WorldWideScience

Sample records for hydrometeorological modeling land

  1. Quantifying near-surface water exchange to assess hydrometeorological models

    Science.gov (United States)

    Parent, Annie-Claude; Anctil, François; Morais, Anne

    2013-04-01

    Modelling water exchange from the lower atmosphere, crop and soil system using hydrometeorological models allows processing an actual evapotranspiration (ETa) which is a complex but critical value for numerous hydrological purposes e.g. hydrological modelling and crop irrigation. This poster presents a summary of the hydrometeorological research activity conducted by our research group. The first purpose of this research is to quantify ETa and drainage of a rainfed potato crop located in South-Eastern Canada. Then, the outputs of the hydrometeorological models under study are compared with the observed turbulent fluxes. Afterwards, the sensibility of the hydrometeorological models to different inputs is assessed for an environment under a changing climate. ETa was measured from micrometeorological instrumentation (CSAT3, Campbell SCI Inc.; Li7500, LiCor Inc.), and the eddy covariance techniques. Near surface soil heat flux and soil water content at different layers from 10 cm to 100 cm were also measured. Other parameters required by the hydrometeorological models were observed using meteorological standard instrumentation: shortwave and longwave solar radiation, wind speed, air temperature, atmospheric pressure and precipitation. The cumulative ETa during the growth season (123 days) was 331.5 mm, with a daily maximum of 6.5 mm at full coverage; precipitation was 350.6 mm which is rather small compared with the historical mean (563.3 mm). This experimentation allowed calculating crop coefficients that vary among the growth season for a rainfed potato crop. Land surface schemes as CLASS (Canadian Land Surface Scheme) and c-ISBA (a Canadian version of the model Interaction Sol-Biosphère-Atmosphère) are 1-D physical hydrometeorological models that produce turbulent fluxes (including ETa) for a given crop. The schemes performances were assessed for both energy and water balance, based on the resulting turbulent fluxes and the given observations. CLASS showed

  2. Hydrometeorological network for flood monitoring and modeling

    Science.gov (United States)

    Efstratiadis, Andreas; Koussis, Antonis D.; Lykoudis, Spyros; Koukouvinos, Antonis; Christofides, Antonis; Karavokiros, George; Kappos, Nikos; Mamassis, Nikos; Koutsoyiannis, Demetris

    2013-08-01

    Due to its highly fragmented geomorphology, Greece comprises hundreds of small- to medium-size hydrological basins, in which often the terrain is fairly steep and the streamflow regime ephemeral. These are typically affected by flash floods, occasionally causing severe damages. Yet, the vast majority of them lack flow-gauging infrastructure providing systematic hydrometric data at fine time scales. This has obvious impacts on the quality and reliability of flood studies, which typically use simplistic approaches for ungauged basins that do not consider local peculiarities in sufficient detail. In order to provide a consistent framework for flood design and to ensure realistic predictions of the flood risk -a key issue of the 2007/60/EC Directive- it is essential to improve the monitoring infrastructures by taking advantage of modern technologies for remote control and data management. In this context and in the research project DEUCALION, we have recently installed and are operating, in four pilot river basins, a telemetry-based hydro-meteorological network that comprises automatic stations and is linked to and supported by relevant software. The hydrometric stations measure stage, using 50-kHz ultrasonic pulses or piezometric sensors, or both stage (piezometric) and velocity via acoustic Doppler radar; all measurements are being temperature-corrected. The meteorological stations record air temperature, pressure, relative humidity, wind speed and direction, and precipitation. Data transfer is made via GPRS or mobile telephony modems. The monitoring network is supported by a web-based application for storage, visualization and management of geographical and hydro-meteorological data (ENHYDRIS), a software tool for data analysis and processing (HYDROGNOMON), as well as an advanced model for flood simulation (HYDROGEIOS). The recorded hydro-meteorological observations are accessible over the Internet through the www-application. The system is operational and its

  3. Representing vegetation processes in hydrometeorological simulations using the WRF model

    DEFF Research Database (Denmark)

    Nielsen, Joakim Refslund

    -ments are still needed in the representation of the land surface variability and of some key land surface processes. This thesis explores two possibilities for improving the near-surface model predictions using the mesoscale Weather Research and Forecasting (WRF) model. In the _rst approach, data from satellite......For accurate predictions of weather and climate, it is important that the land surface and its processes are well represented. In a mesoscale model the land surface processes are calculated in a land surface model (LSM). These pro-cesses include exchanges of energy, water and momentum between...... the land surface components, such as vegetation and soil, and their interactions with the atmosphere. The land surface processes are complex and vary in time and space. Signi_cant e_ort by the land surface community has therefore been invested in improving the LSMs over the recent decades. However, improve...

  4. Cross-compartment evaluation of a fully-coupled hydrometeorological modeling system using comprehensive observation data

    Science.gov (United States)

    Fersch, Benjamin; Senatore, Alfonso; Kunstmann, Harald

    2017-04-01

    Fully-coupled hydrometeorological modeling enables investigations about the complex and often non-linear exchange mechanisms among subsurface, land, and atmosphere with respect to water and energy fluxes. The consideration of lateral redistribution of surface and subsurface water in such modeling systems is a crucial enhancement, allowing for a better representation of surface spatial patterns and providing also channel discharge predictions. However, the evaluation of fully-coupled simulations is difficult since the amount of physical detail along with feedback mechanisms leads to high degrees of freedom. Therefore, comprehensive observation data is required to obtain meaningful model configurations. We present a case study for a medium-sized river catchment in southern Germany that includes the calibration of the stand-alone and the evaluation of the fully-coupled WRF-Hydro modeling system with a horizontal resolution of 1 x 1 km2, for the period June to August 2015. ECMWF ERA-Interim reanalysis is used for model driving. Land-surface processes are represented by the Noah-MP land surface model. Land-cover is described by the EU CORINE data set. Observations for model evaluation are obtained from the TERENO Pre-Alpine observatory (http://www.imk-ifu.kit.edu/tereno.php) and are complemented by further measurements from the ScaleX campaign (http://scalex.imk-ifu.kit.edu) such as atmospheric profiles obtained from radiometer sounding and airborne systems as well as soil moisture and -temperature networks. We show how well water budgets and heat-fluxes are being reproduced by the stand-alone WRF, the stand-alone WRF-Hydro and the fully-coupled WRF-Hydro model.

  5. Evaluation of satellite-model proxies for hydro-meteorological services in the upper Zambezi

    Directory of Open Access Journals (Sweden)

    Mark R. Jury

    2017-10-01

    Insights: Satellite soil moisture and model run-off track the Kafue Hook gauge with correlation values of 84% and 68%, respectively. Satellite river flow estimates achieve a logarithmic fit to monthly and daily gauge of 92% and 65%, respectively. Discrepancies are related to inadequate (calibration reporting and to under-estimation of evaporation in the dry season. Statistical analyses of satellite rainfall and model evaporation are used to suggest improvements to hydro-meteorology network coverage in the upper Zambezi. An automated online network of ∼20 weather stations and river flow gauges appears sufficient, given satellite-model ability to interpolate between observations.

  6. Mathematical Modelling of Thermal Process to Aquatic Environment with Different Hydrometeorological Conditions

    Directory of Open Access Journals (Sweden)

    Alibek Issakhov

    2014-01-01

    Full Text Available This paper presents the mathematical model of the thermal process from thermal power plant to aquatic environment of the reservoir-cooler, which is located in the Pavlodar region, 17 Km to the north-east of Ekibastuz town. The thermal process in reservoir-cooler with different hydrometeorological conditions is considered, which is solved by three-dimensional Navier-Stokes equations and temperature equation for an incompressible flow in a stratified medium. A numerical method based on the projection method, divides the problem into three stages. At the first stage, it is assumed that the transfer of momentum occurs only by convection and diffusion. Intermediate velocity field is solved by fractional steps method. At the second stage, three-dimensional Poisson equation is solved by the Fourier method in combination with tridiagonal matrix method (Thomas algorithm. Finally, at the third stage, it is expected that the transfer is only due to the pressure gradient. Numerical method determines the basic laws of the hydrothermal processes that qualitatively and quantitatively are approximated depending on different hydrometeorological conditions.

  7. Mathematical modelling of thermal process to aquatic environment with different hydrometeorological conditions.

    Science.gov (United States)

    Issakhov, Alibek

    2014-01-01

    This paper presents the mathematical model of the thermal process from thermal power plant to aquatic environment of the reservoir-cooler, which is located in the Pavlodar region, 17 Km to the north-east of Ekibastuz town. The thermal process in reservoir-cooler with different hydrometeorological conditions is considered, which is solved by three-dimensional Navier-Stokes equations and temperature equation for an incompressible flow in a stratified medium. A numerical method based on the projection method, divides the problem into three stages. At the first stage, it is assumed that the transfer of momentum occurs only by convection and diffusion. Intermediate velocity field is solved by fractional steps method. At the second stage, three-dimensional Poisson equation is solved by the Fourier method in combination with tridiagonal matrix method (Thomas algorithm). Finally, at the third stage, it is expected that the transfer is only due to the pressure gradient. Numerical method determines the basic laws of the hydrothermal processes that qualitatively and quantitatively are approximated depending on different hydrometeorological conditions.

  8. Quantification and classification of hydro-meteorological flood controls in northeast Switzerland as a basis for robust impact modelling

    Science.gov (United States)

    Keller, Luise; Rössler, Ole; Weingartner, Rolf

    2016-04-01

    Flood events are generated and shaped by different hydro-meteorological processes. Taking these drivers into account is essential for understanding flood generation and for developing robust hydrological models. We call a hydrological model robust if it is able to reproduce different flood types with different drivers at the same quality. Such models are a prerequisite for assessing climate change impact as they minimize bias associated with a potential change in frequency of projected flood types. For the same reason, identification of the key hydro-meteorological processes is crucial to enable a suitable downscaling of meteorological parameters. To gain understanding of the main hydro-meteorological processes associated with floods in a mesoscale alpine catchment (Thur River, 1700 km2), we analyse all events exceeding a 2-year flood over the past 50 years. Resulting 47 events are temporally delineated based on an adapted constant-k approach (Blume et al., 2007) using hourly runoff data. Each flood event is then characterized based on a variety of hydro-meteorological parameters and indices descriptive of catchment distributed (pre-) event conditions based on daily meteorological data. This comprehensive data set is used to classify the events based on hydro-meteorological parameters only and to derive typical flood-generating "storylines". Changes in these storylines over the past 50 years are discussed. Furthermore, the importance of each hydro-meteorological parameter is quantified which in turn might help to assess uncertainties associated with climate change impact studies. References Blume, T., Zehe, E., and Bronstert, A.: Rainfall - runoff response, event-based runoff coefficients and hydrograph separation, Hydrological Sciences Journal, 52, 843-862, doi:10.1623/hysj.52.5.843, 2007.

  9. Hydro-meteorological risk reduction through land restoration in Rangárvellir, Iceland - an overview of the HydroResilience project

    Science.gov (United States)

    Finger, David C.; Pétursdóttir, Þórunn; Halldórsson, Guðmundur

    2017-04-01

    Ecosystems that are in equilibrium provide vital resources to local inhabitants, including protection from naturally occurring disasters. Natural vegetation cover has been optimized over many years to retain a maximum of rainfall runoff by increasing the field capacity (FC) of the soil cover, securing water availability during droughts and reducing the flood risk during heavy precipitation events. In this presentation we will present the HydroResilience project, which will assess the effects of ecosystem restoration on the runoff dynamics of rainfall water in Rangárvellir, a restoration area in southern Iceland. The Rangárvellir area presents ideal conditions for such investigations. Dramatic deforestation during the last millennium and year round livestock grazing along with devastating ash depositions during volcanic eruptions and a harsh sub-polar oceanic climate have led to severe degradation in Rangárvellir. Since the beginning of the 20th century diverse restoration measures have been implemented making Rangárvellir an ideal case study to investigate the effects of restoration on hydro-meteorological risk reduction. In this project we will assess and quantify the evolution of water resources in Rangárvellir by assessing the runoff dynamics in the main rivers of Rangárvellir under four main scenarios: i) present conditions, ii) degraded conditions as was the case 100 years ago, iii) under hypothetical fully restored ecosystems and, finally, iv) under conditions of a scenario developed in collaboration with local stakeholder groups to optimize socio-ecological benefits. For this purpose the dynamics of the relevant hydrological processes in the area (incl. river runoff, ground water table, snow cover duration, and soil moisture dynamics) will be reconstructed using hydrological models to run the above mentioned scenarios. The scientific findings and conclusion of this project will generate valuable insights on the effects of land restoration on hydro-meteorological

  10. Effects of Seasonal Land Surface Conditions on Hydrometeorological Dynamics in South-western North America

    Science.gov (United States)

    2015-09-21

    Using observations and a distributed hydrologic model to explore runoff thresholds linked with mesquite encroachment in the Sonoran Desert , Water...and cultural shiftsadvancing drylands research and management, Frontiers in Ecology and the Environment, (01 2015): 52. doi: Giuseppe Mascaro... Desert Watershed. American Geophysical Union Fall Meeting, San Francisco, CA. 7. Mendez-Barroso, L.A., Vivoni, E.R., Rodriguez, J.C., Watts, C.J

  11. Coupling X-band dual-polarized mini-radars and hydro-meteorological forecast models: the HYDRORAD project

    Directory of Open Access Journals (Sweden)

    E. Picciotti

    2013-05-01

    Full Text Available Hydro-meteorological hazards like convective outbreaks leading to torrential rain and floods are among the most critical environmental issues world-wide. In that context weather radar observations have proven to be very useful in providing information on the spatial distribution of rainfall that can support early warning of floods. However, quantitative precipitation estimation by radar is subjected to many limitations and uncertainties. The use of dual-polarization at high frequency (i.e. X-band has proven particularly useful for mitigating some of the limitation of operational systems, by exploiting the benefit of easiness to transport and deploy and the high spatial and temporal resolution achievable at small antenna sizes. New developments on X-band dual-polarization technology in recent years have received the interest of scientific and operational communities in these systems. New enterprises are focusing on the advancement of cost-efficient mini-radar network technology, based on high-frequency (mainly X-band and low-power weather radar systems for weather monitoring and hydro-meteorological forecasting. Within the above context, the main objective of the HYDRORAD project was the development of an innovative mbox{integrated} decision support tool for weather monitoring and hydro-meteorological applications. The integrated system tool is based on a polarimetric X-band mini-radar network which is the core of the decision support tool, a novel radar products generator and a hydro-meteorological forecast modelling system that ingests mini-radar rainfall products to forecast precipitation and floods. The radar products generator includes algorithms for attenuation correction, hydrometeor classification, a vertical profile reflectivity correction, a new polarimetric rainfall estimators developed for mini-radar observations, and short-term nowcasting of convective cells. The hydro-meteorological modelling system includes the Mesoscale Model 5

  12. Coupling X-band dual-polarized mini-radars and hydro-meteorological forecast models: the HYDRORAD project

    Science.gov (United States)

    Picciotti, E.; Marzano, F. S.; Anagnostou, E. N.; Kalogiros, J.; Fessas, Y.; Volpi, A.; Cazac, V.; Pace, R.; Cinque, G.; Bernardini, L.; De Sanctis, K.; Di Fabio, S.; Montopoli, M.; Anagnostou, M. N.; Telleschi, A.; Dimitriou, E.; Stella, J.

    2013-05-01

    Hydro-meteorological hazards like convective outbreaks leading to torrential rain and floods are among the most critical environmental issues world-wide. In that context weather radar observations have proven to be very useful in providing information on the spatial distribution of rainfall that can support early warning of floods. However, quantitative precipitation estimation by radar is subjected to many limitations and uncertainties. The use of dual-polarization at high frequency (i.e. X-band) has proven particularly useful for mitigating some of the limitation of operational systems, by exploiting the benefit of easiness to transport and deploy and the high spatial and temporal resolution achievable at small antenna sizes. New developments on X-band dual-polarization technology in recent years have received the interest of scientific and operational communities in these systems. New enterprises are focusing on the advancement of cost-efficient mini-radar network technology, based on high-frequency (mainly X-band) and low-power weather radar systems for weather monitoring and hydro-meteorological forecasting. Within the above context, the main objective of the HYDRORAD project was the development of an innovative integrated decision support tool for weather monitoring and hydro-meteorological applications. The integrated system tool is based on a polarimetric X-band mini-radar network which is the core of the decision support tool, a novel radar products generator and a hydro-meteorological forecast modelling system that ingests mini-radar rainfall products to forecast precipitation and floods. The radar products generator includes algorithms for attenuation correction, hydrometeor classification, a vertical profile reflectivity correction, a new polarimetric rainfall estimators developed for mini-radar observations, and short-term nowcasting of convective cells. The hydro-meteorological modelling system includes the Mesoscale Model 5 (MM5) and the Army Corps

  13. Propagation of hydro-meteorological uncertainty in a model cascade framework to inundation prediction

    Science.gov (United States)

    Rodríguez-Rincón, J. P.; Pedrozo-Acuña, A.; Breña-Naranjo, J. A.

    2015-07-01

    This investigation aims to study the propagation of meteorological uncertainty within a cascade modelling approach to flood prediction. The methodology was comprised of a numerical weather prediction (NWP) model, a distributed rainfall-runoff model and a 2-D hydrodynamic model. The uncertainty evaluation was carried out at the meteorological and hydrological levels of the model chain, which enabled the investigation of how errors that originated in the rainfall prediction interact at a catchment level and propagate to an estimated inundation area and depth. For this, a hindcast scenario is utilised removing non-behavioural ensemble members at each stage, based on the fit with observed data. At the hydrodynamic level, an uncertainty assessment was not incorporated; instead, the model was setup following guidelines for the best possible representation of the case study. The selected extreme event corresponds to a flood that took place in the southeast of Mexico during November 2009, for which field data (e.g. rain gauges; discharge) and satellite imagery were available. Uncertainty in the meteorological model was estimated by means of a multi-physics ensemble technique, which is designed to represent errors from our limited knowledge of the processes generating precipitation. In the hydrological model, a multi-response validation was implemented through the definition of six sets of plausible parameters from past flood events. Precipitation fields from the meteorological model were employed as input in a distributed hydrological model, and resulting flood hydrographs were used as forcing conditions in the 2-D hydrodynamic model. The evolution of skill within the model cascade shows a complex aggregation of errors between models, suggesting that in valley-filling events hydro-meteorological uncertainty has a larger effect on inundation depths than that observed in estimated flood inundation extents.

  14. EDgE multi-model hydro-meteorological seasonal hindcast experiments over Europe

    Science.gov (United States)

    Samaniego, Luis; Thober, Stephan; Kumar, Rohini; Rakovec, Oldrich; Wood, Eric; Sheffield, Justin; Pan, Ming; Wanders, Niko; Prudhomme, Christel

    2017-04-01

    Extreme hydrometeorological events (e.g., floods, droughts and heat waves) caused serious damage to society and infrastructures over Europe during the past decades. Developing a seamless and skillful operational seasonal forecasting system of these extreme events is therefore a key tool for short-term decision making at local and regional scales. The EDgE project funded by the Copernicus programme (C3S) provides an unique opportunity to investigate the skill of a newly created large multi-model hydro-meteorological ensemble for predicting extreme events over the Pan-EU domain at a higher resolution 5×5 km2. Two state-of-the-art seasonal prediction systems were chosen for this project. Two models from the North American MultiModel ensemble (NMME) with 22 realizations, and two models provided by the ECMWF with 30 realizations. All models provide daily forcings (P, Ta, Tmin, Tmax) of the the Pan-EU at 1°. Downscaling has been carried out with the MTCLIM algorithm (Bohn et al. 2013) and external drift Kriging using elevation as drift to induce orographic effects. In this project, four high-resolution seamless hydrologic simulations with the mHM (www.ufz.de/mhm), Noah-MP, VIC and PCR-GLOBWB have been completed for the common hindcast period of 1993-2012 resulting in an ensemble size of 208 realizations. Key indicators are focussing on six terrestrial Essential Climate Variables (tECVs): river runoff, soil moisture, groundwater recharge, precipitation, potential evapotranspiration, and snow water equivalent. Impact Indicators have been co-designed with stakeholders in Norway (hydro-power), UK (water supply), and Spain (river basin authority) to provide an improved information for decision making. The Indicators encompass diverse information such as the occurrence of high and low streamflow percentiles (floods, and hydrological drought) and lower percentiles of top soil moisture (agricultural drought) among others. Preliminary results evaluated at study sites in Norway

  15. Performance of the WRF model to simulate the seasonal and interannual variability of hydrometeorological variables in East Africa: a case study for the Tana River basin in Kenya

    Science.gov (United States)

    Kerandi, Noah Misati; Laux, Patrick; Arnault, Joel; Kunstmann, Harald

    2017-10-01

    This study investigates the ability of the regional climate model Weather Research and Forecasting (WRF) in simulating the seasonal and interannual variability of hydrometeorological variables in the Tana River basin (TRB) in Kenya, East Africa. The impact of two different land use classifications, i.e., the Moderate Resolution Imaging Spectroradiometer (MODIS) and the US Geological Survey (USGS) at two horizontal resolutions (50 and 25 km) is investigated. Simulated precipitation and temperature for the period 2011-2014 are compared with Tropical Rainfall Measuring Mission (TRMM), Climate Research Unit (CRU), and station data. The ability of Tropical Rainfall Measuring Mission (TRMM) and Climate Research Unit (CRU) data in reproducing in situ observation in the TRB is analyzed. All considered WRF simulations capture well the annual as well as the interannual and spatial distribution of precipitation in the TRB according to station data and the TRMM estimates. Our results demonstrate that the increase of horizontal resolution from 50 to 25 km, together with the use of the MODIS land use classification, significantly improves the precipitation results. In the case of temperature, spatial patterns and seasonal cycle are well reproduced, although there is a systematic cold bias with respect to both station and CRU data. Our results contribute to the identification of suitable and regionally adapted regional climate models (RCMs) for East Africa.

  16. Combined use of local and global hydrometeorological data with regional and global hydrological models in the Magdalena - Cauca river basin, Colombia

    Science.gov (United States)

    Rodriguez, Erasmo; Sanchez, Ines; Duque, Nicolas; Lopez, Patricia; Kaune, Alexander; Werner, Micha; Arboleda, Pedro

    2017-04-01

    The Magdalena Cauca Macrobasin (MCMB) in Colombia, with an area of about 257,000 km2, is the largest and most important water resources system in the country. With almost 80% of the Colombian population (46 million people) settled in the basin, it is the main source of water for demands including human consumption, agriculture, hydropower generation, industrial activities and ecosystems. Despite its importance, the basin has witnessed enormous changes in land-cover and extensive deforestation during the last three decades. To make things more complicated, the MCMB currently lacks a set of tools to support planning and decision making processes at scale of the whole watershed. Considering this, the MCMB has been selected as one of the six different regional case studies in the eartH2Observe research project, in which hydrological and meteorological reanalysis products are being validated for the period 1980-2012. The combined use of the hydrological and meteorological reanalysis data, with local hydrometeorological data (precipitation, temperature and streamflow) provided by the National Hydrometeorological Agency (IDEAM), has given us the opportunity to implement and test three hydrological models (VIC, WFLOW and a Water Balance Model based on the Budyko framework) at the basin scale. Additionally, results from the global models in the eartH2Observe hydrological reanalysis have been used to evaluate their performance against the observed streamflow data. This paper discusses the comparison between streamflow observations and simulations from the global hydrological models forced with the WFDEI data, and regional models forced with a combination of observed and meteorological reanalysis data, in the whole domain of the MCMB. For the three regional models analysed results show good performances for some sub-basins and poor performances for others. This can be due to the smoothing of the precipitation fields, interpolated from point daily rainfall data, the effect of

  17. Hydrometeorological Automated Data System

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Office of Hydrologic Development of the National Weather Service operates HADS, the Hydrometeorological Automated Data System. This data set contains the last 48...

  18. Hydrometeorological multi-model ensemble simulations of the 4 November 2011 flash-flood event in Genoa, Italy, in the framework of the DRIHM project

    Science.gov (United States)

    Hally, A.; Caumont, O.; Garrote, L.; Richard, E.; Weerts, A.; Delogu, F.; Fiori, E.; Rebora, N.; Parodi, A.; Mihalović, A.; Ivković, M.; Dekić, L.; van Verseveld, W.; Nuissier, O.; Ducrocq, V.; D'Agostino, D.; Galizia, A.; Danovaro, E.; Clematis, A.

    2014-11-01

    The e-Science environment developed in the framework of the EU-funded DRIHM project was used to demonstrate its capability to provide relevant, meaningful hydrometeorological forecasts. This was illustrated for the tragic case of 4 November 2011, when Genoa, Italy, was flooded as the result of heavy, convective precipitation that inundated the Bisagno catchment. The Meteorological Model Bridge (MMB), an innovative software component developped within the DRIHM project for the interoperability of meteorological and hydrological models, is a key component of the DRIHM e-Science environment. The MMB allowed three different rainfall-discharge models (DRiFt, RIBS, and HBV) to be driven by four mesoscale limited-area atmospheric models (WRF-NMM, WRF-ARW, Meso-NH, and AROME) and a downscaling algorithm (RainFARM) in a seamless fashion. In addition to this multi-model configuration, some of the models were run in probabilistic mode, thus allowing a comprehensive account of modelling errors and a very large amount of likely hydrometeorological scenarios (>1500). The multi-model approach proved to be necessary because, whilst various aspects of the event were successfully simulated by different models, none of the models reproduced all of these aspects correctly. It was shown that the resulting set of simulations helped identify key atmospheric processes responsible for the large rainfall accumulations over the Bisagno basin. The DRIHM e-Science environment facilitated an evaluation of the sensitivity to atmospheric and hydrological modelling errors. This showed that both had a significant impact on predicted discharges, the former being larger than the latter. Finally, the usefulness of the set of hydrometeorological simulations was assessed from a flash-flood early-warning perspective.

  19. Hydrometeorological multi-model ensemble simulations of the 4 November 2011 flash flood event in Genoa, Italy, in the framework of the DRIHM project

    Science.gov (United States)

    Hally, A.; Caumont, O.; Garrote, L.; Richard, E.; Weerts, A.; Delogu, F.; Fiori, E.; Rebora, N.; Parodi, A.; Mihalović, A.; Ivković, M.; Dekić, L.; van Verseveld, W.; Nuissier, O.; Ducrocq, V.; D'Agostino, D.; Galizia, A.; Danovaro, E.; Clematis, A.

    2015-03-01

    The e-Science environment developed in the framework of the EU-funded DRIHM project was used to demonstrate its ability to provide relevant, meaningful hydrometeorological forecasts. This was illustrated for the tragic case of 4 November 2011, when Genoa, Italy, was flooded as the result of heavy, convective precipitation that inundated the Bisagno catchment. The Meteorological Model Bridge (MMB), an innovative software component developed within the DRIHM project for the interoperability of meteorological and hydrological models, is a key component of the DRIHM e-Science environment. The MMB allowed three different rainfall-discharge models (DRiFt, RIBS and HBV) to be driven by four mesoscale limited-area atmospheric models (WRF-NMM, WRF-ARW, Meso-NH and AROME) and a downscaling algorithm (RainFARM) in a seamless fashion. In addition to this multi-model configuration, some of the models were run in probabilistic mode, thus giving a comprehensive account of modelling errors and a very large amount of likely hydrometeorological scenarios (> 1500). The multi-model approach proved to be necessary because, whilst various aspects of the event were successfully simulated by different models, none of the models reproduced all of these aspects correctly. It was shown that the resulting set of simulations helped identify key atmospheric processes responsible for the large rainfall accumulations over the Bisagno basin. The DRIHM e-Science environment facilitated an evaluation of the sensitivity to atmospheric and hydrological modelling errors. This showed that both had a significant impact on predicted discharges, the former being larger than the latter. Finally, the usefulness of the set of hydrometeorological simulations was assessed from a flash flood early-warning perspective.

  20. Hydrometeorological multi-model ensemble simulations of the 4 November 2011 flash flood event in Genoa, Italy, in the framework of the DRIHM project

    Directory of Open Access Journals (Sweden)

    A. Hally

    2015-03-01

    Full Text Available The e-Science environment developed in the framework of the EU-funded DRIHM project was used to demonstrate its ability to provide relevant, meaningful hydrometeorological forecasts. This was illustrated for the tragic case of 4 November 2011, when Genoa, Italy, was flooded as the result of heavy, convective precipitation that inundated the Bisagno catchment. The Meteorological Model Bridge (MMB, an innovative software component developed within the DRIHM project for the interoperability of meteorological and hydrological models, is a key component of the DRIHM e-Science environment. The MMB allowed three different rainfall-discharge models (DRiFt, RIBS and HBV to be driven by four mesoscale limited-area atmospheric models (WRF-NMM, WRF-ARW, Meso-NH and AROME and a downscaling algorithm (RainFARM in a seamless fashion. In addition to this multi-model configuration, some of the models were run in probabilistic mode, thus giving a comprehensive account of modelling errors and a very large amount of likely hydrometeorological scenarios (> 1500. The multi-model approach proved to be necessary because, whilst various aspects of the event were successfully simulated by different models, none of the models reproduced all of these aspects correctly. It was shown that the resulting set of simulations helped identify key atmospheric processes responsible for the large rainfall accumulations over the Bisagno basin. The DRIHM e-Science environment facilitated an evaluation of the sensitivity to atmospheric and hydrological modelling errors. This showed that both had a significant impact on predicted discharges, the former being larger than the latter. Finally, the usefulness of the set of hydrometeorological simulations was assessed from a flash flood early-warning perspective.

  1. Impacts of weighting climate models for hydro-meteorological climate change studies

    Science.gov (United States)

    Chen, Jie; Brissette, François P.; Lucas-Picher, Philippe; Caya, Daniel

    2017-06-01

    Weighting climate models is controversial in climate change impact studies using an ensemble of climate simulations from different climate models. In climate science, there is a general consensus that all climate models should be considered as having equal performance or in other words that all projections are equiprobable. On the other hand, in the impacts and adaptation community, many believe that climate models should be weighted based on their ability to better represent various metrics over a reference period. The debate appears to be partly philosophical in nature as few studies have investigated the impact of using weights in projecting future climate changes. The present study focuses on the impact of assigning weights to climate models for hydrological climate change studies. Five methods are used to determine weights on an ensemble of 28 global climate models (GCMs) adapted from the Coupled Model Intercomparison Project Phase 5 (CMIP5) database. Using a hydrological model, streamflows are computed over a reference (1961-1990) and future (2061-2090) periods, with and without post-processing climate model outputs. The impacts of using different weighting schemes for GCM simulations are then analyzed in terms of ensemble mean and uncertainty. The results show that weighting GCMs has a limited impact on both projected future climate in term of precipitation and temperature changes and hydrology in terms of nine different streamflow criteria. These results apply to both raw and post-processed GCM model outputs, thus supporting the view that climate models should be considered equiprobable.

  2. Modelling land cover change in the Ganga basin

    Science.gov (United States)

    Moulds, S.; Tsarouchi, G.; Mijic, A.; Buytaert, W.

    2013-12-01

    Over recent decades the green revolution in India has driven substantial environmental change. Modelling experiments have identified northern India as a 'hot spot' of land-atmosphere coupling strength during the boreal summer. However, there is a wide range of sensitivity of atmospheric variables to soil moisture between individual climate models. The lack of a comprehensive land cover change dataset to force climate models has been identified as a major contributor to model uncertainty. In this work a time series dataset of land cover change between 1970 and 2010 is constructed for northern India to improve the quantification of regional hydrometeorological feedbacks. The MODIS instrument on board the Aqua and Terra satellites provides near-continuous remotely sensed datasets from 2000 to the present day. However, the quality of satellite products before 2000 is poor. To complete the dataset MODIS images are extrapolated back in time using the Conversion of Land Use and its Effects at small regional extent (CLUE-s) modelling framework. Non-spatial estimates of land cover area from national agriculture and forest statistics, available on a state-wise, annual basis, are used as a direct model input. Land cover change is allocated spatially as a function of biophysical and socioeconomic drivers identified using logistic regression. This dataset will provide an essential input to a high resolution, physically based land surface model to generate the lower boundary condition to assess the impact of land cover change on regional climate.

  3. Future intensification of hydro-meteorological extremes: downscaling using the weather research and forecasting model

    Science.gov (United States)

    El-Samra, R.; Bou-Zeid, E.; Bangalath, H. K.; Stenchikov, G.; El-Fadel, M.

    2017-12-01

    A set of ten downscaling simulations at high spatial resolution (3 km horizontally) were performed using the Weather Research and Forecasting (WRF) model to generate future climate projections of annual and seasonal temperature and precipitation changes over the Eastern Mediterranean (with a focus on Lebanon). The model was driven with the High Resolution Atmospheric Model (HiRAM), running over the whole globe at a resolution of 25 km, under the conditions of two Representative Concentration Pathways (RCP) (4.5 and 8.5). Each downscaling simulation spanned one year. Two past years (2003 and 2008), also forced by HiRAM without data assimilation, were simulated to evaluate the model's ability to capture the cold and wet (2003) and hot and dry (2008) extremes. The downscaled data were in the range of recent observed climatic variability, and therefore corrected for the cold bias of HiRAM. Eight future years were then selected based on an anomaly score that relies on the mean annual temperature and accumulated precipitation to identify the worst year per decade from a water resources perspective. One hot and dry year per decade, from 2011 to 2050, and per scenario was simulated and compared to the historic 2008 reference. The results indicate that hot and dry future extreme years will be exacerbated and the study area might be exposed to a significant decrease in annual precipitation (rain and snow), reaching up to 30% relative to the current extreme conditions.

  4. Future intensification of hydro-meteorological extremes: downscaling using the weather research and forecasting model

    KAUST Repository

    El-Samra, R.

    2017-02-15

    A set of ten downscaling simulations at high spatial resolution (3 km horizontally) were performed using the Weather Research and Forecasting (WRF) model to generate future climate projections of annual and seasonal temperature and precipitation changes over the Eastern Mediterranean (with a focus on Lebanon). The model was driven with the High Resolution Atmospheric Model (HiRAM), running over the whole globe at a resolution of 25 km, under the conditions of two Representative Concentration Pathways (RCP) (4.5 and 8.5). Each downscaling simulation spanned one year. Two past years (2003 and 2008), also forced by HiRAM without data assimilation, were simulated to evaluate the model’s ability to capture the cold and wet (2003) and hot and dry (2008) extremes. The downscaled data were in the range of recent observed climatic variability, and therefore corrected for the cold bias of HiRAM. Eight future years were then selected based on an anomaly score that relies on the mean annual temperature and accumulated precipitation to identify the worst year per decade from a water resources perspective. One hot and dry year per decade, from 2011 to 2050, and per scenario was simulated and compared to the historic 2008 reference. The results indicate that hot and dry future extreme years will be exacerbated and the study area might be exposed to a significant decrease in annual precipitation (rain and snow), reaching up to 30% relative to the current extreme conditions.

  5. Regional model simulation of the hydrometeorological effects of the Fucino Lake on the surrounding region

    Directory of Open Access Journals (Sweden)

    B. Tomassetti

    Full Text Available The drainage of the Fucino Lake of central Italy was completed in 1873, and this possibly caused significant climatic changes over the Fucino basin. In this paper we discuss a set of short-term triple-nested regional model simulations of the meteorological effects of the Fucino Lake on the surrounding region. We find that the model simulates realistic lake-breeze circulations and their response to background winds. The simulations indicate that the lake affects the temperature of the surrounding basin in all seasons and precipitation in the cold season, when cyclonic perturbations move across the region. Some effects of the lake also extend over areas quite far from the Fucino basin. Our results support the hypothesis that the drainage of the lake might have significantly affected the climate of the lake basin. However, longer simulations and further development in some aspects of the model are needed, in order to provide a more statistically robust evaluation of the simulated lake-effects.

    Key words. Hydrology (anthropogenic effects – Meteorology and atmospheric dynamics (climatology; mesoscale meteorology

  6. Modelling land use change in the Ganga basin

    Science.gov (United States)

    Moulds, Simon; Mijic, Ana; Buytaert, Wouter

    2014-05-01

    Over recent decades the green revolution in India has driven substantial environmental change. Modelling experiments have identified northern India as a "hot spot" of land-atmosphere coupling strength during the boreal summer. However, there is a wide range of sensitivity of atmospheric variables to soil moisture between individual climate models. The lack of a comprehensive land use change dataset to force climate models has been identified as a major contributor to model uncertainty. This work aims to construct a monthly time series dataset of land use change for the period 1966 to 2007 for northern India to improve the quantification of regional hydrometeorological feedbacks. The Moderate Resolution Imaging Spectroradiometer (MODIS) instrument on board the Aqua and Terra satellites provides near-continuous remotely sensed datasets from 2000 to the present day. However, the quality and availability of satellite products before 2000 is poor. To complete the dataset MODIS images are extrapolated back in time using the Conversion of Land Use and its Effects at Small regional extent (CLUE-S) modelling framework, recoded in the R programming language to overcome limitations of the original interface. Non-spatial estimates of land use area published by the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) for the study period, available on an annual, district-wise basis, are used as a direct model input. Land use change is allocated spatially as a function of biophysical and socioeconomic drivers identified using logistic regression. The dataset will provide an essential input to a high-resolution, physically-based land-surface model to generate the lower boundary condition to assess the impact of land use change on regional climate.

  7. Separating the effects of changes in land cover and climate: a hydro-meteorological analysis of the past 60 yr in Saxony, Germany

    Science.gov (United States)

    Renner, M.; Brust, K.; Schwärzel, K.; Volk, M.; Bernhofer, C.

    2014-01-01

    Understanding and quantifying the impact of changes in climate and land use/land cover on water availability is a prerequisite to adapt water management; yet, it can be difficult to separate the effects of these different impacts. In this paper we illustrate a separation and attribution method based on a Budyko framework. We assume that evapotranspiration (ET) is limited by the climatic forcing of precipitation (P) and evaporative demand (E0), but modified by land-surface properties. Impacts of changes in climate (i.e., E0/P) or land-surface changes on ET alter the two dimensionless measures describing relative water (ET/P) and energy partitioning (ET/E0), which allows us to separate and quantify these impacts. We use the separation method to quantify the role of environmental factors on ET using 68 small to medium range river basins covering the greatest part of the German Federal State of Saxony within the period of 1950-2009. The region can be considered as a typical central European landscape with considerable anthropogenic impacts. In the long term, most basins are found to follow the Budyko curve which we interpret as a result of the strong interactions of climate, soils and vegetation. However, two groups of basins deviate. Agriculturally dominated basins at lower altitudes exceed the Budyko curve while a set of high altitude, forested basins fall well below. When visualizing the decadal dynamics on the relative partitioning of water and energy the impacts of climatic and land-surface changes become apparent. After 1960 higher forested basins experienced large land-surface changes which show that the air pollution driven tree damages have led to a decline of annual ET on the order of 38%. In contrast, lower, agricultural dominated areas show no significant changes during that time. However, since the 1990s effective mitigation measures on industrial pollution have been established and the apparent brightening and regrowth has resulted in a significant

  8. Regional scale hydrology with a new land surface processes model

    Science.gov (United States)

    Laymon, Charles; Crosson, William

    1995-01-01

    Through the CaPE Hydrometeorology Project, we have developed an understanding of some of the unique data quality issues involved in assimilating data of disparate types for regional-scale hydrologic modeling within a GIS framework. Among others, the issues addressed here include the development of adequate validation of the surface water budget, implementation of the STATSGO soil data set, and implementation of a remote sensing-derived landcover data set to account for surface heterogeneity. A model of land surface processes has been developed and used in studies of the sensitivity of surface fluxes and runoff to soil and landcover characterization. Results of these experiments have raised many questions about how to treat the scale-dependence of land surface-atmosphere interactions on spatial and temporal variability. In light of these questions, additional modifications are being considered for the Marshall Land Surface Processes Model. It is anticipated that these techniques can be tested and applied in conjunction with GCIP activities over regional scales.

  9. Modelling land surface - atmosphere interactions

    DEFF Research Database (Denmark)

    Rasmussen, Søren Højmark

    related to inaccurate land surface modelling, e.g. enhanced warm bias in warm dry summer months. Coupling the regional climate model to a hydrological model shows the potential of improving the surface flux simulations in dry periods and the 2 m air temperature in general. In the dry periods......The study is investigates modelling of land surface – atmosphere interactions in context of fully coupled climatehydrological model. With a special focus of under what condition a fully coupled model system is needed. Regional climate model inter-comparison projects as ENSEMBLES have shown bias...

  10. Hydrological now- and forecasting : Integration of operationally available remotely sensed and forecasted hydrometeorological variables into distributed hydrological models

    NARCIS (Netherlands)

    Schuurmans, J.M.|info:eu-repo/dai/nl/304832650

    2008-01-01

    Keywords: hydrology, models, soil moisture, rainfall, radar, rain gauge, remote sensing, evapotranspiration, forecasting, numerical weather prediction, Netherlands, Langbroekerwetering, Lopikerwaard. Computer simulation models are an important tool for hydrologists. With these models they can

  11. Hydrometeorological multi-model ensemble simulations of the 4 November 2011 flash flood event in Genoa, Italy, in the framework of the DRIHM Project

    NARCIS (Netherlands)

    Hally, A.; Caumont, O.; Garrote, L.; Richard, E.; Weerts, A.H.; Delogu, F.; Fiori, E.; Rebora, N.; Parodi, A.; Mihalovic, A.; Ivkovic, M.; Dekic, L.; Verseveld, W.J.; Nuissier, O.; Ducrocq, V.P.; Agostino, d' D.; Galizia, A.; Danovaro, E.; Clematis, A.

    2015-01-01

    The e-Science environment developed in the framework of the EU-funded DRIHM project was used to demonstrate its ability to provide relevant, meaningful hydrometeorological forecasts. This was illustrated for the tragic case of 4 November 2011, when Genoa, Italy, was flooded as the result of heavy,

  12. Simulating feedbacks in land use and land cover change models

    NARCIS (Netherlands)

    Verburg, P.H.

    2006-01-01

    In spite of the many advances in land use and land cover change modelling over the past decade many challenges remain. One of these challenges relates to the explicit treatment of feedback mechanisms in descriptive models of the land use system. This paper argues for model-based analysis to explore

  13. A two-phase copula entropy-based multiobjective optimization approach to hydrometeorological gauge network design

    Science.gov (United States)

    Xu, Pengcheng; Wang, Dong; Singh, Vijay P.; Wang, Yuankun; Wu, Jichun; Wang, Lachun; Zou, Xinqing; Chen, Yuanfang; Chen, Xi; Liu, Jiufu; Zou, Ying; He, Ruimin

    2017-12-01

    Hydrometeorological data are needed for obtaining point and areal mean, quantifying the spatial variability of hydrometeorological variables, and calibration and verification of hydrometeorological models. Hydrometeorological networks are utilized to collect such data. Since data collection is expensive, it is essential to design an optimal network based on the minimal number of hydrometeorological stations in order to reduce costs. This study proposes a two-phase copula entropy- based multiobjective optimization approach that includes: (1) copula entropy-based directional information transfer (CDIT) for clustering the potential hydrometeorological gauges into several groups, and (2) multiobjective method for selecting the optimal combination of gauges for regionalized groups. Although entropy theory has been employed for network design before, the joint histogram method used for mutual information estimation has several limitations. The copula entropy-based mutual information (MI) estimation method is shown to be more effective for quantifying the uncertainty of redundant information than the joint histogram (JH) method. The effectiveness of this approach is verified by applying to one type of hydrometeorological gauge network, with the use of three model evaluation measures, including Nash-Sutcliffe Coefficient (NSC), arithmetic mean of the negative copula entropy (MNCE), and MNCE/NSC. Results indicate that the two-phase copula entropy-based multiobjective technique is capable of evaluating the performance of regional hydrometeorological networks and can enable decision makers to develop strategies for water resources management.

  14. Hydrological land surface modelling

    DEFF Research Database (Denmark)

    Ridler, Marc-Etienne Francois

    and disaster management. The objective of this study is to develop and investigate methods to reduce hydrological model uncertainty by using supplementary data sources. The data is used either for model calibration or for model updating using data assimilation. Satellite estimates of soil moisture and surface...

  15. Hydrological land surface modelling

    DEFF Research Database (Denmark)

    Ridler, Marc-Etienne Francois

    Recent advances in integrated hydrological and soil-vegetation-atmosphere transfer (SVAT) modelling have led to improved water resource management practices, greater crop production, and better flood forecasting systems. However, uncertainty is inherent in all numerical models ultimately leading...... and disaster management. The objective of this study is to develop and investigate methods to reduce hydrological model uncertainty by using supplementary data sources. The data is used either for model calibration or for model updating using data assimilation. Satellite estimates of soil moisture and surface...... hydrological and tested by assimilating synthetic hydraulic head observations in a catchment in Denmark. Assimilation led to a substantial reduction of model prediction error, and better model forecasts. Also, a new assimilation scheme is developed to downscale and bias-correct coarse satellite derived soil...

  16. OPAL Land Condition Model

    Science.gov (United States)

    2014-08-01

    CENTURY is a computer model of plant-soil ecosystems that simulates the dynamics of grasslands, forest , crops, and savannas with a focus on nutri...Kamnalrut, and J. L. Kinyamario. 1993. Observations and modeling of biomass and soil organic matter dynamics for the grassland biome worldwide. Global

  17. Lunar Landing Operational Risk Model

    Science.gov (United States)

    Mattenberger, Chris; Putney, Blake; Rust, Randy; Derkowski, Brian

    2010-01-01

    Characterizing the risk of spacecraft goes beyond simply modeling equipment reliability. Some portions of the mission require complex interactions between system elements that can lead to failure without an actual hardware fault. Landing risk is currently the least characterized aspect of the Altair lunar lander and appears to result from complex temporal interactions between pilot, sensors, surface characteristics and vehicle capabilities rather than hardware failures. The Lunar Landing Operational Risk Model (LLORM) seeks to provide rapid and flexible quantitative insight into the risks driving the landing event and to gauge sensitivities of the vehicle to changes in system configuration and mission operations. The LLORM takes a Monte Carlo based approach to estimate the operational risk of the Lunar Landing Event and calculates estimates of the risk of Loss of Mission (LOM) - Abort Required and is Successful, Loss of Crew (LOC) - Vehicle Crashes or Cannot Reach Orbit, and Success. The LLORM is meant to be used during the conceptual design phase to inform decision makers transparently of the reliability impacts of design decisions, to identify areas of the design which may require additional robustness, and to aid in the development and flow-down of requirements.

  18. Multifractal Conceptualisation of Hydro-Meteorological Extremes

    Science.gov (United States)

    Tchiguirinskaia, I.; Schertzer, D.; Lovejoy, S.

    2009-04-01

    Hydrology and more generally sciences involved in water resources management, technological or operational developments face a fundamental difficulty: the extreme variability of hydro-meteorological fields. It clearly appears today that this variability is a function of the observation scale and yield hydro-meteorological hazards. Throughout the world, the development of multifractal theory offers new techniques for handling such non-classical variability over wide ranges of time and space scales. The resulting stochastic simulations with a very limited number of parameters well reproduce the long range dependencies and the clustering of rainfall extremes often yielding fat tailed (i.e., an algebraic type) probability distributions. The goal of this work was to investigate the ability of using very short or incomplete data records for reliable statistical predictions of the extremes. In particular we discuss how to evaluate the uncertainty in the empirical or semi-analytical multifractal outcomes. We consider three main aspects of the evaluation, such as the scaling adequacy, the multifractal parameter estimation error and the quantile estimation error. We first use the multiplicative cascade model to generate long series of multifractal data. The simulated samples had to cover the range of the universal multifractal parameters widely available in the scientific literature for the rainfall and river discharges. Using these long multifractal series and their sub-samples, we defined a metric for parameter estimation error. Then using the sets of estimated parameters, we obtained the quantile values for a range of excedance probabilities from 5% to 0.01%. Plotting the error bars on a quantile plot enable an approximation of confidence intervals that would be particularly important for the predictions of multifractal extremes. We finally illustrate the efficiency of such concept on its application to a large database (more than 16000 selected stations over USA and

  19. System-level Auditing of Hydrometeorological Vulnerabilities in the SE US

    Science.gov (United States)

    Barros, A. P.; Brun, J.; Tao, J.; Wilson, A. M.; Jeuland, M. A.

    2011-12-01

    We approach hydrometeorological extremes not as isolated events, but rather in the context of hydroclimatic regimes of SE landscapes, and examine current and future vulnerabilities of freshwater resources and landscapes (land-cover and geophysical hazards) conditional on climate. In particular, we revisit the notion of 'hydrometeorological extremes" from the perspective of runway consequences, tipping points, and environmental resiliency. Results from recent research toward quantifying the relationship between precipitation climatology and basin-scale water budgets and landscape eco-hydrological resiliency in the SE US are presented. Emphasis is placed on the complementary roles of hurricane and tropical storms on the one hand, and light rainfall on the other. The research suggests that vulnerabilities of water systems (natural and man-made) are dynamical, and therefore effective adaptation in a changing climate requires system-level assessments and decision-making. Sustainability of adaptation strategies further requires consideration of coupled human-natural systems. A framework for vulnerability assessment of rapidly urbanizing environments integrating physical, economic and interactive governance models is proposed.

  20. DRIHM: Distributed Research Infrastructure for HydroMeteorology

    Science.gov (United States)

    Parodi, A.

    2012-04-01

    Predicting weather and climate and its impacts on the environment, including hazards such as floods and landslides, is still one of the main challenges of the 21st century with significant societal and economic implications. At the heart of this challenge lies the ability to have easy access to hydrometeorological data and models, and facilitate the collaboration between meteorologists, hydrologists, and Earth science experts for accelerated scientific advances in hydrometeorological research (HMR). to face these problems the DRIHM (Distributed Research Infrastructure for Hydro-Meteorology) project intends to develop a prototype e-Science environment to facilitate this collaboration and provide end-to-end HMR services (models, datasets and post-processing tools) at the European level, with the ability to expand to global scale. The objectives of DRIHM are to lead the definition of a common long-term strategy, to foster the development of new HMR models and observational archives for the study of severe hydrometeorological events, to promote the execution and analysis of high-end simulations, and to support the dissemination of predictive models as decision analysis tools. DRIHM combines the European expertise in HMR, in Grid and High Performance Computing (HPC). Joint research activities will improve the efficient use of the European e-Infrastructures, notably Grid and HPC, for HMR modelling and observational databases, model evaluation tool sets and access to HMR model results. Networking activities will disseminate DRIHM results at the European and global levels in order to increase the cohesion of European and possibly worldwide HMR communities and increase the awareness of ICT potential for HMR. Service activities will deploy the end-to-end DRIHM services and tools in support of HMR networks and virtual organizations on top of the existing European e-Infrastructures.

  1. Central Asian Snow Cover from Hydrometeorological Surveys

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Central Asian Snow Cover from Hydrometeorological Surveys data are based on observations made by personnel for three river basins: Amu Darya, Sir Darya, and...

  2. Trans-African Hydro-Meteorological Observatory

    Science.gov (United States)

    van de Giesen, N.; Andreini, M.; Selker, J.

    2009-04-01

    Our computing capacity to model hydrological processes is such that we can readily model every hectare of the globe's surface in real time. Satellites provide us with important state observations that allow us to calibrate our models and estimate model errors. Still, ground observations will remain necessary to obtain data that can not readily be observed from space. Hydro-Meteorological data availability is particularly scarce in Africa. This presentation launches a simple idea by which Africa can leapfrog into a new era of closely knit environmental observation networks. The basic idea is the design of a robust measurement station, based on the smart use of new sensors without moving parts. For example, instead of using a Eu 5000 long-wave pyrgeometer, a factory calibrated IR microwave oven sensor is used that costs less than Eu 10. In total, each station should cost Eu 200 or less. Every 30 km, one station will be installed, being equivalent to 20,000 stations for all of sub-Saharan Africa. The roll-out will follow the XO project ("100 computer") and focus on high schools. The stations will be accompanied by an educational package that allows high school children to learn about their environment, measurements, electronics, and mathematical modeling. Total program costs lie around MEu 18.

  3. DRIHM: Distributed Research Infrastructure for Hydro-Meteorology

    Science.gov (United States)

    Parodi, A.; Rebora, N.; Kranzlmueller, D.; Schiffers, M.; Clematis, A.; Tafferner, A.; Garrote, L. M.; Llasat Botija, M.; Caumont, O.; Richard, E.; Cros, P.; Dimitrijevic, V.; Jagers, B.; Harpham, Q.; Hooper, R. P.

    2012-12-01

    Hydro-Meteorology Research (HMR) is an area of critical scientific importance and of high societal relevance. It plays a key role in guiding predictions relevant to the safety and prosperity of humans and ecosystems from highly urbanized areas, to coastal zones, and to agricultural landscapes. Of special interest and urgency within HMR is the problem of understanding and predicting the impacts of severe hydro-meteorological events, such as flash-floods and landslides in complex orography areas, on humans and the environment, under the incoming climate change effects. At the heart of this challenge lies the ability to have easy access to hydrometeorological data and models, and facilitate the collaboration between meteorologists, hydrologists, and Earth science experts for accelerated scientific advances in this field. To face these problems the DRIHM (Distributed Research Infrastructure for Hydro-Meteorology) project is developing a prototype e-Science environment to facilitate this collaboration and provide end-to-end HMR services (models, datasets and post-processing tools) at the European level, with the ability to expand to global scale (e.g. cooperation with Earth Cube related initiatives). The objectives of DRIHM are to lead the definition of a common long-term strategy, to foster the development of new HMR models and observational archives for the study of severe hydrometeorological events, to promote the execution and analysis of high-end simulations, and to support the dissemination of predictive models as decision analysis tools. DRIHM combines the European expertise in HMR, in Grid and High Performance Computing (HPC). Joint research activities will improve the efficient use of the European e-Infrastructures, notably Grid and HPC, for HMR modelling and observational databases, model evaluation tool sets and access to HMR model results. Networking activities will disseminate DRIHM results at the European and global levels in order to increase the cohesion

  4. Studying urban land-atmospheric interactions by coupling an urban canopy model with a single column atmospheric models

    Science.gov (United States)

    Song, J.; Wang, Z.

    2013-12-01

    Studying urban land-atmospheric interactions by coupling an urban canopy model with a single column atmospheric models Jiyun Song and Zhi-Hua Wang School of Sustainable Engineering and the Built Environment, Arizona State University, PO Box 875306, Tempe, AZ 85287-5306 Landuse landcover changes in urban area will modify surface energy budgets, turbulent fluxes as well as dynamic and thermodynamic structures of the overlying atmospheric boundary layer (ABL). In order to study urban land-atmospheric interactions, we coupled a single column atmospheric model (SCM) to a cutting-edge single layer urban canopy model (SLUCM). Modification of surface parameters such as the fraction of vegetation and engineered pavements, thermal properties of building and pavement materials, and geometrical features of street canyon, etc. in SLUCM dictates the evolution of surface balance of energy, water and momentum. The land surface states then provide lower boundary conditions to the overlying atmosphere, which in turn modulates the modification of ABL structure as well as vertical profiles of temperature, humidity, wind speed and tracer gases. The coupled SLUCM-SCM model is tested against field measurements of surface layer fluxes as well as profiles of temperature and humidity in the mixed layer under convective conditions. After model test, SLUCM-SCM is used to simulate the effect of changing urban land surface conditions on the evolution of ABL structure and dynamics. Simulation results show that despite the prescribed atmospheric forcing, land surface states impose significant impact on the physics of the overlying vertical atmospheric layer. Overall, this numerical framework provides a useful standalone modeling tool to assess the impacts of urban land surface conditions on the local hydrometeorology through land-atmospheric interactions. It also has potentially far-reaching implications to urban ecohydrological services for cities under future expansion and climate challenges.

  5. The effect of background hydrometeorological conditions on the sensitivity of evapotranspiration to model parameters: analysis with measurements from an Italian alpine catchment

    Directory of Open Access Journals (Sweden)

    N. Montaldo

    2003-01-01

    Full Text Available Recent developments have made land-surface models (LSMs more complex through the inclusion of more processes and controlling variables, increasing numbers of parameters and uncertainty in their estimates. To overcome these uncertainties, prior to applying a distributed LSM over the whole Toce basin (Italian Alps, a field campaign was carried out at an experimental plot within the basin before exploring the skill and parameter importance (sensitivity using the TOPLATS model, an existing LSM. In the summer and autumn of 1999, which included both wet (atmosphere controlled and dry (soil controlled periods, actual evapotranspiration estimates were performed using Bowen ratio and, for a short period, eddy correlation methods. Measurements performed with the two methods are in good agreement. The calibrated LSM predicts actual evapotranspiration quite well over the whole observation period. A sensitivity analysis of the evapotranspiration to model parameters was performed through the global multivariate technique during both wet and dry periods of the campaign. This approach studies the influence of each parameter without conditioning on certain values of the other variables. Hence, all parameters are varied simultaneously using, for instance, a uniform sampling strategy through a Monte Carlo simulation framework. The evapotranspiration is highly sensitive to the soil parameters, especially during wet periods. However, the evapotranspiration is also sensitive to some vegetation parameters and, during dry periods, wilting point is the most critical for evapotranspiration predictions. This result confirms the importance of correct representation of vegetation properties which, in water-limited conditions, control evapotranspiration. Keywords: evapotranspiration, sensitivity analysis, land surface model, eddy correlation, Alpine basin

  6. Analysis of surface and root-zone soil moisture dynamics with ERS scatterometer and the hydrometeorological model SAFRAN-ISBA-MODCOU at Grand Morin watershed (France

    Directory of Open Access Journals (Sweden)

    T. Paris Anguela

    2008-12-01

    Full Text Available Spatial and temporal variations of soil moisture strongly affect flooding, erosion, solute transport and vegetation productivity. Its characterization, offers an avenue to improve our understanding of complex land surface-atmosphere interactions. In this paper, soil moisture dynamics at soil surface (first centimeters and root-zone (up to 1.5 m depth are investigated at three spatial scales: local scale (field measurements, 8×8 km2 (hydrological model and 25×25 km2 scale (ERS scatterometer in a French watershed. This study points out the quality of surface and root-zone soil moisture data for SIM model and ERS scatterometer for a three year period. Surface soil moisture is highly variable because is more influenced by atmospheric conditions (rain, wind and solar radiation, and presents RMSE up to 0.08 m3 m−3. On the other hand, root-zone moisture presents lower variability with small RMSE (between 0.02 and 0.06 m3 m−3. These results will contribute to satellite and model verification of moisture, but also to better application of radar data for data assimilation in future.

  7. Modeling agriculture in the Community Land Model

    Directory of Open Access Journals (Sweden)

    B. Drewniak

    2013-04-01

    Full Text Available The potential impact of climate change on agriculture is uncertain. In addition, agriculture could influence above- and below-ground carbon storage. Development of models that represent agriculture is necessary to address these impacts. We have developed an approach to integrate agriculture representations for three crop types – maize, soybean, and spring wheat – into the coupled carbon–nitrogen version of the Community Land Model (CLM, to help address these questions. Here we present the new model, CLM-Crop, validated against observations from two AmeriFlux sites in the United States, planted with maize and soybean. Seasonal carbon fluxes compared well with field measurements for soybean, but not as well for maize. CLM-Crop yields were comparable with observations in countries such as the United States, Argentina, and China, although the generality of the crop model and its lack of technology and irrigation made direct comparison difficult. CLM-Crop was compared against the standard CLM3.5, which simulates crops as grass. The comparison showed improvement in gross primary productivity in regions where crops are the dominant vegetation cover. Crop yields and productivity were negatively correlated with temperature and positively correlated with precipitation, in agreement with other modeling studies. In case studies with the new crop model looking at impacts of residue management and planting date on crop yield, we found that increased residue returned to the litter pool increased crop yield, while reduced residue returns resulted in yield decreases. Using climate controls to signal planting date caused different responses in different crops. Maize and soybean had opposite reactions: when low temperature threshold resulted in early planting, maize responded with a loss of yield, but soybean yields increased. Our improvements in CLM demonstrate a new capability in the model – simulating agriculture in a realistic way, complete with

  8. Land-use change arising from rural land exchange : an agent-based simulation model

    NARCIS (Netherlands)

    Bakker, Martha M.; Alam, Shah Jamal; van Dijk, Jerry; Rounsevell, Mark D. A.

    Land exchange can be a major factor driving land-use change in regions with high pressure on land, but is generally not incorporated in land-use change models. Here we present an agent-based model to simulate land-use change arising from land exchange between multiple agent types representing

  9. Land-use change arising from rural land exchange: an agent-based simulation model

    NARCIS (Netherlands)

    Bakker, M.M.; Alam, S.J.; Dijk, van J.; Rounsevell, M.D.A.

    2015-01-01

    Land exchange can be a major factor driving land-use change in regions with high pressure on land, but is generally not incorporated in land-use change models. Here we present an agent-based model to simulate land-use change arising from land exchange between multiple agent types representing

  10. The Land Administration Domain Model

    NARCIS (Netherlands)

    Lemmen, C.; Van Oosterom, P.J.M.; Bennett, R.

    2015-01-01

    Societal drivers including poverty eradication, gender equality, indigenous recognition, adequate housing, sustainable agriculture, food security, climate change response, and good governance, influence contemporary land administration design. Equally, the opportunities provided by technological

  11. Assessing Morphological Changes due to Hydrometeorologic Influences in Mehendiganj Island, Meghna Estuary, Bangladesh

    Science.gov (United States)

    Hossain, A.; Ahmed, K. M.; Overeem, I.; Rogers, K. G.

    2014-12-01

    The Ganges-Brahmaputra-Meghna river system is the largest river system in the world with massive discharge rates and sediment loads (annually over one billion tons). Sediment from these rivers has formed one of the largest and most densely populated deltas in the world. The combined rivers discharge through the Meghna estuary into the Bay of Bengal. The study area, Mehendiganj Island, is located in the morphologically dynamic Meghna estuary region of the delta and is characterized by rapid accretion and erosion. The net effect of erosion-accretion processes between the years 1987-2012 was analyzed using Landsat satellite imagery. Time-lapse series were generated over consecutive monsoon periods to estimate net erosion, and reveal that morphological changes are influenced by hydrological conditions (e.g. areal extent of flooding surface, hydrometeorology) driven by high river and sediment discharge, mainly during the seasonal monsoon (wet) period. The hydrological conditions and, consequently, the morphological changes exhibit a skewed pattern in annual distribution on account of high-energy condition prevailing during the monsoon. Total erosion and accretion within the study area was estimated to be about 5997 hectares and 2922 hectares, respectively. The measured annual erosion rates were as high as 1493 hectares, which were about 15% of the existing land surface within the study area. Discharge rates and sediment loads over the course of the study period were calculated using a numerical model (WBMsed) and was validated by comparisons with field-measured values. Moreover, hydrological parameters were analyzed in the context of statistical hydrology in order to obtain trends and were correlated with annual accretion and erosion rates attained from the satellite image analysis. Anomalies in the patterns of annual accretion and erosion rates were detected during extreme hydrometeorological events such as high floodwater years and cyclones. The morphological changes

  12. A Land System representation for global assessments and land-use modeling

    NARCIS (Netherlands)

    van Asselen, S.; Verburg, P.H.

    2012-01-01

    Current global scale land-change models used for integrated assessments and climate modeling are based on classifications of land cover. However, land-use management intensity and livestock keeping are also important aspects of land use, and are an integrated part of land systems. This article aims

  13. A framework for benchmarking land models

    Directory of Open Access Journals (Sweden)

    Y. Q. Luo

    2012-10-01

    Full Text Available Land models, which have been developed by the modeling community in the past few decades to predict future states of ecosystems and climate, have to be critically evaluated for their performance skills of simulating ecosystem responses and feedback to climate change. Benchmarking is an emerging procedure to measure performance of models against a set of defined standards. This paper proposes a benchmarking framework for evaluation of land model performances and, meanwhile, highlights major challenges at this infant stage of benchmark analysis. The framework includes (1 targeted aspects of model performance to be evaluated, (2 a set of benchmarks as defined references to test model performance, (3 metrics to measure and compare performance skills among models so as to identify model strengths and deficiencies, and (4 model improvement. Land models are required to simulate exchange of water, energy, carbon and sometimes other trace gases between the atmosphere and land surface, and should be evaluated for their simulations of biophysical processes, biogeochemical cycles, and vegetation dynamics in response to climate change across broad temporal and spatial scales. Thus, one major challenge is to select and define a limited number of benchmarks to effectively evaluate land model performance. The second challenge is to develop metrics of measuring mismatches between models and benchmarks. The metrics may include (1 a priori thresholds of acceptable model performance and (2 a scoring system to combine data–model mismatches for various processes at different temporal and spatial scales. The benchmark analyses should identify clues of weak model performance to guide future development, thus enabling improved predictions of future states of ecosystems and climate. The near-future research effort should be on development of a set of widely acceptable benchmarks that can be used to objectively, effectively, and reliably evaluate fundamental properties

  14. Hydrocentric view of Agro-ecosystem Resiliency to Extreme Hydrometeorological and Climate Events in the High Plains, US.

    Science.gov (United States)

    Munoz-Arriola, Francisco; Sharma, Ashutosh; Werner, Katherine; Chacon, Juan-Carlos; Corzo, Gerald; Goyal, Manish-Kumar

    2017-04-01

    An increasing incidence of Hydrometeorological and Climate Extreme Events (EHCEs) is challenging food, water, and ecosystem services security at local to global contexts. This study aims to understand how a large-scale representation of agroecosystems and ecosystems respond to EHCE in the Northern Highplains, US. To track such responses the Variable Infiltration Capacity model (VIC) Land Surface Hydrology model was used and two experiments were implemented. The first experiment uses the LAI MODIS15A2 product to capture dynamic responses of vegetation with a time span from 2000 to 2013. The second experiment used a climatological fixed seasonal cycle calculated as the average from the 2000-2013 dynamic MODIS15A2 product to isolate vegetation from soil physical responses. Based on the analyses of multiple hydrological variables and state variables and high-level organization of agroecosystems and ecosystems, we evidence how the influence of droughts and anomalously wet conditions affect hydrological resilience at large scale.

