Sample records for agro-hydrology model eahm

  1. Synergetic Use of Sentinel-1 and 2 to Improve Agro-Hydrological Modeling

    NASA Astrophysics Data System (ADS)

    Ferrant, Sylvain; Kerr, Yann; Al-Bitar, Ahmad; Le Page, Michel; Selles, Adrien; Mermoz, Stephane; Bouvet, Alexandre; Marechal, Jean-Christophe; Tomer, Sat; Sekhar, Muddu; Dedieu, Gerard; Le Toan, Thuy; Bustillo, Vincent

    2016-08-01

    In the context of global changes and population growth, agricultural activities are a growing factor influencing water resources availability in term of quantity and quality. Water management strategies have to be analyzed at a regional catchment scales. Yet, agricultural practices, crop water and nutrient consumption that drive the main water and nutrient fluxes at the catchment scale have to be monitored at a high spatial (crop extension) and temporal resolution (crop growth period). This proceeding describes some advances in the framework of a co-funded ESA Living Planet Fellowship project, called ―agro-hydrology from space‖, which aims at demonstrating the improvement brought by synergetic observations of Sentinel-1 (S1) and Sentinel-2 (S2) satellite mission in agro- hydrological studies. Geo-information time-series of vegetation and water index with multi-spectral optical detection S2 together with surface roughness time series with C-band radar detection S1 are used to re-set soil water holding capacity parameters (depth, porosity) and agricultural practices (sowing date, irrigated area extent) of a crop model coupled with a hydrological model in two contrasted water management issues: stream water nitrate pollution in Gascogne region in south-west of France and groundwater depletion and shortages for irrigation in Deccan Plateau, in south-India.

  2. A component-based, integrated spatially distributed hydrologic/water quality model: AgroEcoSystem-Watershed (AgES-W) overview and application

    USDA-ARS?s Scientific Manuscript database

    AgroEcoSystem-Watershed (AgES-W) is a modular, Java-based spatially distributed model which implements hydrologic/water quality simulation components. The AgES-W model was previously evaluated for streamflow and recently has been enhanced with the addition of nitrogen (N) and sediment modeling compo...

  3. Modelingevapotranspirationina sub-tropical climate

    USGS Publications Warehouse

    Savabi, M.R.; Cochrane, T.A.; German, E.; Ikiz, C.; Cockshutt, N.

    2007-01-01

    Evapotranspiration (ET) loss is estimated at about 80-85% of annual precipitation in South Florida. Accurate prediction of ET is important during and beyond the implementation of the Comprehensive Everglades Restoration Plan (CERP). In the USDA's Everglades Agro-Hydrology Model (EAHM) the soil water intake is linked with the soil water redistribution, soil evaporation, plant transpiration, subsurface lateral flow and subsurface drainage to calculate daily root zone soil water content. Hydrometeorological data from three sites with different soil moisture content and vegetal cover were used to evaluate the EAHM ET routine. In general, the EAHM water balance sub-model simulated the daily ET with acceptable accuracy in the area with standing water (Everglades) while using the Penman method. However, in the area with grass cover, there was a discrepancy between the model simulated and measured ET using either the Penman or the Priestley-Taylor method. The results indicated that in the region with two distinct climate patterns: dry (low humidity, more wind, and less precipitation) and wet (high humidity, less wind and more rainfall) such as South Florida, a combination method like Penman should be used for prediction of daily ET. However, in order to improve the predictability of the ET methods, information about surface albedo is needed for land surfaces with grass vegetation during the growing season.

  4. Agro-hydrology and multi-temporal high-resolution remote sensing: toward an explicit spatial processes calibration

    NASA Astrophysics Data System (ADS)

    Ferrant, S.; Gascoin, S.; Veloso, A.; Salmon-Monviola, J.; Claverie, M.; Rivalland, V.; Dedieu, G.; Demarez, V.; Ceschia, E.; Probst, J.-L.; Durand, P.; Bustillo, V.

    2014-12-01

    The growing availability of high-resolution satellite image series offers new opportunities in agro-hydrological research and modeling. We investigated the possibilities offered for improving crop-growth dynamic simulation with the distributed agro-hydrological model: topography-based nitrogen transfer and transformation (TNT2). We used a leaf area index (LAI) map series derived from 105 Formosat-2 (F2) images covering the period 2006-2010. The TNT2 model (Beaujouan et al., 2002), calibrated against discharge and in-stream nitrate fluxes for the period 1985-2001, was tested on the 2005-2010 data set (climate, land use, agricultural practices, and discharge and nitrate fluxes at the outlet). Data from the first year (2005) were used to initialize the hydrological model. A priori agricultural practices obtained from an extensive field survey, such as seeding date, crop cultivar, and amount of fertilizer, were used as input variables. Continuous values of LAI as a function of cumulative daily temperature were obtained at the crop-field level by fitting a double logistic equation against discrete satellite-derived LAI. Model predictions of LAI dynamics using the a priori input parameters displayed temporal shifts from those observed LAI profiles that are irregularly distributed in space (between field crops) and time (between years). By resetting the seeding date at the crop-field level, we have developed an optimization method designed to efficiently minimize this temporal shift and better fit the crop growth against both the spatial observations and crop production. This optimization of simulated LAI has a negligible impact on water budgets at the catchment scale (1 mm yr-1 on average) but a noticeable impact on in-stream nitrogen fluxes (around 12%), which is of interest when considering nitrate stream contamination issues and the objectives of TNT2 modeling. This study demonstrates the potential contribution of the forthcoming high spatial and temporal resolution

  5. Agro-hydrology and multi temporal high resolution remote sensing: toward an explicit spatial processes calibration

    NASA Astrophysics Data System (ADS)

    Ferrant, S.; Gascoin, S.; Veloso, A.; Salmon-Monviola, J.; Claverie, M.; Rivalland, V.; Dedieu, G.; Demarez, V.; Ceschia, E.; Probst, J.-L.; Durand, P.; Bustillo, V.

    2014-07-01

    The recent and forthcoming availability of high resolution satellite image series offers new opportunities in agro-hydrological research and modeling. We investigated the perspective offered by improving the crop growth dynamic simulation using the distributed agro-hydrological model, Topography based Nitrogen transfer and Transformation (TNT2), using LAI map series derived from 105 Formosat-2 (F2) images during the period 2006-2010. The TNT2 model (Beaujouan et al., 2002), calibrated with discharge and in-stream nitrate fluxes for the period 1985-2001, was tested on the 2006-2010 dataset (climate, land use, agricultural practices, discharge and nitrate fluxes at the outlet). A priori agricultural practices obtained from an extensive field survey such as seeding date, crop cultivar, and fertilizer amount were used as input variables. Continuous values of LAI as a function of cumulative daily temperature were obtained at the crop field level by fitting a double logistic equation against discrete satellite-derived LAI. Model predictions of LAI dynamics with a priori input parameters showed an temporal shift with observed LAI profiles irregularly distributed in space (between field crops) and time (between years). By re-setting seeding date at the crop field level, we proposed an optimization method to minimize efficiently this temporal shift and better fit the crop growth against the spatial observations as well as crop production. This optimization of simulated LAI has a negligible impact on water budget at the catchment scale (1 mm yr-1 in average) but a noticeable impact on in-stream nitrogen fluxes (around 12%) which is of interest considering nitrate stream contamination issues and TNT2 model objectives. This study demonstrates the contribution of forthcoming high spatial and temporal resolution products of Sentinel-2 satellite mission in improving agro-hydrological modeling by constraining the spatial representation of crop productivity.

  6. Synergetic use of Sentinel-1 and 2 to improve agro-hydrological modeling. Results of groundwater pumping estimates in south-India and nitrogen excess in south-west of France

    NASA Astrophysics Data System (ADS)

    Ferrant, S.; Le Page, M.; Kerr, Y. H.; Selles, A.; Mermoz, S.; Al-Bitar, A.; Muddu, S.; Gascoin, S.; Marechal, J. C.; Durand, P.; Salmon-Monviola, J.; Ceschia, E.; Bustillo, V.

    2016-12-01

    Nitrogen transfers at agricultural catchment level are intricately linked to water transfers. Agro-hydrological modeling approaches aim at integrating spatial heterogeneity of catchment physical properties together with agricultural practices to spatially estimate the water and nitrogen cycles. As in hydrology, the calibration schemes are designed to optimize the performance of the temporal dynamics and biases in model simulations, while ignoring the simulated spatial pattern. Yet, crop uses, i.e. transpiration and nitrogen exported by harvest, are the main fluxes at the catchment scale, highly variable in space and time. Geo-information time-series of vegetation and water index with multi-spectral optical detection S2 together with surface roughness time series with C-band radar detection S1 are used to reset soil water holding capacity parameters (depth, porosity) and agricultural practices (sowing date, irrigated area extent) of a crop model coupled with a hydrological model. This study takes two agro-hydrological contexts as demonstrators: 1-spatial nitrogen excess estimation in south-west of France, and 2-groundwater extraction for rice irrigation in south-India. Spatio-temporal patterns are involved in respectively surface water contamination due to over-fertilization and local groundwater shortages due to over-pumping for above rice inundation. Optimized Leaf Area Index profiles are simulated at the satellite images pixel level using an agro-hydrological model to reproduce spatial and temporal crop growth dynamics in south-west of France, improving the in-stream nitrogen fluxes by 12%. Accurate detection of irrigated area extents are obtained with the thresholding method based on optical indices, with a kappa of 0.81 for the dry season 2016. The actual monsoon season is monitored and will be presented. These extents drive the groundwater pumping and are highly variable in time (from 2 to 8% of the total area).

  7. Modelling Mediterranean agro-ecosystems by including agricultural trees in the LPJmL model

    NASA Astrophysics Data System (ADS)

    Fader, M.; von Bloh, W.; Shi, S.; Bondeau, A.; Cramer, W.

    2015-06-01

    Climate and land use change in the Mediterranean region is expected to affect natural and agricultural ecosystems by decreases in precipitation, increases in temperature as well as biodiversity loss and anthropogenic degradation of natural resources. Demographic growth in the Eastern and Southern shores will require increases in food production and put additional pressure on agro-ecosystems and water resources. Coping with these challenges requires informed decisions that, in turn, require assessments by means of a comprehensive agro-ecosystem and hydrological model. This study presents the inclusion of 10 Mediterranean agricultural plants, mainly perennial crops, in an agro-ecosystem model (LPJmL): nut trees, date palms, citrus trees, orchards, olive trees, grapes, cotton, potatoes, vegetables and fodder grasses. The model was successfully tested in three model outputs: agricultural yields, irrigation requirements and soil carbon density. With the development presented in this study, LPJmL is now able to simulate in good detail and mechanistically the functioning of Mediterranean agriculture with a comprehensive representation of ecophysiological processes for all vegetation types (natural and agricultural) and in a consistent framework that produces estimates of carbon, agricultural and hydrological variables for the entire Mediterranean basin. This development pave the way for further model extensions aiming at the representation of alternative agro-ecosystems (e.g. agroforestry), and opens the door for a large number of applications in the Mediterranean region, for example assessments on the consequences of land use transitions, the influence of management practices and climate change impacts.

  8. Modelling Mediterranean agro-ecosystems by including agricultural trees in the LPJmL model

    NASA Astrophysics Data System (ADS)

    Fader, M.; von Bloh, W.; Shi, S.; Bondeau, A.; Cramer, W.

    2015-11-01

    In the Mediterranean region, climate and land use change are expected to impact on natural and agricultural ecosystems by warming, reduced rainfall, direct degradation of ecosystems and biodiversity loss. Human population growth and socioeconomic changes, notably on the eastern and southern shores, will require increases in food production and put additional pressure on agro-ecosystems and water resources. Coping with these challenges requires informed decisions that, in turn, require assessments by means of a comprehensive agro-ecosystem and hydrological model. This study presents the inclusion of 10 Mediterranean agricultural plants, mainly perennial crops, in an agro-ecosystem model (Lund-Potsdam-Jena managed Land - LPJmL): nut trees, date palms, citrus trees, orchards, olive trees, grapes, cotton, potatoes, vegetables and fodder grasses. The model was successfully tested in three model outputs: agricultural yields, irrigation requirements and soil carbon density. With the development presented in this study, LPJmL is now able to simulate in good detail and mechanistically the functioning of Mediterranean agriculture with a comprehensive representation of ecophysiological processes for all vegetation types (natural and agricultural) and in a consistent framework that produces estimates of carbon, agricultural and hydrological variables for the entire Mediterranean basin. This development paves the way for further model extensions aiming at the representation of alternative agro-ecosystems (e.g. agroforestry), and opens the door for a large number of applications in the Mediterranean region, for example assessments of the consequences of land use transitions, the influence of management practices and climate change impacts.

  9. Extract useful knowledge from agro-hydrological simulations data for decision making

    NASA Astrophysics Data System (ADS)

    Gascuel-odoux, C.; Bouadi, T.; Cordier, M.; Quiniou, R.

    2013-12-01

    In recent years, models have been developed and used to test the effect of scenarios and help stakeholders in decision making. Agro-hydrological models have guided agricultural water management by testing the effect of landscape structure and farming system changes on water quantity and quality. Such models generate a large amount of data but few are stored and are often not customized for stakeholders, so that a great amount of information is lost from the simulation process or not transformed in a usable format. A first approach, already published (Trepos et al., 2012), has been developed to identify object oriented tree patterns, that represent surface flow and pollutant pathways from plot to plot, involved in water pollution by herbicides. A simulation model (Gascuel-odoux et al., 2009) predicted herbicide transfer rate, defined as the proportion of applied herbicide that reaches water courses. The predictions were used as a set of learning examples for symbolic learning techniques to induce rules based on qualitative and quantitative attributes and explain two extreme classes in transfer rate. Two automatic symbolic learning techniques were used: the inductive logic programming approach to induce spatial tree patterns, and an attribute-value method to induce aggregated attributes of the trees. A visualization interface allows the users to identify rules explaining contamination and mitigation measures improving the current situation. A second approach has been recently developed to analyse directly the simulated data (Bouadi et al, submitted). A data warehouse called N-catch has been built to store and manage simulation data from the agro-hydrological model TNT2 (Beaujouan et al., 2002). 44 output key simulated variables are stored per plot and at a daily time step on a 50 squared km area, i.e, 8 GB of storage size. After identifying the set of multileveled dimensions integrating hierarchical structures and relationships among related dimension levels, N

  10. Using Data Warehouses to extract knowledge from Agro-Hydrological simulations

    NASA Astrophysics Data System (ADS)

    Bouadi, Tassadit; Gascuel-Odoux, Chantal; Cordier, Marie-Odile; Quiniou, René; Moreau, Pierre

    2013-04-01

    In recent years, simulation models have been used more and more in hydrology to test the effect of scenarios and help stakeholders in decision making. Agro-hydrological models have oriented agricultural water management, by testing the effect of landscape structure and farming system changes on water and chemical emission in rivers. Such models generate a large amount of data while few of them, such as daily concentrations at the outlet of the catchment, or annual budgets regarding soil, water and atmosphere emissions, are stored and analyzed. Thus, a great amount of information is lost from the simulation process. This is due to the large volumes of simulated data, but also to the difficulties in analyzing and transforming the data in an usable information. In this talk we illustrate a data warehouse which has been built to store and manage simulation data coming from the agro-hydrological model TNT (Topography-based nitrogen transfer and transformations, (Beaujouan et al., 2002)). This model simulates the transfer and transformation of nitrogen in agricultural catchments. TNT was used over 10 years on the Yar catchment (western France), a 50 km2 square area which present a detailed data set and have to facing to environmental issue (coastal eutrophication). 44 output key simulated variables are stored at a daily time step, i.e, 8 GB of storage size, which allows the users to explore the N emission in space and time, to quantify all the processes of transfer and transformation regarding the cropping systems, their location within the catchment, the emission in water and atmosphere, and finally to get new knowledge and help in making specific and detailed decision in space and time. We present the dimensional modeling process of the Nitrogen in catchment data warehouse (i.e. the snowflake model). After identifying the set of multileveled dimensions with complex hierarchical structures and relationships among related dimension levels, we chose the snowflake model to

  11. Evaluating Satellite Rainfall Estimates for Agro-hydrological Applications in Africa

    NASA Astrophysics Data System (ADS)

    Senay, G. B.; Verdin, J. P.; Korecha, D.; Asfaw, A.

    2004-12-01

    Regional water balance techniques are used to monitor and forecast crop performance and flooding potentials around the world. In the last few years, satellite rainfall estimates (RFE) have become available at continental scales, which made it possible to develop operational regional water balance models for the monitoring of crops performance and flooding potentials in Africa and other regions of the world as part of an environmental early warning system . The accuracy of RFE in absolute terms and importantly as it relates to agricultural and hydrological applications have not been evaluated systematically. This study evaluated a subset of the Africa-wide RFE product by comparing station-rainfall data and RFE from 1996 to 2002 using over 100 rain-gauge stations from Ethiopia at a dekadal (~10-day) time step. The results showed a general under-estimation of RFE compared to station rainfall values. The correlation between station rainfall data and RFE varied highly from place to place and between seasons. On the other hand, the correlation improved significantly when comparison was made between RFE-derived crop water satisfaction index (WRSI) and station-rainfall-derived WRSI, indicating the usefulness of the RFE for agro-hydrological applications.

  12. Nitrate fluxes to groundwater under citrus orchards in a Mediterranean climate: Observations, calibrated models, simulations and agro-hydrological conclusions

    NASA Astrophysics Data System (ADS)

    Kurtzman, Daniel; Shapira, Roi H.; Bar-Tal, Asher; Fine, Pinchas; Russo, David

    2013-08-01

    Nitrate contamination of groundwater under land used for intensive-agriculture is probably the most worrisome agro-hydrological sustainability problem worldwide. Vadose-zone samples from 0 to 9 m depth under citrus orchards overlying an unconfined aquifer were analyzed for variables controlling water flow and the fate and transport of nitrogen fertilizers. Steady-state estimates of water and NO3-N fluxes to groundwater were found to vary spatially in the ranges of 90-330 mm yr- 1 and 50-220 kg ha- 1 yr- 1, respectively. Calibration of transient models to two selected vadose-zone profiles required limiting the concentration of NO3-N in the solution that is taken up by the roots to 30 mg L- 1. Results of an independent lysimeter experiment showed a similar nitrogen-uptake regime. Simulations of past conditions revealed a significant correlation between NO3-N flux to groundwater and the previous year's precipitation. Simulations of different nitrogen-application rates showed that using half of the nitrogen fertilizer added to the irrigation water by farmers would reduce average NO3-N flux to groundwater by 70%, decrease root nitrogen uptake by 20% and reduce the average pore water NO3-N concentration in the deep vadose zone to below the Israeli drinking water standard; hence this rate of nitrogen application was found to be agro-hydrologically sustainable. Beyond the investigation of nitrate fluxes to groundwater under citrus orchards and the interesting case-study aspects, this work demonstrates a methodology that enables skillful decisions concerning joint sustainability of both the water resource and agricultural production in a common environmental setting.

  13. Simulation of semi-arid hydrological processes at different spatial resolutions using the AgroEcoSystem-Watershed (AgES-W) model

    NASA Astrophysics Data System (ADS)

    Green, T. R.; Erksine, R. H.; David, O.; Ascough, J. C., II; Kipka, H.; Lloyd, W. J.; McMaster, G. S.

    2015-12-01

    Water movement and storage within a watershed may be simulated at different spatial resolutions of land areas or hydrological response units (HRUs). Here, effects of HRU size on simulated soil water and surface runoff are tested using the AgroEcoSystem-Watershed (AgES-W) model with three different resolutions of HRUs. We studied a 56-ha agricultural watershed in northern Colorado, USA farmed primarily under a wheat-fallow rotation. The delineation algorithm was based upon topography (surface flow paths), land use (crop management strips and native grass), and mapped soil units (three types), which produced HRUs that follow the land use and soil boundaries. AgES-W model parameters that control surface and subsurface hydrology were calibrated using simulated daily soil moisture at different landscape positions and depths where soil moisture was measured hourly and averaged up to daily values. Parameter sets were both uniform and spatially variable with depth and across the watershed (5 different calibration approaches). Although forward simulations were computationally efficient (less than 1 minute each), each calibration required thousands of model runs. Execution of such large jobs was facilitated by using the Object Modeling System with the Cloud Services Innovation Platform to manage four virtual machines on a commercial web service configured with a total of 64 computational cores and 120 GB of memory. Results show how spatially distributed and averaged soil moisture and runoff at the outlet vary with different HRU delineations. The results will help guide HRU delineation, spatial resolution and parameter estimation methods for improved hydrological simulations in this and other semi-arid agricultural watersheds.

  14. Water fluxes and diffuse nitrate pollution at river basin scale: coupling of agro-economic models and hydrological approaches.

    PubMed

    Wendland, F; Kunkel, R; Bogena, H; Gömann, H; Kreins, P

    2007-01-01

    An integrated model system has been developed to estimate the impact of nitrogen reduction measures on the nitrogen load in groundwater and in river catchment areas. The focus lies on an area-wide, regionally differentiated, consistent link-up between the indicator "nitrogen balance surplus" and nitrogen charges into surface waters. As a starting point of the analysis actual nitrogen surpluses in the soil were quantified using the agro-economic RAUMIS-model, which considers the most important N-inputs to the soil and N-removals from the soil through crop harvest. The most important pathways for diffuse nitrogen inputs into river systems are modelled with the water balance model GROWA. Additionally, the time-dependent nitrogen degradation along the nitrogen pathways in soil and groundwater are modelled using the WEKU-model. The two selected river basins in Germany cover a variety of landscape units with different hydrological, hydrogeological and socio-economic characteristics. The results indicate a wide range of annual nitrogen surpluses for the rural areas between than 10 kg N ha(-1) x a(-1) and 200 kg N ha(-1) x a(-1) or more, depending on the type and intensity of farming. The level of nitrogen inputs into the surface waters is reduced because of degradation processes during transport in soil and groundwater. Policy impact analyses for a nitrogen tax and a limitation of the livestock density stress the importance of regionally adjusted measures.

  15. The AgroEcoSystem (AgES) response-function model simulates layered soil water dynamics in semi-arid Colorado: sensitivity and calibration

    USDA-ARS?s Scientific Manuscript database

    Simulation of vertical soil hydrology is a critical component of simulating even more complex soil water dynamics in space and time, including land-atmosphere and subsurface interactions. The AgroEcoSystem (AgES) model is defined here as a single land unit implementation of the full AgES-W (Watershe...

  16. Agro-hydrologic landscapes in the Upper Mississippi and Ohio River basins.

    PubMed

    Schilling, Keith E; Wolter, Calvin F; McLellan, Eileen

    2015-03-01

    A critical part of increasing conservation effectiveness is targeting the "right practice" to the "right place" where it can intercept pollutant flowpaths. Conceptually, these flowpaths can be inferred from soil and slope characteristics, and in this study, we developed an agro-hydrologic classification to identify N and P loss pathways and priority conservation practices in small watersheds in the U.S. Midwest. We developed a GIS framework to classify 11,010 small watersheds in the Upper Mississippi and Ohio River basins based on soil permeability and slope characteristics of agricultural cropland areas in each watershed. The amount of cropland in any given watershed varied from <10 to >60 %. Cropland areas were classified into five main categories, with slope classes of <2, 2-5, and >5 %, and soil drainage classes of poorly and well drained. Watersheds in the Upper Mississippi River basin (UMRB) were dominated by cropland areas in low slopes and poorly drained soils, whereas less-intensively cropped watersheds in Wisconsin and Minnesota (in the UMRB) and throughout the Ohio River basin were overwhelmingly well drained. Hydrologic differences in cropped systems indicate that a one-size-fits-all approach to conservation selection will not work. Consulting the classification scheme proposed herein may be an appropriate first-step in identifying those conservation practices that might be most appropriate for small watersheds in the basin.

  17. The Spatially-Distributed Agroecosystem-Watershed (Ages-W) Hydrologic/Water Quality (H/WQ) model for assessment of conservation effects

    USDA-ARS?s Scientific Manuscript database

    AgroEcoSystem-Watershed (AgES-W) is a modular, Java-based spatially distributed model which implements hydrologic/water quality (H/WQ) simulation components under the Object Modeling System (OMS3) environmental modeling framework. AgES-W has recently been enhanced with the addition of nitrogen (N) a...

  18. Modified version of ADM1 model for agro-waste application.

    PubMed

    Galí, A; Benabdallah, T; Astals, S; Mata-Alvarez, J

    2009-06-01

    Agro-residues account for a large proportion of the wastes generated around the world. There is thus a need for a model to simulate the anaerobic digestion processes used in their treatment. We have developed model based on ADM1, to be applied to agro-wastes. We examined and tested the biodegradability of apple, pear, orange, rape, sunflower, pig manure and glycerol wastes to be used as the basis for feeding the model. Moreover, the fractions of particulate COD (X(c)) were calculated, and the disintegration constant was obtained from biodegradability profiles, considering disintegration to be the limiting process. The other kinetic and stoichiometric parameters were taken from the ADM1 model. The model operating under mono-substrate and co-substrate conditions was then validated with batch tests. At the same time the model was validated on a continuous anaerobic reactor operating with pig manure at lab scale. In both cases the correlation between the model and the experimental results was satisfactory. We conclude that the anaerobic digestion model is a reliable tool for the design and operation of plants in which agro-wastes are treated.

