The model was developed on a small (5 ha) cultivated watershed characterized by extreme conditions (slopes of up to 55 %, extreme rainfall events) on the Merapi volcano in Indonesia. Runoff was modelled using two versions of STREAM. First, a lumped version was used to determine the global parameters of the watershed. Second, a distributed version used three parameters for the production of runoff (slope, land cover and roughness), a precise DEM, and the position of waterways for runoff distribution. This information was derived from field observations and interviews with farmers. Both surface runoff models accurately reproduced runoff at the outlet. However, the distributed model (Nash-Sutcliffe = 0.94) was more accurate than the adjusted lumped model (N-S = 0.85), especially for the smallest and biggest runoff events, and produced accurate spatial distribution of runoff production and concentration. Different types of erosion processes (landslides, linear inter-ridge erosion, linear erosion in main waterways) were modelled as a combination of a hazard map (the spatial distribution of runoff/infiltration volume provided by the distributed model), and a susceptibility map combining slope, land cover and tillage, derived from in situ observations and interviews with farmers. Each erosion risk map gives a spatial representation of the different erosion processes including risk intensities and frequencies that were validated by the farmers and by in situ observations. Maps of erosion risk confirmed the impact of the concentration of runoff, the high susceptibility of long steep
Carey, Mark; Baraer, Michel; Mark, Bryan G.; French, Adam; Bury, Jeffrey; Young, Kenneth R.; McKenzie, Jeffrey M.
Glacier shrinkage caused by climate change is likely to trigger diminished and less consistent stream flow in glacier-fed watersheds worldwide. To understand, model, and adapt to these climate-glacier-water changes, it is vital to integrate the analysis of both water availability (the domain of hydrologists) and water use (the focus for social scientists). Drawn from a case study of the Santa River watershed below Peru’s glaciated Cordillera Blanca mountain range, this paper provides a holistic hydro-social framework that identifies five major human variables critical to hydrological modeling because these forces have profoundly influenced water use over the last 60 years: (1) political agendas and economic development; (2) governance: laws and institutions; (3) technology and engineering; (4) land and resource use; and (5) societal responses. Notable shifts in Santa River water use-including major expansions in hydroelectricity generation, large-scale irrigation projects, and other land and resource-use practices-did not necessarily stem from changing glacier runoff or hydrologic shifts, but rather from these human variables. Ultimately, then, water usage is not predictable based on water availability alone. Glacier runoff conforms to certain expected trends predicted by models of progressively reduced glacier storage. However, societal forces establish the legal, economic, political, cultural, and social drivers that actually shape water usage patterns via human modification of watershed dynamics. This hydro-social framework has widespread implications for hydrological modeling in glaciated watersheds from the Andes and Alps to the Himalaya and Tien Shan, as well as for the development of climate change adaptation plans.
Ramirez-Avila, John J; Radcliffe, David E; Osmond, Deanna; Bolster, Carl; Sharpley, Andrew; Ortega-Achury, Sandra L; Forsberg, Adam; Oldham, J Larry
The Agricultural Policy Environmental eXtender (APEX) model has been widely applied to assess phosphorus (P) loss in runoff water and has been proposed as a model to support practical decisions regarding agricultural P management, as well as a model to evaluate tools such as the P Index. The aim of this study is to evaluate the performance of APEX to simulate P losses from agricultural systems to determine its potential use for refinement or replacement of the P Index in the southern region of the United States. Uncalibrated and calibrated APEX model predictions were compared against measured water quality data from row crop fields in North Carolina and Mississippi and pasture fields in Arkansas and Georgia. Calibrated models satisfactorily predicted event-based surface runoff volumes at all sites (Nash-Sutcliffe efficiency [NSE] > 0.47, |percent bias [PBIAS]| < 34) except Arkansas (NSE < 0.11, |PBIAS| < 50) but did not satisfactory simulate sediment, dissolved P, or total P losses in runoff water. The APEX model tended to underestimate dissolved and total P losses from fields where manure was surface applied. The model also overestimated sediments and total P loads during irrigation events. We conclude that the capability of APEX to predict sediment and P losses is limited, and consequently so is the potential for using APEX to make P management recommendations to improve P Indices in the southern United States. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.
Hahm, W. J.; Wang, J.; Druhan, J. L.; Rempe, D.; Dietrich, W. E.
Stream solute concentration-discharge (C-Q) relationships integrate catchment-scale hydrologic and geochemical processes, potentially yielding valuable information about runoff generation and weathering mechanisms. However, recent compilations have established that chemostasis—the condition where solute concentrations are invariant across large ranges of runoff—is observed in watersheds of diverse lithology, climate, and topography, suggesting an equifinality of the C-Q relationship independent of hydrologic process. Here we explore C-Q signals in contrasting catchments of the Eel River Critical Zone (CZ) Observatory in the Northern California Coast Ranges, where, unlike most watersheds where chemostasis has been observed, hillslope hydrologic processes are well characterized via years of intensive hydrologic monitoring. Our two catchments in the Franciscan Complex have radically different runoff generation mechanisms arising from differences in CZ structure: at Elder Creek (Coastal Belt), rain passes vertically as unsaturated flow through soil, saprolite, and a thick weathered rock zone before perching as groundwater on fresh bedrock and flowing laterally through fractures to generate streamflow, resulting in nearly chemostatic major cation behavior (power law C-Q slopes (B) ≈ 0 to -0.1). At Dry Creek (Central Belt), the thin (2 to 3 m) hydrologically active CZ completely saturates in most storm events, generating saturation overland flow across the landscape. New data from Dry Creek reveal log-log C-Q relationships for major cations that exhibit negative curvature, indicating a trend towards increasing dilution at higher flow rates and a possible C-Q signature of overland flow. High geomorphic channel drainage density (16.9 km/km2) results in short flow paths and, presumably, short water hillslope residence times at high runoff when overland flow dominates (> 50 mm d-1). Surprisingly, even at these high runoff rates, pure dilution does not occur (high
Martin, P; Joannon, A; Piskiewicz, N
This article proposes the use of a new model, DIAR (Diagnostic Agronomique du Ruissellement, or Agronomic Assessment of Runoff), for the prediction of the timing of the risk of runoff. DIAR is dedicated to loamy soils which are very sensitive to surface crusting, leading to runoff, soil erosion and muddy flows. The approach is proposed for the north-western European loess belt regions where muddy flows severely impact human activities. The likelihood of runoff is assessed from the sequence of soil surface states generated by cultivation practices. DIAR is based on the calculation of curve number values, for each stage of the soil-surface-state sequence, for calculating runoff for each of these stages. In this study, DIAR is applied to a catchment of 912 ha, cultivated by 26 farmers in the Pays de Caux (Normandy, France) where infrastructures located at the outlet have been damaged several times by muddy flows. Local public authorities involved in reducing muddy flows are eager to limit the agricultural upstream runoff by extending the planting of mustard as a winter cover crop. We tested the efficiency of such a policy on the reduction of the mean runoff. We also tested the year-to-year variability of this efficiency using the acreages of four successive years (1999-2000 to 2002-2003). Finally, the cost-efficiency of the policy was also considered. Though we used the same weather scenario, the initial situation (without much mustard cover) showed a wide year-to-year variation in the total runoff. This variation can be associated with the structure of the farms that cultivate the catchment (Utilised Agricultural Area (UAA) of each farm and percentage of this UAA inside the catchment). Our results showed that the widespread planting of winter cover crops could reduce the runoff by 10-20% compared with the initial situation (depending on the year), and also reduce the year-to-year variability of runoff. For each of the 4 tested years, the cost of the infiltrated m(3
Ghodsi, Seyed Hamed; Kerachian, Reza; Estalaki, Siamak Malakpour; Nikoo, Mohammad Reza; Zahmatkesh, Zahra
In this paper, two deterministic and stochastic multilateral, multi-issue, non-cooperative bargaining methodologies are proposed for urban runoff quality management. In the proposed methodologies, a calibrated Storm Water Management Model (SWMM) is used to simulate stormwater runoff quantity and quality for different urban stormwater runoff management scenarios, which have been defined considering several Low Impact Development (LID) techniques. In the deterministic methodology, the best management scenario, representing location and area of LID controls, is identified using the bargaining model. In the stochastic methodology, uncertainties of some key parameters of SWMM are analyzed using the info-gap theory. For each water quality management scenario, robustness and opportuneness criteria are determined based on utility functions of different stakeholders. Then, to find the best solution, the bargaining model is performed considering a combination of robustness and opportuneness criteria for each scenario based on utility function of each stakeholder. The results of applying the proposed methodology in the Velenjak urban watershed located in the northeastern part of Tehran, the capital city of Iran, illustrate its practical utility for conflict resolution in urban water quantity and quality management. It is shown that the solution obtained using the deterministic model cannot outperform the result of the stochastic model considering the robustness and opportuneness criteria. Therefore, it can be concluded that the stochastic model, which incorporates the main uncertainties, could provide more reliable results.
Driscoll, J. M.
Precipitation in the southwestern United States falls primarily in areas of higher elevation. Drought conditions over the past five years have limited snowpack and rainfall, increasing the vulnerability to and frequency of forest fires in these montane regions. In June 2012, the Little Bear fire burned approximately 69 square miles (44,200 acres) in high-elevation forests of the Rio Hondo headwater catchments, south-central New Mexico. Burn severity was high or moderate on 53 percent of the burn area. The Precipitation Runoff Modeling System (PRMS) is a publically-available watershed model developed by the U.S. Geological Survey (USGS). PRMS data are spatially distributed using a 'Geospatial Fabric' developed at a national scale to define Hydrologic Response Units (HRUs), based on topography and points of interest (such as confluences and streamgages). The Little Bear PRMS study area is comprised of 22 HRUs over a 587 square-mile area contributing to the Rio Hondo above Chavez Canyon streamgage (USGS ID 08390020), in operation from 2008 to 2014. Model input data include spatially-distributed climate data from the National Aeronautics and Space Administration (NASA) DayMet and land cover (such as vegetation and soil properties) data from the USGS Geo Data Portal. Remote sensing of vegetation over time has provided a spatial distribution of recovery and has been applied using dynamic parameters within PRMS on the daily timestep over the study area. Investigation into the source and timing of water budget components in the Rio Hondo watershed may assist water planners and managers in determining how the surface-water and groundwater systems will react to future land use/land cover changes. Further application of PRMS in additional areas will allow for comparison of streamflow before and following wildfire conditions, and may lead to better understanding of the changes in watershed-scale hydrologic processes in the Southwest through post-fire watershed recovery.
Bayless, E.R.; Olyphant, G.A.
Cation distributions in twenty samples of acid-generating salts were compared to those in groundwater and storm runoff from a coal-refuse deposit in an effort to identify source-product relationships. Two mineral suites, one primarily composed of melanterite, rozenite and szomolnokite, and the other composed almost entirely of copiapite, were found to be most abundant at the study site. Comparisons of cation distributions in salts with those in water samples led to an hypothesis that a copiapite-rich suite precipitated from vadose-zone groundwater that was brought to the surface by evaporative forcing. The copiapite-rich suite, which contained larger concentrations of aluminum, calcium and zinc than the melanterite-rozenite-szomolnokite mineral suite, was the primary source of solutes in captured storm runoff. An analysis of samples collected during a summer thunderstorm indicated that the chemistry of surface runoff varied little with time or with distance downstream. The cation distributions in samples of groundwater indicated that iron-rich pore waters observed near the surface in late autumn may have influenced water chemistry in the deeper portions of the unsaturated zone during the 1989 recharge season. The results of this study show that the solutes produced by the two observed salt suites can be distinguished by their mole percent iron and that the source-product relationships can explain observed variability in mine drainage chemistry at the study site
Andersen, Thomas Lykke; Frigaard, Peter
The present book describes the most important aspects of wave generation techniques in physical models. Moreover, the book serves as technical documentation for the wave generation software AwaSys 6, cf. Aalborg University (2012). In addition to the two main authors also Tue Hald and Michael...
Meland, Sondre; Salbu, Brit; Rosseland, Bjørn Olav
The ecotoxicological impact of highway runoff on brown trout (Salmo trutta L.) was studied in an in situ experiment consisting of four 24 h simulated runoff episodes. Fish were maintained in 5 tanks and exposed to highway runoff from a sedimentation pond close to E6 outside the city of Oslo, Norway. The tanks had the following contaminant loadings during the episodes: stream water (control), pond inlet, pond outlet, pond inlet + stream water and pond outlet + stream water. Opposite to road salt and compared to earlier findings, the first two episodes had rather low concentrations of trace metals, hydrocarbons and polycyclic aromatic hydrocarbons. A heavy rainfall before episode 3 increased the concentrations of all the contaminants except road salt which was diluted. In addition, lowered oxygen levels led to hypoxic conditions. Overall the fish exposed to highway runoff had, compared to the control fish, higher concentrations of trace metals in gills and liver, increased activity of the antioxidant defense system represented by superoxide dismutase, catalase and metallothionein, problems with the regulation of plasma Cl and Na, as well as increased levels of blood glucose and pCO(2). Finally, this seemed to affect the metabolism of the fish through reduced condition factor. The observed effects were likely caused by multiple stressors and not by a single contaminant. The sedimentation pond clearly reduced the toxicity of the highway runoff. But even in the least polluted exposure tank (pond outlet + stream water) signs of physiological disturbances were evident.
Elizabeth N. Mihalik; Norm S. Levine; Devendra M. Amatya
Chapel Branch Creek (CBC), located within the Town of Santee adjacent to Lake Marion in Orangeburg County, SC, is listed on the SC 2004 303(d) list of impaired waterbodies due to elevated levels of nitrogen (N), phosphorus (P), chlorophyll-a, and pH. In this study, using a GIS-based approach, two runoff modeling methods, the Rational and SCS-CN methods, have been...
Morrison, Katherine D; Kolden, Crystal A
Wildfire is a common disturbance that can significantly alter vegetation in watersheds and affect the rate of sediment and nutrient transport to adjacent nearshore oceanic environments. Changes in runoff resulting from heterogeneous wildfire effects are not well-understood due to both limitations in the field measurement of runoff and temporally-limited spatial data available to parameterize runoff models. We apply replicable, scalable methods for modeling wildfire impacts on sediment and nonpoint source pollutant export into the nearshore environment, and assess relationships between wildfire severity and runoff. Nonpoint source pollutants were modeled using a GIS-based empirical deterministic model parameterized with multi-year land cover data to quantify fire-induced increases in transport to the nearshore environment. Results indicate post-fire concentration increases in phosphorus by 161 percent, sediments by 350 percent and total suspended solids (TSS) by 53 percent above pre-fire years. Higher wildfire severity was associated with the greater increase in exports of pollutants and sediment to the nearshore environment, primarily resulting from the conversion of forest and shrubland to grassland. This suggests that increasing wildfire severity with climate change will increase potential negative impacts to adjacent marine ecosystems. The approach used is replicable and can be utilized to assess the effects of other types of land cover change at landscape scales. It also provides a planning and prioritization framework for management activities associated with wildfire, including suppression, thinning, and post-fire rehabilitation, allowing for quantification of potential negative impacts to the nearshore environment in coastal basins. Copyright © 2014 Elsevier Ltd. All rights reserved.
Infante Corona, J. A.; Lakhankar, T.; Khanbilvardi, R.; Pradhanang, S. M.
Stream flow estimation and flood prediction influenced by snow melting processes have been studied for the past couple of decades because of their destruction potential, money losses and demises. It has been observed that snow, that was very stationary during its seasons, now is variable in shorter time-scales (daily and hourly) and rapid snowmelt can contribute or been the cause of floods. Therefore, good estimates of snowpack properties on ground are necessary in order to have an accurate prediction of these destructive events. The snow thermal model (SNTHERM) is a 1-dimensional model that analyzes the snowpack properties given the climatological conditions of a particular area. Gridded data from both, in-situ meteorological observations and remote sensing data will be produced using interpolation methods; thus, snow water equivalent (SWE) and snowmelt estimations can be obtained. The soil and water assessment tool (SWAT) is a hydrological model capable of predicting runoff quantity and quality of a watershed given its main physical and hydrological properties. The results from SNTHERM will be used as an input for SWAT in order to have simulated runoff under snowmelt conditions. This project attempts to improve the river discharge estimation considering both, excess rainfall runoff and the snow melting process. Obtaining a better estimation of the snowpack properties and evolution is expected. A coupled use of SNTHERM and SWAT based on meteorological in situ and remote sensed data will improve the temporal and spatial resolution of the snowpack characterization and river discharge estimations, and thus flood prediction.
Versini, Pierre-Antoine; Tchiguirinskaia, Ioulia; Schertzer, Daniel
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
Abrahart, R. J.; Beriro, D. J.
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
Hazenberg, P.; Leijnse, H.; Uijlenhoet, R.; Delobbe, L.; Weerts, A.; Reggiani, P.
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
Mohammad Taghi Dastorani
Full Text Available During recent few decades, due to the importance of the availability of water, and therefore the necesity of predicting run off resulted from rain fall there has been an increase in developing and implementation of new suitable method for prediction of run off using precipitation data. One of these approaches that have been developed in several areas of sciences including water related fields, is soft computing techniques such as artificial neural networks and fuzzy logic systems. This research was designed to evaluate the applicability of artificial neural network and adaptive neuro –fuzzy inference system to model rainfall-runoff process in Zayandeh_rood dam basin. It must be mentioned that, data have been analysed using Wingamma software, to select appropriate type and number of training input data before they can be used in the models. Then, it has been tried to evaluated applicability of artificial neural networks and neuro-fuzzy techniques to predict runoff generated from daily rainfall. Finally, the accuracy of the results produced by these methods has been compared using statistical criterion. Results taken from this research show that artificial neural networks and neuro-fuzzy technique presented different outputs in different conditions in terms of type and number of inputs variables, but both method have been able to produce acceptable results when suitable input variables and network structures are used.
Uncertainties on the spatial distribution of precipitation seriously affect the reliability of the discharge estimates produced by watershed models. Although there is abundant research evaluating the goodness of fit of precipitation estimates obtained with different gauge interpolation methods, few studies have focused on the influence of the interpolation strategy on the response of watershed models. The relevance of this choice may be even greater in the case of mountain catchments, because of the influence of orography on precipitation. This study evaluates the effect of the precipitation interpolation method on the performance of conceptual type snowmelt runoff models. The HBV Light model version 184.108.40.206, operating at daily time steps, is used as a case study. The model is applied in Aconcagua at Chacabuquito catchment, located in the Andes Mountains of Central Chile. The catchment's area is 2110[Km2] and elevation ranges from 950[m.a.s.l.] to 5930[m.a.s.l.] The local meteorological network is sparse, with all precipitation gauges located below 3000[m.a.s.l.] Precipitation amounts corresponding to different elevation zones are estimated through areal averaging of precipitation fields interpolated from gauge data. Interpolation methods applied include kriging with external drift (KED), optimal interpolation method (OIM), Thiessen polygons (TP), multiquadratic functions fitting (MFF) and inverse distance weighting (IDW). Both KED and OIM are able to account for the existence of a spatial trend in the expectation of precipitation. By contrast, TP, MFF and IDW, traditional methods widely used in engineering hydrology, cannot explicitly incorporate this information. Preliminary analysis confirmed that these methods notably underestimate precipitation in the study catchment, while KED and OIM are able to reduce the bias; this analysis also revealed that OIM provides more reliable estimations than KED in this region. Using input precipitation obtained by each method
Penn, C. A.; Clow, D. W.; Sexstone, G. A.