  15. Comparing One-Way and Two-Way Coupled Hydrometeorological Forecasting Systems for Flood Forecasting in the Mediterranean Region

    Directory of Open Access Journals (Sweden)

    Amir Givati

    2016-05-01

    Full Text Available A pair of hydro-meteorological modeling systems were calibrated and evaluated for the Ayalon basin in central Israel to assess the advantages and limitations of one-way versus two-way coupled modeling systems for flood prediction. The models used included the Hydrological Engineering Center-Hydrological Modeling System (HEC-HMS model and the Weather Research and Forecasting (WRF Hydro modeling system. The models were forced by observed, interpolated precipitation from rain-gauges within the basin, and with modeled precipitation from the WRF atmospheric model. Detailed calibration and evaluation was carried out for two major winter storms in January and December 2013. Then, both modeling systems were executed and evaluated in an operational mode for the full 2014/2015 rainy season. Outputs from these simulations were compared to observed measurements from the hydrometric station at the Ayalon basin outlet. Various statistical metrics were employed to quantify and analyze the results: correlation, Root Mean Square Error (RMSE and the Nash–Sutcliffe (NS efficiency coefficient. Foremost, the results presented in this study highlight the sensitivity of hydrological responses to different sources of simulated and observed precipitation data, and demonstrate improvement, although not significant, at the Hydrological response, like simulated hydrographs. With observed precipitation data both calibrated models closely simulated the observed hydrographs. The two-way coupled WRF/WRF-Hydro modeling system produced improved both the precipitation and hydrological simulations as compared to the one-way WRF simulations. Findings from this study, as well as previous studies, suggest that the use of two-way atmospheric-hydrological coupling has the potential to improve precipitation and, therefore, hydrological forecasts for early flood warning applications. However, more research needed in order to better understand the land-atmosphere coupling mechanisms

  16. Land-surface modelling in hydrological perspective

    DEFF Research Database (Denmark)

    Overgaard, Jesper; Rosbjerg, Dan; Butts, M.B.

    2006-01-01

    The purpose of this paper is to provide a review of the different types of energy-based land-surface models (LSMs) and discuss some of the new possibilities that will arise when energy-based LSMs are combined with distributed hydrological modelling. We choose to focus on energy-based approaches......, because in comparison to the traditional potential evapotranspiration models, these approaches allow for a stronger link to remote sensing and atmospheric modelling. New opportunities for evaluation of distributed land-surface models through application of remote sensing are discussed in detail...

  17. Modelling the effect of land use change on hydrological model ...

    African Journals Online (AJOL)

    Conceptual rainfall–runoff models have become a basic tool for evaluating effects of land use/cover changes on the hydrologic processes in small-scale as well as large watersheds. The runoff-producing mechanism is influenced by land use/cover changes. In this study, we analysed the effect of land use change on ...

  18. Land use change modelling: current practice and research priorities

    NARCIS (Netherlands)

    Verburg, P.H.; Schot, P.; Dijst, M.J.; Veldkamp, A.

    2004-01-01

    Land use change models are tools to support the analysis of the causes and consequences of land use dynamics. Scenario analysis with land use models can support land use planning and policy. Numerous land use models are available, developed from different disciplinary backgrounds. This paper reviews

  19. The diagnosis and forecast system of hydrometeorological characteristics for the White, Barents, Kara and Pechora Seas

    Science.gov (United States)

    Fomin, Vladimir; Diansky, Nikolay; Gusev, Anatoly; Kabatchenko, Ilia; Panasenkova, Irina

    2017-04-01

    The diagnosis and forecast system for simulating hydrometeorological characteristics of the Russian Western Arctic seas is presented. It performs atmospheric forcing computation with the regional non-hydrostatic atmosphere model Weather Research and Forecasting model (WRF) with spatial resolution 15 km, as well as computation of circulation, sea level, temperature, salinity and sea ice with the marine circulation model INMOM (Institute of Numerical Mathematics Ocean Model) with spatial resolution 2.7 km, and the computation of wind wave parameters using the Russian wind-wave model (RWWM) with spatial resolution 5 km. Verification of the meteorological characteristics is done for air temperature, air pressure, wind velocity, water temperature, currents, sea level anomaly, wave characteristics such as wave height and wave period. The results of the hydrometeorological characteristic verification are presented for both retrospective and forecast computations. The retrospective simulation of the hydrometeorological characteristics for the White, Barents, Kara and Pechora Seas was performed with the diagnosis and forecast system for the period 1986-2015. The important features of the Kara Sea circulation are presented. Water exchange between Pechora and Kara Seas is described. The importance is shown of using non-hydrostatic atmospheric circulation model for the atmospheric forcing computation in coastal areas. According to the computation results, extreme values of hydrometeorological characteristics were obtained for the Russian Western Arctic seas.

  20. Advances in land modeling of KIAPS based on the Noah Land Surface Model

    Science.gov (United States)

    Koo, Myung-Seo; Baek, Sunghye; Seol, Kyung-Hee; Cho, Kyoungmi

    2017-08-01

    As of 2013, the Noah Land Surface Model (LSM) version 2.7.1 was implemented in a new global model being developed at the Korea Institute of Atmospheric Prediction Systems (KIAPS). This land surface scheme is further refined in two aspects, by adding new physical processes and by updating surface input parameters. Thus, the treatment of glacier land, sea ice, and snow cover are addressed more realistically. Inconsistencies in the amount of absorbed solar flux at ground level by the land surface and radiative processes are rectified. In addition, new parameters are available by using 1-km land cover data, which had usually not been possible at a global scale. Land surface albedo/emissivity climatology is newly created using Moderate-Resolution Imaging Spectroradiometer (MODIS) satellitebased data and adjusted parameterization. These updates have been applied to the KIAPS-developed model and generally provide a positive impact on near-surface weather forecasting.

  1. Land-use change arising from rural land exchange: an agent-based simulation model

    OpenAIRE

    Martha M. Bakker; Alam, Shah Jamal; van Dijk, Jerry; Rounsevell, Mark D A

    2015-01-01

    Land exchange can be a major factor driving land-use change in regions with high pressure on land, but is generally not incorporated in land-use change models. Here we present an agent-based model to simulate land-use change arising from land exchange between multiple agent types representing farmers, nature organizations, and estate owners. The RULEX model (Rural Land EXchange) was calibrated and applied to a 300 km(2) case study area in the east of the Netherlands. Decision rules about whic...

  2. OPAL Netlogo Land Condition Model

    Science.gov (United States)

    2014-08-15

    model of plant-soil ecosystems that simulates the dynamics of grasslands, forest , crops, and savannas with a focus on nutrient (carbon, nitrogen... forest , tall grass and short grass) and one specific training region (central corridor) of the in- stallation. Distance to paved roads and all roads...dynamics for the grassland biome worldwide. Global Biogeochemical Cycles 7:785–809. Polley, H. W., and J. K. Detling. 1989. Defoliation, nitrogen, and

  3. Modeling Historical Land Cover and Land Use: A Review fromContemporary Modeling

    Directory of Open Access Journals (Sweden)

    Laura Alfonsina Chang-Martínez

    2015-09-01

    Full Text Available Spatially-explicit land cover land use change (LCLUC models are becoming increasingly useful tools for historians and archaeologists. Such kinds of models have been developed and used by geographers, ecologists and land managers over the last few decades to carry out prospective scenarios. In this paper, we review historical models to compare them with prospective models, with the assumption that the ample experience gained in the development of models of prospective simulation can benefit the development of models having as their objective the simulation of changes that happened in the past. The review is divided into three sections: in the first section, we explain the functioning of contemporary LCLUC models; in the second section, we analyze historical LCLUC models; in the third section, we compare the former two types of models, and finally, we discuss the contributions to historical LCLUC models of contemporary LCLUC models.

  4. Spatial autocorrelation in multiscale land use models

    NARCIS (Netherlands)

    Overmars, K.P.; Koning, de G.H.J.; Veldkamp, A.

    2003-01-01

    Various modelling approaches exist for the simulation and exploration of land use change. Until recently often ordinary statistics were used in studies dealing with spatial data, although several techniques are available to deal with spatial autocorrelation. This article presents the spatial

  5. ISO 19512 : The land administration domain model

    NARCIS (Netherlands)

    Lemmen, C.H.J.; Van Oosterom, P.J.M.

    2011-01-01

    Focus of this paper is on the Land Administration Domain Model which is under development as an International Standard at ISO. This development is an initiative of the International Federation of Surveyors – FIG. The International Standard is expected to be published in 2012. Why is this development

  6. Application of the Artificial Neural Network model for prediction of monthly Standardized Precipitation and Evapotranspiration Index using hydrometeorological parameters and climate indices in eastern Australia

    Science.gov (United States)

    Deo, Ravinesh C.; Şahin, Mehmet

    2015-07-01

    The forecasting of drought based on cumulative influence of rainfall, temperature and evaporation is greatly beneficial for mitigating adverse consequences on water-sensitive sectors such as agriculture, ecosystems, wildlife, tourism, recreation, crop health and hydrologic engineering. Predictive models of drought indices help in assessing water scarcity situations, drought identification and severity characterization. In this paper, we tested the feasibility of the Artificial Neural Network (ANN) as a data-driven model for predicting the monthly Standardized Precipitation and Evapotranspiration Index (SPEI) for eight candidate stations in eastern Australia using predictive variable data from 1915 to 2005 (training) and simulated data for the period 2006-2012. The predictive variables were: monthly rainfall totals, mean temperature, minimum temperature, maximum temperature and evapotranspiration, which were supplemented by large-scale climate indices (Southern Oscillation Index, Pacific Decadal Oscillation, Southern Annular Mode and Indian Ocean Dipole) and the Sea Surface Temperatures (Nino 3.0, 3.4 and 4.0). A total of 30 ANN models were developed with 3-layer ANN networks. To determine the best combination of learning algorithms, hidden transfer and output functions of the optimum model, the Levenberg-Marquardt and Broyden-Fletcher-Goldfarb-Shanno (BFGS) quasi-Newton backpropagation algorithms were utilized to train the network, tangent and logarithmic sigmoid equations used as the activation functions and the linear, logarithmic and tangent sigmoid equations used as the output function. The best ANN architecture had 18 input neurons, 43 hidden neurons and 1 output neuron, trained using the Levenberg-Marquardt learning algorithm using tangent sigmoid equation as the activation and output functions. An evaluation of the model performance based on statistical rules yielded time-averaged Coefficient of Determination, Root Mean Squared Error and the Mean Absolute

  7. Modelling the effect of land use change on hydrological model ...

    African Journals Online (AJOL)

    2017-04-02

    Apr 2, 2017 ... Keywords: land use/cover change; parameter calibration; linearized; upper Huaihe River Basin ...... programming for modelling coastal algal blooms. ... prediction of reference evapotranspiration with climate change in.

  8. SET UP OF THE NEW AUTOMATIC HYDROMETEOROLOGICAL NETWORK IN HUNGARY

    Directory of Open Access Journals (Sweden)

    J. NAGy

    2013-03-01

    Full Text Available The Hungarian Meteorological Service (OMSZ and General Directorate of Water Management (OVF in Hungary run conventional precipitation measurement networks consisting of at least 1000 stations. OMSZ automated its synoptic and climatological network in 90’s and now more than 100 automatic stations give data every 1-10 minutes via GPRS channel. In 2007 the experts from both institutions determined the requirements of a common network. The predecessor in title of OVF is general Directorate for Water and Environment gave a project proposal in 2008 for establishment of a new hydrometeorological network based on common aims for meteorology and hydrology. The new hydrometeorological network was set up in 2012 financed by KEOP project. This network has got 141 weighing precipitation gauges, 118 temperature - humidity sensors and 25 soil moisture and soil temperature instruments. Near by Tisza-Lake two wind sensors have been installed. The network is operated by OMSZ and OVF together. OVF and its institutions maintain the stations itself and support the electricity. OMSZ operates data collection and transmission, maintaines and calibrates the sensors. Using precipitation data of enhanced network the radar precipitation field quality may be more precise, which are input of run-off model. Thereby the time allowance may be increased in flood-control events. Based on soil moisture and temperature water balance in soil may be modelled and forecast can be produced in different conditions. It is very important task in drought and inland water conditions. Considering OMSZ investment project in which new Doppler dual polarisation radar and 14 disdrometers will be installed, the precipitation estimation may be improved since 2015.

  9. The Land Administration Domain Model (LADM) as the reference model for the Cyprus Land Information System (CLIS)

    NARCIS (Netherlands)

    Elia, E.; Zevenbergen, J.A.; Lemmen, C.H.J.; Van Oosterom, P.J.M.

    2011-01-01

    In this paper the enhancement of the data model of the Cyprus Land Information System (CLIS), with the adoption of the Land Administration Domain Model (LADM) is examined. The Cyprus Land Information System (CLIS), was established in 1999, within the Department of Lands and Surveys (DLS), to support

  10. A domain model for land administration

    NARCIS (Netherlands)

    Lemmen, C.H.J.

    2012-01-01

    75% or the “people to land relationships” worldwide are not documented. This concerns about 4.5 billion cases. With a growing population this situation results in land disputes, land grabbing and neglecting of rights of local people. Land Administration provides documentation on people to land

  11. Investigating hydrometeorological impacts of perennial bioenergy crops under realistic scenario expansions

    Science.gov (United States)

    Wagner, M.; Wang, M.; Miguez-Macho, G.; Miller, J. N.; Bagley, J. E.; Bernacchi, C.; Georgescu, M.

    2016-12-01

    Perennial bioenergy crops, such as switchgrass and miscanthus, have been posed as a more sustainable energy pathway relative to annual bioenergy crops due to their reduced carbon footprint and ability to grow on abandoned and degraded land, thereby, avoiding competition with food crops. Previous studies that replaced annual bioenergy crops with perennial crops noted regional cooling associated with enhanced ET due to their deeper rooting systems extracting deeper soil moisture. This study provides a more realistic assessment by (1) analyzing perennial bioenergy expansion only in suitable abandoned and degraded farmlands, and (2) using field scale measurements of albedo in conjunction with known vegetation fraction and leaf area index (LAI) values. High-resolution (2 km grid spacing) simulations were performed using a state-of-the-art atmospheric model (Weather Research and Forecasting system) dynamically coupled to a land surface model system over the Southern Plains of the U.S., during a normal precipitation year (2007) and a drought year (2011). Our results show that perennial bioenergy crop expansion leads to regional cooling (1-2 oC), that is driven primarily by enhanced reflection of shortwave radiation, and secondarily, by enhanced ET. Perennial bioenergy crop expansion was also shown to mitigate drought impacts through moistening and cooling of the near-surface environment. These impacts, however, were reduced during the drought year as a result of differential environmental conditions, when compared to those of the normal cimate year. This study serves as a major step towards assessing the sustainability of perennial bioenergy crop expansion under diverse hydrometeorological conditions by highlighting the driving mechanisms and processes associated with this energy pathway.

  12. Land administration domain model is an ISO standard now

    NARCIS (Netherlands)

    Lemmen, C.H.J.; Van Oosterom, P.J.M.; Uitermark, H.T.; De Zeeuw, K.

    2013-01-01

    A group of land administration professionals initiated the development of a data model that facilitates the quick and efficient set-up of land registrations. Just like social issues benefit from proper land administration, land administration systems themselves benefit from proper data standards. In

  13. Land surface modeling in convection permitting simulations

    Science.gov (United States)

    van Heerwaarden, Chiel; Benedict, Imme

    2017-04-01

    The next generation of weather and climate models permits convection, albeit at a grid spacing that is not sufficient to resolve all details of the clouds. Whereas much attention is being devoted to the correct simulation of convective clouds and associated precipitation, the role of the land surface has received far less interest. In our view, convective permitting simulations pose a set of problems that need to be solved before accurate weather and climate prediction is possible. The heart of the problem lies at the direct runoff and at the nonlinearity of the surface stress as a function of soil moisture. In coarse resolution simulations, where convection is not permitted, precipitation that reaches the land surface is uniformly distributed over the grid cell. Subsequently, a fraction of this precipitation is intercepted by vegetation or leaves the grid cell via direct runoff, whereas the remainder infiltrates into the soil. As soon as we move to convection permitting simulations, this precipitation falls often locally in large amounts. If the same land-surface model is used as in simulations with parameterized convection, this leads to an increase in direct runoff. Furthermore, spatially non-uniform infiltration leads to a very different surface stress, when scaled up to the course resolution of simulations without convection. Based on large-eddy simulation of realistic convection events at a large domain, this study presents a quantification of the errors made at the land surface in convection permitting simulation. It compares the magnitude of the errors to those made in the convection itself due to the coarse resolution of the simulation. We find that, convection permitting simulations have less evaporation than simulations with parameterized convection, resulting in a non-realistic drying of the atmosphere. We present solutions to resolve this problem.

  14. Large-scale Agroecosytem's Resiliency to Extreme Hydrometeorological and Climate Extreme Events in the Missouri River Basin

    Science.gov (United States)

    Munoz-Arriola, F.; Smith, K.; Corzo, G.; Chacon, J.; Carrillo-Cruz, C.

    2015-12-01

    A major challenge for water, energy and food security relies on the capability of agroecosyststems and ecosystems to adapt to a changing climate and land use changes. The interdependency of these forcings, understood through our ability to monitor and model processes across scales, indicate the "depth" of their impact on agroecosystems and ecosystems, and consequently our ability to predict the system's ability to return to a "normal" state. We are particularly interested in explore two questions: (1) how hydrometeorological and climate extreme events (HCEs) affect sub-seasonal to interannual changes in evapotranspiration and soil moisture? And (2) how agroecosystems recover from the effect of such events. To address those questions we use the land surface hydrologic Variable Infiltration Capacity (VIC) model and the Moderate Resolution Imaging Spectrometer-Leaf Area Index (MODIS-LAI) over two time spans (1950-2013 using a seasonal fixed LAI cycle) and 2001-2013 (an 8-day MODIS-LAI). VIC is forced by daily/16th degree resolution precipitation, minimum and maximum temperature, and wind speed. In this large-scale experiment, resiliency is defined by the capacity of a particular agroecosystem, represented by a grid cell's ET, SM, and LAI to return to a historical average. This broad, yet simplistic definition will contribute to identify the possible components and their scales involved in agroecosystems and ecosystems capacity to adapt to the incidence of HCEs and technologies used to intensify agriculture and diversify their use for food and energy production. Preliminary results show that dynamical changes in land use, tracked by MODIS data, require larger time spans to address properly the influence of technologic improvements in crop production as well as the competition for land for biofuel vs. food production. On the other hand, fixed seasonal changes in land use allow us just to identify hydrologic changes mainly due to climate variability.

  15. Multilevel and multiscale drought reanalysis over France with the Safran-Isba-Modcou hydrometeorological suite

    Directory of Open Access Journals (Sweden)

    J.-P. Vidal

    2010-03-01

    Full Text Available Physically-based droughts can be defined as a water deficit in at least one component of the land surface hydrological cycle. The reliance of different activity domains (water supply, irrigation, hydropower, etc. on specific components of this cycle requires drought monitoring to be based on indices related to meteorological, agricultural, and hydrological droughts. This paper describes a high-resolution retrospective analysis of such droughts in France over the last fifty years, based on the Safran-Isba-Modcou (SIM hydrometeorological suite. The high-resolution 1958–2008 Safran atmospheric reanalysis was used to force the Isba land surface scheme and the hydrogeological model Modcou. Meteorological droughts are characterized with the Standardized Precipitation Index (SPI at time scales varying from 1 to 24 months. Similar standardizing methods were applied to soil moisture and streamflow for identifying multiscale agricultural droughts – through the Standardized Soil Wetness Index (SSWI – and multiscale hydrological droughts, through the Standardized Flow Index (SFI. Based on a common threshold level for all indices, drought event statistics over the 50-yr period – number of events, duration, severity and magnitude – have been derived locally in order to highlight regional differences at multiple time scales and at multiple levels of the hydrological cycle (precipitation, soil moisture, streamflow. Results show a substantial variety of temporal drought patterns over the country that are highly dependent on both the variable and time scale considered. Independent spatio-temporal drought events have then been identified and described by combining local characteristics with the evolution of area under drought. Summary statistics have finally been used to compare past severe drought events, from multi-year precipitation deficits (1989–1990 to short hot and dry periods (2003. Results show that the ranking of drought events depends highly

  16. Modeling Land-Use Decision Behavior with Bayesian Belief Networks

    Directory of Open Access Journals (Sweden)

    Inge Aalders

    2008-06-01

    Full Text Available The ability to incorporate and manage the different drivers of land-use change in a modeling process is one of the key challenges because they are complex and are both quantitative and qualitative in nature. This paper uses Bayesian belief networks (BBN to incorporate characteristics of land managers in the modeling process and to enhance our understanding of land-use change based on the limited and disparate sources of information. One of the two models based on spatial data represented land managers in the form of a quantitative variable, the area of individual holdings, whereas the other model included qualitative data from a survey of land managers. Random samples from the spatial data provided evidence of the relationship between the different variables, which I used to develop the BBN structure. The model was tested for four different posterior probability distributions, and results showed that the trained and learned models are better at predicting land use than the uniform and random models. The inference from the model demonstrated the constraints that biophysical characteristics impose on land managers; for older land managers without heirs, there is a higher probability of the land use being arable agriculture. The results show the benefits of incorporating a more complex notion of land managers in land-use models, and of using different empirical data sources in the modeling process. Future research should focus on incorporating more complex social processes into the modeling structure, as well as incorporating spatio-temporal dynamics in a BBN.

  17. Empirical agent-based land market: Integrating adaptive economic behavior in urban land-use models

    NARCIS (Netherlands)

    Filatova, Tatiana

    2015-01-01

    This paper introduces an economic agent-based model of an urban housing market. The RHEA (Risks and Hedonics in Empirical Agent-based land market) model captures natural hazard risks and environmental amenities through hedonic analysis, facilitating empirical agent-based land market modeling. RHEA

  18. Modelling Participatory Geographic Information System for Customary Land Conflict Resolution

    Science.gov (United States)

    Gyamera, E. A.; Arko-Adjei, A.; Duncan, E. E.; Kuma, J. S. Y.

    2017-11-01

    Since land contributes to about 73 % of most countries Gross Domestic Product (GDP), attention on land rights have tremendously increased globally. Conflicts over land have therefore become part of the major problems associated with land administration. However, the conventional mechanisms for land conflict resolution do not provide satisfactory result to disputants due to various factors. This study sought to develop a Framework of using Participatory Geographic Information System (PGIS) for customary land conflict resolution. The framework was modelled using Unified Modelling Language (UML). The PGIS framework, called butterfly model, consists of three units namely, Social Unit (SU), Technical Unit (TU) and Decision Making Unit (DMU). The name butterfly model for land conflict resolution was adopted for the framework based on its features and properties. The framework has therefore been recommended to be adopted for land conflict resolution in customary areas.

  19. A Land System representation for global assessments and land-use modeling.

    Science.gov (United States)

    van Asselen, Sanneke; Verburg, Peter H

    2012-10-01

    Current global scale land-change models used for integrated assessments and climate modeling are based on classifications of land cover. However, land-use management intensity and livestock keeping are also important aspects of land use, and are an integrated part of land systems. This article aims to classify, map, and to characterize Land Systems (LS) at a global scale and analyze the spatial determinants of these systems. Besides proposing such a classification, the article tests if global assessments can be based on globally uniform allocation rules. Land cover, livestock, and agricultural intensity data are used to map LS using a hierarchical classification method. Logistic regressions are used to analyze variation in spatial determinants of LS. The analysis of the spatial determinants of LS indicates strong associations between LS and a range of socioeconomic and biophysical indicators of human-environment interactions. The set of identified spatial determinants of a LS differs among regions and scales, especially for (mosaic) cropland systems, grassland systems with livestock, and settlements. (Semi-)Natural LS have more similar spatial determinants across regions and scales. Using LS in global models is expected to result in a more accurate representation of land use capturing important aspects of land systems and land architecture: the variation in land cover and the link between land-use intensity and landscape composition. Because the set of most important spatial determinants of LS varies among regions and scales, land-change models that include the human drivers of land change are best parameterized at sub-global level, where similar biophysical, socioeconomic and cultural conditions prevail in the specific regions. © 2012 Blackwell Publishing Ltd.

  20. Tropical Montane Cloud Forests: Hydrometeorological variability in three neighbouring catchments with different forest cover

    Science.gov (United States)

    Ramírez, Beatriz H.; Teuling, Adriaan J.; Ganzeveld, Laurens; Hegger, Zita; Leemans, Rik

    2017-09-01

    Mountain areas are characterized by a large heterogeneity in hydrological and meteorological conditions. This heterogeneity is currently poorly represented by gauging networks and by the coarse scale of global and regional climate and hydrological models. Tropical Montane Cloud Forests (TMCFs) are found in a narrow elevation range and are characterized by persistent fog. Their water balance depends on local and upwind temperatures and moisture, therefore, changes in these parameters will alter TMCF hydrology. Until recently the hydrological functioning of TMCFs was mainly studied in coastal regions, while continental TMCFs were largely ignored. This study contributes to fill this gap by focusing on a TMCF which is located on the northern eastern Andes at an elevation of 1550-2300 m asl, in the Orinoco river basin highlands. In this study, we describe the spatial and seasonal meteorological variability, analyse the corresponding catchment hydrological response to different land cover, and perform a sensitivity analysis on uncertainties related to rainfall interpolation, catchment area estimation and streamflow measurements. Hydro-meteorological measurements, including hourly solar radiation, temperature, relative humidity, wind speed, precipitation, soil moisture and streamflow, were collected from June 2013 to May 2014 at three gauged neighbouring catchments with contrasting TMCF/grassland cover and less than 250 m elevation difference. We found wetter and less seasonally contrasting conditions at higher elevations, indicating a positive relation between elevation and fog or rainfall persistence. This pattern is similar to that of other eastern Andean TMCFs, however, the study site had higher wet season rainfall and lower dry season rainfall suggesting that upwind contrasts in land cover and moisture can influence the meteorological conditions at eastern Andean TMCFs. Contrasting streamflow dynamics between the studied catchments reflect the overall system response

  1. Regional Climate Modeling and Remote Sensing to Characterize Impacts of Civil War Driven Land Use Change on Regional Hydrology and Climate

    Science.gov (United States)

    Maksimowicz, M.; Masarik, M. T.; Brandt, J.; Flores, A. N.

    2016-12-01

    Land use/land cover (LULC) change directly impacts the partitioning of surface mass and energy fluxes. Regional-scale weather and climate are potentially altered by LULC if the resultant changes in partitioning of surface energy fluxes are extensive enough. Dynamics of land use, particularly those related to the social dimensions of the Earth System, are often simplified or not represented in regional land-atmosphere models. This study explores the role of LULC change on a regional hydroclimate system, focusing on potential hydroclimate changes arising from an extended civil conflict in Mozambique. Civil war from 1977-1992 in Mozambique led to land use change at a regional scale as a result of the collapse of large herbivore populations due to poaching. Since the war ended, farming has increased, poaching was curtailed, and animal populations were reintroduced. In this study LULC in a region encompassing Gorongosa is classified at three instances between 1977 to 2015 using Landsat imagery. We use these derived LULC datasets to inform lower boundary conditions in the Weather Research and Forecasting (WRF) model. To quantify potential hydrometeorological changes arising from conflict-driven land use change, we performed a factorial-like experiment by mixing input LULC maps and atmospheric forcing data from before, during, and after the civil war. Analysis of the Landsat data shows measurable land cover change from 1977-present as tree cover encroached into grasslands. Initial tests show corresponding sensitivities to different LULC schemes within the WRF model. Preliminary results suggest that the war did indeed impact regional hydroclimate in a significant way via its direct and indirect impacts on land-atmosphere interactions. Results of this study suggest that LULC change arising from regional conflicts are a potentially understudied, yet important human process to capture in both regional reanalyses and climate change projections.

  2. Performance of ensemble streamflow forecasts under varied hydrometeorological conditions

    Science.gov (United States)

    Benninga, Harm-Jan F.; Booij, Martijn J.; Romanowicz, Renata J.; Rientjes, Tom H. M.

    2017-10-01

    The paper presents a methodology that gives insight into the performance of ensemble streamflow-forecasting systems. We have developed an ensemble forecasting system for the Biała Tarnowska, a mountainous river catchment in southern Poland, and analysed the performance for lead times ranging from 1 to 10 days for low, medium and high streamflow and different hydrometeorological conditions. Precipitation and temperature forecasts from the European Centre for Medium-Range Weather Forecasts served as inputs to a deterministic lumped hydrological (HBV) model. Due to a non-homogeneous bias in time, pre- and post-processing of the meteorological and streamflow forecasts are not effective. The best forecast skill, relative to alternative forecasts based on meteorological climatology, is shown for high streamflow and snow accumulation low-streamflow events. Forecasts of medium-streamflow events and low-streamflow events under precipitation deficit conditions show less skill. To improve performance of the forecasting system for high-streamflow events, the meteorological forecasts are most important. Besides, it is recommended that the hydrological model be calibrated specifically on low-streamflow conditions and high-streamflow conditions. Further, it is recommended that the dispersion (reliability) of the ensemble streamflow forecasts is enlarged by including the uncertainties in the hydrological model parameters and the initial conditions, and by enlarging the dispersion of the meteorological input forecasts.

  3. The hydro-meteorological chain in Piemonte region, North Western Italy - analysis of the HYDROPTIMET test cases

    Directory of Open Access Journals (Sweden)

    D. Rabuffetti

    2005-01-01

    Full Text Available The HYDROPTIMET Project, Interreg IIIB EU program, is developed in the framework of the prediction and prevention of natural hazards related to severe hydro-meteorological events and aims to the optimisation of Hydro-Meteorological warning systems by the experimentation of new tools (such as numerical models to be used operationally for risk assessment. The objects of the research are the mesoscale weather phenomena and the response of watersheds with size ranging from 102 to 103 km2. Non-hydrostatic meteorological models are used to catch such phenomena at a regional level focusing on the Quantitative Precipitation Forecast (QPF. Furthermore hydrological Quantitative Discharge Forecast (QDF are performed by the simulation of run-off generation and flood propagation in the main rivers of the territory. In this way observed data and QPF are used, in a real-time configuration, for one-way forcing of the hydrological model that works operationally connected to the Piemonte Region Alert System. The main hydro-meteorological events that affected Piemonte Region in the last years are analysed, these are the HYDROPTIMET selected test cases of 14–18 November 2002 and 23–26 November 2002. The results obtained in terms of QPF and QDF offer a basis to evaluate the sensitivity of the whole hydro-meteorological chain to the uncertainties in the numerical simulations. Different configurations of non-hydrostatic meteorological models are also evaluated.

  4. Evaluation of the hydro-meteorological chain in Piemonte Region, north western Italy - analysis of two HYDROPTIMET test cases

    Directory of Open Access Journals (Sweden)

    D. Rabuffetti

    2005-01-01

    Full Text Available The HYDROPTIMET Project, Interreg IIIB EU program, is developed in the framework of the prediction and prevention of natural hazards related to severe hydro-meteorological events and aims to the optimisation of Hydro-Meteorological warning systems by the experimentation of new tools (such as numerical models to be used operationally for risk assessment. The object of the research are the Mesoscale weather phenomena and the response of watersheds with size ranging from 102 to 103 km2. Non-hydrostatic meteorological models are used to catch such phenomena at a regional level focusing on the Quantitative Precipitation Forecast (QPF. Furthermore hydrological Quantitative Discharge Forecast (QDF are performed by the simulation of run-off generation and flood propagation in the main rivers of the interested territory. In this way observed data and QPF are used, in a real-time configuration, for one-way forcing of the hydrological model that works operationally connected to the Piemonte Region Alert System. The main hydro-meteorological events that interested Piemonte Region in the last years are studied, these are the HYDROPTIMET selected test cases of 14-18 November 2002 and 23-26 November 2002. The results obtained in terms of QPF and QDF offer a sound basis to evaluate the sensitivity of the whole hydro-meteorological chain to the uncertainties in the numerical simulations. Different configurations of non-hydrostatic meteorological models are also analysed.

  5. Agent-based modeling of urban land-use change

    Science.gov (United States)

    Li, Xinyan; Li, Deren

    2005-10-01

    ABM (Agent-Based Modeling) is a newly developed method of computer simulation. It has characteristics such as active, dynamic, and operational. Urban land-use change has been a focus problem all over the world, especially for the developing countries. We try to use ABM to model the urban land-use changes. By studying the mechanism of urban land use evolvement, we put forwards the thinking of modeling. And an urban land-use change model is built primarily based on the RePast software and GIS spatial database.

  6. Advancing land change modeling: opportunities and research requirements

    National Research Council Canada - National Science Library

    Geographical Sciences Committee; Board on Earth Sciences and Resources; Division on Earth and Life Studies; National Research Council; National Research Council

    2014-01-01

    "Advancing Land Change Modeling: Opportunities and Research Requirements describes various LCM approaches, suggests guidance for their appropriate application, and makes recommendations to improve the integration of observation...

  7. Land surface spinup for episodic modeling

    Science.gov (United States)

    Angevine, W. M.; Bazile, E.; Legain, D.; Pino, D.

    2014-08-01

    Soil moisture strongly controls the surface fluxes in mesoscale numerical models, and thereby influences the boundary layer structure. Proper initialization of soil moisture is therefore critical for faithful simulations. In many applications, such as air quality or process studies, the model is run for short, discrete periods (a day to a month). This paper describes one method for soil initialization in these cases - self-spinup. In self-spinup, the model is initialized with a coarse-resolution operational model or reanalysis output, and run for a month, cycling its own soil variables. This allows the soil variables to develop appropriate spatial variability, and may improve the actual values. The month (or other period) can be run more than once if needed. The case shown is for the Boundary Layer Late Afternoon and Sunset Turbulence experiment, conducted in France in 2011. Self-spinup adds spatial variability, which improves the representation of soil moisture patterns around the experiment location, which is quite near the Pyrenees Mountains. The self-spinup also corrects a wet bias in the large-scale analysis. The overall result is a much-improved simulation of boundary layer structure, evaluated by comparison with soundings from the field site. Self-spinup is not recommended as a substitute for multi-year spinup with an offline land data assimilation system in circumstances where the data sets required for such spinup are available at the required resolution. Self-spinup may fail if the modeled precipitation is poorly simulated. It is an expedient for cases when resources are not available to allow a better method to be used.

  8. A New Conceptual Model for the Continuum of Land Rights

    African Journals Online (AJOL)

    Akrofi

    Abstract. This paper presents a new conceptual model for the land rights continuum. In developing the argument for the proposed model, the theoretical assumptions of the former model are challenged and an understanding of land rights and tenure elements is explored. The evolutionary approach is rejected in order to ...

  9. Land Surface Verification Toolkit (LVT) - A Generalized Framework for Land Surface Model Evaluation

    Science.gov (United States)

    Kumar, Sujay V.; Peters-Lidard, Christa D.; Santanello, Joseph; Harrison, Ken; Liu, Yuqiong; Shaw, Michael

    2011-01-01

    Model evaluation and verification are key in improving the usage and applicability of simulation models for real-world applications. In this article, the development and capabilities of a formal system for land surface model evaluation called the Land surface Verification Toolkit (LVT) is described. LVT is designed to provide an integrated environment for systematic land model evaluation and facilitates a range of verification approaches and analysis capabilities. LVT operates across multiple temporal and spatial scales and employs a large suite of in-situ, remotely sensed and other model and reanalysis datasets in their native formats. In addition to the traditional accuracy-based measures, LVT also includes uncertainty and ensemble diagnostics, information theory measures, spatial similarity metrics and scale decomposition techniques that provide novel ways for performing diagnostic model evaluations. Though LVT was originally designed to support the land surface modeling and data assimilation framework known as the Land Information System (LIS), it also supports hydrological data products from other, non-LIS environments. In addition, the analysis of diagnostics from various computational subsystems of LIS including data assimilation, optimization and uncertainty estimation are supported within LVT. Together, LIS and LVT provide a robust end-to-end environment for enabling the concepts of model data fusion for hydrological applications. The evolving capabilities of LVT framework are expected to facilitate rapid model evaluation efforts and aid the definition and refinement of formal evaluation procedures for the land surface modeling community.

  10. Modelling land Use Change : Improving the prediction of future land use patterns

    NARCIS (Netherlands)

    de Nijs, A.C.M.

    2009-01-01

    Modelling land Use Change: Improving the prediction of future land use patterns. Man has been altering his living environment since prehistoric times and will continue to do so. It is predicted that by 2030 about 90,000 ha will be needed for residential developments in the Netherlands and 55,000 ha

  11. Translation of Land Surface Model Accuracy and Uncertainty into Coupled Land-Atmosphere Prediction

    Science.gov (United States)

    Santanello, Joseph A.; Kumar, Sujay; Peters-Lidard, Christa D.; Harrison, Kenneth W.; Zhou, Shuija

    2012-01-01

    Land-atmosphere (L-A) Interactions playa critical role in determining the diurnal evolution of both planetary boundary layer (PBL) and land surface heat and moisture budgets, as well as controlling feedbacks with clouds and precipitation that lead to the persistence of dry and wet regimes. Recent efforts to quantify the strength of L-A coupling in prediction models have produced diagnostics that integrate across both the land and PBL components of the system. In this study, we examine the impact of improved specification of land surface states, anomalies, and fluxes on coupled WRF forecasts during the summers of extreme dry (2006) and wet (2007) land surface conditions in the U.S. Southern Great Plains. The improved land initialization and surface flux parameterizations are obtained through the use of a new optimization and uncertainty estimation module in NASA's Land Information System (US-OPT/UE), whereby parameter sets are calibrated in the Noah land surface model and classified according to a land cover and soil type mapping of the observation sites to the full model domain. The impact of calibrated parameters on the a) spinup of the land surface used as initial conditions, and b) heat and moisture states and fluxes of the coupled WRF Simulations are then assessed in terms of ambient weather and land-atmosphere coupling along with measures of uncertainty propagation into the forecasts. In addition, the sensitivity of this approach to the period of calibration (dry, wet, average) is investigated. Finally, tradeoffs of computational tractability and scientific validity, and the potential for combining this approach with satellite remote sensing data are also discussed.

  12. A higher order conditional random field model for simultaneous classification of land cover and land use

    Science.gov (United States)

    Albert, Lena; Rottensteiner, Franz; Heipke, Christian

    2017-08-01

    We propose a new approach for the simultaneous classification of land cover and land use considering spatial as well as semantic context. We apply a Conditional Random Fields (CRF) consisting of a land cover and a land use layer. In the land cover layer of the CRF, the nodes represent super-pixels; in the land use layer, the nodes correspond to objects from a geospatial database. Intra-layer edges of the CRF model spatial dependencies between neighbouring image sites. All spatially overlapping sites in both layers are connected by inter-layer edges, which leads to higher order cliques modelling the semantic relation between all land cover and land use sites in the clique. A generic formulation of the higher order potential is proposed. In order to enable efficient inference in the two-layer higher order CRF, we propose an iterative inference procedure in which the two classification tasks mutually influence each other. We integrate contextual relations between land cover and land use in the classification process by using contextual features describing the complex dependencies of all nodes in a higher order clique. These features are incorporated in a discriminative classifier, which approximates the higher order potentials during the inference procedure. The approach is designed for input data based on aerial images. Experiments are carried out on two test sites to evaluate the performance of the proposed method. The experiments show that the classification results are improved compared to the results of a non-contextual classifier. For land cover classification, the result is much more homogeneous and the delineation of land cover segments is improved. For the land use classification, an improvement is mainly achieved for land use objects showing non-typical characteristics or similarities to other land use classes. Furthermore, we have shown that the size of the super-pixels has an influence on the level of detail of the classification result, but also on the

  13. A High-Resolution Hydrometeorological Forcing and Landscape Attributes Data Set for Hydrological Applications over the Southeastern United States

    Science.gov (United States)

    Tao, J.; Barros, A. P.; Bryant, E.; Peters-Lidard, C. D.

    2012-12-01

    In anticipation of NASA's Global Precipitation Measurement (GPM) ground-validation activities the SE United States and synergies with NOAA's Hydrometeorology Testbed-Southeast Pilot Study (HMT-SEPS) in western North Carolina, a high-resolution data set is being developed to provide the Hydrologic Modeling community with common control forcing and landscape attributes to facilitate multi-scale, multi-purpose hydrologic modeling studies ranging from flash-flood forecasting to basin-scale water resource assessments. In the first phase of the project, the goal is to generate quality hydrometeorological forcing data sets at high spatial and temporal resolution (1km×1km, hourly time step) for the five-year time period 2007-2011 with a focus on the river basins with headwaters in the Southern Appalachians: Upper Tennessee River Basin (56,573 km2), Savannah River Basin (27,110 km2), Santee River Basin (39,862 km2) and Yadkin-Pee Dee River Basin (46,310 km2). For subsequent years, the data are updated on every three months. Space-time varying land surface properties such as broadband albedo, broadband emissivity, fractional vegetation coverage and leaf area index are derived from MODIS products. The original products are re-projected and composited to the study area, bilinearly interpolated to basin grids, and then linearly interpolated into hourly time steps from the nominal daily, 8 day or 16 day. Missing data gaps are addressed using physically meaning full constraints based on ancillary data. Precipitation is generated from NCEP/EMC 4KM Gridded Data (GRIB) Stage IV hourly data using the nearest neighbor method. Integration of Stage IV data with precipitation observations from research networks in the region provides dynamic relationships for improving precipitation accuracy in mountainous terrain. The atmospheric forcing data are extracted from North American Regional Reanalysis (NARR) products originally at 32-km spatial resolution and 3-hour temporal resolution

  14. Pairing FLUXNET sites to validate model representations of land-use/land-cover change

    Science.gov (United States)

    Chen, Liang; Dirmeyer, Paul A.; Guo, Zhichang; Schultz, Natalie M.

    2018-01-01

    Land surface energy and water fluxes play an important role in land-atmosphere interactions, especially for the climatic feedback effects driven by land-use/land-cover change (LULCC). These have long been documented in model-based studies, but the performance of land surface models in representing LULCC-induced responses has not been investigated well. In this study, measurements from proximate paired (open versus forest) flux tower sites are used to represent observed deforestation-induced changes in surface fluxes, which are compared with simulations from the Community Land Model (CLM) and the Noah Multi-Parameterization (Noah-MP) land model. Point-scale simulations suggest the CLM can represent the observed diurnal and seasonal changes in net radiation (Rnet) and ground heat flux (G), but difficulties remain in the energy partitioning between latent (LE) and sensible (H) heat flux. The CLM does not capture the observed decreased daytime LE, and overestimates the increased H during summer. These deficiencies are mainly associated with models' greater biases over forest land-cover types and the parameterization of soil evaporation. Global gridded simulations with the CLM show uncertainties in the estimation of LE and H at the grid level for regional and global simulations. Noah-MP exhibits a similar ability to simulate the surface flux changes, but with larger biases in H, G, and Rnet change during late winter and early spring, which are related to a deficiency in estimating albedo. Differences in meteorological conditions between paired sites is not a factor in these results. Attention needs to be devoted to improving the representation of surface heat flux processes in land models to increase confidence in LULCC simulations.

  15. A spatially comprehensive, hydrometeorological data set for Mexico, the U.S., and Southern Canada 1950-2013.

    Science.gov (United States)

    Livneh, Ben; Bohn, Theodore J; Pierce, David W; Munoz-Arriola, Francisco; Nijssen, Bart; Vose, Russell; Cayan, Daniel R; Brekke, Levi

    2015-01-01

    A data set of observed daily precipitation, maximum and minimum temperature, gridded to a 1/16° (~6 km) resolution, is described that spans the entire country of Mexico, the conterminous U.S. (CONUS), and regions of Canada south of 53° N for the period 1950-2013. The dataset improves previous products in spatial extent, orographic precipitation adjustment over Mexico and parts of Canada, and reduction of transboundary discontinuities. The impacts of adjusting gridded precipitation for orographic effects are quantified by scaling precipitation to an elevation-aware 1981-2010 precipitation climatology in Mexico and Canada. Differences are evaluated in terms of total precipitation as well as by hydrologic quantities simulated with a land surface model. Overall, orographic correction impacts total precipitation by up to 50% in mountainous regions outside CONUS. Hydrologic fluxes show sensitivities of similar magnitude, with discharge more sensitive than evapotranspiration and soil moisture. Because of the consistent gridding methodology, the current product reduces transboundary discontinuities as compared with a commonly used reanalysis product, making it suitable for estimating large-scale hydrometeorologic phenomena.

  16. Transcontinental hydrometeorological extremes and streamflow generation in the Pacific Coast

    Science.gov (United States)

    Munoz-Arriola, F.; Lavado, W.; Oglesby, R. J.; Rowe, C. M.; Vazquez-Aguirre, J. L.

    2013-12-01

    Streamflow is a key integrative variable of the hydrologic cycle at the basin scale. In regions along the Pacific coast of the Americas, the role of streamflow varies according to varying physical, biological, and socioeconomical contexts. Improving our understanding of the relationships between those components is a key element to improving the predictability of water availability to sustain food and energy security. However, it is still unclear how large-scale phenomena such as El Niño - Southern Oscillation affect streamflow generation along the Pacific Coast. The present work aims (a) to understand the temporal variability and spatial distribution of hydrometeorological extremes in different basins along the Pacific Coast and (b) how hydrometeorological extreme events contribute to the water year. We hypothesize that hydrometeorologic extreme contributions are to some extent regulated by ENSO, increasing their effect on streamflow generation during extreme-wet and -dry years. Hydrometeorological extreme events are estimated through the use of percentiles of precipitation and streamflow based on a GEV distribution. We assess the Sacramento River Basin (USA), Yaqui and Grijalva River Basins (Mexico) and Chillon River Basin (Perú). Preliminary results show important effects of ENSO negative phase (La Niña) on large streamflow generation in the Grijalva River Basin (Mexico), while in the Sacramento River Basin (USA), the effect is more conspicuous during El Niño, affecting the sustainability of hydropower generation and agricultural activities.

  17. Hydrometeorological and Statistical Analyses of Heavy Rainfall in Midwestern USA

    DEFF Research Database (Denmark)

    Thorndahl, Søren Liedtke; Smith, J. A.; Krajewski, W. F.

    2012-01-01

    During the last two decades the mid-western states of the United States of America has been largely afflicted by heavy flood producing rainfall. Several of these storms seem to have similar hydrometeorological properties in terms of pattern, track, evolution, life cycle, clustering, etc. which raise...

  18. Use of a scenario-neutral approach to identify the key hydro-meteorological attributes that impact runoff from a natural catchment

    Science.gov (United States)

    Guo, Danlu; Westra, Seth; Maier, Holger R.

    2017-11-01

    Scenario-neutral approaches are being used increasingly for assessing the potential impact of climate change on water resource systems, as these approaches allow the performance of these systems to be evaluated independently of climate change projections. However, practical implementations of these approaches are still scarce, with a key limitation being the difficulty of generating a range of plausible future time series of hydro-meteorological data. In this study we apply a recently developed inverse stochastic generation approach to support the scenario-neutral analysis, and thus identify the key hydro-meteorological variables to which the system is most sensitive. The stochastic generator simulates synthetic hydro-meteorological time series that represent plausible future changes in (1) the average, extremes and seasonal patterns of rainfall; and (2) the average values of temperature (Ta), relative humidity (RH) and wind speed (uz) as variables that drive PET. These hydro-meteorological time series are then fed through a conceptual rainfall-runoff model to simulate the potential changes in runoff as a function of changes in the hydro-meteorological variables, and runoff sensitivity is assessed with both correlation and Sobol' sensitivity analyses. The method was applied to a case study catchment in South Australia, and the results showed that the most important hydro-meteorological attributes for runoff were winter rainfall followed by the annual average rainfall, while the PET-related meteorological variables had comparatively little impact. The high importance of winter rainfall can be related to the winter-dominated nature of both the rainfall and runoff regimes in this catchment. The approach illustrated in this study can greatly enhance our understanding of the key hydro-meteorological attributes and processes that are likely to drive catchment runoff under a changing climate, thus enabling the design of tailored climate impact assessments to specific

  19. Maximizing Statistical Power When Verifying Probabilistic Forecasts of Hydrometeorological Events

    Science.gov (United States)

    DeChant, C. M.; Moradkhani, H.

    2014-12-01

    Hydrometeorological events (i.e. floods, droughts, precipitation) are increasingly being forecasted probabilistically, owing to the uncertainties in the underlying causes of the phenomenon. In these forecasts, the probability of the event, over some lead time, is estimated based on some model simulations or predictive indicators. By issuing probabilistic forecasts, agencies may communicate the uncertainty in the event occurring. Assuming that the assigned probability of the event is correct, which is referred to as a reliable forecast, the end user may perform some risk management based on the potential damages resulting from the event. Alternatively, an unreliable forecast may give false impressions of the actual risk, leading to improper decision making when protecting resources from extreme events. Due to this requisite for reliable forecasts to perform effective risk management, this study takes a renewed look at reliability assessment in event forecasts. Illustrative experiments will be presented, showing deficiencies in the commonly available approaches (Brier Score, Reliability Diagram). Overall, it is shown that the conventional reliability assessment techniques do not maximize the ability to distinguish between a reliable and unreliable forecast. In this regard, a theoretical formulation of the probabilistic event forecast verification framework will be presented. From this analysis, hypothesis testing with the Poisson-Binomial distribution is the most exact model available for the verification framework, and therefore maximizes one's ability to distinguish between a reliable and unreliable forecast. Application of this verification system was also examined within a real forecasting case study, highlighting the additional statistical power provided with the use of the Poisson-Binomial distribution.

  20. A traceability framework for diagnostics of global land models

    Science.gov (United States)

    Luo, Yiqi; Xia, Jianyang; Liang, Junyi; Jiang, Lifen; Shi, Zheng; KC, Manoj; Hararuk, Oleksandra; Rafique, Rashid; Wang, Ying-Ping

    2015-04-01

    The biggest impediment to model diagnostics and improvement at present is model intractability. The more processes incorporated, the more difficult it becomes to understand or evaluate model behavior. As a result, uncertainty in predictions among global land models cannot be easily diagnosed and attributed to their sources. We have recently developed an approach to analytically decompose a complex land model into traceable components based on mutually independent properties of modeled core biogeochemical processes. As all global land carbon models share those common properties, this traceability framework is applicable to all of them to improve their tractability. Indeed, we have applied the traceability framework to improve model diagnostics in several aspects. First, we have applied the framework to the Australian Community Atmosphere Biosphere Land Exchange (CABLE) model and Community Land Model version 3.5 (CLM3.5) to identify sources of those model differences. The major causes of different predictions were found to be parameter setting related to carbon input and baseline residence times between the two models. Second, we have used the framework to diagnose impacts of adding nitrogen processes into CABLE on its carbon simulation. Adding nitrogen processes not only reduces net primary production but also shortens residence times in the CABLE model. Third, the framework helps isolate components of CLM3.5 for data assimilation. Data assimilation with global land models has been computationally extremely difficult. By isolating traceable components, we have improved parameterization of CLM3.4 related to soil organic decomposition, microbial kinetics and carbon use efficiency, and litter decomposition. Further, we are currently developing the traceability framework to analyze transient simulations of models that were involved in the coupled Model Intercomparison Project Phase 5 (CMIP5) to improve our understanding on parameter space of global carbon models. This

  1. Development of a Spatial Decision Support System for Analyzing Changes in Hydro-meteorological Risk

    Science.gov (United States)

    van Westen, Cees

    2013-04-01

    In the framework of the EU FP7 Marie Curie ITN Network "CHANGES: Changing Hydro-meteorological Risks, as Analyzed by a New Generation of European Scientists (http://www.changes-itn.eu)", a spatial decision support system is under development with the aim to analyze the effect of risk reduction planning alternatives on reducing the risk now and in the future, and support decision makers in selecting the best alternatives. The SDSS is one of the main outputs of the CHANGES network, which will develop an advanced understanding of how global changes, related to environmental and climate change as well as socio-economical change, may affect the temporal and spatial patterns of hydro-meteorological hazards and associated risks in Europe; how these changes can be assessed, modeled, and incorporated in sustainable risk management strategies, focusing on spatial planning, emergency preparedness and risk communication. The CHANGES network consists of 11 full partners and 6 associate partners of which 5 private companies, representing 10 European countries. The CHANGES network has hired 12 Early Stage Researchers (ESRs) and is currently hiring 3-6 researchers more for the implementation of the SDSS. The Spatial Decision Support System will be composed of a number of integrated components. The Risk Assessment component allows to carry out spatial risk analysis, with different degrees of complexity, ranging from simple exposure (overlay of hazard and assets maps) to quantitative analysis (using different hazard types, temporal scenarios and vulnerability curves) resulting into risk curves. The platform does not include a component to calculate hazard maps, and existing hazard maps are used as input data for the risk component. The second component of the SDSS is a risk reduction planning component, which forms the core of the platform. This component includes the definition of risk reduction alternatives (related to disaster response planning, risk reduction measures and

  2. Modelling land change: the issue of use and cover in wide-scale applications

    NARCIS (Netherlands)

    Bakker, M.M.; Veldkamp, A.

    2008-01-01

    In this article, the underlying causes for the apparent mismatch between land cover and land use in the context of wide-scale land change modelling are explored. A land use-land cover (LU/LC) ratio is proposed as a relevant landscape characteristic. The one-to-one ratio between land use and land

  3. Empirically derived neighbourhood rules for urban land-use modelling

    DEFF Research Database (Denmark)

    Hansen, Henning Sten

    2012-01-01

    interaction between neighbouring land uses is an important component in urban cellular automata. Nevertheless, this component is often calibrated through trial-and-error estimation. The aim of this project has been to develop an empirically derived landscape metric supporting cellular-automata-based land......-use modelling. Through access to very detailed urban land-use data it has been possible to derive neighbourhood rules empirically, and test their sensitivity to the land-use classification applied, the regional variability of the rules, and their time variance. The developed methodology can be implemented...

  4. Enhancing Representation of Subgrid Land Surface Characteristics in the Community Land Model

    Science.gov (United States)

    Ke, Y.; Coleman, A.; Leung, L.; Huang, M.; Li, H.; Wigmosta, M. S.

    2011-12-01

    The Community Land Model (CLM) is the land surface model used in the Community Earth System Model (CESM). In CLM each grid cell is composed of subgrid land units, snow/soil columns and plant functional types (PFTs). In the current version of CLM (CLM4.0), land surface parameters such as vegetated/non-vegetated land cover and surface characteristics including fractional glacier, lake, wetland, urban area, and PFT, and its associated leaf area index (LAI), stem area index (SAI), and canopy top and bottom heights are provided at 0.5° or coarser resolution. This study aims to enhance the representation of the land surface data by (1) creating higher resolution (0.05° or higher) global land surface parameters, and (2) developing an effective and accurate subgrid classification scheme for elevation and PFTs so that variations of land surface processes due to the subgrid distribution of PFTs and elevation can be represented in CLM. To achieve higher-resolution global land surface parameters, MODIS 500m land cover product (MCD12Q1) collected in 2005 was used to generate percentage of glacier, lake, wetland, and urban area and fractional PFTs at 0.05° resolution. Spatially and temporally continuous and consistent global LAI data re-processed and improved from MOD15A2 (http://globalchange.bnu.edu.cn/research/lai), combined with the PFT data, was used to create LAI, SAI, and, canopy top and bottom height data. 30-second soil texture data was obtained from a hybrid 30-second State Soil Geographic Database (STATSGO) and the 5-minute Food and Agriculture Organization two-layer 16-category soil texture dataset. The relationship between global distribution of PFTs and 1-km resolution elevation data is being analyzed to develop a subgrid classification of PFT and elevation. Statistical analysis is being conducted to compare different subgrid classification methods to select a method that explains the highest percentage of subgrid variance in both PFT and elevation distribution

  5. Modeling land development along highway 4 in Southern Thailand

    Directory of Open Access Journals (Sweden)

    Potjamas Chuangchang

    2014-12-01

    Full Text Available This study aims to investigate the change of developed land in three different locations along Highway 4 Road from Phattalung to HatYai. The method involves creating a digitized grid of geographical coordinates covering the study area. The land-use codes and plot identifiers were recorded in database tables indexed by grid coordinates. Logistic regression of land development adjusted for spatial correlation was used to model its change over a 9-year period using land-use at the previous survey combined with location as a determinant. The results show increasing average percentages of developed land (3% in 2000 and 5% in 2009. Land development occurred mostly in the northern location along the Pattalung to HatYai road.

  6. Geographical information modelling for land resource survey

    NARCIS (Netherlands)

    Bruin, de S.

    2000-01-01

    The increasing popularity of geographical information systems (GIS) has at least three major implications for land resources survey. Firstly, GIS allows alternative and richer representation of spatial phenomena than is possible with the traditional paper map. Secondly, digital technology

  7. Landscape models: helping land managers think big

    Science.gov (United States)

    Rachel White; Rhonda Mazza

    2011-01-01

    In a sun-baked, grassy clearing on the east side of the Cascade Range in central Washington, Pacific Northwest (PNW) Research Station landscape ecologist Miles Hemstrom and a group of ecologists and land managers from the Washington Department of Natural Resources (DNR) gather in the shade of a ponderosa pine. Hundreds of years old, this ancient pine has withstood...

  8. Simulating Land-Use Change using an Agent-Based Land Transaction Model

    Science.gov (United States)

    Bakker, M. M.; van Dijk, J.; Alam, S. J.

    2013-12-01

    In the densely populated cultural landscapes of Europe, the vast majority of all land is owned by private parties, be it farmers (the majority), nature organizations, property developers, or citizens. Therewith, the vast majority of all land-use change arises from land transactions between different owner types: successful farms expand at the expense of less successful farms, and meanwhile property developers, individual citizens, and nature organizations also actively purchase land. These land transactions are driven by specific properties of the land, by governmental policies, and by the (economic) motives of both buyers and sellers. Climate/global change can affect these drivers at various scales: at the local scale changes in hydrology can make certain land less or more desirable; at the global scale the agricultural markets will affect motives of farmers to buy or sell land; while at intermediate (e.g. provincial) scales property developers and nature conservationists may be encouraged or discouraged to purchase land. The cumulative result of all these transactions becomes manifest in changing land-use patterns, and consequent environmental responses. Within the project Climate Adaptation for Rural Areas an agent-based land-use model was developed that explores the future response of individual land users to climate change, within the context of wider global change (i.e. policy and market change). It simulates the exchange of land among farmers and between farmers and nature organizations and property developers, for a specific case study area in the east of the Netherlands. Results show that local impacts of climate change can result in a relative stagnation in the land market in waterlogged areas. Furthermore, the increase in dairying at the expense of arable cultivation - as has been observed in the area in the past - is slowing down as arable produce shows a favourable trend in the agricultural world market. Furthermore, budgets for nature managers are

  9. Development of a prototype land use model for statewide transportation planning activities.

    Science.gov (United States)

    2011-11-30

    Future land use forecasting is an important input to transportation planning modeling. Traditionally, land use is allocated to individual : traffic analysis zones (TAZ) based on variables such as the amount of vacant land, zoning restriction, land us...

  10. High-resolution Continental Scale Land Surface Model incorporating Land-water Management in United States

    Science.gov (United States)

    Shin, S.; Pokhrel, Y. N.

    2016-12-01

    Land surface models have been used to assess water resources sustainability under changing Earth environment and increasing human water needs. Overwhelming observational records indicate that human activities have ubiquitous and pertinent effects on the hydrologic cycle; however, they have been crudely represented in large scale land surface models. In this study, we enhance an integrated continental-scale land hydrology model named Leaf-Hydro-Flood to better represent land-water management. The model is implemented at high resolution (5km grids) over the continental US. Surface water and groundwater are withdrawn based on actual practices. Newly added irrigation, water diversion, and dam operation schemes allow better simulations of stream flows, evapotranspiration, and infiltration. Results of various hydrologic fluxes and stores from two sets of simulation (one with and the other without human activities) are compared over a range of river basin and aquifer scales. The improved simulations of land hydrology have potential to build consistent modeling framework for human-water-climate interactions.

  11. Community, conflict and land: exploring the strategic partnership model of South African land restitution

    NARCIS (Netherlands)

    Basu, Soutrik

    2016-01-01

    The Strategic Partnership (SP) model was implemented in the South African land restitution programme. The model prematurely ended in a fiasco that left the community with huge debts and intractable conflicts. This paper aims at understanding the implementation process by taking up the issue of how

  12. Modeled impact of anthropogenic land cover change on climate

    Science.gov (United States)

    Findell, K.L.; Shevliakova, E.; Milly, P.C.D.; Stouffer, R.J.

    2007-01-01

    Equilibrium experiments with the Geophysical Fluid Dynamics Laboratory's climate model are used to investigate the impact of anthropogenic land cover change on climate. Regions of altered land cover include large portions of Europe, India, eastern China, and the eastern United States. Smaller areas of change are present in various tropical regions. This study focuses on the impacts of biophysical changes associated with the land cover change (albedo, root and stomatal properties, roughness length), which is almost exclusively a conversion from forest to grassland in the model; the effects of irrigation or other water management practices and the effects of atmospheric carbon dioxide changes associated with land cover conversion are not included in these experiments. The model suggests that observed land cover changes have little or no impact on globally averaged climatic variables (e.g., 2-m air temperature is 0.008 K warmer in a simulation with 1990 land cover compared to a simulation with potential natural vegetation cover). Differences in the annual mean climatic fields analyzed did not exhibit global field significance. Within some of the regions of land cover change, however, there are relatively large changes of many surface climatic variables. These changes are highly significant locally in the annual mean and in most months of the year in eastern Europe and northern India. They can be explained mainly as direct and indirect consequences of model-prescribed increases in surface albedo, decreases in rooting depth, and changes of stomatal control that accompany deforestation. ?? 2007 American Meteorological Society.

  13. Hard-coded parameters have the largest impact on fluxes of the land surface model Noah-MP

    Science.gov (United States)

    Cuntz, M.; Mai, J.; Samaniego, L. E.; Clark, M. P.; Wulfmeyer, V.; Attinger, S.; Thober, S.

    2015-12-01

    Land surface models incorporate a large number of processes, described by physical and empirical equations. The agilityof the models to react to different meteorological conditions is artificially constrained by having hard-codedparameters in their equations. The land surface model Noah with multiple process options (Noah-MP) is one of the standard land surface schemes in WRFand gives the flexibility to experiment with several model parameterizations of biophysical and hydrologicalprocesses. The model has around 80 parameters per plant functional type or soil class, which are given in tabulatedform and which can be adjusted. Here we looked into the model code in considerable detail and found another 140hard-coded values in all parameterizations, called hidden parameters here, of which around 50-60 are active inspecific combinations of the process options. We quantify global parametric sensitivities (SI) for the traditional and the hidden parameters for five model outputsin 12 MOPEX catchments of very different local hydro-meteorologies. Outputs are photosynthesis, transpiration,latent heat, surface and underground runoff. Photosynthesis is mostly sensitive to parameters describing plant physiology. Its second largest SI is for a hiddenparameter that partitions incoming into direct and diffuse radiation. Transpiration shows very similar SI asphotosynthesis. The SI of latent heat are, however, very different to transpiration. Its largest SI is observed for ahidden parameter in the formulation of soil surface resistance, due to low transpiration in Noah-MP. Surface runoff ismostly sensitive to soil and infiltration parameters. But it is also sensitive to almost all hidden snow parameters,which are about 40% of all hidden parameters. The largest SI of surface runoff is to the albedo of fresh snow and thesecond largest to the thermal conductivity of snow. Sensitive parameters for underground runoff, finally, are a mixtureof those of latent heat and surface runoff. In

  14. An integrated land change model for projecting future climate and land change scenarios

    Science.gov (United States)

    Wimberly, Michael; Sohl, Terry L.; Lamsal, Aashis; Liu, Zhihua; Hawbaker, Todd J.

    2013-01-01

    Climate change will have myriad effects on ecosystems worldwide, and natural and anthropogenic disturbances will be key drivers of these dynamics. In addition to climatic effects, continual expansion of human settlement into fire-prone forests will alter fire regimes, increase human vulnerability, and constrain future forest management options. There is a need for modeling tools to support the simulation and assessment of new management strategies over large regions in the context of changing climate, shifting development patterns, and an expanding wildland-urban interface. To address this need, we developed a prototype land change simulator that combines human-driven land use change (derived from the FORE-SCE model) with natural disturbances and vegetation dynamics (derived from the LADS model) and incorporates novel feedbacks between human land use and disturbance regimes. The prototype model was implemented in a test region encompassing the Denver metropolitan area along with its surrounding forested and agricultural landscapes. Initial results document the feasibility of integrated land change modeling at a regional scale but also highlighted conceptual and technical challenges for this type of model integration. Ongoing development will focus on improving climate sensitivities and modeling constraints imposed by climate change and human population growth on forest management activities.

  15. POSSIBILITIES OF LAND ADMINISTRATION DOMAIN MODEL (LADM IMPLEMENTATION IN NIGERIA

    Directory of Open Access Journals (Sweden)

    S. O. Babalola

    2015-10-01

    Full Text Available LADM covers essential information associated components of land administration and management including those over water and elements above and below the surface of the earth. LADM standard provides an abstract conceptual model with three packages and one sub-package. LADM defined terminology for a land administration system that allows a shared explanation of different formal customary or informal tenures. The standard provides the basis for national and regional profiles and enables the combination of land management information from different sources in a coherent manner. Given this, this paper started with the description of land and land administration in Nigeria. The pre-colonial, colonial and post-colonial era with organization structure was discussed. This discussion is important to present an understanding of the background of any improvement needed for the LADM implementation in Nigeria. The LADM, ISO 19152 and the packages of LADM was discussed, and the comparison of the different aspects of each package and classes were made with Nigerian land administration and the cadastral system. In the comparison made, it was discovered that the concept is similar to LADM packages in Nigerian land administration. Although, the terminology may not be the same in all cases. Having studied conceptualization and the application of LADM, as a model that has essential information associated with components of the land administration. Including those on the land, over water as well as elements above and below the surface of the earth and discovered that the standard is suitable for the country. The model can, therefore, be adopted into Nigerian land administration system by mapping in some of the concepts of LADM.