  19. Evaluation of Irrigation Water Use Efficiency and Water-saving in the Middle Oasis of Heihe River Basin Using a Distributed Agro-hydrological Model

    NASA Astrophysics Data System (ADS)

    Jiang, Y.; Huang, G., Sr.; Xu, X.; Huang, Q.; Huo, Z.

    2015-12-01

    Severe water scarcity and unreasonable allocation are threatening the eco-environment in the Heihe River basin (HRB), an arid and semi-arid watershed in Northwest China. The water use in the middle oasis accounts for about 70% of the total water use in the HRB, in which over 85% are consumed by irrigated agriculture. Thus the regional assessment and improvement of irrigation water use are quite essential for water-saving and eco-environmental sustainability. This paper applied a distributed agro-hydrological model (SWAP-EPIC) integrated with ArcGIS to investigate the irrigation water use efficiency (WUE) in the middle oasis. The detailed distributed data in 2012, including soil properties, irrigation schedules, crop pattern and calendar, were collected and used in the regional simulation. The spatial-temporal distribution of LAI and evapotranspiration (ETa) from remote sensing were used as observations to calibrate the model. Results showed that the simulation data was in a good agreement with the observation one. The relative WUE (i.e. divided by the mean value) ranged from 0.77 to 1.33 in different canal command areas. Large spatial variations of WUE were mainly caused by the non-uniform distribution of irrigation water. The present irrigation performance was poor, and only 50% of total irrigation amount was finally utilized through evapotranspiration in the whole district. While nearly 24% of the irrigation water were lost through field deep percolation and 26% were wasted in canal conveyance. Further analysis of water-saving scenarios was conducted through applying the improved irrigation schedule for each crop-soil unites and increasing the canal conveyance efficiency. Prediction showed that 15% of total irrigation amount can be saved without reduction of crop yield.

  20. Modeling and validation of directional reflectance for heterogeneous agro-forestry scenarios

    NASA Astrophysics Data System (ADS)

    Yelu, Z.; Jing, L.; Qinhuo, L.; Huete, A. R.

    2015-12-01

    Landscape heterogeneity is a common natural phenomenon but is seldom considered in current radiative transfer models for predicting the surface reflectance. This paper developed an explicit analytical Radiative Transfer model for heterogeneous Agro-Forestry scenarios (RTAF) by dividing the scenario into non-boundary regions and boundary regions. The scattering contribution of the non-boundary regions that are treated as homogeneous canopies can be estimated from the SAILH model, whereas that of the boundary regions with lengths, widths, canopy heights, and orientations of the field patches, is calculated based on the bidirectional gap probability by considering the interactions and mutual shadowing effects among different patches. The hot spot factor is extended for heterogeneous scenarios, the Hapke model for soil anisotropy is incorporated, and the contributions of the direct and diffuse radiation are separately calculated. The multi-angular airborne observations and the Discrete Anisotropic Radiative Transfer (DART) model simulations were used for validating and evaluating the RTAF model over an agro-forestry scenario in Heihe River Basin, China. It indicates that the RTAF model can accurately simulate the hemispherical-directional reflectance factors (HDRFs) of the heterogeneous agro-forestry scenario, with an RMSE of 0.0016 and 0.0179 in the red and near-infrared (NIR) bands, respectively. The RTAF model was compared with two widely used models, the dominant cover type (DCT) model and the spectral linear mixture (SLM) model, which either neglected the interactions and mutual shadowing effects between the shelterbets and crops, or did not account for the contribution of the shelterbets. Results suggest that the boundary effect can significantly influence the angular distribution of the HDRFs, and consequently enlarged the HDRF variations between the backward and forward directions in the principle plane. The RTAF model reduced the maximum relative error from 25

  1. Integrated agro-hydrological modelling and economic analysis of BMPs to support decision making and policy design

    NASA Astrophysics Data System (ADS)

    Maroy, E.; Rousseau, A. N.; Hallema, D. W.

    2012-12-01

    With recent efforts and increasing control over point source pollution of freshwater, agricultural non-point pollution sources have become responsible for most of sediment and nutrient loads in North American water systems. Environmental and agricultural agencies have recognised the need for reducing eutrophication and have developed various policies to compel or encourage producers to best management practices (BMPs). Addressing diffuse pollution is challenging considering the complex and cumulative nature of transport processes, high variability in space and time, and prohibitive costs of distributed water quality monitoring. Many policy options exist to push producers to adopt environmentally desirable behaviour while keeping their activity viable, and ensure equitable costs to consumers and tax payers. On the one hand, economic instruments (subsidies, taxes, water quality markets) are designed to maximize cost-effectiveness, so that farmers optimize their production for maximum profit while implementing BMPs. On the other hand, emission standards or regulation of inputs are often easier and less costly to implement. To study economic and environmental impacts of such policies, a distributed modelling approach is needed to deal with the complexity of the system and the large environmental and socio-economic data requirements. Our objective is to integrate agro-hydrological modelling and economic analysis to support decision and policy making processes of BMP implementation. The integrated modelling system GIBSI was developed in an earlier study within the Canadian WEBs project (Watershed Evaluation of BMPs) to evaluate the influence of BMPs on water quality. The case study involved 30 and 15 year records of discharge and water quality measurements respectively, in the Beaurivage River watershed (Quebec, Canada). GIBSI provided a risk-based overview of the impact of BMPs (including vegetated riparian buffer strips, precision slurry application, conversion to

  2. An integrated modeling framework of socio-economic, biophysical, and hydrological processes in Midwest landscapes: Remote sensing data, agro-hydrological model, and agent-based model

    NASA Astrophysics Data System (ADS)

    Ding, Deng

    Intensive human-environment interactions are taking place in Midwestern agricultural systems. An integrated modeling framework is suitable for predicting dynamics of key variables of the socio-economic, biophysical, hydrological processes as well as exploring the potential transitions of system states in response to changes of the driving factors. The purpose of this dissertation is to address issues concerning the interacting processes and consequent changes in land use, water balance, and water quality using an integrated modeling framework. This dissertation is composed of three studies in the same agricultural watershed, the Clear Creek watershed in East-Central Iowa. In the first study, a parsimonious hydrologic model, the Threshold-Exceedance-Lagrangian Model (TELM), is further developed into RS-TELM (Remote Sensing TELM) to integrate remote sensing vegetation data for estimating evapotranspiration. The goodness of fit of RS-TELM is comparable to a well-calibrated SWAT (Soil and Water Assessment Tool) and even slightly superior in capturing intra-seasonal variability of stream flow. The integration of RS LAI (Leaf Area Index) data improves the model's performance especially over the agriculture dominated landscapes. The input of rainfall datasets with spatially explicit information plays a critical role in increasing the model's goodness of fit. In the second study, an agent-based model is developed to simulate farmers' decisions on crop type and fertilizer application in response to commodity and biofuel crop prices. The comparison between simulated crop land percentage and crop rotations with satellite-based land cover data suggest that farmers may be underestimating the effects that continuous corn production has on yields (yield drag). The simulation results given alternative market scenarios based on a survey of agricultural land owners and operators in the Clear Creek Watershed show that, farmers see cellulosic biofuel feedstock production in the form

  3. Virtual hydrology observatory: an immersive visualization of hydrology modeling

    NASA Astrophysics Data System (ADS)

    Su, Simon; Cruz-Neira, Carolina; Habib, Emad; Gerndt, Andreas

    2009-02-01

    The Virtual Hydrology Observatory will provide students with the ability to observe the integrated hydrology simulation with an instructional interface by using a desktop based or immersive virtual reality setup. It is the goal of the virtual hydrology observatory application to facilitate the introduction of field experience and observational skills into hydrology courses through innovative virtual techniques that mimic activities during actual field visits. The simulation part of the application is developed from the integrated atmospheric forecast model: Weather Research and Forecasting (WRF), and the hydrology model: Gridded Surface/Subsurface Hydrologic Analysis (GSSHA). Both the output from WRF and GSSHA models are then used to generate the final visualization components of the Virtual Hydrology Observatory. The various visualization data processing techniques provided by VTK are 2D Delaunay triangulation and data optimization. Once all the visualization components are generated, they are integrated into the simulation data using VRFlowVis and VR Juggler software toolkit. VR Juggler is used primarily to provide the Virtual Hydrology Observatory application with fully immersive and real time 3D interaction experience; while VRFlowVis provides the integration framework for the hydrologic simulation data, graphical objects and user interaction. A six-sided CAVETM like system is used to run the Virtual Hydrology Observatory to provide the students with a fully immersive experience.

  4. Transfer Relations Between Landscape Functions - The Hydrological Point of View

    NASA Astrophysics Data System (ADS)

    Fohrer, N.; Lenhart, T.; Eckhardt, K.; Frede, H.-G.

    EC market policies and regional subsidy programs have an enormous impact on local land use. This has far reaching consequences on various landscape functions. In the joint research project SFB299 at the Giessen University the effect of land use options on economic, ecological and hydrological landscape functions are under investigation. The continuous time step model SWAT-G (Eckhardt et al., 2000; Arnold et al., 1998) is employed to characterize the influence of land use patterns on hydrological processes. The model was calibrated and validated employing a split sample approach. For two mesoscale watersheds (Aar, 60 km2; Dietzhölze, 81 km2) located in the Lahn-Dill- Bergland, Germany, different land use scenarios were analyzed with regard to their hydrological impact. Additionally the effect of land use change was analyzed with an ecological and an agro-economic model. The impact of the stepwise changing land use was expressed as trade off relations between different landscape functions.

  5. Hydrological modelling in forested systems | Science ...

    EPA Pesticide Factsheets

    This chapter provides a brief overview of forest hydrology modelling approaches for answering important global research and management questions. Many hundreds of hydrological models have been applied globally across multiple decades to represent and predict forest hydrological processes. The focus of this chapter is on process-based models and approaches, specifically 'forest hydrology models'; that is, physically based simulation tools that quantify compartments of the forest hydrological cycle. Physically based models can be considered those that describe the conservation of mass, momentum and/or energy. The purpose of this chapter is to provide a brief overview of forest hydrology modeling approaches for answering important global research and management questions. The focus of this chapter is on process-based models and approaches, specifically “forest hydrology models”, i.e., physically-based simulation tools that quantify compartments of the forest hydrological cycle.

  6. Impacts of alternative climate information on hydrologic processes with SWAT: A comparison of NCDC, PRISM and NEXRAD datasets

    USDA-ARS?s Scientific Manuscript database

    Precipitation and temperature are two primary drivers that significantly affect hydrologic processes in a watershed. A network of land-based National Climatic Data Center (NCDC) weather stations has been typically used as a primary source of climate input for agro-ecosystem models. However, the ne...

  7. Expected changes in future agro-climatological conditions in Northeast Thailand and their differences between general circulation models

    NASA Astrophysics Data System (ADS)

    Masaki, Yoshimitsu; Ishigooka, Yasushi; Kuwagata, Tsuneo; Goto, Shinkichi; Sawano, Shinji; Hasegawa, Toshihiro

    2011-12-01

    We have studied future changes in the atmospheric and hydrological environments in Northeast Thailand from the viewpoint of risk assessment of future cultural environments in crop fields. To obtain robust and reliable estimation for future climate, ten general circulation models under three warming scenarios, B1, A1B, and A2, were used in this study. The obtained change trends show that daily maximum air temperature and precipitation will increase by 2.6°C and 4.0%, respectively, whereas soil moisture will decrease by c.a. 1% point in volumetric water content at the end of this century under the A1B scenario. Seasonal contrasts in precipitation will intensify: precipitation increases in the rainy season and precipitation decreases in the dry season. Soil moisture will slightly decrease almost throughout the year. Despite a homogeneous increase in the air temperature over Northeast Thailand, a future decrease in soil water content will show a geographically inhomogeneous distribution: Soil will experience a relative larger decrease in wetness at a shallow depth on the Khorat plateau than in the surrounding mountainous area, reflecting vegetation cover and soil texture. The predicted increase in air temperature is relatively consistent between general circulation models. In contrast, relatively large intermodel differences in precipitation, especially in long-term trends, produce unwanted bias errors in the estimation of other hydrological elements, such as soil moisture and evaporation, and cause uncertainties in projection of the agro-climatological environment. Offline hydrological simulation with a wide precipitation range is one strategy to compensate for such uncertainties and to obtain reliable risk assessment of future cultural conditions in rainfed paddy fields in Northeast Thailand.

  8. Hydrological modelling in forested systems

    EPA Science Inventory

    This chapter provides a brief overview of forest hydrology modelling approaches for answering important global research and management questions. Many hundreds of hydrological models have been applied globally across multiple decades to represent and predict forest hydrological p...

  9. Scale effect challenges in urban hydrology highlighted with a distributed hydrological model

    NASA Astrophysics Data System (ADS)

    Ichiba, Abdellah; Gires, Auguste; Tchiguirinskaia, Ioulia; Schertzer, Daniel; Bompard, Philippe; Ten Veldhuis, Marie-Claire

    2018-01-01

    Hydrological models are extensively used in urban water management, development and evaluation of future scenarios and research activities. There is a growing interest in the development of fully distributed and grid-based models. However, some complex questions related to scale effects are not yet fully understood and still remain open issues in urban hydrology. In this paper we propose a two-step investigation framework to illustrate the extent of scale effects in urban hydrology. First, fractal tools are used to highlight the scale dependence observed within distributed data input into urban hydrological models. Then an intensive multi-scale modelling work is carried out to understand scale effects on hydrological model performance. Investigations are conducted using a fully distributed and physically based model, Multi-Hydro, developed at Ecole des Ponts ParisTech. The model is implemented at 17 spatial resolutions ranging from 100 to 5 m. Results clearly exhibit scale effect challenges in urban hydrology modelling. The applicability of fractal concepts highlights the scale dependence observed within distributed data. Patterns of geophysical data change when the size of the observation pixel changes. The multi-scale modelling investigation confirms scale effects on hydrological model performance. Results are analysed over three ranges of scales identified in the fractal analysis and confirmed through modelling. This work also discusses some remaining issues in urban hydrology modelling related to the availability of high-quality data at high resolutions, and model numerical instabilities as well as the computation time requirements. The main findings of this paper enable a replacement of traditional methods of model calibration by innovative methods of model resolution alteration based on the spatial data variability and scaling of flows in urban hydrology.

  10. Growing C4 perennial grass for bioenergy using a new Agro-BGC ecosystem model

    NASA Astrophysics Data System (ADS)

    di Vittorio, A. V.; Anderson, R. S.; Miller, N. L.; Running, S. W.

    2009-12-01

    Accurate, spatially gridded estimates of bioenergy crop yields require 1) biophysically accurate crop growth models and 2) careful parameterization of unavailable inputs to these models. To meet the first requirement we have added the capacity to simulate C4 perennial grass as a bioenergy crop to the Biome-BGC ecosystem model. This new model, hereafter referred to as Agro-BGC, includes enzyme driven C4 photosynthesis, individual live and dead leaf, stem, and root carbon/nitrogen pools, separate senescence and litter fall processes, fruit growth, optional annual seeding, flood irrigation, a growing degree day phenology with a killing frost option, and a disturbance handler that effectively simulates fertilization, harvest, fire, and incremental irrigation. There are four Agro-BGC vegetation parameters that are unavailable for Panicum virgatum (switchgrass), and to meet the second requirement we have optimized the model across multiple calibration sites to obtain representative values for these parameters. We have verified simulated switchgrass yields against observations at three non-calibration sites in IL. Agro-BGC simulates switchgrass growth and yield at harvest very well at a single site. Our results suggest that a multi-site optimization scheme would be adequate for producing regional-scale estimates of bioenergy crop yields on high spatial resolution grids.

  11. Developing an Agro-Ecological Zoning Model for Tumbleweed (Salsola kali), as Energy Crop in Drylands of Argentina

    NASA Astrophysics Data System (ADS)

    Falasca, Silvia; Pitta-Alvarez, Sandra; Ulberich, Ana

    2016-12-01

    Salsola kali is considered extremely valuable as an energy crop worldwide because it adapts easily to environments with strong abiotic stresses (hydric, saline and alkaline) and produces large amounts of biomass in drylands. This species is categorized as an important weed in Argentina. The aim of this work was to design an agro-ecological zoning model for tumbleweed in Argentina, employing a Geography Information System. Based on the bioclimatic requirements for the species and the climatic data for Argentina (1981-2010 period), an agro-climatic suitability map was drawn. This map was superimposed on the saline and alkaline soil maps delineated by the Food and Agriculture Organization for dry climates, generating the agro-ecological zoning on a scale of 1 : 500 000. This zoning revealed very suitable and suitable cultivation areas on halomorphic soils. The potential growing areas extend from N of the Salta province (approximately 22° S) to the Santa Cruz province (50° S). The use of tumbleweed on halomorphic soils under semi-arid to arid conditions, for the dual purpose of forage use and source of lignocellulosic material for bioenergy, could improve agricultural productivity in these lands. Furthermore, it could also contribute to their environmental sustainability, since the species can be used to reclaim saline soils over the years. Based on international bibliography, the authors outlined an agro-ecological zoning model. This model may be applied to any part of the world, using the agro-ecological limits presented here.

  12. Genetic Programming for Automatic Hydrological Modelling

    NASA Astrophysics Data System (ADS)

    Chadalawada, Jayashree; Babovic, Vladan

    2017-04-01

    One of the recent challenges for the hydrologic research community is the need for the development of coupled systems that involves the integration of hydrologic, atmospheric and socio-economic relationships. This poses a requirement for novel modelling frameworks that can accurately represent complex systems, given, the limited understanding of underlying processes, increasing volume of data and high levels of uncertainity. Each of the existing hydrological models vary in terms of conceptualization and process representation and is the best suited to capture the environmental dynamics of a particular hydrological system. Data driven approaches can be used in the integration of alternative process hypotheses in order to achieve a unified theory at catchment scale. The key steps in the implementation of integrated modelling framework that is influenced by prior understanding and data, include, choice of the technique for the induction of knowledge from data, identification of alternative structural hypotheses, definition of rules, constraints for meaningful, intelligent combination of model component hypotheses and definition of evaluation metrics. This study aims at defining a Genetic Programming based modelling framework that test different conceptual model constructs based on wide range of objective functions and evolves accurate and parsimonious models that capture dominant hydrological processes at catchment scale. In this paper, GP initializes the evolutionary process using the modelling decisions inspired from the Superflex framework [Fenicia et al., 2011] and automatically combines them into model structures that are scrutinized against observed data using statistical, hydrological and flow duration curve based performance metrics. The collaboration between data driven and physical, conceptual modelling paradigms improves the ability to model and manage hydrologic systems. Fenicia, F., D. Kavetski, and H. H. Savenije (2011), Elements of a flexible approach

  13. Agro-tourism and ranking

    NASA Astrophysics Data System (ADS)

    Cioca, L. I.; Giurea, R.; Precazzini, I.; Ragazzi, M.; Achim, M. I.; Schiavon, M.; Rada, E. C.

    2018-05-01

    Nowadays the global tourism growth has caused a significant interest in research focused on the impact of the tourism on environment and community. The purpose of this study is to introduce a new ranking for the classification of tourist accommodation establishments with the functions of agro-tourism boarding house type by examining the sector of agro-tourism based on a research aimed to improve the economic, socio-cultural and environmental performance of agrotourism structures. This paper links the criteria for the classification of agro-tourism boarding houses (ABHs) to the impact of agro-tourism activities on the environment, enhancing an eco-friendly approach on agro-tourism activities by increasing the quality reputation of the agro-tourism products and services. Taking into account the impact on the environment, agrotourism can play an important role by protecting and conserving it.

  14. Climate Change Vulnerability of Agro-Ecosystems: Does socio-economic factors matters?

    NASA Astrophysics Data System (ADS)

    Surendran Nair, S.; Preston, B. L.; King, A. W.; Mei, R.; Post, W. M.

    2013-12-01

    Climate variability and change has direct impacts on agriculture. Despite continual adaptation to climate as well as gains in technology innovation and adoption, agriculture is still vulnerable to changes in temperature and precipitation expected in coming decades. Generally, researchers use two major methodologies to understand the vulnerability of agro-ecosystems to climate change: process-based crop models and empirical models. However, these models are not yet designed to capture the influence of socioeconomic systems on agro-ecosystem processes and outcomes.. However, socioeconomic processes are an important factor driving agro-ecological responses to biophysical processes (climate, topography and soil), because of the role of human agency in mediating the response of agro-ecosystems to climate. We have developed a framework that integrates socioeconomic and biophysical characteristics of agro-ecosystems using cluster analysis and GIS tools. This framework has been applied to the U.S. Southeast to define unique socio-ecological domains for agriculture. The results demonstrate that socioeconomic characteristics are an important factor influencing agriculture production. These results suggest that the lack of attention to socioeconomic conditions and human agency in agro-ecological modeling creates a potential bias with respect to the representation of climate change impacts.

  15. netherland hydrological modeling instrument

    NASA Astrophysics Data System (ADS)

    Hoogewoud, J. C.; de Lange, W. J.; Veldhuizen, A.; Prinsen, G.

    2012-04-01

    Netherlands Hydrological Modeling Instrument A decision support system for water basin management. J.C. Hoogewoud , W.J. de Lange ,A. Veldhuizen , G. Prinsen , The Netherlands Hydrological modeling Instrument (NHI) is the center point of a framework of models, to coherently model the hydrological system and the multitude of functions it supports. Dutch hydrological institutes Deltares, Alterra, Netherlands Environmental Assessment Agency, RWS Waterdienst, STOWA and Vewin are cooperating in enhancing the NHI for adequate decision support. The instrument is used by three different ministries involved in national water policy matters, for instance the WFD, drought management, manure policy and climate change issues. The basis of the modeling instrument is a state-of-the-art on-line coupling of the groundwater system (MODFLOW), the unsaturated zone (metaSWAP) and the surface water system (MOZART-DM). It brings together hydro(geo)logical processes from the column to the basin scale, ranging from 250x250m plots to the river Rhine and includes salt water flow. The NHI is validated with an eight year run (1998-2006) with dry and wet periods. For this run different parts of the hydrology have been compared with measurements. For instance, water demands in dry periods (e.g. for irrigation), discharges at outlets, groundwater levels and evaporation. A validation alone is not enough to get support from stakeholders. Involvement from stakeholders in the modeling process is needed. There fore to gain sufficient support and trust in the instrument on different (policy) levels a couple of actions have been taken: 1. a transparent evaluation of modeling-results has been set up 2. an extensive program is running to cooperate with regional waterboards and suppliers of drinking water in improving the NHI 3. sharing (hydrological) data via newly setup Modeling Database for local and national models 4. Enhancing the NHI with "local" information. The NHI is and has been used for many

  16. Model Calibration in Watershed Hydrology

    NASA Technical Reports Server (NTRS)

    Yilmaz, Koray K.; Vrugt, Jasper A.; Gupta, Hoshin V.; Sorooshian, Soroosh

    2009-01-01

    Hydrologic models use relatively simple mathematical equations to conceptualize and aggregate the complex, spatially distributed, and highly interrelated water, energy, and vegetation processes in a watershed. A consequence of process aggregation is that the model parameters often do not represent directly measurable entities and must, therefore, be estimated using measurements of the system inputs and outputs. During this process, known as model calibration, the parameters are adjusted so that the behavior of the model approximates, as closely and consistently as possible, the observed response of the hydrologic system over some historical period of time. This Chapter reviews the current state-of-the-art of model calibration in watershed hydrology with special emphasis on our own contributions in the last few decades. We discuss the historical background that has led to current perspectives, and review different approaches for manual and automatic single- and multi-objective parameter estimation. In particular, we highlight the recent developments in the calibration of distributed hydrologic models using parameter dimensionality reduction sampling, parameter regularization and parallel computing.

  17. Hydrological modeling in forested systems

    Treesearch

    H.E. Golden; G.R. Evenson; S. Tian; Devendra Amatya; Ge Sun

    2015-01-01

    Characterizing and quantifying interactions among components of the forest hydrological cycle is complex and usually requires a combination of field monitoring and modelling approaches (Weiler and McDonnell, 2004; National Research Council, 2008). Models are important tools for testing hypotheses, understanding hydrological processes and synthesizing experimental data...

  18. A question driven socio-hydrological modeling process

    NASA Astrophysics Data System (ADS)

    Garcia, M.; Portney, K.; Islam, S.