Water supply forecasts are an important tool for water resource managers in areas where surface water is relied on for irrigating agricultural lands and for municipal water supplies. Forecast errors, which correspond to inaccurate predictions of total surface water volume, can lead to mis-allocated water and productivity loss, thus costing stakeholders millions of dollars. The objective of this investigation is to provide water resource managers with an improved understanding of factors contributing to forecast error, and to help increase the accuracy of future forecasts. In many watersheds of the western United States, snowmelt contributes 50-75% of annual surface water flow and controls both the timing and volume of peak flow. Water supply forecasts from the Natural Resources Conservation Service (NRCS), National Weather Service, and similar cooperators use precipitation and snowpack measurements to provide water resource managers with an estimate of seasonal runoff volume. The accuracy of these forecasts can be limited by available snowpack and meteorological data. In the headwaters of the Rio Grande, NRCS produces January through June monthly Water Supply Outlook Reports. This study evaluates the accuracy of these forecasts since 1990, and examines what factors may contribute to forecast error. The Rio Grande headwaters has experienced recent changes in land cover from bark beetle infestation and a large wildfire, which can affect hydrological processes within the watershed. To investigate trends and possible contributing factors in forecast error, a semi-distributed hydrological model was calibrated and run to simulate daily streamflow for the period 1990-2015. Annual and seasonal watershed and sub-watershed water balance properties were compared with seasonal water supply forecasts. Gridded meteorological datasets were used to assess changes in the timing and volume of spring precipitation events that may contribute to forecast error. Additionally, a
Full Text Available This study presents an application of an innovative sampling strategy to assess soil moisture dynamics in a headwater of the Weißeritz in the German eastern Ore Mountains. A grassland site and a forested site were instrumented with two Spatial TDR clusters (STDR that consist of 39 and 32 coated TDR probes of 60 cm length. Distributed time series of vertically averaged soil moisture data from both sites/ensembles were analyzed by statistical and geostatistical methods. Spatial variability and the spatial mean at the forested site were larger than at the grassland site. Furthermore, clustering of TDR probes in combination with long-term monitoring allowed identification of average spatial covariance structures at the small field scale for different wetness states. The correlation length of soil water content as well as the sill to nugget ratio at the grassland site increased with increasing average wetness and but, in contrast, were constant at the forested site. As soil properties at both the forested and grassland sites are extremely variable, this suggests that the correlation structure at the forested site is dominated by the pattern of throughfall and interception. We also found a very strong correlation between antecedent soil moisture at the forested site and runoff coefficients of rainfall-runoff events observed at gauge Rehefeld. Antecedent soil moisture at the forest site explains 92% of the variability in the runoff coefficients. By combining these results with a recession analysis we derived a first conceptual model of the dominant runoff mechanisms operating in this catchment. Finally, we employed a physically based hydrological model to shed light on the controls of soil- and plant morphological parameters on soil average soil moisture at the forested site and the grassland site, respectively. A homogeneous soil setup allowed, after fine tuning of plant morphological parameters, most of the time unbiased predictions of the observed
Christiansen, Daniel E.; Haj, Adel E.; Risley, John C.
The U.S. Geological Survey, in cooperation with the Iowa Department of Natural Resources, constructed Precipitation-Runoff Modeling System models to estimate daily streamflow for 12 river basins in western Iowa that drain into the Missouri River. The Precipitation-Runoff Modeling System is a deterministic, distributed-parameter, physical-process-based modeling system developed to evaluate the response of streamflow and general drainage basin hydrology to various combinations of climate and land use. Calibration periods for each basin varied depending on the period of record available for daily mean streamflow measurements at U.S. Geological Survey streamflow-gaging stations.A geographic information system tool was used to delineate each basin and estimate initial values for model parameters based on basin physical and geographical features. A U.S. Geological Survey automatic calibration tool that uses a shuffled complex evolution algorithm was used for initial calibration, and then manual modifications were made to parameter values to complete the calibration of each basin model. The main objective of the calibration was to match daily discharge values of simulated streamflow to measured daily discharge values. The Precipitation-Runoff Modeling System model was calibrated at 42 sites located in the 12 river basins in western Iowa.The accuracy of the simulated daily streamflow values at the 42 calibration sites varied by river and by site. The models were satisfactory at 36 of the sites based on statistical results. Unsatisfactory performance at the six other sites can be attributed to several factors: (1) low flow, no flow, and flashy flow conditions in headwater subbasins having a small drainage area; (2) poor representation of the groundwater and storage components of flow within a basin; (3) lack of accounting for basin withdrawals and water use; and (4) limited availability and accuracy of meteorological input data. The Precipitation-Runoff Modeling System
Aroca-Jimenez, Estefania; Bodoque, Jose Maria; Diez-Herrero, Andres
Flash floods constitute one of the natural hazards better able to generate risk, particularly with regard to Society. The complexity of this process and its dependence on various factors related to the characteristics of the basin and rainfall make flash floods are difficult to characterize in terms of their hydrological response.To do this, it is essential a proper analysis of the so called 'initial abstractions'. Among all of these processes, infiltration plays a crucial role in explaining the occurrence of floods in mountainous basins.For its characterization the Green-Ampt model , which depends on the characteristics of rainfall and physical properties of soil has been used in this work.This is a method enabling to simulate floods in mountainous basins where hydrological response is sub-daily. However, it has the disadvantage that it is based on physical properties of soil which have a high spatial variability. To address this difficulty soil mapping units have been delineated according to the geomorphological landforms and elements. They represent hydro-functional mapping units that are theoretically homogeneous from the perspective of the pedostructure parameters of the pedon. So the soil texture of each homogeneous group of landform units was studied by granulometric analyses using standarized sieves and Sedigraph devices. In addition, uncertainty associated with the parameterization of the Green-Ampt method has been estimated by implementing a Monte Carlo approach, which required assignment of the proper distribution function to each parameter.The suitability of this method was contrasted by calibrating and validating a hydrological model, in which the generation of runoff hydrograph has been simulated using the SCS unit hydrograph (HEC-GeoHMS software), while flood wave routing has been characterized using the Muskingum-Cunge method. Calibration and validation of the model was from the use of an automatic routine based on the employ of the search algorithm
National Aeronautics and Space Administration — ABSTRACT: The University of New Hampshire (UNH)/Global Runoff Data Centre (GRDC) composite runoff data combines simulated water balance model runoff estimates...
Hansen, Martin Otto Laver; Westergaard, C.
For some time attempts have been made to improve the power curve of stall regulated wind turbines by using devices like vortex generators VG and Gurney flaps. The vortex produces an additional mixing of the boundary layer and the free stream and thereby increasing the momentum close to the wall......, which again delays separation in adverse pressure gradient regions. A model is needed to include the effect of vortex generators in numerical computations of the viscous flow past rotors. In this paper a simple model is proposed....
Liu, Yaoze; Bralts, Vincent F; Engel, Bernard A
The adverse influence of urban development on hydrology and water quality can be reduced by applying best management practices (BMPs) and low impact development (LID) practices. This study applied green roof, rain barrel/cistern, bioretention system, porous pavement, permeable patio, grass strip, grassed swale, wetland channel, retention pond, detention basin, and wetland basin, on Crooked Creek watershed. The model was calibrated and validated for annual runoff volume. A framework for simulating BMPs and LID practices at watershed scales was created, and the impacts of BMPs and LID practices on water quantity and water quality were evaluated with the Long-Term Hydrologic Impact Assessment-Low Impact Development 2.1 (L-THIA-LID 2.1) model for 16 scenarios. The various levels and combinations of BMPs/LID practices reduced runoff volume by 0 to 26.47%, Total Nitrogen (TN) by 0.30 to 34.20%, Total Phosphorus (TP) by 0.27 to 47.41%, Total Suspended Solids (TSS) by 0.33 to 53.59%, Lead (Pb) by 0.30 to 60.98%, Biochemical Oxygen Demand (BOD) by 0 to 26.70%, and Chemical Oxygen Demand (COD) by 0 to 27.52%. The implementation of grass strips in 25% of the watershed where this practice could be applied was the most cost-efficient scenario, with cost per unit reduction of $1m3/yr for runoff, while cost for reductions of two pollutants of concern was $445 kg/yr for Total Nitrogen (TN) and $4871 kg/yr for Total Phosphorous (TP). The scenario with very high levels of BMP and LID practice adoption (scenario 15) reduced runoff volume and pollutant loads from 26.47% to 60.98%, and provided the greatest reduction in runoff volume and pollutant loads among all scenarios. However, this scenario was not as cost-efficient as most other scenarios. The L-THIA-LID 2.1 model is a valid tool that can be applied to various locations to help identify cost effective BMP/LID practice plans at watershed scales. Copyright © 2014 Elsevier B.V. All rights reserved.
Evaluation of radar-derived precipitation estimates using runoff simulation : report for the NFR Energy Norway funded project 'Utilisation of weather radar data in atmospheric and hydrological models'
Abdella, Yisak; Engeland, Kolbjoern; Lepioufle, Jean-Marie
This report presents the results from the project called 'Utilisation of weather radar data in atmospheric and hydrological models' funded by NFR and Energy Norway. Three precipitation products (radar-derived, interpolated and combination of the two) were generated as input for hydrological models. All the three products were evaluated by comparing the simulated and observed runoff at catchments. In order to expose any bias in the precipitation inputs, no precipitation correction factors were applied. Three criteria were used to measure the performance: Nash, correlation coefficient, and bias. The results shows that the simulations with the combined precipitation input give the best performance. We also see that the radar-derived precipitation estimates give reasonable runoff simulation even without a region specific parameters for the Z-R relationship. All the three products resulted in an underestimation of the estimated runoff, revealing a systematic bias in measurements (e.g. catch deficit, orographic effects, Z-R relationships) that can be improved. There is an important potential of using radar-derived precipitation for simulation of runoff, especially in catchments without precipitation gauges inside.(Author)
Langmead, Christopher James
Atomistic simulations of the conformational dynamics of proteins can be performed using either Molecular Dynamics or Monte Carlo procedures. The ensembles of three-dimensional structures produced during simulation can be analyzed in a number of ways to elucidate the thermodynamic and kinetic properties of the system. The goal of this chapter is to review both traditional and emerging methods for learning generative models from atomistic simulation data. Here, the term ‘generative’ refers to a model of the joint probability distribution over the behaviors of the constituent atoms. In the context of molecular modeling, generative models reveal the correlation structure between the atoms, and may be used to predict how the system will respond to structural perturbations. We begin by discussing traditional methods, which produce multivariate Gaussian models. We then discuss GAMELAN (GrAphical Models of Energy LANdscapes), which produces generative models of complex, non-Gaussian conformational dynamics (e.g., allostery, binding, folding, etc) from long timescale simulation data. PMID:24446358
Jacquin, A. P.
This study analyses the effect of precipitation spatial distribution uncertainty on the uncertainty bounds of a snowmelt runoff model's discharge estimates. Prediction uncertainty bounds are derived using the Generalized Likelihood Uncertainty Estimation (GLUE) methodology. The model analysed is a conceptual watershed model operating at a monthly time step. The model divides the catchment into five elevation zones, where the fifth zone corresponds to the catchment glaciers. Precipitation amounts at each elevation zone i are estimated as the product between observed precipitation (at a single station within the catchment) and a precipitation factor FPi. Thus, these factors provide a simplified representation of the spatial variation of precipitation, specifically the shape of the functional relationship between precipitation and height. In the absence of information about appropriate values of the precipitation factors FPi, these are estimated through standard calibration procedures. The catchment case study is Aconcagua River at Chacabuquito, located in the Andean region of Central Chile. Monte Carlo samples of the model output are obtained by randomly varying the model parameters within their feasible ranges. In the first experiment, the precipitation factors FPi are considered unknown and thus included in the sampling process. The total number of unknown parameters in this case is 16. In the second experiment, precipitation factors FPi are estimated a priori, by means of a long term water balance between observed discharge at the catchment outlet, evapotranspiration estimates and observed precipitation. In this case, the number of unknown parameters reduces to 11. The feasible ranges assigned to the precipitation factors in the first experiment are slightly wider than the range of fixed precipitation factors used in the second experiment. The mean squared error of the Box-Cox transformed discharge during the calibration period is used for the evaluation of the
Full Text Available Tracer-aided hydrological models are increasingly used to reveal fundamentals of runoff generation processes and water travel times in catchments. Modelling studies integrating stable water isotopes as tracers are mostly based in temperate and warm climates, leaving catchments with strong snow influences underrepresented in the literature. Such catchments are challenging, as the isotopic tracer signals in water entering the catchments as snowmelt are typically distorted from incoming precipitation due to fractionation processes in seasonal snowpack. We used the Spatially distributed Tracer-Aided Rainfall–Runoff (STARR model to simulate fluxes, storage, and mixing of water and tracers, as well as estimating water ages in three long-term experimental catchments with varying degrees of snow influence and contrasting landscape characteristics. In the context of northern catchments the sites have exceptionally long and rich data sets of hydrometric data and – most importantly – stable water isotopes for both rain and snow conditions. To adapt the STARR model for sites with strong snow influence, we used a novel parsimonious calculation scheme that takes into account the isotopic fractionation through snow sublimation and snowmelt. The modified STARR setup simulated the streamflows, isotope ratios, and snow pack dynamics quite well in all three catchments. From this, our simulations indicated contrasting median water ages and water age distributions between catchments brought about mainly by differences in topography and soil characteristics. However, the variable degree of snow influence in catchments also had a major influence on the stream hydrograph, storage dynamics, and water age distributions, which was captured by the model. Our study suggested that snow sublimation fractionation processes can be important to include in tracer-aided modelling for catchments with seasonal snowpack, while the influence of fractionation during snowmelt
Thirel, Guillaume; Delaigue, Olivier; Coron, Laurent; Perrin, Charles; Andréassian, Vazken
Lumped hydrological models are useful and convenient tools for research, engineering and educational purposes. They propose catchment-scale representations of the precipitation-discharge relationship. Thanks to their limited data requirements, they can be easily implemented and run. With such models, it is possible to simulate a number of hydrological key processes over the catchment with limited structural and parametric complexity, typically evapotranspiration, runoff, underground losses, etc. The Hydrology Group at Irstea (Antony) has been developing a suite of rainfall-runoff models over the past 30 years with the main objectives of designing models as efficient as possible in terms of streamflow simulation, applicable to a wide range of catchments and having low data requirements. This resulted in a suite of models running at different time steps (from hourly to annual) applicable for various issues including water balance estimation, forecasting, simulation of impacts and scenario testing. Recently, Irstea has developed an easy-to-use R-package (R Core Team, 2016), called airGR (Coron et al., 2016, 2017), to make these models widely available. It includes: - the water balance annual GR1A model, - the monthly GR2M model, - three versions of the daily model, namely GR4J, GR5J and GR6J, - the hourly GR4H model, - a degree-day snow model CemaNeige. The airGR package has been designed to facilitate the use by non-expert users and allow the addition of evaluation criteria, models or calibration algorithm selected by the end-user. Each model core is coded in FORTRAN to ensure low computational time. The other package functions (i.e. mainly the calibration algorithm and the efficiency criteria) are coded in R. The package is also used for educational purposes. It allows for convenient implementation of model inter-comparisons and large sample hydrology experiments. The airGR package undergoes continuous developments for improving the efficiency, computational time
Full Text Available Precisely quantitative assessments of stream flow response to climatic change and permafrost thawing are highly challenging and urgent in cold regions. However, due to the notably harsh environmental conditions, there is little field monitoring data of runoff in permafrost regions, which has limited the development of physically based models in these regions. To identify the impacts of climate change in the runoff process in the Three-River Headwater Region (TRHR on the Qinghai-Tibet Plateau, two artificial neural network (ANN models, one with three input variables (previous runoff, air temperature, and precipitation and another with two input variables (air temperature and precipitation only, were developed to simulate and predict the runoff variation in the TRHR. The results show that the three-input variable ANN model has a superior real-time prediction capability and performs well in the simulation and forecasting of the runoff variation in the TRHR. Under the different scenarios conditions, the forecasting results of ANN model indicated that climate change has a great effect on the runoff processes in the TRHR. The results of this study are of practical significance for water resources management and the evaluation of the impacts of climatic change on the hydrological regime in long-term considerations.
Koch, Hagen; Vögele, Stefan
In recent years there have been several heat waves affecting the use of thermoelectric power plants, e.g. in Europe and the U.S. In this paper the linkage between hydro-climatic conditions and possible electricity generation restrictions is described. The coupling of hydrological models and a power plant model is presented. In this approach each power plant is considered separately with its technical specifications. Also environmental regulations, e.g. permissible rise in the cooling water temperature, are considered for the respective power plant. The hydrological models developed to simulate river runoff and water temperature are also site specific. The approach presented is applied to Krümmel nuclear power plant in Germany. Analysed are the uncertainties with regard to electricity generation restrictions on account of climatic developments and corresponding higher water temperatures and low flows. Overall, increased water temperatures and declining river runoff lead to more frequent and more severe generation restrictions. It is concluded that the site-specific approach is necessary to reliably simulate power plants water demand, river runoff and water temperature. Using a simulation time step of one day, electricity generation restrictions are significantly higher than for simulations at monthly time step. - Highlights: • An approach to assess climate effects on electricity generation is presented. • Site specific models for power plants, water temperature and discharge are used. • Monthly and daily simulation time-steps give different results. • Climate change effects on generation depend on cooling system and climate scenario
Roo, de A.P.J.; Wesseling, C.G.; Cremers, N.H.D.T.; Verzandvoort, M.A.; Ritsema, C.J.; Oostindie, K.
The Limburg Soil Erosion Model (LISEM) is described as a way of simulating hydrological and soil erosion processes during single rainfall events on the catchment scale. Sensitivity analysis of the model shows that the initial matric pressure potentialthe hydraulic conductivity of the soil and
M. K. Stewart
Full Text Available The east Otago uplands of New Zealand's South Island have long been studied because of the environmental consequences of converting native tussock grasslands to other land covers, notably forestry and pasture for stock grazing. Early studies showed that afforestation substantially reduced annual water yield, stream peak flows, and 7-day low flows, mainly as a consequence of increased interception. Tritium measurements have indicated that surprisingly old water is present in catchments GH1 and GH2, and the small headwater wetland and catchment (GH5, and contributes strongly to baseflow. The data have been simulated assuming the presence of two types of water in the baseflow, young water from shallow aquifers connecting hillside regolith with the stream, and old water from deep bedrock aquifers, respectively. The mean transit time of the young water is approximately one month, while that of the old water is 25–26 years as revealed by the presence of tritium originating from the bomb-peak in NZ rainfall in late 1960s and early 1970s. Such a long transit time indicates slow release from groundwater reservoirs within the bedrock, which constitute by far the larger of the water stores. Comparison of the results from catchments GH1 (tussock and GH2 (pine forest suggests that about equal quantities of water (85 mm/a are contributed from the deep aquifers in the two catchments, although runoff from the shallow aquifers has been strongly reduced by afforestation in GH2. This study has revealed the presence of a long transit time component of water in runoff in a catchment with crystalline metamorphic bedrock.
Stewart, M. K.; Fahey, B. D.
The east Otago uplands of New Zealand's South Island have long been studied because of the environmental consequences of converting native tussock grasslands to other land covers, notably forestry and pasture for stock grazing. Early studies showed that afforestation substantially reduced annual water yield, stream peak flows, and 7-day low flows, mainly as a consequence of increased interception. Tritium measurements have indicated that surprisingly old water is present in catchments GH1 and GH2, and the small headwater wetland and catchment (GH5), and contributes strongly to baseflow. The data have been simulated assuming the presence of two types of water in the baseflow, young water from shallow aquifers connecting hillside regolith with the stream, and old water from deep bedrock aquifers, respectively. The mean transit time of the young water is approximately one month, while that of the old water is 25-26 years as revealed by the presence of tritium originating from the bomb-peak in NZ rainfall in late 1960s and early 1970s. Such a long transit time indicates slow release from groundwater reservoirs within the bedrock, which constitute by far the larger of the water stores. Comparison of the results from catchments GH1 (tussock) and GH2 (pine forest) suggests that about equal quantities of water (85 mm/a) are contributed from the deep aquifers in the two catchments, although runoff from the shallow aquifers has been strongly reduced by afforestation in GH2. This study has revealed the presence of a long transit time component of water in runoff in a catchment with crystalline metamorphic bedrock.
Malasek, V.; Manek, O.; Masek, V.; Riman, J.