  16. Possibilities of Land Administration Domain Model (ladm) Implementation in Nigeria

    Science.gov (United States)

    Babalola, S. O.; Rahman, A. Abdul; Choon, L. T.; Van Oosterom, P. J. M.

    2015-10-01

    LADM covers essential information associated components of land administration and management including those over water and elements above and below the surface of the earth. LADM standard provides an abstract conceptual model with three packages and one sub-package. LADM defined terminology for a land administration system that allows a shared explanation of different formal customary or informal tenures. The standard provides the basis for national and regional profiles and enables the combination of land management information from different sources in a coherent manner. Given this, this paper started with the description of land and land administration in Nigeria. The pre-colonial, colonial and post-colonial era with organization structure was discussed. This discussion is important to present an understanding of the background of any improvement needed for the LADM implementation in Nigeria. The LADM, ISO 19152 and the packages of LADM was discussed, and the comparison of the different aspects of each package and classes were made with Nigerian land administration and the cadastral system. In the comparison made, it was discovered that the concept is similar to LADM packages in Nigerian land administration. Although, the terminology may not be the same in all cases. Having studied conceptualization and the application of LADM, as a model that has essential information associated with components of the land administration. Including those on the land, over water as well as elements above and below the surface of the earth and discovered that the standard is suitable for the country. The model can, therefore, be adopted into Nigerian land administration system by mapping in some of the concepts of LADM.

  17. Matrix approach to land carbon cycle modeling: A case study with Community Land Model.

    Science.gov (United States)

    Huang, Yuanyuan; Lu, Xingjie; Shi, Zheng; Lawrence, David; Koven, Charles; Xia, Jianyang; Du, Zhenggang; Kluzek, Erik; Luo, Yiqi

    2017-10-20

    The terrestrial carbon (C) cycle has been commonly represented by a series of C balance equations to track C influxes into and effluxes out of individual pools in earth system models (ESMs). This representation matches our understanding of C cycle processes well but makes it difficult to track model behaviors. It is also computationally expensive, limiting the ability to conduct comprehensive parametric sensitivity analyses. To overcome these challenges, we have developed a matrix approach, which reorganizes the C balance equations in the original ESM into one matrix equation without changing any modeled C cycle processes and mechanisms. We applied the matrix approach to the Community Land Model (CLM4.5) with vertically resolved biogeochemistry. The matrix equation exactly reproduces litter and soil organic carbon (SOC) dynamics of the standard CLM4.5 across different spatial-temporal scales. The matrix approach enables effective diagnosis of system properties such as C residence time and attribution of global change impacts to relevant processes. We illustrated, for example, the impacts of CO2 fertilization on litter and SOC dynamics can be easily decomposed into the relative contributions from C input, allocation of external C into different C pools, nitrogen regulation, altered soil environmental conditions, and vertical mixing along the soil profile. In addition, the matrix tool can accelerate model spin-up, permit thorough parametric sensitivity tests, enable pool-based data assimilation, and facilitate tracking and benchmarking of model behaviors. Overall, the matrix approach can make a broad range of future modeling activities more efficient and effective. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

  18. Data model for the collaboration between land administration systems and agricultural land parcel identification systems.

    Science.gov (United States)

    Inan, Halil Ibrahim; Sagris, Valentina; Devos, Wim; Milenov, Pavel; van Oosterom, Peter; Zevenbergen, Jaap

    2010-12-01

    The Common Agricultural Policy (CAP) of the European Union (EU) has dramatically changed after 1992, and from then on the CAP focused on the management of direct income subsidies instead of production-based subsidies. For this focus, Member States (MS) are expected to establish Integrated Administration and Control System (IACS), including a Land Parcel Identification System (LPIS) as the spatial part of IACS. Different MS have chosen different solutions for their LPIS. Currently, some MS based their IACS/LPIS on data from their Land Administration Systems (LAS), and many others use purpose built special systems for their IACS/LPIS. The issue with these different IACS/LPIS is that they do not have standardized structures; rather, each represents a unique design in each MS, both in the case of LAS based or special systems. In this study, we aim at designing a core data model for those IACS/LPIS based on LAS. For this purpose, we make use of the ongoing standardization initiatives for LAS (Land Administration Domain Model: LADM) and IACS/LPIS (LPIS Core Model: LCM). The data model we propose in this study implies the collaboration between LADM and LCM and includes some extensions. Some basic issues with the collaboration model are discussed within this study: registration of farmers, land use rights and farming limitations, geometry/topology, temporal data management etc. For further explanation of the model structure, sample instance level diagrams illustrating some typical situations are also included. Copyright © 2010 Elsevier Ltd. All rights reserved.

  19. Family archives as a source of information about past hydrometeorological extremes in Southern Moravia (Czech Republic)

    Science.gov (United States)

    Chromá, Kateřina

    2014-05-01

    Meteorological and hydrological extremes (hydrometeorological extremes - HMEs) cause great material damage or even loss of human lives in the present time, as well as it was in the past. For the study of their temporal and spatial variability in periods with only natural forcing factors in comparison with those combining also anthropogenic effects it is essential to have the longest possible series of HMEs. In the Czech Lands (recently the Czech Republic), systematic meteorological and hydrological observations started generally in the latter half of the 19th century. Therefore, in order to create long-term series of such extremes, it is necessary to search for other sources of information. There exist different types of documentary evidence used in historical climatology and hydrology, represented by various sources such as annals, chronicles, diaries, private letters, newspapers etc. Besides them, institutional documentary evidence (of economic and administrative character) has particular importance (e.g. taxation records). Documents in family archives represent further promising source of data related to HMEs. The documents kept by the most important lord families in Moravia (e.g. Liechtensteins, Dietrichsteins) are located in Moravian Land Archives in Brno. Besides data about family members, industrial and agricultural business, military questions, travelling and social events, they contain direct or indirect information about HMEs. It concerns descriptions of catastrophic phenomena on the particular demesne (mainly with respect to damage) as well as correspondence related to tax reductions (i.e. they can overlap with taxation records of particular estates). This contribution shows the potential of family archives as a source of information about HMEs, up to now only rarely used, which may extend our knowledge about them. Several examples of such documents are presented. The study is a part of the research project "Hydrometeorological extremes in Southern

  20. Current challenges of implementing anthropogenic land-use and land-cover change in models contributing to climate change assessments

    Science.gov (United States)

    Prestele, Reinhard; Arneth, Almut; Bondeau, Alberte; de Noblet-Ducoudré, Nathalie; Pugh, Thomas A. M.; Sitch, Stephen; Stehfest, Elke; Verburg, Peter H.

    2017-05-01

    Land-use and land-cover change (LULCC) represents one of the key drivers of global environmental change. However, the processes and drivers of anthropogenic land-use activity are still overly simplistically implemented in terrestrial biosphere models (TBMs). The published results of these models are used in major assessments of processes and impacts of global environmental change, such as the reports of the Intergovernmental Panel on Climate Change (IPCC). Fully coupled models of climate, land use and biogeochemical cycles to explore land use-climate interactions across spatial scales are currently not available. Instead, information on land use is provided as exogenous data from the land-use change modules of integrated assessment models (IAMs) to TBMs. In this article, we discuss, based on literature review and illustrative analysis of empirical and modeled LULCC data, three major challenges of this current LULCC representation and their implications for land use-climate interaction studies: (I) provision of consistent, harmonized, land-use time series spanning from historical reconstructions to future projections while accounting for uncertainties associated with different land-use modeling approaches, (II) accounting for sub-grid processes and bidirectional changes (gross changes) across spatial scales, and (III) the allocation strategy of independent land-use data at the grid cell level in TBMs. We discuss the factors that hamper the development of improved land-use representation, which sufficiently accounts for uncertainties in the land-use modeling process. We propose that LULCC data-provider and user communities should engage in the joint development and evaluation of enhanced LULCC time series, which account for the diversity of LULCC modeling and increasingly include empirically based information about sub-grid processes and land-use transition trajectories, to improve the representation of land use in TBMs. Moreover, we suggest concentrating on the

  1. The Cévennes-Vivarais Mediterranean Hydrometeorological Observatory database

    Science.gov (United States)

    Boudevillain, Brice; Delrieu, Guy; Galabertier, Bruno; Bonnifait, Laurent; Bouilloud, Ludovic; Kirstetter, Pierre-Emmanuel; Mosini, Marie-Laure

    2011-07-01

    Intense rain events frequently result in devastating flash floods in Mediterranean regions. To improve the understanding and prediction of these phenomena, the Cévennes-Vivarais Mediterranean Hydrometeorological Observatory (CVMHO) was set up in 2000. The observation strategies deployed include the detailed and long-lasting (>10 years) observation in the Cévennes-Vivarais region (France) using both operational observation systems and research instrumentation. The present note describes the procedures implemented by CVMHO to critically analyze and generate hydrometeorological products for research. The related data can be viewed or downloaded via the Système d'Extraction et de Visualisation des Données de l'Observatoire en Ligne (SEVnOL) interface on the CVMHO Web site.

  2. Co-evolution of transportation and land use : modeling historical dependencies in land use and transportation decision making.

    Science.gov (United States)

    2009-11-01

    The interaction between land use and transportation has long been the central issue in urban and regional planning. Models of such : interactions provide vital information to support many public policy decisions, such as land supply, infrastructure p...

  3. Polarimetric SAR interferometry applied to land ice: modeling

    DEFF Research Database (Denmark)

    Dall, Jørgen; Papathanassiou, Konstantinos; Skriver, Henning

    2004-01-01

    depths. The validity of the scattering models is examined using L-band polarimetric interferometric SAR data acquired with the EMISAR system over an ice cap located in the percolation zone of the Greenland ice sheet. Radar reflectors were deployed on the ice surface prior to the data acquisition in order......This paper introduces a few simple scattering models intended for the application of polarimetric SAR interfer-ometry to land ice. The principal aim is to eliminate the penetration bias hampering ice sheet elevation maps generated with single-channel SAR interferometry. The polarimetric coherent...... scattering models are similar to the oriented-volume model and the random-volume-over-ground model used in vegetation studies, but the ice models are adapted to the different geometry of land ice. Also, due to compaction, land ice is not uniform; a fact that must be taken into account for large penetration...

  4. Mine land reclamation and eco-reconstruction in Shanxi province I: mine land reclamation model.

    Science.gov (United States)

    Bing-yuan, Hao; Li-xun, Kang

    2014-01-01

    Coal resource is the main primary energy in our country, while Shanxi Province is the most important province in resource. Therefore Shanxi is an energy base for our country and has a great significance in energy strategy. However because of the heavy development of the coal resource, the ecological environment is worsening and the farmland is reducing continuously in Shanxi Province. How to resolve the contradiction between coal resource exploitation and environmental protection has become the imperative. Thus the concept of "green mining industry" is arousing more and more attention. In this assay, we will talk about the basic mode of land reclamation in mine area, the engineering study of mine land reclamation, the comprehensive model study of mine land reclamation, and the design and model of ecological agricultural reclamation in mining subsidence.

  5. Mine Land Reclamation and Eco-Reconstruction in Shanxi Province I: Mine Land Reclamation Model

    Science.gov (United States)

    Bing-yuan, Hao; Li-xun, Kang

    2014-01-01

    Coal resource is the main primary energy in our country, while Shanxi Province is the most important province in resource. Therefore Shanxi is an energy base for our country and has a great significance in energy strategy. However because of the heavy development of the coal resource, the ecological environment is worsening and the farmland is reducing continuously in Shanxi Province. How to resolve the contradiction between coal resource exploitation and environmental protection has become the imperative. Thus the concept of “green mining industry” is arousing more and more attention. In this assay, we will talk about the basic mode of land reclamation in mine area, the engineering study of mine land reclamation, the comprehensive model study of mine land reclamation, and the design and model of ecological agricultural reclamation in mining subsidence. PMID:25050398

  6. Modeled historical land use and land cover for the conterminous United States

    Science.gov (United States)

    Sohl, Terry L.; Reker, Ryan; Bouchard, Michelle A.; Sayler, Kristi L.; Dornbierer, Jordan; Wika, Steve; Quenzer, Robert; Friesz, Aaron M.

    2016-01-01

    The landscape of the conterminous United States has changed dramatically over the last 200 years, with agricultural land use, urban expansion, forestry, and other anthropogenic activities altering land cover across vast swaths of the country. While land use and land cover (LULC) models have been developed to model potential future LULC change, few efforts have focused on recreating historical landscapes. Researchers at the US Geological Survey have used a wide range of historical data sources and a spatially explicit modeling framework to model spatially explicit historical LULC change in the conterminous United States from 1992 back to 1938. Annual LULC maps were produced at 250-m resolution, with 14 LULC classes. Assessment of model results showed good agreement with trends and spatial patterns in historical data sources such as the Census of Agriculture and historical housing density data, although comparison with historical data is complicated by definitional and methodological differences. The completion of this dataset allows researchers to assess historical LULC impacts on a range of ecological processes.

  7. A New Conceptual Model for the Continuum of Land Rights | Whittal ...

    African Journals Online (AJOL)

    Legitimacy, legality and complexity are identified as indicators of land tenure security. These lead to the triple vertical indices of land tenure security in the new model. The range of land rights options in use, their associated land tenure, as well as mobility of people and flexibility of land parcels between land rights types, can ...

  8. Differential mortality patterns from hydro-meteorological disasters:Evidence from cause-of-death data by age and sex

    OpenAIRE

    Zagheni, Emilio; Muttarak, Raya; Striessnig, Erich

    2016-01-01

    This paper evaluates the heterogeneous impact of hydro-meteorological disasters on populations along the dimensions of age, sex, and human development. The analysis is based on previously untapped cause-of-death data over the period 1995-2011 that were obtained from the WHO mortality database, and were based on the civil registration records of 63 countries/territories. Using these data, we evaluate patterns of mortality related to meteorological disasters in the spirit of model life tables. ...

  9. Differential mortality patterns from hydro-meteorological disasters: Evidence from cause-of-death data by age and sex

    OpenAIRE

    Zagheni, E.; Muttarak, R.; Strießnig, E.

    2016-01-01

    This paper evaluates the heterogeneous impact of hydro-meteorological disasters on populations along the dimensions of age, sex, and human development. The analysis is based on previously untapped cause-of-death data over the period 1995– 2011 that were obtained from the WHO mortality database, and were based on the civil registration records of 63 countries/territories. Using these data, we evaluate patterns of mortality related to meteorological disasters in the spirit of model life tables....

  10. EVALUATION OF LAND USE/LAND COVER DATASETS FOR URBAN WATERSHED MODELING

    Energy Technology Data Exchange (ETDEWEB)

    S.J. BURIAN; M.J. BROWN; T.N. MCPHERSON

    2001-08-01

    Land use/land cover (LULC) data are a vital component for nonpoint source pollution modeling. Most watershed hydrology and pollutant loading models use, in some capacity, LULC information to generate runoff and pollutant loading estimates. Simple equation methods predict runoff and pollutant loads using runoff coefficients or pollutant export coefficients that are often correlated to LULC type. Complex models use input variables and parameters to represent watershed characteristics and pollutant buildup and washoff rates as a function of LULC type. Whether using simple or complex models an accurate LULC dataset with an appropriate spatial resolution and level of detail is paramount for reliable predictions. The study presented in this paper compared and evaluated several LULC dataset sources for application in urban environmental modeling. The commonly used USGS LULC datasets have coarser spatial resolution and lower levels of classification than other LULC datasets. In addition, the USGS datasets do not accurately represent the land use in areas that have undergone significant land use change during the past two decades. We performed a watershed modeling analysis of three urban catchments in Los Angeles, California, USA to investigate the relative difference in average annual runoff volumes and total suspended solids (TSS) loads when using the USGS LULC dataset versus using a more detailed and current LULC dataset. When the two LULC datasets were aggregated to the same land use categories, the relative differences in predicted average annual runoff volumes and TSS loads from the three catchments were 8 to 14% and 13 to 40%, respectively. The relative differences did not have a predictable relationship with catchment size.

  11. Comparison of Land Skin Temperature from a Land Model, Remote Sensing, and In-situ Measurement

    Science.gov (United States)

    Wang, Aihui; Barlage, Michael; Zeng, Xubin; Draper, Clara Sophie

    2014-01-01

    Land skin temperature (Ts) is an important parameter in the energy exchange between the land surface and atmosphere. Here hourly Ts from the Community Land Model Version 4.0, MODIS satellite observations, and in-situ observations in 2003 were compared. Compared with the in-situ observations over four semi-arid stations, both MODIS and modeled Ts show negative biases, but MODIS shows an overall better performance. Global distribution of differences between MODIS and modeled Ts shows diurnal, seasonal, and spatial variations. Over sparsely vegetated areas, the model Ts is generally lower than the MODIS observed Ts during the daytime, while the situation is opposite at nighttime. The revision of roughness length for heat and the constraint of minimum friction velocity from Zeng et al. [2012] bring the modeled Ts closer to MODIS during the day, and have little effect on Ts at night. Five factors contributing to the Ts differences between the model and MODIS are identified, including the difficulty in properly accounting for cloud cover information at the appropriate temporal and spatial resolutions, and uncertainties in surface energy balance computation, atmospheric forcing data, surface emissivity, and MODIS Ts data. These findings have implications for the cross-evaluation of modeled and remotely sensed Ts, as well as the data assimilation of Ts observations into Earth system models.

  12. Supporting Hydrometeorological Research and Applications with Global Precipitation Measurement (GPM) Products and Services

    Science.gov (United States)

    Liu, Zhong; Ostrenga, D.; Vollmer, B.; Deshong, B.; MacRitchie, K.; Greene, M.; Kempler, S.

    2016-01-01

    Precipitation is an important dataset in hydrometeorological research and applications such as flood modeling, drought monitoring, etc. On February 27, 2014, the NASA Global Precipitation Measurement (GPM) mission was launched to provide the next-generation global observations of rain and snow (http:pmm.nasa.govGPM). The GPM mission consists of an international network of satellites in which a GPM Core Observatory satellite carries both active and passive microwave instruments to measure precipitation and serve as a reference standard, to unify precipitation measurements from a constellation of other research and operational satellites. The NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC) hosts and distributes GPM data. The GES DISC is home to the data archive for the GPM predecessor, the Tropical Rainfall Measuring Mission (TRMM). GPM products currently available include the following:1. Level-1 GPM Microwave Imager (GMI) and partner radiometer products2. Goddard Profiling Algorithm (GPROF) GMI and partner products (Level-2 and Level-3)3. GPM dual-frequency precipitation radar and their combined products (Level-2 and Level-3)4. Integrated Multi-satellitE Retrievals for GPM (IMERG) products (early, late, and final run)GPM data can be accessed through a number of data services (e.g., Simple Subset Wizard, OPeNDAP, WMS, WCS, ftp, etc.). A newly released Unified User Interface or UUI is a single interface to provide users seamless access to data, information and services. For example, a search for precipitation products will not only return TRMM and GPM products, but also other global precipitation products such as MERRA (Modern Era Retrospective-Analysis for Research and Applications), GLDAS (Global Land Data Assimilation Systems), etc.New features and capabilities have been recently added in GIOVANNI to allow exploring and inter-comparing GPM IMERG (Integrated Multi-satelliE Retrievals for GPM) half-hourly and monthly precipitation

  13. Extreme floods and storms in Switzerland since 1868: Case studies and hydro-meteorological patterns

    Science.gov (United States)

    Stucki, Peter; Brönnimann, Stefan; Martius, Olivia; Dierer, Silke

    2013-04-01

    Numerical studies on the generation of extreme floods or windstorms in the Central Alps have been practicable for events which occurred since around 1950. Analyses of earlier events are restricted to increasingly sparse instrumental and documentary data, e.g., ground observations, surface synoptic charts, annals and damage reports. Despite such restrictions, it is desirable to have an extended catalog of extreme heavy precipitation or storm events in order to understand the underlying hydro-meteorological dynamics and to anticipate potential damage to forested areas, cultivated land, buildings or infrastructure. We use a range of available sources to elect a set of historical extreme events. Among these are damage statistics by insurance companies, the EuroClimHist data base on weather and climate history, forestry reports as well as meteorological annals. Moreover, recently digitized and partly homogenized (sub-) daily measurements of precipitation and wind observations (DigiHom project by MeteoSwiss) and the Twentieth Century Reanalysis (20CR) reach back to 1868 or beyond. In addition, we integrate information from a regional version of 20CR which is downscaled by use of the Weather Research and Forecasting (WRF) Model. These datasets cover extreme events on the north and south side of the Alps and hence enable comprehensive, quantitative analyses of Swiss extreme events. For a selection of events prior to 1950, descriptions are given of the spatial extent and intensities, antecedent hydro-climatological settings such as snowmelt as well as of the direct socio-economic impact and costs. Likewise, we assess the meteorological conditions leading to and during the extreme events, including parameters like uplift and moisture transport or propagation of the three-dimensional wind field. We propose five subjective classes of specific flood-generating weather conditions for Switzerland from 24 investigated cases since 1868. Furthermore, we address the applicability of

  14. An update on land-ice modeling in the CESM

    Energy Technology Data Exchange (ETDEWEB)

    Lipscomb, William H [Los Alamos National Laboratory

    2011-01-18

    Mass loss from land ice, including the Greenland and Antarctic ice sheets as well as smaller glacier and ice caps, is making a large and growing contribution to global sea-level rise. Land ice is only beginning to be incorporated in climate models. The goal of the Land Ice Working Group (LIWG) is to develop improved land-ice models and incorporate them in CESM, in order to provide useful, physically-based sea-level predictions. LJWG efforts to date have led to the inclusion of a dynamic ice-sheet model (the Glimmer Community Ice Sheet Model, or Glimmer-CISM) in the Community Earth System Model (CESM), which was released in June 2010. CESM also includes a new surface-mass-balance scheme for ice sheets in the Community Land Model. Initial modeling efforts are focused on the Greenland ice sheet. Preliminary results are promising. In particular, the simulated surface mass balance for Greenland is in good agreement with observations and regional model results. The current model, however, has significant limitations: The land-ice coupling is one-way; we are using a serial version of Glimmer-CISM with the shallow-ice approximation; and there is no ice-ocean coupling. During the next year we plan to implement two-way coupling (including ice-ocean coupling with a dynamic Antarctic ice sheet) with a parallel , higher-order version of Glimmer-CISM. We will also add parameterizations of small glaciers and ice caps. With these model improvements, CESM will be able to simulate all the major contributors to 21st century global sea-level rise. Results of the first round of simulations should be available in time to be included in the Fifth Assessment Report (ARS) of the Intergovernmental Panel on Climate Change.

  15. POSSIBILITIES OF LAND ADMINISTRATION DOMAIN MODEL (LADM) IMPLEMENTATION IN NIGERIA

    OpenAIRE

    Babalola, S. O.; A. Abdul Rahman; Choon, L. T.; van Oosterom, P.J.M.

    2015-01-01

    LADM covers essential information associated components of land administration and management including those over water and elements above and below the surface of the earth. LADM standard provides an abstract conceptual model with three packages and one sub-package. LADM defined terminology for a land administration system that allows a shared explanation of different formal customary or informal tenures. The standard provides the basis for national and regional profiles and enables the com...

  16. Effects of high spatial and temporal resolution Earth observations on simulated hydrometeorological variables in a cropland (southwestern France

    Directory of Open Access Journals (Sweden)

    J. Etchanchu

    2017-11-01

    Full Text Available Agricultural landscapes are often constituted by a patchwork of crop fields whose seasonal evolution is dependent on specific crop rotation patterns and phenologies. This temporal and spatial heterogeneity affects surface hydrometeorological processes and must be taken into account in simulations of land surface and distributed hydrological models. The Sentinel-2 mission allows for the monitoring of land cover and vegetation dynamics at unprecedented spatial resolutions and revisit frequencies (20 m and 5 days, respectively that are fully compatible with such heterogeneous agricultural landscapes. Here, we evaluate the impact of Sentinel-2-like remote sensing data on the simulation of surface water and energy fluxes via the Interactions between the Surface Biosphere Atmosphere (ISBA land surface model included in the EXternalized SURface (SURFEX modeling platform. The study focuses on the effect of the leaf area index (LAI spatial and temporal variability on these fluxes. We compare the use of the LAI climatology from ECOCLIMAP-II, used by default in SURFEX-ISBA, and time series of LAI derived from the high-resolution Formosat-2 satellite data (8 m. The study area is an agricultural zone in southwestern France covering 576 km2 (24 km  ×  24 km. An innovative plot-scale approach is used, in which each computational unit has a homogeneous vegetation type. Evaluation of the simulations quality is done by comparing model outputs with in situ eddy covariance measurements of latent heat flux (LE. Our results show that the use of LAI derived from high-resolution remote sensing significantly improves simulated evapotranspiration with respect to ECOCLIMAP-II, especially when the surface is covered with summer crops. The comparison with in situ measurements shows an improvement of roughly 0.3 in the correlation coefficient and a decrease of around 30 % of the root mean square error (RMSE in the simulated evapotranspiration. This

  17. Global land-use allocation model linked to an integrated assessment model.

    Science.gov (United States)

    Hasegawa, Tomoko; Fujimori, Shinichiro; Ito, Akihiko; Takahashi, Kiyoshi; Masui, Toshihiko

    2017-02-15

    We developed a global land-use allocation model that can be linked to integrated assessment models (IAMs) with a coarser spatial resolution. Using the model, we performed a downscaling of the IAMs' regional aggregated land-use projections to obtain a spatial land-use distribution, which could subsequently be used by Earth system models for global environmental assessments of ecosystem services, food security, and climate policies. Here we describe the land-use allocation model, discuss the verification of the downscaling technique, and explain the influences of the downscaling on estimates of land-use carbon emissions. A comparison of the emissions estimated with and without downscaling suggested that the land-use downscaling would help capture the spatial distribution of carbon stock density and regional heterogeneity of carbon emissions caused by cropland and pasture land expansion. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

  18. Systemic change increases forecast uncertainty of land use change models

    Science.gov (United States)

    Verstegen, J. A.; Karssenberg, D.; van der Hilst, F.; Faaij, A.

    2013-12-01

    Cellular Automaton (CA) models of land use change are based on the assumption that the relationship between land use change and its explanatory processes is stationary. This means that model structure and parameterization are usually kept constant over time, ignoring potential systemic changes in this relationship resulting from societal changes, thereby overlooking a source of uncertainty. Evaluation of the stationarity of the relationship between land use and a set of spatial attributes has been done by others (e.g., Bakker and Veldkamp, 2012). These studies, however, use logistic regression, separate from the land use change model. Therefore, they do not gain information on how to implement the spatial attributes into the model. In addition, they often compare observations for only two points in time and do not check whether the change is statistically significant. To overcome these restrictions, we assimilate a time series of observations of real land use into a land use change CA (Verstegen et al., 2012), using a Bayesian data assimilation technique, the particle filter. The particle filter was used to update the prior knowledge about the parameterization and model structure, i.e. the selection and relative importance of the drivers of location of land use change. In a case study of sugar cane expansion in Brazil, optimal model structure and parameterization were determined for each point in time for which observations were available (all years from 2004 to 2012). A systemic change, i.e. a statistically significant deviation in model structure, was detected for the period 2006 to 2008. In this period the influence on the location of sugar cane expansion of the driver sugar cane in the neighborhood doubled, while the influence of slope and potential yield decreased by 75% and 25% respectively. Allowing these systemic changes to occur in our CA in the future (up to 2022) resulted in an increase in model forecast uncertainty by a factor two compared to the

  19. Meat consumption, production and land use : model implementation and scenarios

    NARCIS (Netherlands)

    Woltjer, G.B.

    2011-01-01

    This report discusses simulations with the LEITAP model about opportunities to reduce land use as a consequence of changing meat consumption and production. In order to be able to generate plausible simulation results, the LEITAP model had to be adjusted. These changes are discussed in the first

  20. Perspective: Economic models of pastoral land tenure | Behnke ...

    African Journals Online (AJOL)

    Reviews some existing economic models of pastoral land tenure, and identifies what appear to be the reasons for their appeal to policy makers. Puts forward an alternative model which can more precisely account for the organization of pastoral tenure systems and which suggests new ways of managing African rangeland.

  1. Comparing and modeling land use organization in cities

    CERN Document Server

    Lenormand, Maxime; Cantú-Ros, Oliva G; Louail, Thomas; Herranz, Ricardo; Barthelemy, Marc; Frías-Martínez, Enrique; Miguel, Maxi San; Ramasco, José J

    2015-01-01

    The advent of geolocated ICT technologies opens the possibility of exploring how people use space in cities, bringing an important new tool for urban scientists and planners, especially for regions where data is scarce or not available. Here we apply a functional network approach to determine land use patterns from mobile phone records. The versatility of the method allows us to run a systematic comparison between Spanish cities of various sizes. The method detects four major land use types that correspond to different temporal patterns. The proportion of these types, their spatial organization and scaling show a strong similarity between all cities that breaks down at a very local scale, where land use mixing is specific to each urban area. Finally, we introduce a model inspired by Schelling's segregation, able to explain and reproduce these results with simple interaction rules between different land uses.

  2. Highlights of advances in the field of hydrometeorological research brought about by the DRIHM project

    Science.gov (United States)

    Caumont, Olivier; Hally, Alan; Garrote, Luis; Richard, Évelyne; Weerts, Albrecht; Delogu, Fabio; Fiori, Elisabetta; Rebora, Nicola; Parodi, Antonio; Mihalović, Ana; Ivković, Marija; Dekić, Ljiljana; van Verseveld, Willem; Nuissier, Olivier; Ducrocq, Véronique; D'Agostino, Daniele; Galizia, Antonella; Danovaro, Emanuele; Clematis, Andrea

    2015-04-01

    The FP7 DRIHM (Distributed Research Infrastructure for Hydro-Meteorology, http://www.drihm.eu, 2011-2015) project intends to develop a prototype e-Science environment to facilitate the collaboration between meteorologists, hydrologists, and Earth science experts for accelerated scientific advances in Hydro-Meteorology Research (HMR). As the project comes to its end, this presentation will summarize the HMR results that have been obtained in the framework of DRIHM. The vision shaped and implemented in the framework of the DRIHM project enables the production and interpretation of numerous, complex compositions of hydrometeorological simulations of flood events from rainfall, either simulated or modelled, down to discharge. Each element of a composition is drawn from a set of various state-of-the-art models. Atmospheric simulations providing high-resolution rainfall forecasts involve different global and limited-area convection-resolving models, the former being used as boundary conditions for the latter. Some of these models can be run as ensembles, i.e. with perturbed boundary conditions, initial conditions and/or physics, thus sampling the probability density function of rainfall forecasts. In addition, a stochastic downscaling algorithm can be used to create high-resolution rainfall ensemble forecasts from deterministic lower-resolution forecasts. All these rainfall forecasts may be used as input to various rainfall-discharge hydrological models that compute the resulting stream flows for catchments of interest. In some hydrological simulations, physical parameters are perturbed to take into account model errors. As a result, six different kinds of rainfall data (either deterministic or probabilistic) can currently be compared with each other and combined with three different hydrological model engines running either in deterministic or probabilistic mode. HMR topics which are allowed or facilitated by such unprecedented sets of hydrometerological forecasts

  3. Modelling and optimization of land use/land cover change in a developing urban catchment.

    Science.gov (United States)

    Xu, Ping; Gao, Fei; He, Junchao; Ren, Xinxin; Xi, Weijin

    2017-06-01

    The impacts of land use/cover change (LUCC) on hydrological processes and water resources are mainly reflected in changes in runoff and pollutant variations. Low impact development (LID) technology is utilized as an effective strategy to control urban stormwater runoff and pollution in the urban catchment. In this study, the impact of LUCC on runoff and pollutants in an urbanizing catchment of Guang-Ming New District in Shenzhen, China, were quantified using a dynamic rainfall-runoff model with the EPA Storm Water Management Model (SWMM). Based on the simulations and observations, the main objectives of this study were: (1) to evaluate the catchment runoff and pollutant variations with LUCC, (2) to select and optimize the appropriate layout of LID in a planning scenario for reducing the growth of runoff and pollutants under LUCC, (3) to assess the optimal planning schemes for land use/cover. The results showed that compared to 2013, the runoff volume, peak flow and pollution load of suspended solids (SS), and chemical oxygen demand increased by 35.1%, 33.6% and 248.5%, and 54.5% respectively in a traditional planning scenario. The assessment result of optimal planning of land use showed that annual rainfall control of land use for an optimal planning scenario with LID technology was 65%, and SS pollutant load reduction efficiency 65.6%.

  4. Analysis of Nigerian Hydrometeorological Data | Dike | Nigerian ...

    African Journals Online (AJOL)

    Rainfall and runoff like most hydrologic events are governed by the laws of chance; hence, their predictions cannot be done in absolute terms. Since there is no universally accepted method for determining the likelihood of a certain magnitude of rainfall or runoff, common probabilistic models were used in this research to ...

  5. Modified Neutral Models as Benchmarks to Evaluate the Dynamics of Land System (DLS Model Performance

    Directory of Open Access Journals (Sweden)

    Yingchang Xiu

    2017-07-01

    Full Text Available Assessing model performance is a continuous challenge for modelers of land use change. Comparing land use models with two neutral models, including the random constraint match model (RCM and growing cluster model (GrC that consider the initial land use patterns using a variety of evaluation metrics, provides a new way to evaluate the accuracy of land use models. However, using only two neutral models is not robust enough for reference maps. A modified neutral model that combines a density-based point pattern analysis and a null neutral model algorithm is introduced. In this case, the modified neutral model generates twenty different spatial pattern results using a random algorithm and mid-point displacement algorithm, respectively. The random algorithm-based modified neutral model (Random_MNM results decrease regularly with the fragmentation degree from 0 to 1, while the mid-point displacement algorithm-based modified neutral model (MPD_MNM results decrease in a fluctuating manner with the fragmentation degree. Using the modified neutral model results as benchmarks, a new proposed land use model, the Dynamics of Land System (DLS model, for Jilin Province of China from 2003 to 2013 is assessed using the Kappa statistic and Kappain-out statistic for simulation accuracy. The results show that the DLS model output presents higher Kappa and Kappain-out values than all the twenty neutral model results. The map comparison results indicate that the DLS model could simulate land use change more accurately compared to the Random_MNM and MPD_MNM. However, the amount and spatial allocation of land transitions for the DLS model are lower than the actual land use change. Improving the accuracy of the land use transition allocations in the DLS model requires further investigation.

  6. Trans-African Hydro-Meteorological Observatory (TAHMO): A network to monitor weather, water, and climate in Africa

    Science.gov (United States)

    Van De Giesen, N.; Hut, R.; Andreini, M.; Selker, J. S.

    2013-12-01

    The Trans-African Hydro-Meteorological Observatory (TAHMO) has a goal to design, build, install and operate a dense network of hydro-meteorological monitoring stations in sub-Saharan Africa; one every 35 km. This corresponds to a total of 20,000 stations. By applying ICT and innovative sensors, each station should cost not more than $500. The stations would be placed at schools and integrated in the environmental curriculum. Data will be combined with models and satellite observations to obtain a very complete insight into the distribution of water and energy stocks and fluxes. Within this project, we have built a prototype of an acoustic disdrometer (rain gauge) that can be produced for much less than the cost of a commercial equivalent with the same specifications. The disdrometer was developed in The Netherlands and tested in Tanzania for a total project cost of Euro 5000. First tests have been run at junior high schools in Ghana to incorporate hydro-meteorological measurements in the science curriculum. The latest activity concerns the organization of a crowdsourcing competitions across Africa to address business development and the design and building of new robust sensors. This has resulted in a wide network throughout the continent to bring this program forward.

  7. Sensitivity of land surface modeling to parameters: An uncertainty quantification method applied to the Community Land Model

    Science.gov (United States)

    Ricciuto, D. M.; Mei, R.; Mao, J.; Hoffman, F. M.; Kumar, J.

    2015-12-01

    Uncertainties in land parameters could have important impacts on simulated water and energy fluxes and land surface states, which will consequently affect atmospheric and biogeochemical processes. Therefore, quantification of such parameter uncertainties using a land surface model is the first step towards better understanding of predictive uncertainty in Earth system models. In this study, we applied a random-sampling, high-dimensional model representation (RS-HDMR) method to analyze the sensitivity of simulated photosynthesis, surface energy fluxes and surface hydrological components to selected land parameters in version 4.5 of the Community Land Model (CLM4.5). Because of the large computational expense of conducting ensembles of global gridded model simulations, we used the results of a previous cluster analysis to select one thousand representative land grid cells for simulation. Plant functional type (PFT)-specific uniform prior ranges for land parameters were determined using expert opinion and literature survey, and samples were generated with a quasi-Monte Carlo approach-Sobol sequence. Preliminary analysis of 1024 simulations suggested that four PFT-dependent parameters (including slope of the conductance-photosynthesis relationship, specific leaf area at canopy top, leaf C:N ratio and fraction of leaf N in RuBisco) are the dominant sensitive parameters for photosynthesis, surface energy and water fluxes across most PFTs, but with varying importance rankings. On the other hand, for surface ans sub-surface runoff, PFT-independent parameters, such as the depth-dependent decay factors for runoff, play more important roles than the previous four PFT-dependent parameters. Further analysis by conditioning the results on different seasons and years are being conducted to provide guidance on how climate variability and change might affect such sensitivity. This is the first step toward coupled simulations including biogeochemical processes, atmospheric processes

  8. Towards A Grid Infrastructure For Hydro-Meteorological Research

    Directory of Open Access Journals (Sweden)

    Michael Schiffers

    2011-01-01

    Full Text Available The Distributed Research Infrastructure for Hydro-Meteorological Study (DRIHMS is a coordinatedaction co-funded by the European Commission. DRIHMS analyzes the main issuesthat arise when designing and setting up a pan-European Grid-based e-Infrastructure for researchactivities in the hydrologic and meteorological fields. The main outcome of the projectis represented first by a set of Grid usage patterns to support innovative hydro-meteorologicalresearch activities, and second by the implications that such patterns define for a dedicatedGrid infrastructure and the respective Grid architecture.

  9. Development of a prototype land use model for statewide transportation planning activities : summary.

    Science.gov (United States)

    2011-01-01

    Developing computer models of land use and : integrated transportation-land use are high : priorities for Florida transportation planners. : Land use information is fundamental to siting : roadways, signaling, setting maintenance : priorities, routin...

  10. Land Surface Model (LSM 1.0) for Ecological, Hydrological, Atmospheric Studies

    Data.gov (United States)

    National Aeronautics and Space Administration — The NCAR LSM 1.0 is a land surface model developed to examine biogeophysical and biogeochemical land-atmosphere interactions, especially the effects of land surfaces...

  11. Opportunities to Improve Impact, Integration, and Evaluation of Land Change Models

    NARCIS (Netherlands)

    Brown, D.G.; Verburg, P.H.; Pontius, R.G.; Lange, M.D.

    2013-01-01

    Land change modeling supports analyses, assessments, and decisions concerning land management by providing a platform for both encoding mechanisms of land-change processes and making projections of future land-cover and land-use patterns. Approaches have ranged from pattern-based methods, such as

  12. Fuzzy modeling of farmers' knowledge for land suitability classification

    NARCIS (Netherlands)

    Sicat, R.S.; Carranza, E.J.M.; Nidumolu, U.B.

    2005-01-01

    In a case study, we demonstrate fuzzy modeling of farmers' knowledge (FK) for agricultural land suitability classification using GIS. Capture of FK was through rapid rural participatory approach. The farmer respondents consider, in order of decreasing importance, cropping season, soil color, soil

  13. ISO 19152 : 2012, Land Administration Domain Model published by ISO

    NARCIS (Netherlands)

    Van Oosterom, P.; Lemmen, C.; Uitermark, H.

    2013-01-01

    This paper describes the last developments of the Land Administration Domain Model (LADM). The Final Draft International Standard, ISO FDIS 19152, unanimously passed on 1 November 2012 the final vote towards becoming an International Standard (IS). After technical editing by ISO secretariat in

  14. Possibilities of Land Administration Domain Model (LADM) implementation in Nigeria

    NARCIS (Netherlands)

    Babalola, S.O.; Rahman, A.A.; Choon, L.T.; Van Oosterom, P.J.M.

    2015-01-01

    LADM covers essential information associated components of land administration and management including those over water and elements above and below the surface of the earth. LADM standard provides an abstract conceptual model with three packages and one sub-package. LADM defined terminology for a

  15. Modelling the Landing of a Plane in a Calculus Lab

    Science.gov (United States)

    Morante, Antonio; Vallejo, Jose A.

    2012-01-01

    We exhibit a simple model of a plane landing that involves only basic concepts of differential calculus, so it is suitable for a first-year calculus lab. We use the computer algebra system Maxima and the interactive geometry software GeoGebra to do the computations and graphics. (Contains 5 figures and 1 note.)

  16. developing a one stop shop model for integrated land information

    African Journals Online (AJOL)

    DEPT OF AGRICULTURAL ENGINEERING

    ABSTRACT. In Ghana much attention has not been given to the development of land information system which will integrate the data on land ownership, land use and land value for all the land agen- cies under the land administration system to facilitate the processing of applications within the land delivery systems.

  17. Modeling land-surface processes and land-atmosphere interactions in the community weather and regional climate WRF model (Invited)

    Science.gov (United States)

    Chen, F.; Barlage, M. J.

    2013-12-01

    The Weather Research and Forecasting (WRF) model has been widely used with high-resolution configuration in the weather and regional climate communities, and hence demands its land-surface models to treat not only fast-response processes, such as plant evapotranspiration that are important for numerical weather prediction but also slow-evolving processes such as snow hydrology and interactions between surface soil water and deep aquifer. Correctly representing urbanization, which has been traditionally ignored in coarse-resolution modeling, is critical for applying WRF to air quality and public health research. To meet these demands, numerous efforts have been undertaken to improve land-surface models (LSM) in WRF, including the recent implementation of the Noah-MP (Noah Multiple-Physics). Noah-MP uses multiple options for key sub-grid land-atmosphere interaction processes (Niu et al., 2011; Yang et al., 2011), and contains a separate vegetation canopy representing within- and under-canopy radiation and turbulent processes, a multilayer physically-based snow model, and a photosynthesis canopy resistance parameterization with a dynamic vegetation model. This paper will focus on the interactions between fast and slow land processes through: 1) a benchmarking of the Noah-MP performance, in comparison to five widely-used land-surface models, in simulating and diagnosing snow evolution for complex terrain forested regions, and 2) the effects of interactions between shallow and deep aquifers on regional weather and climate. Moreover, we will provide an overview of recent improvements of the integrated WRF-Urban modeling system, especially its hydrological enhancements that takes into account the effects of lawn irrigation, urban oasis, evaporation from pavements, anthropogenic moisture sources, and a green-roof parameterization.

  18. Hydrometeorologic impacts of urban expansion and the role of spatial arrangement (Invited)

    Science.gov (United States)

    Bowling, L. C.

    2013-12-01

    Global land cover/land use is changing notably due to expansion of urban areas, resulting in the conversion of natural landscapes to roads, industrial areas, and buildings. The associated reduction in infiltration and runoff lag time have long been the domain of the urban hydrologist, while this landscape transformation also leads to changes in land surface heterogeneities, resulting in alterations of land-atmosphere interactions and convective processes. The integrated impacts of both impervious area and precipitation changes to flood risk in urban environments have not been well-represented by existing predictive tools, which often focus at disparate scales. This presentation attempts an integrated assessment of the multi-scale interaction of urban landcover, hydrology and convective processes, in order to investigate how urbanization has altered the hydrometeorology of urban thunderstorm events, and the role of the spatial arrangement and scale of urban landcover on urban flood frequency. Studies suggest that in some cases, urban influence creates a convergence zone upstream of the urban area, resulting in precipitation increases both upstream and downstream of the urban influence. Total runoff increases consistently with urbanization by restricting infiltration on the land surface, but this is coupled with high uncertainty in the spatial pattern of precipitation change. For some watersheds, the convective influence can result in a significant increase in peak streamflow, relative to impervious influence alone. The spatial pattern of urban development can further affect the hydrologic regime by influencing the hydrologic connectivity of urban areas at the catchment scale, while at the river basin scale the travel time from urban centers to the watershed outlet controls flood magnitudes.

  19. Polar motion excitation from several models of land hydrosphere

    Science.gov (United States)

    Nastula, Jolanta

    2017-04-01

    The impact of land hydrosphere mass variations on polar motion excitation is still not sufficiently estimated and not known as well as the role of the atmosphere and ocean. A comparison of the hydrological excitation function (Hydrological Angular Momentum - HAM) with observed geodetic excitation functions (GAM) is a common method of assessing of the influence of land hydrology on polar motion excitation function. HAM can be estimated either from global models of the land hydrosphere or from the Earth's gravity field variations. Our previous attempt to assess the role of land hydrology in the excitation balance using the hydrological angular momentum (HAM) estimates from Gravity Recovery and Climate Experiment (GRACE) data and hydrological models was not conclusive (Brzeziński et al., 2009, Nastula et al., 2011, Wińska et al., 2016). We found for example that gravimetric-hydrological excitation functions, based on the Gravity and Climate Recovery Experiment (GRACE) gravity fiels determined from the several processing centers differed significantly. Additionally hydrological excitation computed from different hydrological models differed significantly in amplitudes and phases. In this work we re - estimate hydrological polar motion excitation functions from several hydrological models and climate models and from GRACE gravity fields. Our investigations are focused on the influence of land hydrosphere on polar motion excitation functions at seasonal and non-seasonal time scales and comprises two steps: • first determinations hydrological excitation functions (HAM) from regional distribution of Terrestrial Water Storage (TWS). • the second comparison of the global HAM with hydrological signal in the observed geodetic excitation function of polar motion.

  20. Downscaling and hydrological uncertainties in 20th century hydrometeorological reconstructions over France

    Science.gov (United States)

    Vidal, Jean-Philippe; Caillouet, Laurie; Dayon, Gildas; Boé, Julien; Sauquet, Eric; Thirel, Guillaume; Graff, Benjamin

    2017-04-01

    The record length of streamflow observations is generally limited to the last 50 years, which is not enough to properly explore the natural hydrometeorological variability, a key to better understand the effects of anthropogenic climate change. This work proposes a comparison of different hydrometeorological reconstruction datasets over France built on the downscaling of the NOAA 20th century global extended reanalysis (20CR, Compo et al., 2011). It aims at assessing the uncertainties related to these reconstructions and improving our knowledge of the multi-decadal hydrometeorological variability over the 20th century. High-resolution daily meteorological reconstructions over the period 1871-2012 are obtained with two statistical downscaling methods based on the analogue approach: the deterministic ANALOG method (Dayon et al., 2015) and the probabilistic SCOPE method (Caillouet et al., 2016). These reconstructions are then used as forcings for the GR6J lumped conceptual rainfall-runoff model and the SIM physically-based distributed hydrological model, in order to derive daily streamflow reconstructions over a set of around 70 reference near-natural catchments. Results show a large multi-decadal streamflow variability over the last 140 years, which is however relatively consistent over France. Empirical estimates of three types of uncertainty - structure of the downscaling method, small-scale internal variability, and hydrological model structure - show roughly equal contributions to the streamflow uncertainty at the annual time scale, with values as high as 20% of the interannual mean. Caillouet, L., Vidal, J.-P., Sauquet, E., and Graff, B.: Probabilistic precipitation and temperature downscaling of the Twentieth Century Reanalysis over France, Clim. Past, 12, 635-662, doi:10.5194/cp-12-635-2016, 2016. Compo, G. P., Whitaker, J. S., Sardeshmukh, P. D., Matsui, N., Allan, R. J., Yin, X., Gleason, B. E., Vose, R. S., Rutledge, G., Bessemoulin, P., Brönnimann, S

  1. Spatial aggregation of land surface characteristics : impact of resolution of remote sensing data on land surface modelling

    NARCIS (Netherlands)

    Pelgrum, H.

    2000-01-01

    Land surface models describe the exchange of heat, moisture and momentum between the land surface and the atmosphere. These models can be solved regionally using remote sensing measurements as input. Input variables which can be derived from remote sensing measurements are surface albedo,

  2. Farmer-specific relationships between land use change and landscape factors: Introducing agents in empirical land use modelling

    NARCIS (Netherlands)

    Bakker, M.M.; Doorn, van A.M.

    2009-01-01

    Traditional empirical land use change models generally assume one average land use decision-maker. Multi-Agent System (MAS) models, on the other hand, acknowledge existence of different types of agents, but their poor empirical embedding remains a serious handicap. This paper demonstrates how agent

  3. Applicability of land use models for the Houston area test site

    Science.gov (United States)

    Petersburg, R. K.; Bradford, L. H.

    1973-01-01

    Descriptions of land use models are presented which were considered for their applicability to the Houston Area Test Site. These models are representative both of the prevailing theories of land use dynamics and of basic approaches to simulation. The models considered are: a model of metropolis, land use simulation model, emperic land use forecasting model, a probabilistic model for residential growth, and the regional environmental management allocation process. Sources of environmental/resource information are listed.

  4. Modelling regional land change scenarios to assess land abandonment and reforestation dynamics in the Pyrenees (France)

    Science.gov (United States)

    Vacquie, Laure; Houet, Thomas; Sohl, Terry L.; Reker, Ryan; Sayler, Kristi L.

    2015-01-01

    Over the last decades and centuries, European mountain landscapes have experienced substantial transformations. Natural and anthropogenic LULC changes (land use and land cover changes), especially agro-pastoral activities, have directly influenced the spatial organization and composition of European mountain landscapes. For the past sixty years, natural reforestation has been occurring due to a decline in both agricultural production activities and rural population. Stakeholders, to better anticipate future changes, need spatially and temporally explicit models to identify areas at risk of land change and possible abandonment. This paper presents an integrated approach combining forecasting scenarios and a LULC changes simulation model to assess where LULC changes may occur in the Pyrenees Mountains, based on historical LULC trends and a range of future socio-economic drivers. The proposed methodology considers local specificities of the Pyrenean valleys, sub-regional climate and topographical properties, and regional economic policies. Results indicate that some regions are projected to face strong abandonment, regardless of the scenario conditions. Overall, high rates of change are associated with administrative regions where land productivity is highly dependent on socio-economic drivers and climatic and environmental conditions limit intensive (agricultural and/or pastoral) production and profitability. The combination of the results for the four scenarios allows assessments of where encroachment (e.g. colonization by shrublands) and reforestation are the most probable. This assessment intends to provide insight into the potential future development of the Pyrenees to help identify areas that are the most sensitive to change and to guide decision makers to help their management decisions.

  5. Land-atmosphere interactions due to anthropogenic and natural changes in the land surface: A numerical modeling study

    Science.gov (United States)

    Yang, Zhao

    Alterations to the land surface can be attributed to both human activity and natural variability. Human activities, such as urbanization and irrigation, can change the conditions of the land surface by altering albedo, soil moisture, aerodynamic roughness length, the partitioning of net radiation into sensible and latent heat, and other surface characteristics. On the other hand, natural variability, manifested through changes in atmospheric circulation, can also induce land surface changes. These regional scale land surface changes, induced either by humans or natural variability, can effectively modify atmospheric conditions through land-atmosphere interactions. However, only in recent decades have numerical models begun to include representations of the critical processes driving changes at the land surface, and their associated effects on the overlying atmosphere. In this work we explore three mechanisms by which changes to the land surface - both anthropogenic and naturally induced - impact the overlying atmosphere and affect regional hydroclimate. (Abstract shortened by ProQuest.).

  6. Photosynthesis sensitivity to climate change in land surface models

    Science.gov (United States)

    Manrique-Sunen, Andrea; Black, Emily; Verhoef, Anne; Balsamo, Gianpaolo

    2016-04-01

    Accurate representation of vegetation processes within land surface models is key to reproducing surface carbon, water and energy fluxes. Photosynthesis determines the amount of CO2 fixated by plants as well as the water lost in transpiration through the stomata. Photosynthesis is calculated in land surface models using empirical equations based on plant physiological research. It is assumed that CO2 assimilation is either CO2 -limited, radiation -limited ; and in some models export-limited (the speed at which the products of photosynthesis are used by the plant) . Increased levels of atmospheric CO2 concentration tend to enhance photosynthetic activity, but the effectiveness of this fertilization effect is regulated by environmental conditions and the limiting factor in the photosynthesis reaction. The photosynthesis schemes at the 'leaf level' used by land surface models JULES and CTESSEL have been evaluated against field photosynthesis observations. Also, the response of photosynthesis to radiation, atmospheric CO2 and temperature has been analysed for each model, as this is key to understanding the vegetation response that climate models using these schemes are able to reproduce. Particular emphasis is put on the limiting factor as conditions vary. It is found that while at present day CO2 concentrations export-limitation is only relevant at low temperatures, as CO2 levels rise it becomes an increasingly important restriction on photosynthesis.

  7. Land

    CSIR Research Space (South Africa)

    Audouin, M

    2007-01-01

    Full Text Available Unsustainable agricultural practices have had a role to play in the degradation of land on which agriculture depends. South Africa has an international obligation to develop a National Action Programme (NAP), the purpose of which is to identify...

  8. Improved Analyses and Forecasts of Snowpack, Runoff and Drought through Remote Sensing and Land Surface Modeling in Southeastern Europe

    Science.gov (United States)

    Matthews, D.; Brilly, M.; Gregoric, G.; Polajnar, J.; Kobold, M.; Zagar, M.; Knoblauch, H.; Staudinger, M.; Mecklenburg, S.; Lehning, M.; Schweizer, J.; Balint, G.; Cacic, I.; Houser, P.; Pozzi, W.

    2008-12-01

    European hydrometeorological services and research centers are faced with increasing challenges from extremes of weather and climate that require significant investments in new technology and better utilization of existing human and natural resources to provide improved forecasts. Major advances in remote sensing, observation networks, data assimilation, numerical modeling, and communications continue to improve our ability to disseminate information to decision-makers and stake holders. This paper identifies gaps in current technologies, key research and decision-maker teams, and recommends means for moving forward through focused applied research and integration of results into decision support tools. This paper reports on the WaterNet - NASA Water Cycle Solutions Network contacts in Europe and summarizes progress in improving water cycle related decision-making using NASA research results. Products from the Hydrologic Sciences Branch, Goddard Space Flight Center, NASA, Land Information System's (LIS) Land Surface Models (LSM), the SPoRT, CREW , and European Space Agency (ESA), and Joint Research Center's (JRC) natural hazards products, and Swiss Federal Institute for Snow and Avalanche Research's (SLF), and others are discussed. They will be used in collaboration with the ESA and the European Commission to provide solutions for improved prediction of water supplies and stream flow, and droughts and floods, and snow avalanches in the major river basins serviced by EARS, ZAMG, SLF, Vituki Consult, and other European forecast centers. This region of Europe includes the Alps and Carpathian Mountains and is an area of extreme topography with abrupt 2000 m mountains adjacent to the Adriatic Sea. These extremes result in the highest precipitation ( > 5000 mm) in Europe in Montenegro and low precipitation of 300-400 mm at the mouth of the Danube during droughts. The current flood and drought forecasting systems have a spatial resolution of 9 km, which is currently being

  9. Model meets data: Challenges and opportunities to implement land management in Earth System Models

    Science.gov (United States)

    Pongratz, Julia; Dolman, Han; Don, Axel; Erb, Karl-Heinz; Fuchs, Richard; Herold, Martin; Jones, Chris; Luyssaert, Sebastiaan; Kuemmerle, Tobias; Meyfroidt, Patrick; Naudts, Kim

    2017-04-01

    Land-based demand for food and fibre is projected to increase in the future. In light of global sustainability challenges only part of this increase will be met by expansion of land use into relatively untouched regions. Additional demand will have to be fulfilled by intensification and other adjustments in management of land that already is under agricultural and forestry use. Such land management today occurs on about half of the ice-free land surface, as compared to only about one quarter that has undergone a change in land cover. As the number of studies revealing substantial biogeophysical and biogeochemical effects of land management is increasing, moving beyond land cover change towards including land management has become a key focus for Earth system modeling. However, a basis for prioritizing land management activities for implementation in models is lacking. We lay this basis for prioritization in a collaborative project across the disciplines of Earth system modeling, land system science, and Earth observation. We first assess the status and plans of implementing land management in Earth system and dynamic global vegetation models. A clear trend towards higher complexity of land use representation is visible. We then assess five criteria for prioritizing the implementation of land management activities: (1) spatial extent, (2) evidence for substantial effects on the Earth system, (3) process understanding, (4) possibility to link the management activity to existing concepts and structures of models, (5) availability of data required as model input. While the first three criteria have been assessed by an earlier study for ten common management activities, we review strategies for implementation in models and the availability of required datasets. We can thus evaluate the management activities for their performance in terms of importance for the Earth system, possibility of technical implementation in models, and data availability. This synthesis reveals

  10. Statistical Models of Areal Distribution of Fragmented Land Cover Types

    Science.gov (United States)

    Hlavka, C.; Dungan, J.; DAntoni, Hector

    1997-01-01

    Imagery of coarse resolution, such weather satellite imagery with 1 square kilometer pixels, is increasingly used to monitor dynamic and fragmented types of land surface types, such as scars from recent fires and ponds in wetlands. Accurate estimates of these land cover types at regional to global scales are required to assess the roles of fires and wetlands in global warming, yet difficult to compute when much of the area is accounted for by fragments about the same size as the pixels. In previous research, we found that size distribution of the fragments in several example scenes fit simple two-parameter models and related effects of coarse resolution to errors in area estimates based on pixel counts. We summarize our model based approach to improved area estimations and report on progress to develop accurate areas estimates based on modeling the size distribution of the fragments, including analysis of size distributions on an expanded set of maps developed from digital imagery.

  11. Integrating land management into Earth system models: the importance of land use transitions at sub-grid-scale

    Science.gov (United States)

    Pongratz, Julia; Wilkenskjeld, Stiig; Kloster, Silvia; Reick, Christian

    2014-05-01

    Recent studies indicate that changes in surface climate and carbon fluxes caused by land management (i.e., modifications of vegetation structure without changing the type of land cover) can be as large as those caused by land cover change. Further, such effects may occur on substantial areas: while about one quarter of the land surface has undergone land cover change, another fifty percent are managed. This calls for integration of management processes in Earth system models (ESMs). This integration increases the importance of awareness and agreement on how to diagnose effects of land use in ESMs to avoid additional model spread and thus unnecessary uncertainties in carbon budget estimates. Process understanding of management effects, their model implementation, as well as data availability on management type and extent pose challenges. In this respect, a significant step forward has been done in the framework of the current IPCC's CMIP5 simulations (Coupled Model Intercomparison Project Phase 5): The climate simulations were driven with the same harmonized land use dataset that, different from most datasets commonly used before, included information on two important types of management: wood harvest and shifting cultivation. However, these new aspects were employed by only part of the CMIP5 models, while most models continued to use the associated land cover maps. Here, we explore the consequences for the carbon cycle of including subgrid-scale land transformations ("gross transitions"), such as shifting cultivation, as example of the current state of implementation of land management in ESMs. Accounting for gross transitions is expected to increase land use emissions because it represents simultaneous clearing and regrowth of natural vegetation in different parts of the grid cell, reducing standing carbon stocks. This process cannot be captured by prescribing land cover maps ("net transitions"). Using the MPI-ESM we find that ignoring gross transitions

  12. The impact of standard and hard-coded parameters on the hydrologic fluxes in the Noah-MP land surface model

    Science.gov (United States)

    Thober, S.; Cuntz, M.; Mai, J.; Samaniego, L. E.; Clark, M. P.; Branch, O.; Wulfmeyer, V.; Attinger, S.

    2016-12-01

    Land surface models incorporate a large number of processes, described by physical, chemical and empirical equations. The agility of the models to react to different meteorological conditions is artificially constrained by having hard-coded parameters in their equations. Here we searched for hard-coded parameters in the computer code of the land surface model Noah with multiple process options (Noah-MP) to assess the model's agility during parameter estimation. We found 139 hard-coded values in all Noah-MP process options in addition to the 71 standard parameters. We performed a Sobol' global sensitivity analysis to variations of the standard and hard-coded parameters. The sensitivities of the hydrologic output fluxes latent heat and total runoff, their component fluxes, as well as photosynthesis and sensible heat were evaluated at twelve catchments of the Eastern United States with very different hydro-meteorological regimes. Noah-MP's output fluxes are sensitive to two thirds of its standard parameters. The most sensitive parameter is, however, a hard-coded value in the formulation of soil surface resistance for evaporation, which proved to be oversensitive in other land surface models as well. Latent heat and total runoff show very similar sensitivities towards standard and hard-coded parameters. They are sensitive to both soil and plant parameters, which means that model calibrations of hydrologic or land surface models should take both soil and plant parameters into account. Sensible and latent heat exhibit almost the same sensitivities so that calibration or sensitivity analysis can be performed with either of the two. Photosynthesis has almost the same sensitivities as transpiration, which are different from the sensitivities of latent heat. Including photosynthesis and latent heat in model calibration might therefore be beneficial. Surface runoff is sensitive to almost all hard-coded snow parameters. These sensitivities get, however, diminished in total

  13. Customary land tenure dynamics at peri-urban Ghana : Implications for land administration system modeling

    NARCIS (Netherlands)

    Arko-Adjei, A.; de Jong, J.; Zevenbergen, J.A.; Tuladhar, A.M.

    2009-01-01

    Customary land tenure is criticized as dynamic with the institutional framework unable to provide enough tenure security at all times. It is also criticized as ineffective to cope with the trends in land tenure delivery at peri-urban areas where individualization of land and demand for land is high.

  14. Hydrometeorological conditions preceding wildfire, and the subsequent burning of a fen watershed in Fort McMurray, Alberta, Canada

    Science.gov (United States)

    Elmes, Matthew C.; Thompson, Dan K.; Sherwood, James H.; Price, Jonathan S.

    2018-01-01

    The destructive nature of the ˜ 590 000 ha Horse river wildfire in the Western Boreal Plain (WBP), northern Alberta, in May of 2016 motivated the investigation of the hydrometeorological conditions that preceded the fire. Historical climate and field hydrometeorological data from a moderate-rich fen watershed were used to (a) identify whether the spring 2016 conditions were outside the range of natural variability for WBP climate cycles, (b) explain the observed patterns in burn severity across the watershed, and (c) identify whether fall and winter moisture signals observed in peatlands and lowland forests in the region are indicative of wildfire. Field hydrometeorological data from the fen watershed confirmed the presence of cumulative moisture deficits prior to the fire. Hydrogeological investigations highlighted the susceptibility of fen and upland areas to water table and soil moisture decline over rain-free periods (including winter), due to the watershed's reliance on supply from localized flow systems originating in topographic highs. Subtle changes in topographic position led to large changes in groundwater connectivity, leading to greater organic soil consumption by fire in wetland margins and at high elevations. The 2016 spring moisture conditions measured prior to the ignition of the fen watershed were not illustrated well by the Drought Code (DC) when standard overwintering procedures were applied. However, close agreement was found when default assumptions were replaced with measured duff soil moisture recharge and incorporated into the overwintering DC procedure. We conclude that accumulated moisture deficits dating back to the summer of 2015 led to the dry conditions that preceded the fire. The infrequent coinciding of several hydrometeorological conditions, including low autumn soil moisture, a modest snowpack, lack of spring precipitation, and high spring air temperatures and winds, ultimately led to the Horse river wildfire spreading widely and

  15. Introducing preference heterogenity into a monocentric urban model: an agent-based land market model

    OpenAIRE

    Filatova, Tatiana; Parker, Dawn C.; van der Veen, A.; George Mason University

    2008-01-01

    This paper presents an agent-based urban land market model. We first replace the centralized price determination mechanism of the monocentric urban market model with a series of bilateral trades distributed in space and time. We then run the model for agents with heterogeneous preferences for location. Model output is analyzed using a series of macro-scale economic and landscape pattern measures, including land rent gradients estimated using simple regression. We demonstrate that heterogeneit...

  16. The hydrometeorological sustainability of Miscanthus x giganteus as a biofuel crop in the US Midwest

    Science.gov (United States)

    Roy, Gavin R.

    Miscanthus x giganteus (M. x giganteus ) is a dense, 3-5 m tall, productive perennial grass that has been suggested to replace corn as the principal source of biofuel for the US transportation industry. However, cultivating a regime of this water-intensive rhizomatous crop across the US Midwest may not be agronomically realistic if it is unable to survive years of low precipitation or extreme cold wintertime soil temperatures, both of which have previously killed experimental crops. The goal of this research was to use a third-generation land surface model (LSM) to provide a new assessment of the hypothetical biogeophysical sustainability of a regime of M. x giganteus across the US Midwest given that, for the first time, a robust and near-complete dataset over a large area of mature M. x giganteus was available for model validation. Modifications to the local hydrology and microclimate would necessarily occur in areas where M. x giganteus is adapted, but a switch to this biofuel crop can only occur where its intense growing season water usage (up to 600 mm) and wintertime soil temperature requirements (no less than -6° C) are feasibly sustainable without irrigation. The first step was to interpret the observed turbulent and ecosystem flux behavior over an extant area of mature M. x giganteus and replicate this behavior within the SiB3 third-generation LSM (Simple Biosphere Model, version 3). A new vegetation parameterization was developed in SiB3 using several previous empirical studies of M. x giganteus as a foundation. The simulation results were validated against a new, robust series of turbulent and ecosystem flux data taken over a four-hectare experimental crop of M. x giganteus in Champaign, IL, USA from 2011-2013. Wintertime mortality of M. x giganteus was subsequently assessed. It was proposed that areas with higher seasonal snowfall in the US Midwest may be favorable for M. x giganteus sustainability and expansion due to the significant insulating effect

  17. An Extended-range Hydrometeorological Ensemble Prediction System for Alpine Catchments in Switzerland

    Science.gov (United States)

    Monhart, Samuel; Bogner, Konrad; Spirig, Christoph; Bhend, Jonas; Liniger, Mark A.; Zappa, Massimiliano; Schär, Christoph

    2017-04-01

    In recent years meteorological ensemble prediction systems have increasingly be used to feed hydrological models in order to provide probabilistic streamflow forecasts. Such hydrological ensemble prediction systems (HEPS) have been analyzed for different lead times from short-term to seasonal predictions and are used for different applications. Especially at longer lead times both such forecasts exhibit systematic biases which can be removed by applying bias correction techniques to both the meteorological and/or the hydrological output. However, it is still an open question if pre- or post-processing techniques or both should be applied. We will present first results of the analysis of pre- and post-processed extended-range hydrometeorological forecasts. In a first step the performance of bias corrected and downscaled (using quantile mapping) extended-range meteorological forecasts provided by the ECMWF is assessed for approximately 1000 ground observation sites across Europe. Generally, bias corrected meteorological forecasts show positive skill in terms of CRPSS up to three (two) weeks for weekly mean temperature (precipitation) compared to climatological forecasts. For the Alpine region the absolute skill is generally lower but the relative gain in skill resulting from the bias correction is larger. These pre-processed meteorological forecasts of one year of ECMWF extended-range forecasts and corresponding hindcasts are used to feed a hydrological model for a selected catchment in the Alpine area in Switzerland. Furthermore, different post-processing techniques are tested to correct the resulting streamflow forecasts. This will allow to determine the relative effect of pre- and post-processing of extended-range hydrometeorological predictions in Alpine catchments. Future work will include the combination of these corrected streamflow forecasts with electricity price forecasts to optimize the operations and revenues of hydropower systems in the Alps.