    2016-01-01

    Human and hydrological systems are coupled: human activity impacts the hydrological cycle and hydrological conditions can, but do not always, trigger changes in human systems. Traditional modeling approaches with no feedback between hydrological and human systems typically cannot offer insight into how different patterns of natural variability or human-induced changes may propagate through this coupled system. Modeling of coupled human-hydrological systems, also called socio-hydrological systems, recognizes the potential for humans to transform hydrological systems and for hydrological conditions to influence human behavior. However, this coupling introduces new challenges and existing literature does not offer clear guidance regarding model conceptualization. There are no universally accepted laws of human behavior as there are for the physical systems; furthermore, a shared understanding of important processes within the field is often used to develop hydrological models, but there is no such consensus on the relevant processes in socio-hydrological systems. Here we present a question driven process to address these challenges. Such an approach allows modeling structure, scope and detail to remain contingent on and adaptive to the question context. We demonstrate the utility of this process by revisiting a classic question in water resources engineering on reservoir operation rules: what is the impact of reservoir operation policy on the reliability of water supply for a growing city? Our example model couples hydrological and human systems by linking the rate of demand decreases to the past reliability to compare standard operating policy (SOP) with hedging policy (HP). The model shows that reservoir storage acts both as a buffer for variability and as a delay triggering oscillations around a sustainable level of demand. HP reduces the threshold for action thereby decreasing the delay and the oscillation effect. As a result, per capita demand decreases during

  19. Detecting hydrological changes through conceptual model

    NASA Astrophysics Data System (ADS)

    Viola, Francesco; Caracciolo, Domenico; Pumo, Dario; Francipane, Antonio; Valerio Noto, Leonardo

    2015-04-01

    Natural changes and human modifications in hydrological systems coevolve and interact in a coupled and interlinked way. If, on one hand, climatic changes are stochastic, non-steady, and affect the hydrological systems, on the other hand, human-induced changes due to over-exploitation of soils and water resources modifies the natural landscape, water fluxes and its partitioning. Indeed, the traditional assumption of static systems in hydrological analysis, which has been adopted for long time, fails whenever transient climatic conditions and/or land use changes occur. Time series analysis is a way to explore environmental changes together with societal changes; unfortunately, the not distinguishability between causes restrict the scope of this method. In order to overcome this limitation, it is possible to couple time series analysis with an opportune hydrological model, such as a conceptual hydrological model, which offers a schematization of complex dynamics acting within a basin. Assuming that model parameters represent morphological basin characteristics and that calibration is a way to detect hydrological signature at a specific moment, it is possible to argue that calibrating the model over different time windows could be a method for detecting potential hydrological changes. In order to test the capabilities of a conceptual model in detecting hydrological changes, this work presents different "in silico" experiments. A synthetic-basin is forced with an ensemble of possible future scenarios generated with a stochastic weather generator able to simulate steady and non-steady climatic conditions. The experiments refer to Mediterranean climate, which is characterized by marked seasonality, and consider the outcomes of the IPCC 5th report for describing climate evolution in the next century. In particular, in order to generate future climate change scenarios, a stochastic downscaling in space and time is carried out using realizations of an ensemble of General

  20. The Canadian Hydrological Model (CHM): A multi-scale, variable-complexity hydrological model for cold regions

    NASA Astrophysics Data System (ADS)

    Marsh, C.; Pomeroy, J. W.; Wheater, H. S.

    2016-12-01

    There is a need for hydrological land surface schemes that can link to atmospheric models, provide hydrological prediction at multiple scales and guide the development of multiple objective water predictive systems. Distributed raster-based models suffer from an overrepresentation of topography, leading to wasted computational effort that increases uncertainty due to greater numbers of parameters and initial conditions. The Canadian Hydrological Model (CHM) is a modular, multiphysics, spatially distributed modelling framework designed for representing hydrological processes, including those that operate in cold-regions. Unstructured meshes permit variable spatial resolution, allowing coarse resolutions at low spatial variability and fine resolutions as required. Model uncertainty is reduced by lessening the necessary computational elements relative to high-resolution rasters. CHM uses a novel multi-objective approach for unstructured triangular mesh generation that fulfills hydrologically important constraints (e.g., basin boundaries, water bodies, soil classification, land cover, elevation, and slope/aspect). This provides an efficient spatial representation of parameters and initial conditions, as well as well-formed and well-graded triangles that are suitable for numerical discretization. CHM uses high-quality open source libraries and high performance computing paradigms to provide a framework that allows for integrating current state-of-the-art process algorithms. The impact of changes to model structure, including individual algorithms, parameters, initial conditions, driving meteorology, and spatial/temporal discretization can be easily tested. Initial testing of CHM compared spatial scales and model complexity for a spring melt period at a sub-arctic mountain basin. The meshing algorithm reduced the total number of computational elements and preserved the spatial heterogeneity of predictions.

  1. Hydrologic connectivity: Quantitative assessments of hydrologic-enforced drainage structures in an elevation model

    USGS Publications Warehouse

    Poppenga, Sandra K.; Worstell, Bruce B.

    2016-01-01

    Elevation data derived from light detection and ranging present challenges for hydrologic modeling as the elevation surface includes bridge decks and elevated road features overlaying culvert drainage structures. In reality, water is carried through these structures; however, in the elevation surface these features impede modeled overland surface flow. Thus, a hydrologically-enforced elevation surface is needed for hydrodynamic modeling. In the Delaware River Basin, hydrologic-enforcement techniques were used to modify elevations to simulate how constructed drainage structures allow overland surface flow. By calculating residuals between unfilled and filled elevation surfaces, artificially pooled depressions that formed upstream of constructed drainage structure features were defined, and elevation values were adjusted by generating transects at the location of the drainage structures. An assessment of each hydrologically-enforced drainage structure was conducted using field-surveyed culvert and bridge coordinates obtained from numerous public agencies, but it was discovered the disparate drainage structure datasets were not comprehensive enough to assess all remotely located depressions in need of hydrologic-enforcement. Alternatively, orthoimagery was interpreted to define drainage structures near each depression, and these locations were used as reference points for a quantitative hydrologic-enforcement assessment. The orthoimagery-interpreted reference points resulted in a larger corresponding sample size than the assessment between hydrologic-enforced transects and field-surveyed data. This assessment demonstrates the viability of rules-based hydrologic-enforcement that is needed to achieve hydrologic connectivity, which is valuable for hydrodynamic models in sensitive coastal regions. Hydrologic-enforced elevation data are also essential for merging with topographic/bathymetric elevation data that extend over vulnerable urbanized areas and dynamic coastal

  2. A Community Data Model for Hydrologic Observations

    NASA Astrophysics Data System (ADS)

    Tarboton, D. G.; Horsburgh, J. S.; Zaslavsky, I.; Maidment, D. R.; Valentine, D.; Jennings, B.

    2006-12-01

    The CUAHSI Hydrologic Information System project is developing information technology infrastructure to support hydrologic science. Hydrologic information science involves the description of hydrologic environments in a consistent way, using data models for information integration. This includes a hydrologic observations data model for the storage and retrieval of hydrologic observations in a relational database designed to facilitate data retrieval for integrated analysis of information collected by multiple investigators. It is intended to provide a standard format to facilitate the effective sharing of information between investigators and to facilitate analysis of information within a single study area or hydrologic observatory, or across hydrologic observatories and regions. The observations data model is designed to store hydrologic observations and sufficient ancillary information (metadata) about the observations to allow them to be unambiguously interpreted and used and provide traceable heritage from raw measurements to usable information. The design is based on the premise that a relational database at the single observation level is most effective for providing querying capability and cross dimension data retrieval and analysis. This premise is being tested through the implementation of a prototype hydrologic observations database, and the development of web services for the retrieval of data from and ingestion of data into the database. These web services hosted by the San Diego Supercomputer center make data in the database accessible both through a Hydrologic Data Access System portal and directly from applications software such as Excel, Matlab and ArcGIS that have Standard Object Access Protocol (SOAP) capability. This paper will (1) describe the data model; (2) demonstrate the capability for representing diverse data in the same database; (3) demonstrate the use of the database from applications software for the performance of hydrologic analysis

  3. An Educational Model for Hands-On Hydrology Education

    NASA Astrophysics Data System (ADS)

    AghaKouchak, A.; Nakhjiri, N.; Habib, E. H.

    2014-12-01

    This presentation provides an overview of a hands-on modeling tool developed for students in civil engineering and earth science disciplines to help them learn the fundamentals of hydrologic processes, model calibration, sensitivity analysis, uncertainty assessment, and practice conceptual thinking in solving engineering problems. The toolbox includes two simplified hydrologic models, namely HBV-EDU and HBV-Ensemble, designed as a complement to theoretical hydrology lectures. The models provide an interdisciplinary application-oriented learning environment that introduces the hydrologic phenomena through the use of a simplified conceptual hydrologic model. The toolbox can be used for in-class lab practices and homework assignments, and assessment of students' understanding of hydrological processes. Using this modeling toolbox, students can gain more insights into how hydrological processes (e.g., precipitation, snowmelt and snow accumulation, soil moisture, evapotranspiration and runoff generation) are interconnected. The educational toolbox includes a MATLAB Graphical User Interface (GUI) and an ensemble simulation scheme that can be used for teaching more advanced topics including uncertainty analysis, and ensemble simulation. Both models have been administered in a class for both in-class instruction and a final project, and students submitted their feedback about the toolbox. The results indicate that this educational software had a positive impact on students understanding and knowledge of hydrology.

  4. Snow hydrology in a general circulation model

    NASA Technical Reports Server (NTRS)

    Marshall, Susan; Roads, John O.; Glatzmaier, Gary

    1994-01-01

    A snow hydrology has been implemented in an atmospheric general circulation model (GCM). The snow hydrology consists of parameterizations of snowfall and snow cover fraction, a prognostic calculation of snow temperature, and a model of the snow mass and hydrologic budgets. Previously, only snow albedo had been included by a specified snow line. A 3-year GCM simulation with this now more complete surface hydrology is compared to a previous GCM control run with the specified snow line, as well as with observations. In particular, the authors discuss comparisons of the atmospheric and surface hydrologic budgets and the surface energy budget for U.S. and Canadian areas. The new snow hydrology changes the annual cycle of the surface moisture and energy budgets in the model. There is a noticeable shift in the runoff maximum from winter in the control run to spring in the snow hydrology run. A substantial amount of GCM winter precipitation is now stored in the seasonal snowpack. Snow cover also acts as an important insulating layer between the atmosphere and the ground. Wintertime soil temperatures are much higher in the snow hydrology experiment than in the control experiment. Seasonal snow cover is important for dampening large fluctuations in GCM continental skin temperature during the Northern Hemisphere winter. Snow depths and snow extent show good agreement with observations over North America. The geographic distribution of maximum depths is not as well simulated by the model due, in part, to the coarse resolution of the model. The patterns of runoff are qualitatively and quantitatively similar to observed patterns of streamflow averaged over the continental United States. The seasonal cycles of precipitation and evaporation are also reasonably well simulated by the model, although their magnitudes are larger than is observed. This is due, in part, to a cold bias in this model, which results in a dry model atmosphere and enhances the hydrologic cycle everywhere.

  5. Mathematical analysis of the impact mechanism of information platform on agro-product supply chain and agro-product competitiveness

    NASA Astrophysics Data System (ADS)

    Jiang, Qi-Jie; Jin, Mao-Zhu; Ren, Pei-Yu

    2017-04-01

    How to optimize agro-product supply chain to promote its operating efficiency so as to enhance the competitiveness of regional agricultural products has posed a problem to academic circles, business circles and governments of various levels. One way to solve this problem is to introduce an information platform into the supply chain, which this essay focuses on. Firstly, a review of existing research findings concerning the agro-product competitiveness, agro-product supply chain (ASC) and information platform was given. Secondly, we constructed a mathematical model to analyze the impact of information platform on the bullwhip effect in ASC. Thirdly, another mathematical model was constructed to help compare and analyze the impact of information platform on information acquisition of members in ASC. The research results show that the implantation of information platform can mitigate the bullwhip effect in ASC, and members can determine order amount or production more close to the actual market demand. And also the information platform can reduce the time for members in ASC to get information from other members. Besides, information platform can help ASC to alleviate information asymmetry among upstream and downstream members. Furthermore, researches about the operating mechanism and pattern, technical feature and running structure of the information platform, along with their impacts on agro-product supply chain and the competitiveness of agricultural products need to be advanced.

  6. Event-based hydrological modeling for detecting dominant hydrological process and suitable model strategy for semi-arid catchments

    NASA Astrophysics Data System (ADS)

    Huang, Pengnian; Li, Zhijia; Chen, Ji; Li, Qiaoling; Yao, Cheng

    2016-11-01

    To simulate the hydrological processes in semi-arid areas properly is still challenging. This study assesses the impact of different modeling strategies on simulating flood processes in semi-arid catchments. Four classic hydrological models, TOPMODEL, XINANJIANG (XAJ), SAC-SMA and TANK, were selected and applied to three semi-arid catchments in North China. Based on analysis and comparison of the simulation results of these classic models, four new flexible models were constructed and used to further investigate the suitability of various modeling strategies for semi-arid environments. Numerical experiments were also designed to examine the performances of the models. The results show that in semi-arid catchments a suitable model needs to include at least one nonlinear component to simulate the main process of surface runoff generation. If there are more than two nonlinear components in the hydrological model, they should be arranged in parallel, rather than in series. In addition, the results show that the parallel nonlinear components should be combined by multiplication rather than addition. Moreover, this study reveals that the key hydrological process over semi-arid catchments is the infiltration excess surface runoff, a non-linear component.

  7. Accelerating advances in continental domain hydrologic modeling

    USGS Publications Warehouse

    Archfield, Stacey A.; Clark, Martyn; Arheimer, Berit; Hay, Lauren E.; McMillan, Hilary; Kiang, Julie E.; Seibert, Jan; Hakala, Kirsti; Bock, Andrew R.; Wagener, Thorsten; Farmer, William H.; Andreassian, Vazken; Attinger, Sabine; Viglione, Alberto; Knight, Rodney; Markstrom, Steven; Over, Thomas M.

    2015-01-01

    In the past, hydrologic modeling of surface water resources has mainly focused on simulating the hydrologic cycle at local to regional catchment modeling domains. There now exists a level of maturity among the catchment, global water security, and land surface modeling communities such that these communities are converging toward continental domain hydrologic models. This commentary, written from a catchment hydrology community perspective, provides a review of progress in each community toward this achievement, identifies common challenges the communities face, and details immediate and specific areas in which these communities can mutually benefit one another from the convergence of their research perspectives. Those include: (1) creating new incentives and infrastructure to report and share model inputs, outputs, and parameters in data services and open access, machine-independent formats for model replication or reanalysis; (2) ensuring that hydrologic models have: sufficient complexity to represent the dominant physical processes and adequate representation of anthropogenic impacts on the terrestrial water cycle, a process-based approach to model parameter estimation, and appropriate parameterizations to represent large-scale fluxes and scaling behavior; (3) maintaining a balance between model complexity and data availability as well as uncertainties; and (4) quantifying and communicating significant advancements toward these modeling goals.

  8. ERM model analysis for adaptation to hydrological model errors

    NASA Astrophysics Data System (ADS)

    Baymani-Nezhad, M.; Han, D.

    2018-05-01

    Hydrological conditions are changed continuously and these phenomenons generate errors on flood forecasting models and will lead to get unrealistic results. Therefore, to overcome these difficulties, a concept called model updating is proposed in hydrological studies. Real-time model updating is one of the challenging processes in hydrological sciences and has not been entirely solved due to lack of knowledge about the future state of the catchment under study. Basically, in terms of flood forecasting process, errors propagated from the rainfall-runoff model are enumerated as the main source of uncertainty in the forecasting model. Hence, to dominate the exciting errors, several methods have been proposed by researchers to update the rainfall-runoff models such as parameter updating, model state updating, and correction on input data. The current study focuses on investigations about the ability of rainfall-runoff model parameters to cope with three types of existing errors, timing, shape and volume as the common errors in hydrological modelling. The new lumped model, the ERM model, has been selected for this study to evaluate its parameters for its use in model updating to cope with the stated errors. Investigation about ten events proves that the ERM model parameters can be updated to cope with the errors without the need to recalibrate the model.

  9. Hydrological Modeling in Alaska with WRF-Hydro

    NASA Astrophysics Data System (ADS)

    Elmer, N. J.; Zavodsky, B.; Molthan, A.

    2017-12-01

    The operational National Water Model (NWM), implemented in August 2016, is an instantiation of the Weather Research and Forecasting hydrological extension package (WRF-Hydro). Currently, the NWM only covers the contiguous United States, but will be expanded to include an Alaska domain in the future. It is well known that Alaska presents several hydrological modeling challenges, including unique arctic/sub-arctic hydrological processes not observed elsewhere in the United States and a severe lack of in-situ observations for model initialization. This project sets up an experimental version of WRF-Hydro in Alaska mimicking the NWM to gauge the ability of WRF-Hydro to represent hydrological processes in Alaska and identify model calibration challenges. Recent and upcoming launches of hydrology-focused NASA satellite missions such as the Soil Moisture Active Passive (SMAP) and Surface Water Ocean Topography (SWOT) expand the spatial and temporal coverage of observations in Alaska, so this study also lays the groundwork for assimilating these NASA datasets into WRF-Hydro in the future.

  10. Assimilation of remote sensing observations into a continuous distributed hydrological model: impacts on the hydrologic cycle

    NASA Astrophysics Data System (ADS)

    Laiolo, Paola; Gabellani, Simone; Campo, Lorenzo; Cenci, Luca; Silvestro, Francesco; Delogu, Fabio; Boni, Giorgio; Rudari, Roberto

    2015-04-01

    The reliable estimation of hydrological variables (e.g. soil moisture, evapotranspiration, surface temperature) in space and time is of fundamental importance in operational hydrology to improve the forecast of the rainfall-runoff response of catchments and, consequently, flood predictions. Nowadays remote sensing can offer a chance to provide good space-time estimates of several hydrological variables and then improve hydrological model performances especially in environments with scarce in-situ data. This work investigates the impact of the assimilation of different remote sensing products on the hydrological cycle by using a continuous physically based distributed hydrological model. Three soil moisture products derived by ASCAT (Advanced SCATterometer) are used to update the model state variables. The satellite-derived products are assimilated into the hydrological model using different assimilation techniques: a simple nudging and the Ensemble Kalman Filter. Moreover two assimilation strategies are evaluated to assess the impact of assimilating the satellite products at model spatial resolution or at the satellite scale. The experiments are carried out for three Italian catchments on multi year period. The benefits on the model predictions of discharge, LST, evapotranspiration and soil moisture dynamics are tested and discussed.

  11. Hydrological system dynamics of glaciated Karnali River Basin Nepal Himalaya using J2000 Hydrological model

    NASA Astrophysics Data System (ADS)

    Khatiwada, K. R.; Nepal, S.; Panthi, J., Sr.; Shrestha, M.

    2015-12-01

    Hydrological modelling plays an important role in understanding hydrological processes of a catchment. In the context of climate change, the understanding of hydrological characteristic of the catchment is very vital to understand how the climate change will affect the hydrological regime. This research facilitates in better understanding of the hydrological system dynamics of a himalayan mountainous catchment in western Nepal. The Karnali River, longest river flowing inside Nepal, is one of the three major basins of Nepal, having the area of 45269 sq. km. is unique. The basin has steep topography and high mountains to the northern side. The 40% of the basin is dominated by forest land while other land cover are: grass land, bare rocky land etc. About 2% of the areas in basin is covered by permanent glacier apart from that about 12% of basin has the snow and ice cover. There are 34 meteorological stations distributed across the basin. A process oriented distributed J2000 hydrologial model has been applied to understand the hydrological system dynamics. The model application provides distributed output of various hydrological components. The J2000 model applies Hydrological Response Unit (HRU) as a modelling entity. With 6861 HRU and 1010 reaches, the model was calibrated (1981-1999) and validated (2000-2004) at a daily scale using split-sample test. The model is able to capture the overall hydrological dynamics well. The rising limbs and recession limbs are simulated equally and with satisfactory ground water conditions. Based on the graphical and statistical evaluation of the model performance the model is able to simulate hydrological processes fairly well. Calibration shows that Nash Sutcliffe efficiency is 0.91, coefficient of determination is 0.92 Initial observation shows that during the pre-monsoon season(March to May) the glacial runoff is 25% of the total discharge while in the monsoon(June to September) season it is only 13%. The surface runoff

  12. Modeling urbanized watershed flood response changes with distributed hydrological model: key hydrological processes, parameterization and case studies

    NASA Astrophysics Data System (ADS)

    Chen, Y.

    2017-12-01

    Urbanization is the world development trend for the past century, and the developing countries have been experiencing much rapider urbanization in the past decades. Urbanization brings many benefits to human beings, but also causes negative impacts, such as increasing flood risk. Impact of urbanization on flood response has long been observed, but quantitatively studying this effect still faces great challenges. For example, setting up an appropriate hydrological model representing the changed flood responses and determining accurate model parameters are very difficult in the urbanized or urbanizing watershed. In the Pearl River Delta area, rapidest urbanization has been observed in China for the past decades, and dozens of highly urbanized watersheds have been appeared. In this study, a physically based distributed watershed hydrological model, the Liuxihe model is employed and revised to simulate the hydrological processes of the highly urbanized watershed flood in the Pearl River Delta area. A virtual soil type is then defined in the terrain properties dataset, and its runoff production and routing algorithms are added to the Liuxihe model. Based on a parameter sensitive analysis, the key hydrological processes of a highly urbanized watershed is proposed, that provides insight into the hydrological processes and for parameter optimization. Based on the above analysis, the model is set up in the Songmushan watershed where there is hydrological data observation. A model parameter optimization and updating strategy is proposed based on the remotely sensed LUC types, which optimizes model parameters with PSO algorithm and updates them based on the changed LUC types. The model parameters in Songmushan watershed are regionalized at the Pearl River Delta area watersheds based on the LUC types of the other watersheds. A dozen watersheds in the highly urbanized area of Dongguan City in the Pearl River Delta area were studied for the flood response changes due to

  13. Teaching hydrological modelling as a subsidiary subject

    NASA Astrophysics Data System (ADS)

    Hörmann, G.; Schmalz, B.; Fohrer, N.

    2009-04-01

    The department of hydrology and water resources management is part of the Ecology Center of Kiel University, an interdisciplinary research organization. We teach hydrology for geographers, biologists, agricultural engineers and ecologists. Hydrological modeling is part of the curriculum since 1988. It has moved from the subject for specialists to a basic component of all hydrological courses. During the first year, we focussed on in-depth teaching of theory and practice of one big model, but the students found it hard to follow and beyond practical problems. During the last years we switched to a broader, but more shallow policy. Modeling is now part of nearly all courses, but remains limited to mostly 2-4 days of teaching. We now present only very basic theory and leave it to the students to discover the details during the practical work with pre-installed data sets. The poster shows how the models SWAT, Hydrus, Coupmodel, SIMPEL and PC-Raster are embedded in the hydrological curriculum and what kind of problems we experienced in teaching.

  14. Improved hydrological modeling using AGWA; incorporation of different management practices in hydrological modeling.

    NASA Astrophysics Data System (ADS)

    Vithanage, J.; Miller, S. N.; Paige, G. B.; Liu, T.

    2017-12-01

    We present a novel way to simulate the effects of rangeland management decisions in a GIS-based hydrologic modeling toolkit. We have implemented updates to the Automated Geospatial Watershed Assessment tool (AGWA) in which a landscape can be broken into management units (e.g., high intensity grazing, low intensity grazing, fire management, and unmanaged), each of which is assigned a different hydraulic conductivity (Ks) parameter in KINEmatic Runoff and EROSion model (KINEROS2). These updates are designed to provide modeling support to land managers tasked with rangeland watershed management planning and/or monitoring, and evaluation of water resources management. Changes to hydrologic processes and resulting hydrographs and sedigraphs are simulated within the AGWA framework. Case studies are presented in which a user selects various management scenarios and design storms, and the model identifies areas that become susceptible to change as a consequence of management decisions. The baseline (unmanaged) scenario is built using commonly available GIS data, after which the watershed is subdivided into management units. We used an array of design storms with various return periods and frequencies to evaluate the impact of management practices while changing the scale of watershed. Watershed parameters governing interception, infiltration, and surface runoff were determined with the aid of literature published on research studies carried out in the Walnut Gulch Experimental Watershed in southeast Arizona. We observed varied, but significant changes in hydrological responses (runoff) with different management practices as well with varied scales of watersheds. Results show that the toolkit can be used to quantify potential hydrologic change as a result of unitized land use decision-making.

  15. Validation of a national hydrological model

    NASA Astrophysics Data System (ADS)

    McMillan, H. K.; Booker, D. J.; Cattoën, C.

    2016-10-01

    Nationwide predictions of flow time-series are valuable for development of policies relating to environmental flows, calculating reliability of supply to water users, or assessing risk of floods or droughts. This breadth of model utility is possible because various hydrological signatures can be derived from simulated flow time-series. However, producing national hydrological simulations can be challenging due to strong environmental diversity across catchments and a lack of data available to aid model parameterisation. A comprehensive and consistent suite of test procedures to quantify spatial and temporal patterns in performance across various parts of the hydrograph is described and applied to quantify the performance of an uncalibrated national rainfall-runoff model of New Zealand. Flow time-series observed at 485 gauging stations were used to calculate Nash-Sutcliffe efficiency and percent bias when simulating between-site differences in daily series, between-year differences in annual series, and between-site differences in hydrological signatures. The procedures were used to assess the benefit of applying a correction to the modelled flow duration curve based on an independent statistical analysis. They were used to aid understanding of climatological, hydrological and model-based causes of differences in predictive performance by assessing multiple hypotheses that describe where and when the model was expected to perform best. As the procedures produce quantitative measures of performance, they provide an objective basis for model assessment that could be applied when comparing observed daily flow series with competing simulated flow series from any region-wide or nationwide hydrological model. Model performance varied in space and time with better scores in larger and medium-wet catchments, and in catchments with smaller seasonal variations. Surprisingly, model performance was not sensitive to aquifer fraction or rain gauge density.

  16. iTree-Hydro: Snow hydrology update for the urban forest hydrology model

    Treesearch

    Yang Yang; Theodore A. Endreny; David J. Nowak

    2011-01-01

    This article presents snow hydrology updates made to iTree-Hydro, previously called the Urban Forest Effects—Hydrology model. iTree-Hydro Version 1 was a warm climate model developed by the USDA Forest Service to provide a process-based planning tool with robust water quantity and quality predictions given data limitations common to most urban areas. Cold climate...