The claim of Czechoslovak discovery no. 239272 is a model designed for the verification of the properties of a reverse steam generator during the penetration of water, steam-water mixture or steam into liquid metal flowing inside the heat exchange tubes. The design may primarily be used for steam generators with a built-in inter-tube structure. The model is provided with several injection devices configured in different heat exchange tubes, spaced at different distances along the model axis. The design consists in that between the pressure and the circumferential casings there are transverse partitions and that in one chamber consisting of the circumferential casings, pressure casing and two adjoining partitions there is only one passage of the injection device through the inter-tube space. (Z.M.). 1 fig
Coon, William F.
Water-resource managers in Onondaga County, New York, are faced with the challenge of improving the water quality of Onondaga Lake, which has the distinction of being one of the most contaminated lakes in the United States. To assist in this endeavor, during 2003-07 the U.S. Geological Survey (USGS), in cooperation with the Onondaga Lake Partnership, developed a precipitation-runoff model of the 285-square-mile Onondaga Lake Basin with the computer program Hydrological Simulation Program-Fortran (HSPF). The model was intended to provide a tool whereby the processes responsible for the generation of loads of sediment and nutrients that are transported to Onondaga Lake could be better understood. This objective was only partly attained because data for calibration of the model were available from monitoring sites only at or near the mouths of the major tributaries to Onondaga Lake; no calibration data from headwater subbasins, where the loads originated, were available. To address this limitation and thereby decrease the uncertainty in the simulated results that were associated with headwater processes, the USGS conducted a 3-year (2005-08) basinwide study to assess the quality of surface water in the Onondaga Lake Basin. The study quantified the relative contributions of nonpoint sources associated with the major land uses and land covers in the basin and also monitored known sources and presumed sinks of sediment and nutrient loads, which previously had not been evaluated. The use of the newly acquired data to recalibrate the HSPF model resulted in improvements in the simulation of processes in the headwater subbasins, including suspended-sediment, orthophosphate, and phosphorus generation and transport.
Zheng, Y.; Luo, X.; Lin, Z.
The urban environment has a variety of Persistent Toxic Substances (PTS), such as Polycyclic Aromatic Hydrocarbons (PAHs) and mercury. Soil in pervious lands and dust deposited on impervious surfaces are two major sinks of PTSs in urbanized areas, which could contribute significant nonpoint source loadings of PTSs to adjacent waterbodies during rainfall-runoff events and therefore jeopardize aquatic ecosystems. However, PTSs have been much less understood regarding their export mechanisms in urban land uses, and efforts to model nonpoint source pollution processes of PTSs have been rare. We designed and performed in-lab rainfall-runoff simulation experiments to investigate transport of PAHs and mercury by runoff from urban soils. Organic petrology analysis (OPA) techniques were introduced to analyze the soil and sediment compositions. Our study revealed the limitation of the classic enrichment theory which attributes enrichment of pollutants in eroded sediment solely to the sediment's particle size distribution and adopts simple relationships between enrichment ratio and sediment flux. We found that carbonaceous materials (CMs) in soil are the direct and major sorbents for PAHs and mercury, and highly different in content, mobility and adsorption capacity for the PTSs. Anthropogenic CMs like black carbon components largely control the transport of soil PAHs, while humic substances have a dominant influence on the transport of soil mercury. A model was further developed to estimate the enrichment ratio of PAHs, which innovatively applies the fugacity concept.We also conducted field studies on export of PAHs by runoff from urban roads. A variable time-step model was developed to simulate the continuous cycles of PAH buildup and washoff on urban roads. The dependence of the pollution level on antecedent weather conditions was investigated and embodied in the model. The applicability of this approach and its value to environmental management was demonstrated by a case
Full Text Available The main objective of the paper is to understand how the model’s efficiency and the selected climatic indicators are related. The hydrological model applied in this study is a conceptual rainfall-runoff model (the TUW model, which was developed at the Vienna University of Technology. This model was calibrated over three different periods between 1981-2010 in three groups of Austrian catchments (snow, runoff, and soil catchments, which represent a wide range of the hydroclimatic conditions of Austria. The model’s calibration was performed using a differential evolution algorithm (Deoptim. As an objective function, we used a combination of the Nash-Sutcliffe coefficient (NSE and the logarithmic Nash-Sutcliffe coefficient (logNSE. The model’s efficiency was evaluated by Volume error (VE. Subsequently, we evaluated the relationship between the model’s efficiency (VE and changes in the climatic indicators (precipitation ΔP, air temperature ΔT. The implications of findings are discussed in the conclusion.
Tyler Jon Smith
In Montana and much of the Rocky Mountain West, the single most important parameter in forecasting the controls on regional water resources is snowpack. Despite the heightened importance of snowpack, few studies have considered the representation of uncertainty in coupled snowmelt/hydrologic conceptual models. Uncertainty estimation provides a direct interpretation of...
Langmead, Christopher James
Atomistic simulations of the conformational dynamics of proteins can be performed using either Molecular Dynamics or Monte Carlo procedures. The ensembles of three-dimensional structures produced during simulation can be analyzed in a number of ways to elucidate the thermodynamic and kinetic properties of the system. The goal of this chapter is to review both traditional and emerging methods for learning generative models from atomistic simulation data. Here, the term ‘generative’ refers to a...
Full Text Available Introduction: Field plots are widely used in studies related to the measurements of soil loss and modeling of erosion processes. Research efforts are needed to investigate factors affecting the data quality of plots. Spatial scale or size of plots is one of these factors which directly affects measuring runoff and soil loss by means of field plots. The effect of plot size on measured runoff or soil loss from natural plots is known as plot scale effect. On the other hand, variability of runoff and sediment yield from replicated filed plots is a main source of uncertainty in measurement of erosion from plots which should be considered in plot data interpretation processes. Therefore, there is a demand for knowledge of soil erosion processes occurring in plots of different sizes and of factors that determine natural variability, as a basis for obtaining soil loss data of good quality. This study was carried out to investigate the combined effects of these two factors by measurement of runoff and soil loss from replicated plots with different sizes. Materials and Methods: In order to evaluate the variability of runoff and soil loss data seven plots, differing in width and length, were constructed in a uniform slope of 9% at three replicates at Koohin Research Station in Qazvin province. The plots were ploughed up to down slope in September 2011. Each plot was isolated using soil beds with a height of 30 cm, to direct generated surface runoff to the lower part of the plots. Runoff collecting systems composed of gutters, pipes and tankswere installed at the end of each plot. During the two-year study period of 2011-2012, plots were maintained in bare conditions and runoff and soil loss were measured for each single event. Precipitation amounts and characteristics were directly measured by an automatic recording tipping-bucket rain gauge located about 200 m from the experimental plots. The entire runoff volume including eroded sediment was measured on
Vema, Vamsikrishna; Sudheer, K. P.; Chaubey, I.
Watershed hydrological models are effective tools for simulating the hydrological processes in the watershed. Although there are a plethora of hydrological models, none of them can be directly applied to make water conservation decisions in irregularly bounded areas that do not confirm to topographically defined ridge lines. This study proposes a novel hydrological model that can be directly applied to any catchment, with or without ridge line boundaries. The model is based on the water balance concept, and a linear function concept to approximate the cross-boundary flow from upstream areas to the administrative catchment under consideration. The developed model is tested in 2 watersheds - Riesel Experimental Watershed and a sub-basin of Cedar Creek Watershed in Texas, USA. Hypothetical administrative catchments that did not confirm to the location of ridge lines were considered for verifying the efficacy of the model for hydrologic simulations. The linear function concept used to account the cross boundary flow was based on the hypothesis that the flow coming from outside the boundary to administrative area was proportional to the flow generated in the boundary grid cell. The model performance was satisfactory with an NSE and r2 of ≥0.80 and a PBIAS of administrative catchments of the watersheds were in good agreement with the observed hydrographs, indicating a satisfactory performance of the model in the administratively bounded areas.
Jarihani, B.; Sidle, R. C.; Roth, C. H.; Bartley, R.; Wilkinson, S. N.
Understanding the effects of grazing management and land cover changes on surface hydrology is important for water resources and land management. A distributed hydrological modelling platform, wflow, (that was developed as part of Deltares's OpenStreams project) is used to assess the effect of land management practices on runoff generation processes. The model was applied to Weany Creek, a small catchment (13.6 km2) of the Burdekin Basin, North Australia, which is being studied to understand sources of sediment and nutrients to the Great Barrier Reef. Satellite and drone-based ground cover data, high resolution topography from LiDAR, soil properties, and distributed rainfall data were used to parameterise the model. Wflow was used to predict total runoff, peak runoff, time of rise, and lag time for several events of varying magnitudes and antecedent moisture conditions. A nested approach was employed to calibrate the model by using recorded flow hydrographs at three scales: (1) a hillslope sub-catchment: (2) a gullied sub-catchment; and the 13.6 km2 catchment outlet. Model performance was evaluated by comparing observed and predicted stormflow hydrograph attributes using the Nash Sutcliffe efficiency metric. By using a nested approach, spatiotemporal patterns of overland flow occurrence across the catchment can also be evaluated. The results show that a process-based distributed model can be calibrated to simulate spatial and temporal patterns of runoff generation processes, to help identify dominant processes which may be addressed by land management to improve rainfall retention. The model will be used to assess the effects of ground cover changes due to management practices in grazed lands on storm runoff.
Granato, Gregory E.; Tessler, Steven
A National highway and urban runoff waterquality metadatabase was developed by the U.S. Geological Survey in cooperation with the Federal Highway Administration as part of the National Highway Runoff Water-Quality Data and Methodology Synthesis (NDAMS). The database was designed to catalog available literature and to document results of the synthesis in a format that would facilitate current and future research on highway and urban runoff. This report documents the design and implementation of the NDAMS relational database, which was designed to provide a catalog of available information and the results of an assessment of the available data. All the citations and the metadata collected during the review process are presented in a stratified metadatabase that contains citations for relevant publications, abstracts (or previa), and reportreview metadata for a sample of selected reports that document results of runoff quality investigations. The database is referred to as a metadatabase because it contains information about available data sets rather than a record of the original data. The database contains the metadata needed to evaluate and characterize how valid, current, complete, comparable, and technically defensible published and available information may be when evaluated for application to the different dataquality objectives as defined by decision makers. This database is a relational database, in that all information is ultimately linked to a given citation in the catalog of available reports. The main database file contains 86 tables consisting of 29 data tables, 11 association tables, and 46 domain tables. The data tables all link to a particular citation, and each data table is focused on one aspect of the information collected in the literature search and the evaluation of available information. This database is implemented in the Microsoft (MS) Access database software because it is widely used within and outside of government and is familiar to many
Iseri, Haruka; Hiramatsu, Kazuaki; Harada, Masayoshi
A distributed model was developed in order to simulate the process of nitrogen and phosphorus load runoff in the semi-urban watershed of the Chikugo River, Japan. A grid of cells 1km in size was laid over the study area, and several input variables for each cell area including DEM, land use and statistical data were extracted by GIS. In the process of water runoff, hydrograph calculated at Chikugo Barrage was in close agreement with the observed one, which achieved Nash-Sutcliffe coefficient of 0.90. In addition, the model simulated reasonably well the movement of TN and TP at each station. The model was also used to analyze three scenarios based on the watershed management: (1) reduction of nutrient loads from livestock farm, (2) improvement of septic tanks' wastewater treatment system and (3) application of purification function of paddy fields. As a result, effectiveness of management strategy in each scenario depended on land use patterns. The reduction rates of nutrient load effluent in scenarios (1) and (3) were higher than that in scenario (2). The present result suggests that an appropriate management of livestock farm together with the effective use of paddy environment would have significant effects on the reduction of nutrient loads. A suitable management strategy should be planned based on the land use pattern in the watershed.
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.
Stewart, M. K.; Fahey, B. D.
The east Otago uplands of New Zealand's South Island have long been studied because of the environmental consequences of converting native tussock grasslands to other land covers, notably forestry and pasture for stock grazing. Early studies showed that afforestation substantially reduced annual water yield, stream peak flows, and 7-day low flows, mainly as a consequence of increased interception. Tritium measurements have indicated that surprisingly old water is present in catchments GH1 and GH2, and the small headwater wetland and catchment (GH5). The old water contributes strongly to baseflow (and therefore also to quickflow). The data have been simulated assuming the presence of two types of water in the baseflow, young water from shallow aquifers connecting hillside regolith with the stream, and old water from deep bedrock aquifers, respectively. The mean transit time of the young water is of the order of months, while that of the old water is 25-26 years as revealed by the presence of tritium originating from the bomb-peak in NZ rainfall in late 1960s and early 1970s. Such a long transit time indicates slow release from groundwater reservoirs within the bedrock, which constitute by far the larger of the water stores. Comparison of the results from catchments GH1 (tussock) and GH2 (pine forest) suggests that about equal quantities of water (85 mm annually) are contributed from the deep aquifers in the two catchments, although runoff from the shallow aquifers has been strongly reduced by afforestation in GH2.
Sanders, Michael J.; Markstrom, Steven L.; Regan, R. Steven; Atkinson, R. Dwight
A module for simulation of daily mean water temperature in a network of stream segments has been developed as an enhancement to the U.S. Geological Survey Precipitation Runoff Modeling System (PRMS). This new module is based on the U.S. Fish and Wildlife Service Stream Network Temperature model, a mechanistic, one-dimensional heat transport model. The new module is integrated in PRMS. Stream-water temperature simulation is activated by selection of the appropriate input flags in the PRMS Control File and by providing the necessary additional inputs in standard PRMS input files.This report includes a comprehensive discussion of the methods relevant to the stream temperature calculations and detailed instructions for model input preparation.
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
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...
I discuss aspects of composite models of quarks and leptons connected with the dynamics of how these fermions acquire mass. Several issues related to the protection mechanisms necessary to keep quarks and leptons light are illustrated by means of concrete examples and a critical overview of suggestions for family replications is given. Some old and new ideas of how one may actually be able to generate small quark and lepton masses are examined, along with some of the difficulties they encounter in practice. (orig.)
Brande, T. van den; Blocken, B.J.E.; Roels, S.
Wind-driven rain (WDR) is one of the most important moisture sources for a building facade. Therefore, a reliable prediction of WDR loads is a prerequisite to assess the durability of building facade components. However, current state of the art Heat-Air-Moisture (HAM) models that are used to assess
Full Text Available Due to increasing pressures on water resources, there is a need to monitor regional water resource availability in a spatially and temporally explicit manner. However, for many parts of the world, there is insufficient data to quantify stream flow or ground water infiltration rates. We present the results of a pixel-based water balance formulation to partition rainfall into evapotranspiration, surface water runoff and potential ground water infiltration. The method leverages remote sensing derived estimates of precipitation, evapotranspiration, soil moisture, Leaf Area Index, and a single F coefficient to distinguish between runoff and storage changes. The study produced significant correlations between the remote sensing method and field based measurements of river flow in two Vietnamese river basins. For the Ca basin, we found R2 values ranging from 0.88–0.97 and Nash–Sutcliffe efficiency (NSE values varying between 0.44–0.88. The R2 for the Red River varied between 0.87–0.93 and NSE values between 0.61 and 0.79. Based on these findings, we conclude that the method allows for a fast and cost-effective way to map water resource availability in basins with no gauges or monitoring infrastructure, without the need for application of sophisticated hydrological models or resource-intensive data.
Oulehle, F; Cosby, B J; Austnes, K; Evans, C D; Hruška, J; Kopáček, J; Moldan, F; Wright, R F
Nitrogen (N) deposition is globally considered as a major threat to ecosystem functioning with important consequences for biodiversity, carbon sequestration and N retention. Lowered N retention as manifested by elevated concentrations of inorganic N in surface waters indicates ecosystem N saturation. Nitrate (NO3) concentrations in runoff from semi-natural catchments typically show an annual cycle, with low concentrations during the summer and high concentrations during the winter. Process-oriented catchment-scale biogeochemical models provide tools for simulation and testing changes in surface water and soil chemistry in response to changes in sulphur (S) and N deposition and climate. Here we examine the ability of MAGIC to simulate the observed monthly as well as the long-term trends over 10-35 years of inorganic N concentrations in streamwaters from four monitored headwater catchments in Europe: Čertovo Lake in the Czech Republic, Afon Gwy at Plynlimon, UK, Storgama, Norway and G2 NITREX at Gårdsjön, Sweden. The balance between N inputs (mineralization+deposition) and microbial immobilization and plant uptake defined the seasonal pattern of NO3 leaching. N mineralization and N uptake were assumed to be governed by temperature, described by Q10 functions. Seasonality in NO3 concentration and fluxes were satisfactorily reproduced at three sites (R2 of predicted vs. modelled concentrations varied between 0.32 and 0.47 and for fluxes between 0.36 and 0.88). The model was less successful in reproducing the observed NO3 concentrations and fluxes at the experimental N addition site G2 NITREX (R2=0.01 and R2=0.19, respectively). In contrast to the three monitored sites, Gårdsjön is in a state of change from a N-limited to N-rich ecosystem due to 20 years of experimental N addition. At Gårdsjön the measured NO3 seasonal pattern did not follow typical annual cycle for reasons which are not well understood, and thus not simulated by the model. The MAGIC model is
Reano, Dane C; Haver, Darren L; Oki, Lorence R; Yates, Marylynn V
Investigations into the microbiological impacts of urban runoff on receiving water bodies, especially during storm conditions, have yielded general paradigms that influence runoff abatement and control management strategies. To determine whether these trends are present in other runoff sources, the physical, chemical, and microbiological components of residential runoff from eight neighborhoods in Northern and Southern California were characterized over the course of five years. Sampling occurred regularly and during storm events, resulting in 833 data sets. Analysis of runoff data assisted in characterizing residential runoff, elucidating differences between dry and storm conditions, and identifying surrogates capable of assessing microbiological quality. Results indicate that although microbial loading increases during storm events similar to urban runoff, annual microbial loading in these study sites principally occurs during dry conditions (24% storm, 76% dry). Generated artificial neural network and multiple linear regression models assessed surrogate performance by accurately predicting Escherichia coli concentrations from validation data sets (R(2) = 0.74 and 0.77, respectively), but required input from other fecal indicator organism (FIO) variables to maintain performance (R(2) = 0.27 and 0.18, respectively, without FIO). This long-term analysis of residential runoff highlights characteristics distinct from urban runoff and establishes necessary variables for determining microbiological quality, thus better informing future management strategies. Copyright © 2015 Elsevier Ltd. All rights reserved.