  18. Examining the Impacts of High-Resolution Land Surface Initialization on Model Predictions of Convection in the Southeastern U.S.

    Science.gov (United States)

    Case, Jonathan L.; Kumar, Sujay V.; Santos, Pablo; Medlin, Jeffrey M.; Jedlovec, Gary J.

    2009-01-01

    One of the most challenging weather forecast problems in the southeastern U.S. is daily summertime pulse convection. During the summer, atmospheric flow and forcing are generally weak in this region; thus, convection typically initiates in response to local forcing along sea/lake breezes, and other discontinuities often related to horizontal gradients in surface heating rates. Numerical simulations of pulse convection usually have low skill, even in local predictions at high resolution, due to the inherent chaotic nature of these precipitation systems. Forecast errors can arise from assumptions within physics parameterizations, model resolution limitations, as well as uncertainties in both the initial state of the atmosphere and land surface variables such as soil moisture and temperature. For this study, it is hypothesized that high-resolution, consistent representations of surface properties such as soil moisture and temperature, ground fluxes, and vegetation are necessary to better simulate the interactions between the land surface and atmosphere, and ultimately improve predictions of local circulations and summertime pulse convection. The NASA Short-term Prediction Research and Transition (SPORT) Center has been conducting studies to examine the impacts of high-resolution land surface initialization data generated by offline simulations of the NASA Land Informatiot System (LIS) on subsequent numerical forecasts using the Weather Research and Forecasting (WRF) model (Case et al. 2008, to appear in the Journal of Hydrometeorology). Case et al. presents improvements to simulated sea breezes and surface verification statistics over Florida by initializing WRF with land surface variables from an offline LIS spin-up run, conducted on the exact WRF domain and resolution. The current project extends the previous work over Florida, focusing on selected case studies of typical pulse convection over the southeastern U.S., with an emphasis on improving local short-term WRF

  19. Optimal land use/land cover classification using remote sensing imagery for hydrological modeling in a Himalayan watersched

    NARCIS (Netherlands)

    Saran, S.; Sterk, G.; Kumar, S.

    2009-01-01

    Land use/land cover is an important watershed surface characteristic that affects surface runoff and erosion. Many of the available hydrological models divide the watershed into Hydrological Response Units (HRU), which are spatial units with expected similar hydrological behaviours. The division

  20. Modeling and simulating industrial land-use evolution in Shanghai, China

    Science.gov (United States)

    Qiu, Rongxu; Xu, Wei; Zhang, John; Staenz, Karl

    2017-08-01

    This study proposes a cellular automata-based Industrial and Residential Land Use Competition Model to simulate the dynamic spatial transformation of industrial land use in Shanghai, China. In the proposed model, land development activities in a city are delineated as competitions among different land-use types. The Hedonic Land Pricing Model is adopted to implement the competition framework. To improve simulation results, the Land Price Agglomeration Model was devised to simulate and adjust classic land price theory. A new evolutionary algorithm-based parameter estimation method was devised in place of traditional methods. Simulation results show that the proposed model closely resembles actual land transformation patterns and the model can not only simulate land development, but also redevelopment processes in metropolitan areas.

  1. Usefulness of spatially explicit population models in land management

    Energy Technology Data Exchange (ETDEWEB)

    Turner, M.G. [Oak Ridge National Lab., TN (United States); Arthaud, G.J. [Univ. of Georgia, Athens, GA (United States); Engstrom, R.T. [Tall Timbers Research, Inc., Tallahassee, FL (United States); Hejl, S.J. [US Forest Service, Missoula, MT (United States); Liu, Jianguo [Harvard Institute for International Development, Cambridge, MA (United States); Loeb, S. [Clemson Univ., SC (United States); McKelvey, K. [US Forest Service, Arcata, CA (United States)

    1995-02-01

    Land managers need new tools, such as spatial models, to aid them in their decision-making processes because managing for biodiversity, water quality, or natural disturbance is challenging, and landscapes are complex and dynamic. Spatially explicit population models are helpful to managers because these models consider both species - habitat relationships and the arrangement of habitats in space and time. The visualizations that typically accompany spatially explicit models also permit managers to {open_quotes}see{close_quotes} the effects of alternative management strategies on populations of interest. However, the expense entailed in developing the data bases required for spatially explicit models may limit widespread implementation. In addition, many of the models are developed for one or a few species, and dealing with multiple species in a landscape remains a significant challenge. To be most useful to land managers, spatially explicit population models should be user friendly, easily portable, operate on spatial and temporal scales appropriate to management decisions, and use input and output variables that can be measured affordably. 20 refs.

  2. A land-use and land-cover modeling strategy to support a national assessment of carbon stocks and fluxes

    Science.gov (United States)

    Sohl, Terry L.; Sleeter, Benjamin M.; Zhu, Zhi-Liang; Sayler, Kristi L.; Bennett, Stacie; Bouchard, Michelle; Reker, Ryan; Hawbaker, Todd; Wein, Anne; Liu, Shu-Guang; Kanengieter, Ronald; Acevedo, William

    2012-01-01

    Changes in land use, land cover, disturbance regimes, and land management have considerable influence on carbon and greenhouse gas (GHG) fluxes within ecosystems. Through targeted land-use and land-management activities, ecosystems can be managed to enhance carbon sequestration and mitigate fluxes of other GHGs. National-scale, comprehensive analyses of carbon sequestration potential by ecosystem are needed, with a consistent, nationally applicable land-use and land-cover (LULC) modeling framework a key component of such analyses. The U.S. Geological Survey has initiated a project to analyze current and projected future GHG fluxes by ecosystem and quantify potential mitigation strategies. We have developed a unique LULC modeling framework to support this work. Downscaled scenarios consistent with IPCC Special Report on Emissions Scenarios (SRES) were constructed for U.S. ecoregions, and the FORE-SCE model was used to spatially map the scenarios. Results for a prototype demonstrate our ability to model LULC change and inform a biogeochemical modeling framework for analysis of subsequent GHG fluxes. The methodology was then successfully used to model LULC change for four IPCC SRES scenarios for an ecoregion in the Great Plains. The scenario-based LULC projections are now being used to analyze potential GHG impacts of LULC change across the U.S.

  3. Hydrometeorological Hazards: Monitoring, Forecasting, Risk Assessment, and Socioeconomic Responses

    Energy Technology Data Exchange (ETDEWEB)

    Wu, Huan [University of Maryland, College Park, MD, USA; NASA Goddard Space Flight Center, Greenbelt, MD, USA; Huang, Maoyi [Pacific Northwest National Laboratory, Richland, WA, USA; Tang, Qiuhong [Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China; Kirschbaum, Dalia B. [NASA Goddard Space Flight Center, Greenbelt, MD, USA; Ward, Philip [Vrije Universiteit, Amsterdam, Netherlands

    2016-01-01

    Hydrometeorological hazards are caused by extreme meteorological and climate events, such as floods, droughts, hurricanes, tornadoes, or landslides. They account for a dominant fraction of natural hazards and occur in all regions of the world, although the frequency and intensity of certain hazards, and society’s vulnerability to them, differs between regions. Severe storms, strong winds, floods and droughts develop at different spatial and temporal scales, but all can become disasters that cause significant infrastructure damage and claim hundreds of thousands of lives annually worldwide. Oftentimes, multiple hazards can occur simultaneously or trigger cascading impacts from one extreme weather event. For example, in addition to causing injuries, deaths and material damage, a tropical storm can also result in flooding and mudslides, which can disrupt water purification and sewage disposal systems, cause overflow of toxic wastes, and increase propagation of mosquito-borne diseases.

  4. Hydrometeorological Hazards: Monitoring, Forecasting, Risk Assessment, and Socioeconomic Responses

    Science.gov (United States)

    Wu, Huan; Huang, Maoyi; Tang, Qiuhong; Kirschbaum, Dalia B.; Ward, Philip

    2017-01-01

    Hydrometeorological hazards are caused by extreme meteorological and climate events, such as floods, droughts, hurricanes,tornadoes, or landslides. They account for a dominant fraction of natural hazards and occur in all regions of the world, although the frequency and intensity of certain hazards and societies vulnerability to them differ between regions. Severe storms, strong winds, floods, and droughts develop at different spatial and temporal scales, but all can become disasters that cause significant infrastructure damage and claim hundreds of thousands of lives annually worldwide. Oftentimes, multiple hazards can occur simultaneously or trigger cascading impacts from one extreme weather event. For example, in addition to causing injuries, deaths, and material damage, a tropical storm can also result in flooding and mudslides, which can disrupt water purification and sewage disposal systems, cause overflow of toxic wastes, andincrease propagation of mosquito-borne diseases.

  5. Bio-economic farm modelling to analyse agricultural land productivity in Rwanda

    NARCIS (Netherlands)

    Bidogeza, J.C.

    2011-01-01

    Keywords: Rwanda; farm household typology; sustainable technology adoption; multivariate analysis;
    land degradation; food security; bioeconomic model; crop simulation models; organic fertiliser; inorganic fertiliser; policy incentives In Rwanda, land degradation contributes to the low and

  6. A new spatial multiple discrete-continuous modeling approach to land use change analysis.

    Science.gov (United States)

    2013-09-01

    This report formulates a multiple discrete-continuous probit (MDCP) land-use model within a : spatially explicit economic structural framework for land-use change decisions. The spatial : MDCP model is capable of predicting both the type and intensit...

  7. Hydro-meteorological extreme events in the 18th century in Portugal

    Science.gov (United States)

    Fragoso, Marcelo; João Alcoforado, Maria; Taborda, João Paulo

    2013-04-01

    The present work is carried out in the frame of the KLIMHIST PROJECT ("Reconstruction and model simulations of past climate in Portugal using documentary and early instrumental sources, 17th-19th century)", and is devoted to the study of hydro-meteorological extreme events during the last 350 years, in order to understand how they have changed in time and compare them with current analogues. More specifically, the results selected to this presentation will focus on some hydro-meteorological extreme events of the 18th century, like severe droughts, heavy precipitation episodes and windstorms. One of the most noteworthy events was the winterstorm Bárbara (3rd to 6th December 1739), already studied in prior investigations (Taborda et al, 2004; Pfister et al, 2010), a devastating storm with strong impacts in Portugal caused by violent winds and heavy rainfall. Several other extreme events were detected by searching different documentary archives, including individual, administrative and ecclesiastic sources. Moreover, a more detailed insight to the 1783-1787 period will be made with regard the Lisbon region, taking into consideration the availability of information for daily meteorological observations as well as documentary evidences, like descriptions from Gazeta de Lisboa, the periodic with more continuous publication in the 18thcentury. Key-words: Instrumental data, Documentary data, Extreme events, Klimhist Project, Portugal References Pfister, C., Garnier, E., Alcoforado, M.J., Wheeler, D. Luterbacher, J. Nunes, M.F., Taborda, J.P. (2010) The meteorological framework and the cultural memory of three severe winter-storms in early eighteenth-century Europe, Climatic Change, 101, 1-2, 281-310 Taborda, JP; Alcoforado, MJ and Garcia, JC (2004) O Clima do Sul de Portugal no Séc.XVIII, Centro de Estudos Geográficos, Área de de Investigação de Geo-Ecologia, relatório no 2

  8. Understanding decreases in land relative humidity with global warming: conceptual model and GCM simulations

    CERN Document Server

    Byrne, Michael P

    2016-01-01

    Climate models simulate a strong land-ocean contrast in the response of near-surface relative humidity to global warming: relative humidity tends to increase slightly over oceans but decrease substantially over land. Surface energy balance arguments have been used to understand the response over ocean but are difficult to apply over more complex land surfaces. Here, a conceptual box model is introduced, involving moisture transport between the land and ocean boundary layers and evapotranspiration, to investigate the decreases in land relative humidity as the climate warms. The box model is applied to idealized and full-complexity (CMIP5) general circulation model simulations, and it is found to capture many of the features of the simulated changes in land relative humidity. The box model suggests there is a strong link between fractional changes in specific humidity over land and ocean, and the greater warming over land than ocean then implies a decrease in land relative humidity. Evapotranspiration is of sec...

  9. Land Covering Classifications of Boreas Modeling Grid Using AIRSAR Images

    Science.gov (United States)

    Saatchi, Sasan S.; Rignot, Eric

    1996-01-01

    Mapping forest types in the boreal ecosystem in an integrated part of any modeling excercise of biogeophysical processes characterizing the interaction of forest with the atmosphere. In this paper, we report the results of the land cover classification of the SAR data acquired during the BOREAS (BOReal Ecosystem Atmospheric Study) intensive field campaigns over the modeling sub-grid of the southern study area in Saskatchewan , Canada. A Bayesian-maximum-a-posteriori classifier has been applied on the NASA/JPL AIRSAR images covering the region during the peak of the growing season in July, 1994.

  10. Soil Moisture Data Assimilation in the NASA Land Information System for Local Modeling Applications and Improved Situational Awareness

    Science.gov (United States)

    Case, Jonathan L.; Blakenship, Clay B.; Zavodsky, Bradley T.

    2014-01-01

    As part of the NASA Soil Moisture Active Passive (SMAP) Early Adopter (EA) program, the NASA Shortterm Prediction Research and Transition (SPoRT) Center has implemented a data assimilation (DA) routine into the NASA Land Information System (LIS) for soil moisture retrievals from the European Space Agency's Soil Moisture Ocean Salinity (SMOS) satellite. The SMAP EA program promotes application-driven research to provide a fundamental understanding of how SMAP data products will be used to improve decision-making at operational agencies. SPoRT has partnered with select NOAA/NWS Weather Forecast Offices (WFOs) that use output from a real-time regional configuration of LIS, without soil moisture DA, to initialize local numerical weather prediction (NWP) models and enhance situational awareness. Improvements to local NWP with the current LIS have been demonstrated; however, a better representation of the land surface through assimilation of SMOS (and eventually SMAP) retrievals is expected to lead to further model improvement, particularly during warm-season months. SPoRT will collaborate with select WFOs to assess the impact of soil moisture DA on operational forecast situations. Assimilation of the legacy SMOS instrument data provides an opportunity to develop expertise in preparation for using SMAP data products shortly after the scheduled launch on 5 November 2014. SMOS contains a passive L-band radiometer that is used to retrieve surface soil moisture at 35-km resolution with an accuracy of 0.04 cu cm cm (exp -3). SMAP will feature a comparable passive L-band instrument in conjunction with a 3-km resolution active radar component of slightly degraded accuracy. A combined radar-radiometer product will offer unprecedented global coverage of soil moisture at high spatial resolution (9 km) for hydrometeorological applications, balancing the resolution and accuracy of the active and passive instruments, respectively. The LIS software framework manages land surface model

  11. Core principles and concepts in land-use modelling : a literature review

    NARCIS (Netherlands)

    Schrojenstein Lantman, J. van; Verburg, P.; Bregt, A.; Geertman, S.C.M.

    2011-01-01

    Simulation models of land use predict or describe land-use change over space and time. Recent overviews of land-use simulation models show an overwhelming amount of different types of models and applications (Heistermann, Muller & Ronneberger, 2006; Koomen, Stillwell, Bakema & Scholten, 2007;

  12. Core Principles and Concepts in Land-Use Modelling: A Literature Review

    NARCIS (Netherlands)

    Schrojenstein Lantman, van J.P.; Verburg, P.H.; Bregt, A.K.; Geertman, S.

    2011-01-01

    Simulation models of land use predict or describe land-use change over space and time. Recent overviews of land-use simulation models show an overwhelming amount of different types of models and applications (Heistermann, Muller & Ronneberger, 2006; Koomen, Stillwell, Bakema & Scholten,

  13. Spatiotemporal land use modelling to assess land availability for energy crops – illustrated for Mozambique

    NARCIS (Netherlands)

    Hilst, F. van der; Verstegen, J.A.; Karssenberg, D.J.; Faaij, A.P.C.

    2012-01-01

    A method and tool have been developed to assess future developments in land availability for bioenergy crops in a spatially explicit way, while taking into account both the developments in other land use functions, such as land for food, livestock and material production, and the uncertainties in

  14. The NASA-Goddard Multi-Scale Modeling Framework - Land Information System: Global Land/atmosphere Interaction with Resolved Convection

    Science.gov (United States)

    Mohr, Karen Irene; Tao, Wei-Kuo; Chern, Jiun-Dar; Kumar, Sujay V.; Peters-Lidard, Christa D.

    2013-01-01

    The present generation of general circulation models (GCM) use parameterized cumulus schemes and run at hydrostatic grid resolutions. To improve the representation of cloud-scale moist processes and landeatmosphere interactions, a global, Multi-scale Modeling Framework (MMF) coupled to the Land Information System (LIS) has been developed at NASA-Goddard Space Flight Center. The MMFeLIS has three components, a finite-volume (fv) GCM (Goddard Earth Observing System Ver. 4, GEOS-4), a 2D cloud-resolving model (Goddard Cumulus Ensemble, GCE), and the LIS, representing the large-scale atmospheric circulation, cloud processes, and land surface processes, respectively. The non-hydrostatic GCE model replaces the single-column cumulus parameterization of fvGCM. The model grid is composed of an array of fvGCM gridcells each with a series of embedded GCE models. A horizontal coupling strategy, GCE4fvGCM4Coupler4LIS, offered significant computational efficiency, with the scalability and I/O capabilities of LIS permitting landeatmosphere interactions at cloud-scale. Global simulations of 2007e2008 and comparisons to observations and reanalysis products were conducted. Using two different versions of the same land surface model but the same initial conditions, divergence in regional, synoptic-scale surface pressure patterns emerged within two weeks. The sensitivity of largescale circulations to land surface model physics revealed significant functional value to using a scalable, multi-model land surface modeling system in global weather and climate prediction.

  15. Land Surface Modeling Applications for Famine Early Warning

    Science.gov (United States)

    McNally, A.; Verdin, J. P.; Peters-Lidard, C. D.; Arsenault, K. R.; Wang, S.; Kumar, S.; Shukla, S.; Funk, C. C.; Pervez, M. S.; Fall, G. M.; Karsten, L. R.

    2015-12-01

    AGU 2015 Fall Meeting Session ID#: 7598 Remote Sensing Applications for Water Resources Management Land Surface Modeling Applications for Famine Early Warning James Verdin, USGS EROS Christa Peters-Lidard, NASA GSFC Amy McNally, NASA GSFC, UMD/ESSIC Kristi Arsenault, NASA GSFC, SAIC Shugong Wang, NASA GSFC, SAIC Sujay Kumar, NASA GSFC, SAIC Shrad Shukla, UCSB Chris Funk, USGS EROS Greg Fall, NOAA Logan Karsten, NOAA, UCAR Famine early warning has traditionally required close monitoring of agro-climatological conditions, putting them in historical context, and projecting them forward to anticipate end-of-season outcomes. In recent years, it has become necessary to factor in the effects of a changing climate as well. There has also been a growing appreciation of the linkage between food security and water availability. In 2009, Famine Early Warning Systems Network (FEWS NET) science partners began developing land surface modeling (LSM) applications to address these needs. With support from the NASA Applied Sciences Program, an instance of the Land Information System (LIS) was developed to specifically support FEWS NET. A simple crop water balance model (GeoWRSI) traditionally used by FEWS NET took its place alongside the Noah land surface model and the latest version of the Variable Infiltration Capacity (VIC) model, and LIS data readers were developed for FEWS NET precipitation forcings (NOAA's RFE and USGS/UCSB's CHIRPS). The resulting system was successfully used to monitor and project soil moisture conditions in the Horn of Africa, foretelling poor crop outcomes in the OND 2013 and MAM 2014 seasons. In parallel, NOAA created another instance of LIS to monitor snow water resources in Afghanistan, which are an early indicator of water availability for irrigation and crop production. These successes have been followed by investment in LSM implementations to track and project water availability in Sub-Saharan Africa and Yemen, work that is now underway. Adoption of

  16. Development and Application of Nonlinear Land-Use Regression Models

    Science.gov (United States)

    Champendal, Alexandre; Kanevski, Mikhail; Huguenot, Pierre-Emmanuel

    2014-05-01

    The problem of air pollution modelling in urban zones is of great importance both from scientific and applied points of view. At present there are several fundamental approaches either based on science-based modelling (air pollution dispersion) or on the application of space-time geostatistical methods (e.g. family of kriging models or conditional stochastic simulations). Recently, there were important developments in so-called Land Use Regression (LUR) models. These models take into account geospatial information (e.g. traffic network, sources of pollution, average traffic, population census, land use, etc.) at different scales, for example, using buffering operations. Usually the dimension of the input space (number of independent variables) is within the range of (10-100). It was shown that LUR models have some potential to model complex and highly variable patterns of air pollution in urban zones. Most of LUR models currently used are linear models. In the present research the nonlinear LUR models are developed and applied for Geneva city. Mainly two nonlinear data-driven models were elaborated: multilayer perceptron and random forest. An important part of the research deals also with a comprehensive exploratory data analysis using statistical, geostatistical and time series tools. Unsupervised self-organizing maps were applied to better understand space-time patterns of the pollution. The real data case study deals with spatial-temporal air pollution data of Geneva (2002-2011). Nitrogen dioxide (NO2) has caught our attention. It has effects on human health and on plants; NO2 contributes to the phenomenon of acid rain. The negative effects of nitrogen dioxides on plants are the reduction of the growth, production and pesticide resistance. And finally, the effects on materials: nitrogen dioxide increases the corrosion. The data used for this study consist of a set of 106 NO2 passive sensors. 80 were used to build the models and the remaining 36 have constituted

  17. Bioenergy Ecosystem Land-Use Modelling and Field Flux Trial

    Science.gov (United States)

    McNamara, Niall; Bottoms, Emily; Donnison, Iain; Dondini, Marta; Farrar, Kerrie; Finch, Jon; Harris, Zoe; Ineson, Phil; Keane, Ben; Massey, Alice; McCalmont, Jon; Morison, James; Perks, Mike; Pogson, Mark; Rowe, Rebecca; Smith, Pete; Sohi, Saran; Tallis, Mat; Taylor, Gail; Yamulki, Sirwan

    2013-04-01

    Climate change impacts resulting from fossil fuel combustion and concerns about the diversity of energy supply are driving interest to find low-carbon energy alternatives. As a result bioenergy is receiving widespread scientific, political and media attention for its potential role in both supplying energy and mitigating greenhouse (GHG) emissions. It is estimated that the bioenergy contribution to EU 2020 renewable energy targets could require up to 17-21 million hectares of additional land in Europe (Don et al., 2012). There are increasing concerns that some transitions into bioenergy may not be as sustainable as first thought when GHG emissions from the crop growth and management cycle are factored into any GHG life cycle assessment (LCA). Bioenergy is complex and encapsulates a wide range of crops, varying from food crop based biofuels to dedicated second generation perennial energy crops and forestry products. The decision on the choice of crop for energy production significantly influences the GHG mitigation potential. It is recognised that GHG savings or losses are in part a function of the original land-use that has undergone change and the management intensity for the energy crop. There is therefore an urgent need to better quantify both crop and site-specific effects associated with the production of conventional and dedicated energy crops on the GHG balance. Currently, there is scarcity of GHG balance data with respect to second generation crops meaning that process based models and LCAs of GHG balances are weakly underpinned. Therefore, robust, models based on real data are urgently required. In the UK we have recently embarked on a detailed program of work to address this challenge by combining a large number of field studies with state-of-the-art process models. Through six detailed experiments, we are calculating the annual GHG balances of land use transitions into energy crops across the UK. Further, we are quantifying the total soil carbon gain or

  18. A NEW MODEL OF LAND SYSTEM IN UKRAINE WITH REGARD TO THE LOCAL GOVERNMENT REFORM

    Directory of Open Access Journals (Sweden)

    A. Tretiak

    2017-05-01

    Full Text Available During the implementation of land reform in independent Ukraine land system changed twice. Today, due to the decentralization of power is his search for a new model for the future, as outlined in this study. Also note that when we formulated the concept refers to the land system - land system, ie a set of measures for the territorial organization of land and other natural resources, land relations, defined system of ownership and use of land, as well as the principles of the territory. In order to put scientifically based proposals improving the organization and functioning of an effective system of land versatile conceptual model of land system of Ukraine, which includes four functional blocks, namely:1 land system for natural and economic zoning (zoning; 2 land system for administrative-territorial division; 3 land structure by ownership of land; 4 land structure on the forms and methods of land use (types (subtypes of land. Proved that: 1 constitutional definition of administrative-territorial division of Ukraine and strengthening forms of land ownership - private, communal and public, with subsequent legal registration in the Land Code of Ukraine (2001 resulted in the elimination territory of village, town and city councils as the basic foundations Business and financial stability of local communities. Not conducting land works on delimitation of state and municipal property (as of 01.01. 2017 communal lands account for 0.5% of the total area of the country in predictable areas 25-28% and deprivation in 2012. councils powers to manage state-owned land within settlements, along with the elimination of area councils, led to corresponding changes in land structure of Ukraine and elimination of local communities and land-management pryrodokorystu¬vannyam that had a negative impact on quality of life and Security EKU population for sustainable development forms of land use in rural areas. 2 The system of conceptual positions and measures on

  19. How can land-use modelling tools inform bioenergy policies?

    Science.gov (United States)

    Davis, Sarah C; House, Joanna I; Diaz-Chavez, Rocio A; Molnar, Andras; Valin, Hugo; Delucia, Evan H

    2011-04-06

    Targets for bioenergy have been set worldwide to mitigate climate change. Although feedstock sources are often ambiguous, pledges in European nations, the United States and Brazil amount to more than 100 Mtoe of biorenewable fuel production by 2020. As a consequence, the biofuel sector is developing rapidly, and it is increasingly important to distinguish bioenergy options that can address energy security and greenhouse gas mitigation from those that cannot. This paper evaluates how bioenergy production affects land-use change (LUC), and to what extent land-use modelling can inform sound decision-making. We identified local and global internalities and externalities of biofuel development scenarios, reviewed relevant data sources and modelling approaches, identified sources of controversy about indirect LUC (iLUC) and then suggested a framework for comprehensive assessments of bioenergy. Ultimately, plant biomass must be managed to produce energy in a way that is consistent with the management of food, feed, fibre, timber and environmental services. Bioenergy production provides opportunities for improved energy security, climate mitigation and rural development, but the environmental and social consequences depend on feedstock choices and geographical location. The most desirable solutions for bioenergy production will include policies that incentivize regionally integrated management of diverse resources with low inputs, high yields, co-products, multiple benefits and minimal risks of iLUC. Many integrated assessment models include energy resources, trade, technological development and regional environmental conditions, but do not account for biodiversity and lack detailed data on the location of degraded and underproductive lands that would be ideal for bioenergy production. Specific practices that would maximize the benefits of bioenergy production regionally need to be identified before a global analysis of bioenergy-related LUC can be accomplished.

  20. How can land-use modelling tools inform bioenergy policies?

    Science.gov (United States)

    Davis, Sarah C.; House, Joanna I.; Diaz-Chavez, Rocio A.; Molnar, Andras; Valin, Hugo; DeLucia, Evan H.

    2011-01-01

    Targets for bioenergy have been set worldwide to mitigate climate change. Although feedstock sources are often ambiguous, pledges in European nations, the United States and Brazil amount to more than 100 Mtoe of biorenewable fuel production by 2020. As a consequence, the biofuel sector is developing rapidly, and it is increasingly important to distinguish bioenergy options that can address energy security and greenhouse gas mitigation from those that cannot. This paper evaluates how bioenergy production affects land-use change (LUC), and to what extent land-use modelling can inform sound decision-making. We identified local and global internalities and externalities of biofuel development scenarios, reviewed relevant data sources and modelling approaches, identified sources of controversy about indirect LUC (iLUC) and then suggested a framework for comprehensive assessments of bioenergy. Ultimately, plant biomass must be managed to produce energy in a way that is consistent with the management of food, feed, fibre, timber and environmental services. Bioenergy production provides opportunities for improved energy security, climate mitigation and rural development, but the environmental and social consequences depend on feedstock choices and geographical location. The most desirable solutions for bioenergy production will include policies that incentivize regionally integrated management of diverse resources with low inputs, high yields, co-products, multiple benefits and minimal risks of iLUC. Many integrated assessment models include energy resources, trade, technological development and regional environmental conditions, but do not account for biodiversity and lack detailed data on the location of degraded and underproductive lands that would be ideal for bioenergy production. Specific practices that would maximize the benefits of bioenergy production regionally need to be identified before a global analysis of bioenergy-related LUC can be accomplished. PMID

  1. Land Use Scenario Modeling for Flood Risk Mitigation

    Directory of Open Access Journals (Sweden)

    José I. Barredo

    2010-05-01

    Full Text Available It is generally accepted that flood risk has been increasing in Europe in the last decades. Accordingly, it becomes a priority to better understand its drivers and mechanisms. Flood risk is evaluated on the basis of three factors: hazard, exposure and vulnerability. If one of these factors increases, then so does the risk. Land use change models used for ex-ante assessment of spatial trends provide planners with powerful tools for territorial decision making. However, until recently this type of model has been largely neglected in strategic planning for flood risk mitigation. Thus, ex-ante assessment of flood risk is an innovative application of land use change models. The aim of this paper is to propose a flood risk mitigation approach using exposure scenarios. The methodology is applied in the Pordenone province in northern Italy. In the past 50 years Pordenone has suffered several heavy floods, the disastrous consequences of which demonstrated the vulnerability of the area. Results of this study confirm that the main driving force of increased flood risk is found in new urban developments in flood-prone areas.

  2. A review of current calibration and validation practices in land-change modeling

    NARCIS (Netherlands)

    Vliet, van Jasper; Bregt, Arnold K.; Brown, Daniel G.; Delden, van Hedwig; Heckbert, Scott; Verburg, Peter H.

    2016-01-01

    Land-change models are increasingly used to explore land-change dynamics, as well as for policy analyses and scenario studies. In this paper we review calibration and validation approaches adopted for recently published applications of land-change models. We found that statistical analyses and

  3. Model-based analysis of spatio-temporal changes in land use in Northeast China

    NARCIS (Netherlands)

    Xia, T.; Wu, W.; Zhou, Q.; Verburg, P.H.; Yu, Q.Y.; Yang, P.; Ye, L.

    2016-01-01

    Spatially explicit modeling techniques recently emerged as an alternative to monitor land use changes. This study adopted the well-known CLUE-S (Conversion of Land Use and its Effects at Small regional extent) model to analyze the spatio-temporal land use changes in a hot-spot in Northeast China

  4. A review of land-use regression models to assess spatial variation of outdoor air pollution

    National Research Council Canada - National Science Library

    Hoek, Gerard; Beelen, Rob; de Hoogh, Kees; Vienneau, Danielle; Gulliver, John; Fischer, Paul; Briggs, David

    2008-01-01

    .... Current approaches for assessing intra-urban air pollution contrasts include the use of exposure indicator variables, interpolation methods, dispersion models and land-use regression (LUR) models...

  5. Reliable low precision simulations in land surface models

    Science.gov (United States)

    Dawson, Andrew; Düben, Peter D.; MacLeod, David A.; Palmer, Tim N.

    2017-12-01

    Weather and climate models must continue to increase in both resolution and complexity in order that forecasts become more accurate and reliable. Moving to lower numerical precision may be an essential tool for coping with the demand for ever increasing model complexity in addition to increasing computing resources. However, there have been some concerns in the weather and climate modelling community over the suitability of lower precision for climate models, particularly for representing processes that change very slowly over long time-scales. These processes are difficult to represent using low precision due to time increments being systematically rounded to zero. Idealised simulations are used to demonstrate that a model of deep soil heat diffusion that fails when run in single precision can be modified to work correctly using low precision, by splitting up the model into a small higher precision part and a low precision part. This strategy retains the computational benefits of reduced precision whilst preserving accuracy. This same technique is also applied to a full complexity land surface model, resulting in rounding errors that are significantly smaller than initial condition and parameter uncertainties. Although lower precision will present some problems for the weather and climate modelling community, many of the problems can likely be overcome using a straightforward and physically motivated application of reduced precision.

  6. A Multitarget Land Use Change Simulation Model Based on Cellular Automata and Its Application

    National Research Council Canada - National Science Library

    Jun Yang; Fei Chen; Jianchao Xi; Peng Xie; Chuang Li

    2014-01-01

      Based on the analysis of the existing land use change simulation model, combined with macroland use change driving factors and microlocal land use competition, and through the application of Python...

  7. Land Surface Model (LSM 1.0) for Ecological, Hydrological, Atmospheric Studies

    Data.gov (United States)

    National Aeronautics and Space Administration — ABSTRACT: The NCAR LSM 1.0 is a land surface model developed to examine biogeophysical and biogeochemical land-atmosphere interactions, especially the effects of...

  8. EXPERT MODEL OF LAND SUITABILITY ASSESSMENT FOR CROPS

    Directory of Open Access Journals (Sweden)

    Boris Đurđević

    2010-12-01

    Full Text Available A total of 17404 soil samples (2003rd-2009th year were analysed in the eastern Croatia. The largest number of soil samples belongs to the Osijek-Baranya county, which together with both Eastern sugar beet Factories (Osijek and Županja, conduct the soil fertility control (~4200 samples/yr.. Computer model suitability assessment for crops, supported by GIS, proved to be fast, efficient enough reliable in terms of the number of analyzed soil samples. It allows the visualization of the agricultural area and prediction of its production properties for the purposes of analysis, planning and rationalization of agricultural production. With more precise data about the soil (soil, climate and reliable Digital Soil Map of Croatia, the model could be an acceptable, not only to evaluate the suitability for growing different crops but also their need for fertilizer, necessary machinery, repairs (liming, and other measures of organic matter input. The abovementioned aims to eliminate or reduce effects of limiting factors in primary agricultural production. Assessment of the relative benefits of soil presented by computer model for the crops production and geostatistical method kriging in the Osijek-Baranya county showed: 1 Average soil suitability being 60.06 percent. 2 Kriging predicted that 51751 ha (17.16% are of limited resources (N1 for growing crops whereas a 86142 ha (28.57% of land is limited suitably (S3, b 132789 ha (44.04% are moderately suitable (S2 and c 30772 ha (10.28% are of excellent fertility (S1. A large number of eastern Croatian land data showed that the computer-geostatistical model for determination of soil benefits for growing crops was automated, fast and simple to use and suitable for the implementation of GIS and automatically downloading the necessary benefit indicators from the input base (land, analytical and climate as well as data from the digital soil maps able to: a visualize the suitability for soil tillage, b predict the

  9. The modelling of rights, restrictions and responsibilities (RRR) in the land administration domain model (LADM)

    NARCIS (Netherlands)

    Lemmen, C.H.J.; Van Oosterom, P.J.M.; Eisenhut, C.; Uitermark, H.T.

    2010-01-01

    In this paper, the modelling of alternatives for Rights, Restrictions and Responsibilities (RRRs) are discussed, within the context of the Land Administration Domain Model (LADM, ISO 19152, under development). This includes the modelling of holding shares in a RRR. LADM currently provides for the

  10. Introducing preference heterogenity into a monocentric urban model: an agent-based land market model

    NARCIS (Netherlands)

    Filatova, Tatiana; Parker, Dawn C.; van der Veen, A.; George Mason University,

    2008-01-01

    This paper presents an agent-based urban land market model. We first replace the centralized price determination mechanism of the monocentric urban market model with a series of bilateral trades distributed in space and time. We then run the model for agents with heterogeneous preferences for

  11. Enhanced Modeling of Remotely Sensed Annual Land Surface Temperature Cycle

    Science.gov (United States)

    Zou, Z.; Zhan, W.; Jiang, L.

    2017-09-01

    Satellite thermal remote sensing provides access to acquire large-scale Land surface temperature (LST) data, but also generates missing and abnormal values resulting from non-clear-sky conditions. Given this limitation, Annual Temperature Cycle (ATC) model was employed to reconstruct the continuous daily LST data over a year. The original model ATCO used harmonic functions, but the dramatic changes of the real LST caused by the weather changes remained unclear due to the smooth sine curve. Using Aqua/MODIS LST products, NDVI and meteorological data, we proposed enhanced model ATCE based on ATCO to describe the fluctuation and compared their performances for the Yangtze River Delta region of China. The results demonstrated that, the overall root mean square errors (RMSEs) of the ATCE was lower than ATCO, and the improved accuracy of daytime was better than that of night, with the errors decreased by 0.64 K and 0.36 K, respectively. The improvements of accuracies varied with different land cover types: the forest, grassland and built-up areas improved larger than water. And the spatial heterogeneity was observed for performance of ATC model: the RMSEs of built-up area, forest and grassland were around 3.0 K in the daytime, while the water attained 2.27 K; at night, the accuracies of all types significantly increased to similar RMSEs level about 2 K. By comparing the differences between LSTs simulated by two models in different seasons, it was found that the differences were smaller in the spring and autumn, while larger in the summer and winter.

  12. Improving an operational probabilistic hydrometeorological forecasting chain in the Valle d'Aosta Region

    Science.gov (United States)

    Gabellani, Simone; Rudari, Roberto; Ferraris, Luca; Rebora, Nicola; Ratto, Sara; Stevenin, Hervè

    2010-05-01

    The operational hydrometeorological forecasting chain at the basis of the Valle d'Aosta regional warning system integrates a snow model (SRaM) in to a distributed hydrologic model (DRiFt) and uses a stochastic downscaling technique (RainFARM) for generating a high resolution (1km-1h) precipitation ensemble from the quantitative precipitation forecast issued by a Limited area model (COSMO-LAMI) and by the Regional Centres of Valle d'Aosta and Piemonte Regions. The procedure generates discharge ensemble predictions in relevant sections of the Dora river. A second version of the operational chain has been implemented. In this new version of the procedure the initial conditions for the hydrological model (i.e., the soil moisture) and the snow model have been both improved by using data assimilation techniques that combine satellite and ground based measurements. In this work the impact of such modifications are evaluated by comparing the two procedures via back analysis of the last four years.

  13. Simulating Land Use Policies Targeted to Protect Biodiversity with the CLUE-Scanner Model

    NARCIS (Netherlands)

    Verburg, P.H.; Lesschen, J.P.; Koomen, E.; Perez-Soba, M.

    2011-01-01

    This chapter presents an integrated modelling approach for assessing land use changes and its effects on biodiversity. A modelling framework consisting of a macro-economic model, a land use change model, and biodiversity indicator models is described and illustrated with a scenario study for the

  14. Land use/land cover changes and climate: modeling analysis and observational evidence

    NARCIS (Netherlands)

    Pielke sr., R.A.; Pitman, A.; Niyogi, D.; Mahmood, R.; McAlpine, C.; Hossain, F.; Kabat, P.

    2011-01-01

    Agreat deal of attention is devoted to changes in atmospheric composition and the associated regional responses. Less attention is given to the direct influence by human activity on regional climate caused by modification of the atmosphere’s lower boundary—the Earth’s surface. Land use/land cover

  15. Land use and land cover change based on historical space-time model

    Science.gov (United States)

    Sun, Qiong; Zhang, Chi; Liu, Min; Zhang, Yongjing

    2016-09-01

    Land use and cover change is a leading edge topic in the current research field of global environmental changes and case study of typical areas is an important approach understanding global environmental changes. Taking the Qiantang River (Zhejiang, China) as an example, this study explores automatic classification of land use using remote sensing technology and analyzes historical space-time change by remote sensing monitoring. This study combines spectral angle mapping (SAM) with multi-source information and creates a convenient and efficient high-precision land use computer automatic classification method which meets the application requirements and is suitable for complex landform of the studied area. This work analyzes the histological space-time characteristics of land use and cover change in the Qiantang River basin in 2001, 2007 and 2014, in order to (i) verify the feasibility of studying land use change with remote sensing technology, (ii) accurately understand the change of land use and cover as well as historical space-time evolution trend, (iii) provide a realistic basis for the sustainable development of the Qiantang River basin and (iv) provide a strong information support and new research method for optimizing the Qiantang River land use structure and achieving optimal allocation of land resources and scientific management.

  16. GLDAS CLM Land Surface Model L4 Monthly 1.0 x 1.0 degree V001

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set contains a series of land surface parameters simulated from the Common Land Model (CLM) V2.0 model in the Global Land Data Assimilation System (GLDAS)....

  17. GLDAS CLM Land Surface Model L4 3 Hourly 1.0 x 1.0 degree Subsetted V001

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set contains a series of land surface parameters simulated from the Common Land Model (CLM) V2.0 model in the Global Land Data Assimilation System (GLDAS)....

  18. A Local Land Use Competition Cellular Automata Model and Its Application

    Directory of Open Access Journals (Sweden)

    Jun Yang

    2016-06-01

    Full Text Available Cellular automaton (CA is an important method in land use and cover change studies, however, the majority of research focuses on the discovery of macroscopic factors affecting LUCC, which results in ignoring the local effects within the neighborhoods. This paper introduces a Local Land Use Competition Cellular Automata (LLUC-CA model, based on local land use competition, land suitability evaluation, demand analysis of the different land use types, and multi-target land use competition allocation algorithm to simulate land use change at a micro level. The model is applied to simulate land use changes at Jinshitan National Tourist Holiday Resort from 1988 to 2012. The results show that the simulation accuracies were 64.46%, 77.21%, 85.30% and 99.14% for the agricultural land, construction land, forestland and water, respectively. In addition, comparing the simulation results of the LLUC-CA and CA-Markov model with the real land use data, their overall spatial accuracies were found to be 88.74% and 86.82%, respectively. In conclusion, the results from this study indicated that the model was an acceptable method for the simulation of large-scale land use changes, and the approach used here is applicable to analyzing the land use change driven forces and assist in decision-making.

  19. Physics-based Entry, Descent and Landing Risk Model

    Science.gov (United States)

    Gee, Ken; Huynh, Loc C.; Manning, Ted

    2014-01-01

    A physics-based risk model was developed to assess the risk associated with thermal protection system failures during the entry, descent and landing phase of a manned spacecraft mission. In the model, entry trajectories were computed using a three-degree-of-freedom trajectory tool, the aerothermodynamic heating environment was computed using an engineering-level computational tool and the thermal response of the TPS material was modeled using a one-dimensional thermal response tool. The model was capable of modeling the effect of micrometeoroid and orbital debris impact damage on the TPS thermal response. A Monte Carlo analysis was used to determine the effects of uncertainties in the vehicle state at Entry Interface, aerothermodynamic heating and material properties on the performance of the TPS design. The failure criterion was set as a temperature limit at the bondline between the TPS and the underlying structure. Both direct computation and response surface approaches were used to compute the risk. The model was applied to a generic manned space capsule design. The effect of material property uncertainty and MMOD damage on risk of failure were analyzed. A comparison of the direct computation and response surface approach was undertaken.

  20. Land-Use Portfolio Modeler, Version 1.0

    Science.gov (United States)

    Taketa, Richard; Hong, Makiko

    2010-01-01

    -on-investment. The portfolio model, now known as the Land-Use Portfolio Model (LUPM), provided the framework for the development of the Land-Use Portfolio Modeler, Version 1.0 software (LUPM v1.0). The software provides a geographic information system (GIS)-based modeling tool for evaluating alternative risk-reduction mitigation strategies for specific natural-hazard events. The modeler uses information about a specific natural-hazard event and the features exposed to that event within the targeted study region to derive a measure of a given mitigation strategy`s effectiveness. Harnessing the spatial capabilities of a GIS enables the tool to provide a rich, interactive mapping environment in which users can create, analyze, visualize, and compare different

  1. Do Lateral Flows Matter for the Hyperresolution Land Surface Modeling?

    Science.gov (United States)

    Ji, Peng; Yuan, Xing; Liang, Xin-Zhong

    2017-11-01

    Hyperresolution land surface modeling provides an unprecedented opportunity to simulate locally relevant water and energy cycle, but lateral surface and/or subsurface flows that are essential at fine scale are often neglected by most one-dimensional land surface models (LSMs). To analyze effects of lateral flows across scales, a Conjunctive Surface-Subsurface Process model, which considers soil moisture-surface flow interaction and quasi-three-dimensional subsurface flow, is implemented over a mountainous HyperHydro test bed in southwestern USA at different resolutions. Validation over more than 70 International Soil Moisture Network stations shows that there are significant improvements in soil moisture simulations from 30 km to 4 km as finer soil property and precipitation data are used, with correlation increased by 5%-16% and error decreased by 5%. Lateral surface flow has a significant influence on surface soil moisture and ground evaporation even at coarse resolution. Effect of lateral subsurface flow on soil moisture is nontrivial at 1 km or finer resolution especially over wet areas. At 100 m resolution, topography-induced lateral subsurface flow causes drier peaks and wetter valleys, decreases latent heat by 8% at peaks, while increases it by 12% at valleys. Furthermore, influences of lateral subsurface flow on ground evaporation and vegetation transpiration are more significant during dry season due to a stronger coupling between soil moisture and evapotranspiration. Therefore, it is worthy to incorporate lateral flow processes in hyperresolution LSMs to better represent water and energy heterogeneity even with limited hyperresolution meteorological and surface data.

  2. Dynamic Model Investigation of the Landing Characteristics of a Manned Spacecraft

    Science.gov (United States)

    Thompson, William C.

    1964-01-01

    Investigations were made to study the water-landing and certain grounds-surface landing characteristics of a Gemini spacecraft model. The water landing experiments were made by simulating paraglider and parachute letdowns with two 1/6- scale model configurations. Parameters included various combinations of attitude, horizontal speed, vertical speed, and landing skids extended and retracted. Investigations were made in calm water and in waves. The paraglider landings at horizontal speeds of 63 feet per second (19.8 m/sec) which resulted in a noseover or tumbling shortly after initial water contact. The maximum longitudinal acceleration of the model in calm water was about 14g units, and the maximum angular acceleration was 66 radians per second squared. In the parachute landings with the heat shield forward, the model skidded along the water surface on the heat shield. Parachute landings with the small end forward resulted in behavior similar to that of the paraglider landings. The ground-surface landings were made with a 1/3-scale model by simulating a parachute letdown with braking rockets, which were fired prior to touchdown to dissipate vertical velocity. In these landings, control of timing and aligning the rockets on the model was very critical, and violent behavior resulted when either rocket alignment or timing was in error. In the landings that were correctly controlled, the model either remained upright or slowly rolled over on its side.

  3. Modelling the effects of land-use and land-cover change on water availability in the Jordan River region

    Directory of Open Access Journals (Sweden)

    R. Schaldach

    2009-08-01

    Full Text Available Within the GLOWA Jordan River project, a first-time overview of the current and possible future land and water conditions of a major part of the Eastern Mediterranean region (ca. 100 000 km2 is given. First, we applied the hydrological model TRAIN to simulate current water availability (runoff and groundwater recharge and irrigation water demand on a 1 km×1 km spatial resolution. The results demonstrate the scarcity of water resources in the study region, with extremely low values of water availability in the semi-arid and arid parts. Then, a set of four divergent scenarios on the future of water has been developed using a stakeholder driven approach. Relevant drivers for land-use/land-cover change were fed into the LandSHIFT.R model to produce land-use and land-cover maps for the different scenarios. These maps were used as input to TRAIN in order to generate scenarios of water availability and irrigation water demand for the region. For this study, two intermediate scenarios were selected, with projected developments ranging between optimistic and pessimistic futures (with regard to social and economic conditions in the region. Given that climate conditions remain unchanged, the simulations show both increases and decreases in water availability, depending on the future pattern of natural and agricultural vegetation and the related dominance of hydrological processes.

  4. Bayesian calibration of the Community Land Model using surrogates

    Energy Technology Data Exchange (ETDEWEB)

    Ray, Jaideep; Hou, Zhangshuan; Huang, Maoyi; Swiler, Laura Painton

    2014-02-01

    We present results from the Bayesian calibration of hydrological parameters of the Community Land Model (CLM), which is often used in climate simulations and Earth system models. A statistical inverse problem is formulated for three hydrological parameters, conditional on observations of latent heat surface fluxes over 48 months. Our calibration method uses polynomial and Gaussian process surrogates of the CLM, and solves the parameter estimation problem using a Markov chain Monte Carlo sampler. Posterior probability densities for the parameters are developed for two sites with different soil and vegetation covers. Our method also allows us to examine the structural error in CLM under two error models. We find that surrogate models can be created for CLM in most cases. The posterior distributions are more predictive than the default parameter values in CLM. Climatologically averaging the observations does not modify the parameters' distributions significantly. The structural error model reveals a correlation time-scale which can be used to identify the physical process that could be contributing to it. While the calibrated CLM has a higher predictive skill, the calibration is under-dispersive.

  5. Geo-information Based Spatio-temporal Modeling of Urban Land Use and Land Cover Change in Butwal Municipality, Nepal

    Science.gov (United States)

    Mandal, U. K.

    2014-11-01

    Unscientific utilization of land use and land cover due to rapid growth of urban population deteriorates urban condition. Urban growth, land use change and future urban land demand are key concerns of urban planners. This paper is aimed to model urban land use change essential for sustainable urban development. GI science technology was employed to study the urban change dynamics using Markov Chain and CA-Markov and predicted the magnitude and spatial pattern. It was performed using the probability transition matrix from the Markov chain process, the suitability map of each land use/cover types and the contiguity filter. Suitability maps were generated from the MCE process where weight was derived from the pair wise comparison in the AHP process considering slope, land capability, distance to road, and settlement and water bodies as criterion of factor maps. Thematic land use land cover types of 1999, 2006, and 2013 of Landsat sensors were classified using MLC algorithm. The spatial extent increase from 1999 to 2013 in built up , bush and forest was observed to be 48.30 percent,79.48 percent and 7.79 percent, respectively, while decrease in agriculture and water bodies were 30.26 percent and 28.22 percent. The predicted urban LULC for 2020 and 2027 would provide useful inputs to the decision makers. Built up and bush expansion are explored as the main driving force for loss of agriculture and river areas and has the potential to continue in future also. The abandoned area of river bed has been converted to built- up areas.

  6. Modeling Global Change in Local Places: Capturing Global Change and Local Impacts in a Global Land System Change Model

    Science.gov (United States)

    Verburg, P.; Eitelberg, D.; Ornetsmueller, C.; van Vliet, J.

    2015-12-01

    Global land use models are driven by demands for food and urban space. However, at the same time many transitions in land use and land cover are driven by societal changes and the demand for a wide range of landscape functions or ecosystem services, including the conservation of biodiversity, regulation of climate and floods, and recreation. Some of these demands lead to tele-connected land use change through the transport of good and services, others are place-based and shape the local realities of land system change. Most current land use change models focus on land cover changes alone and ignore the importance of changes in land management and landscape configuration that affect climate, biodiversity and the provisioning of ecosystem services. This talk will present an alternative approach to global land use modelling based on the simulation of changes in land systems in response to a wide set of ecosystem service demands. Simulations at global scale illustrate that accounting for demands for livestock products, carbon sequestration and biological conservation (following the Aichi targets) leads to different outcomes of land change models and allows the identification of synergies between carbon and biodiversity targets. An application in Laos indicates the complex transitions in land systems and landscapes that occur upon the transition from shifting cultivation to permanent agriculture and tree-crop plantations. We discuss the implications of such land system representations for Earth system modelling.

  7. Land Surface Modeling and Data Assimilation to Support Physical Precipitation Retrievals for GPM

    Science.gov (United States)

    Peters-Lidard, Christa D.; Tian. Yudong; Kumar, Sujay; Geiger, James; Choudhury, Bhaskar

    2010-01-01

    Objective: The objective of this proposal is to provide a routine land surface modeling and data assimilation capability for GPM in order to provide global land surface states that are necessary to support physical precipitation retrieval algorithms over land. It is well-known that surface emission, particularly over the range of frequencies to be included in GPM, is sensitive to land surface states, including soil properties, vegetation type and greenness, soil moisture, surface temperature, and snow cover, density, and grain size. Therefore, providing a robust capability to routinely provide these critical land states is essential to support GPM-era physical retrieval algorithms over land.

  8. Assessing Independent Variables Used in Econometric Modeling Forest Land Use or Land Cover Change: A Meta-Analysis

    Science.gov (United States)

    J Jeuck; F. Cubbage; R. Abt; R. Bardon; J. McCarter; J. Coulston; M. Renkow

    2014-01-01

    : We conducted a meta-analysis on 64 econometric models from 47 studies predicting forestland conversion to agriculture (F2A), forestland to development (F2D), forestland to non-forested (F2NF) and undeveloped (including forestland) to developed (U2D) land. Over 250 independent econometric variables were identified from 21 F2A models, 21 F2D models, 12 F2NF models, and...

  9. Land surface process and radiobrightness modeling of the Great Plains

    Science.gov (United States)

    Judge, Jasmeet

    Accurate estimation of stored water by Land Surface Process (LSP) models is crucial to the prediction of continental weather and near-term climate by General Circulation Models (GCMs). This dissertation represents an important step toward assimilating the satellite radiometric observations to improve the soil moisture estimates. It consists of "forward" modeling of terrain brightnesses through a biophysically-based Land Surface Process/Radiobrightness (LSP/R) model, and correlating ground-based brightnesses with those from the Special Sensor Microwave/Imager (SSM/I). The LSP/R model was modified and calibrated for representative terrain in the Great Plains during summertime, when the surface processes are dominant and strongly coupled. The calibration used data from two collaborative field investigations, the fourth and the fifth Radiobrightness Energy Balance Experiments (REBEX-4 and REBEX-5). REBEX-4 was a collaboration with the Atmospheric Environment Service (AES), Canada, at the USGS EROS Data Center near Sioux Falls, SD. During the experiment, we observed microwave emission and concurrent micro-meteorological parameters at a bare soil and a nearby grass site from June-September in 1996. REBEX-5 was the University of Michigan's contribution to an extensive field investigation, Southern Great Plains Hydrology Experiment (SGP'97), conducted in north central Oklahoma from June 18--July 17 in 1997. During REBEX-5, we measured brightnesses of senescent winter wheat and after harvest wheat-stubble. In general, the calibrated LSP model predicted realistic surface processes that compared well with the field observations. The model predictions were most sensitive to shortwave albedo of the terrain and soil thermal and hydraulic conductivities. The Radiobrightness module captured the mean diurnal variations in brightnesses. The H-pol terrain brightnesses at 19 GHz were more sensitive to soil moisture and roughness than the V-pol brightnesses. The comparison of the EASE

  10. Relationship between MRPV Model Parameters from MISRL2 Land Surface Product and Land Covers: A Case Study within Mainland Spain

    Directory of Open Access Journals (Sweden)

    Patricia Arrogante-Funes

    2017-11-01

    Full Text Available In this study, we showed that the multi-angle satellite remote sensing product, MISR L2 Land Surface (MIL2ASLS, which has a scale of 1.1 km, could be suitable for improving land-cover studies. Using seven images from this product, captured by the multi-angle imaging spectroradiometer sensor (MISR, we explored the values reached by the three parameters (ρ0, Θ, and k of the Rahman–Pinty–Verstraete model, which was modified by Martonchick (MRPV. Thereafter, we compared the values and behaviors shown in seven Co-ordination of Information on the Environment (CORINE land cover categories, in the red and near infrared (NIR bands, over the seven MISR orbits captured in 2006 for Mainland Spain. Furthermore, we used Normalized Difference Vegetation Index (NDVI, Leaf Area Index (LAI, and Fraction of Photosynthetically Active Radiation (FPAR ancillary data and the illumination angles from the same pixels, which made up the images. These ancillary data were also provided by the MISR products. An inferential statistic test was performed to evaluate the relationship between each parameter–band combination, and the land cover in every MISR orbit used. The results suggested that the ρ0 parameters of this product seemed to be the most related to photosynthetic activity, and it should be comparable with the widely-used NDVI. On the other hand, the k and Θ parameter values were not related, or at least not entirely related, to the phenology of land coverage. These seemed to be more influenced by the anisotropy behavior of the studied land cover pixels. Additionally, we observed, by constructing analysis of variance, how the mean of each MRPV parameter–band differed statistically (p < 0.01 by land covers and orbits. This study suggested that the MISR MRPV model parameter data product has great potential to be used to improve land cover applications.

  11. Using Runoff Data to Calibrate the Community Land Model

    Science.gov (United States)

    Ray, J.; Hou, Z.; Huang, M.; Swiler, L.

    2014-12-01

    We present a statistical method for calibrating the Community Land Model (CLM) using streamflow observations collected between 1999 and 2008 at the outlet of two river basins from the Model Parameter Estimation Experiment (MOPEX), Oostanaula River at Resaca GA, and Walnut River at Winfield KS.. The observed streamflow shows variability over a large range of time-scales, none of which significantly dominates the others; consequently, the time-series seems noisy and is difficult to be directly used in model parameter estimation efforts without significant filtering. We perform a multi-resolution wavelet decomposition of the observed streamflow, and use the wavelet power coefficients (WPC) as the tuning data. We construct a mapping (a surrogate model) between WPC and three hydrological parameters of the CLM using a training set of 256 CLM runs. The dependence of WPC on the parameters is complex and cannot be captured using a surrogate unless the parameter combinations yield physically plausible model predictions, i.e., those that are skillful when compared to observations. Retaining only the top quartile of the runs ensures skillfulness, as measured by the RMS error between observations and CLM predictions. This "screening" of the training data yields a region (the "valid" region) in the parameter space where accurate surrogate models can be created. We construct a classifier for the "valid" region, and, in conjunction with the surrogate models for WPC, pose a Bayesian inverse problem for the three hydrological parameters. The inverse problem is solved using an adaptive Markov chain Monte Carlo (MCMC) method to construct a three-dimensional posterior distribution for the hydrological parameters. Posterior predictive tests using the surrogate model reveal that the posterior distribution is more predictive than the nominal values of the parameters, which are used as default values in the current version of CLM. The effectiveness of the inversion is then validated by

  12. An End-to-End System to Enable Quick, Easy and Inexpensive Deployment of Hydrometeorological Stations

    Science.gov (United States)

    Celicourt, P.; Piasecki, M.

    2014-12-01

    The high cost of hydro-meteorological data acquisition, communication and publication systems along with limited qualified human resources is considered as the main reason why hydro-meteorological data collection remains a challenge especially in developing countries. Despite significant advances in sensor network technologies which gave birth to open hardware and software, low-cost (less than $50) and low-power (in the order of a few miliWatts) sensor platforms in the last two decades, sensors and sensor network deployment remains a labor-intensive, time consuming, cumbersome, and thus expensive task. These factors give rise for the need to develop a affordable, simple to deploy, scalable and self-organizing end-to-end (from sensor to publication) system suitable for deployment in such countries. The design of the envisioned system will consist of a few Sensed-And-Programmed Arduino-based sensor nodes with low-cost sensors measuring parameters relevant to hydrological processes and a Raspberry Pi micro-computer hosting the in-the-field back-end data management. This latter comprises the Python/Django model of the CUAHSI Observations Data Model (ODM) namely DjangODM backed by a PostgreSQL Database Server. We are also developing a Python-based data processing script which will be paired with the data autoloading capability of Django to populate the DjangODM database with the incoming data. To publish the data, the WOFpy (WaterOneFlow Web Services in Python) developed by the Texas Water Development Board for 'Water Data for Texas' which can produce WaterML web services from a variety of back-end database installations such as SQLite, MySQL, and PostgreSQL will be used. A step further would be the development of an appealing online visualization tool using Python statistics and analytics tools (Scipy, Numpy, Pandas) showing the spatial distribution of variables across an entire watershed as a time variant layer on top of a basemap.

  13. Invited perspectives: Hydrological perspectives on precipitation intensity-duration thresholds for landslide initiation: proposing hydro-meteorological thresholds

    Science.gov (United States)

    Bogaard, Thom; Greco, Roberto

    2018-01-01

    Many shallow landslides and debris flows are precipitation initiated. Therefore, regional landslide hazard assessment is often based on empirically derived precipitation intensity-duration (ID) thresholds and landslide inventories. Generally, two features of precipitation events are plotted and labeled with (shallow) landslide occurrence or non-occurrence. Hereafter, a separation line or zone is drawn, mostly in logarithmic space. The practical background of ID is that often only meteorological information is available when analyzing (non-)occurrence of shallow landslides and, at the same time, it could be that precipitation information is a good proxy for both meteorological trigger and hydrological cause. Although applied in many case studies, this approach suffers from many false positives as well as limited physical process understanding. Some first steps towards a more hydrologically based approach have been proposed in the past, but these efforts received limited follow-up.Therefore, the objective of our paper is to (a) critically analyze the concept of precipitation ID thresholds for shallow landslides and debris flows from a hydro-meteorological point of view and (b) propose a trigger-cause conceptual framework for lumped regional hydro-meteorological hazard assessment based on published examples and associated discussion. We discuss the ID thresholds in relation to return periods of precipitation, soil physics, and slope and catchment water balance. With this paper, we aim to contribute to the development of a stronger conceptual model for regional landslide hazard assessment based on physical process understanding and empirical data.

  14. Invited perspectives: Hydrological perspectives on precipitation intensity-duration thresholds for landslide initiation: proposing hydro-meteorological thresholds

    Directory of Open Access Journals (Sweden)

    T. Bogaard

    2018-01-01

    Full Text Available Many shallow landslides and debris flows are precipitation initiated. Therefore, regional landslide hazard assessment is often based on empirically derived precipitation intensity-duration (ID thresholds and landslide inventories. Generally, two features of precipitation events are plotted and labeled with (shallow landslide occurrence or non-occurrence. Hereafter, a separation line or zone is drawn, mostly in logarithmic space. The practical background of ID is that often only meteorological information is available when analyzing (non-occurrence of shallow landslides and, at the same time, it could be that precipitation information is a good proxy for both meteorological trigger and hydrological cause. Although applied in many case studies, this approach suffers from many false positives as well as limited physical process understanding. Some first steps towards a more hydrologically based approach have been proposed in the past, but these efforts received limited follow-up.Therefore, the objective of our paper is to (a critically analyze the concept of precipitation ID thresholds for shallow landslides and debris flows from a hydro-meteorological point of view and (b propose a trigger–cause conceptual framework for lumped regional hydro-meteorological hazard assessment based on published examples and associated discussion. We discuss the ID thresholds in relation to return periods of precipitation, soil physics, and slope and catchment water balance. With this paper, we aim to contribute to the development of a stronger conceptual model for regional landslide hazard assessment based on physical process understanding and empirical data.

  15. Investigation Of The Hydro-Meteorological Hazards Along The Bulgarian Coast Of The Black Sea By Reconstructions Of Historical Storms

    CERN Document Server

    Galabov, Vasko; Bogatchev, Andrey; Tsenova, Boryana

    2015-01-01

    Information about the hydro-meteorological parameters during the extreme sea storms is of significant importance for the sustainable development in the context of flood risk for the coastal areas. Usually there is a lack of sufficiently long history of instrumental measurements of the extreme winds, waves and storm surges. Simulation of historical storms is an important tool to evaluate the potential coastal hazards. In the absence of measured data hindcasts can satisfy the need for historical data. The wave and storm-surge regional numerical simulations have been carried out for the ten most severe storms over the Bulgarian coast of the Black Sea from the period 1972-2012. The ERA-Interim and ERA-40 reanalysis of wind at 10 m and mean sea level pressure have been downscaled with a high resolution atmospheric model ALADIN to the horizontal and time scales suitable for precise evaluation of hydro-meteorological parameters during the storms. The downscaled fields of wind and sea level pressure have been used as...

  16. Land Use models in complex societal problem solving: Plug and play or networking?

    NARCIS (Netherlands)

    Sterk, B.; Leeuwis, C.; Ittersum, van M.K.

    2009-01-01

    Land use systems research addresses issues, such as agricultural policy making, land use planning and integrated water management, that often involve multiple stakeholders. Several potential roles for land use models in multi-stakeholder situations have been identified, such as: a heuristic role,

  17. Cross-site comparison of land-use decision-making and its consequences across land systems with a generalized agent-based model.

    Science.gov (United States)

    Magliocca, Nicholas R; Brown, Daniel G; Ellis, Erle C

    2014-01-01

    Local changes in land use result from the decisions and actions of land-users within land systems, which are structured by local and global environmental, economic, political, and cultural contexts. Such cross-scale causation presents a major challenge for developing a general understanding of how local decision-making shapes land-use changes at the global scale. This paper implements a generalized agent-based model (ABM) as a virtual laboratory to explore how global and local processes influence the land-use and livelihood decisions of local land-users, operationalized as settlement-level agents, across the landscapes of six real-world test sites. Test sites were chosen in USA, Laos, and China to capture globally-significant variation in population density, market influence, and environmental conditions, with land systems ranging from swidden to commercial agriculture. Publicly available global data were integrated into the ABM to model cross-scale effects of economic globalization on local land-use decisions. A suite of statistics was developed to assess the accuracy of model-predicted land-use outcomes relative to observed and random (i.e. null model) landscapes. At four of six sites, where environmental and demographic forces were important constraints on land-use choices, modeled land-use outcomes were more similar to those observed across sites than the null model. At the two sites in which market forces significantly influenced land-use and livelihood decisions, the model was a poorer predictor of land-use outcomes than the null model. Model successes and failures in simulating real-world land-use patterns enabled the testing of hypotheses on land-use decision-making and yielded insights on the importance of missing mechanisms. The virtual laboratory approach provides a practical framework for systematic improvement of both theory and predictive skill in land change science based on a continual process of experimentation and model enhancement.