  17. Can the super model (SUMO) method improve hydrological simulations? Exploratory tests with the GR hydrological models

    NASA Astrophysics Data System (ADS)

    Santos, Léonard; Thirel, Guillaume; Perrin, Charles

    2017-04-01

    Errors made by hydrological models may come from a problem in parameter estimation, uncertainty on observed measurements, numerical problems and from the model conceptualization that simplifies the reality. Here we focus on this last issue of hydrological modeling. One of the solutions to reduce structural uncertainty is to use a multimodel method, taking advantage of the great number and the variability of existing hydrological models. In particular, because different models are not similarly good in all situations, using multimodel approaches can improve the robustness of modeled outputs. Traditionally, in hydrology, multimodel methods are based on the output of the model (the simulated flow series). The aim of this poster is to introduce a different approach based on the internal variables of the models. The method is inspired by the SUper MOdel (SUMO, van den Berge et al., 2011) developed for climatology. The idea of the SUMO method is to correct the internal variables of a model taking into account the values of the internal variables of (an)other model(s). This correction is made bilaterally between the different models. The ensemble of the different models constitutes a super model in which all the models exchange information on their internal variables with each other at each time step. Due to this continuity in the exchanges, this multimodel algorithm is more dynamic than traditional multimodel methods. The method will be first tested using two GR4J models (in a state-space representation) with different parameterizations. The results will be presented and compared to traditional multimodel methods that will serve as benchmarks. In the future, other rainfall-runoff models will be used in the super model. References van den Berge, L. A., Selten, F. M., Wiegerinck, W., and Duane, G. S. (2011). A multi-model ensemble method that combines imperfect models through learning. Earth System Dynamics, 2(1) :161-177.

  18. Subdivision of Texas watersheds for hydrologic modeling.

    DOT National Transportation Integrated Search

    2009-06-01

    The purpose of this report is to present a set of findings and examples for subdivision of watersheds for hydrologic modeling. Three approaches were used to examine the impact of watershed subdivision on modeled hydrologic response: (1) An equal-area...

  19. Balancing model complexity and measurements in hydrology

    NASA Astrophysics Data System (ADS)

    Van De Giesen, N.; Schoups, G.; Weijs, S. V.

    2012-12-01

    The Data Processing Inequality implies that hydrological modeling can only reduce, and never increase, the amount of information available in the original data used to formulate and calibrate hydrological models: I(X;Z(Y)) ≤ I(X;Y). Still, hydrologists around the world seem quite content building models for "their" watersheds to move our discipline forward. Hydrological models tend to have a hybrid character with respect to underlying physics. Most models make use of some well established physical principles, such as mass and energy balances. One could argue that such principles are based on many observations, and therefore add data. These physical principles, however, are applied to hydrological models that often contain concepts that have no direct counterpart in the observable physical universe, such as "buckets" or "reservoirs" that fill up and empty out over time. These not-so-physical concepts are more like the Artificial Neural Networks and Support Vector Machines of the Artificial Intelligence (AI) community. Within AI, one quickly came to the realization that by increasing model complexity, one could basically fit any dataset but that complexity should be controlled in order to be able to predict unseen events. The more data are available to train or calibrate the model, the more complex it can be. Many complexity control approaches exist in AI, with Solomonoff inductive inference being one of the first formal approaches, the Akaike Information Criterion the most popular, and Statistical Learning Theory arguably being the most comprehensive practical approach. In hydrology, complexity control has hardly been used so far. There are a number of reasons for that lack of interest, the more valid ones of which will be presented during the presentation. For starters, there are no readily available complexity measures for our models. Second, some unrealistic simplifications of the underlying complex physics tend to have a smoothing effect on possible model

  20. Modeling Hydrological Extremes in the Anthropocene

    NASA Astrophysics Data System (ADS)

    Di Baldassarre, Giuliano; Martinez, Fabian; Kalantari, Zahra; Viglione, Alberto

    2017-04-01

    Hydrological studies have investigated human impacts on hydrological extremes, i.e. droughts and floods, while social studies have explored human responses and adaptation to them. Yet, there is still little understanding about the dynamics resulting from two-way feedbacks, i.e. both impacts and responses. Traditional risk assessment methods therefore fail to assess future dynamics, and thus risk reduction strategies built on these methods can lead to unintended consequences in the medium-long term. Here we review the dynamics resulting from the reciprocal links between society and hydrological extremes, and describe initial efforts to model floods and droughts in the Anthropocene. In particular, we first discuss the need for a novel approach to explicitly account for human interactions with both hydrological extremes, and then present a stylized model simulating the reciprocal effects between droughts, foods and reservoir operation rules. Unprecedented opportunities offered by the growing availability of global data and worldwide archives to uncover the mutual shaping of hydrological extremes and society across places and scales are also discussed.

  1. Modeling the Hydrological Regime of Turkana Lake (Kenya, Ethiopia) by Combining Spatially Distributed Hydrological Modeling and Remote Sensing Datasets

    NASA Astrophysics Data System (ADS)

    Anghileri, D.; Kaelin, A.; Peleg, N.; Fatichi, S.; Molnar, P.; Roques, C.; Longuevergne, L.; Burlando, P.

    2017-12-01

    Hydrological modeling in poorly gauged basins can benefit from the use of remote sensing datasets although there are challenges associated with the mismatch in spatial and temporal scales between catchment scale hydrological models and remote sensing products. We model the hydrological processes and long-term water budget of the Lake Turkana catchment, a transboundary basin between Kenya and Ethiopia, by integrating several remote sensing products into a spatially distributed and physically explicit model, Topkapi-ETH. Lake Turkana is the world largest desert lake draining a catchment of 145'500 km2. It has three main contributing rivers: the Omo river, which contributes most of the annual lake inflow, the Turkwel river, and the Kerio rivers, which contribute the remaining part. The lake levels have shown great variations in the last decades due to long-term climate fluctuations and the regulation of three reservoirs, Gibe I, II, and III, which significantly alter the hydrological seasonality. Another large reservoir is planned and may be built in the next decade, generating concerns about the fate of Lake Turkana in the long run because of this additional anthropogenic pressure and increasing evaporation driven by climate change. We consider different remote sensing datasets, i.e., TRMM-V7 for precipitation, MERRA-2 for temperature, as inputs to the spatially distributed hydrological model. We validate the simulation results with other remote sensing datasets, i.e., GRACE for total water storage anomalies, GLDAS-NOAH for soil moisture, ERA-Interim/Land for surface runoff, and TOPEX/Poseidon for satellite altimetry data. Results highlight how different remote sensing products can be integrated into a hydrological modeling framework accounting for their relative uncertainties. We also carried out simulations with the artificial reservoirs planned in the north part of the catchment and without any reservoirs, to assess their impacts on the catchment hydrological

  2. Advancing the Implementation of Hydrologic Models as Web-based Applications

    NASA Astrophysics Data System (ADS)

    Dahal, P.; Tarboton, D. G.; Castronova, A. M.

    2017-12-01

    Advanced computer simulations are required to understand hydrologic phenomenon such as rainfall-runoff response, groundwater hydrology, snow hydrology, etc. Building a hydrologic model instance to simulate a watershed requires investment in data (diverse geospatial datasets such as terrain, soil) and computer resources, typically demands a wide skill set from the analyst, and the workflow involved is often difficult to reproduce. This work introduces a web-based prototype infrastructure in the form of a web application that provides researchers with easy to use access to complete hydrological modeling functionality. This includes creating the necessary geospatial and forcing data, preparing input files for a model by applying complex data preprocessing, running the model for a user defined watershed, and saving the results to a web repository. The open source Tethys Platform was used to develop the web app front-end Graphical User Interface (GUI). We used HydroDS, a webservice that provides data preparation processing capability to support backend computations used by the app. Results are saved in HydroShare, a hydrologic information system that supports the sharing of hydrologic data, model and analysis tools. The TOPographic Kinematic APproximation and Integration (TOPKAPI) model served as the example for which we developed a complete hydrologic modeling service to demonstrate the approach. The final product is a complete modeling system accessible through the web to create input files, and run the TOPKAPI hydrologic model for a watershed of interest. We are investigating similar functionality for the preparation of input to Regional Hydro-Ecological Simulation System (RHESSys). Key Words: hydrologic modeling, web services, hydrologic information system, HydroShare, HydroDS, Tethys Platform

  3. Open source data assimilation framework for hydrological modeling

    NASA Astrophysics Data System (ADS)

    Ridler, Marc; Hummel, Stef; van Velzen, Nils; Katrine Falk, Anne; Madsen, Henrik

    2013-04-01

    An open-source data assimilation framework is proposed for hydrological modeling. Data assimilation (DA) in hydrodynamic and hydrological forecasting systems has great potential to improve predictions and improve model result. The basic principle is to incorporate measurement information into a model with the aim to improve model results by error minimization. Great strides have been made to assimilate traditional in-situ measurements such as discharge, soil moisture, hydraulic head and snowpack into hydrologic models. More recently, remotely sensed data retrievals of soil moisture, snow water equivalent or snow cover area, surface water elevation, terrestrial water storage and land surface temperature have been successfully assimilated in hydrological models. The assimilation algorithms have become increasingly sophisticated to manage measurement and model bias, non-linear systems, data sparsity (time & space) and undetermined system uncertainty. It is therefore useful to use a pre-existing DA toolbox such as OpenDA. OpenDA is an open interface standard for (and free implementation of) a set of tools to quickly implement DA and calibration for arbitrary numerical models. The basic design philosophy of OpenDA is to breakdown DA into a set of building blocks programmed in object oriented languages. To implement DA, a model must interact with OpenDA to create model instances, propagate the model, get/set variables (or parameters) and free the model once DA is completed. An open-source interface for hydrological models exists capable of all these tasks: OpenMI. OpenMI is an open source standard interface already adopted by key hydrological model providers. It defines a universal approach to interact with hydrological models during simulation to exchange data during runtime, thus facilitating the interactions between models and data sources. The interface is flexible enough so that models can interact even if the model is coded in a different language, represent

  4. Human impact parameterization in global hydrological models improves estimates of monthly discharges and hydrological extremes: a multi-model validation study

    NASA Astrophysics Data System (ADS)

    Veldkamp, Ted; Ward, Philip; de Moel, Hans; Aerts, Jeroen; Muller Schmied, Hannes; Portmann, Felix; Zhao, Fang; Gerten, Dieter; Masaki, Yoshimitsu; Pokhrel, Yadu; Satoh, Yusuke; Gosling, Simon; Zaherpour, Jamal; Wada, Yoshihide

    2017-04-01

    Human impacts on freshwater resources and hydrological features form the core of present-day water related hazards, like flooding, droughts, water scarcity, and water quality issues. Driven by the societal and scientific needs to correctly model such water related hazards a fair amount of resources has been invested over the past decades to represent human activities and their interactions with the hydrological cycle in global hydrological models (GHMs). Use of these GHMs - including the human dimension - is widespread, especially in water resources research. Evaluation or comparative assessments of the ability of such GHMs to represent real-world hydrological conditions are, unfortunately, however often limited to (near-)natural river basins. Such studies are, therefore, not able to test the model representation of human activities and its associated impact on estimates of freshwater resources or assessments of hydrological extremes. Studies that did perform a validation exercise - including the human dimension and looking into managed catchments - either focused only on one hydrological model, and/or incorporated only a few data points (i.e. river basins) for validation. To date, a comprehensive comparative analysis that evaluates whether and where incorporating the human dimension actually improves the performance of different GHMs with respect to their representation of real-world hydrological conditions and extremes is missing. The absence of such study limits the potential benchmarking of GHMs and their outcomes in hydrological hazard and risk assessments significantly, potentially hampering incorporation of GHMs and their modelling results in actual policy making and decision support with respect to water resources management. To address this issue, we evaluate in this study the performance of five state-of-the-art GHMs that include anthropogenic activities in their modelling scheme, with respect to their representation of monthly discharges and hydrological

  5. Integrating hydrologic modeling web services with online data sharing to prepare, store, and execute models in hydrology

    NASA Astrophysics Data System (ADS)

    Gan, T.; Tarboton, D. G.; Dash, P. K.; Gichamo, T.; Horsburgh, J. S.

    2017-12-01

    Web based apps, web services and online data and model sharing technology are becoming increasingly available to support research. This promises benefits in terms of collaboration, platform independence, transparency and reproducibility of modeling workflows and results. However, challenges still exist in real application of these capabilities and the programming skills researchers need to use them. In this research we combined hydrologic modeling web services with an online data and model sharing system to develop functionality to support reproducible hydrologic modeling work. We used HydroDS, a system that provides web services for input data preparation and execution of a snowmelt model, and HydroShare, a hydrologic information system that supports the sharing of hydrologic data, model and analysis tools. To make the web services easy to use, we developed a HydroShare app (based on the Tethys platform) to serve as a browser based user interface for HydroDS. In this integration, HydroDS receives web requests from the HydroShare app to process the data and execute the model. HydroShare supports storage and sharing of the results generated by HydroDS web services. The snowmelt modeling example served as a use case to test and evaluate this approach. We show that, after the integration, users can prepare model inputs or execute the model through the web user interface of the HydroShare app without writing program code. The model input/output files and metadata describing the model instance are stored and shared in HydroShare. These files include a Python script that is automatically generated by the HydroShare app to document and reproduce the model input preparation workflow. Once stored in HydroShare, inputs and results can be shared with other users, or published so that other users can directly discover, repeat or modify the modeling work. This approach provides a collaborative environment that integrates hydrologic web services with a data and model sharing

  6. Fallon, Nevada FORGE Thermal-Hydrological-Mechanical Models

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Blankenship, Doug; Sonnenthal, Eric

    Archive contains thermal-mechanical simulation input/output files. Included are files which fall into the following categories: ( 1 ) Spreadsheets with various input parameter calculations ( 2 ) Final Simulation Inputs ( 3 ) Native-State Thermal-Hydrological Model Input File Folders ( 4 ) Native-State Thermal-Hydrological-Mechanical Model Input Files ( 5 ) THM Model Stimulation Cases See 'File Descriptions.xlsx' resource below for additional information on individual files.

  7. Multi-model analysis in hydrological prediction

    NASA Astrophysics Data System (ADS)

    Lanthier, M.; Arsenault, R.; Brissette, F.

    2017-12-01

    Hydrologic modelling, by nature, is a simplification of the real-world hydrologic system. Therefore ensemble hydrological predictions thus obtained do not present the full range of possible streamflow outcomes, thereby producing ensembles which demonstrate errors in variance such as under-dispersion. Past studies show that lumped models used in prediction mode can return satisfactory results, especially when there is not enough information available on the watershed to run a distributed model. But all lumped models greatly simplify the complex processes of the hydrologic cycle. To generate more spread in the hydrologic ensemble predictions, multi-model ensembles have been considered. In this study, the aim is to propose and analyse a method that gives an ensemble streamflow prediction that properly represents the forecast probabilities and reduced ensemble bias. To achieve this, three simple lumped models are used to generate an ensemble. These will also be combined using multi-model averaging techniques, which generally generate a more accurate hydrogram than the best of the individual models in simulation mode. This new predictive combined hydrogram is added to the ensemble, thus creating a large ensemble which may improve the variability while also improving the ensemble mean bias. The quality of the predictions is then assessed on different periods: 2 weeks, 1 month, 3 months and 6 months using a PIT Histogram of the percentiles of the real observation volumes with respect to the volumes of the ensemble members. Initially, the models were run using historical weather data to generate synthetic flows. This worked for individual models, but not for the multi-model and for the large ensemble. Consequently, by performing data assimilation at each prediction period and thus adjusting the initial states of the models, the PIT Histogram could be constructed using the observed flows while allowing the use of the multi-model predictions. The under-dispersion has been

  8. airGRteaching: an R-package designed for teaching hydrology with lumped hydrological models

    NASA Astrophysics Data System (ADS)

    Thirel, Guillaume; Delaigue, Olivier; Coron, Laurent; Andréassian, Vazken; Brigode, Pierre

    2017-04-01

    Lumped hydrological models are useful and convenient tools for research, engineering and educational purposes. They propose catchment-scale representations of the precipitation-discharge relationship. Thanks to their limited data requirements, they can be easily implemented and run. With such models, it is possible to simulate a number of hydrological key processes over the catchment with limited structural and parametric complexity, typically evapotranspiration, runoff, underground losses, etc. The Hydrology Group at Irstea (Antony) has been developing a suite of rainfall-runoff models over the past 30 years. This resulted in a suite of models running at different time steps (from hourly to annual) applicable for various issues including water balance estimation, forecasting, simulation of impacts and scenario testing. Recently, Irstea has developed an easy-to-use R-package (R Core Team, 2016), called airGR (Coron et al., 2016, 2017), to make these models widely available. Although its initial target public was hydrological modellers, the package is already used for educational purposes. Indeed, simple models allow for rapidly visualising the effects of parameterizations and model components on flows hydrographs. In order to avoid the difficulties that students may have when manipulating R and datasets, we developed (Delaigue and Coron, 2016): - Three simplified functions to prepare data, calibrate a model and run a simulation - Simplified and dynamic plot functions - A shiny (Chang et al., 2016) interface that connects this R-package to a browser-based visualisation tool. On this interface, the students can use different hydrological models (including the possibility to use a snow-accounting model), manually modify their parameters and automatically calibrate their parameters with diverse objective functions. One of the visualisation tabs of the interface includes observed precipitation and temperature, simulated snowpack (if any), observed and simulated

  9. Cyberinfrastructure to Support Collaborative and Reproducible Computational Hydrologic Modeling

    NASA Astrophysics Data System (ADS)

    Goodall, J. L.; Castronova, A. M.; Bandaragoda, C.; Morsy, M. M.; Sadler, J. M.; Essawy, B.; Tarboton, D. G.; Malik, T.; Nijssen, B.; Clark, M. P.; Liu, Y.; Wang, S. W.

    2017-12-01

    Creating cyberinfrastructure to support reproducibility of computational hydrologic models is an important research challenge. Addressing this challenge requires open and reusable code and data with machine and human readable metadata, organized in ways that allow others to replicate results and verify published findings. Specific digital objects that must be tracked for reproducible computational hydrologic modeling include (1) raw initial datasets, (2) data processing scripts used to clean and organize the data, (3) processed model inputs, (4) model results, and (5) the model code with an itemization of all software dependencies and computational requirements. HydroShare is a cyberinfrastructure under active development designed to help users store, share, and publish digital research products in order to improve reproducibility in computational hydrology, with an architecture supporting hydrologic-specific resource metadata. Researchers can upload data required for modeling, add hydrology-specific metadata to these resources, and use the data directly within HydroShare.org for collaborative modeling using tools like CyberGIS, Sciunit-CLI, and JupyterHub that have been integrated with HydroShare to run models using notebooks, Docker containers, and cloud resources. Current research aims to implement the Structure For Unifying Multiple Modeling Alternatives (SUMMA) hydrologic model within HydroShare to support hypothesis-driven hydrologic modeling while also taking advantage of the HydroShare cyberinfrastructure. The goal of this integration is to create the cyberinfrastructure that supports hypothesis-driven model experimentation, education, and training efforts by lowering barriers to entry, reducing the time spent on informatics technology and software development, and supporting collaborative research within and across research groups.

  10. Revisiting an interdisciplinary hydrological modelling project. A socio-hydrology (?) example from the early 2000s

    NASA Astrophysics Data System (ADS)

    Seidl, Roman; Barthel, Roland

    2016-04-01

    Interdisciplinary scientific and societal knowledge plays an increasingly important role in global change research. Also, in the field of water resources interdisciplinarity as well as cooperation with stakeholders from outside academia have been recognized as important. In this contribution, we revisit an integrated regional modelling system (DANUBIA), which was developed by an interdisciplinary team of researchers and relied on stakeholder participation in the framework of the GLOWA-Danube project from 2001 to 2011 (Mauser and Prasch 2016). As the model was developed before the current increase in literature on participatory modelling and interdisciplinarity, we ask how a socio-hydrology approach would have helped and in what way it would have made the work different. The present contribution firstly presents the interdisciplinary concept of DANUBIA, mainly with focus on the integration of human behaviour in a spatially explicit, process-based numerical modelling system (Roland Barthel, Janisch, Schwarz, Trifkovic, Nickel, Schulz, and Mauser 2008; R. Barthel, Nickel, Meleg, Trifkovic, and Braun 2005). Secondly, we compare the approaches to interdisciplinarity in GLOWA-Danube with concepts and ideas presented by socio-hydrology. Thirdly, we frame DANUBIA and a review of key literature on socio-hydrology in the context of a survey among hydrologists (N = 184). This discussion is used to highlight gaps and opportunities of the socio-hydrology approach. We show that the interdisciplinary aspect of the project and the participatory process of stakeholder integration in DANUBIA were not entirely successful. However, important insights were gained and important lessons were learnt. Against the background of these experiences we feel that in its current state, socio-hydrology is still lacking a plan for knowledge integration. Moreover, we consider necessary that socio-hydrology takes into account the lessons learnt from these earlier examples of knowledge integration

  11. OpenDA-WFLOW framework for improving hydrologic predictions using distributed hydrologic models

    NASA Astrophysics Data System (ADS)

    Weerts, Albrecht; Schellekens, Jaap; Kockx, Arno; Hummel, Stef

    2017-04-01

    Data assimilation (DA) holds considerable potential for improving hydrologic predictions (Liu et al., 2012) and increase the potential for early warning and/or smart water management. However, advances in hydrologic DA research have not yet been adequately or timely implemented in operational forecast systems to improve the skill of forecasts for better informed real-world decision making. The objective of this work is to highlight the development of a generic linkage of the open source OpenDA package and the open source community hydrologic modeling framework Openstreams/WFLOW and its application in operational hydrological forecasting on various spatial scales. The coupling between OpenDA and Openstreams/wflow framework is based on the emerging standard Basic Model Interface (BMI) as advocated by CSDMS using cross-platform webservices (i.e. Apache Thrift) developed by Hut et al. (2016). The potential application of the OpenDA-WFLOW for operational hydrologic forecasting including its integration with Delft-FEWS (used by more than 40 operational forecast centers around the world (Werner et al., 2013)) is demonstrated by the presented case studies. We will also highlight the possibility to give real-time insight into the working of the DA methods applied for supporting the forecaster as mentioned as one of the burning issues by Liu et al., (2012).

  12. Macroscale hydrologic modeling of ecologically relevant flow metrics

    NASA Astrophysics Data System (ADS)

    Wenger, Seth J.; Luce, Charles H.; Hamlet, Alan F.; Isaak, Daniel J.; Neville, Helen M.

    2010-09-01

    Stream hydrology strongly affects the structure of aquatic communities. Changes to air temperature and precipitation driven by increased greenhouse gas concentrations are shifting timing and volume of streamflows potentially affecting these communities. The variable infiltration capacity (VIC) macroscale hydrologic model has been employed at regional scales to describe and forecast hydrologic changes but has been calibrated and applied mainly to large rivers. An important question is how well VIC runoff simulations serve to answer questions about hydrologic changes in smaller streams, which are important habitat for many fish species. To answer this question, we aggregated gridded VIC outputs within the drainage basins of 55 streamflow gages in the Pacific Northwest United States and compared modeled hydrographs and summary metrics to observations. For most streams, several ecologically relevant aspects of the hydrologic regime were accurately modeled, including center of flow timing, mean annual and summer flows and frequency of winter floods. Frequencies of high and low flows in the summer were not well predicted, however. Predictions were worse for sites with strong groundwater influence, and some sites showed errors that may result from limitations in the forcing climate data. Higher resolution (1/16th degree) modeling provided small improvements over lower resolution (1/8th degree). Despite some limitations, the VIC model appears capable of representing several ecologically relevant hydrologic characteristics in streams, making it a useful tool for understanding the effects of hydrology in delimiting species distributions and predicting the potential effects of climate shifts on aquatic organisms.

  13. Hydrologic Predictions in the Anthropocene: Exploration with Co-evolutionary Socio-hydrologic Models

    NASA Astrophysics Data System (ADS)

    Sivapalan, Murugesu; Tian, Fuqiang; Liu, Dengfeng

    2013-04-01

    Socio-hydrology studies the co-evolution and self-organization of humans in the hydrologic landscape, which requires a thorough understanding of the complex interactions between humans and water. On the one hand, the nature of water availability greatly impacts the development of society. On the other hand, humans can significantly alter the spatio-temporal distribution of water and in this way provide feedback to the society itself. The human-water system functions underlying such complex human-water interactions are not well understood. Exploratory models with the appropriate level of simplification in any given area can be valuable to understand these functions and the self-organization associated with socio-hydrology. In this study, a simple coupled modeling framework for socio-hydrology co-evolution is developed, and is used to illustrate the explanatory power of such models. In the Tarim River, humans depend heavily on agricultural production (other industries can be ignored for a start), and the social processes can be described principally by two variables, i.e., irrigated-area and human population. The eco-hydrological processes are expressed in terms of area under natural vegetation and stream discharge. The study area is the middle and the lower reaches of the Tarim River, which is divided into two modeling units, i.e. middle reach and lower reach. In each modeling unit, four ordinary differential equations are used to simulate the dynamics of the hydrological system represented by stream discharge, ecological system represented by area under natural vegetation, the economic system represented by irrigated area under agriculture and social system represented by human population. The four dominant variables are coupled together by several internal variables. For example, the stream discharge is coupled to irrigated area by the colonization rate and mortality rate of the irrigated area in the middle reach and the irrigated area is coupled to stream

  14. Revising Hydrology of a Land Surface Model

    NASA Astrophysics Data System (ADS)

    Le Vine, Nataliya; Butler, Adrian; McIntyre, Neil; Jackson, Christopher

    2015-04-01

    Land Surface Models (LSMs) are key elements in guiding adaptation to the changing water cycle and the starting points to develop a global hyper-resolution model of the terrestrial water, energy and biogeochemical cycles. However, before this potential is realised, there are some fundamental limitations of LSMs related to how meaningfully hydrological fluxes and stores are represented. An important limitation is the simplistic or non-existent representation of the deep subsurface in LSMs; and another is the lack of connection of LSM parameterisations to relevant hydrological information. In this context, the paper uses a case study of the JULES (Joint UK Land Environmental Simulator) LSM applied to the Kennet region in Southern England. The paper explores the assumptions behind JULES hydrology, adapts the model structure and optimises the coupling with the ZOOMQ3D regional groundwater model. The analysis illustrates how three types of information can be used to improve the model's hydrology: a) observations, b) regionalized information, and c) information from an independent physics-based model. It is found that: 1) coupling to the groundwater model allows realistic simulation of streamflows; 2) a simple dynamic lower boundary improves upon JULES' stationary unit gradient condition; 3) a 1D vertical flow in the unsaturated zone is sufficient; however there is benefit in introducing a simple dual soil moisture retention curve; 4) regionalized information can be used to describe soil spatial heterogeneity. It is concluded that relatively simple refinements to the hydrology of JULES and its parameterisation method can provide a substantial step forward in realising its potential as a high-resolution multi-purpose model.