Hasan, Emad; Tarhule, Aondover; Kirstetter, Pierre-Emmanuel; Clark, Race; Hong, Yang
In data scarce basins, such as the Nile River Basin (NRB) in Africa, constraints related to data availability, quality, and access often complicate attempts to estimate runoff sensitivity using conventional methods. In this paper, we show that by integrating the concept of the aridity index (AI) (derived from the Budyko curve) and climate elasticity, we can obtain the first order response of the runoff sensitivity using minimal data input and modeling expertise or experience. The concept of runoff elasticity relies on the fact that the energy available for evapotranspiration plays a major role in determining whether the precipitation received within a drainage basin generates runoff. The approach does not account for human impacts on runoff modification and or diversions. By making use of freely available gauge-corrected satellite data for precipitation, temperature, runoff, and potential evapotranspiration, we derived the sensitivity indicator (β) to determine the runoff response to changes in precipitation and temperature for four climatic zones in the NRB, namely, tropical, subtropical, semiarid and arid zones. The proposed sensitivity indicator can be partitioned into different elasticity components i.e: precipitation (εp), potential evapotranspiration (εETp), temperature (εT) and the total elasticity (εtot) . These elasticities allow robust quantification of the runoff response to the potential changes in precipitation and temperature with a high degree of accuracy. Results indicate that the tropical zone is energy-constrained with low sensitivity, (β 1.0) . The subtropical-highland zone moves between energy-limited to water-limited conditions during periods of wet and dry spells with varying sensitivity. The semiarid and arid zones are water limited, with high sensitivity, (β > 1.0) . The calculated runoff elasticities show that a 10% decrease in precipitation leads to a decrease in runoff of between 19% in the tropical zone and 30% in the arid zones
van Heeswijk, Marijke
Surface water has been diverted from the Salmon Creek Basin for irrigation purposes since the early 1900s, when the Bureau of Reclamation built the Okanogan Project. Spring snowmelt runoff is stored in two reservoirs, Conconully Reservoir and Salmon Lake Reservoir, and gradually released during the growing season. As a result of the out-of-basin streamflow diversions, the lower 4.3 miles of Salmon Creek typically has been a dry creek bed for almost 100 years, except during the spring snowmelt season during years of high runoff. To continue meeting the water needs of irrigators but also leave water in lower Salmon Creek for fish passage and to help restore the natural ecosystem, changes are being considered in how the Okanogan Project is operated. This report documents development of a precipitation-runoff model for the Salmon Creek Basin that can be used to simulate daily unregulated streamflows. The precipitation-runoff model is a component of a Decision Support System (DSS) that includes a water-operations model the Bureau of Reclamation plans to develop to study the water resources of the Salmon Creek Basin. The DSS will be similar to the DSS that the Bureau of Reclamation and the U.S. Geological Survey developed previously for the Yakima River Basin in central southern Washington. The precipitation-runoff model was calibrated for water years 1950-89 and tested for water years 1990-96. The model was used to simulate daily streamflows that were aggregated on a monthly basis and calibrated against historical monthly streamflows for Salmon Creek at Conconully Dam. Additional calibration data were provided by the snowpack water-equivalent record for a SNOTEL station in the basin. Model input time series of daily precipitation and minimum and maximum air temperatures were based on data from climate stations in the study area. Historical records of unregulated streamflow for Salmon Creek at Conconully Dam do not exist for water years 1950-96. Instead, estimates of
Ph.H.B.F. Franses (Philip Hans); S. Stremersch (Stefan)
textabstractUsing only aggregate sales data, the model we propose decomposes the diffusion processes of the respective technological generations and tests if different technological generations have different diffusion parameters. It also estimates the location of the generational transition from
Baumatz, D.; Milner, M.
The 4-channel delay generator model 5740 generates 4-pulse groups in independent channels. The device offers the possibility of controlling both the time intervals between the pulses of a group and the rate of generation of groups
Latron, J.; Solar, M.; Nord, G.; Llorens, P.; Gallart, F.
Hydrological response and runoff processes have been studied in the Vallcebre research basins (North Eastern Spain) for almost 20 years. Results obtained allowed to build a more complete perceptual model of the hydrological functioning of Mediterranean mountains basins. On a seasonal and monthly scale, there was no simple relationship between rainfall and runoff depths. Monthly rainfall and runoff values revealed the existence of a threshold in the relationship between rainfall and runoff depths. At the event scale, the storm-flow coefficient had a clear seasonal pattern. The effect of the water table position on how rainfall and runoff volumes relate was observed. Examination of soil water potential and water table dynamics during representative floods helped to identify 3 types of characteristic hydrological behaviour during the year. Under dry conditions, runoff was generated essentially as infiltration excess runoff in low permeable areas, whereas saturation excess runoff dominated during wetting-up and wet conditions. During wetting-up transition, saturated areas resulted from the development of scattered perched water tables, whereas in wet conditions they were linked to the rise of the shallow water table. (Author) 8 refs.
Jennett, Tyson S; Zheng, Youbin
This review is a synthesis of the current knowledge regarding the effects of green roof substrate components and their retentive capacity for nutrients, particularly phosphorus (P). Substrates may behave as either sources or sinks of P depending on the components they are formulated from, and to date, the total P-adsorbing capacity of a substrate has not been quantified as the sum of the contributions of its components. Few direct links have been established among substrate components and their physicochemical characteristics that would affect P-retention. A survey of recent literature presented herein highlights the trends within individual component selection (clays and clay-like material, organics, conventional soil and sands, lightweight inorganics, and industrial wastes and synthetics) for those most common during substrate formulation internationally. Component selection will vary with respect to ease of sourcing component materials, cost of components, nutrient-retention capacity, and environmental sustainability. However, the number of distinct components considered for inclusion in green roof substrates continues to expand, as the desires of growers, material suppliers, researchers and industry stakeholders are incorporated into decision-making. Furthermore, current attempts to characterize the most often used substrate components are also presented whereby runoff quality is correlated to entire substrate performance. With the use of well-described characterization (constant capacitance model) and modeling techniques (the soil assemblage model), it is proposed that substrates optimized for P adsorption may be developed through careful selection of components with prior knowledge of their chemical properties, that may increase retention of P in plant-available forms, thereby reducing green roof fertilizer requirements and P losses in roof runoff. Copyright © 2017 Elsevier Ltd. All rights reserved.
Full Text Available Introduction: Snowmelt runoff plays an important role in providing water and agricultural resources, especially in mountainous areas. There are different methods to simulate the process of snowmelt. Inter alia, degree-day model, based on temperature-index is more cited. Snowmelt Runoff Model is a conceptual hydrological model to simulate and predict the daily flow of rivers in the mountainous basins on the basis of comparing the accuracy of AVHRR and TM satellite images to determine snow cover in Karun Basin. Additionally, overestimation of snow-covered area decreased with increasing spatial resolution of satellite data.Studies conducted in the Zayandehrood watershed dam, showed that in the calculation of the snow map cover, changes from MODIS satellite imagery, at the time that the image does not exist, using the digital elevation model and regression analysis can provide to estimate the appropriate data from satellites. In the study of snow cover in eastern Turkey, in the mountainous regions of the Euphrates River, data from five meteorological stations and MODIS images were used with a resolution of 500 m. The results showed that satellite images have a good accuracy in estimating snow cover. In a Watershed in northern Pakistan in the period from 2000 to 2006, SRM model was used to estimate the snow cover using MODIS images. The purpose of this study was to evaluate the snowmelt runoff using remote sensing data and SRM model for flow simulation, based on statistical parameters in the Kardeh dam basin. Materials and Methods: Kardeh dam basin has an area of about 560 square kilometers and is located in the north of Mashhad. This area is in the East of Hezarmasjed – kopehdagh zone that is one of the main basins of Kashafrood. This basin is a mountainous area. About 261 km of the basin is located at above 2000 m. The lowest point of the basin is at the watershed outlet with1300 meters and the highest point in the basin, in the North West part
Wilusz, D. C.; Harman, C. J.; Ball, W. P.; Maxwell, R. M.; Buda, A. R.
The backward transit-time distribution (bTTD) is the time-varying, probabilistic distribution of water travel times or, equivalently, water ages in catchment outflow. The bTTD is increasingly seen as a master variable of catchment hydrology that links flow and transport processes, in part because it is believed to embed information about runoff generation mechanisms (RGMs) that are difficult to directly observe. The ability to use water age to make inferences about RGMs depends on the degree of "age equifinality" in a watershed, defined here as the phenomenon where significant volumes of similarly-aged water are delivered to the outlet by different RGMs at the same time. When age equifinality is low (e.g., all discharge is old groundwater), the mapping of water age to the RGM may be simple; when age equifinality is high (e.g., discharge is a mix of old groundwater and old interflow), this mapping may be impossible. In this study we conduct experiments in a virtual watershed to (1) understand the hydrologic conditions that lead to age equifinality, (2) identify relationships between water age and RGMs that are particularly obscured/unobscured by age equifinality, and (3) test the generalizability of these relationships in other watersheds. Our experiments used the fully-distributed surface-groundwater model ParFlow, which simulates a suite of RGMs, plus SLIM-FAST particle tracking. To improve realism, the watershed model was parameterized and forced using extensive field data from the USDA's Mahantango Creek experimental catchment in PA, USA. The model output is being interrogated to understand the time-varying relationships between the composition of RGMs and the bTTD at the outlet. We are also testing the robustness of these relationships by re-running our model with controlled differences in climate, topography, and scale. Initial results suggest high age equifinality at peak flows due to overlapping young water contributions from infiltration- and saturation
Full Text Available Frequency and intensity of river floods rise observed in the North Caucasus during last decades is considered to be driven by recent climate change. In order to predict possible future trends in extreme hydrological events in the context of climate change, it is essential to estimate the contribution of different feed sources in complicated flow-forming processes in the alpine part of the North Caucasus. A study was carried out for the Djankuat River basin, the representative for the North Caucasus system. Simultaneous measurements of electrical conductivity, isotopic and ion balance equations, and energy balance modeling of ice and snow melt were used to evaluate the contribution of different sources and processes in the Djankuat River runoff regime formation. A forecast of possible future changes in the Djankuat glacier melting regime according to the predicted climate changes was done.
Hazenberg, Pieter; Leijnse, Hidde; Uijlenhoet, Remko
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.
Moustafa, S.; Rennermalm, A.; van As, D.; Overeem, I.; Tedesco, M.; Mote, T. L.; Koenig, L.; Smith, L. C.; Hagedorn, B.; Sletten, R. S.; Mikkelsen, A. B.; Hasholt, B.; Hall, D. K.; Fettweis, X.; Pitcher, L. H.; Hubbard, A.
Greenland ice sheet surface ablation now dominates its total mass loss contributions to sea-level rise. Despite the increasing importance of Greenland's sea-level contribution, a quantitative inter-comparison between modeled and measured melt, runoff and discharge across multiple drainage basins is conspicuously lacking. Here we investigate the accuracy of model discharge estimates from the Modèle Atmosphérique Régionale (MAR v3.5.2) regional climate model by comparison with in situ proglacial river discharge measurements at three West Greenland drainage basins - North River (Thule), Watson River (Kangerlussuaq), and Naujat Kuat River (Nuuk). At each target catchment, we: 1) determine optimal drainage basin delineations; 2) assess primary drivers of melt; 3) evaluate MAR at daily, 5-, 10- and 20-day time scales; and 4) identify potential sources for model-observation discrepancies. Our results reveal that MAR resolves daily discharge variability poorly in the Nuuk and Thule basins (r2 = 0.4-0.5), but does capture variability over 5-, 10-, and 20-day means (r2 > 0.7). Model agreement with river flow data, though, is reduced during periods of peak discharge, particularly for the exceptional melt and discharge events of July 2012. Daily discharge is best captured by MAR across the Watson River basin, whilst there is lower correspondence between modeled and observed discharge at the Thule and Naujat Kuat River basins. We link the main source of model error to an underestimation of cloud cover, overestimation of surface albedo, and apparent warm bias in near-surface air temperatures. For future inter-comparison, we recommend using observations from catchments that have a self-contained and well-defined drainage area and an accurate discharge record over variable years coincident with a reliable automatic weather station record. Our study highlights the importance of improving MAR modeled surface albedo, cloud cover representation, and delay functions to reduce model
Athron, Peter; Park, Jae-hyeon; Stöckinger, Dominik; Voigt, Alexander
We introduce FlexibleSUSY, a Mathematica and C++ package, which generates a fast, precise C++ spectrum generator for any SUSY model specified by the user. The generated code is designed with both speed and modularity in mind, making it easy to adapt and extend with new features. The model is specified by supplying the superpotential, gauge structure and particle content in a SARAH model file; specific boundary conditions e.g. at the GUT, weak or intermediate scales are defined in a separate FlexibleSUSY model file. From these model files, FlexibleSUSY generates C++ code for self-energies, tadpole corrections, renormalization group equations (RGEs) and electroweak symmetry breaking (EWSB) conditions and combines them with numerical routines for solving the RGEs and EWSB conditions simultaneously. The resulting spectrum generator is then able to solve for the spectrum of the model, including loop-corrected pole masses, consistent with user specified boundary conditions. The modular structure of the generated code allows for individual components to be replaced with an alternative if available. FlexibleSUSY has been carefully designed to grow as alternative solvers and calculators are added. Predefined models include the MSSM, NMSSM, E6SSM, USSM, R-symmetric models and models with right-handed neutrinos.
Sundqvist, Jan-Olov; Stenmarck, Aasa; Ekvall, Tomas
The research presented in this report is part of the effort to estimate future Swedish waste quantities in the research programme Towards Sustainable Waste Management. More specifically, we estimate future waste coefficients that are designed to be fed into EMEC, which describes the Swedish economy in terms of 26 industrial sectors, a public sector, and households. Production in the model of industry and public sector requires input of labour, capital, energy, and other commodities. With waste-intensity coefficients added to each production parameter in each sector, EMEC can calculate the future waste quantities generated in different economic scenarios. To produce the waste-intensity coefficients, we make a survey of the current Swedish waste statistics. For each waste category from each sector we estimate whether the quantity depends primarily on the production in the sector, on the inputs of commodities, on the depreciation of capital goods, or on the size of the workforce in the sector. We calculate current waste-intensity coefficients by dividing the waste quantities by the parameter(s) to which they are assigned. We also present five different scenarios to describe how the waste intensity can develop until the year 2030. As far as possible and when deemed to be relevant, we have set the industrial waste generation to depend on the use of a commodity or an energy carrier. The quantity of spent vehicles and most equipment is set to depend on the depreciation of capital goods. Some wastes have been allocated to the staff, for example household waste from business. The quantities of wastes from households have a similar approach where every waste category is assigned to a combination of 26 different commodities
Maaløe, Lars; Fraccaro, Marco; Winther, Ole
Deep generative models trained with large amounts of unlabelled data have proven to be powerful within the domain of unsupervised learning. Many real life data sets contain a small amount of labelled data points, that are typically disregarded when training generative models. We propose the Clust...... a log-likelihood of −79.38 nats on permutation invariant MNIST, while also achieving competitive semi-supervised classification accuracies. The model can also be trained fully unsupervised, and still improve the log-likelihood performance with respect to related methods.......Deep generative models trained with large amounts of unlabelled data have proven to be powerful within the domain of unsupervised learning. Many real life data sets contain a small amount of labelled data points, that are typically disregarded when training generative models. We propose the Cluster...
Panday, Prajjwal K.; Williams, Christopher A.; Frey, Karen E.; Brown, Molly E.
Previous studies have drawn attention to substantial hydrological changes taking place in mountainous watersheds where hydrology is dominated by cryospheric processes. Modelling is an important tool for understanding these changes but is particularly challenging in mountainous terrain owing to scarcity of ground observations and uncertainty of model parameters across space and time. This study utilizes a Markov Chain Monte Carlo data assimilation approach to examine and evaluate the performance of a conceptual, degree-day snowmelt runoff model applied in the Tamor River basin in the eastern Nepalese Himalaya. The snowmelt runoff model is calibrated using daily streamflow from 2002 to 2006 with fairly high accuracy (average Nash-Sutcliffe metric approx. 0.84, annual volume bias runoff in the Tamor River basin for the 2002-2006 period is estimated to be 29.7+/-2.9% (which includes 4.2+/-0.9% from snowfall that promptly melts), whereas 70.3+/-2.6% is attributed to contributions from rainfall. On average, the elevation zone in the 4000-5500m range contributes the most to basin runoff, averaging 56.9+/-3.6% of all snowmelt input and 28.9+/-1.1% of all rainfall input to runoff. Model simulated streamflow using an interpolated precipitation data set decreases the fractional contribution from rainfall versus snowmelt compared with simulations using observed station precipitation. Model experiments indicate that the hydrograph itself does not constrain estimates of snowmelt versus rainfall contributions to total outflow but that this derives from the degree-day melting model. Lastly, we demonstrate that the data assimilation approach is useful for quantifying and reducing uncertainty related to model parameters and thus provides uncertainty bounds on snowmelt and rainfall contributions in such mountainous watersheds.
Hong, Nian; Hama, Takehide; Suenaga, Yuichi; Aqili, Sayed Waliullah; Huang, Xiaowu; Wei, Qiaoyan; Kawagoshi, Yasunori
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.
da Silva, Felipe das Neves Roque; Alves, José Luis Drummond; Cataldi, Marcio
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
DOE DWDCG. Tables were then created for each analyte that listed the PRSs average value by storm water station allowing a tabular view of the mapped data. The final table that was created listed the number of high erosion PRSs and regular PRSs over background values that were contained in each watershed. An overall relationship between the high erosion PRSs or the regular PRSs and the storm water stations was not identified through the methods used in this research. However, the Arc Hydro data models created for this analysis were used to track possible sources of contamination found through sampling at the storm water gaging stations. This geometric network tracing was used to identify possible relationships between the storm water stations and the PRSs. The methods outlined for the geometric network tracing could be used to find other relationships between the sites. A cursory statistical analysis was performed which could be expanded and applied to the data sets generated during this research to establish a broader relationship between the PRSs and storm water stations
Full Text Available Soil erosion has been recognized as one of the major threats to our environment and water quality worldwide, especially in China. To mitigate nonpoint source water quality problems caused by soil erosion, best management practices (BMPs and/or conservation programs have been adopted. Watershed models, such as the Annualized Agricultural Non-Point Source Pollutant Loading model (AnnAGNPS, have been developed to aid in the evaluation of watershed response to watershed management practices. The model has been applied worldwide and proven to be a very effective tool in identifying the critical areas which had serious erosion, and in aiding in decision-making processes for adopting BMPs and/or conservation programs so that cost/benefit can be maximized and non-point source pollution control can be achieved in the most efficient way. The main goal of this study was to assess the characteristics of soil erosion, sediment and sediment delivery of a watershed so that effective conservation measures can be implemented. To achieve the overall objective of this study, all necessary data for the 4,184 km2 Daning River watershed in the Three-Gorge region of the Yangtze River of China were assembled. The model was calibrated using observed monthly runoff from 1998 to 1999 (Nash-Sutcliffe coefficient of efficiency of 0.94 and R2 of 0.94 and validated using the observed monthly runoff from 2003 to 2005 (Nash-Sutcliffe coefficient of efficiency of 0.93 and R2 of 0.93. Additionally, the model was validated using annual average sediment of 2000–2002 (relative error of −0.34 and 2003–2004 (relative error of 0.18 at Wuxi station. Post validation simulation showed that approximately 48% of the watershed was under the soil loss tolerance released by the Ministry of Water Resources of China (500 t·km−2·y−1. However, 8% of the watershed had soil erosion of exceeding 5,000 t·km−2
Singh, R. K.; Panda, R. K.; Satapathy, K. K.; Ngachan, S. V.
SummaryA study was undertaken to develop appropriate vegetative as well as structural measures to control sediment yield from a 239.44 ha small multi-vegetated watershed in high rainfall and high land slope conditions of eastern Himalayan range in India using a physically based distributed parameters Water Erosion Prediction Project (WEPP) model. The model was calibrated and validated using field-measured data pertaining to 86 storms of monsoon season 2003 and 98 storms of 2004. The daily simulated runoff and sediment yield of the Umroi watershed for the calibration and validation periods were found to match with their measured counterparts at 95% significance level as shown by the Student's t-tests. The model simulated daily runoff quite well as corroborated by reasonably high Nash-Sutcliffe simulation coefficients of 0.94 and 0.87, low root mean square errors of 1.42 and 1.77 mm, and low percent deviations of -1.71 and -3.01, respectively for calibration and validation periods. The performance of the model for simulating daily sediment yield was also quite good with Nash-Sutcliffe simulation coefficients of 0.95 and 0.90, root mean square errors of 0.08 and 0.09 Mg ha -1 and percent deviations of 3.05 and -5.23, respectively for calibration and validation periods. Subsequently, the calibrated and validated model was used to simulate vegetative (crop, level of fertilization and tillage) and structural (rock-fill check dam and trash barrier) measures and combinations of vegetative and structural control to evaluate their impacts on runoff and sediment yield reduction. Simulations of different vegetative management scenarios indicated that replacing traditional bun agriculture and upland paddy crop with maize, soybean, and peanut would reduce sediment yield by 18.68, 29.60 and 27.70%, respectively. Field cultivator and drill-no-tillage systems have the potential to reduce sediment yield by 13.14 and 21.88%, respectively as compared to the existing practice of
This tutorial paper provides information relevant to the selection and generation of stochastic inputs to simulation studies. The primary area considered is multivariate but much of the philosophy at least is relevant to univariate inputs as well. 14 refs.