  18. Combining emperical and theory-based land use modelling approaches to assess future availability of land and economic potential for sustainable biofuel production: Argentina as a case study

    NARCIS (Netherlands)

    Diogo, V.; van der Hilst, Floortje; van Eijck, Janske; Faaij, André; Verstegen, Judith; Hilbert, J.; Carballo, S.; Volante, J.

    2014-01-01

    In this paper, a land-use modelling framework is presented combining empirical and theory-based modelling approaches to determine economic potential of biofuel production avoiding indirect land-use changes (iLUC) resulting from land competition with other functions. The empirical approach explores

  19. Results from Assimilating AMSR-E Soil Moisture Estimates into a Land Surface Model Using an Ensemble Kalman Filter in the Land Information System

    Science.gov (United States)

    Blankenship, Clay B.; Crosson, William L.; Case, Jonathan L.; Hale, Robert

    2010-01-01

    Improve simulations of soil moisture/temperature, and consequently boundary layer states and processes, by assimilating AMSR-E soil moisture estimates into a coupled land surface-mesoscale model Provide a new land surface model as an option in the Land Information System (LIS)

  20. Coupling a groundwater model with a land surface model to improve water and energy cycle simulation

    Directory of Open Access Journals (Sweden)

    W. Tian

    2012-12-01

    Full Text Available Water and energy cycles interact, making these two processes closely related. Land surface models (LSMs can describe the water and energy cycles on the land surface, but their description of the subsurface water processes is oversimplified, and lateral groundwater flow is ignored. Groundwater models (GWMs describe the dynamic movement of the subsurface water well, but they cannot depict the physical mechanisms of the evapotranspiration (ET process in detail. In this study, a coupled model of groundwater flow with a simple biosphere (GWSiB is developed based on the full coupling of a typical land surface model (SiB2 and a 3-D variably saturated groundwater model (AquiferFlow. In this coupled model, the infiltration, ET and energy transfer are simulated by SiB2 using the soil moisture results from the groundwater flow model. The infiltration and ET results are applied iteratively to drive the groundwater flow model. After the coupled model is built, a sensitivity test is first performed, and the effect of the groundwater depth and the hydraulic conductivity parameters on the ET are analyzed. The coupled model is then validated using measurements from two stations located in shallow and deep groundwater depth zones. Finally, the coupled model is applied to data from the middle reach of the Heihe River basin in the northwest of China to test the regional simulation capabilities of the model.

  1. SHIWA Services for Workflow Creation and Sharing in Hydrometeorolog

    Science.gov (United States)

    Terstyanszky, Gabor; Kiss, Tamas; Kacsuk, Peter; Sipos, Gergely

    2014-05-01

    pre-deployed workflow engines or submits workflow engines with the workflow to local or remote resources to execute workflows. The SHIWA Proxy Server manages certificates needed to execute the workflows on different DCIs. Currently SSP supports sharing of ASKALON, Galaxy, GWES, Kepler, LONI Pipeline, MOTEUR, Pegasus, P-GRADE, ProActive, Triana, Taverna and WS-PGRADE workflows. Further workflow systems can be added to the simulation platform as required by research communities. The FP7 'Building a European Research Community through Interoperable Workflows and Data' (ER-flow) project disseminates the achievements of the SHIWA project to build workflow user communities across Europe. ER-flow provides application supports to research communities within (Astrophysics, Computational Chemistry, Heliophysics and Life Sciences) and beyond (Hydrometeorology and Seismology) to develop, share and run workflows through the simulation platform. The simulation platform supports four usage scenarios: creating and publishing workflows in the repository, searching and selecting workflows in the repository, executing non-native workflows and creating and running meta-workflows. The presentation will outline the CGI concept, the SHIWA Simulation Platform, the ER-flow usage scenarios and how the Hydrometeorology research community runs simulations on SSP.

  2. Land surface evapotranspiration modelling at the regional scale

    Science.gov (United States)

    Raffelli, Giulia; Ferraris, Stefano; Canone, Davide; Previati, Maurizio; Gisolo, Davide; Provenzale, Antonello

    2017-04-01

    Climate change has relevant implications for the environment, water resources and human life in general. The observed increment of mean air temperature, in addition to a more frequent occurrence of extreme events such as droughts, may have a severe effect on the hydrological cycle. Besides climate change, land use changes are assumed to be another relevant component of global change in terms of impacts on terrestrial ecosystems: socio-economic changes have led to conversions between meadows and pastures and in most cases to a complete abandonment of grasslands. Water is subject to different physical processes among which evapotranspiration (ET) is one of the most significant. In fact, ET plays a key role in estimating crop growth, water demand and irrigation water management, so estimating values of ET can be crucial for water resource planning, irrigation requirement and agricultural production. Potential evapotranspiration (PET) is the amount of evaporation that occurs when a sufficient water source is available. It can be estimated just knowing temperatures (mean, maximum and minimum) and solar radiation. Actual evapotranspiration (AET) is instead the real quantity of water which is consumed by soil and vegetation; it is obtained as a fraction of PET. The aim of this work was to apply a simplified hydrological model to calculate AET for the province of Turin (Italy) in order to assess the water content and estimate the groundwater recharge at a regional scale. The soil is seen as a bucket (FAO56 model, Allen et al., 1998) made of different layers, which interact with water and vegetation. The water balance is given by precipitations (both rain and snow) and dew as positive inputs, while AET, runoff and drainage represent the rate of water escaping from soil. The difference between inputs and outputs is the water stock. Model data inputs are: soil characteristics (percentage of clay, silt, sand, rocks and organic matter); soil depth; the wilting point (i.e. the

  3. What are the hydro-meteorological controls on flood characteristics?

    Science.gov (United States)

    Nied, Manuela; Schröter, Kai; Lüdtke, Stefan; Nguyen, Viet Dung; Merz, Bruno

    2017-02-01

    Flood events can be expressed by a variety of characteristics such as flood magnitude and extent, event duration or incurred loss. Flood estimation and management may benefit from understanding how the different flood characteristics relate to the hydrological catchment conditions preceding the event and to the meteorological conditions throughout the event. In this study, we therefore propose a methodology to investigate the hydro-meteorological controls on different flood characteristics, based on the simulation of the complete flood risk chain from the flood triggering precipitation event, through runoff generation in the catchment, flood routing and possible inundation in the river system and floodplains to flood loss. Conditional cumulative distribution functions and regression tree analysis delineate the seasonal varying flood processes and indicate that the effect of the hydrological pre-conditions, i.e. soil moisture patterns, and of the meteorological conditions, i.e. weather patterns, depends on the considered flood characteristic. The methodology is exemplified for the Elbe catchment. In this catchment, the length of the build-up period, the event duration and the number of gauges undergoing at least a 10-year flood are governed by weather patterns. The affected length and the number of gauges undergoing at least a 2-year flood are however governed by soil moisture patterns. In case of flood severity and loss, the controlling factor is less pronounced. Severity is slightly governed by soil moisture patterns whereas loss is slightly governed by weather patterns. The study highlights that flood magnitude and extent arise from different flood generation processes and concludes that soil moisture patterns as well as weather patterns are not only beneficial to inform on possible flood occurrence but also on the involved flood processes and resulting flood characteristics.

  4. Hydrometeorological threshold conditions for debris flow initiation in Norway

    Directory of Open Access Journals (Sweden)

    N. K. Meyer

    2012-10-01

    Full Text Available Debris flows, triggered by extreme precipitation events and rapid snow melt, cause considerable damage to the Norwegian infrastructure every year. To define intensity-duration (ID thresholds for debris flow initiation critical water supply conditions arising from intensive rainfall or snow melt were assessed on the basis of daily hydro-meteorological information for 502 documented debris flow events. Two threshold types were computed: one based on absolute ID relationships and one using ID relationships normalized by the local precipitation day normal (PDN. For each threshold type, minimum, medium and maximum threshold values were defined by fitting power law curves along the 10th, 50th and 90th percentiles of the data population. Depending on the duration of the event, the absolute threshold intensities needed for debris flow initiation vary between 15 and 107 mm day−1. Since the PDN changes locally, the normalized thresholds show spatial variations. Depending on location, duration and threshold level, the normalized threshold intensities vary between 6 and 250 mm day−1. The thresholds obtained were used for a frequency analysis of over-threshold events giving an estimation of the exceedance probability and thus potential for debris flow events in different parts of Norway. The absolute thresholds are most often exceeded along the west coast, while the normalized thresholds are most frequently exceeded on the west-facing slopes of the Norwegian mountain ranges. The minimum thresholds derived in this study are in the range of other thresholds obtained for regions with a climate comparable to Norway. Statistics reveal that the normalized threshold is more reliable than the absolute threshold as the former shows no spatial clustering of debris flows related to water supply events captured by the threshold.

  5. Modeling the Driving Forces of the Land Use and Land Cover Changes Along the Upper Yangtze River of China

    Science.gov (United States)

    Yin, Run Sheng; Xiang, Qing; Xu, Jin Tao; Deng, Xiang Zheng

    2010-03-01

    Induced by high population density, rapid but uneven economic growth, and historic resource exploitation, China’s upper Yangtze basin has witnessed remarkable changes in land use and cover, which have resulted in severe environmental consequences, such as flooding, soil erosion, and habitat loss. This article examines the causes of land use and land cover change (LUCC) along the Jinsha River, one primary section of the upper Yangtze, aiming to better understand the human impact on the dynamic LUCC process and to support necessary policy actions for more sustainable land use and environmental protection. Using a repeated cross-sectional dataset covering 31 counties over four time periods from 1975 to 2000, we develop a fractional logit model to empirically determine the effects of socioeconomic and institutional factors on changes for cropland, forestland, and grassland. It is shown that population expansion, food self-sufficiency, and better market access drove cropland expansion, while industrial development contributed significantly to the increase of forestland and the decrease of other land uses. Similarly, stable tenure had a positive effect on forest protection. Moreover, past land use decisions were less significantly influenced by distorted market signals. We believe that these and other findings carry important policy implications.

  6. The transparency, reliability and utility of tropical rainforest land-use and land-cover change models.

    Science.gov (United States)

    Rosa, Isabel M D; Ahmed, Sadia E; Ewers, Robert M

    2014-06-01

    Land-use and land-cover (LULC) change is one of the largest drivers of biodiversity loss and carbon emissions globally. We use the tropical rainforests of the Amazon, the Congo basin and South-East Asia as a case study to investigate spatial predictive models of LULC change. Current predictions differ in their modelling approaches, are highly variable and often poorly validated. We carried out a quantitative review of 48 modelling methodologies, considering model spatio-temporal scales, inputs, calibration and validation methods. In addition, we requested model outputs from each of the models reviewed and carried out a quantitative assessment of model performance for tropical LULC predictions in the Brazilian Amazon. We highlight existing shortfalls in the discipline and uncover three key points that need addressing to improve the transparency, reliability and utility of tropical LULC change models: (1) a lack of openness with regard to describing and making available the model inputs and model code; (2) the difficulties of conducting appropriate model validations; and (3) the difficulty that users of tropical LULC models face in obtaining the model predictions to help inform their own analyses and policy decisions. We further draw comparisons between tropical LULC change models in the tropics and the modelling approaches and paradigms in other disciplines, and suggest that recent changes in the climate change and species distribution modelling communities may provide a pathway that tropical LULC change modellers may emulate to further improve the discipline. Climate change models have exerted considerable influence over public perceptions of climate change and now impact policy decisions at all political levels. We suggest that tropical LULC change models have an equally high potential to influence public opinion and impact the development of land-use policies based on plausible future scenarios, but, to do that reliably may require further improvements in the

  7. Urban flood early warning systems: approaches to hydrometeorological forecasting and communicating risk

    Science.gov (United States)

    Cranston, Michael; Speight, Linda; Maxey, Richard; Tavendale, Amy; Buchanan, Peter

    2015-04-01

    One of the main challenges for the flood forecasting community remains the provision of reliable early warnings of surface (or pluvial) flooding. The Scottish Flood Forecasting Service has been developing approaches for forecasting the risk of surface water flooding including capitalising on the latest developments in quantitative precipitation forecasting from the Met Office. A probabilistic Heavy Rainfall Alert decision support tool helps operational forecasters assess the likelihood of surface water flooding against regional rainfall depth-duration estimates from MOGREPS-UK linked to historical short-duration flooding in Scotland. The surface water flood risk is communicated through the daily Flood Guidance Statement to emergency responders. A more recent development is an innovative risk-based hydrometeorological approach that links 24-hour ensemble rainfall forecasts through a hydrological model (Grid-to-Grid) to a library of impact assessments (Speight et al., 2015). The early warning tool - FEWS Glasgow - presents the risk of flooding to people, property and transport across a 1km grid over the city of Glasgow with a lead time of 24 hours. Communication of the risk was presented in a bespoke surface water flood forecast product designed based on emergency responder requirements and trialled during the 2014 Commonwealth Games in Glasgow. The development of new approaches to surface water flood forecasting are leading to improved methods of communicating the risk and better performance in early warning with a reduction in false alarm rates with summer flood guidance in 2014 (67%) compared to 2013 (81%) - although verification of instances of surface water flooding remains difficult. However the introduction of more demanding hydrometeorological capabilities with associated greater levels of uncertainty does lead to an increased demand on operational flood forecasting skills and resources. Speight, L., Cole, S.J., Moore, R.J., Pierce, C., Wright, B., Golding, B

  8. Modeling Forest Succession among Ecological Land Units in Northern Minnesota

    Directory of Open Access Journals (Sweden)

    George Host

    1998-12-01

    Full Text Available Field and modeling studies were used to quantify potential successional pathways among fine-scale ecological classification units within two geomorphic regions of north-central Minnesota. Soil and overstory data were collected on plots stratified across low-relief ground moraines and undulating sand dunes. Each geomorphic feature was sampled across gradients of topography or soil texture. Overstory conditions were sampled using five variable-radius point samples per plot; soil samples were analyzed for carbon and nitrogen content. Climatic, forest composition, and soil data were used to parameterize the sample plots for use with LINKAGES, a forest growth model that simulates changes in composition and soil characteristics over time. Forest composition and soil properties varied within and among geomorphic features. LINKAGES simulations were using "bare ground" and the current overstory as starting conditions. Northern hardwoods or pines dominated the late-successional communities of morainal and dune landforms, respectively. The morainal landforms were dominated by yellow birch and sugar maple; yellow birch reached its maximum abundance in intermediate landscape positions. On the dune sites, pine was most abundant in drier landscape positions, with white spruce increasing in abundance with increasing soil moisture and N content. The differences in measured soil properties and predicted late-successional composition indicate that ecological land units incorporate some of the key variables that govern forest composition and structure. They further show the value of ecological classification and modeling for developing forest management strategies that incorporate the spatial and temporal dynamics of forest ecosystems.

  9. SMOS brightness temperature assimilation into the Community Land Model

    Directory of Open Access Journals (Sweden)

    D. Rains

    2017-11-01

    Full Text Available SMOS (Soil Moisture and Ocean Salinity mission brightness temperatures at a single incident angle are assimilated into the Community Land Model (CLM across Australia to improve soil moisture simulations. Therefore, the data assimilation system DasPy is coupled to the local ensemble transform Kalman filter (LETKF as well as to the Community Microwave Emission Model (CMEM. Brightness temperature climatologies are precomputed to enable the assimilation of brightness temperature anomalies, making use of 6 years of SMOS data (2010–2015. Mean correlation R with in situ measurements increases moderately from 0.61 to 0.68 (11 % for upper soil layers if the root zone is included in the updates. A reduced improvement of 5 % is achieved if the assimilation is restricted to the upper soil layers. Root-zone simulations improve by 7 % when updating both the top layers and root zone, and by 4 % when only updating the top layers. Mean increments and increment standard deviations are compared for the experiments. The long-term assimilation impact is analysed by looking at a set of quantiles computed for soil moisture at each grid cell. Within hydrological monitoring systems, extreme dry or wet conditions are often defined via their relative occurrence, adding great importance to assimilation-induced quantile changes. Although still being limited now, longer L-band radiometer time series will become available and make model output improved by assimilating such data that are more usable for extreme event statistics.

  10. Historical reconstruction of spatial distribution of land use/land cover in the early reclaimed time of Northeast China——Based on the HLURM model

    Science.gov (United States)

    Yang, Yuanyuan; Zhang, Shuwen; Liu, Yansui

    2017-04-01

    Understanding long-term human-environment interactions is essential to understanding changes in terrestrial ecosystems and this requires historical reconstruction of past land cover changes. Historical reconstruction of land use/land cover (LULC) aims to reproduce information concerning past land use, not only the quantity of land use/cover in a historical period, but also the spatial distribution. Recently, improved remote sensing technology has made feasible the continuous observation of land cover. However, remotely-sensed data have only existed for the last four decades at most, following the advent of the first land satellite, LandSat-1, launched in 1972. Prior to that, other data sources must be relied on, which may cover the global scale but often inconsistently. In this context, increasing numbers of researchers have made efforts to reconstruct historical LULC based on prime data sources and research approaches. And significant progress in gathering historical land change data has been made both at global and regional scales. However, most of the existing historical LULC reconstructions do not sufficiently meet the requirements of climate assessments due to insufficient spatial and thematic detail and the lack of consideration of various land change types. Most current studies do not thematically represent 100% of the land area, and ignore the consideration of completing land categories and land conversion types. Current research mainly focuses on arable land, wetland and forestland and it does not provide information on land categories such as settlement, water, and other land types. It is a research direction to build historical spatial land use and land cover datasets with high resolution. This paper provides a retrospective overview of historical reconstruction methods of past land-cover based on the prime data sources and research approaches. This research also explored the possibility of building a spatial-explicit modeling framework named HLURM

  11. Modelling Nitrogen Oxides in Los Angeles Using a Hybrid Dispersion/Land Use Regression Model

    Science.gov (United States)

    Wilton, Darren C.

    The goal of this dissertation is to develop models capable of predicting long term annual average NOx concentrations in urban areas. Predictions from simple meteorological dispersion models and seasonal proxies for NO2 oxidation were included as covariates in a land use regression (LUR) model for NOx in Los Angeles, CA. The NO x measurements were obtained from a comprehensive measurement campaign that is part of the Multi-Ethnic Study of Atherosclerosis Air Pollution Study (MESA Air). Simple land use regression models were initially developed using a suite of GIS-derived land use variables developed from various buffer sizes (R²=0.15). Caline3, a simple steady-state Gaussian line source model, was initially incorporated into the land-use regression framework. The addition of this spatio-temporally varying Caline3 covariate improved the simple LUR model predictions. The extent of improvement was much more pronounced for models based solely on the summer measurements (simple LUR: R²=0.45; Caline3/LUR: R²=0.70), than it was for models based on all seasons (R²=0.20). We then used a Lagrangian dispersion model to convert static land use covariates for population density, commercial/industrial area into spatially and temporally varying covariates. The inclusion of these covariates resulted in significant improvement in model prediction (R²=0.57). In addition to the dispersion model covariates described above, a two-week average value of daily peak-hour ozone was included as a surrogate of the oxidation of NO2 during the different sampling periods. This additional covariate further improved overall model performance for all models. The best model by 10-fold cross validation (R²=0.73) contained the Caline3 prediction, a static covariate for length of A3 roads within 50 meters, the Calpuff-adjusted covariates derived from both population density and industrial/commercial land area, and the ozone covariate. This model was tested against annual average NOx

  12. Assimilation of neural network soil moisture in land surface models

    Science.gov (United States)

    Rodriguez-Fernandez, Nemesio; de Rosnay, Patricia; Albergel, Clement; Aires, Filipe; Prigent, Catherine; Kerr, Yann; Richaume, Philippe; Muñoz-Sabater, Joaquin; Drusch, Matthias

    2017-04-01

    In this study a set of land surface data assimilation (DA) experiments making use of satellite derived soil moisture (SM) are presented. These experiments have two objectives: (1) to test the information content of satellite remote sensing of soil moisture for numerical weather prediction (NWP) models, and (2) to test a simplified assimilation of these data through the use of a Neural Network (NN) retrieval. Advanced Scatterometer (ASCAT) and Soil Moisture and Ocean Salinity (SMOS) data were used. The SMOS soil moisture dataset was obtained specifically for this project training a NN using SMOS brightness temperatures as input and using as reference for the training European Centre for Medium-Range Weather Forecasts (ECMWF) H-TESSEL SM fields. In this way, the SMOS NN SM dataset has a similar climatology to that of the model and it does not present a global bias with respect to the model. The DA experiments are computed using a surface-only Land Data Assimilation System (so-LDAS) based on the HTESSEL land surface model. This system is very computationally efficient and allows to perform long surface assimilation experiments (one whole year, 2012). SMOS NN SM DA experiments are compared to ASCAT SM DA experiments. In both cases, experiments with and without 2 m air temperature and relative humidity DA are discussed using different observation errors for the ASCAT and SMOS datasets. Seasonal, geographical and soil-depth-related differences between the results of those experiments are presented and discussed. The different SM analysed fields are evaluated against a large number of in situ measurements of SM. On average, the SM analysis gives in general similar results to the model open loop with no assimilation even if significant differences can be seen for specific sites with in situ measurements. The sensitivity to observation errors to the SM dataset slightly differs depending on the networks of in situ measurements, however it is relatively low for the tests

  13. Using Eddy Covariance Tower Clusters To Evaluate Biogeophysical Impacts Of Land Cover In The Community Land Model (CLM)

    Science.gov (United States)

    Burakowski, E. A.; Ollinger, S. V.; Bonan, G. B.; Ouimette, A.; Lepine, L. C.; Tawfik, A. B.; Zarzycki, C. M.; Fogarty, S.; Novick, K. A.

    2015-12-01

    The Community Land Model (CLM) land surface model has been used widely to evaluate biogeophysical responses to land cover and land use change. Here, we compare surface attributes collected from eddy covariance towers clusters to uncoupled point CLM (PTCLM) simulations. The tower clusters collect surface energy fluxes over adjacent forested and deforested land surface types located within 10-km of each other in temperate eastern North America. Summer surface albedo is very well simulated over cropland, C-3 grassland, and broadleaf deciduous temperate forests. In winter, modeled snow cover persists longer in spring than at the tower sites, resulting in higher average winter and spring albedo. Latent heat does not vary significantly among the three tower sites. PTCLM underestimates forest latent heat and overestimates cropland and grassland summer latent heat. We evaluate temperature differences between forested and deforested sites due to changes in surface albedo, energy redistribution due to changes in surface roughness, and energy redistribution due to changes in latent and sensible heat partitioning (e.g., Bowen ratio). Surprisingly, temperature differences resulting from radiative forcing due to changes in surface albedo are relatively minor at the tower sites and generally too high in PTCLM. We conclude that the increased surface roughness of forests contributes strongly to nocturnal cooling over deforested tower sites in winter and daytime warming in summer. The importance of biogeophysical coupling between the land surface and atmosphere on energy redistribution due to surface roughness is explored using high-resolution (28-km) Variable Resolution Community Earth System Model (VR-CESM) simulations.

  14. Quantifying and Analysing Neighbourhood Characteristics Supporting Urban Land-Use Modelling

    DEFF Research Database (Denmark)

    Hansen, Henning Sten

    2009-01-01

    Land-use modelling and spatial scenarios have gained increased attention as a means to meet the challenge of reducing uncertainty in the spatial planning and decision-making. Several organisations have developed software for land-use modelling. Many of the recent modelling efforts incorporate cel...

  15. Participatory Scenario Development to Address Potential Impacts of Land Use Change: An Example from the Italian Alps

    Directory of Open Access Journals (Sweden)

    Žiga Malek

    2015-05-01

    Full Text Available Changes to land use such as the removal of natural vegetation and expansion of urban areas can result in degradation of the landscape and an increase in hydro-meteorological risk. This has led to higher interest by decision-makers and scientists in the future consequences of these drivers. Scenario development can be a useful tool for addressing the high uncertainty regarding modeling future land use changes. Scenarios are not exact forecasts, but images of plausible futures. When studying future land dynamics, emphasis should be given to areas experiencing high rates of socioeconomic change. We have focused on the eastern Italian Alps, which face increasing pressure from tourism development. Identified drivers of local land use change are mostly external and difficult to quantify. This area, characterized by a traditional Alpine landscape, is subject to high levels of hydro-meteorological risk, another reason to study potential future land use changes. We tested a scenario generation method based on existing decisions and assumptions about future tourism development. We aimed to develop a framework leading to plausible scenarios that can overcome data inaccessibility and address external drivers. We combined qualitative methods, such as stakeholder interviews and cognitive mapping, with geospatial methods, such as geographic information systems, geostatistics, and environmental modeling. We involved stakeholders from the beginning to support the steps of generating data, understanding the system of land use change, and developing a land use change model for scenario development. In this way, we generated spatio-temporal scenarios that can assist future spatial planning and improve preparedness for possible undesirable development.

  16. A large set of potential past, present and future hydro-meteorological time series for the UK

    Directory of Open Access Journals (Sweden)

    B. P. Guillod

    2018-01-01

    Full Text Available Hydro-meteorological extremes such as drought and heavy precipitation can have large impacts on society and the economy. With potentially increasing risks associated with such events due to climate change, properly assessing the associated impacts and uncertainties is critical for adequate adaptation. However, the application of risk-based approaches often requires large sets of extreme events, which are not commonly available. Here, we present such a large set of hydro-meteorological time series for recent past and future conditions for the United Kingdom based on weather@home 2, a modelling framework consisting of a global climate model (GCM driven by observed or projected sea surface temperature (SST and sea ice which is downscaled to 25 km over the European domain by a regional climate model (RCM. Sets of 100 time series are generated for each of (i a historical baseline (1900–2006, (ii five near-future scenarios (2020–2049 and (iii five far-future scenarios (2070–2099. The five scenarios in each future time slice all follow the Representative Concentration Pathway 8.5 (RCP8.5 and sample the range of sea surface temperature and sea ice changes from CMIP5 (Coupled Model Intercomparison Project Phase 5 models. Validation of the historical baseline highlights good performance for temperature and potential evaporation, but substantial seasonal biases in mean precipitation, which are corrected using a linear approach. For extremes in low precipitation over a long accumulation period ( > 3 months and shorter-duration high precipitation (1–30 days, the time series generally represents past statistics well. Future projections show small precipitation increases in winter but large decreases in summer on average, leading to an overall drying, consistently with the most recent UK Climate Projections (UKCP09 but larger in magnitude than the latter. Both drought and high-precipitation events are projected to increase in frequency and

  17. A large set of potential past, present and future hydro-meteorological time series for the UK

    Science.gov (United States)

    Guillod, Benoit P.; Jones, Richard G.; Dadson, Simon J.; Coxon, Gemma; Bussi, Gianbattista; Freer, James; Kay, Alison L.; Massey, Neil R.; Sparrow, Sarah N.; Wallom, David C. H.; Allen, Myles R.; Hall, Jim W.

    2018-01-01

    Hydro-meteorological extremes such as drought and heavy precipitation can have large impacts on society and the economy. With potentially increasing risks associated with such events due to climate change, properly assessing the associated impacts and uncertainties is critical for adequate adaptation. However, the application of risk-based approaches often requires large sets of extreme events, which are not commonly available. Here, we present such a large set of hydro-meteorological time series for recent past and future conditions for the United Kingdom based on weather@home 2, a modelling framework consisting of a global climate model (GCM) driven by observed or projected sea surface temperature (SST) and sea ice which is downscaled to 25 km over the European domain by a regional climate model (RCM). Sets of 100 time series are generated for each of (i) a historical baseline (1900-2006), (ii) five near-future scenarios (2020-2049) and (iii) five far-future scenarios (2070-2099). The five scenarios in each future time slice all follow the Representative Concentration Pathway 8.5 (RCP8.5) and sample the range of sea surface temperature and sea ice changes from CMIP5 (Coupled Model Intercomparison Project Phase 5) models. Validation of the historical baseline highlights good performance for temperature and potential evaporation, but substantial seasonal biases in mean precipitation, which are corrected using a linear approach. For extremes in low precipitation over a long accumulation period ( > 3 months) and shorter-duration high precipitation (1-30 days), the time series generally represents past statistics well. Future projections show small precipitation increases in winter but large decreases in summer on average, leading to an overall drying, consistently with the most recent UK Climate Projections (UKCP09) but larger in magnitude than the latter. Both drought and high-precipitation events are projected to increase in frequency and intensity in most regions

  18. Research priorities in land use and land-cover change for the Earth System and Integrated Assessment Modelling

    NARCIS (Netherlands)

    Hibbard, K.; Janetos, A.; Vuuren, van D.; Pongratz, J.; Rose, S.; Betts, R.; Herold, M.; Feddema, J.

    2010-01-01

    This special issue has highlighted recent and innovative methods and results that integrate observations and modelling analyses of regional to global aspect of biophysical and biogeochemical interactions of land-cover change with the climate system. Both the Earth System and the Integrated

  19. NLDAS VIC Land Surface Model L4 Monthly Climatology 0.125 x 0.125 degree V002

    Data.gov (United States)

    National Aeronautics and Space Administration — Abstract: This data set contains a series of land surface parameters simulated from the VIC land-surface model (LSM) for Phase 2 of the North American Land Data...

  20. NLDAS VIC Land Surface Model L4 Monthly 0.125 x 0.125 degree V002

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set contains a series of land surface parameters simulated from the VIC land-surface model (LSM) for Phase 2 of the North American Land Data Assimilation...

  1. NLDAS VIC Land Surface Model L4 Hourly 0.125 x 0.125 degree V002

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set contains a series of land surface parameters simulated from the VIC land-surface model (LSM) for Phase 2 of the North American Land Data Assimilation...

  2. NLDAS Noah Land Surface Model L4 Hourly 0.125 x 0.125 degree V002

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set contains a series of land surface parameters simulated from the Noah land-surface model (LSM) for Phase 2 of the North American Land Data Assimilation...

  3. NLDAS Noah Land Surface Model L4 Monthly 0.125 x 0.125 degree V002

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set contains a series of land surface parameters simulated from the Noah land-surface model (LSM) for Phase 2 of the North American Land Data Assimilation...

  4. NLDAS Mosaic Land Surface Model L4 Hourly 0.125 x 0.125 degree V002

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set contains a series of land surface parameters simulated from the Mosaic land-surface model (LSM) for Phase 2 of the North American Land Data...

  5. NLDAS Mosaic Land Surface Model L4 Monthly 0.125 x 0.125 degree V002

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set contains a series of land surface parameters simulated from the Mosaic land-surface model (LSM) for Phase 2 of the North American Land Data...

  6. Developing alternative models to acquire land sustainably in the ...

    African Journals Online (AJOL)

    Land redistribution must be accompanied by the relevant resources required for sustainable farming production and its beneficiaries must be capacitated before being settled on farms. Then farming productions must be monitored and evaluated for sustainability. Then, livelihood improvement on land reform beneficiaries ...

  7. Accounting for heterogeneity of public lands in hedonic property models

    Science.gov (United States)

    Charlotte Ham; Patricia A. Champ; John B. Loomis; Robin M. Reich

    2012-01-01

    Open space lands, national forests in particular, are usually treated as homogeneous entities in hedonic price studies. Failure to account for the heterogeneous nature of public open spaces may result in inappropriate inferences about the benefits of proximate location to such lands. In this study the hedonic price method is used to estimate the marginal values for...

  8. developing a one stop shop model for integrated land information

    African Journals Online (AJOL)

    DEPT OF AGRICULTURAL ENGINEERING

    human settlement, land services and land regis- try (Grant, 2004). This paper adopts the one stop shop concept of ... for data on a computer in one office to be accessed on a computer in another office or even in the .... RESULTS AND DISCUSSION. Figure 5 shows the main interface of the devel- oped LANMANK program.

  9. Calibration and validation of land-use models

    NARCIS (Netherlands)

    Vliet, van J.

    2013-01-01

    Land use is constantly changing. For example, urban areas expand as a result of population growth, cropping patterns change to fulfil the demand for bioenergy and natural vegetation recovers in locations where farmers cease to farm. Understanding these changes is pivotal to explore future land-use

  10. The modelling of spatial units (parcels) in the land administration domain model (LADM)

    NARCIS (Netherlands)

    Lemmen, C.H.J.; Van Oosterom, P.J.M.; Thompson, R.J.; Hespanha, J.P.; Uitermark, H.T.

    2010-01-01

    The Land Administration Domain Model (LADM) is under development within the Technical Committee 211 (TC211) of the International Organisation for Standardization (ISO) and identified as ISO 19152. Within the LADM classical cadastral concepts as “parcel” and “boundary” have been extended to be able

  11. Aerodynamics of a Gulfstream G550 Nose Landing Gear Model

    Science.gov (United States)

    Neuhart, Dan H.; Khorrami, Mehdi R.; Choudhari, Meelan M.

    2009-01-01

    In this paper we discuss detailed steady and unsteady aerodynamic measurements of a Gulfstream G550 nose landing gear model. The quarter-scale, high-fidelity model includes part of the lower fuselage and the gear cavity. The full model configuration allowed for removal of various gear components (e.g. light cluster, steering mechanism, hydraulic lines, etc.) in order to document their effects on the local flow field. The measurements were conducted at a Reynolds number of 7.3 x 10(exp 4) based on the shock strut (piston) diameter and a freestream Mach number of 0.166. Additional data were also collected at lower Mach numbers of 0.12 and 0.145 and correspondingly lower Reynolds numbers. The boundary layer on the piston was tripped to enable turbulent flow separation, so as to better mimic the conditions encountered during flight. Steady surface pressures were gathered from an extensive number of static ports on the wheels, door, fuselage, and within the gear cavity. To better understand the resultant flow interactions between gear components, surface pressure fluctuations were collected via sixteen dynamic pressure sensors strategically placed on various subcomponents of the gear. Fifteen of the transducers were flush mounted on the gear surface at fixed locations, while the remaining one was a mobile transducer that could be placed at numerous varying locations. The measured surface pressure spectra are mainly broadband in nature, lacking any local peaks associated with coherent vortex shedding. This finding is in agreement with off-surface flow measurements using PIV that revealed the flow field to be a collection of separated shear layers without any dominant vortex shedding processes.

  12. Combining agent functional types, capitals and services to model land use dynamics

    NARCIS (Netherlands)

    Murray-Rust, D.; van Vliet, J.; Brown, C.; Alam, S. J.; Robinson, D. T.; Verburg, P.H.; Rounsevell, M.D.A.

    2014-01-01

    Models of land use change are becoming increasingly complex as they attempt to explore the effects of climatic, political, economic and demographic change on land systems and the services these systems produce. 'Bottom-up' agent based models are a useful method for exploring the effects of local

  13. Specialization of the Land Administration Domain Model (LADM) : An Option for Expanding the Legal Profiles

    NARCIS (Netherlands)

    Paasch, J.; Van Oosterom, P.; Paulsson, J.; Lemmen, C.

    2013-01-01

    The Land Administration Domain Model, LADM, passed on the 1st of November 2012 unanimously the final vote towards becoming an international standard, ISO 19152. Based on the standard this paper is a proposal for a more detailed classification of interests in land as modelled within LADM and an

  14. Role of land state in a high resolution mesoscale model for ...

    Indian Academy of Sciences (India)

    global models predicted the large scale event, they failed to predict realistic location, timing, amount, intensity and distribution of rainfall over the region. The goal of this study is to assess the impact of land state conditions in simulating this severe event using a high resolution mesoscale model. The land conditions such as ...

  15. Development of a Landforms Model for Puerto Rico and its Application for Land Cover Change Analysis

    Science.gov (United States)

    Sebastian Martinuzzi; William A. Gould; Olga M. Ramos Gonzalez; Brook E. Edwards

    2007-01-01

    Comprehensive analysis of land morphology is essential to supporting a wide range environmental studies. We developed a landforms model that identifies eleven landform units for Puerto Rico based on parameters of land position and slope. The model is capable of extracting operational information in a simple way and is adaptable to different environments and objectives...

  16. The dynamics of shifting cultivation captured in an extended Constrained Cellular Automata land use model

    NARCIS (Netherlands)

    Wickramasuriya, R.C.; Bregt, A.K.; Delden, van H.; Hagen-Zanker, A.

    2009-01-01

    This paper presents an extension to the Constrained Cellular Automata (CCA) land use model of White et al. [White, R., Engelen, G., Uljee, I., 1997. The use of constrained cellular automata for high-resolution modelling of urban land-use dynamics. Environment and Planning B: Planning and Design

  17. Nature-based solutions for hydro-meteorological risk reduction and nutrient removal in the Nordic and Arctic regions

    Science.gov (United States)

    Bring, Arvid; Kalantari, Zahra

    2017-04-01

    Natural ecological functions provide essential and fundamental benefits to mankind, but can also be actively employed in nature-based solutions to specific challenges in society. For example, water-related ecosystem services have a role in such societal benefits as flood protection, erosion control, and excess nutrient removal. Ecosystem services may be produced and consumed in different locations, and research has recently attempted to formalize this discrepancy in identifying service providing areas (SPAs), service benefitting areas (SBAs), and service connecting areas (SCAs). However, in terms of water-related services, there is a lack of formal evaluation of how SPAs, SBAs, and SCAs are related to hydrological measures such as discharge, flood recurrence, excess nutrient removal, etc. We seek to map SPAs, SBAs and SCAs for a number of key ecosystem services in the Nordic and Arctic region though established ecological definitions (typically, based on land use) and evaluate the findings alongside metrics of hydrological connectivity (river networks), provisioning areas (runoff generating areas), and benefitting areas (river stretches where water flow is moderated). We make use of extensive GIS analysis using both high-resolution land cover data and river network maps. In the end, the results are expected to contribute to identifying how water-related ecosystem services can be employed as nature-based solutions for hydro-meteorological risk reduction and nutrient removal in a changing climate in the Nordic and Arctic regions.

  18. A novel assessment of the role of land-use and land-cover change in the global carbon cycle, using a new Dynamic Global Vegetation Model version of the CABLE land surface model

    Science.gov (United States)

    Haverd, Vanessa; Smith, Benjamin; Nieradzik, Lars; Briggs, Peter; Canadell, Josep

    2017-04-01

    In recent decades, terrestrial ecosystems have sequestered around 1.2 PgC y-1, an amount equivalent to 20% of fossil-fuel emissions. This land carbon flux is the net result of the impact of changing climate and CO2 on ecosystem productivity (CO2-climate driven land sink ) and deforestation, harvest and secondary forest regrowth (the land-use change (LUC) flux). The future trajectory of the land carbon flux is highly dependent upon the contributions of these processes to the net flux. However their contributions are highly uncertain, in part because the CO2-climate driven land sink and LUC components are often estimated independently, when in fact they are coupled. We provide a novel assessment of global land carbon fluxes (1800-2015) that integrates land-use effects with the effects of changing climate and CO2 on ecosystem productivity. For this, we use a new land-use enabled Dynamic Global Vegetation Model (DGVM) version of the CABLE land surface model, suitable for use in attributing changes in terrestrial carbon balance, and in predicting changes in vegetation cover and associated effects on land-atmosphere exchange. In this model, land-use-change is driven by prescribed gross land-use transitions and harvest areas, which are converted to changes in land-use area and transfer of carbon between pools (soil, litter, biomass, harvested wood products and cleared wood pools). A novel aspect is the treatment of secondary woody vegetation via the coupling between the land-use module and the POP (Populations Order Physiology) module for woody demography and disturbance-mediated landscape heterogeneity. Land-use transitions to and from secondary forest tiles modify the patch age distribution within secondary-vegetated tiles, in turn affecting biomass accumulation and turnover rates and hence the magnitude of the secondary forest sink. The resulting secondary forest patch age distribution also influences the magnitude of the secondary forest harvest and clearance fluxes

  19. Wetland methane modelling over the Scandinavian Arctic: Performance of current land-surface models

    Science.gov (United States)

    Hayman, Garry; Quiquet, Aurélien; Gedney, Nicola; Clark, Douglas; Friend, Andrew; George, Charles; Prigent, Catherine

    2014-05-01

    Wetlands are generally accepted as being the largest, but least well quantified, single natural source of CH4, with global emission estimates ranging from 100-231 Tg yr-1 [1] and for which the Boreal and Arctic regions make a significant contribution [2, 3]. The recent review by Melton et al. [4] has provided a summary of the current state of knowledge on the modelling of wetlands and the outcome of the WETCHIMP model intercomparison exercise. Melton et al. found a large variation in the wetland areas and associated methane emissions from the participating models and varying responses to climate change. In this paper, we report results from offline runs of two land surface models over Scandinavia (JULES, the Joint UK Land Environment Simulator [5, 6] and HYBRID8 [7]), using the same driving meteorological dataset (CRU-NCEP) for the period from January 1980 to December 2010. Although the two land surface models are very different, both models have used a TOPMODEL approach to derive the wetland area and have similar parameterisations of the methane wetland emissions. We find that both models give broadly similar results. They underestimate the wetland areas over Northern Scandinavia, compared to remote sensing and map-based datasets of wetlands [8]. This leads to lower predicted methane emissions compared to those observed on the ground and from aircraft [9]. We will present these findings and identify possible reasons for the underprediction. We will show the sensitivity to using the observed wetland areas to improve the methane emission estimates. References [1] Denman, K., et al.,: Couplings Between Changes in the Climate System and Biogeochemistry, In Climate Change 2007: The Physical Science Basis, Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, United Kingdom, 2007; [2] Smith, L. C., et al.: Siberian peatlands a net carbon sink and global methane source since the early

  20. Land Use and Land Cover Changes under Climate Uncertainty: Modelling the Impacts on Hydropower Production in Western Africa

    Directory of Open Access Journals (Sweden)

    Salomon Obahoundje

    2017-01-01

    Full Text Available The Bui hydropower plant plays a vital role in the socio-economic development of Ghana. This paper attempt to explore the combined effects of climate-land use land cover change on power production using the (WEAP model: Water Evaluation and Planning system. The historical analysis of rainfall and stream flow variability showed that the annual coefficient of variation of rainfall and stream flow are, respectively, 8.6% and 60.85%. The stream flow varied greatly than the rainfall, due to land use land cover changes (LULC. In fact, the LULC analysis revealed important changes in vegetative areas and water bodies. The WEAP model evaluation showed that combined effects of LULC and climate change reduce water availability for all of demand sectors, including hydropower generation at the Bui hydropower plant. However, it was projected that Bui power production will increase by 40.7% and 24.93%, respectively, under wet and adaptation conditions, and decrease by 46% and 2.5%, respectively, under dry and current conditions. The wet condition is defined as an increase in rainfall by 14%, the dry condition as the decrease in rainfall by 15%; current account is business as usual, and the adaptation is as the efficient use of water for the period 2012–2040.

  1. Evaluation of Intensive Construction Land Use in the Emerging City Based on PSR-Entropy model

    Science.gov (United States)

    Jia, Yuanyuan; Lei, Guangyu

    2018-01-01

    A comprehensive understanding of emerging city land utilization and the evaluation of intensive land use in the Emerging City will provide the comprehensive and reliable technical basis for the planning and management. It is an important node. According to the Han cheng from 2008 to 2016 years of land use, based on PSR-Entropy model of land use evaluation system, using entropy method to determine the index weight, the introduction of comprehensive index method to evaluate the degree of land use. The results show that the intensive land use comprehensive evaluation index of Han cheng increased from 2008 to 2015, but the land intensive use can not achieve the standards. The potential of further enhancing space is relatively large.

  2. Developing A One Stop Shop Model For Integrated Land Information ...

    African Journals Online (AJOL)

    Net 2005 and Microsoft Visio. A Land Management Key (LANMANK) program was finally developed with geodatabase capabilities for storing and displaying spatial data as well as other non-spatial data. LANMANK has a unique parcel identifier ...

  3. On the Choice of Soil Hydraulic Models in Land-Surface Schemes

    Science.gov (United States)

    Shao, Yaping; Irannejad, Parviz

    The uncertainties in soil hydraulic functions and soil hydraulic parameters affect the performance of land-surface schemes used in climate and weather prediction models. The Clapp-Hornberger soil hydraulic model of is most widely used in land-surface modelling, while other models favoured by soil physicists are hardly used for the purpose. In this study, we give a summary of four soil hydraulic models and examine the impact of these models on the performance of a land-surface scheme. It is found that inconsistency in soil hydraulic functions and parameters leads to different outcomes in land-surface modelling. We introduce a technique to match the soil hydraulic parameters for different models, so that the disagreement in the description of soil hydraulic properties among different models is reduced, while intrinsic differences in the soil hydraulic functions remain. The numerical tests also show that the land-surface model has a degree of tolerance to the uncertainties in soil hydraulic models, at least in the case of off-line simulations. The van Genuchten model performs well, but is numerically expensive. The Brooks-Corey and Clapp-Hornberger models are sufficiently accurate with numerical efficiency, and are therefore more suitable for land-surface schemes used in atmospheric models.

  4. Signature project 1B-integrated land-use, transportation and environmental modeling.

    Science.gov (United States)

    2014-05-01

    Land use and transportation are inextricably linked. Models that capture the dynamics and interactions of both systems are indispensable for evaluating alternative courses of action in policy and investment. These models must be spatially disaggregat...

  5. Forecasting skills of the ensemble hydro-meteorological system for the Po river floods

    Science.gov (United States)

    Ricciardi, Giuseppe; Montani, Andrea; Paccagnella, Tiziana; Pecora, Silvano; Tonelli, Fabrizio

    2013-04-01

    The Po basin is the largest and most economically important river-basin in Italy. Extreme hydrological events, including floods, flash floods and droughts, are expected to become more severe in the next future due to climate change, and related ground effects are linked both with environmental and social resilience. A Warning Operational Center (WOC) for hydrological event management was created in Emilia Romagna region. In the last years, the WOC faced challenges in legislation, organization, technology and economics, achieving improvements in forecasting skill and information dissemination. Since 2005, an operational forecasting and modelling system for flood modelling and forecasting has been implemented, aimed at supporting and coordinating flood control and emergency management on the whole Po basin. This system, referred to as FEWSPo, has also taken care of environmental aspects of flood forecast. The FEWSPo system has reached a very high level of complexity, due to the combination of three different hydrological-hydraulic chains (HEC-HMS/RAS - MIKE11 NAM/HD, Topkapi/Sobek), with several meteorological inputs (forecasted - COSMOI2, COSMOI7, COSMO-LEPS among others - and observed). In this hydrological and meteorological ensemble the management of the relative predictive uncertainties, which have to be established and communicated to decision makers, is a debated scientific and social challenge. Real time activities face professional, modelling and technological aspects but are also strongly interrelated with organization and human aspects. The authors will report a case study using the operational flood forecast hydro-meteorological ensemble, provided by the MIKE11 chain fed by COSMO_LEPS EQPF. The basic aim of the proposed approach is to analyse limits and opportunities of the long term forecast (with a lead time ranging from 3 to 5 days), for the implementation of low cost actions, also looking for a well informed decision making and the improvement of

  6. Challenges and opportunities in land surface modelling of savanna ecosystems

    Directory of Open Access Journals (Sweden)

    R. Whitley

    2017-10-01

    Full Text Available The savanna complex is a highly diverse global biome that occurs within the seasonally dry tropical to sub-tropical equatorial latitudes and are structurally and functionally distinct from grasslands and forests. Savannas are open-canopy environments that encompass a broad demographic continuum, often characterised by a changing dominance between C3-tree and C4-grass vegetation, where frequent environmental disturbances such as fire modulates the balance between ephemeral and perennial life forms. Climate change is projected to result in significant changes to the savanna floristic structure, with increases to woody biomass expected through CO2 fertilisation in mesic savannas and increased tree mortality expected through increased rainfall interannual variability in xeric savannas. The complex interaction between vegetation and climate that occurs in savannas has traditionally challenged terrestrial biosphere models (TBMs, which aim to simulate the interaction between the atmosphere and the land surface to predict responses of vegetation to changing in environmental forcing. In this review, we examine whether TBMs are able to adequately represent savanna fluxes and what implications potential deficiencies may have for climate change projection scenarios that rely on these models. We start by highlighting the defining characteristic traits and behaviours of savannas, how these differ across continents and how this information is (or is not represented in the structural framework of many TBMs. We highlight three dynamic processes that we believe directly affect the water use and productivity of the savanna system: phenology, root-water access and fire dynamics. Following this, we discuss how these processes are represented in many current-generation TBMs and whether they are suitable for simulating savanna fluxes.Finally, we give an overview of how eddy-covariance observations in combination with other data sources can be used in model

  7. Challenges and opportunities in land surface modelling of savanna ecosystems

    Science.gov (United States)

    Whitley, Rhys; Beringer, Jason; Hutley, Lindsay B.; Abramowitz, Gabriel; De Kauwe, Martin G.; Evans, Bradley; Haverd, Vanessa; Li, Longhui; Moore, Caitlin; Ryu, Youngryel; Scheiter, Simon; Schymanski, Stanislaus J.; Smith, Benjamin; Wang, Ying-Ping; Williams, Mathew; Yu, Qiang

    2017-10-01

    The savanna complex is a highly diverse global biome that occurs within the seasonally dry tropical to sub-tropical equatorial latitudes and are structurally and functionally distinct from grasslands and forests. Savannas are open-canopy environments that encompass a broad demographic continuum, often characterised by a changing dominance between C3-tree and C4-grass vegetation, where frequent environmental disturbances such as fire modulates the balance between ephemeral and perennial life forms. Climate change is projected to result in significant changes to the savanna floristic structure, with increases to woody biomass expected through CO2 fertilisation in mesic savannas and increased tree mortality expected through increased rainfall interannual variability in xeric savannas. The complex interaction between vegetation and climate that occurs in savannas has traditionally challenged terrestrial biosphere models (TBMs), which aim to simulate the interaction between the atmosphere and the land surface to predict responses of vegetation to changing in environmental forcing. In this review, we examine whether TBMs are able to adequately represent savanna fluxes and what implications potential deficiencies may have for climate change projection scenarios that rely on these models. We start by highlighting the defining characteristic traits and behaviours of savannas, how these differ across continents and how this information is (or is not) represented in the structural framework of many TBMs. We highlight three dynamic processes that we believe directly affect the water use and productivity of the savanna system: phenology, root-water access and fire dynamics. Following this, we discuss how these processes are represented in many current-generation TBMs and whether they are suitable for simulating savanna fluxes.Finally, we give an overview of how eddy-covariance observations in combination with other data sources can be used in model benchmarking and

  8. Uncertainties in coupled regional Arctic climate simulations associated with the used land surface model

    Science.gov (United States)

    Matthes, Heidrun; Rinke, Annette; Zhou, Xu; Dethloff, Klaus

    2017-08-01

    Permafrost is one of the most important components of Arctic land. Regional atmosphere-snow-permafrost interactions can be best studied with Regional Climate Models (RCMs) due to their higher horizontal resolution compared to global climate models. The development of Arctic RCMs with sophisticated land models is therefore very important. Comparing RCMs with different land surface model (LSM) components then allows the quantification of the uncertainties associated with the LSM. This study analyzes two simulations of coupled atmosphere-land RCMs over the Arctic, which differ only in their land component, while the atmospheric model component is the same. Specifically, we examine HIRHAM5-CLM4 (HIRHAM5 coupled with the sophisticated land model CLM4) and HIRHAM5 (HIRHAM5 coupled with the simpler land model of ECHAM5). We discuss the two models' abilities to represent observations on permafrost-like permafrost extent, active layer thickness (ALT), and soil temperature profiles, as well as on the representation of the Arctic atmosphere, based on simulations over 1979-2014. In comparison to HIRHAM5, HIRHAM5-CLM4 significantly reduces the simulated bias in ALT and winter soil temperatures. We find that the simulation of soil temperature and subsequently ALT is sensitive to soil thermal and hydraulic parameter representation in the models. The simulation of permafrost extent is sensitive to the initial soil temperature state in the models. Both HIRHAM5 and HIRHAM5-CLM4 do similarly well in modeling the Arctic 2 m air temperature and atmospheric circulation. Changing the land model impacts the 2 m air temperature significantly over land and the atmospheric circulation predominantly over the Arctic Ocean, associated with changes in baroclinic cyclones.

  9. 2-way coupling the hydrological land surface model PROMET with the regional climate model MM5

    Directory of Open Access Journals (Sweden)

    F. Zabel

    2013-05-01

    Full Text Available Most land surface hydrological models (LSHMs consider land surface processes (e.g. soil–plant–atmosphere interactions, lateral water flows, snow and ice in a spatially detailed manner. The atmosphere is considered as exogenous driver, neglecting feedbacks between the land surface and the atmosphere. On the other hand, regional climate models (RCMs generally simulate land surface processes through coarse descriptions and spatial scales but include land–atmosphere interactions. What is the impact of the differently applied model physics and spatial resolution of LSHMs on the performance of RCMs? What feedback effects are induced by different land surface models? This study analyses the impact of replacing the land surface module (LSM within an RCM with a high resolution LSHM. A 2-way coupling approach was applied using the LSHM PROMET (1 × 1 km2 and the atmospheric part of the RCM MM5 (45 × 45 km2. The scaling interface SCALMET is used for down- and upscaling the linear and non-linear fluxes between the model scales. The change in the atmospheric response by MM5 using the LSHM is analysed, and its quality is compared to observations of temperature and precipitation for a 4 yr period from 1996 to 1999 for the Upper Danube catchment. By substituting the Noah-LSM with PROMET, simulated non-bias-corrected near-surface air temperature improves for annual, monthly and daily courses when compared to measurements from 277 meteorological weather stations within the Upper Danube catchment. The mean annual bias was improved from −0.85 to −0.13 K. In particular, the improved afternoon heating from May to September is caused by increased sensible heat flux and decreased latent heat flux as well as more incoming solar radiation in the fully coupled PROMET/MM5 in comparison to the NOAH/MM5 simulation. Triggered by the LSM replacement, precipitation overall is reduced; however simulated precipitation amounts are still of high uncertainty, both

  10. Incorporation of water vapor transfer in the JULES Land Surface Model: implications for key soil variables and land surface fluxes

    OpenAIRE

    Garcia Gonzalez, R.; Verhoef, A.; Luigi Vidale, P.; I. Braud

    2012-01-01

    This study focuses on the mechanisms underlying water and heat transfer in upper soil layers, and their effects on soil physical prognostic variables and the individual components of the energy balance. The skill of the JULES (Joint UK Environment Simulator) land surface model (LSM) to simulate key soil variables, such as soil moisture content and surface temperature, and fluxes such as evaporation, is investigated. The Richards equation for soil water transfer, as used in most LSMs, was upda...

  11. Extension of the SIM Hydrometeorological Reanalysis Over the Entire 20th Century by Combination of Observations and Statistical Downscaling

    Science.gov (United States)

    Minvielle, M.; Céron, J.; Page, C.

    2013-12-01

    The SAFRAN-ISBA-MODCOU (SIM) system is a combination of three different components: an atmospheric analysis system (SAFRAN) providing the atmospheric forcing for a land surface model (ISBA) that computes surface water and energy budgets and a hydrological model (MODCOU) that provides river flows and level of several aquifers. The variables generated by the SIM chain constitute the SIM reanalysis and the current version only covers the 1958-2012 period. However, long climate datasets are required for evaluation and verification of climate hindcasts/forecasts and to isolate the contribution of natural decadal variability from that of anthropogenic forcing to climate variations. The aim of this work is to extend of the fine-mesh SIM reanalysis to the entire 20th century, especially focusing on temperature and rainfall over France, but also soil wetness and river flows. This extension will first allow a detailed investigation of the influence of decadal variability on France at very fine spatial scales and will provide crucial information for climate model evaluation. Before 1958, the density of available observations from Météo-France necessary to force SAFRAN (rainfall, snow, wind, temperature, humidity, cloudiness) is much lower than today, and not sufficient to produce a correct SIM reanalysis. That's why is has been decided to use the available atmospheric observations over the past decades combined to a statistical downscaling algorithm to overcome the lack of observations. The DSCLIM software package implemented by the CERFACS and using a weather typing based statistical methodology will be used as statistical downscaling method to reconstruct the atmospheric variables necessary to force the ISBA-MODCOU hydrological component. The first stage of this work was to estimate and compare the bias and strengths of the two approaches in their ability to reconstruct the past decades. In this sense, SIM hydro-meteorological experiments were performed for some recent

  12. Rewilding as nature based solution in land management

    Science.gov (United States)

    Novara, Agata; Gristina, Luciano; Keesstra, Saskia; Pereira, Paulo; Cerda, Artemio

    2017-04-01

    Rewilding is an effective tool of ecological restoration and a nature based solution for hydro-meteorological risk control. Rewilding contributes to reduce flood risk, resist droughts, helps to restore soil organic matter content, increases soil and plant biodiversity, improves the overall ecosystem and human health. The key element of rewilding is not the nature control, but following the natural processes to restore the key soil ecological factors and their connectivity. Rewilding can be applicable at different ecosystem stages, from natural reserve to more anthropogenic system such as agricultural land through the restoration of wild soil function trough permaculture or forest farming. The proposed nature based solution not only avoid the investment in traditional engineering but it also an opportunities for creating new economics model based on wild nature (ecoturism, education, wild edible plants). This work is a review of applied rewilding actions and considerations on future nature based solutions applications will be discussed .

  13. Information Entropy Suggests Stronger Nonlinear Associations between Hydro-Meteorological Variables and ENSO

    Directory of Open Access Journals (Sweden)

    Tue M. Vu

    2018-01-01

    Full Text Available Understanding the teleconnections between hydro-meteorological data and the El Niño–Southern Oscillation cycle (ENSO is an important step towards developing flood early warning systems. In this study, the concept of mutual information (MI was applied using marginal and joint information entropy to quantify the linear and non-linear relationship between annual streamflow, extreme precipitation indices over Mekong river basin, and ENSO. We primarily used Pearson correlation as a linear association metric for comparison with mutual information. The analysis was performed at four hydro-meteorological stations located on the mainstream Mekong river basin. It was observed that the nonlinear correlation information is comparatively higher between the large-scale climate index and local hydro-meteorology data in comparison to the traditional linear correlation information. The spatial analysis was carried out using all the grid points in the river basin, which suggests a spatial dependence structure between precipitation extremes and ENSO. Overall, this study suggests that mutual information approach can further detect more meaningful connections between large-scale climate indices and hydro-meteorological variables at different spatio-temporal scales. Application of nonlinear mutual information metric can be an efficient tool to better understand hydro-climatic variables dynamics resulting in improved climate-informed adaptation strategies.

  14. Trend Analysis of Hydro-meteorological variables in the coastal area ...

    African Journals Online (AJOL)

    ADOWIE PERE

    ABSTRACT; This paper presents the application of Mann-Kendall trend test and Standard. Anomaly index onhydro-meteorological variables in the coastal area of Lagos state in order to determine the nature of trend and level of significance. The hydro-meteorological data such as air temperature, relative humidity, wind ...

  15. Modeling and analyzing land use and land cover change in Metropolitan Birmingham Area using Landsat TM, OLI data

    Science.gov (United States)

    Jing, Xuehan

    The Birmingham Metropolitan Area experienced land use land cover (LULC) change over the last three decades, such as the development of urban area, the development of transportation system, deforestation, and rise of population. The main purpose of the thesis is to model and analyze the LULC change through last three decades in Birmingham area, and also simulate the LULC in next three decades. Landsat 5 Thematic Mapper (TM) and Landsat 8 Operational Land Imager (OLI) data from U.S. Geological Survey (USGS) is used for investigating the LULC in Birmingham area. Supervised Classification is used; the maximum overall accuracy is 86.33%. Drivers such as transportation, topographic measures, population and income, location measures are analyzed. Remote sensing indices are also derived from Landsat data, such as NDVI, NDBI, MNDWI, and LST. Pearson's Correlation test is run among the LULC proportion, drivers within counties and census tracts. Finally, the cellular automation model SLEUTH is used to simulate the future pattern of LULC. The results shows the Birmingham experienced a significant LULC change in last three decades. Transportation and slope are two main factors in terms of LULC change. In summary, the thesis completes a systematic LULC classification in Birmingham area in last three decades, and uses different methods to model and analyze LULC and eventually simulate the LULC pattern in next three decades.

  16. Estimation of Arable Land Loss in Shandong Province, China based on BFAST Model

    Science.gov (United States)

    Liu, Y.

    2016-12-01

    With the rapid development of national economy and rise of industrialization, China has been one of the countries which has the fastest urbanization process. From 2001 to 2005, China lost over 2000 km2 fertile arable land every year because of urban expansion. Arable land area declining continuously poses a threat to China's food security. Land survey is the direct way to statistic the arable land status, which lasts long time and needs mounts of financial support. Remote sensing is a perfect way to survey land use and its dynamics at large scale. This paper aims to evaluate the detailed status of agricultural land loss of Shandong Province, China by using BFAST (Breaks for Additive Seasonal and Trend) model. First, the 30m spatial resolution global land cover products GlobeLand30 in 2000 and 2010 are used to locate pixels transforming from agricultural land to artificial cover during this period. Within a MODIS pixel (250m) area, if over half of GlobeLand30 pixels have changed from arable land to artificial cover, then the responding MODIS pixel is classified as changed area, whose phenology reflected by NDVI time series curve will also change. Then, BFAST is used to detect the break point which represents the time of change occurred using MODIS NDVI time series data. From 2002 to 2010, Shandong Province lost its 1063.03 km2 arable land in total. Arable land loss has a declining trend in each year and most loss occurred in 2002 and 2003. Spatially, cities which has higher level of economic development in central and eastern regions lost more arable land. Finally, compare this result with statistical data from China's national Bureau of Statistics, there is a strong positive relationship.

  17. The Nexus Land-Use model version 1.0, an approach articulating biophysical potentials and economic dynamics to model competition for land-use

    Directory of Open Access Journals (Sweden)

    F. Souty

    2012-10-01

    Full Text Available Interactions between food demand, biomass energy and forest preservation are driving both food prices and land-use changes, regionally and globally. This study presents a new model called Nexus Land-Use version 1.0 which describes these interactions through a generic representation of agricultural intensification mechanisms within agricultural lands. The Nexus Land-Use model equations combine biophysics and economics into a single coherent framework to calculate crop yields, food prices, and resulting pasture and cropland areas within 12 regions inter-connected with each other by international trade. The representation of cropland and livestock production systems in each region relies on three components: (i a biomass production function derived from the crop yield response function to inputs such as industrial fertilisers; (ii a detailed representation of the livestock production system subdivided into an intensive and an extensive component, and (iii a spatially explicit distribution of potential (maximal crop yields prescribed from the Lund-Postdam-Jena global vegetation model for managed Land (LPJmL. The economic principles governing decisions about land-use and intensification are adapted from the Ricardian rent theory, assuming cost minimisation for farmers. In contrast to the other land-use models linking economy and biophysics, crops are aggregated as a representative product in calories and intensification for the representative crop is a non-linear function of chemical inputs. The model equations and parameter values are first described in details. Then, idealised scenarios exploring the impact of forest preservation policies or rising energy price on agricultural intensification are described, and their impacts on pasture and cropland areas are investigated.

  18. Monthly hydrometeorological ensemble prediction of streamflow droughts and corresponding drought indices

    Science.gov (United States)

    Fundel, F.; Jörg-Hess, S.; Zappa, M.

    2013-01-01

    Streamflow droughts, characterized by low runoff as consequence of a drought event, affect numerous aspects of life. Economic sectors that are impacted by low streamflow are, e.g., power production, agriculture, tourism, water quality management and shipping. Those sectors could potentially benefit from forecasts of streamflow drought events, even of short events on the monthly time scales or below. Numerical hydrometeorological models have increasingly been used to forecast low streamflow and have become the focus of recent research. Here, we consider daily ensemble runoff forecasts for the river Thur, which has its source in the Swiss Alps. We focus on the evaluation of low streamflow and of the derived indices as duration, severity and magnitude, characterizing streamflow droughts up to a lead time of one month. The ECMWF VarEPS 5-member ensemble reforecast, which covers 18 yr, is used as forcing for the hydrological model PREVAH. A thorough verification reveals that, compared to probabilistic peak-flow forecasts, which show skill up to a lead time of two weeks, forecasts of streamflow droughts are skilful over the entire forecast range of one month. For forecasts at the lower end of the runoff regime, the quality of the initial state seems to be crucial to achieve a good forecast quality in the longer range. It is shown that the states used in this study to initialize forecasts satisfy this requirement. The produced forecasts of streamflow drought indices, derived from the ensemble forecasts, could be beneficially included in a decision-making process. This is valid for probabilistic forecasts of streamflow drought events falling below a daily varying threshold, based on a quantile derived from a runoff climatology. Although the forecasts have a tendency to overpredict streamflow droughts, it is shown that the relative economic value of the ensemble forecasts reaches up to 60%, in case a forecast user is able to take preventive action based on the forecast.

  19. Monthly hydrometeorological ensemble prediction of streamflow droughts and corresponding drought indices

    Directory of Open Access Journals (Sweden)

    F. Fundel

    2013-01-01

    Full Text Available Streamflow droughts, characterized by low runoff as consequence of a drought event, affect numerous aspects of life. Economic sectors that are impacted by low streamflow are, e.g., power production, agriculture, tourism, water quality management and shipping. Those sectors could potentially benefit from forecasts of streamflow drought events, even of short events on the monthly time scales or below. Numerical hydrometeorological models have increasingly been used to forecast low streamflow and have become the focus of recent research. Here, we consider daily ensemble runoff forecasts for the river Thur, which has its source in the Swiss Alps. We focus on the evaluation of low streamflow and of the derived indices as duration, severity and magnitude, characterizing streamflow droughts up to a lead time of one month.