  15. Advancing Collaboration through Hydrologic Data and Model Sharing

    NASA Astrophysics Data System (ADS)

    Tarboton, D. G.; Idaszak, R.; Horsburgh, J. S.; Ames, D. P.; Goodall, J. L.; Band, L. E.; Merwade, V.; Couch, A.; Hooper, R. P.; Maidment, D. R.; Dash, P. K.; Stealey, M.; Yi, H.; Gan, T.; Castronova, A. M.; Miles, B.; Li, Z.; Morsy, M. M.

    2015-12-01

    HydroShare is an online, collaborative system for open sharing of hydrologic data, analytical tools, and models. It supports the sharing of and collaboration around "resources" which are defined primarily by standardized metadata, content data models for each resource type, and an overarching resource data model based on the Open Archives Initiative's Object Reuse and Exchange (OAI-ORE) standard and a hierarchical file packaging system called "BagIt". HydroShare expands the data sharing capability of the CUAHSI Hydrologic Information System by broadening the classes of data accommodated to include geospatial and multidimensional space-time datasets commonly used in hydrology. HydroShare also includes new capability for sharing models, model components, and analytical tools and will take advantage of emerging social media functionality to enhance information about and collaboration around hydrologic data and models. It also supports web services and server/cloud based computation operating on resources for the execution of hydrologic models and analysis and visualization of hydrologic data. HydroShare uses iRODS as a network file system for underlying storage of datasets and models. Collaboration is enabled by casting datasets and models as "social objects". Social functions include both private and public sharing, formation of collaborative groups of users, and value-added annotation of shared datasets and models. The HydroShare web interface and social media functions were developed using the Django web application framework coupled to iRODS. Data visualization and analysis is supported through the Tethys Platform web GIS software stack. Links to external systems are supported by RESTful web service interfaces to HydroShare's content. This presentation will introduce the HydroShare functionality developed to date and describe ongoing development of functionality to support collaboration and integration of data and models.

  16. Publishing and sharing of hydrologic models through WaterHUB

    NASA Astrophysics Data System (ADS)

    Merwade, V.; Ruddell, B. L.; Song, C.; Zhao, L.; Kim, J.; Assi, A.

    2011-12-01

    Most hydrologists use hydrologic models to simulate the hydrologic processes to understand hydrologic pathways and fluxes for research, decision making and engineering design. Once these tasks are complete including publication of results, the models generally are not published or made available to the public for further use and improvement. Although publication or sharing of models is not required for journal publications, sharing of models may open doors for new collaborations, and avoids duplication of efforts if other researchers are interested in simulating a particular watershed for which a model already exists. For researchers, who are interested in sharing models, there are limited avenues to publishing their models to the wider community. Towards filling this gap, a prototype cyberinfrastructure (CI), called WaterHUB, is developed for sharing hydrologic data and modeling tools in an interactive environment. To test the utility of WaterHUB for sharing hydrologic models, a system to publish and share SWAT (Soil Water Assessment Tool) is developed. Users can utilize WaterHUB to search and download existing SWAT models, and also upload new SWAT models. Metadata such as the name of the watershed, name of the person or agency who developed the model, simulation period, time step, and list of calibrated parameters also published with individual model.

  17. Hydrologic Modeling of Boreal Forest Ecosystems

    NASA Technical Reports Server (NTRS)

    Haddeland, I.; Lettenmaier, D. P.

    1995-01-01

    This study focused on the hydrologic response, including vegetation water use, of two test regions within the Boreal-Ecosystem-Atmosphere Study (BOREAS) region in the Canadian boreal forest, one north of Prince Albert, Saskatchewan, and the other near Thompson, Manitoba. Fluxes of moisture and heat were studied using a spatially distributed hydrology soil-vegetation-model (DHSVM).

  18. Spectroscopic measurements of soybeans used to parameterize physiological traits in the AgroIBIS ecosystem model

    NASA Astrophysics Data System (ADS)

    Singh, A.; Serbin, S.; Kucharik, C. J.; Townsend, P. A.

    2014-12-01

    Ecosystem models such AgroIBIS require detailed parameterizations of numerous vegetation traits related to leaf structure, biochemistry and photosynthetic capacity to properly assess plant carbon assimilation and yield response to environmental variability. In general, these traits are estimated from a limited number of field measurements or sourced from the literature, but rarely is the full observed range of variability in these traits utilized in modeling activities. In addition, pathogens and pests, such as the exotic soybean aphid (Aphis glycines), which affects photosynthetic pathways in soybean plants by feeding on phloem and sap, can potentially impact plant productivity and yields. Capturing plant responses to pest pressure in conjunction with environmental variability is of considerable interest to managers and the scientific community alike. In this research, we employed full-range (400-2500 nm) field and laboratory spectroscopy to rapidly characterize the leaf biochemical and physiological traits, namely foliar nitrogen, specific leaf area (SLA) and the maximum rate of RuBP carboxylation by the enzyme RuBisCo (Vcmax) in soybean plants, which experienced a broad range of environmental conditions and soybean aphid pressures. We utilized near-surface spectroscopic remote sensing measurements as a means to capture the spatial and temporal patterns of aphid impacts across broad aphid pressure levels. In addition, we used the spectroscopic data to generate a much larger dataset of key model parameters required by AgroIBIS than would be possible through traditional measurements of biochemistry and leaf-level gas exchange. The use of spectroscopic retrievals of soybean traits allowed us to better characterize the variability of plant responses associated with aphid pressure to more accurately model the likely impacts of soybean aphid on soybeans. Our next steps include the coupling of the information derived from our spectral measurements with the Agro

  19. Exploration of warm-up period in conceptual hydrological modelling

    NASA Astrophysics Data System (ADS)

    Kim, Kue Bum; Kwon, Hyun-Han; Han, Dawei

    2018-01-01

    One of the important issues in hydrological modelling is to specify the initial conditions of the catchment since it has a major impact on the response of the model. Although this issue should be a high priority among modelers, it has remained unaddressed by the community. The typical suggested warm-up period for the hydrological models has ranged from one to several years, which may lead to an underuse of data. The model warm-up is an adjustment process for the model to reach an 'optimal' state, where internal stores (e.g., soil moisture) move from the estimated initial condition to an 'optimal' state. This study explores the warm-up period of two conceptual hydrological models, HYMOD and IHACRES, in a southwestern England catchment. A series of hydrologic simulations were performed for different initial soil moisture conditions and different rainfall amounts to evaluate the sensitivity of the warm-up period. Evaluation of the results indicates that both initial wetness and rainfall amount affect the time required for model warm up, although it depends on the structure of the hydrological model. Approximately one and a half months are required for the model to warm up in HYMOD for our study catchment and climatic conditions. In addition, it requires less time to warm up under wetter initial conditions (i.e., saturated initial conditions). On the other hand, approximately six months is required for warm-up in IHACRES, and the wet or dry initial conditions have little effect on the warm-up period. Instead, the initial values that are close to the optimal value result in less warm-up time. These findings have implications for hydrologic model development, specifically in determining soil moisture initial conditions and warm-up periods to make full use of the available data, which is very important for catchments with short hydrological records.

  20. Gsflow-py: An integrated hydrologic model development tool

    NASA Astrophysics Data System (ADS)

    Gardner, M.; Niswonger, R. G.; Morton, C.; Henson, W.; Huntington, J. L.

    2017-12-01

    Integrated hydrologic modeling encompasses a vast number of processes and specifications, variable in time and space, and development of model datasets can be arduous. Model input construction techniques have not been formalized or made easily reproducible. Creating the input files for integrated hydrologic models (IHM) requires complex GIS processing of raster and vector datasets from various sources. Developing stream network topology that is consistent with the model resolution digital elevation model is important for robust simulation of surface water and groundwater exchanges. Distribution of meteorologic parameters over the model domain is difficult in complex terrain at the model resolution scale, but is necessary to drive realistic simulations. Historically, development of input data for IHM models has required extensive GIS and computer programming expertise which has restricted the use of IHMs to research groups with available financial, human, and technical resources. Here we present a series of Python scripts that provide a formalized technique for the parameterization and development of integrated hydrologic model inputs for GSFLOW. With some modifications, this process could be applied to any regular grid hydrologic model. This Python toolkit automates many of the necessary and laborious processes of parameterization, including stream network development and cascade routing, land coverages, and meteorological distribution over the model domain.

  1. Jump-Diffusion models and structural changes for asset forecasting in hydrology

    NASA Astrophysics Data System (ADS)

    Tranquille Temgoua, André Guy; Martel, Richard; Chang, Philippe J. J.; Rivera, Alfonso

    2017-04-01

    Impacts of climate change on surface water and groundwater are of concern in many regions of the world since water is an essential natural resource. Jump-Diffusion models are generally used in economics and other related fields but not in hydrology. The potential application could be made for hydrologic data series analysis and forecast. The present study uses Jump-Diffusion models by adding structural changes to detect fluctuations in hydrologic processes in relationship with climate change. The model implicitly assumes that modifications in rivers' flowrates can be divided into three categories: (a) normal changes due to irregular precipitation events especially in tropical regions causing major disturbance in hydrologic processes (this component is modelled by a discrete Brownian motion); (b) abnormal, sudden and non-persistent modifications in hydrologic proceedings are handled by Poisson processes; (c) the persistence of hydrologic fluctuations characterized by structural changes in hydrological data related to climate variability. The objective of this paper is to add structural changes in diffusion models with jumps, in order to capture the persistence of hydrologic fluctuations. Indirectly, the idea is to observe if there are structural changes of discharge/recharge over the study area, and to find an efficient and flexible model able of capturing a wide variety of hydrologic processes. Structural changes in hydrological data are estimated using the method of nonlinear discrete filters via Method of Simulated Moments (MSM). An application is given using sensitive parameters such as baseflow index and recession coefficient to capture discharge/recharge. Historical dataset are examined by the Volume Spread Analysis (VSA) to detect real time and random perturbations in hydrologic processes. The application of the method allows establishing more accurate hydrologic parameters. The impact of this study is perceptible in forecasting floods and groundwater

  2. Impact of a statistical bias correction on the projected simulated hydrological changes obtained from three GCMs and two hydrology models

    NASA Astrophysics Data System (ADS)

    Hagemann, Stefan; Chen, Cui; Haerter, Jan O.; Gerten, Dieter; Heinke, Jens; Piani, Claudio

    2010-05-01

    Future climate model scenarios depend crucially on their adequate representation of the hydrological cycle. Within the European project "Water and Global Change" (WATCH) special care is taken to couple state-of-the-art climate model output to a suite of hydrological models. This coupling is expected to lead to a better assessment of changes in the hydrological cycle. However, due to the systematic model errors of climate models, their output is often not directly applicable as input for hydrological models. Thus, the methodology of a statistical bias correction has been developed, which can be used for correcting climate model output to produce internally consistent fields that have the same statistical intensity distribution as the observations. As observations, global re-analysed daily data of precipitation and temperature are used that are obtained in the WATCH project. We will apply the bias correction to global climate model data of precipitation and temperature from the GCMs ECHAM5/MPIOM, CNRM-CM3 and LMDZ-4, and intercompare the bias corrected data to the original GCM data and the observations. Then, the orginal and the bias corrected GCM data will be used to force two global hydrology models: (1) the hydrological model of the Max Planck Institute for Meteorology (MPI-HM) consisting of the Simplified Land surface (SL) scheme and the Hydrological Discharge (HD) model, and (2) the dynamic vegetation model LPJmL operated by the Potsdam Institute for Climate Impact Research. The impact of the bias correction on the projected simulated hydrological changes will be analysed, and the resulting behaviour of the two hydrology models will be compared.

  3. Approaches to modelling hydrology and ecosystem interactions

    NASA Astrophysics Data System (ADS)

    Silberstein, Richard P.

    2014-05-01

    As the pressures of industry, agriculture and mining on groundwater resources increase there is a burgeoning un-met need to be able to capture these multiple, direct and indirect stresses in a formal framework that will enable better assessment of impact scenarios. While there are many catchment hydrological models and there are some models that represent ecological states and change (e.g. FLAMES, Liedloff and Cook, 2007), these have not been linked in any deterministic or substantive way. Without such coupled eco-hydrological models quantitative assessments of impacts from water use intensification on water dependent ecosystems under changing climate are difficult, if not impossible. The concept would include facility for direct and indirect water related stresses that may develop around mining and well operations, climate stresses, such as rainfall and temperature, biological stresses, such as diseases and invasive species, and competition such as encroachment from other competing land uses. Indirect water impacts could be, for example, a change in groundwater conditions has an impact on stream flow regime, and hence aquatic ecosystems. This paper reviews previous work examining models combining ecology and hydrology with a view to developing a conceptual framework linking a biophysically defensable model that combines ecosystem function with hydrology. The objective is to develop a model capable of representing the cumulative impact of multiple stresses on water resources and associated ecosystem function.

  4. Remote sensing applications to hydrologic modeling

    NASA Technical Reports Server (NTRS)

    Dozier, J.; Estes, J. E.; Simonett, D. S.; Davis, R.; Frew, J.; Marks, D.; Schiffman, K.; Souza, M.; Witebsky, E.

    1977-01-01

    An energy balance snowmelt model for rugged terrain was devised and coupled to a flow model. A literature review of remote sensing applications to hydrologic modeling was included along with a software development outline.

  5. Improving student comprehension of the interconnectivity of the hydrologic cycle with a novel 'hydrology toolbox', integrated watershed model, and companion textbook

    NASA Astrophysics Data System (ADS)

    Huning, L. S.; Margulis, S. A.

    2013-12-01

    Concepts in introductory hydrology courses are often taught in the context of process-based modeling that ultimately is integrated into a watershed model. In an effort to reduce the learning curve associated with applying hydrologic concepts to real-world applications, we developed and incorporated a 'hydrology toolbox' that complements a new, companion textbook into introductory undergraduate hydrology courses. The hydrology toolbox contains the basic building blocks (functions coded in MATLAB) for an integrated spatially-distributed watershed model that makes hydrologic topics (e.g. precipitation, snow, radiation, evaporation, unsaturated flow, infiltration, groundwater, and runoff) more user-friendly and accessible for students. The toolbox functions can be used in a modular format so that students can study individual hydrologic processes and become familiar with the hydrology toolbox. This approach allows such courses to emphasize understanding and application of hydrologic concepts rather than computer coding or programming. While topics in introductory hydrology courses are often introduced and taught independently or semi-independently, they are inherently interconnected. These toolbox functions are therefore linked together at the end of the course to reinforce a holistic understanding of how these hydrologic processes are measured, interconnected, and modeled. They are integrated into a spatially-distributed watershed model or numerical laboratory where students can explore a range of topics such as rainfall-runoff modeling, urbanization, deforestation, watershed response to changes in parameters or forcings, etc. Model output can readily be visualized and analyzed by students to understand watershed response in a real river basin or a simple 'toy' basin. These tools complement the textbook, each of which has been well received by students in multiple hydrology courses with various disciplinary backgrounds. The same governing equations that students have

  6. Description of the National Hydrologic Model for use with the Precipitation-Runoff Modeling System (PRMS)

    USGS Publications Warehouse

    Regan, R. Steven; Markstrom, Steven L.; Hay, Lauren E.; Viger, Roland J.; Norton, Parker A.; Driscoll, Jessica M.; LaFontaine, Jacob H.

    2018-01-08

    This report documents several components of the U.S. Geological Survey National Hydrologic Model of the conterminous United States for use with the Precipitation-Runoff Modeling System (PRMS). It provides descriptions of the (1) National Hydrologic Model, (2) Geospatial Fabric for National Hydrologic Modeling, (3) PRMS hydrologic simulation code, (4) parameters and estimation methods used to compute spatially and temporally distributed default values as required by PRMS, (5) National Hydrologic Model Parameter Database, and (6) model extraction tool named Bandit. The National Hydrologic Model Parameter Database contains values for all PRMS parameters used in the National Hydrologic Model. The methods and national datasets used to estimate all the PRMS parameters are described. Some parameter values are derived from characteristics of topography, land cover, soils, geology, and hydrography using traditional Geographic Information System methods. Other parameters are set to long-established default values and computation of initial values. Additionally, methods (statistical, sensitivity, calibration, and algebraic) were developed to compute parameter values on the basis of a variety of nationally-consistent datasets. Values in the National Hydrologic Model Parameter Database can periodically be updated on the basis of new parameter estimation methods and as additional national datasets become available. A companion ScienceBase resource provides a set of static parameter values as well as images of spatially-distributed parameters associated with PRMS states and fluxes for each Hydrologic Response Unit across the conterminuous United States.

  7. Testing the Structure of Hydrological Models using Genetic Programming

    NASA Astrophysics Data System (ADS)

    Selle, B.; Muttil, N.

    2009-04-01

    Genetic Programming is able to systematically explore many alternative model structures of different complexity from available input and response data. We hypothesised that genetic programming can be used to test the structure hydrological models and to identify dominant processes in hydrological systems. To test this, genetic programming was used to analyse a data set from a lysimeter experiment in southeastern Australia. The lysimeter experiment was conducted to quantify the deep percolation response under surface irrigated pasture to different soil types, water table depths and water ponding times during surface irrigation. Using genetic programming, a simple model of deep percolation was consistently evolved in multiple model runs. This simple and interpretable model confirmed the dominant process contributing to deep percolation represented in a conceptual model that was published earlier. Thus, this study shows that genetic programming can be used to evaluate the structure of hydrological models and to gain insight about the dominant processes in hydrological systems.

  8. A comparison of hydrological deformation using GPS and global hydrological model for the Eurasian plate

    NASA Astrophysics Data System (ADS)

    Li, Zhen; Yue, Jianping; Li, Wang; Lu, Dekai; Li, Xiaogen

    2017-08-01

    The 0.5° × 0.5° gridded hydrological loading from Global Land Surface Discharge Model (LSDM) mass distributions is adopted for 32 GPS sites on the Eurasian plate from January 2010 to January 2014. When the heights of these sites that have been corrected for the effects of non-tidal atmospheric and ocean loading are adjusted by the hydrological loading deformation, more than one third of the root-mean-square (RMS) values of the GPS height variability become larger. After analyzing the results by continuous wavelet transform (CWT) and wavelet transform coherence (WTC), we confirm that hydrological loading primarily contributes to the annual variations in GPS heights. Further, the cross wavelet transform (XWT) is used to investigate the relative phase between the time series of GPS heights and hydrological deformation, and it is indicated that the annual oscillations in the two time series are physically related for some sites; other geophysical effect, GPS systematic errors and hydrological modeling errors could result in the phase asynchrony between GPS and hydrological loading signals for the other sites. Consequently, the phase asynchrony confirms that the annual fluctuations in GPS observations result from a combination of geophysical signals and systematic errors.

  9. Delineating wetland catchments and modeling hydrologic ...

    EPA Pesticide Factsheets

    In traditional watershed delineation and topographic modeling, surface depressions are generally treated as spurious features and simply removed from a digital elevation model (DEM) to enforce flow continuity of water across the topographic surface to the watershed outlets. In reality, however, many depressions in the DEM are actual wetland landscape features with seasonal to permanent inundation patterning characterized by nested hierarchical structures and dynamic filling–spilling–merging surface-water hydrological processes. Differentiating and appropriately processing such ecohydrologically meaningful features remains a major technical terrain-processing challenge, particularly as high-resolution spatial data are increasingly used to support modeling and geographic analysis needs. The objectives of this study were to delineate hierarchical wetland catchments and model their hydrologic connectivity using high-resolution lidar data and aerial imagery. The graph-theory-based contour tree method was used to delineate the hierarchical wetland catchments and characterize their geometric and topological properties. Potential hydrologic connectivity between wetlands and streams were simulated using the least-cost-path algorithm. The resulting flow network delineated potential flow paths connecting wetland depressions to each other or to the river network on scales finer than those available through the National Hydrography Dataset. The results demonstrated that

  10. How to handle spatial heterogeneity in hydrological models.

    NASA Astrophysics Data System (ADS)

    Loritz, Ralf; Neuper, Malte; Gupta, Hoshin; Zehe, Erwin

    2017-04-01

    The amount of data we observe in our environmental systems is larger than ever. This leads to a new kind of problem where hydrological modelers can have access to large datasets with various quantitative and qualitative observations but are uncertain about the information content with respect to the hydrological functioning of a landscape. For example digital elevation models obviously contain plenty of information about the topography of a landscape; however the question of relevance for Hydrology is how much of this information is important for the hydrological functioning of a landscape. This kind of question is not limited to topography and we can ask similar questions when handling distributed rainfall data or geophysical images. In this study we would like to show how one can separate dominant patterns in the landscape from idiosyncratic system details. We use a 2D numerical hillslope model in combination with an extensive research data set to test a variety of different model setups that are built upon different landscape characteristics and run by different rainfalls measurements. With the help of information theory based measures we can identify and learn how much heterogeneity is really necessary for successful hydrological simulations and how much of it we can neglect.

  11. An integrated crop and hydrologic modeling system to estimate hydrologic impacts of crop irrigation demands

    Treesearch

    R.T. McNider; C. Handyside; K. Doty; W.L. Ellenburg; J.F. Cruise; J.R. Christy; D. Moss; V. Sharda; G. Hoogenboom; Peter Caldwell

    2015-01-01

    The present paper discusses a coupled gridded crop modeling and hydrologic modeling system that can examine the benefits of irrigation and costs of irrigation and the coincident impact of the irrigation water withdrawals on surface water hydrology. The system is applied to the Southeastern U.S. The system tools to be discussed include a gridded version (GriDSSAT) of...

  12. Advances in the spatially distributed ages-w model: parallel computation, java connection framework (JCF) integration, and streamflow/nitrogen dynamics assessment

    USDA-ARS?s Scientific Manuscript database

    AgroEcoSystem-Watershed (AgES-W) is a modular, Java-based spatially distributed model which implements hydrologic and water quality (H/WQ) simulation components under the Java Connection Framework (JCF) and the Object Modeling System (OMS) environmental modeling framework. AgES-W is implicitly scala...

  13. Development of an integrated generic model for multi-scale assessment of the impacts of agro-ecosystems on major ecosystem services in West Africa.

    PubMed

    Belem, Mahamadou; Saqalli, Mehdi

    2017-11-01

    This paper presents an integrated model assessing the impacts of climate change, agro-ecosystem and demographic transition patterns on major ecosystem services in West-Africa along a partial overview of economic aspects (poverty reduction, food self-sufficiency and income generation). The model is based on an agent-based model associated with a soil model and multi-scale spatial model. The resulting Model for West-Africa Agro-Ecosystem Integrated Assessment (MOWASIA) is ecologically generic, meaning it is designed for all sudano-sahelian environments but may then be used as an experimentation facility for testing different scenarios combining ecological and socioeconomic dimensions. A case study in Burkina Faso is examined to assess the environmental and economic performances of semi-continuous and continuous farming systems. Results show that the semi-continuous system using organic fertilizer and fallowing practices contribute better to environment preservation and food security than the more economically performant continuous system. In addition, this study showed that farmers heterogeneity could play an important role in agricultural policies planning and assessment. In addition, the results showed that MOWASIA is an effective tool for designing, analysing the impacts of agro-ecosystems. Copyright © 2017. Published by Elsevier Ltd.

  14. Real-world hydrologic assessment of a fully-distributed hydrological model in a parallel computing environment

    NASA Astrophysics Data System (ADS)

    Vivoni, Enrique R.; Mascaro, Giuseppe; Mniszewski, Susan; Fasel, Patricia; Springer, Everett P.; Ivanov, Valeriy Y.; Bras, Rafael L.