Anderson, R.; Gronewold, A.; Alameddine, I.; Reckhow, K.
The latest official assessment of United States (US) surface water quality indicates that pathogens are a leading cause of coastal shoreline water quality standard violations. Rainfall-runoff and hydrodynamic water quality models are commonly used to predict fecal indicator bacteria (FIB) concentrations in these waters and to subsequently identify climate change, land use, and pollutant mitigation scenarios which might improve water quality and lead to reinstatement of a designated use. While decay, settling, and other loss kinetics dominate FIB fate and transport in freshwater systems, previous authors identify tidal advection as a dominant fate and transport process in coastal estuaries. As a result, acknowledging hydrodynamic model input (e.g. watershed runoff) variability and parameter (e.g tidal dynamics parameter) uncertainty is critical to building a robust coastal water quality model. Despite the widespread application of watershed models (and associated model calibration procedures), we find model inputs and parameters are commonly encoded as deterministic point estimates (as opposed to random variables), an approach which effectively ignores potential sources of variability and uncertainty. Here, we present an innovative approach to building, calibrating, and propagating uncertainty and variability through a coupled data-based mechanistic (DBM) rainfall-runoff and tidal prism water quality model. While we apply the model to an ungauged tributary of the Newport River Estuary (one of many currently impaired shellfish harvesting waters in Eastern North Carolina), our model can be used to evaluate water quality restoration scenarios for coastal waters with a wide range of designated uses. We begin by calibrating the DBM rainfall-runoff model, as implemented in the IHACRES software package, using a regionalized calibration approach. We then encode parameter estimates as random variables (in the rainfall-runoff component of our comprehensive model) via the
Full Text Available Direct measurement of surface runoff is often associated with errors and inaccuracies which results to unreliable hydrological data. An automatic Runoff-meter using tipping buckets arrangement calibrated to tip 0.14 liter of runoff water per tip with an accuracy of ± 0.001 litre was used to measure surface runoff from a steel bounded soil tray of dimension (1200 mm X 900 mm X 260 mm filled with sand loamy to the depth of 130 mm and inclined at angle (0 0 , 5 0 ,12 0 and 15 0 horizontal to the instrument. The effect of varying angles of inclination on runoff intensity, sediment loss rate and sediment loss is significant at 5 % confidence level, while surface runoff is not significant at 5 % confidence level. Total highest sediment loss of 458.2 g and 313.4 g were observed at angle 15 0 and 12 0 respectively. Total surface runoff of 361.5 mm and 445.8 mm were generated at inclined angle of 0 0 and 5 0 , while at angle 12 0 and 15 0 , 564.3 mm and 590.0 mm of surface runoff were generated. In addition, runoff intensity and sediment loss rate were highest at angle 15 0 , while the lowest values of 1.5mm/min and 5.43 g/min were obtained at angle of inclination 5 0 . The results showed that strong relationship existed among the hydrological variables as a result of subjecting the steel bounded soil tray to different angles of inclination. Such results would provide useful data for the running of physics-based deterministic model of surface runoff and erosion which will be useful for the design of hydrological structures, land use planning and management.
Segura, C.; Nickolas, L. B.; Leshchinsky, B. A.
Even though it is widely recognized that water quality and availability are crucial to society and wildlife sustainability, we are still not able to predict how much water is moved through a given catchment after a storm event nor what nutrients, solutes, and contaminates are mobilized. We will present preliminary results of a study incorporating of hydrometric information, water stable isotopes (δ18O), and concentrations of total nitrogen (TN), ammonia (NH3), and nitrate (NO3) within 4 sites in a nested framework at the HJ Andrews Experimental Forest (HJA), OR. Preliminary analysis of 2 storms (54mm and 145mm) indicate highly variable responses across space along with a positive relation between transit time of event water and storm magnitude in all catchments. In addition there appears to be a moisture threshold after which transit time scales with drainage area across the landscape likely related to higher degree of connectivity. We also found a strong correlation between transit times computed based on temporal variability of δ18O and electrical connectivity (EC). This lead to the analysis of over 50 storm across 10 catchments in the HJA during the last 3 years. In-stream NO3- during storm response are highest within the smaller catchments (1-5 km2) and tend to remain elevated throughout the response period. The larger catchments (15-64 km2) demonstrate smaller increases in NO3-, the response time lags behind that of the smaller catchments, and the concentration returns rapidly to baseflow conditions rather than remaining elevated. In contrast, in-stream NH3 show a higher degree of similarity between sites in terms of magnitude and timing of increases in concentration over the duration of the response period. Ultimately we found that fractions of inorganic nitrogen correlate with transit time and drainage area, opening the possibility of a catchment wide model of nutrient export prediction.
Full Text Available A conceptual lumped rainfall-runoff flood event model was developed and applied on the Gardon catchment located in Southern France and various single-objective and multi-objective functions were used for its calibration. The model was calibrated on 15 events and validated on 14 others. The results of both the calibration and validation phases are compared on the basis of their performance with regards to six criteria, three global criteria and three relative criteria representing volume, peakflow, and the root mean square error. The first type of criteria gives more weight to large events whereas the second considers all events to be of equal weight. The results show that the calibrated parameter values are dependent on the type of criteria used. Significant trade-offs are observed between the different objectives: no unique set of parameters is able to satisfy all objectives simultaneously. Instead, the solution to the calibration problem is given by a set of Pareto optimal solutions. From this set of optimal solutions, a balanced aggregated objective function is proposed, as a compromise between up to three objective functions. The single-objective and multi-objective calibration strategies are compared both in terms of parameter variation bounds and simulation quality. The results of this study indicate that two well chosen and non-redundant objective functions are sufficient to calibrate the model and that the use of three objective functions does not necessarily yield different results. The problems of non-uniqueness in model calibration, and the choice of the adequate objective functions for flood event models, emphasise the importance of the modeller's intervention. The recent advances in automatic optimisation techniques do not minimise the user's responsibility, who has to choose multiple criteria based on the aims of the study, his appreciation on the errors induced by data and model structure and his knowledge of the
Yu, Pengtao; Wang, Yanhui; Coles, Neil; Xiong, Wei; Xu, Lihong
The "Grain for Green Project" is a country-wide ecological program to converse marginal cropland to forest, which has been implemented in China since 2002. To quantify influence of this significant vegetation change, Guansihe Hydrological (GSH) Model, a validated physically-based distributed hydrological model, was applied to simulate runoff responses to land use change in the Guansihe watershed that is located in the upper reaches of the Yangtze River basin in Southwestern China with an area of only 21.1 km2. Runoff responses to two single rainfall events, 90 mm and 206 mm respectively, were simulated for 16 scenarios of cropland to forest conversion. The model simulations indicated that the total runoff generated after conversion to forest was strongly dependent on whether the land was initially used for dry croplands without standing water in fields or constructed (or walled) paddy fields. The simulated total runoff generated from the two rainfall events displayed limited variation for the conversion of dry croplands to forest, while it strongly decreased after paddy fields were converted to forest. The effect of paddy terraces on runoff generation was dependent on the rainfall characteristics and antecedent moisture (or saturation) conditions in the fields. The reduction in simulated runoff generated from intense rainfall events suggested that afforestation and terracing might be effective in managing runoff and had the potential to mitigate flooding in southwestern China. PMID:26192181
S. H. Ali
Full Text Available The hydrology of Upper Indus basin is not recognized well due to the intricacies in the climate and geography, and the scarcity of data above 5000 m a.s.l where most of the precipitation falls in the form of snow. The main objective of this study is to measure the contributions of different components of runoff in Upper Indus basin. To achieve this goal, the Modified positive degree day model (MPDDM was used to simulate the runoff and investigate its components in two catchments of Upper Indus basin, Hunza and Gilgit River basins. These two catchments were selected because of their different glacier coverage, contrasting area distribution at high altitudes and significant impact on the Upper Indus River flow. The components of runoff like snow-ice melt and rainfall-base flow were identified by the model. The simulation results show that the MPDDM shows a good agreement between observed and modeled runoff of these two catchments and the effects of snow and ice are mainly reliant on the catchment characteristics and the glaciated area. For Gilgit River basin, the largest contributor to runoff is rain-base flow, whereas large contribution of snow-ice melt observed in Hunza River basin due to its large fraction of glaciated area. This research will not only contribute to the better understanding of the impacts of climate change on the hydrological response in the Upper Indus, but will also provide guidance for the development of hydropower potential and water resources assessment in these catchments.
Watershed-scale fate and transport models are important tools for estimating the sources, transformation, and transport of contaminants to surface water systems. Precipitation is one of the primary inputs to watershed biogeochemical models, influencing changes in the water budge...
Deckers, Dave L.E.H.; Booij, Martijn J.; Rientjes, T.H.M.; Krol, Martinus S.
This study attempts to examine if catchment variability favours regionalisation by principles of catchment similarity. Our work combines calibration of a simple conceptual model for multiple objectives and multi-regression analyses to establish a regional model between model sensitive parameters and
Full Text Available A distributed or semi-distributed deterministic hydrological model should consider the hydrologically most relevant catchment characteristics. These are heterogeneously distributed within a watershed but often interrelated and subject to a certain spatial organization which results in archetypes of combined characteristics. In order to reproduce the natural rainfall–runoff response the reduction of variance of catchment properties as well as the incorporation of the spatial organization of the catchment are desirable. In this study the width-function approach is utilized as a basic characteristic to analyse the succession of catchment characteristics. By applying this technique we were able to assess the context of catchment properties like soil or topology along the streamflow length and the network geomorphology, giving indications of the spatial organization of a catchment. Moreover, this information and this technique have been implemented in an algorithm for automated sub-basin ascertainment, which included the definition of zones within the newly defined sub-basins. The objective was to provide sub-basins that were less heterogeneous than common separation schemes. The algorithm was applied to two parameters characterizing the topology and soil of four mid-European watersheds. Resulting partitions indicated a wide range of applicability for the method and the algorithm. Additionally, the intersection of derived zones for different catchment characteristics could give insights into sub-basin similarities. Finally, a HBV96 case study demonstrated the potential benefits of modelling with the new subdivision technique.
Ala-aho, P. O. A.; Tetzlaff, D.; Laudon, H.; McNamara, J. P.; Soulsby, C.
We use the Spatially distributed Tracer-Aided Rainfall-Runoff (STARR) modelling framework to explore non-stationary flow and isotope response in three northern headwater catchments. The model simulates dynamic, spatially variable tracer concentration in different water stores and fluxes within a catchment, which can constrain internal catchment mixing processes, flow paths and associated water ages. To date, a major limitation in using such models in snow-dominated catchments has been the difficulties in paramaterising the isotopic transformations in snowpack accumulation and melt. We use high quality long term datasets for hydrometrics and stable water isotopes collected in three northern study catchments for model calibration and testing. The three catchments exhibit different hydroclimatic conditions, soil and vegetation types, and topographic relief, which brings about variable degree of snow dominance across the catchments. To account for the snow influence we develop novel formulations to estimate the isotope evolution in the snowpack and melt. Algorithms for the isotopic evolution parameterize an isotopic offset between snow evaporation and melt fluxes and the remaining snow storage. The model for each catchment is calibrated to match both streamflow and tracer concentration at the stream outlet to ensure internal consistency of the system behaviour. The model is able to reproduce the streamflow along with the spatio-temporal differences in tracer concentrations across the three studies catchments reasonably well. Incorporating the spatially distributed snowmelt processes and associated isotope transformations proved essential in capturing the stream tracer reponse for strongly snow-influenced cathments. This provides a transferrable tool which can be used to understand spatio-temporal variability of mixing and water ages for different storages and flow paths in other snow influenced, environments.
Dominguez Calle, Efrain Antonio
The application of mathematical modelling to evaluate the hydrological response of different river basins under multiple climate scenarios has become a wide spread tool. However, most of the existing models demand high volumes of data and high data quality. Usually, in Latin America not only the amount of data is scarce, but also the quality of it is very poor, so it is difficult to implement mathematical models with good validation results. Additionally, those models have to be applied over big geographical regions making the hydrological modelling process an almost impossible task. All these factors are pointing to the necessity to develop low data demanding models with few data quality requirements. In this light, this paper shows an attempt to develop a hydrological model under these restrictions. The results shown are concerned with the validation assessment of a study case in Colombia over an extensive region for the Catatumbo watershed. Finally, the improvements currently under implementation are shown
Kansas Data Access and Support Center — This digital spatial data set provides information on the spatial distribution of potential runoff-contributing areas in Kansas. Potential runoff-contributing areas...
Sudeep Marwaha; Alka Aroa; Satma M C; Rajni Jain; R C Goyal
For production systems like expert systems, a rule generation software can facilitate the faster deployment. The software process model for rule generation using decision tree classifier refers to the various steps required to be executed for the development of a web based software model for decision rule generation. The Royce’s final waterfall model has been used in this paper to explain the software development process. The paper presents the specific output of various steps of modified wat...
Versini, Pierre-Antoine; Gires, Auguste; Tchinguirinskaia, Ioulia; Schertzer, Daniel
Currently widespread in new urban projects, green roofs have shown a positive impact on urban runoff at the building scale: decrease and slow-down of the peak discharge, and decrease of runoff volume. The present work aims to study their possible impact at the catchment scale, more compatible with stormwater management issues. For this purpose, a specific module dedicated to simulating the hydrological behaviour of a green roof has been developed in the distributed rainfall-runoff model (Multi-Hydro). It has been applied on a French urban catchment where most of the building roofs are flat and assumed to accept the implementation of a green roof. Catchment responses to several rainfall events covering a wide range of meteorological situations have been simulated. The simulation results show green roofs can significantly reduce runoff volume and the magnitude of peak discharge (up to 80%) depending on the rainfall event and initial saturation of the substrate. Additional tests have been made to assess the susceptibility of this response regarding both spatial distributions of green roofs and precipitation. It appears that the total area of greened roofs is more important than their locations. On the other hand, peak discharge reduction seems to be clearly dependent on spatial distribution of precipitation.
Full Text Available In the distributed hydrological simulations for complex mountain areas, large amounts of meteorological input parameters with high spatial and temporal resolutions are necessary. However, the extreme scarcity and uneven distribution of the traditional meteorological observation stations in cold and arid regions of Northwest China makes it very difficult in meeting the requirements of hydrological simulations. Alternatively, regional climate models (RCMs, which can provide a variety of distributed meteorological data with high temporal and spatial resolution, have become an effective solution to improve hydrological simulation accuracy and to further study water resource responses to human activities and global climate change. In this study, abundant and evenly distributed virtual weather stations in the upper reaches of the Heihe River Basin (HRB of Northwest China were built for the optimization of the input data, and thus a regional integrated environmental model system (RIEMS based on RCM and a distributed hydrological model of soil and water assessment tool (SWAT were integrated as a coupled climate–hydrological RIEMS-SWAT model, which was applied to simulate monthly runoff from 1995 to 2010 in the region. Results show that the simulated and observed values are close; Nash–Sutcliffe efficiency is higher than 0.65; determination coefficient (R2 values are higher than 0.70; percent bias is controlled within ±20%; and root-mean-square-error-observation standard deviation ratio is less than 0.65. These results indicate that the coupled model can present basin hydrological processes properly, and provide scientific support for prediction and management of basin water resources.
Jørgensen, Peter Bjørn; Schmidt, Mikkel Nørgaard; Winther, Ole
Generative deep machine learning models now rival traditional quantum-mechanical computations in predicting properties of new structures, and they come with a significantly lower computational cost, opening new avenues in computational molecular science. In the last few years, a variety of deep...... generative models have been proposed for modeling molecules, which differ in both their model structure and choice of input features. We review these recent advances within deep generative models for predicting molecular properties, with particular focus on models based on the probabilistic autoencoder (or...
Wium-Andersen, Tove; Nielsen, A.H.; Hvitved-Jacobsen, Thorkild
A model, targeting eutrophication of stormwater detention ponds was developed and applied to sim-ulate pH, dissolved oxygen and the development of algae and plant biomass in two mature plantedwetponds for run off control. The model evaluated algal and plant biomass growth into three groupsnamely;...
C.R. Schwalm; D.N. Huntzinger; R.B. Cook; Y. Wei; I.T. Baker; R.P. Neilson; B. Poulter; Peter Caldwell; G. Sun; H.Q. Tian; N. Zeng
Significant changes in the water cycle are expected under current global environmental change. Robust assessment of present-day water cycle dynamics at continental to global scales is confounded by shortcomings in the observed record. Modeled assessments also yield conflicting results which are linked to differences in model structure and simulation protocol. Here we...
Risley, John C.; Granato, Gregory E.
In 2012, the U.S. Geological Survey and the Oregon Department of Transportation began a cooperative study to demonstrate use of the Stochastic Empirical Loading and Dilution Model (SELDM) for runoff-quality analyses in Oregon. SELDM can be used to estimate stormflows, constituent concentrations, and loads from the area upstream of a stormflow discharge site, from the site of interest and in the receiving waters downstream of the discharge. SELDM also can be used to assess the potential effectiveness of best management practices (BMP) for mitigating potential effects of runoff in receiving waters. Nominally, SELDM is a highway-runoff model, but it is well suited for analysis of runoff from other land uses as well. This report provides case studies and examples to demonstrate stochastic-runoff modeling concepts and to demonstrate application of the model. Basin characteristics from six Oregon highway study sites were used to demonstrate various applications of the model. The highway catchment and upstream basin drainage areas of these study sites ranged from 3.85 to 11.83 acres and from 0.16 to 6.56 square miles, respectively. The upstream basins of two sites are urbanized, and the remaining four sites are less than 5 percent impervious. SELDM facilitates analysis by providing precipitation, pre-storm streamflow, and other variables by region or from hydrologically similar sites. In Oregon, there can be large variations in precipitation and streamflow among nearby sites. Therefore, spatially interpolated geographic information system data layers containing storm-event precipitation and pre-storm streamflow statistics specific to Oregon were created for the study using Kriging techniques. Concentrations and loads of cadmium, chloride, chromium, copper, iron, lead, nickel, phosphorus, and zinc were simulated at the six Oregon highway study sites by using statistics from sites in other areas of the country. Water‑quality datasets measured at hydrologically similar
Simões, M Godoy
ForewordPrefaceAcknowledgmentsAuthorsPrinciples of Alternative Sources of Energy and Electric GenerationScope of This ChapterLegal DefinitionsPrinciples of Electrical ConversionBasic Definitions of Electrical PowerCharacteristics of Primary SourcesCharacteristics of Remote Industrial, Commercial, and Residential Sites and Rural EnergySelection of the Electric GeneratorInterfacing Primary Source, Generator, and LoadExample of a Simple Integrated Generating and Energy-Storing SystemSolved ProblemsSuggested ProblemsReferencesSteady-State Model of Induction GeneratorsScope of This ChapterInterconnection and Disconnection of the Electric Distribution NetworkRobustness of Induction GeneratorsClassical Steady-State Representation of the Asynchronous MachineGenerated PowerInduced TorqueRepresentation of Induction Generator LossesMeasurement of Induction Generator ParametersBlocked Rotor Test (s = 1)No-Load Test (s = 0)Features of Induction Machines Working as Generators Interconnected to the Distribution NetworkHigh-...
Qi, Hongkai; Qi, Zhiming; Zhang, T Q; Tan, C S; Sadhukhan, Debasis
Modeling soil phosphorus (P) losses by surface and subsurface flow pathways is essential in developing successful strategies for P pollution control. We used the ICECREAM model to simultaneously simulate P losses in surface and subsurface flow, as well as to assess effectiveness of field practices in reducing P losses. Monitoring data from a mineral-P-fertilized clay loam field in southwestern Ontario, Canada, were used for calibration and validation. After careful adjustment of model parameters, ICECREAM was shown to satisfactorily simulate all major processes of surface and subsurface P losses. When the calibrated model was used to assess tillage and fertilizer management scenarios, results point to a 10% reduction in total P losses by shifting autumn tillage to spring, and a 25.4% reduction in total P losses by injecting fertilizer rather than broadcasting. Although the ICECREAM model was effective in simulating surface and subsurface P losses when thoroughly calibrated, further testing is needed to confirm these results with manure P application. As illustrated here, successful use of simulation models requires careful verification of model routines and comprehensive calibration to ensure that site-specific processes are accurately represented. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.