    The ECMWF VarEPS 5-member ensemble reforecast, which covers 18 yr, is used as forcing for the hydrological model PREVAH. A thorough verification reveals that, compared to probabilistic peak-flow forecasts, which show skill up to a lead time of two weeks, forecasts of streamflow droughts are skilful over the entire forecast range of one month. For forecasts at the lower end of the runoff regime, the quality of the initial state seems to be crucial to achieve a good forecast quality in the longer range. It is shown that the states used in this study to initialize forecasts satisfy this requirement. The produced forecasts of streamflow drought indices, derived from the ensemble forecasts, could be beneficially included in a decision-making process. This is valid for probabilistic forecasts of streamflow drought events falling below a daily varying threshold, based on a quantile derived from a runoff climatology. Although the forecasts have a tendency to overpredict streamflow droughts, it is shown that the relative economic value of the ensemble forecasts reaches up to 60%, in case a forecast user is able to take preventive

  20. The Land Use Model Intercomparison Project (LUMIP) contribution to CMIP6: rationale and experimental design

    Science.gov (United States)

    Lawrence, David M.; Hurtt, George C.; Arneth, Almut; Brovkin, Victor; Calvin, Kate V.; Jones, Andrew D.; Jones, Chris D.; Lawrence, Peter J.; de Noblet-Ducoudré, Nathalie; Pongratz, Julia; Seneviratne, Sonia I.; Shevliakova, Elena

    2016-09-01

    Human land-use activities have resulted in large changes to the Earth's surface, with resulting implications for climate. In the future, land-use activities are likely to expand and intensify further to meet growing demands for food, fiber, and energy. The Land Use Model Intercomparison Project (LUMIP) aims to further advance understanding of the impacts of land-use and land-cover change (LULCC) on climate, specifically addressing the following questions. (1) What are the effects of LULCC on climate and biogeochemical cycling (past-future)? (2) What are the impacts of land management on surface fluxes of carbon, water, and energy, and are there regional land-management strategies with the promise to help mitigate climate change? In addressing these questions, LUMIP will also address a range of more detailed science questions to get at process-level attribution, uncertainty, data requirements, and other related issues in more depth and sophistication than possible in a multi-model context to date. There will be particular focus on the separation and quantification of the effects on climate from LULCC relative to all forcings, separation of biogeochemical from biogeophysical effects of land use, the unique impacts of land-cover change vs. land-management change, modulation of land-use impact on climate by land-atmosphere coupling strength, and the extent to which impacts of enhanced CO2 concentrations on plant photosynthesis are modulated by past and future land use.LUMIP involves three major sets of science activities: (1) development of an updated and expanded historical and future land-use data set, (2) an experimental protocol for specific LUMIP experiments for CMIP6, and (3) definition of metrics and diagnostic protocols that quantify model performance, and related sensitivities, with respect to LULCC. In this paper, we describe LUMIP activity (2), i.e., the LUMIP simulations that will formally be part of CMIP6. These experiments are explicitly designed to be

  1. Reexamination and further development of two-stream canopy radiative transfer models for global land modeling

    Science.gov (United States)

    Yuan, Hua; Dai, Yongjiu; Dickinson, Robert E.; Pinty, Bernard; Shangguan, Wei; Zhang, Shupeng; Wang, Lili; Zhu, Siguang

    2017-03-01

    Four representative two-stream canopy radiative transfer models were examined and intercompared using the same configuration. Based on the comparison results, two modifications were introduced to the widely used Dickinson-Sellers model and then incorporated into the Community Land Model (CLM4.5). The modified model was tested against Monte-Carlo simulations and produced significant improvements in the simulated canopy transmittance and albedo values. In direct comparison with MODIS albedo data, the modified model shows good performance over most snow/ice-free vegetated areas, especially for regions that are covered by dense canopy. The modified model shows seasonally dependent behavior mainly in the near-infrared band. Thus, the improvements are not present in all seasons. Large biases are still noticeable in sparsely vegetated areas, in particular for the snow/ice covered regions, that is possibly related to the model, the land surface input data, or even the observations themselves. Further studies focusing on the impact of the seasonal changes in leaf optical properties, the parameterizations for snow/ice covered regions and the case of sparsely vegetated areas, are recommended.

  2. Using exploratory regression to identify optimal driving factors for cellular automaton modeling of land use change.

    Science.gov (United States)

    Feng, Yongjiu; Tong, Xiaohua

    2017-09-22

    Defining transition rules is an important issue in cellular automaton (CA)-based land use modeling because these models incorporate highly correlated driving factors. Multicollinearity among correlated driving factors may produce negative effects that must be eliminated from the modeling. Using exploratory regression under pre-defined criteria, we identified all possible combinations of factors from the candidate factors affecting land use change. Three combinations that incorporate five driving factors meeting pre-defined criteria were assessed. With the selected combinations of factors, three logistic regression-based CA models were built to simulate dynamic land use change in Shanghai, China, from 2000 to 2015. For comparative purposes, a CA model with all candidate factors was also applied to simulate the land use change. Simulations using three CA models with multicollinearity eliminated performed better (with accuracy improvements about 3.6%) than the model incorporating all candidate factors. Our results showed that not all candidate factors are necessary for accurate CA modeling and the simulations were not sensitive to changes in statistically non-significant driving factors. We conclude that exploratory regression is an effective method to search for the optimal combinations of driving factors, leading to better land use change models that are devoid of multicollinearity. We suggest identification of dominant factors and elimination of multicollinearity before building land change models, making it possible to simulate more realistic outcomes.

  3. Estimating impacts of climate change policy on land use: an agent-based modelling approach.

    Directory of Open Access Journals (Sweden)

    Fraser J Morgan

    Full Text Available Agriculture is important to New Zealand's economy. Like other primary producers, New Zealand strives to increase agricultural output while maintaining environmental integrity. Utilising modelling to explore the economic, environmental and land use impacts of policy is critical to understand the likely effects on the sector. Key deficiencies within existing land use and land cover change models are the lack of heterogeneity in farmers and their behaviour, the role that social networks play in information transfer, and the abstraction of the global and regional economic aspects within local-scale approaches. To resolve these issues we developed the Agent-based Rural Land Use New Zealand model. The model utilises a partial equilibrium economic model and an agent-based decision-making framework to explore how the cumulative effects of individual farmer's decisions affect farm conversion and the resulting land use at a catchment scale. The model is intended to assist in the development of policy to shape agricultural land use intensification in New Zealand. We illustrate the model, by modelling the impact of a greenhouse gas price on farm-level land use, net revenue, and environmental indicators such as nutrient losses and soil erosion for key enterprises in the Hurunui and Waiau catchments of North Canterbury in New Zealand. Key results from the model show that farm net revenue is estimated to increase over time regardless of the greenhouse gas price. Net greenhouse gas emissions are estimated to decline over time, even under a no GHG price baseline, due to an expansion of forestry on low productivity land. Higher GHG prices provide a greater net reduction of emissions. While social and geographic network effects have minimal impact on net revenue and environmental outputs for the catchment, they do have an effect on the spatial arrangement of land use and in particular the clustering of enterprises.

  4. Estimating impacts of climate change policy on land use: an agent-based modelling approach.

    Science.gov (United States)

    Morgan, Fraser J; Daigneault, Adam J

    2015-01-01

    Agriculture is important to New Zealand's economy. Like other primary producers, New Zealand strives to increase agricultural output while maintaining environmental integrity. Utilising modelling to explore the economic, environmental and land use impacts of policy is critical to understand the likely effects on the sector. Key deficiencies within existing land use and land cover change models are the lack of heterogeneity in farmers and their behaviour, the role that social networks play in information transfer, and the abstraction of the global and regional economic aspects within local-scale approaches. To resolve these issues we developed the Agent-based Rural Land Use New Zealand model. The model utilises a partial equilibrium economic model and an agent-based decision-making framework to explore how the cumulative effects of individual farmer's decisions affect farm conversion and the resulting land use at a catchment scale. The model is intended to assist in the development of policy to shape agricultural land use intensification in New Zealand. We illustrate the model, by modelling the impact of a greenhouse gas price on farm-level land use, net revenue, and environmental indicators such as nutrient losses and soil erosion for key enterprises in the Hurunui and Waiau catchments of North Canterbury in New Zealand. Key results from the model show that farm net revenue is estimated to increase over time regardless of the greenhouse gas price. Net greenhouse gas emissions are estimated to decline over time, even under a no GHG price baseline, due to an expansion of forestry on low productivity land. Higher GHG prices provide a greater net reduction of emissions. While social and geographic network effects have minimal impact on net revenue and environmental outputs for the catchment, they do have an effect on the spatial arrangement of land use and in particular the clustering of enterprises.

  5. Decision analysis and risk models for land development affecting infrastructure systems.

    Science.gov (United States)

    Thekdi, Shital A; Lambert, James H

    2012-07-01

    Coordination and layering of models to identify risks in complex systems such as large-scale infrastructure of energy, water, and transportation is of current interest across application domains. Such infrastructures are increasingly vulnerable to adjacent commercial and residential land development. Land development can compromise the performance of essential infrastructure systems and increase the costs of maintaining or increasing performance. A risk-informed approach to this topic would be useful to avoid surprise, regret, and the need for costly remedies. This article develops a layering and coordination of models for risk management of land development affecting infrastructure systems. The layers are: system identification, expert elicitation, predictive modeling, comparison of investment alternatives, and implications of current decisions for future options. The modeling layers share a focus on observable factors that most contribute to volatility of land development and land use. The relevant data and expert evidence include current and forecasted growth in population and employment, conservation and preservation rules, land topography and geometries, real estate assessments, market and economic conditions, and other factors. The approach integrates to a decision framework of strategic considerations based on assessing risk, cost, and opportunity in order to prioritize needs and potential remedies that mitigate impacts of land development to the infrastructure systems. The approach is demonstrated for a 5,700-mile multimodal transportation system adjacent to 60,000 tracts of potential land development. © 2011 Society for Risk Analysis.

  6. A window of opportunities : the contributions of land use modelling to societal learning

    NARCIS (Netherlands)

    Sterk, B.

    2007-01-01

    It has been argued that the management of land, whether at the field, farm or regional scale, can benefit from computer-based land use system analysis. As a result, a large number of computer-based models and tools have been produced over the past decades with the aim of providing support to policy

  7. Modelling nitrate from land-surface to wells-perforations under Mediterranean agricultural land: success, failure, and future scenarios

    Science.gov (United States)

    Levy, Yehuda; Chefetz, Benny; Shapira, Roi; Kurtzman, Daniel

    2017-04-01

    Contamination of groundwater resources by nitrate due to leaching under agricultural land is probably the most troublesome agriculture-related water contamination, worldwide. Deep soil sampling (10 m) were used for calibrating vertical flow and nitrogen-transport numerical models of the unsaturated zone, under different agricultural land uses. Vegetables fields (potato and strawberries) and deciduous (persimmon) orchards in the Sharon area overlaying the coastal aquifer of Israel, were examined. Average nitrate-nitrogen fluxes below vegetables fields were 210-290 kg ha-1 a-1 and under deciduous orchards were 110-140 kg ha-1 a-1. The output water and nitrate-nitrogen fluxes of the unsaturated zone models were used as input for a three dimensional flow and nitrate-transport model in the aquifer under an area of 13.3 square kilometers of agricultural land. The area was subdivided to 4 agricultural land-uses: vegetables, deciduous, citrus orchards and non-cultivated. Fluxes of water and nitrate-nitrogen below citrus orchards were taken from a previous study in this area (Kurtzman et al., 2013, j. Contam. Hydrol.). The groundwater flow model was calibrated to well heads only by changing the hydraulic conductivity while transient recharge fluxes were constraint to the bottom-fluxes of the unsaturated zone flow models. The nitrate-transport model in the aquifer, which was fed at the top by the nitrate fluxes of the unsaturated zone models, succeeded in reconstructing the average nitrate concentration in the wells. On the other hand, this transport model failed in calculating the high concentrations in the most contaminated wells and the large spatial variability of nitrate-concentrations in the aquifer. In order to reconstruct the spatial variability and enable predictions nitrate-fluxes from the unsaturated zone were multiplied by local multipliers. This action was rationalized by the fact that the high concentrations in some wells cannot be explained by regular

  8. Hydro-meteorological causes of floods on the Upper and Central Danube River in the years 1895, 1897 and 1899

    Science.gov (United States)

    Garaj, Marcel

    2017-04-01

    Historical climatology and hydrology are uprising scientific disciplines. They stay at the intersection of natural and socio-economic sciences. The main objective is to reconstruct the temporal and spatial aspects of the extreme situations which occurred in the past. It can improve hydro-meteorological modelling, predictions and future scenarios if historical data are included. This paper studies the hydro-meteorological causes of selected floods on the Upper and Central Danube River basin at the end of the 19th century. The main objective was to analyse the temperature conditions and precipitation amounts in the researched area based on data from meteorological and hydrological yearbooks from the Austro-Hungarian Monarchy. The analysis of the meteorological causes of a winter flood in 1895 is based on precipitation amount maps and mean monthly air temperature maps for winter 1894/1895. Graphs of the duration of the snow cover and snow depths for the Salzburg and Kremsmünster stations in March 1895 are also presented. Deviations in the mean daily air temperature from the long term averages (1881 - 1910, 1961 - 1990) are analysed at two selected stations, i.e., Kremsmünster and Höhenpeissenberg. The flood wave from 17 April 1895 had a peak discharge of 15 200 m3.s-1 at the Orsova - Turnu Severin station. The analysis of the summer floods in 1897 and 1899 is based on monthly precipitation maps for the specific months with particular rainfall episodes. There are also graphs of deviations in the cumulative precipitation from the long term averages at the Kremsmünster station in July 1897 and September 1899. In Bratislava, the peak discharge of the July 1897 flood wave reached 10 140 m3.s-1 and the September 1899 flood exceeded that with a peak discharge of 10 870 m3.s-1 and a water stage of 970 cm.

  9. mRM - multiscale Routing Model for Land Surface and Hydrologic Models

    Science.gov (United States)

    Cuntz, M.; Thober, S.; Mai, J.; Samaniego, L. E.; Gochis, D. J.; Kumar, R.

    2015-12-01

    Routing streamflow through a river network is a basic step within any distributed hydrologic model. It integrates the generated runoff and allows comparison with observed discharge at the outlet of a catchment. The Muskingum routing is a textbook river routing scheme that has been implemented in Earth System Models (e.g., WRF-HYDRO), stand-alone routing schemes (e.g., RAPID), and hydrologic models (e.g., the mesoscale Hydrologic Model). Most implementations suffer from a high computational demand because the spatial routing resolution is fixed to that of the elevation model irrespective of the hydrologic modeling resolution. This is because the model parameters are scale-dependent and cannot be used at other resolutions without re-estimation. Here, we present the multiscale Routing Model (mRM) that allows for a flexible choice of the routing resolution. mRM exploits the Multiscale Parameter Regionalization (MPR) included in the open-source mesoscale Hydrologic Model (mHM, www.ufz.de/mhm) that relates model parameters to physiographic properties and allows to estimate scale-independent model parameters. mRM is currently coupled to mHM and is presented here as stand-alone Free and Open Source Software (FOSS). The mRM source code is highly modular and provides a subroutine for internal re-use in any land surface scheme. mRM is coupled in this work to the state-of-the-art land surface model Noah-MP. Simulation results using mRM are compared with those available in WRF-HYDRO for the Red River during the period 1990-2000. mRM allows to increase the routing resolution from 100m to more than 10km without deteriorating the model performance. Therefore, it speeds up model calculation by reducing the contribution of routing to total runtime from over 80% to less than 5% in the case of WRF-HYDRO. mRM thus makes discharge data available to land surface modeling with only little extra calculations.

  10. Comparing the Performance of Three Land Models in Global C Cycle Simulations: A Detailed Structural Analysis: Structural Analysis of Land Models

    Energy Technology Data Exchange (ETDEWEB)

    Rafique, Rashid [Department of Microbiology and Plant Biology, University of Oklahoma, Norman OK USA; Joint Global Change Research Institute, Pacific Northwest National Lab, College Park, MD USA; Xia, Jianyang [School of Ecological and Environmental Science, East China Normal University, Shanghai China; Research Center for Global Change and Ecological Forecasting, East China Normal University; Hararuk, Oleksandra [Department of Microbiology and Plant Biology, University of Oklahoma, Norman OK USA; Leng, Guoyong [Joint Global Change Research Institute, Pacific Northwest National Lab, College Park, MD USA; Asrar, Ghassem [Joint Global Change Research Institute, Pacific Northwest National Lab, College Park, MD USA; Luo, Yiqi [Department of Microbiology and Plant Biology, University of Oklahoma, Norman OK USA

    2016-04-01

    Land models are valuable tools to understand the dynamics of global carbon (C) cycle. Various models have been developed and used for predictions of future C dynamics but uncertainties still exist. Diagnosing the models’ behaviors in terms of structures can help to narrow down the uncertainties in prediction of C dynamics. In this study three widely used land surface models, namely CSIRO’s Atmosphere Biosphere Land Exchange (CABLE) with 9 C pools, Community Land Model (version 3.5) combined with Carnegie-Ames-Stanford Approach (CLM-CASA) with 12 C pools and Community Land Model (version 4) (CLM4) with 26 C pools were driven by the observed meteorological forcing. The simulated C storage and residence time were used for analysis. The C storage and residence time were computed globally for all individual soil and plant pools, as well as net primary productivity (NPP) and its allocation to different plant components’ based on these models. Remotely sensed NPP and statistically derived HWSD, and GLC2000 datasets were used as a reference to evaluate the performance of these models. Results showed that CABLE exhibited better agreement with referenced C storage and residence time for plant and soil pools, as compared with CLM-CASA and CLM4. CABLE had longer bulk residence time for soil C pools and stored more C in roots, whereas, CLM-CASA and CLM4 stored more C in woody pools due to differential NPP allocation. Overall, these results indicate that the differences in C storage and residence times in three models are largely due to the differences in their fundamental structures (number of C pools), NPP allocation and C transfer rates. Our results have implications in model development and provide a general framework to explain the bias/uncertainties in simulation of C storage and residence times from the perspectives of model structures.

  11. Implementing land use change models in the developing world

    CSIR Research Space (South Africa)

    Le Roux, Alize

    2013-07-01

    Full Text Available It is difficult for policy and decision makers to observe and quantify the implications of their land use policies and strategies and what it might or might not mean for a city's landscape a decade or more from now. The CSIR Spatial Planning Systems...

  12. Assimilation of multispectral measurements in interactive land surface models

    NARCIS (Netherlands)

    Menenti, M.

    1998-01-01

    The paper presents highlights of a five-years investigation on the use of airborne and space observations to study the heat and water balance of heterogeneous land surfaces. Three algorithms to estimate heat fluxes using satellite observations were developed and evaluated against ground measurements

  13. Ecological models for rehabilitation of degraded hilly lands in ...

    African Journals Online (AJOL)

    Mo

    great ecological and social effects also have been achieved. The urbanization has become evident and fast in the region since 1978. More and more factories and buildings took the place of agriculture fields in the flatland. Many farmers gave up rice in the flatlands and extended dry farming system to hilly lands and forests, ...

  14. Biofuels and Land Use Change: Applying Recent Evidence to Model Estimates

    Directory of Open Access Journals (Sweden)

    Wallace E. Tyner

    2013-01-01

    Full Text Available Biofuels impact on global land use has been a controversial yet important topic. Up until recently, there has not been enough biofuels to have caused major land use change, so the evidence from actual global land use data has been scant. However, in the past decade, there have been 72 million hectares added to global crop cover. In this research we take advantage of this new data to calibrate the Global Trade Analysis Project (GTAP model and parameters. We make two major changes. First, we calibrate the land transformation parameters (called constant elasticity of transformation, CET to global regions so that the parameters better reflect the actual land cover change that has occurred. Second, we alter the land cover nesting structure. In the old GTAP model, cropland, pasture, and forest were all in the same nest suggesting, everything else being equal, that pasture or forest convert to cropland with equal ease and cost. However, we now take advantage of the fact that pasture converts to cropland at lower cost than forest. The paper provides the theoretical and empirical justification for these two model improvements. Then it re-evaluates the global land use impacts due to the USA ethanol program using the improved model tuned with actual observations. Finally, it shows that compared to the old model, the new model projects: (1 less expansion in global cropland due to ethanol expansion; (2 lower U.S. share in global cropland expansion; (3 and lower forest share in global cropland expansion.

  15. A Framework for the Land Use Change Dynamics Model Compatible with RCMs

    Directory of Open Access Journals (Sweden)

    Xiangzheng Deng

    2013-01-01

    Full Text Available A framework of land use change dynamics (LUCD model compatible with regional climate models (RCMs is introduced in this paper. The LUCD model can be subdivided into three modules, namely, economic module, vegetation change module, and agent-based module. The economic module is capable of estimating the demand of land use changes in economic activities maximizing economic utility. A computable general equilibrium (CGE modeling framework is introduced and an approach to introduce land as a production factor into the economic module is proposed. The vegetation change module provides the probability of vegetation change driven by climate change. The agroecological zone (AEZ model is supposed to be the optimal option for constructing the vegetation change module. The agent-based module identifies whether the land use change demand and vegetation change can be realized and provides the land use change simulation results which are the underlying surfaces needed by RCM. By importing the RCMs' simulation results of climate change and providing the simulation results of land use change for RCMs, the LUCD model would be compatible with RCMs. The coupled simulation system composed of LUCD and RCMs can be very effective in simulating the land surface processes and their changing patterns.

  16. Hydrometeorological and Epidemiological Time Markers for Urban Malaria in Niamey, Niger (Invited)

    Science.gov (United States)

    Williams, E.

    2010-12-01

    This study is concerned with the seasonal evolution of malaria in Niamey, Niger. This capital city in the Sahel of West Africa is burdened with 100,000 cases of malaria annually. Approximately fifty clinics distributed throughout the city document presumed malaria cases with weekly resolution, enabling the study of time series for malaria development as the wet season evolves. A remarkable feature of these time series is the abrupt increase in reported cases (by factors of 2-5) in a single week, occurring synchronously over the entire city. This study explores the hypothesis that this abrupt increase in malaria is caused by an earlier abrupt increase in the total area of standing water, sustained for the remainder of the wet season and available for the laying of mosquito eggs and larvae, followed by the abrupt increase in the population of anopheles mosquitoes. Prior to this special event, the surface rainfall from storm events disappears by evaporation within 1-2 days or less, and any eggs or larvae present do not survive to adults. The abrupt onset in sustained standing water is often caused by a single mesoscale convective system whose overall distribution of rainfall is roughly uniform over the scale of the city (~10 km), and whose new surface water bumps up the ambient nighttime relative humidity over the 80% mark. This threshold value has long been recognized as the most typical screen-level value of relative humidity over tropical oceans, implying that nighttime land surfaces with only a few percent coverage of standing water behave thermodynamically as ocean surfaces. Hydrometeorological and epidemiological observations from seven wet seasons (2004-2010) in Niamey are examined to explore the working hypothesis. The calendar dates for onset of standing water (t0) in hourly relative humidity data, and the onset (t2) of malaria in weekly clinic reports, vary by as much as one month from season to season, depending on the history of the rainfall in the wet

  17. Improving the representation of river-groundwater interactions in land surface modeling at the regional scale: Observational evidence and parameterization applied in the Community Land Model

    KAUST Repository

    Zampieri, Matteo

    2012-02-01

    Groundwater is an important component of the hydrological cycle, included in many land surface models to provide a lower boundary condition for soil moisture, which in turn plays a key role in the land-vegetation-atmosphere interactions and the ecosystem dynamics. In regional-scale climate applications land surface models (LSMs) are commonly coupled to atmospheric models to close the surface energy, mass and carbon balance. LSMs in these applications are used to resolve the momentum, heat, water and carbon vertical fluxes, accounting for the effect of vegetation, soil type and other surface parameters, while lack of adequate resolution prevents using them to resolve horizontal sub-grid processes. Specifically, LSMs resolve the large-scale runoff production associated with infiltration excess and sub-grid groundwater convergence, but they neglect the effect from loosing streams to groundwater. Through the analysis of observed data of soil moisture obtained from the Oklahoma Mesoscale Network stations and land surface temperature derived from MODIS we provide evidence that the regional scale soil moisture and surface temperature patterns are affected by the rivers. This is demonstrated on the basis of simulations from a land surface model (i.e., Community Land Model - CLM, version 3.5). We show that the model cannot reproduce the features of the observed soil moisture and temperature spatial patterns that are related to the underlying mechanism of reinfiltration of river water to groundwater. Therefore, we implement a simple parameterization of this process in CLM showing the ability to reproduce the soil moisture and surface temperature spatial variabilities that relate to the river distribution at regional scale. The CLM with this new parameterization is used to evaluate impacts of the improved representation of river-groundwater interactions on the simulated water cycle parameters and the surface energy budget at the regional scale. © 2011 Elsevier B.V.

  18. Impact of Soil Moisture Assimilation on Land Surface Model Spin-Up and Coupled LandAtmosphere Prediction

    Science.gov (United States)

    Santanello, Joseph A., Jr.; Kumar, Sujay V.; Peters-Lidard, Christa D.; Lawston, P.

    2016-01-01

    Advances in satellite monitoring of the terrestrial water cycle have led to a concerted effort to assimilate soil moisture observations from various platforms into offline land surface models (LSMs). One principal but still open question is that of the ability of land data assimilation (LDA) to improve LSM initial conditions for coupled short-term weather prediction. In this study, the impact of assimilating Advanced Microwave Scanning Radiometer for EOS (AMSR-E) soil moisture retrievals on coupled WRF Model forecasts is examined during the summers of dry (2006) and wet (2007) surface conditions in the southern Great Plains. LDA is carried out using NASAs Land Information System (LIS) and the Noah LSM through an ensemble Kalman filter (EnKF) approach. The impacts of LDA on the 1) soil moisture and soil temperature initial conditions for WRF, 2) land-atmosphere coupling characteristics, and 3) ambient weather of the coupled LIS-WRF simulations are then assessed. Results show that impacts of soil moisture LDA during the spin-up can significantly modify LSM states and fluxes, depending on regime and season. Results also indicate that the use of seasonal cumulative distribution functions (CDFs) is more advantageous compared to the traditional annual CDF bias correction strategies. LDA performs consistently regardless of atmospheric forcing applied, with greater improvements seen when using coarser, global forcing products. Downstream impacts on coupled simulations vary according to the strength of the LDA impact at the initialization, where significant modifications to the soil moisture flux- PBL-ambient weather process chain are observed. Overall, this study demonstrates potential for future, higher-resolution soil moisture assimilation applications in weather and climate research.

  19. Comparing the Degree of Land-Atmosphere Interaction in Four Atmospheric General Circulation Models

    Science.gov (United States)

    Koster, Randal D.; Dirmeyer, Paul A.; Hahmann, Andrea N.; Ijpelaar, Ruben; Tyahla, Lori; Cox, Peter; Suarez, Max J.; Houser, Paul R. (Technical Monitor)

    2001-01-01

    Land-atmosphere feedback, by which (for example) precipitation-induced moisture anomalies at the land surface affect the overlying atmosphere and thereby the subsequent generation of precipitation, has been examined and quantified with many atmospheric general circulation models (AGCMs). Generally missing from such studies, however, is an indication of the extent to which the simulated feedback strength is model dependent. Four modeling groups have recently performed a highly controlled numerical experiment that allows an objective inter-model comparison of land-atmosphere feedback strength. The experiment essentially consists of an ensemble of simulations in which each member simulation artificially maintains the same time series of surface prognostic variables. Differences in atmospheric behavior between the ensemble members then indicates the degree to which the state of the land surface controls atmospheric processes in that model. A comparison of the four sets of experimental results shows that feedback strength does indeed vary significantly between the AGCMs.

  20. Land-use transition for bioenergy and climate stabilization: model comparison of drivers, impacts and interactions with other land use based mitigation options

    Energy Technology Data Exchange (ETDEWEB)

    Popp, Alexander; Rose, Steven K.; Calvin, Katherine V.; Van Vuuren, Detlef; Dietrich, Jan P.; Wise, Marshall A.; Stehfest, Eike; Humpenoder, Florian; Kyle, G. Page; Van Vliet, Jasper; Bauer, Nico; Lotze-Campen, Hermann; Klein, David; Kriegler, Elmar

    2014-04-01

    This study is a model comparison assessing the drivers and impacts of bioenergy production on the global land system and the interaction with other land use based mitigation options in the context of the EMF 27 project. We compare and evaluate results from three integrated assessment models (GCAM, IMAGE, and ReMIND/MAgPIE). All three models project that dedicated bioenergy crops and biomass residues are a potentially important and cost-effective component of the energy system. But bioenergy deployment levels and feedstock composition vary notably across models as do the implications for land-use and greenhouse gas emissions and the interaction with other land use based mitigation measures. Despite numerous model differences, we identify a few that are likely contributing to differences in land-use and emissions attributable to energy crop deployment.

  1. The importance of land cover change across urban-rural typologies for climate modeling.

    Science.gov (United States)

    Vargo, Jason; Habeeb, Dana; Stone, Brian

    2013-01-15

    Land cover changes affect local surface energy balances by changing the amount of solar energy reflected, the magnitude and duration over which absorbed energy is released as heat, and the amount of energy that is diverted to non-heating fluxes through evaporation. However, such local influences often are only crudely included in climate modeling exercises, if at all. A better understanding of local land conversion dynamics can serve to inform inputs for climate models and increase the role for land use planning in climate management policy. Here we present a new approach for projecting and incorporating metropolitan land cover change into mesoscale climate and other environmental assessment models. Our results demonstrate the relative contributions of different land development patterns to land cover change and conversion and suggest that regional growth management strategies serving to increase settlement densities over time can have a significant influence on the rate of deforestation per unit of population growth. Employing the approach presented herein, the impacts of land conversion on climate change and on parallel environmental systems and services, such as ground water recharge, habitat provision, and food production, may all be investigated more closely and managed through land use planning. Copyright © 2012 Elsevier Ltd. All rights reserved.

  2. ANALYSIS OF LAND RESOURCES SUITABILITY BY FUNCTIONAL MODEL IN EASTERN CROATIA REGION

    Directory of Open Access Journals (Sweden)

    Vladimir Vukadinović

    2011-06-01

    Full Text Available A total of 17405 soil samples (2003rd-2009th years were analyzed in the eastern part of Croatia. The aim of this paper is to assess land suitability for crops i.e. to describe quantitatively land quality and indicate disadvantages of land using system in investigated area. The described mathematical model uses score functions for estimating indicators of soil suitability. Soil suitability assessment computer model for crops, supported by GIS, proved to be fast, efficient and enough reliable. Using GIS tool it is possible to visualize land suitability and present it in different cartographic bases such as maps whereas using geostatistical method – kriging enables to possible to provide regionalization of production area based on quantitative assessment of land suitability for crops.

  3. Integrated Assessment Modeling of Carbon Sequestration and Land Use Emissions Using Detailed Model Results and Observations

    Energy Technology Data Exchange (ETDEWEB)

    Dr. Atul Jain

    2005-04-17

    This report outlines the progress on the development and application of Integrated Assessment Modeling of Carbon Sequestrations and Land Use Emissions supported by the DOE Office of Biological and Environmental Research (OBER), U.S. Department of Energy, Grant No. DOE-DE-FG02-01ER63069. The overall objective of this collaborative project between the University of Illinois at Urbana-Champaign (UIUC), Oak Ridge National Laboratory (ORNL), Lawrence Livermore National Laboratory (LLNL), and Pacific Northwest National Laboratory (PNNL) was to unite the latest advances in carbon cycle research with scientifically based models and policy-related integrated assessment tools that incorporate computationally efficient representations of the latest knowledge concerning science and emission trajectories, and their policy implications. As part of this research we accomplished the following tasks that we originally proposed: (1) In coordination with LLNL and ORNL, we enhanced the Integrated Science Assessment Model's (ISAM) parametric representation of the ocean and terrestrial carbon cycles that better represent spatial and seasonal variations, which are important to study the mechanisms that influence carbon sequestration in the ocean and terrestrial ecosystems; (2) Using the MiniCAM modeling capability, we revised the SRES (IPCC Special Report on Emission Scenarios; IPCC, 2000) land use emission scenarios; and (3) On the application front, the enhanced version of ISAM modeling capability is applied to understand how short- and long-term natural carbon fluxes, carbon sequestration, and human emissions contribute to the net global emissions (concentrations) trajectories required to reach various concentration (emission) targets. Under this grant, 21 research publications were produced. In addition, this grant supported a number of graduate and undergraduate students whose fundamental research was to learn a disciplinary field in climate change (e.g., ecological dynamics

  4. Incorporating a Process-Based Land Use Variable into Species- Distribution Modelling and an Estimated Probability of Species Occurrence Into a Land Change Model: A Case of Albania

    Science.gov (United States)

    Laze, Kuenda

    2016-08-01

    Modelling of land use may be improved by incorporating the results of species distribution modelling and species distribution modelling may be upgraded if a variable of the process-based variable of forest cover change or accessibility of forest from human settlement is included. This work presents the results of spatially explicit analyses of the changes in forest cover from 2000 to 2007 using the method of Geographically Weighted Regression (GWR) and of the species distribution for protected species of Lynx lynx martinoi, Ursus arctos using Generalized Linear Models (GLMs). The methodological approach is separately searching for a parsimonious model for forest cover change and species distribution for the entire territory of Albania. The findings of this work show that modelling of land change and of species distribution is indeed value-added by showing higher values of model selection of corrected Akaike Information Criterion. These results provide evidences on the effects of process-based variables on species distribution modelling and on the performance of species distribution modelling as well as show an example of the incorporation of estimated probability of species occurrences in a land change modelling.

  5. Recent Progresses in Incorporating Human Land-Water Management into Global Land Surface Models Toward Their Integration into Earth System Models

    Science.gov (United States)

    Pokhrel, Yadu N.; Hanasaki, Naota; Wada, Yoshihide; Kim, Hyungjun

    2016-01-01

    The global water cycle has been profoundly affected by human land-water management. As the changes in the water cycle on land can affect the functioning of a wide range of biophysical and biogeochemical processes of the Earth system, it is essential to represent human land-water management in Earth system models (ESMs). During the recent past, noteworthy progress has been made in large-scale modeling of human impacts on the water cycle but sufficient advancements have not yet been made in integrating the newly developed schemes into ESMs. This study reviews the progresses made in incorporating human factors in large-scale hydrological models and their integration into ESMs. The study focuses primarily on the recent advancements and existing challenges in incorporating human impacts in global land surface models (LSMs) as a way forward to the development of ESMs with humans as integral components, but a brief review of global hydrological models (GHMs) is also provided. The study begins with the general overview of human impacts on the water cycle. Then, the algorithms currently employed to represent irrigation, reservoir operation, and groundwater pumping are discussed. Next, methodological deficiencies in current modeling approaches and existing challenges are identified. Furthermore, light is shed on the sources of uncertainties associated with model parameterizations, grid resolution, and datasets used for forcing and validation. Finally, representing human land-water management in LSMs is highlighted as an important research direction toward developing integrated models using ESM frameworks for the holistic study of human-water interactions within the Earths system.

  6. The catastrophic flash-flood event of 8–9 September 2002 in the Gard region, France: a first case study for the Cévennes–Vivarais Mediterranean Hydrometeorological Observatory

    OpenAIRE

    Delrieu, Guy; Nicol, John; Yates, Eddy; Kirstetter, Pierre-Emmanuel; Creutin, Jean-Dominique; Anquetin, Sandrine; Obled, Charles; Saulnier, Georges-Marie; Ducrocq, Véronique; Gaume, Eric; PAYRASTRE, Olivier; ANDRIEU, Hervé; Ayral, Pierre-Alain; Bouvier, Christophe; Neppel, Luc

    2005-01-01

    The Cévennes–Vivarais Mediterranean Hydrometeorological Observatory (OHM-CV) is a research initiative aimed at improving the understanding and modeling of the Mediterranean intense rain events that frequently result in devastating flash floods in southern France. A primary objective is to bring together the skills of meteorologists and hydrologists, modelers and instrumentalists, researchers and practitioners, to cope with these rather unpredictable events. In line with previously published f...

  7. Methodical modeling of the investment value of land plots for housing development

    National Research Council Canada - National Science Library

    Kulakov Kirill; Baronin Sergey

    2017-01-01

    ... from major developers that in the context of the turbulent economy it is especially important. In this regard great scientific and practical interest is the modeling of the investment value of land plots for housing development...

  8. Equity analysis of land use and transport plans using an integrated spatial model.

    Science.gov (United States)

    2010-02-01

    This paper describes a study to investigate how a spatial economic model can be used to evaluate the equity effects of land use and transport policies intended to reduce greenhouse gas emissions. The Activity Allocation Module of the PECAS (Productio...

  9. An exploration of scenarios to support sustainable land management using integrated environmental socio-economic models

    NARCIS (Netherlands)

    Fleskens, L.; Nainggolan, D.; Stringer, L.C.

    2014-01-01

    Scenario analysis constitutes a valuable deployment method for scientific models to inform environmental decision-making, particularly for evaluating land degradation mitigation options, which are rarely based on formal analysis. In this paper we demonstrate such an assessment using the

  10. Implementation of Biophysical Factors Into the Land Surface and Atmosphere Interaction Model

    Science.gov (United States)

    Hong, S.; Lakshmi, V.; Small, E. E.; Chen, F.

    2006-12-01

    We test the NOAH land surface model implemented into the weather research and forecasting model (WRF) by simulating surface skin temperature, vegetation fraction, and evapotranspiration in order to improve the model simulation. This study has two major questions: 1) Is the model simulation reliable with respect to real- time land surface variation and 2) what improvements from satellite remote sensing can be implemented or parameterized into the model simulations. The relationship between skin temperature and vegetation fraction impacts the variation of evapotranpiration, which is influenced by moisture availability on the surface and vice versa. The skin surface temperature varies with vegetation amount, land cover type, precipitation, topography, soil type and texture. Complex interactions between them determine the relationship between skin temperature and vegetation fraction and hence the evapotranspiration. Of the factors that influence the land surface-atmosphere interactions, water content in vegetation is investigated to examine the possibility of the model improvement. Vegetation water content, which is differently controlled by vegetation types, varies with land cover type as well as with the moisture conditions on the land surface. Oklahoma in the central U.S. is selected as the study area because it shows large variations of vegetation, from bare soil to fully vegetated, and of surface temperature during rainy seasons. The simulated variables are compared to the MODIS satellite data and the Mesonet ground-based observations. The model simulation is calibrated based on the real surface conditions provided by Mesonet observation data.

  11. Incorporating root hydraulic redistribution and compensatory water uptake in the Common Land Model: Effects on site level and global land modeling

    Science.gov (United States)

    Zhu, Siguang; Chen, Haishan; Zhang, Xiangxiang; Wei, Nan; Shangguan, Wei; Yuan, Hua; Zhang, Shupeng; Wang, Lili; Zhou, Lihua; Dai, Yongjiu

    2017-07-01

    Treatment of plant water uptake through the roots remains a significant issue in land surface models. Most current land surface models calculate the root water uptake (RWU) by extracting soil water in different soil layers based on the relative soil water availability and the root fraction of each layer within the rooting zone. This approach is also used as the default in the Common Land Model (CoLM). This approach often significantly underestimates plant transpiration during dry periods. Therefore, more realistic RWU functions are needed in land surface models. In this study, the modified CoLM with root hydraulic redistribution (HR) and compensatory water uptake (CWU) was evaluated against the CoLM with the default approach by comparing the observed and simulated latent and sensible heat fluxes observed from three sites that experience seasonal drought over the measured periods. We found that the CoLM using the default RWU significantly underestimated latent heat fluxes and overestimated the sensible heat fluxes over dry periods, whereas those biases were significantly reduced by the CoLM with HR and CWU functions. We also ran global offline simulations using the revised CoLM to evaluate the performance of these alternative RWU functions on the global scale. Compared with the estimated latent heat fluxes from the FLUXNET-model tree ensemble model product, CoLM with HR and CWU functions significantly improved the estimated latent heat fluxes over the Amazon, Southern Africa, and Central Asia during their dry seasons. Therefore, we recommend the implementation of HR and CWU in land surface models.

  12. A Generalized Deforestation and Land-Use Change Scenario Generator for Use in Climate Modelling Studies.

    Directory of Open Access Journals (Sweden)

    Adrian Mark Tompkins

    Full Text Available A new deforestation and land-use change scenario generator model (FOREST-SAGE is presented that is designed to interface directly with dynamic vegetation models used in latest generation earth system models. The model requires a regional-scale scenario for aggregate land-use change that may be time-dependent, provided by observational studies or by regional land-use change/economic models for future projections. These land-use categories of the observations/economic model are first translated into equivalent plant function types used by the particular vegetation model, and then FOREST-SAGE disaggregates the regional-scale scenario to the local grid-scale of the earth system model using a set of risk-rules based on factors such as proximity to transport networks, distance weighted population density, forest fragmentation and presence of protected areas and logging concessions. These rules presently focus on the conversion of forest to agriculture and pasture use, but could be generalized to other land use change conversions. After introducing the model, an evaluation of its performance is shown for the land-cover changes that have occurred in the Central African Basin from 2001-2010 using retrievals from MODerate Resolution Imaging Spectroradiometer Vegetation Continuous Field data. The model is able to broadly reproduce the spatial patterns of forest cover change observed by MODIS, and the use of the local-scale risk factors enables FOREST-SAGE to improve land use change patterns considerably relative to benchmark scenarios used in the latest Coupled Model Intercomparison Project integrations. The uncertainty to the various risk factors is investigated using an ensemble of investigations, and it is shown that the model is sensitive to the population density, forest fragmentation and reforestation factors specified.

  13. A Generalized Deforestation and Land-Use Change Scenario Generator for Use in Climate Modelling Studies

    Science.gov (United States)

    Tompkins, Adrian Mark; Caporaso, Luca; Biondi, Riccardo; Bell, Jean Pierre

    2015-01-01

    A new deforestation and land-use change scenario generator model (FOREST-SAGE) is presented that is designed to interface directly with dynamic vegetation models used in latest generation earth system models. The model requires a regional-scale scenario for aggregate land-use change that may be time-dependent, provided by observational studies or by regional land-use change/economic models for future projections. These land-use categories of the observations/economic model are first translated into equivalent plant function types used by the particular vegetation model, and then FOREST-SAGE disaggregates the regional-scale scenario to the local grid-scale of the earth system model using a set of risk-rules based on factors such as proximity to transport networks, distance weighted population density, forest fragmentation and presence of protected areas and logging concessions. These rules presently focus on the conversion of forest to agriculture and pasture use, but could be generalized to other land use change conversions. After introducing the model, an evaluation of its performance is shown for the land-cover changes that have occurred in the Central African Basin from 2001–2010 using retrievals from MODerate Resolution Imaging Spectroradiometer Vegetation Continuous Field data. The model is able to broadly reproduce the spatial patterns of forest cover change observed by MODIS, and the use of the local-scale risk factors enables FOREST-SAGE to improve land use change patterns considerably relative to benchmark scenarios used in the latest Coupled Model Intercomparison Project integrations. The uncertainty to the various risk factors is investigated using an ensemble of investigations, and it is shown that the model is sensitive to the population density, forest fragmentation and reforestation factors specified. PMID:26394392

  14. Study on Spatial Model of Land Use Based on CA - Markov Model after Returning Cropland to Forest

    Science.gov (United States)

    Qiu, Chun-xia; Han, Dong; Dong, Qian-kun; Mao, Qin-qin

    2017-07-01

    At present, the frontier of global environmental change research is land use / cover change, and an important way to understand global land change is to analyze and study typical areas. In order to study the law and the driving mechanism of land use change in the loess hilly and gully region, this paper takes the county south ditch watershed as an example, takes the remote sensing image of the basin in 1995, 2005 and 2015 as the data source, combined with the topographic data, And the spatial and temporal dynamics of land use before and after returning farmland to forest in Nangou watershed was analyzed. Finally, based on the land use situation in 2015, a variety of CA criteria were used to carry out modeling analysis to predict the land use in 2025 Type of purpose. And thus hope for the region to implement the scientific implementation of the project of returning farmland to forest.

  15. LAND COVER CLASSIFICATION OF MULTI-SENSOR IMAGES BY DECISION FUSION USING WEIGHTS OF EVIDENCE MODEL

    Directory of Open Access Journals (Sweden)

    P. Li

    2012-07-01

    Full Text Available This paper proposed a novel method of decision fusion based on weights of evidence model (WOE. The probability rules from classification results from each separate dataset were fused using WOE to produce the posterior probability for each class. The final classification was obtained by maximum probability. The proposed method was evaluated in land cover classification using two examples. The results showed that the proposed method effectively combined multisensor data in land cover classification and obtained higher classification accuracy than the use of single source data. The weights of evidence model provides an effective decision fusion method for improved land cover classification using multi-sensor data.

  16. Mapping Biophysical Parameters for Land Surface Modeling over the Continental US Using MODIS and Landsat

    Directory of Open Access Journals (Sweden)

    Lahouari Bounoua

    2015-01-01

    Full Text Available In terms of the space cities occupy, urbanization appears as a minor land transformation. However, it permanently modifies land’s ecological functions, altering its carbon, energy, and water fluxes. It is therefore necessary to develop a land cover characterization at fine spatial and temporal scales to capture urbanization’s effects on surface fluxes. We develop a series of biophysical vegetation parameters such as the fraction of photosynthetically active radiation, leaf area index, vegetation greenness fraction, and roughness length over the continental US using MODIS and Landsat products for 2001. A 13-class land cover map was developed at a climate modeling grid (CMG merging the 500 m MODIS land cover and the 30 m impervious surface area from the National Land Cover Database. The landscape subgrid heterogeneity was preserved using fractions of each class from the 500 m and 30 m into the CMG. Biophysical parameters were computed using the 8-day composite Normalized Difference Vegetation Index produced by the North American Carbon Program. In addition to urban impact assessments, this dataset is useful for the computation of surface fluxes in land, vegetation, and urban models and is expected to be widely used in different land cover and land use change applications.

  17. Interoperable Domain Models: the ISO Land Administration Domain Model Ladm and its External Classes

    Science.gov (United States)

    Lemmen, C. H. J.; van Oosterom, P. J. M.; Uitermark, H. T.; Zevenbergen, J. A.; Cooper, A. K.

    2011-08-01

    This paper provides a brief overview of one of the first spatial domain standards: a standard for the domain of Land Administration (LA). This standard is in the draft stage of development now (May 2011). The development of domain standards is a logical follow up after domain-independent standards, which are available now in the area of geo-information processing. The Land Administration Domain Model (LADM) provides a conceptual schema with three basic packages with a limited scope: parties, rights (and restrictions/responsibilities) and spatial units. Certain classes are outside the scope but can be referred to. An important aspect in the development of a coherent (Spatial) Information Infrastructures - (S)II is that the various standardized domain models are reusing the same model patterns as solutions for the same situations. In this paper the LADM and its external classes are briefly presented. It outlines the advantages of standardized domain models in the development of (S)II and the importance of LA as an authentic register, in relation to other authentic registers, such as for addresses, population, companies, topography, or buildings. This will be illustrated with the Dutch case of authentic registers.

  18. Spatially explicit integrated modeling and economic valuation of climate driven land use change and its indirect effects

    OpenAIRE

    Bateman, Ian; Agarwala, Matthew; Binner, Amy; Coombes, Emma; Day, Brett; Ferrini, Silvia; Fezzi, Carlo; Hutchins, Michael; Lovett, Andrew; Posen, Paulette

    2016-01-01

    We present an integrated model of the direct consequences of climate change on land use, and the indirect effects of induced land use change upon the natural environment. The model predicts climate-driven shifts in the profitability of alternative uses of agricultural land. Both the direct impact of climate change and the induced shift in land use patterns will cause secondary effects on the water environment, for which agriculture is the major source of diffuse pollution. We model the impact...

  19. Regional Climate Modeling over the Marmara Region, Turkey, with Improved Land Cover Data

    Science.gov (United States)

    Sertel, E.; Robock, A.

    2007-12-01

    Land surface controls the partitioning of available energy at the surface between sensible and latent heat,and controls partitioning of available water between evaporation and runoff. Current land cover data available within the regional climate models such as Regional Atmospheric Modeling System (RAMS), the Fifth-Generation NCAR/Penn State Mesoscale Model (MM5) and Weather Research and Forecasting (WRF) was obtained from 1- km Advanced Very High Resolution Radiometer satellite images spanning April 1992 through March 1993 with an unsupervised classification technique. These data are not up-to-date and are not accurate for all regions and some land cover types such as urban areas. Here we introduce new, up-to-date and accurate land cover data for the Marmara Region, Turkey derived from Landsat Enhanced Thematic Mapper images into the WRF regional climate model. We used several image processing techniques to create accurate land cover data from Landsat images obtained between 2001 and 2005. First, all images were atmospherically and radiometrically corrected to minimize contamination effects of atmospheric particles and systematic errors. Then, geometric correction was performed for each image to eliminate geometric distortions and define images in a common coordinate system. Finally, unsupervised and supervised classification techniques were utilized to form the most accurate land cover data yet for the study area. Accuracy assessments of the classifications were performed using error matrix and kappa statistics to find the best classification results. Maximum likelihood classification method gave the most accurate results over the study area. We compared the new land cover data with the default WRF land cover data. WRF land cover data cannot represent urban areas in the cities of Istanbul, Izmit, and Bursa. As an example, both original satellite images and new land cover data showed the expansion of urban areas into the Istanbul metropolitan area, but in the WRF

  20. The Ocean-Land-Atmosphere Model (OLAM): A new Generation of Earth System Model

    Science.gov (United States)

    Walko, R. L.; Avissar, R.

    2006-12-01

    The Ocean-Land-Atmosphere Model (OLAM) has been developed to extend the capabilities of the Regional Atmospheric Modeling System (RAMS) to a global modeling framework. OLAM is a new model with regard to its dynamic core, grid configuration, memory structure, and numerical solution technique. Instead of the Boussinesq approximation used in RAMS, OLAM solves the full compressible Navier-Stokes equations in conservation form using finite-volume numerical operators that conserve mass, momentum, and energy to machine precision. In place of RAMS' structured multiple nested grids and hexahedral grid cells on a polar stereographic projection, OLAM uses a single unstructured grid and pentahedral (prism) grid cells (with a triangular footprint) which conform to the sphere without a coordinate transformation. OLAM's grid topology enables local mesh refinement to any degree without the need for special grid nesting algorithms; all communication between regions of different resolution is accomplished seamlessly by flux-conservative advective and diffusive transport. OLAM represents topography using a form of the volume-fraction or shaved grid cell method in which model levels are strictly horizontal, rather than terrain- following, and therefore intersect topography. Grid cell face areas, which explicitly appear in the finite volume equations and are pre-computed and stored, are reduced in proportion to any blockage by topography, thereby correctly regulating inter-cell transport and preventing advective flux normal to the ground surface. Apart from its dynamic core and grid configuration, OLAM bears a strong resemblance to RAMS. Both models share the same physical parameterizations for microphysics, land and vegetation water and energy balances, radiative transfer, and sub-grid cumulus convection. Model coding structure, I/O file formats, and methods of compiling, initializing, and executing the models are very similar or identical. Results of a variety of OLAM simulations

  1. Exploiting remote sensing land surface temperature in distributed hydrological modelling: the example of the Continuum model

    Directory of Open Access Journals (Sweden)

    F. Silvestro

    2013-01-01

    Full Text Available Full process description and distributed hydrological models are very useful tools in hydrology as they can be applied in different contexts and for a wide range of aims such as flood and drought forecasting, water management, and prediction of impact on the hydrologic cycle due to natural and human-induced changes. Since they must mimic a variety of physical processes, they can be very complex and with a high degree of parameterization. This complexity can be increased by necessity of augmenting the number of observable state variables in order to improve model validation or to allow data assimilation.

    In this work a model, aiming at balancing the need to reproduce the physical processes with the practical goal of avoiding over-parameterization, is presented. The model is designed to be implemented in different contexts with a special focus on data-scarce environments, e.g. with no streamflow data.

    All the main hydrological phenomena are modelled in a distributed way. Mass and energy balance are solved explicitly. Land surface temperature (LST, which is particularly suited to being extensively observed and assimilated, is an explicit state variable.

    A performance evaluation, based on both traditional and satellite derived data, is presented with a specific reference to the application in an Italian catchment. The model has been firstly calibrated and validated following a standard approach based on streamflow data. The capability of the model in reproducing both the streamflow measurements and the land surface temperature from satellites has been investigated.

    The model has been then calibrated using satellite data and geomorphologic characteristics of the basin in order to test its application on a basin where standard hydrologic observations (e.g. streamflow data are not available. The results have been compared with those obtained by the standard calibration strategy based on streamflow data.

  2. The development and application of a decision support system for land management in the Lake Tahoe Basin—The Land Use Simulation Model

    Science.gov (United States)

    Forney, William M.; Oldham, I. Benson; Crescenti, Neil

    2013-01-01

    This report describes and applies the Land Use Simulation Model (LUSM), the final modeling product for the long-term decision support project funded by the Southern Nevada Public Land Management Act and developed by the U.S. Geological Survey’s Western Geographic Science Center for the Lake Tahoe Basin. Within the context of the natural-resource management and anthropogenic issues of the basin and in an effort to advance land-use and land-cover change science, this report addresses the problem of developing the LUSM as a decision support system. It includes consideration of land-use modeling theory, fire modeling and disturbance in the wildland-urban interface, historical land-use change and its relation to active land management, hydrologic modeling and the impact of urbanization as related to the Lahontan Regional Water Quality Control Board’s recently developed Total Maximum Daily Load report for the basin, and biodiversity in urbanizing areas. The LUSM strives to inform land-management decisions in a complex regulatory environment by simulating parcel-based, land-use transitions with a stochastic, spatially constrained, agent-based model. The tool is intended to be useful for multiple purposes, including the multiagency Pathway 2007 regional planning effort, the Tahoe Regional Planning Agency (TRPA) Regional Plan Update, and complementary research endeavors and natural-resource-management efforts. The LUSM is an Internet-based, scenario-generation decision support tool for allocating retired and developed parcels over the next 20 years. Because USGS staff worked closely with TRPA staff and their “Code of Ordinances” and analyzed datasets of historical management and land-use practices, this report accomplishes the task of providing reasonable default values for a baseline scenario that can be used in the LUSM. One result from the baseline scenario for the model suggests that all vacant parcels could be allocated within 12 years. Results also include

  3. Combined effects of climate models, hydrological model structures and land use scenarios on hydrological impacts of climate change

    DEFF Research Database (Denmark)

    Karlsson, Ida B.; Sonnenborg, Torben O.; Refsgaard, Jens Christian

    2016-01-01

    to cause little change in mean hydrological responses and little variation between hydrological models. Differences in hydrological model responses to land use were, however, significant for extremes due to dissimilarities in hydrological model structure and process equations. The climate model choice......Impact studies of the hydrological response of future climate change are important for the water authorities when risk assessment, management and adaptation to a changing climate are carried out. The objective of this study was to model the combined effect of land use and climate changes...... on hydrology for a 486 km2 catchment in Denmark and to evaluate the sensitivity of the results to the choice of hydrological model. Three hydrological models, NAM, SWAT and MIKE SHE, were constructed and calibrated using similar methods. Each model was forced with results from four climate models and four land...

  4. Modeling the Behaviour of an Advanced Material Based Smart Landing Gear System for Aerospace Vehicles

    Science.gov (United States)

    Varughese, Byji; Dayananda, G. N.; Rao, M. Subba

    2008-07-01

    The last two decades have seen a substantial rise in the use of advanced materials such as polymer composites for aerospace structural applications. In more recent years there has been a concerted effort to integrate materials, which mimic biological functions (referred to as smart materials) with polymeric composites. Prominent among smart materials are shape memory alloys, which possess both actuating and sensory functions that can be realized simultaneously. The proper characterization and modeling of advanced and smart materials holds the key to the design and development of efficient smart devices/systems. This paper focuses on the material characterization; modeling and validation of the model in relation to the development of a Shape Memory Alloy (SMA) based smart landing gear (with high energy dissipation features) for a semi rigid radio controlled airship (RC-blimp). The Super Elastic (SE) SMA element is configured in such a way that it is forced into a tensile mode of high elastic deformation. The smart landing gear comprises of a landing beam, an arch and a super elastic Nickel-Titanium (Ni-Ti) SMA element. The landing gear is primarily made of polymer carbon composites, which possess high specific stiffness and high specific strength compared to conventional materials, and are therefore ideally suited for the design and development of an efficient skid landing gear system with good energy dissipation characteristics. The development of the smart landing gear in relation to a conventional metal landing gear design is also dealt with.

  5. An integrated modelling framework for regulated river systems in Land Surface Hydrological Models

    Science.gov (United States)

    Rehan Anis, Muhammad; razavi, Saman; Wheater, Howard

    2017-04-01

    Many of the large river systems around the world are highly regulated with numerous physical flow control and storage structures as well as a range of water abstraction rules and regulations. Most existing Land Surface Models (LSM) do not represent the modifications to the hydrological regimes introduced by water management (reservoirs, irrigation diversions, etc.). The interactions between natural hydrological processes and changes in water and energy fluxes and storage due to human interventions are important to the understanding of how these systems may respond to climate change amongst other drivers for change as well as to the assessment of their feedbacks to the climate system at regional and global scales. This study presents an integrated modelling approach to include human interventions within natural hydrological systems using a fully coupled modelling platform. The Bow River Basin in Alberta (26,200 km2), one of the most managed Canadian rivers, is used to demonstrate the approach. We have dynamically linked the MESH modelling system, which embeds the Canadian Land Surface Scheme (CLASS), with the MODSIM-DSS water management modelling tool. MESH models the natural hydrology while MODSIM optimizes the reservoir operation of 4 simulated reservoirs to satisfy demands within the study basin. MESH was calibrated for the catchments upstream the reservoirs and gave good performance (NSE = 0.81) while BIAS was only 2.3% at the catchment outlet. Without coupling with MODSIM (i.e. no regulation), simulated hydrographs at the catchment outlet were in complete disagreement with observations (NSE = 0.28). The coupled model simulated the optimization introduced by the operation of the multi-reservoir system in the Bow river basin and shows excellent agreement between observed and simulated hourly flows (NSE = 0.98). Irrigation demands are fully satisfied during summer, however, there are some shortages in winter demand from industries, which can be rectified by

  6. Economic and Physical Modeling of Land Use in GCAM 3.0 and an Application to Agricultural Productivity, Land, and Terrestrial Carbon

    Energy Technology Data Exchange (ETDEWEB)

    Wise, Marshall A.; Calvin, Katherine V.; Kyle, G. Page; Luckow, Patrick; Edmonds, James A.

    2014-09-01

    We explore the impact of changes in agricultural productivity on global land use and terrestrial carbon using the new agriculture and land use modeling approach developed for Global Change Assessment Model (GCAM) version 3.0. This approach models economic land use decisions with regional, physical, and technological specificity while maintaining economic and physical integration with the rest of the GCAM model. Physical land characteristics and quantities are tracked explicitly, and crop production practices are modeled discretely to facilitate coupling with physical models. Economic land allocation is modeled with non-linear functions in a market equilibrium rather than through a constrained optimization. In this paper, we explore three scenarios of future agriculture productivity in all regions of the globe over this century, ranging from a high growth to a zero growth level. The higher productivity growth scenario leads to lower crop prices, increased production of crops in developing nations, preservation of global forested lands and lower terrestrial carbon emissions. The scenario with no productivity improvement results in higher crop prices, an expansion of crop production in the developed world, loss of forested lands globally, and higher terrestrial carbon emissions.

  7. Analysis and Modeling of Urban Land Cover Change in Setúbal and Sesimbra, Portugal

    Directory of Open Access Journals (Sweden)

    Yikalo H. Araya

    2010-06-01

    Full Text Available The expansion of cities entails the abandonment of forest and agricultural lands, and these lands’ conversion into urban areas, which results in substantial impacts on ecosystems. Monitoring these changes and planning urban development can be successfully achieved using multitemporal remotely sensed data, spatial metrics, and modeling. In this paper, urban land use change analysis and modeling was carried out for the Concelhos of Setúbal and Sesimbra in Portugal. An existing land cover map for the year 1990, together with two derived land cover maps from multispectral satellite images for the years 2000 and 2006, were utilized using an object-oriented classification approach. Classification accuracy assessment revealed satisfactory results that fulfilled minimum standard accuracy levels. Urban land use dynamics, in terms of both patterns and quantities, were studied using selected landscape metrics and the Shannon Entropy index. Results show that urban areas increased by 91.11% between 1990 and 2006. In contrast, the change was only 6.34% between 2000 and 2006. The entropy value was 0.73 for both municipalities in 1990, indicating a high rate of urban sprawl in the area. In 2006, this value, for both Sesimbra and Setúbal, reached almost 0.90. This is demonstrative of a tendency toward intensive urban sprawl. Urban land use change for the year 2020 was modeled using a Cellular Automata based approach. The predictive power of the model was successfully validated using Kappa variations. Projected land cover changes show a growing tendency in urban land use, which might threaten areas that are currently reserved for natural parks and agricultural lands.

  8. Simulation of boreal Summer Monsoon Rainfall using CFSV2_SSiB model: sensitivity to Land Use Land Cover (LULC)

    Science.gov (United States)

    Chilukoti, N.; Xue, Y.

    2016-12-01

    The land surface play a vital role in determining the surface energy budget, accurate representation of land use and land cover (LULC) is necessary to improve forecast. In this study, we have investigated the influence of surface vegetation maps with different LULC on simulating the boreal summer monsoon rainfall. Using a National Centres for Environmental Prediction (NCEP) Coupled Forecast System version 2(CFSv2) model coupled with Simplified Simple Biosphere (SSiB) model, two experiments were conducted: one with old vegetation map and one with new vegetation map. The significant differences between new and old vegetation map were in semi-arid and arid areas. For example, in old map Tibetan plateau classified as desert, which is not appropriate, while in new map it was classified as grasslands or shrubs with bare soil. Old map classified the Sahara desert as a bare soil and shrubs with bare soil, whereas in new map it was classified as bare ground. In addition to central Asia and the Sahara desert, in new vegetation map, Europe had more cropped area and India's vegetation cover was changed from crops and forests to wooded grassland and small areas of grassland and shrubs. The simulated surface air temperature with new map shows a significant improvement over Asia, South Africa, and northern America by some 1 to 2ºC and 2 to 3ºC over north east China and these are consistent with the reduced rainfall biases over Africa, near Somali coast, north east India, Bangladesh, east China sea, eastern Pacific and northern USA. Over Indian continent and bay of Bengal dry rainfall anomalies that is the only area showing large dry rainfall bias, however, they were unchanged with new map simulation. Overall the CFSv2(coupled with SSiB) model with new vegetation map show a promising result in improving the monsoon forecast by improving the Land -Atmosphere interactions. To compare with the LULC forcing, experiment was conducted using the Global Forecast System (GFS) simulations

  9. The global land surface energy balance and its representation in CMIP5 models

    Science.gov (United States)

    Wild, Martin; Folini, Doris; Hakuba, Maria; Schär, Christoph; Seneviratne, Sonia; Kato, Seiji; Rutan, David; Ammann, Christof; Wood, Eric; König-Langlo, Gert

    2015-04-01

    The energy budget over terrestrial surfaces is a key determinant of the land surface climate and governs a variety of physical, chemical and biological surface processes. The purpose of the present study is to establish new reference estimates for the different components of the energy balance over global land surfaces. Thanks to the impressive progress in space-based observation systems in the past decade, we now know the energy exchanges between our planet and the surrounding space with unprecedented accuracy. However, the energy flows at the Earth's surface have not been established with the same accuracy, since they cannot be directly measured from satellites. Accordingly, estimates on the magnitude of the fluxes at terrestrial surfaces largely vary, and latest climate models from the Coupled Model Intercomparison Project Phase 5 (CMIP5) still show significant differences in their simulated energy budgets on a land mean basis, which prevents a consistent simulation of the land surface processes in these models. In the present study we use to the extent possible direct observations of surface radiative fluxes from the Global Energy Balance Archive (GEBA) and the Baseline Surface Radiation Network (BSRN) to better constrain the simulated fluxes over global land surfaces. These model-calculated fluxes stem from the comprehensive set of more than 40 global climate from CMIP5 used in the latest IPCC report AR5. The CMIP5 models overall still show a tendency to overestimate the downward solar and underestimate the downward thermal radiation at terrestrial surfaces, a long standing problem in climate modelling. Based on the direct radiation observations and the bias structure of the CMIP5 models we infer best estimates for the downward solar and thermal radiation averaged over global land surfaces. They amount to 184 Wm-2 and 306 Wm-2, respectively. These values closely agree with the respective quantities independently derived by recent state-of-the-art reanalyses

  10. Reconciling Land-Ocean Moisture Transport Variability in Reanalyses with P-ET in Observationally-Driven Land Surface Models

    Science.gov (United States)

    Robertson, Franklin R.; Bosilovich, Michael G.; Roberts, Jason B.

    2016-01-01

    Vertically integrated atmospheric moisture transport from ocean to land [vertically integrated atmospheric moisture flux convergence (VMFC)] is a dynamic component of the global climate system but remains problematic in atmospheric reanalyses, with current estimates having significant multidecadal global trends differing even in sign. Continual evolution of the global observing system, particularly stepwise improvements in satellite observations, has introduced discrete changes in the ability of data assimilation to correct systematic model biases, manifesting as nonphysical variability. Land surface models (LSMs) forced with observed precipitation P and near-surface meteorology and radiation provide estimates of evapotranspiration (ET). Since variability of atmospheric moisture storage is small on interannual and longer time scales, VMFC equals P minus ET is a good approximation and LSMs can provide an alternative estimate. However, heterogeneous density of rain gauge coverage, especially the sparse coverage over tropical continents, remains a serious concern. Rotated principal component analysis (RPCA) with prefiltering of VMFC to isolate the artificial variability is used to investigate artifacts in five reanalysis systems. This procedure, although ad hoc, enables useful VMFC corrections over global land. The P minus ET estimates from seven different LSMs are evaluated and subsequently used to confirm the efficacy of the RPCA-based adjustments. Global VMFC trends over the period 1979-2012 ranging from 0.07 to minus 0.03 millimeters per day per decade are reduced by the adjustments to 0.016 millimeters per day per decade, much closer to the LSM P minus ET estimate (0.007 millimeters per day per decade). Neither is significant at the 90 percent level. ENSO (El Nino-Southern Oscillation)-related modulation of VMFC and P minus ET remains the largest global interannual signal, with mean LSM and adjusted reanalysis time series correlating at 0.86.

  11. Coupling integrated assessment and earth system models: concepts and an application to land use change

    Science.gov (United States)

    O'Neill, B. C.; Lawrence, P.; Ren, X.