    2011-10-01

    SummaryA major challenge in the use of fully-distributed hydrologic models has been the lack of computational capabilities for high-resolution, long-term simulations in large river basins. In this study, we present the parallel model implementation and real-world hydrologic assessment of the Triangulated Irregular Network (TIN)-based Real-time Integrated Basin Simulator (tRIBS). Our parallelization approach is based on the decomposition of a complex watershed using the channel network as a directed graph. The resulting sub-basin partitioning divides effort among processors and handles hydrologic exchanges across boundaries. Through numerical experiments in a set of nested basins, we quantify parallel performance relative to serial runs for a range of processors, simulation complexities and lengths, and sub-basin partitioning methods, while accounting for inter-run variability on a parallel computing system. In contrast to serial simulations, the parallel model speed-up depends on the variability of hydrologic processes. Load balancing significantly improves parallel speed-up with proportionally faster runs as simulation complexity (domain resolution and channel network extent) increases. The best strategy for large river basins is to combine a balanced partitioning with an extended channel network, with potential savings through a lower TIN resolution. Based on these advances, a wider range of applications for fully-distributed hydrologic models are now possible. This is illustrated through a set of ensemble forecasts that account for precipitation uncertainty derived from a statistical downscaling model.

  15. Ensemble catchment hydrological modelling for climate change impact analysis

    NASA Astrophysics Data System (ADS)

    Vansteenkiste, Thomas; Ntegeka, Victor; Willems, Patrick

    2014-05-01

    It is vital to investigate how the hydrological model structure affects the climate change impact given that future changes not in the range for which the models were calibrated or validated are likely. Thus an ensemble modelling approach which involves a diversity of models with different structures such as spatial resolutions and process descriptions is crucial. The ensemble modelling approach was applied to a set of models: from the lumped conceptual models NAM, PDM and VHM, an intermediate detailed and distributed model WetSpa, to the highly detailed and fully distributed model MIKE-SHE. Explicit focus was given to the high and low flow extremes. All models were calibrated for sub flows and quick flows derived from rainfall and potential evapotranspiration (ETo) time series. In general, all models were able to produce reliable estimates of the flow regimes under the current climate for extreme peak and low flows. An intercomparison of the low and high flow changes under changed climatic conditions was made using climate scenarios tailored for extremes. Tailoring was important for two reasons. First, since the use of many scenarios was not feasible it was necessary to construct few scenarios that would reasonably represent the range of extreme impacts. Second, scenarios would be more informative as changes in high and low flows would be easily traced to changes of ETo and rainfall; the tailored scenarios are constructed using seasonal changes that are defined using different levels of magnitude (high, mean and low) for rainfall and ETo. After simulation of these climate scenarios in the five hydrological models, close agreement was found among the models. The different models predicted similar range of peak flow changes. For the low flows, however, the differences in the projected impact range by different hydrological models was larger, particularly for the drier scenarios. This suggests that the hydrological model structure is critical in low flow predictions

  16. From local hydrological process analysis to regional hydrological model application in Benin: Concept, results and perspectives

    NASA Astrophysics Data System (ADS)

    Bormann, H.; Faß, T.; Giertz, S.; Junge, B.; Diekkrüger, B.; Reichert, B.; Skowronek, A.

    This paper presents the concept, first results and perspectives of the hydrological sub-project of the IMPETUS-Benin project which is part of the GLOWA program funded by the German ministry of education and research. In addition to the research concept, first results on field hydrology, pedology, hydrogeology and hydrological modelling are presented, focusing on the understanding of the actual hydrological processes. For analysing the processes a 30 km 2 catchment acting as a super test site was chosen which is assumed to be representative for the entire catchment of about 15,000 km 2. First results of the field investigations show that infiltration, runoff generation and soil erosion strongly depend on land cover and land use which again influence the soil properties significantly. A conceptual hydrogeological model has been developed summarising the process knowledge on runoff generation and subsurface hydrological processes. This concept model shows a dominance of fast runoff components (surface runoff and interflow), a groundwater recharge along preferential flow paths, temporary interaction between surface and groundwater and separate groundwater systems on different scales (shallow, temporary groundwater on local scale and permanent, deep groundwater on regional scale). The findings of intensive measurement campaigns on soil hydrology, groundwater dynamics and soil erosion have been integrated into different, scale-dependent hydrological modelling concepts applied at different scales in the target region (upper Ouémé catchment in Benin, about 15,000 km 2). The models have been applied and successfully validated. They will be used for integrated scenario analyses in the forthcoming project phase to assess the impacts of global change on the regional water cycle and on typical problem complexes such as food security in West African countries.

  17. Ensemble Analysis of Variational Assimilation of Hydrologic and Hydrometeorological Data into Distributed Hydrologic Model

    NASA Astrophysics Data System (ADS)

    Lee, H.; Seo, D.; Koren, V.

    2008-12-01

    A prototype 4DVAR (four-dimensional variational) data assimilator for gridded Sacramento soil-moisture accounting and kinematic-wave routing models in the Hydrology Laboratory's Research Distributed Hydrologic Model (HL-RDHM) has been developed. The prototype assimilates streamflow and in-situ soil moisture data and adjusts gridded precipitation and climatological potential evaporation data to reduce uncertainty in the model initial conditions for improved monitoring and prediction of streamflow and soil moisture at the outlet and interior locations within the catchment. Due to large degrees of freedom involved, data assimilation (DA) into distributed hydrologic models is complex. To understand and assess sensitivity of the performance of DA to uncertainties in the model initial conditions and in the data, two synthetic experiments have been carried out in an ensemble framework. Results from the synthetic experiments shed much light on the potential and limitations with DA into distributed models. For initial real-world assessment, the prototype DA has also been applied to the headwater basin at Eldon near the Oklahoma-Arkansas border. We present these results and describe the next steps.

  18. Findings and Challenges in Fine-Resolution Large-Scale Hydrological Modeling

    NASA Astrophysics Data System (ADS)

    Her, Y. G.

    2017-12-01

    Fine-resolution large-scale (FL) modeling can provide the overall picture of the hydrological cycle and transport while taking into account unique local conditions in the simulation. It can also help develop water resources management plans consistent across spatial scales by describing the spatial consequences of decisions and hydrological events extensively. FL modeling is expected to be common in the near future as global-scale remotely sensed data are emerging, and computing resources have been advanced rapidly. There are several spatially distributed models available for hydrological analyses. Some of them rely on numerical methods such as finite difference/element methods (FDM/FEM), which require excessive computing resources (implicit scheme) to manipulate large matrices or small simulation time intervals (explicit scheme) to maintain the stability of the solution, to describe two-dimensional overland processes. Others make unrealistic assumptions such as constant overland flow velocity to reduce the computational loads of the simulation. Thus, simulation efficiency often comes at the expense of precision and reliability in FL modeling. Here, we introduce a new FL continuous hydrological model and its application to four watersheds in different landscapes and sizes from 3.5 km2 to 2,800 km2 at the spatial resolution of 30 m on an hourly basis. The model provided acceptable accuracy statistics in reproducing hydrological observations made in the watersheds. The modeling outputs including the maps of simulated travel time, runoff depth, soil water content, and groundwater recharge, were animated, visualizing the dynamics of hydrological processes occurring in the watersheds during and between storm events. Findings and challenges were discussed in the context of modeling efficiency, accuracy, and reproducibility, which we found can be improved by employing advanced computing techniques and hydrological understandings, by using remotely sensed hydrological

  19. visCOS: An R-package to evaluate model performance of hydrological models

    NASA Astrophysics Data System (ADS)

    Klotz, Daniel; Herrnegger, Mathew; Wesemann, Johannes; Schulz, Karsten

    2016-04-01

    The evaluation of model performance is a central part of (hydrological) modelling. Much attention has been given to the development of evaluation criteria and diagnostic frameworks. (Klemeš, 1986; Gupta et al., 2008; among many others). Nevertheless, many applications exist for which objective functions do not yet provide satisfying summaries. Thus, the necessity to visualize results arises in order to explore a wider range of model capacities, be it strengths or deficiencies. Visualizations are usually devised for specific projects and these efforts are often not distributed to a broader community (e.g. via open source software packages). Hence, the opportunity to explicitly discuss a state-of-the-art presentation technique is often missed. We therefore present a comprehensive R-package for evaluating model performance by visualizing and exploring different aspects of hydrological time-series. The presented package comprises a set of useful plots and visualization methods, which complement existing packages, such as hydroGOF (Zambrano-Bigiarini et al., 2012). It is derived from practical applications of the hydrological models COSERO and COSEROreg (Kling et al., 2014). visCOS, providing an interface in R, represents an easy-to-use software package for visualizing and assessing model performance and can be implemented in the process of model calibration or model development. The package provides functions to load hydrological data into R, clean the data, process, visualize, explore and finally save the results in a consistent way. Together with an interactive zoom function of the time series, an online calculation of the objective functions for variable time-windows is included. Common hydrological objective functions, such as the Nash-Sutcliffe Efficiency and the Kling-Gupta Efficiency, can also be evaluated and visualized in different ways for defined sub-periods like hydrological years or seasonal sections. Many hydrologists use long-term water-balances as a

  20. Hydrological model uncertainty due to spatial evapotranspiration estimation methods

    NASA Astrophysics Data System (ADS)

    Yu, Xuan; Lamačová, Anna; Duffy, Christopher; Krám, Pavel; Hruška, Jakub

    2016-05-01

    Evapotranspiration (ET) continues to be a difficult process to estimate in seasonal and long-term water balances in catchment models. Approaches to estimate ET typically use vegetation parameters (e.g., leaf area index [LAI], interception capacity) obtained from field observation, remote sensing data, national or global land cover products, and/or simulated by ecosystem models. In this study we attempt to quantify the uncertainty that spatial evapotranspiration estimation introduces into hydrological simulations when the age of the forest is not precisely known. The Penn State Integrated Hydrologic Model (PIHM) was implemented for the Lysina headwater catchment, located 50°03‧N, 12°40‧E in the western part of the Czech Republic. The spatial forest patterns were digitized from forest age maps made available by the Czech Forest Administration. Two ET methods were implemented in the catchment model: the Biome-BGC forest growth sub-model (1-way coupled to PIHM) and with the fixed-seasonal LAI method. From these two approaches simulation scenarios were developed. We combined the estimated spatial forest age maps and two ET estimation methods to drive PIHM. A set of spatial hydrologic regime and streamflow regime indices were calculated from the modeling results for each method. Intercomparison of the hydrological responses to the spatial vegetation patterns suggested considerable variation in soil moisture and recharge and a small uncertainty in the groundwater table elevation and streamflow. The hydrologic modeling with ET estimated by Biome-BGC generated less uncertainty due to the plant physiology-based method. The implication of this research is that overall hydrologic variability induced by uncertain management practices was reduced by implementing vegetation models in the catchment models.

  1. [Environmental quality assessment of regional agro-ecosystem in Loess Plateau].

    PubMed

    Wang, Limei; Meng, Fanping; Zheng, Jiyong; Wang, Zhonglin

    2004-03-01

    Based on the detection and analysis of the contamination status of agro-ecosystem with apple-crops intercropping as the dominant cropping model in Loess Plateau, the individual factor and comprehensive environmental quality were assessed by multilevel fuzzy synthetic evaluation model, analytical hierarchy process(AHP), and improved standard weight deciding method. The results showed that the quality of soil, water and agricultural products was grade I, the social economical environmental quality was grade II, the ecological environmental quality was grade III, and the comprehensive environmental quality was grade I. The regional agro-ecosystem dominated by apple-crops intercropping was not the best model for the ecological benefits, but had the better social economical benefits.

  2. ArgoEcoSystem-watershed (AgES-W) model evaluation for streamflow and nitrogen/sediment dynamics on a midwest agricultural watershed

    USDA-ARS?s Scientific Manuscript database

    AgroEcoSystem-Watershed (AgES-W) is a modular, Java-based spatially distributed model which implements hydrologic/water quality simulation components under the Object Modeling System Version 3 (OMS3). The AgES-W model was previously evaluated for streamflow and recently has been enhanced with the ad...

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

    NASA Astrophysics Data System (ADS)

    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.

  4. Meteorological risks are drivers of environmental innovation in agro-ecosystem management

    NASA Astrophysics Data System (ADS)

    Gobin, Anne; Van de Vijver, Hans; Vanwindekens, Frédéric; de Frutos Cachorro, Julia; Verspecht, Ann; Planchon, Viviane; Buyse, Jeroen

    2017-04-01

    Agricultural crop production is to a great extent determined by weather conditions. The research hypothesis is that meteorological risks act as drivers of environmental innovation in agro-ecosystem management. The methodology comprised five major parts: the hazard, its impact on different agro-ecosystems, vulnerability, risk management and risk communication. Generalized Extreme Value (GEV) theory was used to model annual maxima of meteorological variables based on a location-, scale- and shape-parameter that determine the center of the distribution, the deviation of the location-parameter and the upper tail decay, respectively. Spatial interpolation of GEV-derived return levels resulted in spatial temperature extremes, precipitation deficits and wet periods. The temporal overlap between extreme weather conditions and sensitive periods in the agro-ecosystem was realised using a bio-physically based modelling framework that couples phenology, a soil water balance and crop growth. 20-year return values for drought and waterlogging during different crop stages were related to arable yields. The method helped quantify agricultural production risks and rate both weather and crop-based agricultural insurance. The spatial extent of vulnerability is developed on different layers of geo-information to include meteorology, soil-landscapes, crop cover and management. Vulnerability of agroecosystems was mapped based on rules set by experts' knowledge and implemented by Fuzzy Inference System modelling and Geographical Information System tools. The approach was applied for cropland vulnerability to heavy rain and grassland vulnerability to drought. The level of vulnerability and resilience of an agro-ecosystem was also determined by risk management which differed across sectors and farm types. A calibrated agro-economic model demonstrated a marked influence of climate adapted land allocation and crop management on individual utility. The "chain of risk" approach allowed for

  5. Use of hydrologic and hydrodynamic modeling for ecosystem restoration

    USGS Publications Warehouse

    Obeysekera, J.; Kuebler, L.; Ahmed, S.; Chang, M.-L.; Engel, V.; Langevin, C.; Swain, E.; Wan, Y.

    2011-01-01

    Planning and implementation of unprecedented projects for restoring the greater Everglades ecosystem are underway and the hydrologic and hydrodynamic modeling of restoration alternatives has become essential for success of restoration efforts. In view of the complex nature of the South Florida water resources system, regional-scale (system-wide) hydrologic models have been developed and used extensively for the development of the Comprehensive Everglades Restoration Plan. In addition, numerous subregional-scale hydrologic and hydrodynamic models have been developed and are being used for evaluating project-scale water management plans associated with urban, agricultural, and inland costal ecosystems. The authors provide a comprehensive summary of models of all scales, as well as the next generation models under development to meet the future needs of ecosystem restoration efforts in South Florida. The multiagency efforts to develop and apply models have allowed the agencies to understand the complex hydrologic interactions, quantify appropriate performance measures, and use new technologies in simulation algorithms, software development, and GIS/database techniques to meet the future modeling needs of the ecosystem restoration programs. Copyright ?? 2011 Taylor & Francis Group, LLC.

  6. Satellite-derived potential evapotranspiration for distributed hydrologic runoff modeling

    NASA Astrophysics Data System (ADS)

    Spies, R. R.; Franz, K. J.; Bowman, A.; Hogue, T. S.; Kim, J.

    2012-12-01

    Distributed models have the ability of incorporating spatially variable data, especially high resolution forcing inputs such as precipitation, temperature and evapotranspiration in hydrologic modeling. Use of distributed hydrologic models for operational streamflow prediction has been partially hindered by a lack of readily available, spatially explicit input observations. Potential evapotranspiration (PET), for example, is currently accounted for through PET input grids that are based on monthly climatological values. The goal of this study is to assess the use of satellite-based PET estimates that represent the temporal and spatial variability, as input to the National Weather Service (NWS) Hydrology Laboratory Research Distributed Hydrologic Model (HL-RDHM). Daily PET grids are generated for six watersheds in the upper Mississippi River basin using a method that applies only MODIS satellite-based observations and the Priestly Taylor formula (MODIS-PET). The use of MODIS-PET grids will be tested against the use of the current climatological PET grids for simulating basin discharge. Gridded surface temperature forcing data are derived by applying the inverse distance weighting spatial prediction method to point-based station observations from the Automated Surface Observing System (ASOS) and Automated Weather Observing System (AWOS). Precipitation data are obtained from the Climate Prediction Center's (CPC) Climatology-Calibrated Precipitation Analysis (CCPA). A-priori gridded parameters for the Sacramento Soil Moisture Accounting Model (SAC-SMA), Snow-17 model, and routing model are initially obtained from the Office of Hydrologic Development and further calibrated using an automated approach. The potential of the MODIS-PET to be used in an operational distributed modeling system will be assessed with the long-term goal of promoting research to operations transfers and advancing the science of hydrologic forecasting.

  7. Hydrological Modelling the Middle Magdalena Valley (Colombia)

    NASA Astrophysics Data System (ADS)

    Arenas, M. C.; Duque, N.; Arboleda, P.; Guadagnini, A.; Riva, M.; Donado-Garzon, L. D.

    2017-12-01

    Hydrological distributed modeling is key point for a comprehensive assessment of the feedback between the dynamics of the hydrological cycle, climate conditions and land use. Such modeling results are markedly relevant in the fields of water resources management, natural hazards and oil and gas industry. Here, we employ TopModel (TOPography based hydrological MODEL) for the hydrological modeling of an area in the Middle Magdalena Valley (MMV), a tropical basin located in Colombia. This study is located over the intertropical convergence zone and is characterized by special meteorological conditions, with fast water fluxes over the year. It has been subject to significant land use changes, as a result of intense economical activities, i.e., and agriculture, energy and oil & gas production. The model employees a record of 12 years of daily precipitation and evapotranspiration data as inputs. Streamflow data monitored across the same time frame are used for model calibration. The latter is performed by considering data from 2000 to 2008. Model validation then relies on observations from 2009 to 2012. The robustness of our analyses is based on the Nash-Sutcliffe coefficient (values of this metric being 0.62 and 0.53, respectively for model calibration and validation). Our results reveal high water storage capacity in the soil, and a marked subsurface runoff, consistent with the characteristics of the soil types in the regions. A significant influence on runoff response of the basin to topographical factors represented in the model is evidenced. Our calibrated model provides relevant indications about recharge in the region, which is important to quantify the interaction between surface water and groundwater, specially during the dry season, which is more relevant in climate-change and climate-variability scenarios.

  8. Bangladesh Agro-Climatic Environmental Monitoring Project

    NASA Technical Reports Server (NTRS)

    Vermillion, C.; Maurer, H.; Williams, M.; Kamowski, J.; Moore, T.; Maksimovich, W.; Obler, H.; Gilbert, E.

    1988-01-01

    The Agro-Climatic Environmental Monitoring Project (ACEMP) is based on a Participating Agency Service Agreement (PASA) between the Agency for International Development (AID) and the National Oceanic and Atmospheric Administration (NOAA). In FY80, the Asia Bureau and Office of Federal Disaster Assistance (OFDA), worked closely to develop a funding mechanism which would meet Bangladesh's needs both for flood and cyclone warning capability and for application of remote sensing data to development problems. In FY90, OFDA provided for a High Resolution Picture Transmission (HRPT) receiving capability to improve their forecasting accuracy for cyclones, flooding and storm surges. That equipment is primarily intended as a disaster prediction and preparedness measure. The ACEM Project was designed to focus on the development applications of remote sensing technology. Through this Project, AID provided to the Bangladesh Government (BDG) the equipment, technical assistance, and training necessary to collect and employ remote sensing data made available by satellites as well as hydrological data obtained from data collection platforms placed in major rivers. The data collected will enable the BDG to improve the management of its natural resources.

  9. Legacy model integration for enhancing hydrologic interdisciplinary research

    NASA Astrophysics Data System (ADS)

    Dozier, A.; Arabi, M.; David, O.

    2013-12-01

    Many challenges are introduced to interdisciplinary research in and around the hydrologic science community due to advances in computing technology and modeling capabilities in different programming languages, across different platforms and frameworks by researchers in a variety of fields with a variety of experience in computer programming. Many new hydrologic models as well as optimization, parameter estimation, and uncertainty characterization techniques are developed in scripting languages such as Matlab, R, Python, or in newer languages such as Java and the .Net languages, whereas many legacy models have been written in FORTRAN and C, which complicates inter-model communication for two-way feedbacks. However, most hydrologic researchers and industry personnel have little knowledge of the computing technologies that are available to address the model integration process. Therefore, the goal of this study is to address these new challenges by utilizing a novel approach based on a publish-subscribe-type system to enhance modeling capabilities of legacy socio-economic, hydrologic, and ecologic software. Enhancements include massive parallelization of executions and access to legacy model variables at any point during the simulation process by another program without having to compile all the models together into an inseparable 'super-model'. Thus, this study provides two-way feedback mechanisms between multiple different process models that can be written in various programming languages and can run on different machines and operating systems. Additionally, a level of abstraction is given to the model integration process that allows researchers and other technical personnel to perform more detailed and interactive modeling, visualization, optimization, calibration, and uncertainty analysis without requiring deep understanding of inter-process communication. To be compatible, a program must be written in a programming language with bindings to a common

  10. Brokering as a framework for hydrological model repeatability

    NASA Astrophysics Data System (ADS)

    Fuka, Daniel; Collick, Amy; MacAlister, Charlotte; Braeckel, Aaron; Wright, Dawn; Jodha Khalsa, Siri; Boldrini, Enrico; Easton, Zachary

    2015-04-01

    Data brokering aims to provide those in the the sciences with quick and repeatable access to data that represents physical, biological, and chemical characteristics; specifically to accelerate scientific discovery. Environmental models are useful tools to understand the behavior of hydrological systems. Unfortunately, parameterization of these hydrological models requires many different data, from different sources, and from different disciplines (e.g., atmospheric, geoscience, ecology). In basin scale hydrological modeling, the traditional procedure for model initialization starts with obtaining elevation models, land-use characterizations, soils maps, and weather data. It is often the researcher's past experience with these datasets that determines which datasets will be used in a study, and often newer, or more suitable data products will exist. An added complexity is that various science communities have differing data formats, storage protocols, and manipulation methods, which makes use by a non native user exceedingly difficult and time consuming. We demonstrate data brokering as a means to address several of these challenges. We present two test case scenarios in which researchers attempt to reproduce hydrological model results using 1) general internet based data gathering techniques, and 2) a scientific data brokering interface. We show that data brokering can increase the efficiency with which data are obtained, models are initialized, and results are analyzed. As an added benefit, it appears brokering can significantly increase the repeatability of a given study.

  11. Modeling greenhouse gas emissions and nutrient transport in managed arable soils with a fully coupled hydrology-biogeochemical modeling system

    NASA Astrophysics Data System (ADS)

    Haas, Edwin; Klatt, Steffen; Kiese, Ralf; Butterbach-Bahl, Klaus; Kraft, Philipp; Breuer, Lutz

    2015-04-01

    The use of mineral nitrogen fertilizer sustains the global food production and therefore the livelihood of human kind. The rise in world population will put pressure on the global agricultural system to increase its productivity leading most likely to an intensification of mineral nitrogen fertilizer use. The fate of excess nitrogen and its distribution within landscapes is manifold. Process knowledge on the site scale has rapidly grown in recent years and models have been developed to simulate carbon and nitrogen cycling in managed ecosystems on the site scale. Despite first regional studies, the carbon and nitrogen cycling on the landscape or catchment scale is not fully understood. In this study we present a newly developed modelling approach by coupling the fully distributed hydrology model CMF (catchment modelling framework) to the process based regional ecosystem model LandscapeDNDC for the investigation of hydrological processes and carbon and nitrogen transport and cycling, with a focus on nutrient displacement and resulting greenhouse gas emissions in various virtual landscapes / catchment to demonstrate the capabilities of the modelling system. The modelling system was applied to simulate water and nutrient transport at the at the Yanting Agro-ecological Experimental Station of Purple Soil, Sichuan province, China. The catchment hosts cypress forests on the outer regions, arable fields on the sloping croplands cultivated with wheat-maize rotations and paddy rice fields in the lowland. The catchment consists of 300 polygons vertically stratified into 10 soil layers. Ecosystem states (soil water content and nutrients) and fluxes (evapotranspiration) are exchanged between the models at high temporal scales (hourly to daily) forming a 3-dimensional model application. The water flux and nutrients transport in the soil is modelled using a 3D Richards/Darcy approach for subsurface fluxes with a kinematic wave approach for surface water runoff and the

  12. Coupled Crop/Hydrology Model to Estimate Expanded Irrigation Impact on Water Resources

    NASA Astrophysics Data System (ADS)

    Handyside, C. T.; Cruise, J.