Chen, X.; Huang, G.
In recent years, distributed hydrological models have been widely used in storm water management, water resources protection and so on. Therefore, how to evaluate the uncertainty of the model reasonably and efficiently becomes a hot topic today. In this paper, the soil and water assessment tool (SWAT) model is constructed for the study area of China's Feilaixia watershed, and the uncertainty of the runoff simulation is analyzed by GLUE method deeply. Taking the initial parameter range of GLUE method as the research core, the influence of different initial parameter ranges on model uncertainty is studied. In this paper, two sets of parameter ranges are chosen as the object of study, the first one (range 1) is recommended by SWAT-CUP and the second one (range 2) is calibrated by SUFI-2. The results showed that under the same number of simulations (10,000 times), the overall uncertainty obtained by the range 2 is less than the range 1. Specifically, the "behavioral" parameter sets for the range 2 is 10000 and for the range 1 is 4448. In the calibration and the validation, the ratio of P-factor to R-factor for range 1 is 1.387 and 1.391, and for range 2 is 1.405 and 1.462 respectively. In addition, the simulation result of range 2 is better with the NS and R2 slightly higher than range 1. Therefore, it can be concluded that using the parameter range calibrated by SUFI-2 as the initial parameter range for the GLUE is a way to effectively capture and evaluate the simulation uncertainty.
Luo, L.; Wang, Z.
Soil Conservation Service Curve Number (SCS-CN) based hydrologic model, has widely been used for agricultural watersheds in recent years. However, there will be relative error when applying it due to differentiation of geographical and climatological conditions. This paper introduces a more adaptable and propagable model based on the modified SCS-CN method, which specializes into two different scale cases of research regions. Combining the typical conditions of the Zhanghe irrigation district in southern part of China, such as hydrometeorologic conditions and surface conditions, SCS-CN based models were established. The Xinbu-Qiao River basin (area =1207 km2) and the Tuanlin runoff test area (area =2.87 km2)were taken as the study areas of basin scale and field scale in Zhanghe irrigation district. Applications were extended from ordinary meso-scale watershed to field scale in Zhanghe paddy field-dominated irrigated . Based on actual measurement data of land use, soil classification, hydrology and meteorology, quantitative evaluation and modifications for two coefficients, i.e. preceding loss and runoff curve, were proposed with corresponding models, table of CN values for different landuse and AMC(antecedent moisture condition) grading standard fitting for research cases were proposed. The simulation precision was increased by putting forward a 12h unit hydrograph of the field area, and 12h unit hydrograph were simplified. Comparison between different scales show that it’s more effectively to use SCS-CN model on field scale after parameters calibrated in basin scale These results can help discovering the rainfall-runoff rule in the district. Differences of established SCS-CN model's parameters between the two study regions are also considered. Varied forms of landuse and impacts of human activities were the important factors which can impact the rainfall-runoff relations in Zhanghe irrigation district.
Khan, M.; Abdul-Aziz, O. I.
Potential changes in climatic drivers and land cover features can significantly influence the stormwater budget in the Northwest Florida Basin. We investigated the hydro-climatic and land use sensitivities of stormwater runoff by developing a large-scale process-based rainfall-runoff model for the large basin by using the EPA Storm Water Management Model (SWMM 5.1). Climatic and hydrologic variables, as well as land use/cover features were incorporated into the model to account for the key processes of coastal hydrology and its dynamic interactions with groundwater and sea levels. We calibrated and validated the model by historical daily streamflow observations during 2009-2012 at four major rivers in the basin. Downscaled climatic drivers (precipitation, temperature, solar radiation) projected by twenty GCMs-RCMs under CMIP5, along with the projected future land use/cover features were also incorporated into the model. The basin storm runoff was then simulated for the historical (2000s = 1976-2005) and two future periods (2050s = 2030-2059, and 2080s = 2070-2099). Comparative evaluation of the historical and future scenarios leads to important guidelines for stormwater management in Northwest Florida and similar regions under a changing climate and environment.
Hosseini, Mohammadreza; Nunes, João Pedro; González Pelayo, Oscar; Keizer, Jan Jacob; Ritsema, Coen; Geissen, Violette
Models can be valuable for foreseeing the hydrological effects of fires and to plan and execute post-fire management alternatives. In this study, the revised Morgan-Morgan-Finney (MMF) model was utilized to simulate runoff and soil erosion in recently burned maritime pine plantations with different fire regimes, in a wet Mediterranean area of north-central Portugal. The MMF model was adjusted for burned zones in order to accommodate seasonal patterns in runoff and soil erosion, attributed to changes in soil water repellency and vegetation recovery. The model was then assessed by applying it for a sum of 18 experimental micro-plots (0.25 m2) at 9 1x-burnt and 9 4x-burnt slopes, using both literature-based and calibrated parameters, with the collected data used to assess the robustness of each parameterization. The estimate of erosion was more exact than that of runoff, with a general Nash-Sutcliffe efficiency of 0.54. Slope angle and the soil's effective hydrological depth (which relies on upon vegetation and additionally crop cover) were found to be the primary parameters enhancing model results, and different hydrological depths were expected to separate between the two differentiating fire regimes. This relative analysis demonstrated that most existing benchmark parameters can be utilized to apply MMF in burnt pine regions with moderate severity to support post-fire management; however it also showed that further endeavours ought to concentrate on mapping soil depth and vegetation cover to enhance these simulations.
Kerlin, T.W.; Katz, E.M.; Freels, J.; Thakkar, J.
Moving boundary, nodal models with dynamic energy balances, dynamic mass balances, quasi-static momentum balances, and an equivalent single channel approach have been developed for steam generators used in nuclear power plants. The model for the U-tube recirculation type steam generator is described and comparisons are made of responses from models of different complexity; non-linear versus linear, high-order versus low order, detailed modeling of the control system versus a simple control assumption. The results of dynamic tests on nuclear power systems show that when this steam generator model is included in a system simulation there is good agreement with actual plant performance. (author)
Daily Streamflow Predictions in an Ungauged Watershed in Northern California Using the Precipitation-Runoff Modeling System (PRMS): Calibration Challenges when nearby Gauged Watersheds are Hydrologically Dissimilar
Dhakal, A. S.; Adera, S.
Accurate daily streamflow prediction in ungauged watersheds with sparse information is challenging. The ability of a hydrologic model calibrated using nearby gauged watersheds to predict streamflow accurately depends on hydrologic similarities between the gauged and ungauged watersheds. This study examines daily streamflow predictions using the Precipitation-Runoff Modeling System (PRMS) for the largely ungauged San Antonio Creek watershed, a 96 km2 sub-watershed of the Alameda Creek watershed in Northern California. The process-based PRMS model is being used to improve the accuracy of recent San Antonio Creek streamflow predictions generated by two empirical methods. Although San Antonio Creek watershed is largely ungauged, daily streamflow data exists for hydrologic years (HY) 1913 - 1930. PRMS was calibrated for HY 1913 - 1930 using streamflow data, modern-day land use and PRISM precipitation distribution, and gauged precipitation and temperature data from a nearby watershed. The PRMS model was then used to generate daily streamflows for HY 1996-2013, during which the watershed was ungauged, and hydrologic responses were compared to two nearby gauged sub-watersheds of Alameda Creek. Finally, the PRMS-predicted daily flows between HY 1996-2013 were compared to the two empirically-predicted streamflow time series: (1) the reservoir mass balance method and (2) correlation of historical streamflows from 80 - 100 years ago between San Antonio Creek and a nearby sub-watershed located in Alameda Creek. While the mass balance approach using reservoir storage and transfers is helpful for estimating inflows to the reservoir, large discrepancies in daily streamflow estimation can arise. Similarly, correlation-based predicted daily flows which rely on a relationship from flows collected 80-100 years ago may not represent current watershed hydrologic conditions. This study aims to develop a method of streamflow prediction in the San Antonio Creek watershed by examining PRMS
Voinov, Alexey; Kolagani, Nagesh; McCall, Michael K; Glynn, Pierre D.; Kragt, Marit E; Ostermann, Frank O; Pierce, Suzanne A; Ramu, Palaniappan
This paper updates and builds on ‘Modelling with Stakeholders’ Voinov and Bousquet, 2010 which demonstrated the importance of, and demand for, stakeholder participation in resource and environmental modelling. This position paper returns to the concepts of that publication and reviews the progress made since 2010. A new development is the wide introduction and acceptance of social media and web applications, which dramatically changes the context and scale of stakeholder interactions and participation. Technology advances make it easier to incorporate information in interactive formats via visualization and games to augment participatory experiences. Citizens as stakeholders are increasingly demanding to be engaged in planning decisions that affect them and their communities, at scales from local to global. How people interact with and access models and data is rapidly evolving. In turn, this requires changes in how models are built, packaged, and disseminated: citizens are less in awe of experts and external authorities, and they are increasingly aware of their own capabilities to provide inputs to planning processes, including models. The continued acceleration of environmental degradation and natural resource depletion accompanies these societal changes, even as there is a growing acceptance of the need to transition to alternative, possibly very different, life styles. Substantive transitions cannot occur without significant changes in human behaviour and perceptions. The important and diverse roles that models can play in guiding human behaviour, and in disseminating and increasing societal knowledge, are a feature of stakeholder processes today.
Jean Maikon Santos Oliveira
Full Text Available Fire significantly affects hydrological processes in the waters hed because it changes land cover and it creates a double layer of hydrophobic soil co vered with ash, increasing the surface runoff and the production of debris flow in the basin. Assessing the impacts of fire on overland flow requires the use of modeli ng softwares capable of simulating post-fire discharge. Because a total of 760 wildfire s were detected in the Upper Uberabinha River subbasin in the last nine years, it is o f dire importance to understand the consequential impacts of fire on hydrological pr ocesses in this basin. In this study, the HEC-HMS model was used to evaluate post-fire di scharge in the Upper Uberabinha River watershed. Model was previously calibrated and validated using two representative storms observed in the wet season. After calibra tion, the 5-, 10-, 25-, 50-, 100-, and 200-year storms were simulated in scenarios with incr easing burn severity. The calibrated model performed well in the prediction of discha rge values at a daily basis (0% difference in peak tim ing; 0% difference in peak flow ; 31.8% BIAS . Peak flow and discharge volume increased and peak timing shifted to the left as severity of burn increased. The highest increment in peak discharge was 74. 7% for the 10-year storm, whereas overall discharge volume raised in up to 31.9% f or the 50-year storm, both after simulation in the mos t fire-impacted scenario. The results reveal that fire highly affects hydrological characteristics, e.g. peak timing a nd flow and discharge volume, in the Upper Uberabinha River watershed. The authors su ggest further investigations concerning the impacts of wildfire on other proc esses, such as the production of debris flow in the basin.
Precipitation is one of the primary forcing functions of hydrologic and watershed fate and transport models; however, in light of advances in precipitation estimates across watersheds, data remain highly uncertain. A wide variety of simulated and observed precipitation data are a...
Pilcher, Darren J.; Siedlecki, Samantha A.; Hermann, Albert J.; Coyle, Kenneth O.; Mathis, Jeremy T.; Evans, Wiley
The Gulf of Alaska (GOA) receives substantial summer freshwater runoff from glacial meltwater. The alkalinity of this runoff is highly dependent on the glacial source and can modify the coastal carbon cycle. We use a regional ocean biogeochemical model to simulate CO2 uptake in the GOA under different alkalinity-loading scenarios. The GOA is identified as a current net sink of carbon, though low-alkalinity tidewater glacial runoff suppresses summer coastal carbon uptake. Our model shows that increasing the alkalinity generates an increase in annual CO2 uptake of 1.9-2.7 TgC/yr. This transition is comparable to a projected change in glacial runoff composition (i.e., from tidewater to land-terminating) due to continued climate warming. Our results demonstrate an important local carbon-climate feedback that can significantly increase coastal carbon uptake via enhanced air-sea exchange, with potential implications to the coastal ecosystems in glaciated areas around the world.
Morched, A.S. [BPR Energie, Sherbrooke, PQ (Canada)
Distributed resources can impact the performance of host power systems during both normal and abnormal system conditions. This PowerPoint presentation discussed the use of dynamic models for identifying potential interaction problems between interconnected systems. The models were designed to simulate steady state behaviour as well as transient responses to system disturbances. The distributed generators included directly coupled and electronically coupled generators. The directly coupled generator was driven by wind turbines. Simplified models of grid-side inverters, electronically coupled wind generators and doubly-fed induction generators (DFIGs) were presented. The responses of DFIGs to wind variations were evaluated. Synchronous machine and electronically coupled generator responses were compared. The system model components included load models, generators, protection systems, and system equivalents. Frequency responses to islanding events were reviewed. The study demonstrated that accurate simulations are needed to predict the impact of distributed generation resources on the performance of host systems. Advances in distributed generation technology have outpaced the development of models needed for integration studies. tabs., figs.
Full Text Available This study intended to illustrate the distribution of surface run-off. The methodology was by using Kineros model (kinetic run-off and erosion model. This model is a part of AGWA program which is as the development of ESRI ArcView SIG software that is as a tool for analysing hydrological phenomena in research about watershed simulating the process of infiltration, run-off depth, and erosion in a watershed of small scale such as ≤100 km2. The procedures are as follow: to analyse the run-off depth in Brantas sub-watershed, Klojen District by using Kineros model based on the land use change due to the rainfall simulation with the return period of 2 years, 5 years, 10 years, and 25 years. Results show that the difference of land use affect the surface run-off or there is the correlation between land use and surface run-off depth. The maximum surface run-off depth in the year 2000 was 134.26 mm; in 2005 it was 139.36 mm; and in 2010 it was 142.76 mm. There was no significant difference between Kineros model and observation in field, the relative error was only 9.09%.
Moffa, P.E. (Calocerinos and Spina, Liverpool, NY); Freedman, S.D.; Owens, E.M.; Field, R.; Cibik, C.
The control, treatment and management of urban runoff and sewer overflow are reviewed. Simplified modeling and monitoring techniques are used to characterize urban runoff and to assess control alternatives. (KRM)
Ying, G.; Sansalone, J.
SummaryWith respect to hydrologic processes, the impervious pavement interface significantly alters relationships between rainfall and runoff. Commensurate with alteration of hydrologic processes the pavement also facilitates transport and solubility of dry deposition particulate matter (PM) in runoff. This study examines dry depositional flux rates, granulometric modification by runoff transport, as well as generation of total dissolved solids (TDS), alkalinity and conductivity in source area runoff resulting from PM solubility. PM is collected from a paved source area transportation corridor (I-10) in Baton Rouge, Louisiana encompassing 17 dry deposition and 8 runoff events. The mass-based granulometric particle size distribution (PSD) is measured and modeled through a cumulative gamma function, while PM surface area distributions across the PSD follow a log-normal distribution. Dry deposition flux rates are modeled as separate first-order exponential functions of previous dry hours (PDH) for PM and suspended, settleable and sediment fractions. When trans-located from dry deposition into runoff, PSDs are modified, with a d50m decreasing from 331 to 14 μm after transport and 60 min of settling. Solubility experiments as a function of pH, contact time and particle size using source area rainfall generate constitutive models to reproduce pH, alkalinity, TDS and alkalinity for historical events. Equilibrium pH, alkalinity and TDS are strongly influenced by particle size and contact times. The constitutive leaching models are combined with measured PSDs from a series of rainfall-runoff events to demonstrate that the model results replicate alkalinity and TDS in runoff from the subject watershed. Results illustrate the granulometry of dry deposition PM, modification of PSDs along the drainage pathway, and the role of PM solubility for generation of TDS, alkalinity and conductivity in urban source area rainfall-runoff.
Koster, Randal D.; Mahanama, P. P.
Key to translating soil moisture memory into subseasonal precipitation and air temperature forecast skill is a realistic treatment of evaporation in the forecast system used - in particular, a realistic treatment of how evaporation responds to variations in soil moisture. The inherent soil moisture-evaporation relationships used in today's land surface models (LSMs), however, arguably reflect little more than guesswork given the lack of evaporation and soil moisture data at the spatial scales represented by regional and global models. Here we present a new approach for evaluating this critical aspect of LSMs. Seasonally averaged precipitation is used as a proxy for seasonally-averaged soil moisture, and seasonally-averaged air temperature is used as a proxy for seasonally-averaged evaporation (e.g., more evaporative cooling leads to cooler temperatures) the relationship between historical precipitation and temperature measurements accordingly mimics in certain important ways nature's relationship between soil moisture and evaporation. Additional information on the relationship is gleaned from joint analysis of precipitation and streamflow measurements. An experimental framework that utilizes these ideas to guide the development of an improved soil moisture-evaporation relationship is described and demonstrated.
Full Text Available Ain Sefra is one of the Algerian cities that had been experienced several devastating floods during the past 100 years. The purpose of this study is to simulate runoff in the semi-arid region of Ain Sefra watershed through the employing of the Hydrologic Engineering Center – Hydrologic Modelling System (HEC-HMS. In this paper, the frequency storm is used for the meteorological model, the Soil Conservation Service – curve number (SCS-CN is selected to calculate the loss rate and Soil Conservation Service unit hydrograph method have been applied to simulate the runoff rate. After calibration and validation, the simulated peak discharges were very close with observed values. The Nash–Sutcliffe efficiency coefficient was 0.95, indicates that the hydrological modeling results are satisfactory and accepted for simulation of rainfall-runoff. The peak discharges obtained for the 10, 50, 100 and 1000 year storms are respectively 425.8, 750.5, 904.3 and 1328.3 m3∙s−1.
Full Text Available The application of hydrological and water quality models is an efficient approach to better understand the processes of environmental deterioration. This study evaluated the ability of the Annualized Agricultural Non-Point Source (AnnAGNPS model to predict runoff, total nitrogen (TN and total phosphorus (TP loading in a typical small watershed of a hilly region near Taihu Lake, China. Runoff was calibrated and validated at both an annual and monthly scale, and parameter sensitivity analysis was performed for TN and TP before the two water quality components were calibrated. The results showed that the model satisfactorily simulated runoff at annual and monthly scales, both during calibration and validation processes. Additionally, results of parameter sensitivity analysis showed that the parameters Fertilizer rate, Fertilizer organic, Canopy cover and Fertilizer inorganic were more sensitive to TN output. In terms of TP, the parameters Residue mass ratio, Fertilizer rate, Fertilizer inorganic and Canopy cover were the most sensitive. Based on these sensitive parameters, calibration was performed. TN loading produced satisfactory results for both the calibration and validation processes, whereas the performance of TP loading was slightly poor. The simulation results showed that AnnAGNPS has the potential to be used as a valuable tool for the planning and management of watersheds.
Full Text Available Water balance models provide significant input to integrated models that are used to simulate river basin processes. However, one of the primary problems involves the coupling and simultaneous calibration of rainfall-runoff and groundwater models. This problem manifests itself through circular arguments - the hydrologic model is modified to calculate highly discretized groundwater recharge rates as input to the groundwater model which provides modeled base flow for the flood-routing module of the rainfall-runoff model. A possibility to overcome this problem using a modified version of the HBV Model is presented in this paper. Regionalisation and optimization methods lead to objective and efficient calibration despite large numbers of parameters. The representation of model parameters by transfer functions of catchment characteristics enables consistent parameter estimation. By establishing such relationships, models are calibrated for the parameters of the transfer functions instead of the model parameters themselves. Simulated annealing, using weighted Nash-Sutcliffe-coefficients of variable temporal aggregation, assists in efficient parameterisations. The simulations are compared to observed discharge and groundwater recharge modeled by the State Institute for Environmental Protection Baden-Württemberg using the model TRAIN-GWN.