    2016-12-01

    Collaboration between the integrated assessment modeling (IAM) and earth system modeling (ESM) communities is increasing, driven by a growing interest in research questions that require analysis integrating both social and natural science components. This collaboration often takes the form of integrating their respective models. There are a number of approaches available to implement this integration, ranging from one-way linkages to full two-way coupling, as well as approaches that retain a single modeling framework but improve the representation of processes from the other framework. We discuss the pros and cons of these different approaches and the conditions under which a two-way coupling of IAMs and ESMs would be favored over a one-way linkage. We propose a criterion that is necessary and sufficient to motivate two-way coupling: A human process must have an effect on an earth system process that is large enough to cause a change in the original human process that is substantial compared to other uncertainties in the problem being investigated. We then illustrate a test of this criterion for land use-climate interactions based on work using the Community Earth System Model (CESM) and land use scenarios from the Representative Concentration Pathways (RCPs), in which we find that the land use effect on regional climate is unlikely to meet the criterion. We then show an example of implementing a one-way linkage of land use and agriculture between an IAM, the integrated Population-Economy-Technology-Science (iPETS) model, and CESM that produces fully consistent outcomes between iPETS and the CESM land surface model. We use the linked system to model the influence of climate change on crop yields, agricultural land use, crop prices and food consumption under two alternative future climate scenarios. This application demonstrates the ability to link an IAM to a global land surface and climate model in a computationally efficient manner.

  12. A stochastic Forest Fire Model for future land cover scenarios assessment

    Directory of Open Access Journals (Sweden)

    M. D'Andrea

    2010-10-01

    Full Text Available Land cover is affected by many factors including economic development, climate and natural disturbances such as wildfires. The ability to evaluate how fire regimes may alter future vegetation, and how future vegetation may alter fire regimes, would assist forest managers in planning management actions to be carried out in the face of anticipated socio-economic and climatic change. In this paper, we present a method for calibrating a cellular automata wildfire regime simulation model with actual data on land cover and wildfire size-frequency. The method is based on the observation that many forest fire regimes, in different forest types and regions, exhibit power law frequency-area distributions. The standard Drossel-Schwabl cellular automata Forest Fire Model (DS-FFM produces simulations which reproduce this observed pattern. However, the standard model is simplistic in that it considers land cover to be binary – each cell either contains a tree or it is empty – and the model overestimates the frequency of large fires relative to actual landscapes. Our new model, the Modified Forest Fire Model (MFFM, addresses this limitation by incorporating information on actual land use and differentiating among various types of flammable vegetation. The MFFM simulation model was tested on forest types with Mediterranean and sub-tropical fire regimes. The results showed that the MFFM was able to reproduce structural fire regime parameters for these two regions. Further, the model was used to forecast future land cover. Future research will extend this model to refine the forecasts of future land cover and fire regime scenarios under climate, land use and socio-economic change.

  13. Evaluation of Landing Characteristics Achieved by Simulations and Flight Tests on a Small-scaled Model Related to Magnetically Levitated Advanced Take-off and Landing Operations

    NARCIS (Netherlands)

    Rohacs, D.; Voskuijl, M.; Siepenkotter, N.

    2014-01-01

    The goal of this paper is to simulate and measure on a small-scaled model the landing characteristics related to take-off and landing (TOL) operations supported by a magnetic levitation (MAGLEV) system as ground-based power supply. The technical feasibility and the potential benefits of using

  14. 78 FR 6319 - Notice of Availability of the Report: Recommended Parameters for Solid Flame Models for Land...

    Science.gov (United States)

    2013-01-30

    ... the Montoir large scale LNG fire test over land conducted by Gaz de France in 1989. FERC staff... Models for Land Based Liquefied Natural Gas Spills The staff of the Federal Energy Regulatory Commission... gas (LNG) pool fires on land. The report investigates the effects of matching both individual modeling...

  15. LAND – PRICE DETERMINANTS USING THE SPATIAL ECONOMETRICS MODELING IN THE MOLDAVIAN REAL ESTATE MARKET

    Directory of Open Access Journals (Sweden)

    Anatol RACUL

    2012-01-01

    Full Text Available The purpose of this paper is to determine the factors which influence the land market in Republic of Moldova. The paper aims to discover the determinants for land pricing using the spatial econometrics modeling, as it is widely used when the spatial component is present. The country’s agricultural economy combined with the interest of international organizations and limited data availability directed the focus of this empirical study towards land for agricultural purposes. The factors which determine the land market (for agricultural purposes in Republic of Moldova are mainly related to economic characteristics of land, such as field productivity, the position on the local landscape (characterized by angle and soil quality, proximity to local or national roads (due to storage and transportation reasons, and economic characteristics of owners. Also, another important role in land market price creation is the pressure of urban space to transform land for agricultural use close to cities and villages in spaces for industrial or residential purposes. This is characterized by the financial pressure from the urban centers which has become significant in land transactions.

  16. Integrating Ecosystem Carbon Dynamics into State-and-Transition Simulation Models of Land Use/Land Cover Change

    Science.gov (United States)

    Sleeter, B. M.; Daniel, C.; Frid, L.; Fortin, M. J.

    2016-12-01

    State-and-transition simulation models (STSMs) provide a general approach for incorporating uncertainty into forecasts of landscape change. Using a Monte Carlo approach, STSMs generate spatially-explicit projections of the state of a landscape based upon probabilistic transitions defined between states. While STSMs are based on the basic principles of Markov chains, they have additional properties that make them applicable to a wide range of questions and types of landscapes. A current limitation of STSMs is that they are only able to track the fate of discrete state variables, such as land use/land cover (LULC) classes. There are some landscape modelling questions, however, for which continuous state variables - for example carbon biomass - are also required. Here we present a new approach for integrating continuous state variables into spatially-explicit STSMs. Specifically we allow any number of continuous state variables to be defined for each spatial cell in our simulations; the value of each continuous variable is then simulated forward in discrete time as a stochastic process based upon defined rates of change between variables. These rates can be defined as a function of the realized states and transitions of each cell in the STSM, thus providing a connection between the continuous variables and the dynamics of the landscape. We demonstrate this new approach by (1) developing a simple IPCC Tier 3 compliant model of ecosystem carbon biomass, where the continuous state variables are defined as terrestrial carbon biomass pools and the rates of change as carbon fluxes between pools, and (2) integrating this carbon model with an existing LULC change model for the state of Hawaii, USA.

  17. Assessing carbon stocks and modelling win-win scenarios of carbon sequestration through land-use changes

    Energy Technology Data Exchange (ETDEWEB)

    Ponce-Hernandez, R.; Koohafkan, P.; Antoine, J. (eds.)

    2004-07-01

    This publication presents a methodology and software tools for assessing carbon stocks and modelling scenarios of carbon sequestration that were developed and tested in pilot field studies in Mexico and Cuba. The models and tools enable the analysis of land use change scenarios in order to identify in a given area (watershed or district) land use alternatives and land management practices that simultaneously maximize food production, maximize soil carbon sequestration, maximize biodiversity conservation and minimize land degradation. The objective is to develop and implement 'win-win' options that satisfy the multiple goals of farmers, land users and other stakeholders in relation to food security, carbon sequestration, biodiversity and land conservation.

  18. Calibration of a distributed hydrology and land surface model using energy flux measurements

    DEFF Research Database (Denmark)

    Larsen, Morten Andreas Dahl; Refsgaard, Jens Christian; Jensen, Karsten H.

    2016-01-01

    In this study we develop and test a calibration approach on a spatially distributed groundwater-surface water catchment model (MIKE SHE) coupled to a land surface model component with particular focus on the water and energy fluxes. The model is calibrated against time series of eddy flux measure...

  19. Palaeoclimatological perspective on river basin hydrometeorology: case of the Mekong Basin

    Science.gov (United States)

    Räsänen, T. A.; Lehr, C.; Mellin, I.; Ward, P. J.; Kummu, M.

    2013-05-01

    Globally, there have been many extreme weather events in recent decades. A challenge has been to determine whether these extreme weather events have increased in number and intensity compared to the past. This challenge is made more difficult due to the lack of long-term instrumental data, particularly in terms of river discharge, in many regions including Southeast Asia. Thus our main aim in this paper is to develop a river basin scale approach for assessing interannual hydrometeorological and discharge variability on long, palaeological, time scales. For the development of the basin-wide approach, we used the Mekong River basin as a case study area, although the approach is also intended to be applicable to other basins. Firstly, we derived a basin-wide Palmer Drought Severity Index (PDSI) from the Monsoon Asia Drought Atlas (MADA). Secondly, we compared the basin-wide PDSI with measured discharge to validate our approach. Thirdly, we used basin-wide PDSI to analyse the hydrometeorology and discharge of the case study area over the study period of 1300-2005. For the discharge-MADA comparison and hydrometeorological analyses, we used methods such as linear correlations, smoothing, moving window variances, Levene type tests for variances, and wavelet analyses. We found that the developed basin-wide approach based on MADA can be used for assessing long-term average conditions and interannual variability for river basin hydrometeorology and discharge. It provides a tool for studying interannual discharge variability on a palaeological time scale, and therefore the approach contributes to a better understanding of discharge variability during the most recent decades. Our case study revealed that the Mekong has experienced exceptional levels of interannual variability during the post-1950 period, which could not be observed in any other part of the study period. The increased variability was found to be at least partly associated with increased El Niño Southern

  20. GLDAS Noah Land Surface Model L4 Monthly 1.0 x 1.0 degree V001

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set contains a series of land surface parameters simulated from the Noah 2.7.1 model in the Global Land Data Assimilation System (GLDAS). The data are in...

  1. GLDAS Noah Land Surface Model L4 3 Hourly 0.25 x 0.25 degree Subsetted V001

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set contains a series of land surface parameters simulated from the Noah 2.7.1 model in the Global Land Data Assimilation System (GLDAS). The data are in...

  2. GLDAS Noah Land Surface Model L4 3 Hourly 1.0 x 1.0 degree Subsetted V001

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set contains a series of land surface parameters simulated from the Noah 2.7.1 model in the Global Land Data Assimilation System (GLDAS). The data are in...

  3. GLDAS Noah Land Surface Model L4 Monthly 0.25 x 0.25 degree V001

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set contains a series of land surface parameters simulated from the Noah 2.7.1 model in the Global Land Data Assimilation System (GLDAS). The data are in...

  4. GLDAS VIC Land Surface Model L4 Monthly 1.0 x 1.0 degree V001

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set contains a series of land surface parameters simulated from the Variable Infiltration Capacity (VIC) model in the Global Land Data Assimilation System...

  5. GLDAS Mosaic Land Surface Model L4 Monthly 1.0 x 1.0 degree V001

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set contains a series of land surface parameters simulated from the Mosaic model in the Global Land Data Assimilation System (GLDAS). The data are in 1.0...

  6. GLDAS VIC Land Surface Model L4 3 Hourly 1.0 x 1.0 degree V001

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set contains a series of land surface parameters simulated from the Variable Infiltration Capacity (VIC) Model in the Global Land Data Assimilation System...

  7. NLDAS Mosaic Land Surface Model L4 Monthly Climatology 0.125 x 0.125 degree V002

    Data.gov (United States)

    National Aeronautics and Space Administration — This monthly climatology data set contains a series of land surface parameters simulated from the Mosaic land-surface model (LSM) for Phase 2 of the North American...

  8. NLDAS Noah Land Surface Model L4 Monthly Climatology 0.125 x 0.125 degree V002

    Data.gov (United States)

    National Aeronautics and Space Administration — This monthly climatology data set contains a series of land surface parameters simulated from the Noah land-surface model (LSM) for Phase 2 of the North American...

  9. Land-use change trajectories up to 2050: insights from a global agro-economic model comparison

    NARCIS (Netherlands)

    Schmitz, C.; Meijl, van J.C.M.; Kyle, P.; Nelson, G.C.; Fujimori, S.; Gurgel, A.; Havlik, P.; Heyhoe, E.; Mason d'Croz, D.; Popp, A.; Sands, R.; Tabeau, A.A.; Mensbrugghe, van der D.; Lampe, von M.; Wise, M.; Blanc, E.; Hasegawa, T.; Kavallari, A.; Valin, H.

    2014-01-01

    Changes in agricultural land use have important implications for environmental services. Previous studies of agricultural land-use futures have been published indicating large uncertainty due to different model assumptions and methodologies. In this article we present a first comprehensive

  10. GLDAS Mosaic Land Surface Model L4 3 Hourly 1.0 x 1.0 degree Subsetted V001

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set contains a series of land surface parameters simulated from the Mosaic model in the Global Land Data Assimilation System (GLDAS). The data are in 1.0...

  11. An econometric analysis of changes in arable land utilization using multinomial logit model in Pinggu district, Beijing, China.

    Science.gov (United States)

    Xu, Yueqing; McNamara, Paul; Wu, Yanfang; Dong, Yue

    2013-10-15

    Arable land in China has been decreasing as a result of rapid population growth and economic development as well as urban expansion, especially in developed regions around cities where quality farmland quickly disappears. This paper analyzed changes in arable land utilization during 1993-2008 in the Pinggu district, Beijing, China, developed a multinomial logit (MNL) model to determine spatial driving factors influencing arable land-use change, and simulated arable land transition probabilities. Land-use maps, as well as social-economic and geographical data were used in the study. The results indicated that arable land decreased significantly between 1993 and 2008. Lost arable land shifted into orchard, forestland, settlement, and transportation land. Significant differences existed for arable land transitions among different landform areas. Slope, elevation, population density, urbanization rate, distance to settlements, and distance to roadways were strong drivers influencing arable land transition to other uses. The MNL model was proved effective for predicting transition probabilities in land use from arable land to other land-use types, thus can be used for scenario analysis to develop land-use policies and land-management measures in this metropolitan area. Copyright © 2013 Elsevier Ltd. All rights reserved.

  12. Forecasting Urban Vacancy Dynamics in a Shrinking City: A Land Transformation Model

    Directory of Open Access Journals (Sweden)

    Jaekyung Lee

    2017-04-01

    Full Text Available In the past two centuries, many American urban areas have experienced significant expansion in both populating and depopulating cities. The pursuit of bigger, faster, and more growth-oriented planning parallels a situation where municipal decline has also been recognized as a global epidemic. In recent decades many older industrial cities have experienced significant depopulation, job loss, economic decline, and massive increases in vacant and abandoned properties due primarily to losses in industry and relocating populations. Despite continuous economic decline and depopulation, many of these so-called ‘shrinking cities’ still chase growth-oriented planning policies, due partially to inabilities to accurately predict future urban growth/decline patterns. This capability is critical to understanding land use alternation patterns and predicting future possible scenarios for the development of more proactive land use policies dealing with urban decline and regeneration. In this research, the city of Chicago, Illinois, USA is used as a case site to test an urban land use change model that predicts urban decline in a shrinking city, using vacant land as a proxy. Our approach employs the Land Transformation Model (LTM, which combines Geographic Information Systems and artificial neural networks to forecast land use change. Results indicate that the LTM is a good resource to simulate urban vacant land changes. Mobility and housing market conditions seem to be the primary variables contributing to decline.

  13. An Exploration of Scenarios to Support Sustainable Land Management Using Integrated Environmental Socio-economic Models

    Science.gov (United States)

    Fleskens, L.; Nainggolan, D.; Stringer, L. C.

    2014-11-01

    Scenario analysis constitutes a valuable deployment method for scientific models to inform environmental decision-making, particularly for evaluating land degradation mitigation options, which are rarely based on formal analysis. In this paper we demonstrate such an assessment using the PESERA-DESMICE modeling framework with various scenarios for 13 global land degradation hotspots. Starting with an initial assessment representing land degradation and productivity under current conditions, options to combat instances of land degradation are explored by determining: (1) Which technologies are most biophysically appropriate and most financially viable in which locations; we term these the "technology scenarios"; (2) how policy instruments such as subsidies influence upfront investment requirements and financial viability and how they lead to reduced levels of land degradation; we term these the "policy scenarios"; and (3) how technology adoption affects development issues such as food production and livelihoods; we term these the "global scenarios". Technology scenarios help choose the best technology for a given area in biophysical and financial terms, thereby outlining where policy support may be needed to promote adoption; policy scenarios assess whether a policy alternative leads to a greater extent of technology adoption; while global scenarios demonstrate how implementing technologies may serve wider sustainable development goals. Scenarios are applied to assess spatial variation within study sites as well as to compare across different sites. Our results show significant scope to combat land degradation and raise agricultural productivity at moderate cost. We conclude that scenario assessment can provide informative input to multi-level land management decision-making processes.

  14. Sensing Urban Land-Use Patterns by Integrating Google Tensorflow and Scene-Classification Models

    Science.gov (United States)

    Yao, Y.; Liang, H.; Li, X.; Zhang, J.; He, J.

    2017-09-01

    With the rapid progress of China's urbanization, research on the automatic detection of land-use patterns in Chinese cities is of substantial importance. Deep learning is an effective method to extract image features. To take advantage of the deep-learning method in detecting urban land-use patterns, we applied a transfer-learning-based remote-sensing image approach to extract and classify features. Using the Google Tensorflow framework, a powerful convolution neural network (CNN) library was created. First, the transferred model was previously trained on ImageNet, one of the largest object-image data sets, to fully develop the model's ability to generate feature vectors of standard remote-sensing land-cover data sets (UC Merced and WHU-SIRI). Then, a random-forest-based classifier was constructed and trained on these generated vectors to classify the actual urban land-use pattern on the scale of traffic analysis zones (TAZs). To avoid the multi-scale effect of remote-sensing imagery, a large random patch (LRP) method was used. The proposed method could efficiently obtain acceptable accuracy (OA = 0.794, Kappa = 0.737) for the study area. In addition, the results show that the proposed method can effectively overcome the multi-scale effect that occurs in urban land-use classification at the irregular land-parcel level. The proposed method can help planners monitor dynamic urban land use and evaluate the impact of urban-planning schemes.

  15. Modeling salt movement and halophytic crop growth on marginal lands with the APEX model

    Science.gov (United States)

    Goehring, N.; Saito, L.; Verburg, P.; Jeong, J.; Garrett, A.

    2016-12-01

    Saline soils negatively impact crop productivity in nearly 20% of irrigated agricultural lands worldwide. At these saline sites, cultivation of highly salt-tolerant plants, known as halophytes, may increase productivity compared to conventional salt-sensitive crops (i.e., glycophytes), thereby increasing the economic potential of marginal lands. Through a variety of mechanisms, halophytes are more effective than glycophytes at excluding, accumulating, and secreting salts from their tissues. Each mechanism can have a different impact on the salt balance in the plant-soil-water system. To date, little information is available to understand the long-term impacts of halophyte cultivation on environmental quality. This project utilizes the Agricultural Policy/Environmental Extender (APEX) model, developed by the US Department of Agriculture, to model the growth and production of two halophytic crops. The crops being modeled include quinoa (Chenopodium quinoa), which has utilities for human consumption and forage, and AC Saltlander green wheatgrass (Elymus hoffmannii), which has forage utility. APEX simulates salt movement between soil layers and accounts for the salt balance in the plant-soil-water system, including salinity in irrigation water and crop-specific salt uptake. Key crop growth parameters in APEX are derived from experimental growth data obtained under non-stressed conditions. Data from greenhouse and field experiments in which quinoa and AC Saltlander were grown under various soil salinity and irrigation salinity treatments are being used to parameterize, calibrate, and test the model. This presentation will discuss progress on crop parameterization and completed model runs under different salt-affected soil and irrigation conditions.

  16. Differential mortality patterns from hydro-meteorological disasters: Evidence from cause-of-death data by age and sex. Vienna Yearbook of Population Research|Vienna Yearbook of Population Research 2015|

    OpenAIRE

    Zagheni, Emilio; Striessnig, Erich; Muttarak, Raya

    2016-01-01

    This paper evaluates the heterogeneous impact of hydro-meteorological disasters on populations along the dimensions of age, sex, and human development. The analysis is based on previously untapped cause-of-death data over the period 1995– 2011 that were obtained from the WHO mortality database, and were based on the civil registration records of 63 countries/territories. Using these data, we evaluate patterns of mortality related to meteorological disasters in the spirit of model life tables....

  17. AVALON: definition and modeling of a vertical takeoff and landing UAV

    Science.gov (United States)

    Silva, N. B. F.; Marconato, E. A.; Branco, K. R. L. J. C.

    2015-09-01

    Unmanned Aerial Vehicles (UAVs) have been used in numerous applications, like remote sensing, precision agriculture and atmospheric data monitoring. Vertical takeoff and landing (VTOL) is a modality of these aircrafts, which are capable of taking off and landing vertically, like a helicopter. This paper presents the definition and modeling of a fixed- wing VTOL, named AVALON (Autonomous VerticAL takeOff and laNding), which has the advantages of traditional aircrafts with improved performance and can take off and land in small areas. The principles of small UAVs development were followed to achieve a better design and to increase the range of applications for this VTOL. Therefore, we present the design model of AVALON validated in a flight simulator and the results show its validity as a physical option for an UAV platform.

  18. Integrated Dynamic Gloabal Modeling of Land Use, Energy and Economic Growth

    Energy Technology Data Exchange (ETDEWEB)

    Atul Jain, University of Illinois, Urbana-Champaign, IL; Neill, NCAR, Boulder, CO

    2009-10-14

    The overall objective of this collaborative project is to integrate an existing general equilibrium energy-economic growth model with a biogeochemical cycles and biophysical models in order to more fully explore the potential contribution of land use-related activities to future emissions scenarios. Land cover and land use change activities, including deforestation, afforestation, and agriculture management, are important source of not only CO2, but also non-CO2 GHGs. Therefore, contribution of land-use emissions to total emissions of GHGs is important, and consequently their future trends are relevant to the estimation of climate change and its mitigation. This final report covers the full project period of the award, beginning May 2006, which includes a sub-contract to Brown University later transferred to the National Center for Atmospheric Research (NCAR) when Co-PI Brian O'Neill changed institutional affiliations.

  19. Consequential life cycle inventory modelling of land use induced by crop consumption

    DEFF Research Database (Denmark)

    Kløverpris, Jesper Hedal

    cycle assessments involving crop consumption. Increased demand for a given crop can be met by intensification, expansion, and/or by displacement of other crops or pastures. The last option will reduce the supply of other agricultural products, which may then be replaced elsewhere. Such displacement-replacement......The purpose of the present PhD project was to identify the mechanisms governing global land use consequences of increased crop demand in a given location and, based on this conceptual analysis, to present and demonstrate a method proposal for construction of land use data that can be used in life...... mechanisms are governed by the availability of suitable agricultural land and several economic conditions, such as transport and trade costs. To estimate the land use response to an increase in crop demand, economic modelling can be used. In this project, the economic equilibrium model GTAP (Global Trade...

  20. State-dependent errors in a land surface model across biomes inferred from eddy covariance observations on multiple timescales

    NARCIS (Netherlands)

    Wang, T.; Brender, P.; Ciais, P.; Piao, S.; Mahecha, M.D.; Chevallier, F.; Reichstein, M.; Ottle, C.; Maignan, F.; Arain, A.; Bohrer, G.; Cescatti, A.; Kiely, G.; Law, B.E.; Lutz, M.; Montagnani, L.; Moors, E.J.

    2012-01-01

    Characterization of state-dependent model biases in land surface models can highlight model deficiencies, and provide new insights into model development. In this study, artificial neural networks (ANNs) are used to estimate the state-dependent biases of a land surface model (ORCHIDEE: ORganising

  1. Monitoring arid-land groundwater abstraction through optimization of a land surface model with remote sensing-based evaporation

    KAUST Repository

    Lopez Valencia, Oliver Miguel

    2018-02-01

    The increase in irrigated agriculture in Saudi Arabia is having a large impact on its limited groundwater resources. While large-scale water storage changes can be estimated using satellite data, monitoring groundwater abstraction rates is largely non-existent at either farm or regional level, so water management decisions remain ill-informed. Although determining water use from space at high spatiotemporal resolutions remains challenging, a number of approaches have shown promise, particularly in the retrieval of crop water use via evaporation. Apart from satellite-based estimates, land surface models offer a continuous spatial-temporal evolution of full land-atmosphere water and energy exchanges. In this study, we first examine recent trends in terrestrial water storage depletion within the Arabian Peninsula and explore its relation to increased agricultural activity in the region using satellite data. Next, we evaluate a number of large-scale remote sensing-based evaporation models, giving insight into the challenges of evaporation retrieval in arid environments. Finally, we present a novel method aimed to retrieve groundwater abstraction rates used in irrigated fields by constraining a land surface model with remote sensing-based evaporation observations. The approach is used to reproduce reported irrigation rates over 41 center-pivot irrigation fields presenting a range of crop dynamics over the course of one year. The results of this application are promising, with mean absolute errors below 3 mm:day-1, bias of -1.6 mm:day-1, and a first rough estimate of total annual abstractions of 65.8 Mm3 (close to the estimated value using reported farm data, 69.42 Mm3). However, further efforts to address the overestimation of bare soil evaporation in the model are required. The uneven coverage of satellite data within the study site allowed us to evaluate its impact on the optimization, with a better match between observed and obtained irrigation rates on fields with

  2. A review of land-use regression models to assess spatial variation of outdoor air pollution

    Science.gov (United States)

    Hoek, Gerard; Beelen, Rob; de Hoogh, Kees; Vienneau, Danielle; Gulliver, John; Fischer, Paul; Briggs, David

    Studies on the health effects of long-term average exposure to outdoor air pollution have played an important role in recent health impact assessments. Exposure assessment for epidemiological studies of long-term exposure to ambient air pollution remains a difficult challenge because of substantial small-scale spatial variation. Current approaches for assessing intra-urban air pollution contrasts include the use of exposure indicator variables, interpolation methods, dispersion models and land-use regression (LUR) models. LUR models have been increasingly used in the past few years. This paper provides a critical review of the different components of LUR models. We identified 25 land-use regression studies. Land-use regression combines monitoring of air pollution at typically 20-100 locations, spread over the study area, and development of stochastic models using predictor variables usually obtained through geographic information systems (GIS). Monitoring is usually temporally limited: one to four surveys of typically one or two weeks duration. Significant predictor variables include various traffic representations, population density, land use, physical geography (e.g. altitude) and climate. Land-use regression methods have generally been applied successfully to model annual mean concentrations of NO 2, NO x, PM 2.5, the soot content of PM 2.5 and VOCs in different settings, including European and North-American cities. The performance of the method in urban areas is typically better or equivalent to geo-statistical methods, such as kriging, and dispersion models. Further developments of the land-use regression method include more focus on developing models that can be transferred to other areas, inclusion of additional predictor variables such as wind direction or emission data and further exploration of focalsum methods. Models that include a spatial and a temporal component are of interest for (e.g. birth cohort) studies that need exposure variables on a finer

  3. Advancing land surface model development with satellite-based Earth observations

    Science.gov (United States)

    Orth, Rene; Dutra, Emanuel; Trigo, Isabel F.; Balsamo, Gianpaolo

    2017-04-01

    The land surface forms an essential part of the climate system. It interacts with the atmosphere through the exchange of water and energy and hence influences weather and climate, as well as their predictability. Correspondingly, the land surface model (LSM) is an essential part of any weather forecasting system. LSMs rely on partly poorly constrained parameters, due to sparse land surface observations. With the use of newly available land surface temperature observations, we show in this study that novel satellite-derived datasets help to improve LSM configuration, and hence can contribute to improved weather predictability. We use the Hydrology Tiled ECMWF Scheme of Surface Exchanges over Land (HTESSEL) and validate it comprehensively against an array of Earth observation reference datasets, including the new land surface temperature product. This reveals satisfactory model performance in terms of hydrology, but poor performance in terms of land surface temperature. This is due to inconsistencies of process representations in the model as identified from an analysis of perturbed parameter simulations. We show that HTESSEL can be more robustly calibrated with multiple instead of single reference datasets as this mitigates the impact of the structural inconsistencies. Finally, performing coupled global weather forecasts we find that a more robust calibration of HTESSEL also contributes to improved weather forecast skills. In summary, new satellite-based Earth observations are shown to enhance the multi-dataset calibration of LSMs, thereby improving the representation of insufficiently captured processes, advancing weather predictability and understanding of climate system feedbacks. Orth, R., E. Dutra, I. F. Trigo, and G. Balsamo (2016): Advancing land surface model development with satellite-based Earth observations. Hydrol. Earth Syst. Sci. Discuss., doi:10.5194/hess-2016-628

  4. Improving evapotranspiration in a land surface model using biophysical variables derived from MSG/SEVIRI satellite

    Directory of Open Access Journals (Sweden)

    N. Ghilain

    2012-08-01

    Full Text Available Monitoring evapotranspiration over land is highly dependent on the surface state and vegetation dynamics. Data from spaceborn platforms are desirable to complement estimations from land surface models. The success of daily evapotranspiration monitoring at continental scale relies on the availability, quality and continuity of such data. The biophysical variables derived from SEVIRI on board the geostationary satellite Meteosat Second Generation (MSG and distributed by the Satellite Application Facility on Land surface Analysis (LSA-SAF are particularly interesting for such applications, as they aimed at providing continuous and consistent daily time series in near-real time over Africa, Europe and South America. In this paper, we compare them to monthly vegetation parameters from a database commonly used in numerical weather predictions (ECOCLIMAP-I, showing the benefits of the new daily products in detecting the spatial and temporal (seasonal and inter-annual variability of the vegetation, especially relevant over Africa. We propose a method to handle Leaf Area Index (LAI and Fractional Vegetation Cover (FVC products for evapotranspiration monitoring with a land surface model at 3–5 km spatial resolution. The method is conceived to be applicable for near-real time processes at continental scale and relies on the use of a land cover map. We assess the impact of using LSA-SAF biophysical variables compared to ECOCLIMAP-I on evapotranspiration estimated by the land surface model H-TESSEL. Comparison with in-situ observations in Europe and Africa shows an improved estimation of the evapotranspiration, especially in semi-arid climates. Finally, the impact on the land surface modelled evapotranspiration is compared over a north–south transect with a large gradient of vegetation and climate in Western Africa using LSA-SAF radiation forcing derived from remote sensing. Differences are highlighted. An evaluation against remote sensing derived land

  5. Integrating Modelling Approaches for Understanding Telecoupling: Global Food Trade and Local Land Use

    Directory of Open Access Journals (Sweden)

    James D. A. Millington

    2017-08-01

    Full Text Available The telecoupling framework is an integrated concept that emphasises socioeconomic and environmental interactions between distant places. Viewed through the lens of the telecoupling framework, land use and food consumption are linked across local to global scales by decision-making agents and trade flows. Quantitatively modelling the dynamics of telecoupled systems like this could be achieved using numerous different modelling approaches. For example, previous approaches to modelling global food trade have often used partial equilibrium economic models, whereas recent approaches to representing local land use decision-making have widely used agent-based modelling. System dynamics models are well established for representing aggregated flows and stores of products and values between distant locations. We argue that hybrid computational models will be useful for capitalising on the strengths these different modelling approaches each have for representing the various concepts in the telecoupling framework. However, integrating multiple modelling approaches into hybrid models faces challenges, including data requirements and uncertainty assessment. To help guide the development of hybrid models for investigating sustainability through the telecoupling framework here we examine important representational and modelling considerations in the context of global food trade and local land use. We report on the development of our own model that incorporates multiple modelling approaches in a modular approach to negotiate the trade-offs between ideal representation and modelling resource constraints. In this initial modelling our focus is on land use and food trade in and between USA, China and Brazil, but also accounting for the rest of the world. We discuss the challenges of integrating multiple modelling approaches to enable analysis of agents, flows, and feedbacks in the telecoupled system. Our analysis indicates differences in representation of agency

  6. Land-Atmosphere Coupling in the Multi-Scale Modelling Framework

    Science.gov (United States)

    Kraus, P. M.; Denning, S.

    2015-12-01

    The Multi-Scale Modeling Framework (MMF), in which cloud-resolving models (CRMs) are embedded within general circulation model (GCM) gridcells to serve as the model's cloud parameterization, has offered a number of benefits to GCM simulations. The coupling of these cloud-resolving models directly to land surface model instances, rather than passing averaged atmospheric variables to a single instance of a land surface model, the logical next step in model development, has recently been accomplished. This new configuration offers conspicuous improvements to estimates of precipitation and canopy through-fall, but overall the model exhibits warm surface temperature biases and low productivity.This work presents modifications to a land-surface model that take advantage of the new multi-scale modeling framework, and accommodate the change in spatial scale from a typical GCM range of ~200 km to the CRM grid-scale of 4 km.A parameterization is introduced to apportion modeled surface radiation into direct-beam and diffuse components. The diffuse component is then distributed among the land-surface model instances within each GCM cell domain. This substantially reduces the number excessively low light values provided to the land-surface model when cloudy conditions are modeled in the CRM, associated with its 1-D radiation scheme. The small spatial scale of the CRM, ~4 km, as compared with the typical ~200 km GCM scale, provides much more realistic estimates of precipitation intensity, this permits the elimination of a model parameterization of canopy through-fall. However, runoff at such scales can no longer be considered as an immediate flow to the ocean. Allowing sub-surface water flow between land-surface instances within the GCM domain affords better realism and also reduces temperature and productivity biases.The MMF affords a number of opportunities to land-surface modelers, providing both the advantages of direct simulation at the 4 km scale and a much reduced

  7. Sustainability of integrated land and water resources management in the face of climate and land use changes

    Science.gov (United States)

    Setegn, Shimelis

    2017-04-01

    Sustainable development integrates economic development, social development, and environmental protection. Land and Water resources are under severe pressure from increasing populations, fast development, deforestation, intensification of agriculture and the degrading environment in many part of the world. The demand for adequate and safe supplies of water is becoming crucial especially in the overpopulated urban centers of the Caribbean islands. Moreover, population growth coupled with environmental degradation and possible adverse impacts of land use and climate change are major factors limiting freshwater resource availability. The main objective of this study is to develop a hydrological model and analyze the spatiotemporal variability of hydrological processes in the Caribbean islands of Puerto Rico and Jamaica. Physically based eco-hydrological model was developed and calibrated in the Rio Grande Manati and Wag water watershed. Spatial distribution of annual hydrological processes, water balance components for wet and dry years, and annual hydrological water balance of the watershed are discussed. The impact of land use and climate change are addressed in the watersheds. Appropriate nature based adaptation strategies were evaluated. The study will present a good understanding of advantages and disadvantages of nature-based solutions for adapting climate change, hydro-meteorological risks and other extreme hydrological events.

  8. Soil mapping and processes modelling for sustainable land management: a review

    Science.gov (United States)

    Pereira, Paulo; Brevik, Eric; Muñoz-Rojas, Miriam; Miller, Bradley; Smetanova, Anna; Depellegrin, Daniel; Misiune, Ieva; Novara, Agata; Cerda, Artemi

    2017-04-01

    Soil maps and models are fundamental for a correct and sustainable land management (Pereira et al., 2017). They are an important in the assessment of the territory and implementation of sustainable measures in urban areas, agriculture, forests, ecosystem services, among others. Soil maps represent an important basis for the evaluation and restoration of degraded areas, an important issue for our society, as consequence of climate change and the increasing pressure of humans on the ecosystems (Brevik et al. 2016; Depellegrin et al., 2016). The understanding of soil spatial variability and the phenomena that influence this dynamic is crucial to the implementation of sustainable practices that prevent degradation, and decrease the economic costs of soil restoration. In this context, soil maps and models are important to identify areas affected by degradation and optimize the resources available to restore them. Overall, soil data alone or integrated with data from other sciences, is an important part of sustainable land management. This information is extremely important land managers and decision maker's implements sustainable land management policies. The objective of this work is to present a review about the advantages of soil mapping and process modeling for sustainable land management. References Brevik, E., Calzolari, C., Miller, B., Pereira, P., Kabala, C., Baumgarten, A., Jordán, A. (2016) Historical perspectives and future needs in soil mapping, classification and pedological modelling, Geoderma, 264, Part B, 256-274. Depellegrin, D.A., Pereira, P., Misiune, I., Egarter-Vigl, L. (2016) Mapping Ecosystem Services in Lithuania. International Journal of Sustainable Development and World Ecology, 23, 441-455. Pereira, P., Brevik, E., Munoz-Rojas, M., Miller, B., Smetanova, A., Depellegrin, D., Misiune, I., Novara, A., Cerda, A. (2017) Soil mapping and process modelling for sustainable land management. In: Pereira, P., Brevik, E., Munoz-Rojas, M., Miller, B

  9. An Approach for Calculating Land Valuation by Using Inspire Data Models

    Science.gov (United States)

    Aydinoglu, A. C.; Bovkir, R.

    2017-11-01

    Land valuation is a highly important concept for societies and governments have always emphasis on the process especially for taxation, expropriation, market capitalization and economic activity purposes. To success an interoperable and standardised land valuation, INSPIRE data models can be very practical and effective. If data used in land valuation process produced in compliance with INSPIRE specifications, a reliable and effective land valuation process can be performed. In this study, possibility of the performing land valuation process with using the INSPIRE data models was analysed and with the help of Geographic Information Systems (GIS) a case study in Pendik was implemented. For this purpose, firstly data analysis and gathering was performed. After, different data structures were transformed according to the INSPIRE data model requirements. For each data set necessary ETL (Extract-Transform-Load) tools were produced and all data transformed according to the target data requirements. With the availability and practicability of spatial analysis tools of GIS software, land valuation calculations were performed for study area.

  10. Assessing Independent Variables Used in Econometric Modeling Forest Land Use or Land Cover Change: A Meta-Analysis

    Directory of Open Access Journals (Sweden)

    James A. Jeuck

    2014-07-01

    Full Text Available We conducted a meta-analysis on 64 econometric models from 47 studies predicting forestland conversion to agriculture (F2A, forestland to development (F2D, forestland to non-forested (F2NF and undeveloped (including forestland to developed (U2D land. Over 250 independent econometric variables were identified from 21 F2A models, 21 F2D models, 12 F2NF models, and 10 U2D models. These variables were organized into a hierarchy of 119 independent variable groups, 15 categories, and 4 econometric drivers suitable for conducting simple vote count statistics. Vote counts were summarized at the independent variable group level and formed into ratios estimating the predictive success of each variable group. Two ratios estimates were developed based on (1 proportion of times the independent variables had statistical significance and (2 proportion of times independent variables met the original study authors’ expectations. In F2D models, we confirmed the success of popular independent variables such as population, income, and urban proximity estimates but found timber rents and site productivity variables less successful. In F2A models, we confirmed success of popular explanatory variables such as forest and agricultural rents and costs, governmental programs, and site quality, but we found population, income, and urban proximity estimates less successful. In U2D models, successful independent variables found were urban rents and costs, zoning issues concerning forestland loss, site quality, urban proximity, population, and income. In F2NF models, we found poor success using timber rents but high success using agricultural rents, site quality, population, and income. Success ratios and discussion of new or less popular, but promising, variables was also included. This meta-analysis provided insight into the general success of econometric independent variables for future forest-use or -cover change research.

  11. Hydro-Meteorological Hazards Assessment Based Upon Climate Change Considerations in Isfara Basin

    Science.gov (United States)

    Ramesh, Azadeh; Conrad, Christopher; Mannig, Birgit; Schrader, Frank

    2013-04-01

    Central Asia is highly exposed and vulnerable to hydro-meteorological hazards and presents a constant threat to the population, in particular with flood and mudflow as frequent events in this region. Annual floods and mudflows cause enormous economic and social affects e.g. damages on houses and infrastructure in the floodplains, agricultural production particularly for water control (channels, bridges, etc.). An important challenge for the assessment of hydro-meteorological hazards is climate change, which is altering exposure. In the framework of the Trans-boundary Water Management in Central Asia/WMBOCA project, supported by TWM-CA and CAWa projects of German Research Centre for Geosciences (GFZ) and German Aerospace Center (DLR), we developed an approach how to address flood and mudflow using the official sources have been performed for selected areas in Central Asia based upon climate change considerations. This research has been carried out for the Isfara River basin which is located in northern Tajikistan and south-western Kyrgyzstan. The Isfara River basin belongs to Sugdh Oblast in Tajikistan and to Batken Oblast in Kyrgyzstan. The study begins with a description of the employed sources and methodology. The ensuing section offers analysis of exposure to hydro-meteorological hazards. Then, the study covers an overview of work related to the analysis of changes in mudflow and flood hazards in the past 20 years. Additionally, exposure to hydro-meteorological hazards in the case study has been assessed against a backdrop of rising climate change and variability for year 2050. This study presents initial findings from these analyses which are including (a) mapping of previous floods and mudflows in the basin, using conventional and traditional sources, supported remote sensing tools, (b) forecast of floods and mudflows in the basin, based upon climate change scenarios, and finally (c) supporting the local authorities and administrations in consideration of

  12. 2016 International Land Model Benchmarking (ILAMB) Workshop Report

    Energy Technology Data Exchange (ETDEWEB)

    Hoffman, Forrest M. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Koven, Charles D. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Keppel-Aleks, Gretchen [Univ. of Michigan, Ann Arbor, MI (United States); Lawrence, David M. [National Center for Atmospheric Research, Boulder, CO (United States); Riley, William J. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Randerson, James T. [Univ. of California, Irvine, CA (United States); Ahlström, Anders [Stanford Univ., Stanford, CA (United States); Lund Univ., Lund (Sweden); Abramowitz, Gabriel [Univ. of New South Wales, Sydney, NSW (Australia); Baldocchi, Dennis D. [Univ. of California, Berkeley, CA (United States); Best, Martin J. [UK Met Office, Exeter, EX1 3PB (United Kingdom); Bond-Lamberty, Benjamin [Joint Global Change Research Institute, Pacific Northwest National Lab. (PNNL), College Park, MD (United States); De Kauwe, Martin G. [Macquarie Univ., NSW (Australia); Denning, A. Scott [Colorado State Univ., Fort Collins, CO (United States); Desai, Ankur R. [Univ. of Wisconsin, Madison, WI (United States); Eyring, Veronika [Deutsches Zentrum fuer Luft- und Raumfahrt (DLR), Oberpfaffenhofen (Germany); Fisher, Joshua B. [California Inst. of Technology (CalTech), Pasadena, CA (United States). Jet Propulsion Lab.; Fisher, Rosie A. [National Center for Atmospheric Research, Boulder, CO (United States); Gleckler, Peter J. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Huang, Maoyi [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Hugelius, Gustaf [Stockholm Univ. (Sweden); Jain, Atul K. [Univ. of Illinois, Urbana, IL (United States); Kiang, Nancy Y. [NASA Goddard Institute for Space Studies, Columbia Univ., New York, NY (United States); Kim, Hyungjum [University of Tokyo, Bunkyo-ku, Tokyo (Japan); Koster, Randal D. [NASA Goddard Space Flight Center (GSFC), Greenbelt, MD (United States); Kumar, Sujay V. [NASA Goddard Space Flight Center (GSFC), Greenbelt, MD (United States); Li, Hongyi [Tsinghua Univ., Beijing (China). Dept. of Hydraulic Engineering; Luo, Yiqi [Univ. of Oklahoma, Norman, OK (United States); Mao, Jiafu [Univ. of Illinois at Urbana-Champaign, Urbana, IL (United States); McDowell, Nathan G. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Mishra, Umakant [Argonne National Lab. (ANL), Argonne, IL (United States); Moorcroft, Paul R. [Harvard Univ., Cambridge, MA (United States); Pau, George S.H. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Ricciuto, Daniel M. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Schaefer, Kevin [Univ. of Colorado, Boulder, CO (United States). National Snow and Ice Data Center, Cooperative Institute for Research in Environmental Sciences; Schwalm, Christopher R. [Woods Hole Research Center, Falmouth, MA (United States); Serbin, Shawn P. [Brookhaven National Lab. (BNL), Upton, NY (United States); Shevliakova, Elena [Geophysical Fluid Dynamics Laboratory, Princeton Univ., Princeton, NJ (United States); Slater, Andrew G. [Univ. of Colorado, Boulder, CO (United States). National Snow and Ice Data Center, Cooperative Institute for Research in Environmental Sciences; Tang, Jinyun [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Williams, Mathew [Univ. of Edinburgh, Scotland (United Kingdom). School of GeoSciences and NERC National Centre for Earth Observation; Xia, Jianyang [Univ. of Oklahoma, Norman, OK (United States); East China Normal Univ. (ECNU), Shanghai (China). Tiantong National Forest Ecosystem Observation and Research Station, School of Ecological and Environmental Sciences; Xu, Chonggang [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Joseph, Renu [US Department of Energy, Germantown, MD (United States); Koch, Dorothy [US Department of Energy, Germantown, MD (United States)

    2017-04-01

    As Earth system models become increasingly complex, there is a growing need for comprehensive and multi-faceted evaluation of model projections. To advance understanding of biogeochemical processes and their interactions with hydrology and climate under conditions of increasing atmospheric carbon dioxide, new analysis methods are required that use observations to constrain model predictions, inform model development, and identify needed measurements and field experiments. Better representations of biogeochemistry–climate feedbacks and ecosystem processes in these models are essential for reducing uncertainties associated with projections of climate change during the remainder of the 21st century.

  13. 2016 International Land Model Benchmarking (ILAMB) Workshop Report

    Science.gov (United States)

    Hoffman, Forrest M.; Koven, Charles D.; Keppel-Aleks, Gretchen; Lawrence, David M.; Riley, William J.; Randerson, James T.; Ahlstrom, Anders; Abramowitz, Gabriel; Baldocchi, Dennis D.; Best, Martin J.; hide

    2016-01-01

    As earth system models (ESMs) become increasingly complex, there is a growing need for comprehensive and multi-faceted evaluation of model projections. To advance understanding of terrestrial biogeochemical processes and their interactions with hydrology and climate under conditions of increasing atmospheric carbon dioxide, new analysis methods are required that use observations to constrain model predictions, inform model development, and identify needed measurements and field experiments. Better representations of biogeochemistryclimate feedbacks and ecosystem processes in these models are essential for reducing the acknowledged substantial uncertainties in 21st century climate change projections.

  14. Asteroid modeling for testing spacecraft approach and landing.

    Science.gov (United States)

    Martin, Iain; Parkes, Steve; Dunstan, Martin; Rowell, Nick

    2014-01-01

    Spacecraft exploration of asteroids presents autonomous-navigation challenges that can be aided by virtual models to test and develop guidance and hazard-avoidance systems. Researchers have extended and applied graphics techniques to create high-resolution asteroid models to simulate cameras and other spacecraft sensors approaching and descending toward asteroids. A scalable model structure with evenly spaced vertices simplifies terrain modeling, avoids distortion at the poles, and enables triangle-strip definition for efficient rendering. To create the base asteroid models, this approach uses two-phase Poisson faulting and Perlin noise. It creates realistic asteroid surfaces by adding both crater models adapted from lunar terrain simulation and multiresolution boulders. The researchers evaluated the virtual asteroids by comparing them with real asteroid images, examining the slope distributions, and applying a surface-relative feature-tracking algorithm to the models.

  15. An integrated computer modeling environment for regional land use, air quality, and transportation planning

    Energy Technology Data Exchange (ETDEWEB)

    Hanley, C.J. [Sandia National Labs., Albuquerque, NM (United States); Marshall, N.L. [Resource Systems Group, Inc., White River Junction, VT (United States)

    1997-04-01

    The Land Use, Air Quality, and Transportation Integrated Modeling Environment (LATIME) represents an integrated approach to computer modeling and simulation of land use allocation, travel demand, and mobile source emissions for the Albuquerque, New Mexico, area. This environment provides predictive capability combined with a graphical and geographical interface. The graphical interface shows the causal relationships between data and policy scenarios and supports alternative model formulations. Scenarios are launched from within a Geographic Information System (GIS), and data produced by each model component at each time step within a simulation is stored in the GIS. A menu-driven query system is utilized to review link-based results and regional and area-wide results. These results can also be compared across time or between alternative land use scenarios. Using this environment, policies can be developed and implemented based on comparative analysis, rather than on single-step future projections. 16 refs., 3 figs., 2 tabs.

  16. An Integrated Software Framework to Support Semantic Modeling and Reasoning of Spatiotemporal Change of Geographical Objects: A Use Case of Land Use and Land Cover Change Study

    OpenAIRE

    Wenwen Li; Xiran Zhou; Sheng Wu

    2016-01-01

    Evolving Earth observation and change detection techniques enable the automatic identification of Land Use and Land Cover Change (LULCC) over a large extent from massive amounts of remote sensing data. It at the same time poses a major challenge in effective organization, representation and modeling of such information. This study proposes and implements an integrated computational framework to support the modeling, semantic and spatial reasoning of change information with regard to space, ti...

  17. Refining multi-model projections of temperature extremes by evaluation against land-atmosphere coupling diagnostics

    Science.gov (United States)

    Sippel, Sebastian; Zscheischler, Jakob; Mahecha, Miguel D.; Orth, Rene; Reichstein, Markus; Vogel, Martha; Seneviratne, Sonia I.

    2017-05-01

    The Earth's land surface and the atmosphere are strongly interlinked through the exchange of energy and matter. This coupled behaviour causes various land-atmosphere feedbacks, and an insufficient understanding of these feedbacks contributes to uncertain global climate model projections. For example, a crucial role of the land surface in exacerbating summer heat waves in midlatitude regions has been identified empirically for high-impact heat waves, but individual climate models differ widely in their respective representation of land-atmosphere coupling. Here, we compile an ensemble of 54 combinations of observations-based temperature (T) and evapotranspiration (ET) benchmarking datasets and investigate coincidences of T anomalies with ET anomalies as a proxy for land-atmosphere interactions during periods of anomalously warm temperatures. First, we demonstrate that a large fraction of state-of-the-art climate models from the Coupled Model Intercomparison Project (CMIP5) archive produces systematically too frequent coincidences of high T anomalies with negative ET anomalies in midlatitude regions during the warm season and in several tropical regions year-round. These coincidences (high T, low ET) are closely related to the representation of temperature variability and extremes across the multi-model ensemble. Second, we derive a land-coupling constraint based on the spread of the T-ET datasets and consequently retain only a subset of CMIP5 models that produce a land-coupling behaviour that is compatible with these benchmark estimates. The constrained multi-model simulations exhibit more realistic temperature extremes of reduced magnitude in present climate in regions where models show substantial spread in T-ET coupling, i.e. biases in the model ensemble are consistently reduced. Also the multi-model simulations for the coming decades display decreased absolute temperature extremes in the constrained ensemble. On the other hand, the differences between projected

  18. Recent Advances in Modeling of the Atmospheric Boundary Layer and Land Surface in the Coupled WRF-CMAQ Model

    Science.gov (United States)

    Advances in the land surface model (LSM) and planetary boundary layer (PBL) components of the WRF-CMAQ coupled meteorology and air quality modeling system are described. The aim of these modifications was primarily to improve the modeling of ground level concentrations of trace c...

  19. Coupling the land surface model NOAHMP with the generic crop growth model GECROS: Model calibration and validation

    Science.gov (United States)

    Ingwersen, Joachim; Högy, Petra; Wizemann, Hans-Dieter; Streck, Thilo

    2017-04-01

    Weather and climate simulations depend on an accurate description of the exchange of water, energy and momentum between land surface and atmosphere. In state-of-the-art land surface models the vegetation dynamics is "frozen" that means prescribed in lookup tables. As a consequence growth and development of a crop is independent from the prevailing weather conditions, and an important feedback between atmosphere and land surface is not captured. In the present study we coupled the land surface model NOAHMP with the mechanistic generic crop growth model GECROS. On the basis of a comprehensive 5-year dataset on eddy covariance energy- and water fluxes and soil water and crop data from two different climate regions of Southwest Germany, we adapted the crop growth model GECROS, integrated it with NOAHMP, calibrated the coupled model for winter wheat and silage maize and tested its robustness in multiple-year validation runs against independent measurements. For winter wheat the model performed well both for the calibration and validation phase. Inter-annual and regional differences in crop development due to temperature anomalies were well reproduced by the model. Also the decline of evapotranspiration over the maturing phase was properly simulated. In case of maize the model performed not as good as for winter wheat. We attribute this somewhat lower model performance to the pronounced differences among maize cultivars, the high sensitivity of maize development to drill and emergence date, and its higher susceptibility to early summer droughts. Moreover, the model systematically overestimated evapotranspiration during long lasting droughts like in June 2014 indicating that in the current state NOAHMP-GECROS has some limitations in simulating water stress. We attribute this weakness to the uniform root distribution and the hydraulic functions (Clapp-Hornberger) that are implemented in NOAHMP which result in a uniform depletion of the soil water profile. The novel model

  20. Geostatistics and Hydrology : Part 3: Hydro-Meteorological Network Design

    NARCIS (Netherlands)

    Van Dijk, M.J.; Rientjes, T.H.M.

    1994-01-01

    At present, the collection of environmental information is increasing in importance. Environmental modelling and defining measures relating to environmental protection policies are usually taken on the basis of the collected information. Especially in the more developed countries, hydrologists and

  1. Application of the Land Administration Domain Model to the City of ...

    African Journals Online (AJOL)

    ISO) late in 2012 as an International Standard for modelling basic land administration (LA) information. The LADM aims to provide a common vocabulary within the LA domain. This research examined the core data model of CoJLIS against the ...

  2. GIS based generation of dynamic hydrological and land patch simulation models for rural watershed areas

    Directory of Open Access Journals (Sweden)

    M. Varga

    2016-03-01

    Full Text Available This paper introduces a GIS based methodology to generate dynamic process model for the simulation based analysis of a sensitive rural watershed. The Direct Computer Mapping (DCM based solution starts from GIS layers and, via the graph interpretation and graphical edition of the process network, the expert interface is able to integrate the field experts’ knowledge in the computer aided generation of the simulation model. The methodology was applied and tested for the Southern catchment basin of Lake Balaton, Hungary. In the simplified hydrological model the GIS description of nine watercourses, 121 water sections, 57 small lakes and 20 Lake Balaton compartments were mapped through the expert interface to the dynamic databases of the DCM model. The hydrological model involved precipitation, evaporation, transpiration, runoff, infiltration. The COoRdination of INformation on the Environment (CORINE land cover based simplified “land patch” model considered the effect of meteorological and hydrological scenarios on freshwater resources in the land patches, rivers and lakes. The first results show that the applied model generation methodology helps to build complex models, which, after validation can support the analysis of various land use, with the consideration of environmental aspects.

  3. Soft landing on an irregular shape asteroid using Multiple-Horizon Multiple-Model Predictive Control

    Science.gov (United States)

    AlandiHallaj, MohammadAmin; Assadian, Nima

    2017-11-01

    This study has introduced a predictive framework including a heuristic guidance law named Predictive Path Planning and Multiple-Horizon Multiple-Model Predictive Control as the control scheme for soft landing on an irregular-shaped asteroid. The dynamical model of spacecraft trajectory around an asteroid is introduced. The reference-landing trajectory is generated using Predictive Path Planning. Not only does the presented guidance law satisfy the collision avoidance constraint, but also guarantees the landing accuracy and vertical landing condition. Multiple-Horizon Multiple-Model Predictive Control is employed to make the spacecraft track the designed reference trajectory. The proposed control approach, which is a Model Predictive Control scheme, utilizes several prediction models instead of one. In this manner, it heritages the advantages of optimality and tackling external disturbances and model uncertainties from classical Model Predictive Control and at the same time has the advantage of lower computational burden than Model Predictive Control. Finally, numerical simulations are carried out to demonstrate the feasibility and effectiveness of the proposed control approach in achieving the desired conditions in presence of uncertainties and disturbances.

  4. A national fine spatial scale land-use regression model for ozone

    NARCIS (Netherlands)

    Kerckhoffs, Jules|info:eu-repo/dai/nl/411260502; Wang, Meng|info:eu-repo/dai/nl/345480279; Meliefste, Kees; Malmqvist, Ebba; Fischer, Paul; Janssen, Nicole A H; Beelen, Rob|info:eu-repo/dai/nl/30483100X; Hoek, Gerard|info:eu-repo/dai/nl/069553475

    Uncertainty about health effects of long-term ozone exposure remains. Land use regression (LUR) models have been used successfully for modeling fine scale spatial variation of primary pollutants but very limited for ozone. Our objective was to assess the feasibility of developing a national LUR

  5. Carbon emission and sequestration by agricultural land use : a model study for Europe

    NARCIS (Netherlands)

    Vleeshouwers, L.M.; Verhagen, A.

    2002-01-01

    A model was developed to calculate carbon fluxes from agricultural soils. The model includes the effects of crop (species, yield and rotation), climate (temperature, rainfall and evapotranspiration) and soil (carbon content and water retention capacity) on the carbon budget of agricultural land. The

  6. Aggregation of spatial units in linear programming models to explore land use options.

    NARCIS (Netherlands)

    Hijmans, R.J.; Ittersum, van M.K.

    1996-01-01

    Consequences of aggregating spatial units in an interactive multiple-goal linear programming (IMGLP) model are analysed for a schematized and an existing IMGLP model (GOAL) exploring land use options for the European Union. A discrimination was made between effects on objective functions for the

  7. A hierarchical updating method for finite element model of airbag buffer system under landing impact

    Directory of Open Access Journals (Sweden)

    He Huan

    2015-12-01

    Full Text Available In this paper, we propose an impact finite element (FE model for an airbag landing buffer system. First, an impact FE model has been formulated for a typical airbag landing buffer system. We use the independence of the structure FE model from the full impact FE model to develop a hierarchical updating scheme for the recovery module FE model and the airbag system FE model. Second, we define impact responses at key points to compare the computational and experimental results to resolve the inconsistency between the experimental data sampling frequency and experimental triggering. To determine the typical characteristics of the impact dynamics response of the airbag landing buffer system, we present the impact response confidence factors (IRCFs to evaluate how consistent the computational and experiment results are. An error function is defined between the experimental and computational results at key points of the impact response (KPIR to serve as a modified objective function. A radial basis function (RBF is introduced to construct updating variables for a surrogate model for updating the objective function, thereby converting the FE model updating problem to a soluble optimization problem. Finally, the developed method has been validated using an experimental and computational study on the impact dynamics of a classic airbag landing buffer system.

  8. Air pollution dispersion model in Prague - land development plan modelling of the year 2010

    Energy Technology Data Exchange (ETDEWEB)

    Hornicek, K. [Road and Motorway Directorate (Czech Republic)

    2000-07-01

    motorways. The GIS presentation of the model play important role in process of a land development plan and it creates a tool how to present the main impacts on ambitious city development. The fact, that the Prague municipality has accepted Prague land development plan in September 1999 was thanks to number of similar models, which helped to show impacts coming from different human activities. (authors)

  9. Watershed Models for Predicting Nitrogen Loads from Artificially Drained Lands

    Science.gov (United States)

    R. Wayne Skaggs; George M. Chescheir; Glenn Fernandez; Devendra M. Amatya

    2003-01-01

    Non-point sources of pollutants originate at the field scale but water quality problems usually occur at the watershed or basin scale. This paper describes a series of models developed for poorly drained watersheds. The models use DRAINMOD to predict hydrology at the field scale and a range of methods to predict channel hydraulics and nitrogen transport. In-stream...

  10. Land-cover in Watershed Models for Western Ghats

    Indian Academy of Sciences (India)

    6

    the models quoted by the Central Water Commission (CWC, 2010) in its 'State of the art report' and hence can be considered to be one accepted for general application for estimation of runoff. Hence, the present work is .... purpose, the NITK model is applied on three catchments for which reliable runoff values is available.

  11. Bus Lifecycle Cost Model for Federal Land Management Agencies.

    Science.gov (United States)

    2011-09-30

    The Bus Lifecycle Cost Model is a spreadsheet-based planning tool that estimates capital, operating, and maintenance costs for various bus types over the full lifecycle of the vehicle. The model is based on a number of operating characteristics, incl...

  12. Nonlinear modeling of adaptive magnetorheological landing gear dampers under impact conditions

    Science.gov (United States)

    Ahuré Powell, Louise A.; Choi, Young T.; Hu, Wei; Wereley, Norman M.

    2016-11-01

    Adaptive landing gear dampers that can continuously adjust their stroking load in response to various operating conditions have been investigated for improving the landing performance of a lightweight helicopter. In prior work, adaptive magnetorheological (MR) landing gear dampers that maintained a constant peak stroking force of 4000 lbf across sink rates ranging from 6 to 12 ft s‑1 were designed, fabricated and successfully tested. In this follow-on effort, it is desired to expand the high end of the sink rate range to hold the peak stroking load constant for sink rates ranging from 6 to 26 ft s‑1, thus extending the high end of the speed range from 12 (in the first study) to 26 ft s‑1. To achieve this increase, a spring-based relief valve MR landing gear damper was developed. In order to better understand the MR landing gear damper behavior, a modified nonlinear Bingham Plastic model was formulated, and it incorporates Darcy friction, viscous forces across the MR and relief valves to better account for the damper force behavior at higher speeds. In addition, gas pressure inside the MR damper piston is considered so the total damper force includes a gas force. The MR landing gear damper performance is characterized using drop tests, and the experiments are used to validate model predictions data at low and high nominal impact speeds up to 26 ft s‑1 (shaft velocity of 9.6 ft s‑1).

  13. Land-Surface Modeling and Climate Simulations: Results over the Autstralian Region from Sixteen AMIP2 Models

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, H; Henderson-Sellers, A; Irannejad, P; Sharmeen, S; Phillips, T; McGuffie, K

    2002-05-02

    This report presents analyses of sixteen models from the Atmospheric Model Intercomparison Project II (AMIP2) over the Australian region. It is focused on assessing how well surface climate and fluxes over this region are simulated in current Atmospheric General Circulation Models (AGCMs) forced by observed sea surface temperatures (SSTs). The importance of land-surface modeling on model predictability is also investigated. In this preliminary analysis, the Bureau of Meteorology (BoM) observational rainfall, temperature and surface evapotranspiration datasets are used in validating surface climatologies simulated by the 16 models. Specifically, the Linear Error in Probability Space (LEPS) score is calculated in assessing the skill of the models in simulating surface Climate anomalies for the 17-year period (1979 to 1995). Numerous model differences are seen with some aspects of the model performance being linked to the complexity of land-surface schemes used. The connection between model skill in simulating surface climate anomalies and surface flux anomalies is explored. Lag-correlation analysis is conducted. Results reveal that ''climatic memory'' derived from land-surface processes (e.g: soil moisture) has different features in the sixteen models: some models show rapid feedback processes between land-surface and the overlying atmosphere, while others show slowly varying processes in which anomalous surface conditions have impacts on the model integrations on longer time-scales. It is found that models with simple bucket-type scheme tend to have a more rapid decay rate in the retention of soil moisture anomalies, and therefore, soil moisture conditions have a much weaker influence on forecasting surface climate anomalies. This study suggests that land-surface modeling has the potential to influence AGCM predictability on seasonal and even longer time scales.

  14. Spatial Predictive Modeling and Remote Sensing of Land Use Change in the Chesapeake Bay Watershed

    Science.gov (United States)

    Goetz, Scott J.; Bockstael, Nancy E.; Jantz, Claire A.

    2005-01-01

    This project was focused on modeling the processes by which increasing demand for developed land uses, brought about by changes in the regional economy and the socio-demographics of the region, are translated into a changing spatial pattern of land use. Our study focused on a portion of the Chesapeake Bay Watershed where the spatial patterns of sprawl represent a set of conditions generally prevalent in much of the U.S. Working in the region permitted us access to (i) a time-series of multi-scale and multi-temporal (including historical) satellite imagery and (ii) an established network of collaborating partners and agencies willing to share resources and to utilize developed techniques and model results. In addition, a unique parcel-level tax assessment database and linked parcel boundary maps exists for two counties in the Maryland portion of this region that made it possible to establish a historical cross-section time-series database of parcel level development decisions. Scenario analyses of future land use dynamics provided critical quantitative insight into the impact of alternative land management and policy decisions. These also have been specifically aimed at addressing growth control policies aimed at curbing exurban (sprawl) development. Our initial technical approach included three components: (i) spatial econometric modeling of the development decision, (ii) remote sensing of suburban change and residential land use density, including comparisons of past change from Landsat analyses and more traditional sources, and (iii) linkages between the two through variable initialization and supplementation of parcel level data. To these we added a fourth component, (iv) cellular automata modeling of urbanization, which proved to be a valuable addition to the project. This project has generated both remote sensing and spatially explicit socio-economic data to estimate and calibrate the parameters for two different types of land use change models and has

  15. Dynamic model and performance analysis of landing buffer for bionic locust mechanism

    Science.gov (United States)

    Chen, Dian-Sheng; Zhang, Zi-Qiang; Chen, Ke-Wei

    2016-06-01

    The landing buffer is an important problem in the research on bionic locust jumping robots, and the different modes of landing and buffering can affect the dynamic performance of the buffering process significantly. Based on an experimental observation, the different modes of landing and buffering are determined, which include the different numbers of landing legs and different motion modes of legs in the buffering process. Then a bionic locust mechanism is established, and the springs are used to replace the leg muscles to achieve a buffering effect. To reveal the dynamic performance in the buffering process of the bionic locust mechanism, a dynamic model is established with different modes of landing and buffering. In particular, to analyze the buffering process conveniently, an equivalent vibration dynamic model of the bionic locust mechanism is proposed. Given the support forces of the ground to the leg links, which can be obtained from the dynamic model, the spring forces of the legs and the impact resistance of each leg are the important parameters affecting buffering performance, and evaluation principles for buffering performance are proposed according to the aforementioned parameters. Based on the dynamic model and these evaluation principles, the buffering performances are analyzed and compared in different modes of landing and buffering on a horizontal plane and an inclined plane. The results show that the mechanism with the ends of the legs sliding can obtain a better dynamic performance. This study offers primary theories for buffering dynamics and an evaluation of landing buffer performance, and it establishes a theoretical basis for studies and engineering applications.

  16. Do Land Markets Matter? A Modeling Ontology and Experimental Design to Test the Effects of Land Markets for an Agent-based Model of Ex-urban Residential Land-use Change.

    NARCIS (Netherlands)

    Parker, D.C.; Brown, D.G.; Filatova, Tatiana; Riolo, R.; Robinson, D.T.; Sun, S.; Heppenstall, A.J.; Crooks, A.T.; See, L.M.; Batty, M.