    2017-12-01

    A coupled agricultural and hydrologic systems model is used to examine the environmental impact of irrigation in the Southeast. A gridded crop model for the Southeast is used to determine regional irrigation demand. This irrigation demand is used in a regional hydrologic model to determine the hydrologic impact of irrigation. For the Southeast to maintain/expand irrigated agricultural production and provide adaptation to climate change and climate variability it will require integrated agricultural and hydrologic system models that can calculate irrigation demand and the impact of the this demand on the river hydrology. These integrated models can be used as (1) historical tools to examine vulnerability of expanded irrigation to past climate extremes (2) future tools to examine the sustainability of expanded irrigation under future climate scenarios and (3) a real-time tool to allow dynamic water resource management. Such tools are necessary to assure stakeholders and the public that irrigation can be carried out in a sustainable manner. The system tools to be discussed include a gridded version of the crop modeling system (DSSAT). The gridded model is referred to as GriDSSAT. The irrigation demand from GriDSSAT is coupled to a regional hydrologic model developed by the Eastern Forest Environmental Threat Assessment Center of the USDA Forest Service) (WaSSI). The crop model provides the dynamic irrigation demand which is a function of the weather. The hydrologic model includes all other competing uses of water. Examples of use the crop model coupled with the hydrologic model include historical analyses which show the change in hydrology as additional acres of irrigated land are added to water sheds. The first order change in hydrology is computed in terms of changes in the Water Availability Stress Index (WASSI) which is the ratio of water demand (irrigation, public water supply, industrial use, etc.) and water availability from the hydrologic model. Also

  13. Hydrological changes in the Amur river basin: two approaches for assignment of climate projections into hydrological model

    NASA Astrophysics Data System (ADS)

    Gelfan, Alexander; Kalugin, Andrei; Motovilov, Yury

    2017-04-01

    A regional hydrological model was setup to assess possible impact of climate change on the hydrological regime of the Amur drainage basin (the catchment area is 1 855 000 km2). The model is based on the ECOMAG hydrological modeling platform and describes spatially distributed processes of water cycle in this great basin with account for flow regulation by the Russian and Chinese reservoirs. Earlier, the regional hydrological model was intensively evaluated against 20-year streamflow data over the whole Amur basin and, being driven by 252-station meteorological observations as input data, demonstrated good performance. In this study, we firstly assessed the reliability of the model to reproduce the historical streamflow series when Global Climate Model (GCM) simulation data are used as input into the hydrological model. Data of nine GCMs involved in CMIP5 project was utilized and we found that ensemble mean of annual flow is close to the observed flow (error is about 14%) while data of separate GCMs may result in much larger errors. Reproduction of seasonal flow for the historical period turned out weaker; first of all because of large errors in simulated seasonal precipitation, so hydrological consequences of climate change were estimated just in terms of annual flow. We analyzed the hydrological projections from the climate change scenarios. The impacts were assessed in four 20-year periods: early- (2020-2039), mid- (2040-2059) and two end-century (2060-2079; 2080-2099) periods using an ensemble of nine GCMs and four Representative Concentration Pathways (RCP) scenarios. Mean annual runoff anomalies calculated as percentages of the future runoff (simulated under 36 GCM-RCP combinations of climate scenarios) to the historical runoff (simulated under the corresponding GCM outputs for the reference 1986-2005 period) were estimated. Hydrological model gave small negative runoff anomalies for almost all GCM-RCP combinations of climate scenarios and for all 20-year

  14. Meteorological risks are drivers of environmental innovation in agro-ecosystem management

    NASA Astrophysics Data System (ADS)

    Gobin, Anne; Van de Vyver, Hans; Vanwindekens, Frédéric; Planchon, Viviane; Verspecht, Ann; Frutos de Cachorro, Julia; Buysse, Jeroen

    2016-04-01

    Extreme weather events such as droughts, heat waves and rain storms are projected to increase both in frequency and magnitude with climate change. The research hypothesis of the MERINOVA project is that meteorological risks act as drivers of environmental innovation in agro-ecosystem management which is being tested using a chain of risk approach. The project comprises of five major parts that reflect the chain of risks: the hazard, its impact on different agro-ecosystems, vulnerability, risk management and risk communication. Generalized Extreme Value (GEV) theory was used to model annual maxima of meteorological variables based on a location-, scale- and shape-parameter that determine the center of the distribution, the deviation of the location-parameter and the upper tail decay, respectively. Spatial interpolation of GEV-derived return levels has yielded maps of temperature extremes, precipitation deficits and wet periods. The degree of temporal overlap between extreme weather conditions and sensitive periods in the agro-ecosystem was determined using a bio-physically based modelling framework that couples phenological models, a soil water balance, crop growth and environmental models. 20-year return values for frost, heat stress, drought, waterlogging and field access during different crop stages were related to arable yields. The spatial extent of vulnerability is developed on different layers of spatial information that include inter alia meteorology, soil-landscapes, crop cover and management. The level of vulnerability and resilience of an agro-ecosystem is also determined by risk management. The types of agricultural risk and their relative importance differ across sectors and farm types as elucidated by questionnaires and focus groups. Risk types are distinguished according to production, market, institutional, financial and liability risks. A portfolio of potential strategies was identified at farm, market and policy level. In conclusion, MERINOVA

  15. A physically-based Distributed Hydrologic Model for Tropical Catchments

    NASA Astrophysics Data System (ADS)

    Abebe, N. A.; Ogden, F. L.

    2010-12-01

    Hydrological models are mathematical formulations intended to represent observed hydrological processes in a watershed. Simulated watersheds in turn vary in their nature based on their geographic location, altitude, climatic variables and geology and soil formation. Due to these variations, available hydrologic models vary in process formulation, spatial and temporal resolution and data demand. Many tropical watersheds are characterized by extensive and persistent biological activity and a large amount of rain. The Agua Salud catchments located within the Panama Canal Watershed, Panama, are such catchments identified by steep rolling topography, deep soils derived from weathered bedrock, and limited exposed bedrock. Tropical soils are highly affected by soil cracks, decayed tree roots and earthworm burrows forming a network of preferential flow paths that drain to a perched water table, which forms at a depth where the vertical hydraulic conductivity is significantly reduced near the bottom of the bioturbation layer. We have developed a physics-based, spatially distributed, multi-layered hydrologic model to simulate the dominant processes in these tropical watersheds. The model incorporates the major flow processes including overland flow, channel flow, matrix and non-Richards film flow infiltration, lateral downslope saturated matrix and non-Darcian pipe flow in the bioturbation layer, and deep saturated groundwater flow. Emphasis is given to the modeling of subsurface unsaturated zone soil moisture dynamics and the saturated preferential lateral flow from the network of macrospores. Preliminary results indicate that the model has the capability to simulate the complex hydrological processes in the catchment and will be a useful tool in the ongoing comprehensive ecohydrological studies in tropical catchments, and help improve our understanding of the hydrological effects of deforestation and aforestation.

  16. A "total parameter estimation" method in the varification of distributed hydrological models

    NASA Astrophysics Data System (ADS)

    Wang, M.; Qin, D.; Wang, H.

    2011-12-01

    Conventionally hydrological models are used for runoff or flood forecasting, hence the determination of model parameters are common estimated based on discharge measurements at the catchment outlets. With the advancement in hydrological sciences and computer technology, distributed hydrological models based on the physical mechanism such as SWAT, MIKESHE, and WEP, have gradually become the mainstream models in hydrology sciences. However, the assessments of distributed hydrological models and model parameter determination still rely on runoff and occasionally, groundwater level measurements. It is essential in many countries, including China, to understand the local and regional water cycle: not only do we need to simulate the runoff generation process and for flood forecasting in wet areas, we also need to grasp the water cycle pathways and consumption process of transformation in arid and semi-arid regions for the conservation and integrated water resources management. As distributed hydrological model can simulate physical processes within a catchment, we can get a more realistic representation of the actual water cycle within the simulation model. Runoff is the combined result of various hydrological processes, using runoff for parameter estimation alone is inherits problematic and difficult to assess the accuracy. In particular, in the arid areas, such as the Haihe River Basin in China, runoff accounted for only 17% of the rainfall, and very concentrated during the rainy season from June to August each year. During other months, many of the perennial rivers within the river basin dry up. Thus using single runoff simulation does not fully utilize the distributed hydrological model in arid and semi-arid regions. This paper proposed a "total parameter estimation" method to verify the distributed hydrological models within various water cycle processes, including runoff, evapotranspiration, groundwater, and soil water; and apply it to the Haihe river basin in

  17. The Regional Hydrologic Extremes Assessment System: A software framework for hydrologic modeling and data assimilation

    PubMed Central

    Das, Narendra; Stampoulis, Dimitrios; Ines, Amor; Fisher, Joshua B.; Granger, Stephanie; Kawata, Jessie; Han, Eunjin; Behrangi, Ali

    2017-01-01

    The Regional Hydrologic Extremes Assessment System (RHEAS) is a prototype software framework for hydrologic modeling and data assimilation that automates the deployment of water resources nowcasting and forecasting applications. A spatially-enabled database is a key component of the software that can ingest a suite of satellite and model datasets while facilitating the interfacing with Geographic Information System (GIS) applications. The datasets ingested are obtained from numerous space-borne sensors and represent multiple components of the water cycle. The object-oriented design of the software allows for modularity and extensibility, showcased here with the coupling of the core hydrologic model with a crop growth model. RHEAS can exploit multi-threading to scale with increasing number of processors, while the database allows delivery of data products and associated uncertainty through a variety of GIS platforms. A set of three example implementations of RHEAS in the United States and Kenya are described to demonstrate the different features of the system in real-world applications. PMID:28545077

  18. The Regional Hydrologic Extremes Assessment System: A software framework for hydrologic modeling and data assimilation.

    PubMed

    Andreadis, Konstantinos M; Das, Narendra; Stampoulis, Dimitrios; Ines, Amor; Fisher, Joshua B; Granger, Stephanie; Kawata, Jessie; Han, Eunjin; Behrangi, Ali

    2017-01-01

    The Regional Hydrologic Extremes Assessment System (RHEAS) is a prototype software framework for hydrologic modeling and data assimilation that automates the deployment of water resources nowcasting and forecasting applications. A spatially-enabled database is a key component of the software that can ingest a suite of satellite and model datasets while facilitating the interfacing with Geographic Information System (GIS) applications. The datasets ingested are obtained from numerous space-borne sensors and represent multiple components of the water cycle. The object-oriented design of the software allows for modularity and extensibility, showcased here with the coupling of the core hydrologic model with a crop growth model. RHEAS can exploit multi-threading to scale with increasing number of processors, while the database allows delivery of data products and associated uncertainty through a variety of GIS platforms. A set of three example implementations of RHEAS in the United States and Kenya are described to demonstrate the different features of the system in real-world applications.

  19. RHydro - Hydrological models and tools to represent and analyze hydrological data in R

    NASA Astrophysics Data System (ADS)

    Reusser, Dominik; Buytaert, Wouter

    2010-05-01

    In hydrology, basic equations and procedures keep being implemented from scratch by scientist, with the potential for errors and inefficiency. The use of libraries can overcome these problems. Other scientific disciplines such as mathematics and physics have benefited significantly from such an approach with freely available implementations for many routines. As an example, hydrological libraries could contain: Major representations of hydrological processes such as infiltration, sub-surface runoff and routing algorithms. Scaling functions, for instance to combine remote sensing precipitation fields with rain gauge data Data consistency checks Performance measures. Here we present a beginning for such a library implemented in the high level data programming language R. Currently, Top-model, data import routines for WaSiM-ETH as well basic visualization and evaluation tools are implemented. The design is such, that a definition of import scripts for additional models is sufficient to have access to the full set of evaluation and visualization tools.

  20. Hydrologic modeling strategy for the Islamic Republic of Mauritania, Africa

    USGS Publications Warehouse

    Friedel, Michael J.

    2008-01-01

    The government of Mauritania is interested in how to maintain hydrologic balance to ensure a long-term stable water supply for minerals-related, domestic, and other purposes. Because of the many complicating and competing natural and anthropogenic factors, hydrologists will perform quantitative analysis with specific objectives and relevant computer models in mind. Whereas various computer models are available for studying water-resource priorities, the success of these models to provide reliable predictions largely depends on adequacy of the model-calibration process. Predictive analysis helps us evaluate the accuracy and uncertainty associated with simulated dependent variables of our calibrated model. In this report, the hydrologic modeling process is reviewed and a strategy summarized for future Mauritanian hydrologic modeling studies.

  1. Testing the structure of a hydrological model using Genetic Programming

    NASA Astrophysics Data System (ADS)

    Selle, Benny; Muttil, Nitin

    2011-01-01

    SummaryGenetic Programming is able to systematically explore many alternative model structures of different complexity from available input and response data. We hypothesised that Genetic Programming can be used to test the structure of hydrological models and to identify dominant processes in hydrological systems. To test this, Genetic Programming was used to analyse a data set from a lysimeter experiment in southeastern Australia. The lysimeter experiment was conducted to quantify the deep percolation response under surface irrigated pasture to different soil types, watertable depths and water ponding times during surface irrigation. Using Genetic Programming, a simple model of deep percolation was recurrently evolved in multiple Genetic Programming runs. This simple and interpretable model supported the dominant process contributing to deep percolation represented in a conceptual model that was published earlier. Thus, this study shows that Genetic Programming can be used to evaluate the structure of hydrological models and to gain insight about the dominant processes in hydrological systems.

  2. Green roof hydrologic performance and modeling: a review.

    PubMed

    Li, Yanling; Babcock, Roger W

    2014-01-01

    Green roofs reduce runoff from impervious surfaces in urban development. This paper reviews the technical literature on green roof hydrology. Laboratory experiments and field measurements have shown that green roofs can reduce stormwater runoff volume by 30 to 86%, reduce peak flow rate by 22 to 93% and delay the peak flow by 0 to 30 min and thereby decrease pollution, flooding and erosion during precipitation events. However, the effectiveness can vary substantially due to design characteristics making performance predictions difficult. Evaluation of the most recently published study findings indicates that the major factors affecting green roof hydrology are precipitation volume, precipitation dynamics, antecedent conditions, growth medium, plant species, and roof slope. This paper also evaluates the computer models commonly used to simulate hydrologic processes for green roofs, including stormwater management model, soil water atmosphere and plant, SWMS-2D, HYDRUS, and other models that are shown to be effective for predicting precipitation response and economic benefits. The review findings indicate that green roofs are effective for reduction of runoff volume and peak flow, and delay of peak flow, however, no tool or model is available to predict expected performance for any given anticipated system based on design parameters that directly affect green roof hydrology.

  3. Hydrological Modeling Reproducibility Through Data Management and Adaptors for Model Interoperability

    NASA Astrophysics Data System (ADS)

    Turner, M. A.

    2015-12-01

    Because of a lack of centralized planning and no widely-adopted standards among hydrological modeling research groups, research communities, and the data management teams meant to support research, there is chaos when it comes to data formats, spatio-temporal resolutions, ontologies, and data availability. All this makes true scientific reproducibility and collaborative integrated modeling impossible without some glue to piece it all together. Our Virtual Watershed Integrated Modeling System provides the tools and modeling framework hydrologists need to accelerate and fortify new scientific investigations by tracking provenance and providing adaptors for integrated, collaborative hydrologic modeling and data management. Under global warming trends where water resources are under increasing stress, reproducible hydrological modeling will be increasingly important to improve transparency and understanding of the scientific facts revealed through modeling. The Virtual Watershed Data Engine is capable of ingesting a wide variety of heterogeneous model inputs, outputs, model configurations, and metadata. We will demonstrate one example, starting from real-time raw weather station data packaged with station metadata. Our integrated modeling system will then create gridded input data via geostatistical methods along with error and uncertainty estimates. These gridded data are then used as input to hydrological models, all of which are available as web services wherever feasible. Models may be integrated in a data-centric way where the outputs too are tracked and used as inputs to "downstream" models. This work is part of an ongoing collaborative Tri-state (New Mexico, Nevada, Idaho) NSF EPSCoR Project, WC-WAVE, comprised of researchers from multiple universities in each of the three states. The tools produced and presented here have been developed collaboratively alongside watershed scientists to address specific modeling problems with an eye on the bigger picture of

  4. Uncertainty Propagation of Non-Parametric-Derived Precipitation Estimates into Multi-Hydrologic Model Simulations

    NASA Astrophysics Data System (ADS)

    Bhuiyan, M. A. E.; Nikolopoulos, E. I.; Anagnostou, E. N.

    2017-12-01

    Quantifying the uncertainty of global precipitation datasets is beneficial when using these precipitation products in hydrological applications, because precipitation uncertainty propagation through hydrologic modeling can significantly affect the accuracy of the simulated hydrologic variables. In this research the Iberian Peninsula has been used as the study area with a study period spanning eleven years (2000-2010). This study evaluates the performance of multiple hydrologic models forced with combined global rainfall estimates derived based on a Quantile Regression Forests (QRF) technique. In QRF technique three satellite precipitation products (CMORPH, PERSIANN, and 3B42 (V7)); an atmospheric reanalysis precipitation and air temperature dataset; satellite-derived near-surface daily soil moisture data; and a terrain elevation dataset are being utilized in this study. A high-resolution, ground-based observations driven precipitation dataset (named SAFRAN) available at 5 km/1 h resolution is used as reference. Through the QRF blending framework the stochastic error model produces error-adjusted ensemble precipitation realizations, which are used to force four global hydrological models (JULES (Joint UK Land Environment Simulator), WaterGAP3 (Water-Global Assessment and Prognosis), ORCHIDEE (Organizing Carbon and Hydrology in Dynamic Ecosystems) and SURFEX (Stands for Surface Externalisée) ) to simulate three hydrologic variables (surface runoff, subsurface runoff and evapotranspiration). The models are forced with the reference precipitation to generate reference-based hydrologic simulations. This study presents a comparative analysis of multiple hydrologic model simulations for different hydrologic variables and the impact of the blending algorithm on the simulated hydrologic variables. Results show how precipitation uncertainty propagates through the different hydrologic model structures to manifest in reduction of error in hydrologic variables.

  5. Hydrologic characteristics of freshwater mussel habitat: novel insights from modeled flows

    USGS Publications Warehouse

    Drew, C. Ashton; Eddy, Michele; Kwak, Thomas J.; Cope, W. Gregory; Augspurger, Tom

    2018-01-01

    The ability to model freshwater stream habitat and species distributions is limited by the spatially sparse flow data available from long-term gauging stations. Flow data beyond the immediate vicinity of gauging stations would enhance our ability to explore and characterize hydrologic habitat suitability. The southeastern USA supports high aquatic biodiversity, but threats, such as landuse alteration, climate change, conflicting water-resource demands, and pollution, have led to the imperilment and legal protection of many species. The ability to distinguish suitable from unsuitable habitat conditions, including hydrologic suitability, is a key criterion for successful conservation and restoration of aquatic species. We used the example of the critically endangered Tar River Spinymussel (Parvaspina steinstansana) and associated species to demonstrate the value of modeled flow data (WaterFALL™) to generate novel insights into population structure and testable hypotheses regarding hydrologic suitability. With ordination models, we: 1) identified all catchments with potentially suitable hydrology, 2) identified 2 distinct hydrologic environments occupied by the Tar River Spinymussel, and 3) estimated greater hydrological habitat niche breadth of assumed surrogate species associates at the catchment scale. Our findings provide the first demonstrated application of complete, continuous, regional modeled hydrologic data to freshwater mussel distribution and management. This research highlights the utility of modeling and data-mining methods to facilitate further exploration and application of such modeled environmental conditions to inform aquatic species management. We conclude that such an approach can support landscape-scale management decisions that require spatial information at fine resolution (e.g., enhanced National Hydrology Dataset catchments) and broad extent (e.g., multiple river basins).

  6. From spatially variable streamflow to distributed hydrological models: Analysis of key modeling decisions

    NASA Astrophysics Data System (ADS)

    Fenicia, Fabrizio; Kavetski, Dmitri; Savenije, Hubert H. G.; Pfister, Laurent

    2016-02-01

    This paper explores the development and application of distributed hydrological models, focusing on the key decisions of how to discretize the landscape, which model structures to use in each landscape element, and how to link model parameters across multiple landscape elements. The case study considers the Attert catchment in Luxembourg—a 300 km2 mesoscale catchment with 10 nested subcatchments that exhibit clearly different streamflow dynamics. The research questions are investigated using conceptual models applied at hydrologic response unit (HRU) scales (1-4 HRUs) on 6 hourly time steps. Multiple model structures are hypothesized and implemented using the SUPERFLEX framework. Following calibration, space/time model transferability is tested using a split-sample approach, with evaluation criteria including streamflow prediction error metrics and hydrological signatures. Our results suggest that: (1) models using geology-based HRUs are more robust and capture the spatial variability of streamflow time series and signatures better than models using topography-based HRUs; this finding supports the hypothesis that, in the Attert, geology exerts a stronger control than topography on streamflow generation, (2) streamflow dynamics of different HRUs can be represented using distinct and remarkably simple model structures, which can be interpreted in terms of the perceived dominant hydrologic processes in each geology type, and (3) the same maximum root zone storage can be used across the three dominant geological units with no loss in model transferability; this finding suggests that the partitioning of water between streamflow and evaporation in the study area is largely independent of geology and can be used to improve model parsimony. The modeling methodology introduced in this study is general and can be used to advance our broader understanding and prediction of hydrological behavior, including the landscape characteristics that control hydrologic response, the

  7. Macroscale hydrologic modeling of ecologically relevant flow metrics

    Treesearch

    Seth J. Wenger; Charles H. Luce; Alan F. Hamlet; Daniel J. Isaak; Helen M. Neville

    2010-01-01

    Stream hydrology strongly affects the structure of aquatic communities. Changes to air temperature and precipitation driven by increased greenhouse gas concentrations are shifting timing and volume of streamflows potentially affecting these communities. The variable infiltration capacity (VIC) macroscale hydrologic model has been employed at regional scales to describe...

  8. Multi-model ensemble hydrologic prediction using Bayesian model averaging

    NASA Astrophysics Data System (ADS)

    Duan, Qingyun; Ajami, Newsha K.; Gao, Xiaogang; Sorooshian, Soroosh

    2007-05-01

    Multi-model ensemble strategy is a means to exploit the diversity of skillful predictions from different models. This paper studies the use of Bayesian model averaging (BMA) scheme to develop more skillful and reliable probabilistic hydrologic predictions from multiple competing predictions made by several hydrologic models. BMA is a statistical procedure that infers consensus predictions by weighing individual predictions based on their probabilistic likelihood measures, with the better performing predictions receiving higher weights than the worse performing ones. Furthermore, BMA provides a more reliable description of the total predictive uncertainty than the original ensemble, leading to a sharper and better calibrated probability density function (PDF) for the probabilistic predictions. In this study, a nine-member ensemble of hydrologic predictions was used to test and evaluate the BMA scheme. This ensemble was generated by calibrating three different hydrologic models using three distinct objective functions. These objective functions were chosen in a way that forces the models to capture certain aspects of the hydrograph well (e.g., peaks, mid-flows and low flows). Two sets of numerical experiments were carried out on three test basins in the US to explore the best way of using the BMA scheme. In the first set, a single set of BMA weights was computed to obtain BMA predictions, while the second set employed multiple sets of weights, with distinct sets corresponding to different flow intervals. In both sets, the streamflow values were transformed using Box-Cox transformation to ensure that the probability distribution of the prediction errors is approximately Gaussian. A split sample approach was used to obtain and validate the BMA predictions. The test results showed that BMA scheme has the advantage of generating more skillful and equally reliable probabilistic predictions than original ensemble. The performance of the expected BMA predictions in terms of

  9. A RETROSPECTIVE ANALYSIS OF MODEL UNCERTAINTY FOR FORECASTING HYDROLOGIC CHANGE

    EPA Science Inventory

    GIS-based hydrologic modeling offers a convenient means of assessing the impacts associated with land-cover/use change for environmental planning efforts. Alternative future scenarios can be used as input to hydrologic models and compared with existing conditions to evaluate pot...

  10. Modeling post-wildfire hydrological processes with ParFlow

    NASA Astrophysics Data System (ADS)

    Escobar, I. S.; Lopez, S. R.; Kinoshita, A. M.

    2017-12-01

    Wildfires alter the natural processes within a watershed, such as surface runoff, evapotranspiration rates, and subsurface water storage. Post-fire hydrologic models are typically one-dimensional, empirically-based models or two-dimensional, conceptually-based models with lumped parameter distributions. These models are useful for modeling and predictions at the watershed outlet; however, do not provide detailed, distributed hydrologic processes at the point scale within the watershed. This research uses ParFlow, a three-dimensional, distributed hydrologic model to simulate post-fire hydrologic processes by representing the spatial and temporal variability of soil burn severity (via hydrophobicity) and vegetation recovery. Using this approach, we are able to evaluate the change in post-fire water components (surface flow, lateral flow, baseflow, and evapotranspiration). This work builds upon previous field and remote sensing analysis conducted for the 2003 Old Fire Burn in Devil Canyon, located in southern California (USA). This model is initially developed for a hillslope defined by a 500 m by 1000 m lateral extent. The subsurface reaches 12.4 m and is assigned a variable cell thickness to explicitly consider soil burn severity throughout the stages of recovery and vegetation regrowth. We consider four slope and eight hydrophobic layer configurations. Evapotranspiration is used as a proxy for vegetation regrowth and is represented by the satellite-based Simplified Surface Energy Balance (SSEBOP) product. The pre- and post-fire surface runoff, subsurface storage, and surface storage interactions are evaluated at the point scale. Results will be used as a basis for developing and fine-tuning a watershed-scale model. Long-term simulations will advance our understanding of post-fire hydrological partitioning between water balance components and the spatial variability of watershed processes, providing improved guidance for post-fire watershed management. In reference

  11. Hydrological excitation of polar motion by different variables of the GLDAS models

    NASA Astrophysics Data System (ADS)

    Wińska, Małgorzata; Nastula, Jolanta

    Continental hydrological loading, by land water, snow, and ice, is an element that is strongly needed for a full understanding of the excitation of polar motion. In this study we compute different estimations of hydrological excitation functions of polar motion (Hydrological Angular Momentum - HAM) using various variables from the Global Land Data Assimilation System (GLDAS) models of land hydrosphere. The main aim of this study is to show the influence of different variables for example: total evapotranspiration, runoff, snowmelt, soil moisture to polar motion excitations in annual and short term scale. In our consideration we employ several realizations of the GLDAS model as: GLDAS Common Land Model (CLM), GLDAS Mosaic Model, GLDAS National Centers for Environmental Prediction/Oregon State University/Air Force/Hydrologic Research Lab Model (Noah), GLDAS Variable Infiltration Capacity (VIC) Model. Hydrological excitation functions of polar motion, both global and regional, are determined by using selected variables of these GLDAS realizations. First we compare a timing, spectra and phase diagrams of different regional and global HAMs with each other. Next, we estimate, the hydrological signal in geodetically observed polar motion excitation by subtracting the atmospheric -- AAM (pressure + wind) and oceanic -- OAM (bottom pressure + currents) contributions. Finally, the hydrological excitations are compared to these hydrological signal in observed polar motion excitation series. The results help us understand which variables of considered hydrological models are the most important for the polar motion excitation and how well we can close polar motion excitation budget in the seasonal and inter-annual spectral ranges.