Kavka, Petr; Krasa, Josef; Bek, Stanislav
The article shows results of topographic factor (the LS factor in USLE) derivation enhancement focused on detailed Airborne Laser Scanning (ALS) based DEMs. It describes a flow paths generation technique using triangulated irregular network (TIN) for terrain morphology description, which is not yet established in soil loss computations. This technique was compared with other procedures of flow direction and flow paths generation based on commonly used raster model (DEM). These overland flow characteristics together with therefrom derived flow accumulation are significant inputs for many scientific models. Particularly they are used in all USLE-based soil erosion models, from which USLE2D, RUSLE3D, Watem/Sedem or USPED can be named as the most acknowledged. Flow routing characteristics are also essential parameters in physically based hydrological and soil erosion models like HEC-HMS, Wepp, Erosion3D, LISEM, SMODERP, etc. Mentioned models are based on regular raster grids, where the identification of runoff direction is problematic. The most common method is Steepest descent (one directional flow), which corresponds well with the concentration of surface runoff into concentrated flow. The Steepest descent algorithm for the flow routing doesn't provide satisfying results, it often creates parallel and narrow flow lines while not respecting real morphological conditions. To overcome this problem, other methods (such as Flux Decomposition, Multiple flow, Deterministic Infinity algorithm etc.) separate the outflow into several components. This approach leads to unrealistic diffusion propagation of the runoff and makes it impossible to be used for simulation of dominant morphological features, such as artificial rills, hedges, sediment traps etc. The modern methods of mapping ground elevations, especially ALS, provide very detailed models even for large river basins, including morphological details. New algorithms for derivation a runoff direction have been developed as
Mernild, Sebastian H.; Liston, Glen E.; Hiemstra, Christopher A.
A regional atmospheric model, the HIRHAM4 regional climate model (RCM) using boundary conditions from the ECHAM5 atmosphere-ocean general circulation model (AOGCM), was downscaled to a 500-m gridcell increment using SnowModel to simulate 131 yr (1950-2080) of hydrologic cycle evolution in west...... Greenland's Kangerlussuaq drainage. Projected changes in the Greenland Ice Sheet (GrIS) surface mass balance (SMB) and runoff are relevant for potential hydropower production and prediction of ecosystem changes in sensitive Kangerlussuaq Fjord systems. Mean annual surface air temperatures and precipitation...
Quinn, D.; Brooks, E. S.; Robichaud, P. R.; Dobre, M.; Brown, R. E.; Wagenbrenner, J.
The cascading consequences of fire-induced ecological changes have profound impacts on both natural and managed forest ecosystems. Forest managers tasked with implementing post-fire mitigation strategies need robust tools to evaluate the effectiveness of their decisions, particularly those affecting hydrological recovery. Various hillslope-scale interfaces of the physically-based Water Erosion Prediction Project (WEPP) model have been successfully validated for this purpose using fire-effected plot experiments, however these interfaces are explicitly designed to simulate single hillslopes. Spatially-distributed, catchment-scale WEPP interfaces have been developed over the past decade, however none have been validated for post-fire simulations, posing a barrier to adoption for forest managers. In this validation study, we compare WEPP simulations with pre- and post-fire hydrological records for three forested catchments (W. Willow, N. Thomas, and S. Thomas) that burned in the 2011 Wallow Fire in Northeastern Arizona, USA. Simulations were conducted using two approaches; the first using automatically created inputs from an online, spatial, post-fire WEPP interface, and the second using manually created inputs which incorporate the spatial variability of fire effects observed in the field. Both approaches were compared to five years of observed post-fire sediment and flow data to assess goodness of fit.
Elçi, A; Karadaş, D; Fistikoğlu, O
A numerical modeling case study of groundwater flow in a diffuse pollution prone area is presented. The study area is located within the metropolitan borders of the city of Izmir, Turkey. This groundwater flow model was unconventional in the application since the groundwater recharge parameter in the model was estimated using a lumped, transient water-budget based precipitation-runoff model that was executed independent of the groundwater flow model. The recharge rate obtained from the calibrated precipitation-runoff model was used as input to the groundwater flow model, which was eventually calibrated to measured water table elevations. Overall, the flow model results were consistent with field observations and model statistics were satisfactory. Water budget results of the model revealed that groundwater recharge comprised about 20% of the total water input for the entire study area. Recharge was the second largest component in the budget after leakage from streams into the subsurface. It was concluded that the modeling results can be further used as input for contaminant transport modeling studies in order to evaluate the vulnerability of water resources of the study area to diffuse pollution.
de Hamer, W.; Love, D.; Booij, Martijn J.; Hoekstra, Arjen Ysbert
In semi‐arid regions, small artificial surface reservoirs are important to meet the domestic and agricultural water requirements of smallholder farmers. The research objective of the study was to determine the rainfall‐runoff relation of two ungauged rivers using the measured water levels of the
Capra, Lucia; Coviello, Velio; Borselli, Lorenzo; Márquez-Ramírez, Víctor-Hugo; Arámbula-Mendoza, Raul
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
Ovtcharova, I. [Energoproekt, Sofia (Bulgaria)
In the presentation some of the calculated results of horizontal steam generator PGV - 440 modelling with RELAP5/Mod3 are described. Two nodalization schemes have been used with different components in the steam dome. A study of parameters variation on the steam generator work and calculated results is made in cases with separator and branch.
Generative models of music are in need of performance and gesture additions, i.e. inclusions of subtle temporal and dynamic alterations, and gestures so as to render the music musical. While much of the research regarding music generation is based on music theory, the work presented here is based...
Ovtcharova, I [Energoproekt, Sofia (Bulgaria)
In the presentation some of the calculated results of horizontal steam generator PGV - 440 modelling with RELAP5/Mod3 are described. Two nodalization schemes have been used with different components in the steam dome. A study of parameters variation on the steam generator work and calculated results is made in cases with separator and branch.
National Aeronautics and Space Administration — M4 Engineering proposes to develop a generalized reduced order model generation method. This method will allow for creation of reduced order aeroservoelastic state...
Chardon, J.; Mathevet, T.; Le Lay, M.; Gailhard, J.
dynamic and processes, i. e. sample heterogeneity. For a same streamflow range corresponds different processes such as rising limbs or recession, where uncertainties are different. The dynamical approach improves reliability, skills and sharpness of forecasts and globally reduces confidence intervals width. When compared in details, the dynamical approach allows a noticeable reduction of confidence intervals during recessions where uncertainty is relatively lower and a slight increase of confidence intervals during rising limbs or snowmelt where uncertainty is greater. The dynamic approach, validated by forecaster's experience that considered the empirical approach not discriminative enough, improved forecaster's confidence and communication of uncertainties. Montanari, A. and Brath, A., (2004). A stochastic approach for assessing the uncertainty of rainfall-runoff simulations. Water Resources Research, 40, W01106, doi:10.1029/2003WR002540. Schaefli, B., Balin Talamba, D. and Musy, A., (2007). Quantifying hydrological modeling errors through a mixture of normal distributions. Journal of Hydrology, 332, 303-315.
HEP event generators aim to describe high-energy collisions in full exclusive detail. They combine perturbative matrix elements and parton showers with dynamical models of less well-understood phenomena such as hadronization, diffraction, and the so-called underlying event. We briefly summarise some of the main concepts relevant to the modelling of soft/inclusive hadron interactions in MC generators, in particular PYTHIA, with emphasis on questions recently highlighted by LHC data.
Pineux, N.; Degré, A.
Between 1998 and 2004, Europe suffered from more than hundred major inundations, responsible for some 700 deaths, for the moving of about half a million of people and the economic losses of at least 25 billions Euros covered by the insurance policies. Within this context, EU launched the 2007/60/CE directive. The inundations are natural phenomenon. They cannot be avoided. Nevertheless this directive permits to better evaluate the risks and to coordinate the management measures taken at member states level. In most countries, inundation maps only include rivers' overflowing. In Wallonia, overland flows and mudflows also cause huge damages, and must be included in the flood hazard map. Indeed, the cleaning operations for a village can lead to an estimated cost of 11 000 €. Average construction cost of retention dams to control off-site damage caused by floods and muddy flows was valued at 380 000€, and yearly dredging costs associated with these retention ponds at 15 000€. For a small city for which a study was done in a more specific way (Gembloux), the mean annual cost for the damages that can generate the runoff is about 20 000€. This cost consists of the physical damages caused to the real estate and movable properties of the residents as well as the emergency operations of the firemen and the city. On top of damages to public infrastructure (clogging of trenches, silting up of retention ponds) and to private property by muddy flows, runoff generates a significant loss of arable land. Yet, the soil resource is not an unlimited commodity. Moreover, sediments' transfer to watercourses alters their physical and chemical quality. And that is not to mention the increased psychological stress for people. But to map overland flood and mud flow hazard is a real challenge. This poster will present the methodology used to in Wallonia. The methodology is based on 3 project rainfalls: 25, 50 and 100 years return period (consistency with the cartography of the
Jacquin, A. P.
This study is intended to quantify the impact of uncertainty about precipitation spatial distribution on predictive uncertainty of a snowmelt runoff model. This problem is especially relevant in mountain catchments with a sparse precipitation observation network and relative short precipitation records. The model analysed is a conceptual watershed model operating at a monthly time step. The model divides the catchment into five elevation zones, where the fifth zone corresponds to the catchment's glaciers. Precipitation amounts at each elevation zone i are estimated as the product between observed precipitation at a station and a precipitation factor FPi. If other precipitation data are not available, these precipitation factors must be adjusted during the calibration process and are thus seen as parameters of the model. In the case of the fifth zone, glaciers are seen as an inexhaustible source of water that melts when the snow cover is depleted.The catchment case study is Aconcagua River at Chacabuquito, located in the Andean region of Central Chile. The model's predictive uncertainty is measured in terms of the output variance of the mean squared error of the Box-Cox transformed discharge, the relative volumetric error, and the weighted average of snow water equivalent in the elevation zones at the end of the simulation period. Sobol's variance decomposition (SVD) method is used for assessing the impact of precipitation spatial distribution, represented by the precipitation factors FPi, on the models' predictive uncertainty. In the SVD method, the first order effect of a parameter (or group of parameters) indicates the fraction of predictive uncertainty that could be reduced if the true value of this parameter (or group) was known. Similarly, the total effect of a parameter (or group) measures the fraction of predictive uncertainty that would remain if the true value of this parameter (or group) was unknown, but all the remaining model parameters could be fixed
Advances in deep generative models are at the forefront of deep learning research because of the promise they offer for allowing data-efficient learning, and for model-based reinforcement learning. In this talk I'll review a few standard methods for approximate inference and introduce modern approximations which allow for efficient large-scale training of a wide variety of generative models. Finally, I'll demonstrate several important application of these models to density estimation, missing data imputation, data compression and planning.
... water) on the rivers of the Crimean Mountains were used materials of observations for long-term period (from the beginning of observations to 2010 inclusive) on 54 of streamflow station with using a the so-called «operator» model for maximum runoff formation. Keywords: maximum runoff; rain floods; hillslope runoff; karst ...
Braga, Ana Cláudia F. Medeiros; Silva, Richarde Marques da; Santos, Celso Augusto Guimarães; Galvão, Carlos de Oliveira; Nobre, Paulo
The coastal zone of northeastern Brazil is characterized by intense human activities and by large settlements and also experiences high soil losses that can contribute to environmental damage. Therefore, it is necessary to build an integrated modeling-forecasting system for rainfall-runoff erosion that assesses plans for water availability and sediment yield that can be conceived and implemented. In this work, we present an evaluation of an integrated modeling system for a basin located in this region with a relatively low predictability of seasonal rainfall and a small area (600 km2). The National Center for Environmental Predictions - NCEP’s Regional Spectral Model (RSM) nested within the Center for Weather Forecasting and Climate Studies - CPTEC’s Atmospheric General Circulation Model (AGCM) were investigated in this study, and both are addressed in the simulation work. The rainfall analysis shows that: (1) the dynamic downscaling carried out by the regional RSM model approximates the frequency distribution of the daily observed data set although errors were detected in the magnitude and timing (anticipation of peaks, for example) at the daily scale, (2) an unbiased precipitation forecast seemed to be essential for use of the results in hydrological models, and (3) the information directly extracted from the global model may also be useful. The simulated runoff and reservoir-stored volumes are strongly linked to rainfall, and their estimation accuracy was significantly improved at the monthly scale, thus rendering the results useful for management purposes. The runoff-erosion forecasting displayed a large sediment yield that was consistent with the predicted rainfall.
This paper analyzes the properties of runoff electoral systems when voters are strategic. A model of three-candidate runoff elections is presented, and two new features are included: the risk of upset victory in the second round is endogenous, and many types of runoff systems are considered. Three main results emerge. First, runoff elections produce equilibria in which only two candidates receive a positive fraction of the votes. Second, a sincere voting equilibrium does not always exist. Fin...
W. L. Quinton
Full Text Available In northern alpine tundra, large slope gradients, late-lying snow drifts and shallow soils overlying impermeable substrates all contribute to large hillslope runoff volumes during the spring freshet. Understanding the processes and pathways of hillslope runoff in this environment is, therefore, critical to understanding the water cycle within northern alpine tundra ecosystems. This study: (a presents the results of a field study on runoff from a sub-alpine tundra hillslope with a large snow drift during the spring melt period; (b identifies the major runoff processes that must be represented in simulations of snowmelt runoff from sub-alpine tundra hillslopes; (c describes how these processes can be represented in a numerical simulation model; and d compares field measurements with modelled output to validate or refute the conceptual understanding of runoff generation embodied in the process simulations. The study was conducted at Granger Creek catchment, 15 km south of Whitehorse, Yukon Territory, Canada, on a north-facing slope below a late-lying snow drift. For the freshet period, the major processes to be represented in a runoff model include the rate of meltwater release from the late-lying snowdrift, the elevation and thickness of the saturated layer, the magnitude of the soil permeability and its variation with depth. The daily cycle of net all-wave radiation was observed to drive the diurnal pulses of melt water from the drift; this, in turn, was found to control the daily pulses of flow through the hillslope subsurface and in the stream channel. The computed rate of frost table lowering fell within the observed values; however, there was wide variation among the measured frost table depths. Spatial variability in frost table depth would result in spatial variabilities in saturated layer depth and thickness, which would, in turn, produce variations in subsurface flow rates over the slope, including preferential flowpaths. Keywords
Derdour Abdessamed; Bouanani Abderrazak; Babahamed Kamila
Ain Sefra is one of the Algerian cities that had been experienced several devastating floods during the past 100 years. The purpose of this study is to simulate runoff in the semi-arid region of Ain Sefra watershed through the employing of the Hydrologic Engineering Center – Hydrologic Modelling System (HEC-HMS). In this paper, the frequency storm is used for the meteorological model, the Soil Conservation Service – curve number (SCS-CN) is selected to calculate the loss rate and Soil Conserv...
Sampson, Victor; Grooms, Jonathon
The Generate an Argument instructional model was designed to engage students in scientific argumentation. By using this model, students develop complex reasoning and critical-thinking skills, understand the nature and development of scientific knowledge, and improve their communication skills (Duschl and Osborne 2002). This article describes the…
Herbert, Luke Thomas; Sharp, Robin
We present a framework for the automated generation of fault trees from models of realworld process workflows, expressed in a formalised subset of the popular Business Process Modelling and Notation (BPMN) language. To capture uncertainty and unreliability in workflows, we extend this formalism...
Koutny, M.; Timmer, Mark; Ulidowski, I.; Katoen, Joost P.; van de Pol, Jan Cornelis; Stoelinga, Mariëlle Ida Antoinette
This paper introduces a framework for the efficient modelling and generation of Markov automata. It consists of (1) the data-rich process-algebraic language MAPA, allowing concise modelling of systems with nondeterminism, probability and Markovian timing; (2) a restricted form of the language, the
In a repository containing low- and intermediate-level waste, gas generation will occur principally by the coupled processes of metal corrosion and microbial degradation of cellulosic waste. This Paper describes a mathematical model design to address gas generation by these mechanisms. The metal corrosion model incorporates a three-stage process encompassing both aerobic and anaerobic corrosion regimes; the microbial degradation model simulates the activities of eight different microbial populations, which are maintained as functions both of pH and of the concentrations of particular chemical species. Gas concentrations have been measured over a period of three years in large-scale drum experiments designed to simulate repository conditions. Model predictions are confirmed against the experimental measurements, and a prediction is then made of gas concentrations and generation rates over an assessment period of one million years in a radioactive waste repository. (author)
In a repository containing low- and intermediate-level waste, gas generation will occur principally by the coupled processes of metal corrosion and microbial degradation of cellulosic waste. This paper describes a mathematical model designed to address gas generation by these mechanisms. The metal corrosion model incorporates a three-stage process encompassing both aerobic and anaerobic corrosion regimes; the microbial degradation model simulates the activities of eight different microbial populations, which are maintained as functions both of pH and of the concentrations of particular chemical species. Gas concentrations have been measured over a period of three years in large-scale drum experiments designed to simulate repository conditions. Model predictions are confirmed against the experimental measurements, and a prediction is then made of gas concentrations and generation rates over an assessment period of one million years in a radioactive waste repository. (Author)
Full Text Available In this study we propose a multi-source data approach for quantifying long-term flooding and aquifer recharge in ungauged ephemeral rivers. The methodology is applied to the Buffels River, at 9000 km2 the largest ephemeral river in Namaqualand (NW South Africa, a region with scarce stream flow records limiting research investigating hydrological response to global change. Daily discharge and annual flood series (1965–2006 were estimated from a distributed rainfall-runoff hydrological model (TETIS using rainfall gauge records located within the catchment. The model was calibrated and validated with data collected during a two year monitoring programme (2005–2006 at two stream flow stations, one each in the upper and lower reaches of the catchment. In addition to the modelled flow records, non-systematic flood data were reconstructed using both sedimentary and documentary evidence. The palaeoflood record identified at least 25 large floods during the last 700 yr; with the largest floods reaching a minimum discharge of 255 m3 s−1 (450 yr return period in the upper basin, and 510 m3 s−1 (100 yr return period in the lower catchment. Since AD 1925, the flood hydrology of the Buffels River has been characterised by a decrease in the magnitude and frequency of extreme floods, with palaeoflood discharges (period 1500–1921 five times greater than the largest modelled floods during the period 1965–2006. Large floods generated the highest hydrograph volumes, however their contribution to aquifer recharge is limited as this depends on other factors such as flood duration and storage capacity of the unsaturated zone prior to the flood. Floods having average return intervals of 5–10 yr (120–140 m3 s−1 and flowing for 12 days are able to fully saturate the Spektakel aquifer in the lower Buffels River basin. Alluvial aquifer storage capacity limiting potential recharge
Friese, Ryan D.; Tallent, Nathan R.; Vishnu, Abhinav; Kerbyson, Darren J.; Hoisie, Adolfy
Many applications have irregular behavior --- non-uniform input data, input-dependent solvers, irregular memory accesses, unbiased branches --- that cannot be captured using today's automated performance modeling techniques. We describe new hierarchical critical path analyses for the \\Palm model generation tool. To create a model's structure, we capture tasks along representative MPI critical paths. We create a histogram of critical tasks with parameterized task arguments and instance counts. To model each task, we identify hot instruction-level sub-paths and model each sub-path based on data flow, instruction scheduling, and data locality. We describe application models that generate accurate predictions for strong scaling when varying CPU speed, cache speed, memory speed, and architecture. We present results for the Sweep3D neutron transport benchmark; Page Rank on multiple graphs; Support Vector Machine with pruning; and PFLOTRAN's reactive flow/transport solver with domain-induced load imbalance.
Nguyen, D.H.; Neises, G.J.; Howard, M.L.