    2012-01-01

    Urban sprawl is shaped by various geographical, ecological and social factors under the influence of land market forces. When modeling this process, geographers and economists tend to prioritize factors most relevant to their own domain. Still, there are very few structured systematic comparisons

  17. Environmental modelling of use of treated organic waste on agricultural land

    DEFF Research Database (Denmark)

    Hansen, Trine Lund; Christensen, Thomas Højlund; Schmidt, S.

    2006-01-01

    assessment of environmental effects from land application of treated organic MSW: DST (Decision Support Tool, USA), IWM (Integrated Waste Management, UK), THE IFEU PROJECT (Germany), ORWARE (ORganic WAste REsearch, Sweden) and EASEWASTE (Environmental Assessment of Solid Waste Systems and Technologies......, Denmark). DST and IWM are life cycle inventory (LCI) models, thus not performing actual impact assessment. The DST model includes only one water emission (biological oxygen demand) from compost leaching in the results and IWM considers only air emissions from avoided production of commercial fertilizers....... THE IFEU PROJECT, ORWARE and EASEWASTE are life cycle assessment (LCA) models containing more detailed land application modules. A case study estimating the environmental impacts from land application of 1 ton of composted source sorted organic household waste was performed to compare the results from...

  18. Simulation of Urban Heat Island Mitigation Strategies in Atlanta, GA Using High-Resolution Land Use/Land Cover Data Set to Enhance Meteorological Modeling

    Science.gov (United States)

    Crosson, William L.; Dembek, Scott; Estes, Maurice G., Jr.; Limaye, Ashutosh S.; Lapenta, William; Quattrochi, Dale A.; Johnson, Hoyt; Khan, Maudood

    2006-01-01

    The specification of land use/land cover (LULC) and associated land surface parameters in meteorological models at all scales has a major influence on modeled surface energy fluxes and boundary layer states. In urban areas, accurate representation of the land surface may be even more important than in undeveloped regions due to the large heterogeneity within the urban area. Deficiencies in the characterization of the land surface related to the spatial or temporal resolution of the data, the number of LULC classes defined, the accuracy with which they are defined, or the degree of heterogeneity of the land surface properties within each class may degrade the performance of the models. In this study, an experiment was conducted to test a new high-resolution LULC data set for meteorological simulations for the Atlanta, Georgia metropolitan area using a mesoscale meteorological model and to evaluate the effects of urban heat island (UHI) mitigation strategies on modeled meteorology for 2030. Simulation results showed that use of the new LULC data set reduced a major deficiency of the land use data used previously, specifically the poor representation of urban and suburban land use. Performance of the meteorological model improved substantially, with the overall daytime cold bias reduced by over 30%. UHI mitigation strategies were projected to offset much of a predicted urban warming between 2000 and 2030. In fact, for the urban core, the cooling due to UHI mitigation strategies was slightly greater than the warming associated with urbanization over this period. For the larger metropolitan area, cooling only partially offset the projected warming trend.

  19. WASCAL - West African Science Service Center on Climate Change and Adapted Land Use Regional Climate Simulations and Land-Atmosphere Simulations for West Africa at DKRZ and elsewhere

    Science.gov (United States)

    Hamann, Ilse; Arnault, Joel; Bliefernicht, Jan; Klein, Cornelia; Heinzeller, Dominikus; Kunstmann, Harald

    2014-05-01

    Changing climate and hydro-meteorological boundary conditions are among the most severe challenges to Africa in the 21st century. In particular West Africa faces an urgent need to develop effective adaptation and mitigation strategies to cope with negative impacts on humans and environment due to climate change, increased hydro-meteorological variability and land use changes. To help meet these challenges, the German Federal Ministry of Education and Research (BMBF) started an initiative with institutions in Germany and West African countries to establish together a West African Science Service Center on Climate Change and Adapted Land Use (WASCAL). This activity is accompanied by an establishment of trans-boundary observation networks, an interdisciplinary core research program and graduate research programs on climate change and related issues for strengthening the analytical capabilities of the Science Service Center. A key research activity of the WASCAL Competence Center is the provision of regional climate simulations in a fine spatio-temporal resolution for the core research sites of WASCAL for the present and the near future. The climate information is needed for subsequent local climate impact studies in agriculture, water resources and further socio-economic sectors. The simulation experiments are performed using regional climate models such as COSMO-CLM, RegCM and WRF and statistical techniques for a further refinement of the projections. The core research sites of WASCAL are located in the Sudanian Savannah belt in Northern Ghana, Southern Burkina Faso and Northern Benin. The climate in this region is semi-arid with six rainy months. Due to the strong population growth in West Africa, many areas of the Sudanian Savannah have been already converted to farmland since the majority of the people are living directly or indirectly from the income produced in agriculture. The simulation experiments of the Competence Center and the Core Research Program are

  20. Investigation on the Expansion of Urban Construction Land Use Based on the CART-CA Model

    Directory of Open Access Journals (Sweden)

    Yongxiang Yao

    2017-05-01

    Full Text Available Change in urban construction land use is an important factor when studying urban expansion. Many scholars have combined cellular automata (CA with data mining algorithms to perform relevant simulation studies. However, the parameters for rule extraction are difficult to determine and the rules are simplex, and together, these factors tend to introduce excessive fitting problems and low modeling accuracy. In this paper, we propose a method to extract the transformation rules for a CA model based on the Classification and Regression Tree (CART. In this method, CART is used to extract the transformation rules for the CA. This method first adopts the CART decision tree using the bootstrap algorithm to mine the rules from the urban land use while considering the factors that impact the geographic spatial variables in the CART regression procedure. The weights of individual impact factors are calculated to generate a logistic regression function that reflects the change in urban construction land use. Finally, a CA model is constructed to simulate and predict urban construction land expansion. The urban area of Xinyang City in China is used as an example for this experimental research. After removing the spatial invariant region, the overall simulation accuracy is 81.38% and the kappa coefficient is 0.73. The results indicate that by using the CART decision tree to train the impact factor weights and extract the rules, it can effectively increase the simulation accuracy of the CA model. From convenience and accuracy perspectives for rule extraction, the structure of the CART decision tree is clear, and it is very suitable for obtaining the cellular rules. The CART-CA model has a relatively high simulation accuracy in modeling urban construction land use expansion, it provides reliable results, and is suitable for use as a scientific reference for urban construction land use expansion.

  1. Spatial stochastic regression modelling of urban land use

    Science.gov (United States)

    Arshad, S. H. M.; Jaafar, J.; Abiden, M. Z. Z.; Latif, Z. A.; Rasam, A. R. A.

    2014-02-01

    Urbanization is very closely linked to industrialization, commercialization or overall economic growth and development. This results in innumerable benefits of the quantity and quality of the urban environment and lifestyle but on the other hand contributes to unbounded development, urban sprawl, overcrowding and decreasing standard of living. Regulation and observation of urban development activities is crucial. The understanding of urban systems that promotes urban growth are also essential for the purpose of policy making, formulating development strategies as well as development plan preparation. This study aims to compare two different stochastic regression modeling techniques for spatial structure models of urban growth in the same specific study area. Both techniques will utilize the same datasets and their results will be analyzed. The work starts by producing an urban growth model by using stochastic regression modeling techniques namely the Ordinary Least Square (OLS) and Geographically Weighted Regression (GWR). The two techniques are compared to and it is found that, GWR seems to be a more significant stochastic regression model compared to OLS, it gives a smaller AICc (Akaike's Information Corrected Criterion) value and its output is more spatially explainable.

  2. Specialization of the Land Administration Domain Model (LADM): An Option for Expanding the Legal Profiles

    OpenAIRE

    Paasch, J.; Van Oosterom, P.; Paulsson, J.; C. Lemmen

    2013-01-01

    The Land Administration Domain Model, LADM, passed on the 1st of November 2012 unanimously the final vote towards becoming an international standard, ISO 19152. Based on the standard this paper is a proposal for a more detailed classification of interests in land as modelled within LADM and an attempt to raise the awareness of the possibilities to further develop the LADM?s “right”, “restriction” and “responsibility” (RRR) classes. The current standardised classification of RRRs in the LADM i...

  3. Fuzzy Optimization of Option Pricing Model and Its Application in Land Expropriation

    Directory of Open Access Journals (Sweden)

    Aimin Heng

    2014-01-01

    Full Text Available Option pricing is irreversible, fuzzy, and flexible. The fuzzy measure which is used for real option pricing is a useful supplement to the traditional real option pricing method. Based on the review of the concepts of the mean and variance of trapezoidal fuzzy number and the combination with the Carlsson-Fuller model, the trapezoidal fuzzy variable can be used to represent the current price of land expropriation and the sale price of land on the option day. Fuzzy Black-Scholes option pricing model can be constructed under fuzzy environment and problems also can be solved and discussed through numerical examples.

  4. Effect of Load-Alleviating Structure on the Landing Behavior of a Reentry-Capsule Model

    Science.gov (United States)

    Hoffman, E. L.; McGhee, J. R.; Stubbs, S. M.

    1961-01-01

    Model tests have been made to determine the landing-impact characteristics of a parachute-supported reentry capsule that had a compliable metal structure as a load-alleviating device. A 1/6-scale dynamic model having compliable aluminum-alloy legs designed to give a low onset rate of acceleration on impact was tested at flight-path angles of 90 degrees (vertical) and 35 degrees, at a vertical velocity of 30 ft/sec (full scale), and at contact attitudes of 0 degrees and +/-30 degrees. Landings were made on concrete, sand, and water.

  5. Modeling Rainfall-Runoff Response to Land Use and Land Cover Change in Rwanda (1990–2016

    Directory of Open Access Journals (Sweden)

    Fidele Karamage

    2017-02-01

    Full Text Available Stormwater runoff poses serious environmental problems and public health issues in Rwanda, a tropical country that is increasingly suffering from severe floods, landslides, soil erosion and water pollution. Using the WetSpa Extension model, this study assessed the changes in rainfall runoff depth in Rwanda from 1990 to 2016 in response to precipitation and land use changes. Our results show that Rwanda has experienced a significant conversion of natural forest and grassland to cropland and built-up areas. During the period 1990–2016, 7090.02 km2 (64.5% and 1715.26 km2 (32.1% of forest and grassland covers were lost, respectively, while the cropland and built-up areas increased by 135.3% (8503.75 km2 and 304.3% (355.02 km2, respectively. According to our estimates, the land use change effect resulted in a national mean runoff depth increase of 2.33 mm/year (0.38%. Although precipitation change affected the inter-annual fluctuation of runoff, the long-term trend of runoff was dominated by land use change. The top five districts that experienced the annual runoff depth increase (all >3.8 mm/year are Rubavu, Nyabihu, Ngororero, Gakenke, and Musanze. Their annual runoff depths increased at a rate of >3.8 mm/year during the past 27 years, due to severe deforestation (ranging from 62% to 85% and cropland expansion (ranging from 123% to 293%. These areas require high priority in runoff control using terracing in croplands and rainwater harvesting systems such as dam/reservoirs, percolation tanks, storage tanks, etc. The wet season runoff was three times higher than the dry season runoff in Rwanda; appropriate rainwater management and reservation could provide valuable irrigation water for the dry season or drought years (late rainfall onsets or early rainfall cessations. It was estimated that a reservation of 30.5% (3.99 km3 of the runoff in the wet season could meet the cropland irrigation water gap during the dry season in 2016.

  6. Hydrologic models for land-atmosphere retrospective studies of the use of LANDSAT and AVHRR data

    Science.gov (United States)

    Duchon, Claude E.; Williams, T. H. Lee; Nicks, Arlin D.

    1988-01-01

    The use of a Geographic Information System (GIS) and LANDSAT analysis in conjunction with the Simulator for Water Resources on a Rural Basin (SWRRB) hydrologic model to examine the water balance on the Little Washita River basin is discussed. LANDSAT analysis was used to divide the basin into eight non-contiguous land covers or subareas: rangeland, grazed range, winter wheat, alfalfa/pasture, bare soil, water, woodland, and impervious land (roads, quarry). The use of a geographic information system allowed for the calculation of SWRRB model parameters in each subarea. Four data sets were constructed in order to compare SWRRB estimates of hydrologic processes using two methods of maximum LAI and two methods of watershed subdivision. Maximum LAI was determined from a continental scale map, which provided a value of 4.5 for the entire basin, and from its association with the type of land-cover (eight values). The two methods of watershed subdivision were determined according to drainage subbasin (four) and the eight land-covers. These data sets were used with the SWRRB model to obtain daily hydrologic estimates for 1985. The results of the one year analysis lead to the conclusion that the greater homogeneity of a land-cover subdivision provides better water yield estimates than those based on a drainage properties subdivision.

  7. Simulation of Land-Use Development, Using a Risk-Regarding Agent-Based Model

    Directory of Open Access Journals (Sweden)

    F. Hosseinali

    2012-01-01

    Full Text Available The aim of this paper is to study the spatial consequences of applying different Attitude Utility Functions (AUFs, which reflect peoples’ simplified psychological frames, to investment plans in land-use decision making. For this purpose, we considered and implemented an agent-based model with new methods for searching landscapes, for selecting parcels to develop, and for allowing competitions among agents. Besides this, GIS (Geographic Information Systems as a versatile and powerful medium of analyzing and representing spatial data is used. Our model is implemented on an artificial landscape in which land is being developed by agents. The agents are assumed to be mobile developers that are equipped with several land-related objectives. In this paper, agents mimic various risk-bearing attitudes and sometimes compete for developing the same parcel. The results reveal that patterns of land-use development are different in the two cases of regarding and disregarding AUFs. Therefore, it is considered here that using the attitudes of people towards risk helps the model to better simulate the decision making of land-use developers. The different attitudes toward risk used in this study can be attributed to different categories of developers based on sets of characteristics such as income, age, or education.

  8. NetLand: quantitative modeling and visualization of Waddington's epigenetic landscape using probabilistic potential.

    Science.gov (United States)

    Guo, Jing; Lin, Feng; Zhang, Xiaomeng; Tanavde, Vivek; Zheng, Jie

    2017-05-15

    Waddington's epigenetic landscape is a powerful metaphor for cellular dynamics driven by gene regulatory networks (GRNs). Its quantitative modeling and visualization, however, remains a challenge, especially when there are more than two genes in the network. A software tool for Waddington's landscape has not been available in the literature. We present NetLand, an open-source software tool for modeling and simulating the kinetic dynamics of GRNs, and visualizing the corresponding Waddington's epigenetic landscape in three dimensions without restriction on the number of genes in a GRN. With an interactive and graphical user interface, NetLand can facilitate the knowledge discovery and experimental design in the study of cell fate regulation (e.g. stem cell differentiation and reprogramming). NetLand can run under operating systems including Windows, Linux and OS X. The executive files and source code of NetLand as well as a user manual, example models etc. can be downloaded from http://netland-ntu.github.io/NetLand/ . zhengjie@ntu.edu.sg. Supplementary data are available at Bioinformatics online.

  9. Peak Vertical Ground Reaction Force during Two-Leg Landing: A Systematic Review and Mathematical Modeling

    Directory of Open Access Journals (Sweden)

    Wenxin Niu

    2014-01-01

    Full Text Available Objectives. (1 To systematically review peak vertical ground reaction force (PvGRF during two-leg drop landing from specific drop height (DH, (2 to construct a mathematical model describing correlations between PvGRF and DH, and (3 to analyze the effects of some factors on the pooled PvGRF regardless of DH. Methods. A computerized bibliographical search was conducted to extract PvGRF data on a single foot when participants landed with both feet from various DHs. An innovative mathematical model was constructed to analyze effects of gender, landing type, shoes, ankle stabilizers, surface stiffness and sample frequency on PvGRF based on the pooled data. Results. Pooled PvGRF and DH data of 26 articles showed that the square root function fits their relationship well. An experimental validation was also done on the regression equation for the medicum frequency. The PvGRF was not significantly affected by surface stiffness, but was significantly higher in men than women, the platform than suspended landing, the barefoot than shod condition, and ankle stabilizer than control condition, and higher than lower frequencies. Conclusions. The PvGRF and root DH showed a linear relationship. The mathematical modeling method with systematic review is helpful to analyze the influence factors during landing movement without considering DH.

  10. Sugarcane Land Classification with Satellite Imagery using Logistic Regression Model

    Science.gov (United States)

    Henry, F.; Herwindiati, D. E.; Mulyono, S.; Hendryli, J.

    2017-03-01

    This paper discusses the classification of sugarcane plantation area from Landsat-8 satellite imagery. The classification process uses binary logistic regression method with time series data of normalized difference vegetation index as input. The process is divided into two steps: training and classification. The purpose of training step is to identify the best parameter of the regression model using gradient descent algorithm. The best fit of the model can be utilized to classify sugarcane and non-sugarcane area. The experiment shows high accuracy and successfully maps the sugarcane plantation area which obtained best result of Cohen’s Kappa value 0.7833 (strong) with 89.167% accuracy.

  11. ICT approaches to integrating institutional and non-institutional data services for better understanding of hydro-meteorological phenomena

    Directory of Open Access Journals (Sweden)

    T. Bedrina

    2012-06-01

    Full Text Available It is widely recognised that an effective exploitation of Information and Communication Technologies (ICT is an enabling factor to achieve major advancements in Hydro-Meteorological Research (HMR. Recently, a lot of attention has been devoted to the use of ICT in HMR activities, e.g. in order to facilitate data exchange and integration, to improve computational capabilities and consequently model resolution and quality. Nowadays, ICT technologies have demonstrated that it is possible to extend monitoring networks by integrating sensors and other sources of data managed by volunteer's communities. These networks are constituted by peers that span a wide portion of the territory in many countries. The peers are "location aware" in the sense that they provide information strictly related with their geospatial location. The coverage of these networks, in general, is not uniform and the location of peers may follow random distribution. The ICT features used to set up the network are lightweight and user friendly, thus, permitting the peers to join the network without the necessity of specialised ICT knowledge. In this perspective it is of increasing interest for HMR activities to elaborate of Personal Weather Station (PWS networks, capable to provide almost real-time, location aware, weather data.

    Moreover, different big players of the web arena are now providing world-wide backbones, suitable to present on detailed map location aware information, obtained by mashing up data from different sources. This is the case, for example, with Google Earth and Google Maps.

    This paper presents the design of a mashup application aimed at aggregating, refining and visualizing near real-time hydro-meteorological datasets. In particular, we focused on the integration of instant precipitation depths, registered either by widespread semi-professional weather stations and official ones. This sort of information has high importance and usefulness in

  12. ICT approaches to integrating institutional and non-institutional data services for better understanding of hydro-meteorological phenomena

    Science.gov (United States)

    Bedrina, T.; Parodi, A.; Quarati, A.; Clematis, A.

    2012-06-01

    It is widely recognised that an effective exploitation of Information and Communication Technologies (ICT) is an enabling factor to achieve major advancements in Hydro-Meteorological Research (HMR). Recently, a lot of attention has been devoted to the use of ICT in HMR activities, e.g. in order to facilitate data exchange and integration, to improve computational capabilities and consequently model resolution and quality. Nowadays, ICT technologies have demonstrated that it is possible to extend monitoring networks by integrating sensors and other sources of data managed by volunteer's communities. These networks are constituted by peers that span a wide portion of the territory in many countries. The peers are "location aware" in the sense that they provide information strictly related with their geospatial location. The coverage of these networks, in general, is not uniform and the location of peers may follow random distribution. The ICT features used to set up the network are lightweight and user friendly, thus, permitting the peers to join the network without the necessity of specialised ICT knowledge. In this perspective it is of increasing interest for HMR activities to elaborate of Personal Weather Station (PWS) networks, capable to provide almost real-time, location aware, weather data. Moreover, different big players of the web arena are now providing world-wide backbones, suitable to present on detailed map location aware information, obtained by mashing up data from different sources. This is the case, for example, with Google Earth and Google Maps. This paper presents the design of a mashup application aimed at aggregating, refining and visualizing near real-time hydro-meteorological datasets. In particular, we focused on the integration of instant precipitation depths, registered either by widespread semi-professional weather stations and official ones. This sort of information has high importance and usefulness in decision support systems and Civil

  13. Spatial validation of large scale land surface models against monthly land surface temperature patterns using innovative performance metrics.

    Science.gov (United States)

    Koch, Julian; Siemann, Amanda; Stisen, Simon; Sheffield, Justin

    2016-04-01

    Land surface models (LSMs) are a key tool to enhance process understanding and to provide predictions of the terrestrial hydrosphere and its atmospheric coupling. Distributed LSMs predict hydrological states and fluxes, such as land surface temperature (LST) or actual evapotranspiration (aET), at each grid cell. LST observations are widely available through satellite remote sensing platforms that enable comprehensive spatial validations of LSMs. In spite of the availability of LST data, most validation studies rely on simple cell to cell comparisons and thus do not regard true spatial pattern information. This study features two innovative spatial performance metrics, namely EOF- and connectivity-analysis, to validate predicted LST patterns by three LSMs (Mosaic, Noah, VIC) over the contiguous USA. The LST validation dataset is derived from global High-Resolution-Infrared-Radiometric-Sounder (HIRS) retrievals for a 30 year period. The metrics are bias insensitive, which is an important feature in order to truly validate spatial patterns. The EOF analysis evaluates the spatial variability and pattern seasonality, and attests better performance to VIC in the warm months and to Mosaic and Noah in the cold months. Further, more than 75% of the LST variability can be captured by a single pattern that is strongly driven by air temperature. The connectivity analysis assesses the homogeneity and smoothness of patterns. The LSMs are most reliable at predicting cold LST patterns in the warm months and vice versa. Lastly, the coupling between aET and LST is investigated at flux tower sites and compared against LSMs to explain the identified LST shortcomings.

  14. Inferring land use and land cover impact on stream water quality using a Bayesian hierarchical modeling approach in the Xitiaoxi River Watershed, China.

    Science.gov (United States)

    Wan, Rongrong; Cai, Shanshan; Li, Hengpeng; Yang, Guishan; Li, Zhaofu; Nie, Xiaofei

    2014-01-15

    Lake eutrophication has become a very serious environmental problem in China. If water pollution is to be controlled and ultimately eliminated, it is essential to understand how human activities affect surface water quality. A recently developed technique using the Bayesian hierarchical linear regression model revealed the effects of land use and land cover (LULC) on stream water quality at a watershed scale. Six LULC categories combined with watershed characteristics, including size, slope, and permeability were the variables that were studied. The pollutants of concern were nutrient concentrations of total nitrogen (TN) and total phosphorus (TP), common pollutants found in eutrophication. The monthly monitoring data at 41 sites in the Xitiaoxi Watershed, China during 2009-2010 were used for model demonstration. The results showed that the relationships between LULC and stream water quality are so complicated that the effects are varied over large areas. The models suggested that urban and agricultural land are important sources of TN and TP concentrations, while rural residential land is one of the major sources of TN. Certain agricultural practices (excessive fertilizer application) result in greater concentrations of nutrients in paddy fields, artificial grasslands, and artificial woodlands. This study suggests that Bayesian hierarchical modeling is a powerful tool for examining the complicated relationships between land use and water quality on different scales, and for developing land use and water management policies. Copyright © 2013 Elsevier Ltd. All rights reserved.

  15. Coupling a three-dimensional subsurface flow and transport model with a land surface model to simulate stream-aquifer-land interactions (CP v1.0)

    Science.gov (United States)

    Bisht, Gautam; Huang, Maoyi; Zhou, Tian; Chen, Xingyuan; Dai, Heng; Hammond, Glenn E.; Riley, William J.; Downs, Janelle L.; Liu, Ying; Zachara, John M.

    2017-12-01

    A fully coupled three-dimensional surface and subsurface land model is developed and applied to a site along the Columbia River to simulate three-way interactions among river water, groundwater, and land surface processes. The model features the coupling of the Community Land Model version 4.5 (CLM4.5) and a massively parallel multiphysics reactive transport model (PFLOTRAN). The coupled model, named CP v1.0, is applied to a 400 m × 400 m study domain instrumented with groundwater monitoring wells along the Columbia River shoreline. CP v1.0 simulations are performed at three spatial resolutions (i.e., 2, 10, and 20 m) over a 5-year period to evaluate the impact of hydroclimatic conditions and spatial resolution on simulated variables. Results show that the coupled model is capable of simulating groundwater-river-water interactions driven by river stage variability along managed river reaches, which are of global significance as a result of over 30 000 dams constructed worldwide during the past half-century. Our numerical experiments suggest that the land-surface energy partitioning is strongly modulated by groundwater-river-water interactions through expanding the periodically inundated fraction of the riparian zone, and enhancing moisture availability in the vadose zone via capillary rise in response to the river stage change. Meanwhile, CLM4.5 fails to capture the key hydrologic process (i.e., groundwater-river-water exchange) at the site, and consequently simulates drastically different water and energy budgets. Furthermore, spatial resolution is found to significantly impact the accuracy of estimated the mass exchange rates at the boundaries of the aquifer, and it becomes critical when surface and subsurface become more tightly coupled with groundwater table within 6 to 7 meters below the surface. Inclusion of lateral subsurface flow influenced both the surface energy budget and subsurface transport processes as a result of river-water intrusion into the

  16. Simulating carbon exchange using a regional atmospheric model coupled to an advanced land-surface model

    Directory of Open Access Journals (Sweden)

    H. W. Ter Maat

    2010-08-01

    Full Text Available This paper is a case study to investigate what the main controlling factors are that determine atmospheric carbon dioxide content for a region in the centre of The Netherlands. We use the Regional Atmospheric Modelling System (RAMS, coupled with a land surface scheme simulating carbon, heat and momentum fluxes (SWAPS-C, and including also submodels for urban and marine fluxes, which in principle should include the dominant mechanisms and should be able to capture the relevant dynamics of the system. To validate the model, observations are used that were taken during an intensive observational campaign in central Netherlands in summer 2002. These include flux-tower observations and aircraft observations of vertical profiles and spatial fluxes of various variables.

    The simulations performed with the coupled regional model (RAMS-SWAPS-C are in good qualitative agreement with the observations. The station validation of the model demonstrates that the incoming shortwave radiation and surface fluxes of water and CO2 are well simulated. The comparison against aircraft data shows that the regional meteorology (i.e. wind, temperature is captured well by the model. Comparing spatially explicitly simulated fluxes with aircraft observed fluxes we conclude that in general latent heat fluxes are underestimated by the model compared to the observations but that the latter exhibit large variability within all flights. Sensitivity experiments demonstrate the relevance of the urban emissions of carbon dioxide for the carbon balance in this particular region. The same tests also show the relation between uncertainties in surface fluxes and those in atmospheric concentrations.

  17. Integrated Multimedia Modeling System Response to Regional Land Management Change

    Science.gov (United States)

    A multi-media system of nitrogen and co-pollutant models describing critical physical and chemical processes that cascade synergistically and competitively through the environment, the economy and society has been developed at the USEPA Office of research and development. It is ...

  18. Export of microplastics from land to sea. A modelling approach

    NARCIS (Netherlands)

    Siegfried, Max; Koelmans, A.A.; Besseling, E.; Kroeze, C.

    2017-01-01

    Quantifying the transport of plastic debris from river to sea is crucial for assessing the risks of plastic debris to human health and the environment. We present a global modelling approach to analyse the composition and quantity of point-source microplastic fluxes from European rivers to the sea.

  19. Spatiotemporal variability of hydrometeorological extremes and their impacts in the Jihlava region in the 1650-1880 period

    Science.gov (United States)

    Dolak, Lukas; Brazdil, Rudolf; Chroma, Katerina; Valasek, Hubert; Reznickova, Ladislava

    2017-04-01

    Different documentary evidence (taxation records, chronicles, insurance reports etc.) and secondary sources (peer-reviewed papers, historical literature, newspapers) are used for reconstruction of hydrometeorological extremes (HMEs) in the former Jihlava region in the 1651-1880 period. The study describes the system of tax alleviation in Moravia, presents assessment of the impacts of HMEs with regard to physical-geographical characteristic of area studied, presents up to now non-utilized documentary evidence (early fire and hail damage insurance claims) and application of the new methodological approaches for the analysis of HMEs impacts. During the period studied more than 500 HMEs were analysed for the 19 estates (past basic economic units) in the region. Thunderstorm in 1651 in Rančířov (the Jihlava estate), which caused damage on the fields and meadows, is the first recorded extreme event. Downpours causing flash floods and hailstorms are the most frequently recorded natural disasters. Together with floods, droughts, windstorms, blizzards, late frosts and lightning strikes starting fires caused enormous damage as well. The impacts of HMEs are classified into three categories: impacts on agricultural production, material property and the socio-economic impacts. Natural disasters became the reasons of losses of human lives, property, supplies and farming equipment. HMEs caused damage to fields and meadows, depletion of livestock and triggered the secondary consequences as lack of seeds and finance, high prices, indebtedness, poverty and deterioration in field fertility. The results are discussed with respect to uncertainties associated with documentary evidences and their spatiotemporal distribution. The paper shows that particularly archival records, preserved in the Moravian Land Archives in Brno and other district archives, represent a unique source of data contributing to the better understanding of extreme events and their impacts in the past.

  20. Impact of land management on hydrological functioning in cultivated landscapes: a coupled model of functional assessment

    Science.gov (United States)

    Paré, Nakié; Biarnès, Anne; Barbier, Jean-Marc; Voltz, Marc

    2010-05-01

    In cultivated landscapes, hydrological functioning is highly influenced by anthropic drivers. Indeed, spatio-temporal patterns in land management affect processes such as run-off or pollutant flow. Reciprocally, at the scale of a cropping season, hydrological functioning of land influences farmers' actions on crops. Consequently, the assessment of the hydrologic impacts of land management needs recognition of the global functioning of the system which requires a close coupling between the modelling of land management actions and hydrological processes. Most of hydrological models take into account a spatial representation of the landscape mosaic created by land management. However the resolution used for the temporal evolution of this pattern is coarser than the one required by hydrological model which simulate processes over short time steps. Consequently, there is a need for more accurate temporal representation of land management which means an analysis of the crop management systems and the integration of bio-physical feedback mechanisms on management decisions. We propose an approach for assessing the hydrological impact of crop management system in the specific case of pollutant loading in a perennial crop area, based on the coupling of a distributed hydrological model with a farmer's decision model. This latter model represents land management with decision rules applied by farmers to drive their collection of plots during the whole cropping cycle. It includes agronomic rules based on indicators of the state of the bio-physical system at plot levels as well as work organisation rules at farm level. Different types of crop management system induced by the diversity of farmers are thus represented by different rules set which can be spatially distributed. The spatial pattern in crop management represented by the decision model determines the hydrological functioning of the landscape. A feedback exists since the hydrological processes like the spatio

  1. Export of microplastics from land to sea. A modelling approach.

    Science.gov (United States)

    Siegfried, Max; Koelmans, Albert A; Besseling, Ellen; Kroeze, Carolien

    2017-12-15

    Quantifying the transport of plastic debris from river to sea is crucial for assessing the risks of plastic debris to human health and the environment. We present a global modelling approach to analyse the composition and quantity of point-source microplastic fluxes from European rivers to the sea. The model accounts for different types and sources of microplastics entering river systems via point sources. We combine information on these sources with information on sewage management and plastic retention during river transport for the largest European rivers. Sources of microplastics include personal care products, laundry, household dust and tyre and road wear particles (TRWP). Most of the modelled microplastics exported by rivers to seas are synthetic polymers from TRWP (42%) and plastic-based textiles abraded during laundry (29%). Smaller sources are synthetic polymers and plastic fibres in household dust (19%) and microbeads in personal care products (10%). Microplastic export differs largely among European rivers, as a result of differences in socio-economic development and technological status of sewage treatment facilities. About two-thirds of the microplastics modelled in this study flow into the Mediterranean and Black Sea. This can be explained by the relatively low microplastic removal efficiency of sewage treatment plants in the river basins draining into these two seas. Sewage treatment is generally more efficient in river basins draining into the North Sea, the Baltic Sea and the Atlantic Ocean. We use our model to explore future trends up to the year 2050. Our scenarios indicate that in the future river export of microplastics may increase in some river basins, but decrease in others. Remarkably, for many basins we calculate a reduction in river export of microplastics from point-sources, mainly due to an anticipated improvement in sewage treatment. Copyright © 2017 Elsevier Ltd. All rights reserved.

  2. Clarity versus complexity: land-use modeling as a practical tool for decision-makers.

    Science.gov (United States)

    Sohl, Terry L; Claggett, Peter R

    2013-11-15

    The last decade has seen a remarkable increase in the number of modeling tools available to examine future land-use and land-cover (LULC) change. Integrated modeling frameworks, agent-based models, cellular automata approaches, and other modeling techniques have substantially improved the representation of complex LULC systems, with each method using a different strategy to address complexity. However, despite the development of new and better modeling tools, the use of these tools is limited for actual planning, decision-making, or policy-making purposes. LULC modelers have become very adept at creating tools for modeling LULC change, but complicated models and lack of transparency limit their utility for decision-makers. The complicated nature of many LULC models also makes it impractical or even impossible to perform a rigorous analysis of modeling uncertainty. This paper provides a review of land-cover modeling approaches and the issues causes by the complicated nature of models, and provides suggestions to facilitate the increased use of LULC models by decision-makers and other stakeholders. The utility of LULC models themselves can be improved by 1) providing model code and documentation, 2) through the use of scenario frameworks to frame overall uncertainties, 3) improving methods for generalizing key LULC processes most important to stakeholders, and 4) adopting more rigorous standards for validating models and quantifying uncertainty. Communication with decision-makers and other stakeholders can be improved by increasing stakeholder participation in all stages of the modeling process, increasing the transparency of model structure and uncertainties, and developing user-friendly decision-support systems to bridge the link between LULC science and policy. By considering these options, LULC science will be better positioned to support decision-makers and increase real-world application of LULC modeling results. Published by Elsevier Ltd.

  3. Clarity versus complexity: land-use modeling as a practical tool for decision-makers

    Science.gov (United States)

    Sohl, Terry L.; Claggett, Peter R.

    2013-01-01

    The last decade has seen a remarkable increase in the number of modeling tools available to examine future land-use and land-cover (LULC) change. Integrated modeling frameworks, agent-based models, cellular automata approaches, and other modeling techniques have substantially improved the representation of complex LULC systems, with each method using a different strategy to address complexity. However, despite the development of new and better modeling tools, the use of these tools is limited for actual planning, decision-making, or policy-making purposes. LULC modelers have become very adept at creating tools for modeling LULC change, but complicated models and lack of transparency limit their utility for decision-makers. The complicated nature of many LULC models also makes it impractical or even impossible to perform a rigorous analysis of modeling uncertainty. This paper provides a review of land-cover modeling approaches and the issues causes by the complicated nature of models, and provides suggestions to facilitate the increased use of LULC models by decision-makers and other stakeholders. The utility of LULC models themselves can be improved by 1) providing model code and documentation, 2) through the use of scenario frameworks to frame overall uncertainties, 3) improving methods for generalizing key LULC processes most important to stakeholders, and 4) adopting more rigorous standards for validating models and quantifying uncertainty. Communication with decision-makers and other stakeholders can be improved by increasing stakeholder participation in all stages of the modeling process, increasing the transparency of model structure and uncertainties, and developing user-friendly decision-support systems to bridge the link between LULC science and policy. By considering these options, LULC science will be better positioned to support decision-makers and increase real-world application of LULC modeling results.

  4. Application of the WEPS and SWEEP models to non-agricultural disturbed lands.

    Science.gov (United States)

    Tatarko, J; van Donk, S J; Ascough, J C; Walker, D G

    2016-12-01

    Wind erosion not only affects agricultural productivity but also soil, air, and water quality. Dust and specifically particulate matter ≤10 μm (PM-10) has adverse effects on respiratory health and also reduces visibility along roadways, resulting in auto accidents. The Wind Erosion Prediction System (WEPS) was developed by the USDA-Agricultural Research Service to simulate wind erosion and provide for conservation planning on cultivated agricultural lands. A companion product, known as the Single-Event Wind Erosion Evaluation Program (SWEEP), has also been developed which consists of the stand-alone WEPS erosion submodel combined with a graphical interface to simulate soil loss from single (i.e., daily) wind storm events. In addition to agricultural lands, wind driven dust emissions also occur from other anthropogenic sources such as construction sites, mined and reclaimed areas, landfills, and other disturbed lands. Although developed for agricultural fields, WEPS and SWEEP are useful tools for simulating erosion by wind for non-agricultural lands where typical agricultural practices are not employed. On disturbed lands, WEPS can be applied for simulating long-term (i.e., multi-year) erosion control strategies. SWEEP on the other hand was developed specifically for disturbed lands and can simulate potential soil loss for site- and date-specific planned surface conditions and control practices. This paper presents novel applications of WEPS and SWEEP for developing erosion control strategies on non-agricultural disturbed lands. Erosion control planning with WEPS and SWEEP using water and other dust suppressants, wind barriers, straw mulch, re-vegetation, and other management practices is demonstrated herein through the use of comparative simulation scenarios. The scenarios confirm the efficacy of the WEPS and SWEEP models as valuable tools for supporting the design of erosion control plans for disturbed lands that are not only cost-effective but also incorporate

  5. Application of the WEPS and SWEEP models to non-agricultural disturbed lands

    Directory of Open Access Journals (Sweden)

    J. Tatarko

    2016-12-01

    Full Text Available Wind erosion not only affects agricultural productivity but also soil, air, and water quality. Dust and specifically particulate matter ≤10 μm (PM-10 has adverse effects on respiratory health and also reduces visibility along roadways, resulting in auto accidents. The Wind Erosion Prediction System (WEPS was developed by the USDA-Agricultural Research Service to simulate wind erosion and provide for conservation planning on cultivated agricultural lands. A companion product, known as the Single-Event Wind Erosion Evaluation Program (SWEEP, has also been developed which consists of the stand-alone WEPS erosion submodel combined with a graphical interface to simulate soil loss from single (i.e., daily wind storm events. In addition to agricultural lands, wind driven dust emissions also occur from other anthropogenic sources such as construction sites, mined and reclaimed areas, landfills, and other disturbed lands. Although developed for agricultural fields, WEPS and SWEEP are useful tools for simulating erosion by wind for non-agricultural lands where typical agricultural practices are not employed. On disturbed lands, WEPS can be applied for simulating long-term (i.e., multi-year erosion control strategies. SWEEP on the other hand was developed specifically for disturbed lands and can simulate potential soil loss for site- and date-specific planned surface conditions and control practices. This paper presents novel applications of WEPS and SWEEP for developing erosion control strategies on non-agricultural disturbed lands. Erosion control planning with WEPS and SWEEP using water and other dust suppressants, wind barriers, straw mulch, re-vegetation, and other management practices is demonstrated herein through the use of comparative simulation scenarios. The scenarios confirm the efficacy of the WEPS and SWEEP models as valuable tools for supporting the design of erosion control plans for disturbed lands that are not only cost-effective but

  6. Spatial Modeling of Agricultural Land-Use Change at Global Scale

    Science.gov (United States)

    Meiyappan, Prasanth; Dalton, Michael; O'Neill, Brian C.; Jain, Atul K.

    2013-12-01

    Land use is both a source and consequence of climate change. Long-term modeling of land use is central in global scale assessments using Integrated Assessment Models (IAMs) to explore policy alternatives; especially because adaptation and mitigation of climate change requires long-term commitment. We present a land-use change modeling framework that can reproduce the past 100 years of evolution of global cropland and pastureland patterns to a reasonable accuracy. The novelty of our approach underlies in integrating knowledge from both the observed behavior and economic rationale behind land-use decisions, thereby making up for the intrinsic deficits in both the disciplines. The underlying economic rationale is profit maximization of individual landowners that implicitly reflects local-level decisions-making process at a larger scale. Observed behavior based on examining the relationships between contemporary land-use patterns and its socioeconomic and biophysical drivers, enters as an explicit factor into the economic framework. The land-use allocation is modified by autonomous developments and competition between land-use types. The framework accounts for spatial heterogeneity in the nature of driving factors across geographic regions. The model is currently configured to downscale continental-scale aggregate land-use information to region specific changes in land-use patterns (0.5-deg spatial resolution). The temporal resolution is one year. The historical validation experiment is facilitated by synthesizing gridded maps of a wide range of potential biophysical and socioeconomic driving factors for the 20th century. To our knowledge, this is the first retrospective analysis that has been successful in reproducing the historical experience at a global scale. We apply the method to gain useful insights on two questions: (1) what are the dominant socioeconomic and biophysical driving factors of contemporary cropland and pastureland patterns, across geographic

  7. Long-range hydrometeorological ensemble predictions of drought parameters

    Science.gov (United States)

    Fundel, F.; Jörg-Hess, S.; Zappa, M.

    2012-06-01

    Low streamflow as consequence of a drought event affects numerous aspects of life. Economic sectors that may be impacted by drought are, e.g. power production, agriculture, tourism and water quality management. Numerical models have increasingly been used to forecast low-flow and have become the focus of recent research. Here, we consider daily ensemble runoff forecasts for the river Thur, which has its source in the Swiss Alps. We focus on the low-flow indices duration, severity and magnitude, with a forecast lead-time of one month, to assess their potential usefulness for predictions. The ECMWF VarEPS 5 member reforecast, which covers 18 yr, is used as forcing for the hydrological model PREVAH. A thorough verification shows that, compared to peak flow, probabilistic low-flow forecasts are skillful for longer lead-times, low-flow index forecasts could also be beneficially included in a decision-making process. The results suggest monthly runoff forecasts are useful for accessing the risk of hydrological droughts.

  8. Hydro-meteorological evaluation of downscaled global ensemble rainfall forecasts

    Science.gov (United States)

    Gaborit, Étienne; Anctil, François; Fortin, Vincent; Pelletier, Geneviève

    2013-04-01

    Ensemble rainfall forecasts are of high interest for decision making, as they provide an explicit and dynamic assessment of the uncertainty in the forecast (Ruiz et al. 2009). However, for hydrological forecasting, their low resolution currently limits their use to large watersheds (Maraun et al. 2010). In order to bridge this gap, various implementations of the statistic-stochastic multi-fractal downscaling technique presented by Perica and Foufoula-Georgiou (1996) were compared, bringing Environment Canada's global ensemble rainfall forecasts from a 100 by 70-km resolution down to 6 by 4-km, while increasing each pixel's rainfall variance and preserving its original mean. For comparison purposes, simpler methods were also implemented such as the bi-linear interpolation, which disaggregates global forecasts without modifying their variance. The downscaled meteorological products were evaluated using different scores and diagrams, from both a meteorological and a hydrological view points. The meteorological evaluation was conducted comparing the forecasted rainfall depths against nine days of observed values taken from Québec City rain gauge database. These 9 days present strong precipitation events occurring during the summer of 2009. For the hydrologic evaluation, the hydrological models SWMM5 and (a modified version of) GR4J were implemented on a small 6 km2 urban catchment located in the Québec City region. Ensemble hydrologic forecasts with a time step of 3 hours were then performed over a 3-months period of the summer of 2010 using the original and downscaled ensemble rainfall forecasts. The most important conclusions of this work are that the overall quality of the forecasts was preserved during the disaggregation procedure and that the disaggregated products using this variance-enhancing method were of similar quality than bi-linear interpolation products. However, variance and dispersion of the different members were, of course, much improved for the

  9. Using a Cellular Automata-Markov Model to Reconstruct Spatial Land-Use Patterns in Zhenlai County, Northeast China

    Directory of Open Access Journals (Sweden)

    Yuanyuan Yang

    2015-05-01

    Full Text Available Decadal to centennial land use and land cover change has been consistently singled out as a key element and an important driver of global environmental change, playing an essential role in balancing energy use. Understanding long-term human-environment interactions requires historical reconstruction of past land use and land cover changes. Most of the existing historical reconstructions have insufficient spatial and thematic detail and do not consider various land change types. In this context, this paper explored the possibility of using a cellular automata-Markov model in 90 m × 90 m spatial resolution to reconstruct historical land use in the 1930s in Zhenlai County, China. Then the three-map comparison methodology was employed to assess the predictive accuracy of the transition modeling. The model could produce backward projections by analyzing land use changes in recent decades, assuming that the present land use pattern is dynamically dependent on the historical one. The reconstruction results indicated that in the 1930s most of the study area was occupied by grasslands, followed by wetlands and arable land, while other land categories occupied relatively small areas. Analysis of the three-map comparison illustrated that the major differences among the three maps have less to do with the simulation model and more to do with the inconsistencies among the land categories during the study period. Different information provided by topographic maps and remote sensing images must be recognized.

  10. Development Model of Oxide of Nitrogen Concentration and Land Use Characteristics in Bangkok Area

    Directory of Open Access Journals (Sweden)

    Ratthapol Sillaparassamee

    2016-07-01

    Full Text Available In this study, NOx concentrations and land use characteristics were correlated to develop a Land Use Regression (LUR model for application in Bangkok Metropolitan, Thailand. Measured NOx concentrations data from thirteen air quality monitoring stations located in Bangkok area were analyzed to develop LUR equations. Land use data obtained from site survey method and was characterized into the following categories, i.e., building with 1-2 floors, building with 3-5 floors, building with over 5 floors, green area, road area, space area and open water. The results showed that NOx concentration positively correlated with percentage areas of building 3-5 floors, building >5 floors and road area while NOx had a negative relationship with building 1-2 floors, green area, and space area. The obtained regression model was able to predict 89% of the variation in NOx concentration.

  11. Advancements in Modelling of Land Surface Energy Fluxes with Remote Sensing at Different Spatial Scales

    DEFF Research Database (Denmark)

    Guzinski, Radoslaw

    , and the resultant uxes were compared to field based measurements and to the output of a well calibrated, physically-based distributed hydrological model. The "Triangle" approach was applied in semi-arid Spanish landscape at spatial resolutions ranging from 30 m to 4 km. The study resulted in a number...... climate, weather and numerous biophysical processes, such as plant productivity. As energy is required for ET to occur, it also forms a link between the land-surface energy uxes and water uxes. Therefore, to be able to obtain reliable estimates of ET, reliable estimates of the other land-surface energy...... of this study was to look at, and improve, various approaches for modelling the land-surface energy uxes at different spatial scales. The work was done using physically-based Two-Source Energy Balance (TSEB) approach as well as semi-empirical \\Triangle" approach. The TSEB-based approach was the main focus...

  12. Modeling and Validation of a Navy A6-Intruder Actively Controlled Landing Gear System

    Science.gov (United States)

    Horta, Lucas G.; Daugherty, Robert H.; Martinson, Veloria J.

    1999-01-01

    Concepts for long-range air travel are characterized by airframe designs with long, slender, relatively flexible fuselages. One aspect often overlooked is ground-induced vibration of these aircraft. This paper presents an analytical and experimental study of reducing ground-induced aircraft vibration loads by using actively controlled landing gear. A facility has been developed to test various active landing gear control concepts and their performance, The facility uses a Navy A6 Intruder landing gear fitted with an auxiliary hydraulic supply electronically controlled by servo valves. An analytical model of the gear is presented, including modifications to actuate the gear externally, and test data are used to validate the model. The control design is described and closed-loop test and analysis comparisons are presented.

  13. Integrating Modelling Approaches for Understanding Telecoupling:Global Food Trade and Local Land Use

    OpenAIRE

    James D. A. Millington; Hang Xiong; Steve Peterson; Jeremy Woods

    2017-01-01

    The telecoupling framework is an integrated concept that emphasises socioeconomic and environmental interactions between distant places. Viewed through the lens of the telecoupling framework, land use and food consumption are linked across local to global scales by decision-making agents and trade flows. Quantitatively modelling the dynamics of telecoupled systems like this could be achieved using numerous different modelling approaches. For example, previous approaches to modelling global fo...

  14. A daily water balance model for representing streamflow generation process following land use change

    OpenAIRE

    Bari, M. A.; K. R. J. Smettem

    2005-01-01

    International audience; A simple conceptual water balance model representing the streamflow generation processes on a daily time step following land use change is presented. The model consists of five stores: (i) Dry, Wet and Subsurface Stores for vertical and lateral water flow, (ii) a transient Stream zone Store (iii) a saturated Goundwater Store. The soil moisture balance in the top soil Dry and Wet Stores are the most important component of the model and characterize the dynamically varyi...

  15. Land Building Models: Uncertainty in and Sensitivity to Input Parameters

    Science.gov (United States)

    2013-08-01

    Science (69):370-380. Parker, G., C. Paola, K. X. Whipple, and D. Mohrig. 1998. Alluvial fans formed by channelized fluvial sheet flow. I: Theory...simulates the evolution of a prograding fan -shaped delta advancing into open water. This model is an extension of a tool developed for managing the...with depth in a pair of cores collected from a non-fresh Spartina alterniflora-dominated stable marsh site. The profile clearly reflects the dynamic

  16. Simulations of chlorophyll fluorescence incorporated into the Community Land Model version 4.

    Science.gov (United States)

    Lee, Jung-Eun; Berry, Joseph A; van der Tol, Christiaan; Yang, Xi; Guanter, Luis; Damm, Alexander; Baker, Ian; Frankenberg, Christian

    2015-09-01

    Several studies have shown that satellite retrievals of solar-induced chlorophyll fluorescence (SIF) provide useful information on terrestrial photosynthesis or gross primary production (GPP). Here, we have incorporated equations coupling SIF to photosynthesis in a land surface model, the National Center for Atmospheric Research Community Land Model version 4 (NCAR CLM4), and have demonstrated its use as a diagnostic tool for evaluating the calculation of photosynthesis, a key process in a land surface model that strongly influences the carbon, water, and energy cycles. By comparing forward simulations of SIF, essentially as a byproduct of photosynthesis, in CLM4 with observations of actual SIF, it is possible to check whether the model is accurately representing photosynthesis and the processes coupled to it. We provide some background on how SIF is coupled to photosynthesis, describe how SIF was incorporated into CLM4, and demonstrate that our simulated relationship between SIF and GPP values are reasonable when compared with satellite (Greenhouse gases Observing SATellite; GOSAT) and in situ flux-tower measurements. CLM4 overestimates SIF in tropical forests, and we show that this error can be corrected by adjusting the maximum carboxylation rate (Vmax ) specified for tropical forests in CLM4. Our study confirms that SIF has the potential to improve photosynthesis simulation and thereby can play a critical role in improving land surface and carbon cycle models. © 2015 John Wiley & Sons Ltd.

  17. Representing Northern Peatland Hydrology and Biogeochemistry within the Community Land Model

    Science.gov (United States)

    Shi, X.; Ricciuto, D. M.; Xu, X.; Thornton, P. E.; Hanson, P. J.; Mao, J.; Sebestyen, S.; Griffiths, N.

    2015-12-01

    Northern peatlands are projected to become very important in future carbon-climate feedback due to their large carbon storage and vulnerability to changes in hydrology and climate impacts. Understanding the hydrology and biogeochemistry is a fundamental task for projecting the fate of massive carbon stores in these systems under future climate change. Models have started to address microtopographic controls on peatland hydrology, but none have considered a prognostic calculation of water table dynamics in vegetated peatlands rather than prescribed regional water tables. We introduced here a new configuration of the Community Land Model (CLM), which includes a fully prognostic water table calculation between hummock and hollow microtopography in a vegetated peatland. We further integrated the hydrology treatment with vertically structured soil organic matter pools, and a newly developed microbial functional group-based methane module. The model was further used to test against observational data obtained within Spruce and Peatland Responses Under Climatic and Environmental Change (SPRUCE) project. Results for water table dynamic, carbon profile, and land surface fluxes of carbon dioxide and methane were reasonable. Model simulations showed that warming and elevated CO2 had significant impacts on land surface fluxes of methane and carbon dioxide. The warming-induced hydrological changes are another factors influencing biogeochemistry along soil profiles and land surface gas fluxes. These preliminary results provide some insights for field experiments as well as data-model comparison in next phase of the SPRUCE project.

  18. A land use regression model for predicting ambient fine particulate matter across Los Angeles, CA.

    Science.gov (United States)

    Moore, D K; Jerrett, M; Mack, W J; Künzli, N

    2007-03-01

    Land use regression (LUR) models have been used successfully for predicting local variation in traffic pollution, but few studies have explored this method for deriving fine particle exposure surfaces. The primary purpose of this method is to develop a LUR model for predicting fine particle or PM(2.5) mass over the five county metropolitan statistical area (MSA) of Los Angeles. PM(2.5) includes all particles with diameter less than or equal to 2.5 microns. In the Los Angeles MSA, 23 monitors of PM(2.5) were available in the year 2000. This study uses GIS to integrate data regarding land use, transportation and physical geography to derive a PM(2.5) dataset covering Los Angeles. Multiple linear regression was used to create the model for predicting the PM(2.5) surface. Our parsimonious model explained 69% of the variance in PM(2.5) with three predictors: (1) traffic density within 300 m, (2) industrial land area within 5000 m, and (3) government land area within 5000 m of the monitoring site. These results suggest the LUR method can refine exposure models for epidemiologic studies in a North American context.

  19. Modeling urban land use changes in Lanzhou based on artificial neural network and cellular automata

    Science.gov (United States)

    Xu, Xibao; Zhang, Jianming; Zhou, Xiaojian

    2008-10-01

    This paper presented a model to simulate urban land use changes based on artificial neural network (ANN) and cellular automata (CA). The model was scaled down at the intra-urban level with subtle land use categorization, developed with Matlab 7.2 and loosely coupled with GIS. Urban land use system is a very complicated non-linear social system influenced by many factors. In this paper, four aspects of a totality 17 factors, including physical, social-economic, neighborhoods and policy, were considered synthetically. ANN was proposed as a solution of CA model calibration through its training to acquire the multitudinous parameters as a substitute for the complex transition rules. A stochastic perturbation parameter v was added into the model, and five different scenarios with different values of v and the threshold were designed for simulations and predictions to explore their effects on urban land use changes. Simulations of 2005 and predictions of 2015 under the five different scenarios were made and evaluated. Finally, the advantages and disadvantages of the model were discussed.

  20. Using Intel's Knight Landing Processor to Accelerate Global Nested Air Quality Prediction Modeling System (GNAQPMS) Model

    Science.gov (United States)

    Wang, H.; Chen, H.; Chen, X.; Wu, Q.; Wang, Z.

    2016-12-01

    The Global Nested Air Quality Prediction Modeling System for Hg (GNAQPMS-Hg) is a global chemical transport model coupled Hg transport module to investigate the mercury pollution. In this study, we present our work of transplanting the GNAQPMS model on Intel Xeon Phi processor, Knights Landing (KNL) to accelerate the model. KNL is the second-generation product adopting Many Integrated Core Architecture (MIC) architecture. Compared with the first generation Knight Corner (KNC), KNL has more new hardware features, that it can be used as unique processor as well as coprocessor with other CPU. According to the Vtune tool, the high overhead modules in GNAQPMS model have been addressed, including CBMZ gas chemistry, advection and convection module, and wet deposition module. These high overhead modules were accelerated by optimizing code and using new techniques of KNL. The following optimized measures was done: 1) Changing the pure MPI parallel mode to hybrid parallel mode with MPI and OpenMP; 2.Vectorizing the code to using the 512-bit wide vector computation unit. 3. Reducing unnecessary memory access and calculation. 4. Reducing Thread Local Storage (TLS) for common variables with each OpenMP thread in CBMZ. 5. Changing the way of global communication from files writing and reading to MPI functions. After optimization, the performance of GNAQPMS is greatly increased both on CPU and KNL platform, the single-node test showed that optimized version has 2.6x speedup on two sockets CPU platform and 3.3x speedup on one socket KNL platform compared with the baseline version code, which means the KNL has 1.29x speedup when compared with 2 sockets CPU platform.

  1. A Semi-Empirical Emissivity Model for use in Passive Microwave Precipitation Retrievals Over Land

    Science.gov (United States)

    Ringerud, S.; Kummerow, C. D.; Peters-Lidard, C. D.

    2013-12-01

    The upcoming NASA Global Precipitation Measurement Mission (GPM) offers the opportunity for greatly increased understanding of global rainfall and the hydrologic cycle. The GPM algorithm team has made improvement in passive microwave remote sensing of precipitation over land a priority for this mission, and developed a framework allowing for algorithm advancement for individual land surface types as new techniques are developed. An accurate understanding of land surface emissivity in terms of associated surface properties is necessary for any physically-based retrieval scheme over land. This is a complex problem for passive microwave sensors, as the emissivity of land surfaces in the microwave region is large and dynamic, making it difficult to distinguish hydrometeor signal from the highly variable surface emission. In an effort to understand and model the surface emissivity, a semi-empirical technique is developed and tested over the US Southern Great Plains (SGP) area. A physical model is used to calculate emissivity at the 10 GHz frequency, combining contributions from the underlying soil as well as vegetation layers, including the dielectric and roughness effects of each medium. Radiative transfer through each layer is calculated. Adjustments are added for post-precipitation surface water emissivity effects on both the soil and water-coated vegetation. A 5-year dataset of retrieved emissivities from the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) is employed for calculation of a robust set of channel covariances. These covariances, combined with the modeled 10 GHz emissivities, provide emissivity values for each AMSR-E channel, which are then used to compute top of the atmosphere brightness temperatures (TBs). Initial results comparing these calculated TBs to observed values show correlations of 0.87-0.97, with the lowest correlations appearing in the highest frequencies of the microwave window region. Such a modeling system could

  2. Modeling Soil Organic Carbon for Agricultural Land Use Under Various Management Practices

    Science.gov (United States)

    Kotamarthi, V. R.; Drewniak, B.; Song, J.; Prell, J.; Jacob, R. L.

    2009-12-01

    Bioenergy is generating tremendous interest as an alternative energy source that is both environmentally friendly and economically competitive. The amount of land designated for agriculture is expected to expand, including changes in the current distribution of crops, as demand for biofuels increases as a carbon neutral alternative fuel source. However, the influence of agriculture on the carbon cycle is complex, and varies depending on land use change and management practices. The purpose of this research is to integrate agriculture in the carbon-nitrogen based Community Land Model (CLM) to evaluate the above and below ground carbon storage for corn, soybean, and wheat crop lands. The new model, CLM-Crop simulates carbon allocation during four growth stages, a soybean nitrogen fixation scheme, fertilizer, and harvest practices. We present results from this model simulation, which includes the impact of a new dynamic roots module to simulate the changing root structure and depth with growing season based on the availability of water and nitrogen in the root zone and a retranslocation scheme to simulate redistribution of nitrogen from leaves, roots, and stems to grain during organ development for crop yields, leaf area index (LAI), carbon allocation, and changes in soil carbon budgets under various practices such as fertilizer and residue management. Simulated crop yields for corn, soybean and wheat are in general agreement with measurements. Initial model results indicate a loss of soil organic carbon over cultivated lands after removal of natural vegetation which continues in the following years. Soil carbon in crop lands is a strong function of the residue management and has the potential to impact crop yields significantly.

  3. Interactions between Climate, Socioeconomics, and Land Dynamics in Qinghai Province, China: A LUCD Model-Based Numerical Experiment

    Directory of Open Access Journals (Sweden)

    Xiangzheng Deng

    2013-01-01

    Full Text Available This simulation-based research produces a set of forecast land use data of Qinghai Province, China, applying the land use change dynamics (LUCD model. The simulation results show that the land use pattern will almost keep being consistent in the period from 2010 to 2050 with that in 2000 in Qinghai Province. Grassland and barren or sparsely vegetated land will cover more than 80% of the province’s total area. The land use change will be inconspicuous in the period from 2010 to 2050 involving only 0.49% of the province’s land. The expansion of urban and built-up land, grassland, and barren or sparsely vegetated land and the area reduction of mixed dryland/irrigated cropland and pasture, water bodies, and snow or ice will dominate land use changes of the case study area. The changes of urban and built-up land and mixed dryland/irrigated cropland and pasture will slow down over time. Meanwhile, the change rates of water bodies, snow and ice, barren or sparsely vegetated land, and grassland will show an inverted U-shaped trajectory. Except for providing underlying surfaces for RCMs for future climate change assessment, this empirical research of regional land use change may enhance the understanding of land surface system dynamics.

  4. The quest for the perfect model: Pre World War 1. Military land use modeling of the Greater Copenhagen area

    DEFF Research Database (Denmark)

    Svenningsen, Stig Roar; Brandt, Jesper; Christensen, Andreas Aagaard

    the rotational system. At first the survey campaign seems to be going very well, but relative quickly did the military run into problems. The rapid urbanization of the landscape north of Copenhagen meant, that farming did not take place and at the island of Amager southwest of Copenhagen the farmers didn’t use......Anthropogenic land use practices are the single most important factor in the changing European landscapes. Respectively much attention has been devoted within Landscape Ecology to analyze changing patterns of land use and develop research strategies to understand the processes behind these changes...... and to inform policy makers. Models are used as an important tool in this research partly due to the revolution in information technologies during the last 30 years, which has made modeling more widespread in the research community. However modeling human decision making in form of land use practices...

  5. A dynamic simulation/optimization model for scheduling restoration of degraded military training lands.

    Science.gov (United States)

    Önal, Hayri; Woodford, Philip; Tweddale, Scott A; Westervelt, James D; Chen, Mengye; Dissanayake, Sahan T M; Pitois, Gauthier

    2016-04-15

    Intensive use of military vehicles on Department of Defense training installations causes deterioration in ground surface quality. Degraded lands restrict the scheduled training activities and jeopardize personnel and equipment safety. We present a simulation-optimization approach and develop a discrete dynamic optimization model to determine an optimum land restoration for a given training schedule and availability of financial resources to minimize the adverse effects of training on military lands. The model considers weather forecasts, scheduled maneuver exercises, and unique qualities and importance of the maneuver areas. An application of this approach to Fort Riley, Kansas, shows that: i) starting with natural conditions, the total amount of training damages would increase almost linearly and exceed a quarter of the training area and 228 gullies would be formed (mostly in the intensive training areas) if no restoration is carried out over 10 years; ii) assuming an initial state that resembles the present conditions, sustaining the landscape requires an annual restoration budget of $957 thousand; iii) targeting a uniform distribution of maneuver damages would increase the total damages and adversely affect the overall landscape quality, therefore a selective restoration strategy may be preferred; and iv) a proactive restoration strategy would be optimal where land degradations are repaired before they turn into more severe damages that are more expensive to repair and may pose a higher training risk. The last finding can be used as a rule-of-thumb for land restoration efforts in other installations with similar characteristics. Copyright © 2016 Elsevier Ltd. All rights reserved.

  6. Integrating remotely sensed land cover observations and a biogeochemical model for estimating forest ecosystem carbon dynamics

    Science.gov (United States)

    Liu, J.; Liu, S.; Loveland, T.R.; Tieszen, L.L.

    2008-01-01

    Land cover change is one of the key driving forces for ecosystem carbon (C) dynamics. We present an approach for using sequential remotely sensed land cover observations and a biogeochemical model to estimate contemporary and future ecosystem carbon trends. We applied the General Ensemble Biogeochemical Modelling System (GEMS) for the Laurentian Plains and Hills ecoregion in the northeastern United States for the period of 1975-2025. The land cover changes, especially forest stand-replacing events, were detected on 30 randomly located 10-km by 10-km sample blocks, and were assimilated by GEMS for biogeochemical simulations. In GEMS, each unique combination of major controlling variables (including land cover change history) forms a geo-referenced simulation unit. For a forest simulation unit, a Monte Carlo process is used to determine forest type, forest age, forest biomass, and soil C, based on the Forest Inventory and Analysis (FIA) data and the U.S. General Soil Map (STATSGO) data. Ensemble simulations are performed for each simulation unit to incorporate input data uncertainty. Results show that on average forests of the Laurentian Plains and Hills ecoregion have been sequestrating 4.2 Tg C (1 teragram = 1012 gram) per year, including 1.9 Tg C removed from the ecosystem as the consequences of land cover change. ?? 2008 Elsevier B.V.

  7. LAND SUITABILITY SCENARIOS FOR ARID COASTAL PLAINS USING GIS MODELING: SOUTHWESTERN SINAI COASTAL PLAIN, EGYPT

    Directory of Open Access Journals (Sweden)

    Ahmed Mohamed Wahid

    2009-12-01

    Full Text Available Site selection analysis was carried out to find the best suitable lands for development activities in an example of promising coastal plains, southwestern Sinai, Egypt. Two GIS models were developed to represent two scenarios of land use suitability in the study area using GIS Multi Criteria Analysis Modeling. The factors contributed in the analysis are the Topography, Land cover, Existing Land use, Flash flood index, Drainage lines and Water points. The first scenario was to classify the area according to various gradual ranges of suitability. According to this scenario, the area is classified into five classes of suitability. The percentage of suitability values are 51.16, 6.13, 22.32, 18.49 and 1.89% for unsuitable, least suitable, low suitable, suitable and high suitable, respectively. The second scenario is developed for a particular kind of land use planning; tourism and recreation projects. The suitability map of this scenario was classified into five values. Unsuitable areas represent 51.18% of the study area, least suitable 16.67%, low suitable 22.85%, suitable 8.61%, and high suitable 0.68%. The best area for locating development projects is the area surrounding El-Tor City and close to the coast. This area could be an urban extension of El-Tor City with more economical and environmental management.

  8. LAND SUITABILITY SCENARIOS FOR ARID COASTAL PLAINS USING GIS MODELING: SOUTHWESTERN SINAI COASTAL PLAIN, EGYPT

    Directory of Open Access Journals (Sweden)

    Ahmed Wahid

    2009-01-01

    Full Text Available Site selection analysis was carried out to find the best suitable lands for development activities in an example of promising coastal plains, southwestern Sinai, Egypt. Two GIS models were developed to represent two scenarios of land use suitability in the study area using GIS Multi Criteria Analysis Modeling. The factors contributed in the analysis are the Topography, Land cover, Existing Land use, Flash flood index, Drainage lines and Water points. The first scenario was to classify the area according to various gradual ranges of suitability. According to this scenario, the area is classified into five classes of suitability. The percentage of suitability values are 51.16, 6.13, 22.32, 18.49 and 1.89% for unsuitable, least suitable, low suitable, suitable and high suitable, respectively. The second scenario is developed for a particular kind of land use planning; tourism and recreation projects. The suitability map of this scenario was classified into five values. Unsuitable areas represent 51.18% of the study area, least suitable 16.67%, low suitable 22.85%, suitable 8.61%, and high suitable 0.68%. The best area for locating development projects is the area surrounding El-Tor City and close to the coast. This area could be an urban extension of El-Tor City with more economical and environmental management.