This paper presents a CONTEMPT-LT/28 containment model that has been developed by Wolf Creek Nuclear Operating Corporation (WCNOC) to predict containment pressure and temperature behavior during the postulated events at Wolf Creek Generating Station (WCGS). The model has been validated using data provided in the WCGS Updated Safety Analysis Report (USAR). CONTEMPT-LT/28 model has been used extensively at WCGS to support plant operations, and recently, to support its 4.5% thermal power uprate project
Bracken (Nee Bull), L. J.; Kirkby, M. J.
Runoff from semi-arid hillslopes in SE Spain is generated very selectively at all scales. Site response at the 1 m2 scale may be described by the dynamics of local infiltration and crusting, defining Hydrologically Similar Surfaces (HYSS), which are strongly associated with soil type and vegetation cover. This study reports the use of several reconnaissance methods to define HYSS consistently. These methods are (1) the use of small sediment traps which disturb the surface minimally,(2) the use of painted lines and (3) the identification of Morphological Zones associated with different levels of runoff and sediment transport. Five monitoring sites were established on hillslope concavities in two semi-arid catchments in South East Spain. Rainfall data were also collected from the nearest gauge established during previous research. Results show that a storm event in the Rambla de Nogalte on the 30th of June of 83.0 mm was responsible for a maximum runoff depth of 12 cm and a maximum hillslope sediment transport of 1886 cm3 m-1. The same storm in the Rambla de Torrealvilla produced 53.4 mm of rainfall on the 1st of July 2002, had a maximum runoff depth of 26 cm and was responsible for a maximum hillslope sediment transport of 2311 cm3 m-1. In general sediment transport rate and sediment travel distance increased with the distance downslope into the hillslope hollow, and these were related to the maximum depth of flow produced over the hillside. Very little sediment movement occurred directly downslope of bushes as was expected. No significant relationships were established between sediment transport and slope angle or vegetation cover. However, sediment transport and depth of runoff varied with lithology, with marl sites producing the most runoff and sediment transport. The site located on red schist was particularly unresponsive to rainfall and did not experience much sediment transport. Initial models for the response of larger areas suggest that runoff is controlled
Klotz, Daniel; Herrnegger, Mathew; Schulz, Karsten
(Whitley et al., 1994), which might be understood as the idea that acquired characteristics during the lifetime of an individual can be transferred between generations. A hierarchical objective function is used for the model evaluation. This enables model preemption (Tolson et al., 2010) and reduces the amount of model evaluations in the early stages of optimization. References: • Samaniego, L., Kumar, R., Attinger, S. (2010): Multiscale parameter regionalization of a grid-based hydrologic model at the mesoscale, Water Resour. Res., doi: 10.1029/2008WR007327 • Kling, H., Stanzel, P., Fuchs, M., and Nachtnebel, H. P. (2014): Performance of the COSERO precipitation-runoff model under non-stationary conditions in basins with different climates, Hydrolog. Sci. J., doi:10.1080/02626667.2014.959956. • C. Ryan, J.J. Collins, Ji, Collins, M. O'Neil (1998): Evolving Programs for an Arbitrary Language, Lecture Notes in Computer Science 1391, Proceedings of the First European Workshop on Genetic Programming. • B.A. Tolson, S. Razavi, L.S. Matott, N.R. Thomson, A. MacLean, F.R. Seglenieks (2010): Reducing the computational cost of automatic calibration through model preemption, Water Resour. Res., 46, W11523, doi:10.1029/2009WR008957. • D. Whitley, S. Gordon, K. Mathias (1994): Lamarckian evolution, the Baldwin effect, and function optimization, in Parallel Problem Solving from Nature (PPSN) III, Y. Davidor, H.-P. Schwefel, and R. Manner, Eds. Berlin: Springer-Verlag, pp. 6-15.
Russo, A.J.; Campbell, R.B.
One of the possible consequences of disruptions in tokamaks is the generation of runaway electrons which can impact plasma facing components and cause damage, owing to high local energy deposition. This problem becomes more serious as the machine size and plasma current increase. Since large size and high currents are characteristics of proposed future machines, control of runaway generation is an important design consideration. A lumped circuit model for disruption runaway electron generation indicates that impurity concentration and type, as well as plasma motion, can strongly influence runaway behaviour. A comparison of disruption data from several runs on JET and DIII-D with model results demonstrate the effects of impurities, and plasma motion, on runaway number density and energy. The model is also applied to the calculation of runaway currents for ITER. (author). 16 refs, 13 figs
Full Text Available Many factors such as freeze-thaw (FT cycle influence soil behavior. Application of soil amendments can play an important role on runoff time commencement (RT, volume (RV and soil loss (SL on soils subjected to FT cycles. However, limited studies have been documented on this subject. The present study was therefore carried out under rainfall simulation circumstances to investigate the effect of different rates of zeolite application to control the effects of FT on basic hydrological variables such as runoff production and soil loss. Towards this attempt, the effect of application of different rates of 250, 500 and 750 g m−2 of zeolite applied before, during and after the occurrence of FT cycle on RT, RV and SL was assessed in a completely randomized design. Treatments were set up in two categories viz. control (without zeolite application, and three rates and times of zeolite application in small 0.25 m2-experimental plots in three replications. The results showed that application of zeolite had significant effects on hydrological behavior of soil induced by FT cycles. Application rate of 750 g m−2 prior to FT cycle increased RT and reduced RV and SL at rates of 644%, 68% and 91%, respectively. The results also verified that zeolite could successfully mitigate the impacts of FT cycle on the main soil hydrological variables of soil profile induced by FT cycle. It is accordingly recommended to employ zeolite as an effective amendment to control soil erosion in steep and degraded rangelands where surface soil is exposed to rainfall and runoff.
Lupankwa, Keretia; Love, David; Mapani, Benjamin; Mseka, Stephen; Meck, Maideyi
The impacts of mining on the environment depend on the nature of the ore body, the type of mining and the size of operation. The focus of this study is on Trojan Nickel Mine which is located 90 km north of Harare, Zimbabwe. It produces nickel from iron, iron-nickel and copper-nickel sulphides and disposes of waste rock in a rock dump. Surface water samples were taken at 11 points selected from a stream which drains the rock dump, a stream carrying underground water and the river into which these streams discharge. Samples were analysed for metals using atomic absorption spectrometry, for sulphates by gravitation and for carbonates and bicarbonates by back titration. Ninteen rock samples were collected from the dump and static tests were performed using the Sobek acid base accounting method. The results show that near neutral runoff (pH 7.0-8.5) with high concentrations of sulphate (over 100 mg/L) and some metals (Pb > 1.0 mg/L and Ni > 0.2 mg/L) emanates from the dump. This suggests that acid mine drainage is buffered in the dump (probably by carbonates). This is supported by the static tests, which show that the fine fraction of dump material neutralises acid. Runoff from the dump flows into a pond. Concentrations of sulphates and metals decrease after the dump runoff enters the pond, but sufficient remains to increase levels of calcium, sulphate, bicarbonate, iron and lead in the Pote River. The drop in concentrations at the pond indicates that the settling process has a positive effect on water quality. This could be enhanced by treating the pond water to raise pH, thus precipitating out metals and decreasing their concentrations in water draining from the pond.
Full Text Available Syntax-directed translation tools require the specification of a language by means of a formal grammar. This grammar must conform to the specific requirements of the parser generator to be used. This grammar is then annotated with semantic actions for the resulting system to perform its desired function. In this paper, we introduce ModelCC, a model-based parser generator that decouples language specification from language processing, avoiding some of the problems caused by grammar-driven parser generators. ModelCC receives a conceptual model as input, along with constraints that annotate it. It is then able to create a parser for the desired textual syntax and the generated parser fully automates the instantiation of the language conceptual model. ModelCC also includes a reference resolution mechanism so that ModelCC is able to instantiate abstract syntax graphs, rather than mere abstract syntax trees.
Aljoumani, Basem; Kluge, Björn; sanchez, Josep; Wessolek, Gerd
Highways and main roads are potential sources of contamination for the surrounding environment. High traffic rates result in elevated heavy metal concentrations in road runoff, soil and water seepage, which has attracted much attention in the recent past. Prediction of heavy metals transfer near the roadside into deeper soil layers are very important to prevent the groundwater pollution. This study was carried out on data of a number of lysimeters which were installed along the A115 highway (Germany) with a mean daily traffic of 90.000 vehicles per day. Three polyethylene (PE) lysimeters were installed at the A115 highway. They have the following dimensions: length 150 cm, width 100 cm, height 60 cm. The lysimeters were filled with different soil materials, which were recently used for embankment construction in Germany. With the obtained data, we will develop a time series analysis model to predict total and dissolved metal concentration in road runoff and in soil solution of the roadside embankments. The time series consisted of monthly measurements of heavy metals and was transformed to a stationary situation. Subsequently, the transformed data will be used to conduct analyses in the time domain in order to obtain the parameters of a seasonal autoregressive integrated moving average (ARIMA) model. Four phase approaches for identifying and fitting ARIMA models will be used: identification, parameter estimation, diagnostic checking, and forecasting. An automatic selection criterion, such as the Akaike information criterion, will use to enhance this flexible approach to model building
Betzel, Richard F; Avena-Koenigsberger, Andrea; Goñi, Joaquín; He, Ye; de Reus, Marcel A; Griffa, Alessandra; Vértes, Petra E; Mišic, Bratislav; Thiran, Jean-Philippe; Hagmann, Patric; van den Heuvel, Martijn; Zuo, Xi-Nian; Bullmore, Edward T; Sporns, Olaf
The human connectome represents a network map of the brain's wiring diagram and the pattern into which its connections are organized is thought to play an important role in cognitive function. The generative rules that shape the topology of the human connectome remain incompletely understood. Earlier work in model organisms has suggested that wiring rules based on geometric relationships (distance) can account for many but likely not all topological features. Here we systematically explore a family of generative models of the human connectome that yield synthetic networks designed according to different wiring rules combining geometric and a broad range of topological factors. We find that a combination of geometric constraints with a homophilic attachment mechanism can create synthetic networks that closely match many topological characteristics of individual human connectomes, including features that were not included in the optimization of the generative model itself. We use these models to investigate a lifespan dataset and show that, with age, the model parameters undergo progressive changes, suggesting a rebalancing of the generative factors underlying the connectome across the lifespan. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.
Ylijoki, J. [VTT Energy, Espoo (Finland); Palsinajaervi, C.; Porkholm, K. [IVO International Ltd, Vantaa (Finland)
In this paper the capability of the five- and six-equation models of the simulation code APROS to simulate the behaviour of the horizontal steam generator is discussed. Different nodalizations are used in the modelling and the results of the stationary state runs are compared. Exactly the same nodalizations have been created for the five- and six-equation models. The main simulation results studied in this paper are void fraction and mass flow distributions in the secondary side of the steam generator. It was found that quite a large number of simulation volumes is required to simulate the distributions with a reasonable accuracy. The simulation results of the different models are presented and their validity is discussed. (orig.). 4 refs.
Ylijoki, J [VTT Energy, Espoo (Finland); Palsinajaervi, C; Porkholm, K [IVO International Ltd, Vantaa (Finland)
In this paper the capability of the five- and six-equation models of the simulation code APROS to simulate the behaviour of the horizontal steam generator is discussed. Different nodalizations are used in the modelling and the results of the stationary state runs are compared. Exactly the same nodalizations have been created for the five- and six-equation models. The main simulation results studied in this paper are void fraction and mass flow distributions in the secondary side of the steam generator. It was found that quite a large number of simulation volumes is required to simulate the distributions with a reasonable accuracy. The simulation results of the different models are presented and their validity is discussed. (orig.). 4 refs.
Robinson, A.C.; Farnsworth, A.V.; Montgomery, S.T.; Peery, J.S.; Merewether, K.O.
Sandia National Laboratories has prime responsibility for neutron generator design and manufacturing, and is committed to developing predictive tools for modeling neutron generator performance. An important aspect of understanding component performance is explosively driven ferroelectric power supply modeling. EMMA (ElectroMechanical Modeling in ALEGRA) is a three dimensional compile time version of Sandia's ALEGRA code. The code is built on top of the general ALEGRA framework for parallel shock-physics computations but also includes additional capability for modeling the electric potential field in dielectrics. The overall package includes shock propagation due to explosive detonation, depoling of ferroelectric ceramics, electric field calculation and coupling with a general lumped element circuit equation system. The AZTEC parallel iterative solver is used to solve for the electric potential. The DASPK differential algebraic equation package is used to solve the circuit equation system. Sample calculations are described
Full Text Available Predicting surface runoff from catchment to large region is a fundamental and challenging task in hydrology. This paper presents a comprehensive review for various studies conducted for improving runoff predictions from catchment to large region in the last several decades. This review summarizes the well-established methods and discusses some promising approaches from the following four research fields: (1 modeling catchment, regional and global runoff using lumped conceptual rainfall-runoff models, distributed hydrological models, and land surface models, (2 parameterizing hydrological models in ungauged catchments, (3 improving hydrological model structure, and (4 using new remote sensing precipitation data.
Teo, E. K.; Beganskas, S.; Young, K. S.; Weir, W. B.; Harmon, R. E.; Lozano, S.; Fisher, A. T.
Many aquifer systems in central coastal California face a triple threat of excess demand, changing land use, and a shifting climate. These last two factors can contribute to reductions in groundwater recharge. Managed aquifer recharge using distributed stormwater collection (DSC-MAR) is an adaptation technique for collecting excess stormwater runoff from hillslopes for infiltration into underlying aquifers, before that water reaches a "blue line" stream. We are developing a decision support system (DSS) that combines surface and subsurface hydrogeological data with high-resolution predictions of hillslope runoff, with specific application to Santa Cruz and northern Monterey Counties. Other studies presented at AGU will focus on the northern and southern parts of our study region (San Lorenzo River Basin, Lower Pajaro River Basin). This presentation focuses on mid-Santa Cruz County, including the Soquel-Aptos Groundwater Basin. The DSS uses a geographic information system to compile and merge data from numerous local, state, and federal sources to identify locations on the landscape where DSC-MAR may be most suitable. This requires classification of disparate data types so that they can be combined. Stormwater runoff for individual river basins in the study region was simulated using historical streamflow data for calibration and validation. Both analyses were completed with relatively fine resolution, from 10 m2 pixels for elevation to 0.1-1.0 km hydrologic response units for properties such as soil and vegetation properties. Future climate is uncertain, so we used historical data to create a catalog of dry, normal, and wet hydrologic conditions, then created synthetic future climate scenarios for simulation. The DDS shows that there are numerous regions in mid-Santa Cruz County where there is a confluence of MAR suitability and the generation of stormwater runoff that could supply recharge projects (with a nominal target of 100 ac-ft/yr of infiltration), even
The problem of generating a large hierarchy in compactified supersymmetric models is re-examined. It is shown how, even for the class of models for which Str M 2 is non-vanishing, a combination of non-perturbative effects and radiative corrections may lead to an exponentially large hierarchy. A corollary is that the couplings of the effective field theory in the visible sector should be small, i.e., perturbation theory should be applicable. (orig.)
Milligan, M.R.; Pang, C.K.
This paper examines the methods of incorporating wind generation in two production costing models: one is a load duration curve (LDC) based model and the other is a chronological-based model. These two models were used to evaluate the impacts of wind generation on two utility systems using actual collected wind data at two locations with high potential for wind generation. The results are sensitive to the selected wind data and the level of benefits of wind generation is sensitive to the load forecast. The total production cost over a year obtained by the chronological approach does not differ significantly from that of the LDC approach, though the chronological commitment of units is more realistic and more accurate. Chronological models provide the capability of answering important questions about wind resources which are difficult or impossible to address with LDC models
Locatelli, Luca; Gabriel, S.; Mark, O.
. The impact of retrofitting a retention-detention unit of 3.3 m(3)/100 m(2) (volume/impervious area) was simulated for a small catchment in Copenhagen using MIKE URBAN. The retention-detention unit was shown to prevent flooding from the sewer for a 10-year rainfall event. Statistical analysis of continuous...... simulations covering 22 years showed that annual stormwater runoff was reduced by 68-87%, and that the retention volume was on average 53% full at the beginning of rain events. The effect of different retention-detention volume combinations was simulated, and results showed that allocating 20...
This paper describes a method for using Generative Adversarial Networks to learn distributed representations of natural language documents. We propose a model that is based on the recently proposed Energy-Based GAN, but instead uses a Denoising Autoencoder as the discriminator network. Document representations are extracted from the hidden layer of the discriminator and evaluated both quantitatively and qualitatively.
Farmer, William H.; Knight, Rodney R.; Eash, David A.; Kasey J. Hutchinson,; Linhart, S. Mike; Christiansen, Daniel E.; Archfield, Stacey A.; Over, Thomas M.; Kiang, Julie E.
Daily records of streamflow are essential to understanding hydrologic systems and managing the interactions between human and natural systems. Many watersheds and locations lack streamgages to provide accurate and reliable records of daily streamflow. In such ungaged watersheds, statistical tools and rainfall-runoff models are used to estimate daily streamflow. Previous work compared 19 different techniques for predicting daily streamflow records in the southeastern United States. Here, five of the better-performing methods are compared in a different hydroclimatic region of the United States, in Iowa. The methods fall into three classes: (1) drainage-area ratio methods, (2) nonlinear spatial interpolations using flow duration curves, and (3) mechanistic rainfall-runoff models. The first two classes are each applied with nearest-neighbor and map-correlated index streamgages. Using a threefold validation and robust rank-based evaluation, the methods are assessed for overall goodness of fit of the hydrograph of daily streamflow, the ability to reproduce a daily, no-fail storage-yield curve, and the ability to reproduce key streamflow statistics. As in the Southeast study, a nonlinear spatial interpolation of daily streamflow using flow duration curves is found to be a method with the best predictive accuracy. Comparisons with previous work in Iowa show that the accuracy of mechanistic models with at-site calibration is substantially degraded in the ungaged framework.
Todini, E.; Bartholmes, J.
The project EFFS (European Flood Forecasting System) aims at developing a flood forecasting system for the major river basins all over Europe. To extend the forecast- ing and thus the warning time in a significant way (up to 10 days) meteorological forecasting data from the ECMWF will be used as input to hydrological models. For this purpose it is fundamental to have a reliable rainfall-runoff model. For the river Po basin we chose the TOPKAPI model (Ciarapica, Todini 1998). TOPKAPI is a physi- cally based rainfall-runoff model that maintains its physical significance passing from hillslope to large basin scale. The aim of the distributed version is to reproduce the spatial variability and to lead to a better understanding of scaling effects on meteo- rological data used as well as of physical phenomena and parameters. By now the TOPKAPI model has been applied successfully to basins of smaller and medium size (up to 8000 km2). The present work also proves that TOPKAPI is a valuable flood forecasting tool for larger basins such as the Po river. An advantage of the TOPKAPI model is its physical basis. It doesn't need a "real" calibration in the common sense of the expression. The calibration work that has to be done is due to the unavoidable averaging and approximation in the input data representing various phenomena. This reduces the calibration work as well as the length of data required. The model was implemented on the Po river at spatial steps of 1km and time steps of 1 hour using available data during the year 1994. After the calibration phase, mesoscale forecasts (from ECMWF) as well as forecasts of LAM models (DWD,DMI) will be used as input to the Po river models and their behaviour will be studied as a function of the prediction quality and of the coarseness of the spatial discretisation.
Barlow, J. E.; Goodrich, D. C.; Guertin, D. P.; Burns, I. S.
Wildfires in the Western United States can alter landscapes by removing vegetation and changing soil properties. These altered landscapes produce more runoff than pre-fire landscapes which can lead to post-fire flooding that can damage infrastructure and impair natural resources. Resources, structures, historical artifacts and others that could be impacted by increased runoff are considered values at risk. .The Automated Geospatial Watershed Assessment tool (AGWA) allows users to quickly set up and execute the Kinematic Runoff and Erosion model (KINEROS2 or K2) in the ESRI ArcMap environment. The AGWA-K2 workflow leverages the visualization capabilities of GIS to facilitate evaluation of rapid watershed assessments for post-fire planning efforts. High relative change in peak discharge