  12. Diagnosing the impact of alternative calibration strategies on coupled hydrologic models

    NASA Astrophysics Data System (ADS)

    Smith, T. J.; Perera, C.; Corrigan, C.

    2017-12-01

    Hydrologic models represent a significant tool for understanding, predicting, and responding to the impacts of water on society and society on water resources and, as such, are used extensively in water resources planning and management. Given this important role, the validity and fidelity of hydrologic models is imperative. While extensive focus has been paid to improving hydrologic models through better process representation, better parameter estimation, and better uncertainty quantification, significant challenges remain. In this study, we explore a number of competing model calibration scenarios for simple, coupled snowmelt-runoff models to better understand the sensitivity / variability of parameterizations and its impact on model performance, robustness, fidelity, and transferability. Our analysis highlights the sensitivity of coupled snowmelt-runoff model parameterizations to alterations in calibration approach, underscores the concept of information content in hydrologic modeling, and provides insight into potential strategies for improving model robustness / fidelity.

  13. Correcting Inadequate Model Snow Process Descriptions Dramatically Improves Mountain Hydrology Simulations

    NASA Astrophysics Data System (ADS)

    Pomeroy, J. W.; Fang, X.

    2014-12-01

    The vast effort in hydrology devoted to parameter calibration as a means to improve model performance assumes that the models concerned are not fundamentally wrong. By focussing on finding optimal parameter sets and ascribing poor model performance to parameter or data uncertainty, these efforts may fail to consider the need to improve models with more intelligent descriptions of hydrological processes. To test this hypothesis, a flexible physically based hydrological model including a full suite of snow hydrology processes as well as warm season, hillslope and groundwater hydrology was applied to Marmot Creek Research Basin, Canadian Rocky Mountains where excellent driving meteorology and basin biophysical descriptions exist. Model parameters were set from values found in the basin or from similar environments; no parameters were calibrated. The model was tested against snow surveys and streamflow observations. The model used algorithms that describe snow redistribution, sublimation and forest canopy effects on snowmelt and evaporative processes that are rarely implemented in hydrological models. To investigate the contribution of these processes to model predictive capability, the model was "falsified" by deleting parameterisations for forest canopy snow mass and energy, blowing snow, intercepted rain evaporation, and sublimation. Model falsification by ignoring forest canopy processes contributed to a large increase in SWE errors for forested portions of the research basin with RMSE increasing from 19 to 55 mm and mean bias (MB) increasing from 0.004 to 0.62. In the alpine tundra portion, removing blowing processes resulted in an increase in model SWE MB from 0.04 to 2.55 on north-facing slopes and -0.006 to -0.48 on south-facing slopes. Eliminating these algorithms degraded streamflow prediction with the Nash Sutcliffe efficiency dropping from 0.58 to 0.22 and MB increasing from 0.01 to 0.09. These results show dramatic model improvements by including snow

  14. Towards simplification of hydrologic modeling: Identification of dominant processes

    USGS Publications Warehouse

    Markstrom, Steven; Hay, Lauren E.; Clark, Martyn P.

    2016-01-01

    The Precipitation–Runoff Modeling System (PRMS), a distributed-parameter hydrologic model, has been applied to the conterminous US (CONUS). Parameter sensitivity analysis was used to identify: (1) the sensitive input parameters and (2) particular model output variables that could be associated with the dominant hydrologic process(es). Sensitivity values of 35 PRMS calibration parameters were computed using the Fourier amplitude sensitivity test procedure on 110 000 independent hydrologically based spatial modeling units covering the CONUS and then summarized to process (snowmelt, surface runoff, infiltration, soil moisture, evapotranspiration, interflow, baseflow, and runoff) and model performance statistic (mean, coefficient of variation, and autoregressive lag 1). Identified parameters and processes provide insight into model performance at the location of each unit and allow the modeler to identify the most dominant process on the basis of which processes are associated with the most sensitive parameters. The results of this study indicate that: (1) the choice of performance statistic and output variables has a strong influence on parameter sensitivity, (2) the apparent model complexity to the modeler can be reduced by focusing on those processes that are associated with sensitive parameters and disregarding those that are not, (3) different processes require different numbers of parameters for simulation, and (4) some sensitive parameters influence only one hydrologic process, while others may influence many

  15. Feedback Loop of Data Infilling Using Model Result of Actual Evapotranspiration from Satellites and Hydrological Model

    NASA Astrophysics Data System (ADS)

    Murdi Hartanto, Isnaeni; Alexandridis, Thomas K.; van Andel, Schalk Jan; Solomatine, Dimitri

    2014-05-01

    Using satellite data in a hydrological model has long been occurring in modelling of hydrological processes, as a source of low cost regular data. The methods range from using satellite products as direct input, model validation, and data assimilation. However, the satellite data frequently face the missing value problem, whether due to the cloud cover or the limited temporal coverage. The problem could seriously affect its usefulness in hydrological model, especially if the model uses it as direct input, so data infilling becomes one of the important parts in the whole modelling exercise. In this research, actual evapotranspiration product from satellite is directly used as input into a spatially distributed hydrological model, and validated by comparing the catchment's end discharge with measured data. The instantaneous actual evapotranspiration is estimated from MODIS satellite images using a variation of the energy balance model for land (SEBAL). The eight-day cumulative actual evapotranspiration is then obtained by a temporal integration that uses the reference evapotranspiration calculated from meteorological data [1]. However, the above method cannot fill in a cell if the cell is constantly having no-data value during the eight-day periods. The hydrological model requires full set of data without no-data cells, hence, the no-data cells in the satellite's evapotranspiration map need to be filled in. In order to fills the no-data cells, an output of hydrological model is used. The hydrological model is firstly run with reference evapotranspiration as input to calculate discharge and actual evapotranspiration. The no-data cells in the eight-day cumulative map from the satellite are then filled in with the output of the first run of hydrological model. The final data is then used as input in a hydrological model to calculate discharge, thus creating a loop. The method is applied in the case study of Rijnland, the Netherlands where in the winter, cloud cover is

  16. Combined effects of climate and land-use change on the provision of ecosystem services in rice agro-ecosystems

    NASA Astrophysics Data System (ADS)

    Langerwisch, Fanny; Václavík, Tomáš; von Bloh, Werner; Vetter, Tobias; Thonicke, Kirsten

    2018-01-01

    Irrigated rice croplands are among the world’s most important agro-ecosystems. They provide food for more than 3.5 billion people and a range of other ecosystem services (ESS). However, the sustainability of rice agro-ecosystems is threatened by continuing climate and land-use changes. To estimate their combined effects on a bundle of ESS, we applied the vegetation and hydrology model LPJmL to seven study areas in the Philippines and Vietnam. We quantified future changes in the provision of four essential ESS (carbon storage, carbon sequestration, provision of irrigation water and rice production) under two climate scenarios (until 2100) and three site-specific land-use scenarios (until 2030), and examined the synergies and trade-offs in ESS responses to these drivers. Our results show that not all services can be provided in the same amounts in the future. In the Philippines and Vietnam the projections estimated a decrease in rice yields (by approximately 30%) and in carbon storage (by 15%) and sequestration (by 12%) towards the end of the century under the current land-use pattern. In contrast, the amount of available irrigation water was projected to increase in all scenarios by 10%-20%. However, the results also indicate that land-use change may partially offset the negative climate impacts in regions where cropland expansion is possible, although only at the expense of natural vegetation. When analysing the interactions between ESS, we found consistent synergies between rice production and carbon storage and trade-offs between carbon storage and provision of irrigation water under most scenarios. Our results show that not only the effects of climate and land-use change alone but also the interaction between ESS have to be considered to allow sustainable management of rice agro-ecosystems under global change.

  17. JAMS - a software platform for modular hydrological modelling

    NASA Astrophysics Data System (ADS)

    Kralisch, Sven; Fischer, Christian

    2015-04-01

    Current challenges of understanding and assessing the impacts of climate and land use changes on environmental systems demand for an ever-increasing integration of data and process knowledge in corresponding simulation models. Software frameworks that allow for a seamless creation of integrated models based on less complex components (domain models, process simulation routines) have therefore gained increasing attention during the last decade. JAMS is an Open-Source software framework that has been especially designed to cope with the challenges of eco-hydrological modelling. This is reflected by (i) its flexible approach for representing time and space, (ii) a strong separation of process simulation components from the declarative description of more complex models using domain specific XML, (iii) powerful analysis and visualization functions for spatial and temporal input and output data, and (iv) parameter optimization and uncertainty analysis functions commonly used in environmental modelling. Based on JAMS, different hydrological and nutrient-transport simulation models were implemented and successfully applied during the last years. We will present the JAMS core concepts and give an overview of models, simulation components and support tools available for that framework. Sample applications will be used to underline the advantages of component-based model designs and to show how JAMS can be used to address the challenges of integrated hydrological modelling.

  18. Hydrology under change: an evaluation protocol to investigate how hydrological models deal with changing catchments

    Treesearch

    G. Thirel; V. Andreassian; C. Perrin; J.-N. Audouy; L. Berthet; Pamela Edwards; N. Folton; C. Furusho; A. Kuentz; J. Lerat; G. Lindstrom; E. Martin; T. Mathevet; R. Merz; J. Parajka; D. Ruelland; J. Vaze

    2015-01-01

    Testing hydrological models under changing conditions is essential to evaluate their ability to cope with changing catchments and their suitability for impact studies. With this perspective in mind, a workshop dedicated to this issue was held at the 2013 General Assembly of the International Association of Hydrological Sciences (IAHS) in Göteborg, Sweden, in July 2013...

  19. A sensitivity analysis of regional and small watershed hydrologic models

    NASA Technical Reports Server (NTRS)

    Ambaruch, R.; Salomonson, V. V.; Simmons, J. W.

    1975-01-01

    Continuous simulation models of the hydrologic behavior of watersheds are important tools in several practical applications such as hydroelectric power planning, navigation, and flood control. Several recent studies have addressed the feasibility of using remote earth observations as sources of input data for hydrologic models. The objective of the study reported here was to determine how accurately remotely sensed measurements must be to provide inputs to hydrologic models of watersheds, within the tolerances needed for acceptably accurate synthesis of streamflow by the models. The study objective was achieved by performing a series of sensitivity analyses using continuous simulation models of three watersheds. The sensitivity analysis showed quantitatively how variations in each of 46 model inputs and parameters affect simulation accuracy with respect to five different performance indices.

  20. On science versus engineering in hydrological modelling

    NASA Astrophysics Data System (ADS)

    Melsen, Lieke

    2017-04-01

    It is always stressed that hydrological modelling is very important, to prevent floods, to mitigate droughts, to ensure food production or nature conservation. All very true, but I believe that focussing so much on the application of our knowledge (which I call `the engineering approach'), does not stimulate thorough system understanding (which I call `the scientific approach'). In many studies, science and engineering approaches are mixed, which results in large uncertainty e.g. due to a lack of system understanding. To what extent engineering and science approached are mixed depends on the Philosophy of Science of the researcher; verificationism seems to be closer related to engineering, than falsificationism or Bayesianism. In order to grow our scientific knowledge, which means increasing our understanding of the system, we need to be more critical towards the models that we use, but also recognize all the processes that influence the hydrological cycle. In an era called 'The Anthropocene' the influence of humans on the water system can no longer be neglected, and if we choose a scientific approach we have to account for human-induced processes. Summarizing, I believe that we have to account for human impact on the hydrological system, but we have to resist the temptation to directly quantify the hydrological impact on the human system.

  1. Comparisons of regional Hydrological Angular Momentum (HAM) of the different models

    NASA Astrophysics Data System (ADS)

    Nastula, J.; Kolaczek, B.; Popinski, W.

    2006-10-01

    In the paper hydrological excitations of the polar motion (HAM) were computed from various hydrological data series (NCEP, ECMWF, CPC water storage and LaD World Simulations of global continental water). HAM series obtained from these four models and the geodetic excitation function GEOD computed from the polar motion COMB03 data were compared in the seasonal spectral band. The results show big differences of these hydrological excitation functions as well as of their spectra in the seasonal spectra band. Seasonal oscillations of the global geophysical excitation functions (AAM + OAM + HAM) in all cases besides the NCEP/NCAR model are smaller than the geodetic excitation function. It means that these models need further improvement and perhaps not only hydrological models need improvements.

  2. Improving Permafrost Hydrology Prediction Through Data-Model Integration

    NASA Astrophysics Data System (ADS)

    Wilson, C. J.; Andresen, C. G.; Atchley, A. L.; Bolton, W. R.; Busey, R.; Coon, E.; Charsley-Groffman, L.

    2017-12-01

    The CMIP5 Earth System Models were unable to adequately predict the fate of the 16GT of permafrost carbon in a warming climate due to poor representation of Arctic ecosystem processes. The DOE Office of Science Next Generation Ecosystem Experiment, NGEE-Arctic project aims to reduce uncertainty in the Arctic carbon cycle and its impact on the Earth's climate system by improved representation of the coupled physical, chemical and biological processes that drive how much buried carbon will be converted to CO2 and CH4, how fast this will happen, which form will dominate, and the degree to which increased plant productivity will offset increased soil carbon emissions. These processes fundamentally depend on permafrost thaw rate and its influence on surface and subsurface hydrology through thermal erosion, land subsidence and changes to groundwater flow pathways as soil, bedrock and alluvial pore ice and massive ground ice melts. LANL and its NGEE colleagues are co-developing data and models to better understand controls on permafrost degradation and improve prediction of the evolution of permafrost and its impact on Arctic hydrology. The LANL Advanced Terrestrial Simulator was built using a state of the art HPC software framework to enable the first fully coupled 3-dimensional surface-subsurface thermal-hydrology and land surface deformation simulations to simulate the evolution of the physical Arctic environment. Here we show how field data including hydrology, snow, vegetation, geochemistry and soil properties, are informing the development and application of the ATS to improve understanding of controls on permafrost stability and permafrost hydrology. The ATS is being used to inform parameterizations of complex coupled physical, ecological and biogeochemical processes for implementation in the DOE ACME land model, to better predict the role of changing Arctic hydrology on the global climate system. LA-UR-17-26566.

  3. Probabilistic flood inundation prediction within a coupled hydrodynamic, distributed hydrologic modeling framework

    NASA Astrophysics Data System (ADS)

    Adams, T. E.

    2016-12-01

    Accurate and timely predictions of the lateral exent of floodwaters and water level depth in floodplain areas are critical globally. This paper demonstrates the coupling of hydrologic ensembles, derived from the use of numerical weather prediction (NWP) model forcings as input to a fully distributed hydrologic model. Resulting ensemble output from the distributed hydrologic model are used as upstream flow boundaries and lateral inflows to a 1-D hydrodynamic model. An example is presented for the Potomac River in the vicinity of Washington, DC (USA). The approach taken falls within the broader goals of the Hydrologic Ensemble Prediction EXperiment (HEPEX).

  4. Strategies for using remotely sensed data in hydrologic models

    NASA Technical Reports Server (NTRS)

    Peck, E. L.; Keefer, T. N.; Johnson, E. R. (Principal Investigator)

    1981-01-01

    Present and planned remote sensing capabilities were evaluated. The usefulness of six remote sensing capabilities (soil moisture, land cover, impervious area, areal extent of snow cover, areal extent of frozen ground, and water equivalent of the snow cover) with seven hydrologic models (API, CREAMS, NWSRFS, STORM, STANFORD, SSARR, and NWSRFS Snowmelt) were reviewed. The results indicate remote sensing information has only limited value for use with the hydrologic models in their present form. With minor modifications to the models the usefulness would be enhanced. Specific recommendations are made for incorporating snow covered area measurements in the NWSRFS Snowmelt model. Recommendations are also made for incorporating soil moisture measurements in NWSRFS. Suggestions are made for incorporating snow covered area, soil moisture, and others in STORM and SSARR. General characteristics of a hydrologic model needed to make maximum use of remotely sensed data are discussed. Suggested goals for improvements in remote sensing for use in models are also established.

  5. Sharing hydrological knowledge: an international comparison of hydrological models in the Meuse River Basin

    NASA Astrophysics Data System (ADS)

    Bouaziz, Laurène; Sperna Weiland, Frederiek; Drogue, Gilles; Brauer, Claudia; Weerts, Albrecht

    2015-04-01

    International collaboration between institutes and universities working and studying the same transboundary basin is needed for consensus building around possible effects of climate change and climate adaptation measures. Education, experience and expert knowledge of the hydrological community have resulted in the development of a great variety of model concepts, calibration and analysis techniques. Intercomparison could be a first step into consensus modeling or an ensemble based modeling strategy. Besides these practical objectives, such an intercomparison offers the opportunity to explore different ranges of models and learn from each other, hopefully increasing the insight into the hydrological processes that play a role in the transboundary basin. In this experiment, different international research groups applied their rainfall-runoff model in the Ourthe, a Belgium sub-catchment of the Meuse. Data preparation involved the interpolation of hourly precipitation station data collected and owned by the Service Public de Wallonie1 and the freely available E-OBS dataset for daily temperature (Haylock et al., 2008). Daily temperature was disaggregated to hourly values and potential evaporation was derived with the Hargreaves formula. The data was made available to the researchers through an FTP server. The protocol for the modeling involved a split-sample calibration and validation for pre-defined periods. Objective functions for calibration were fixed but the calibration algorithm was a free choice of the research groups. The selection of calibration algorithm was considered model dependent because lumped as well as computationally less efficient distributed models were used. For each model, an ensemble of best performing parameter sets was selected and several performance metrics enabled to assess the models' abilities to simulate discharge. The aim of this experiment is to identify those model components and structures that increase model performance and may best

  6. Simulated discharge trends indicate robustness of hydrological models in a changing climate

    NASA Astrophysics Data System (ADS)

    Addor, Nans; Nikolova, Silviya; Seibert, Jan

    2016-04-01

    Assessing the robustness of hydrological models under contrasted climatic conditions should be part any hydrological model evaluation. Robust models are particularly important for climate impact studies, as models performing well under current conditions are not necessarily capable of correctly simulating hydrological perturbations caused by climate change. A pressing issue is the usually assumed stationarity of parameter values over time. Modeling experiments using conceptual hydrological models revealed that assuming transposability of parameters values in changing climatic conditions can lead to significant biases in discharge simulations. This raises the question whether parameter values should to be modified over time to reflect changes in hydrological processes induced by climate change. Such a question denotes a focus on the contribution of internal processes (i.e., catchment processes) to discharge generation. Here we adopt a different perspective and explore the contribution of external forcing (i.e., changes in precipitation and temperature) to changes in discharge. We argue that in a robust hydrological model, discharge variability should be induced by changes in the boundary conditions, and not by changes in parameter values. In this study, we explore how well the conceptual hydrological model HBV captures transient changes in hydrological signatures over the period 1970-2009. Our analysis focuses on research catchments in Switzerland undisturbed by human activities. The precipitation and temperature forcing are extracted from recently released 2km gridded data sets. We use a genetic algorithm to calibrate HBV for the whole 40-year period and for the eight successive 5-year periods to assess eventual trends in parameter values. Model calibration is run multiple times to account for parameter uncertainty. We find that in alpine catchments showing a significant increase of winter discharge, this trend can be captured reasonably well with constant

  7. Neural Networks for Hydrological Modeling Tool for Operational Purposes

    NASA Astrophysics Data System (ADS)

    Bhatt, Divya; Jain, Ashu

    2010-05-01

    Hydrological models are useful in many water resources applications such as flood control, irrigation and drainage, hydro power generation, water supply, erosion and sediment control, etc. Estimates of runoff are needed in many water resources planning, design development, operation and maintenance activities. Runoff is generally computed using rainfall-runoff models. Computer based hydrologic models have become popular for obtaining hydrological forecasts and for managing water systems. Rainfall-runoff library (RRL) is computer software developed by Cooperative Research Centre for Catchment Hydrology (CRCCH), Australia consisting of five different conceptual rainfall-runoff models, and has been in operation in many water resources applications in Australia. Recently, soft artificial intelligence tools such as Artificial Neural Networks (ANNs) have become popular for research purposes but have not been adopted in operational hydrological forecasts. There is a strong need to develop ANN models based on real catchment data and compare them with the conceptual models actually in use in real catchments. In this paper, the results from an investigation on the use of RRL and ANNs are presented. Out of the five conceptual models in the RRL toolkit, SimHyd model has been used. Genetic Algorithm has been used as an optimizer in the RRL to calibrate the SimHyd model. Trial and error procedures were employed to arrive at the best values of various parameters involved in the GA optimizer to develop the SimHyd model. The results obtained from the best configuration of the SimHyd model are presented here. Feed-forward neural network model structure trained by back-propagation training algorithm has been adopted here to develop the ANN models. The daily rainfall and runoff data derived from Bird Creek Basin, Oklahoma, USA have been employed to develop all the models included here. A wide range of error statistics have been used to evaluate the performance of all the models

  8. Quantifying and Generalizing Hydrologic Responses to Dam Regulation using a Statistical Modeling Approach

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    McManamay, Ryan A

    2014-01-01

    Despite the ubiquitous existence of dams within riverscapes, much of our knowledge about dams and their environmental effects remains context-specific. Hydrology, more than any other environmental variable, has been studied in great detail with regard to dam regulation. While much progress has been made in generalizing the hydrologic effects of regulation by large dams, many aspects of hydrology show site-specific fidelity to dam operations, small dams (including diversions), and regional hydrologic regimes. A statistical modeling framework is presented to quantify and generalize hydrologic responses to varying degrees of dam regulation. Specifically, the objectives were to 1) compare the effects ofmore » local versus cumulative dam regulation, 2) determine the importance of different regional hydrologic regimes in influencing hydrologic responses to dams, and 3) evaluate how different regulation contexts lead to error in predicting hydrologic responses to dams. Overall, model performance was poor in quantifying the magnitude of hydrologic responses, but performance was sufficient in classifying hydrologic responses as negative or positive. Responses of some hydrologic indices to dam regulation were highly dependent upon hydrologic class membership and the purpose of the dam. The opposing coefficients between local and cumulative-dam predictors suggested that hydrologic responses to cumulative dam regulation are complex, and predicting the hydrology downstream of individual dams, as opposed to multiple dams, may be more easy accomplished using statistical approaches. Results also suggested that particular contexts, including multipurpose dams, high cumulative regulation by multiple dams, diversions, close proximity to dams, and certain hydrologic classes are all sources of increased error when predicting hydrologic responses to dams. Statistical models, such as the ones presented herein, show promise in their ability to model the effects of dam regulation effects

  9. Hydrologic Implications of Dynamical and Statistical Approaches to Downscaling Climate Model Outputs

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Wood, Andrew W; Leung, Lai R; Sridhar, V

    Six approaches for downscaling climate model outputs for use in hydrologic simulation were evaluated, with particular emphasis on each method's ability to produce precipitation and other variables used to drive a macroscale hydrology model applied at much higher spatial resolution than the climate model. Comparisons were made on the basis of a twenty-year retrospective (1975–1995) climate simulation produced by the NCAR-DOE Parallel Climate Model (PCM), and the implications of the comparison for a future (2040–2060) PCM climate scenario were also explored. The six approaches were made up of three relatively simple statistical downscaling methods – linear interpolation (LI), spatial disaggregationmore » (SD), and bias-correction and spatial disaggregation (BCSD) – each applied to both PCM output directly (at T42 spatial resolution), and after dynamical downscaling via a Regional Climate Model (RCM – at ½-degree spatial resolution), for downscaling the climate model outputs to the 1/8-degree spatial resolution of the hydrological model. For the retrospective climate simulation, results were compared to an observed gridded climatology of temperature and precipitation, and gridded hydrologic variables resulting from forcing the hydrologic model with observations. The most significant findings are that the BCSD method was successful in reproducing the main features of the observed hydrometeorology from the retrospective climate simulation, when applied to both PCM and RCM outputs. Linear interpolation produced better results using RCM output than PCM output, but both methods (PCM-LI and RCM-LI) lead to unacceptably biased hydrologic simulations. Spatial disaggregation of the PCM output produced results similar to those achieved with the RCM interpolated output; nonetheless, neither PCM nor RCM output was useful for hydrologic simulation purposes without a bias-correction step. For the future climate scenario, only the BCSD-method (using PCM or RCM) was able

  10. A framework for human-hydrologic system model development integrating hydrology and water management: application to the Cutzamala water system in Mexico

    NASA Astrophysics Data System (ADS)

    Wi, S.; Freeman, S.; Brown, C.

    2017-12-01

    This study presents a general approach to developing computational models of human-hydrologic systems where human modification of hydrologic surface processes are significant or dominant. A river basin system is represented by a network of human-hydrologic response units (HHRUs) identified based on locations where river regulations happen (e.g., reservoir operation and diversions). Natural and human processes in HHRUs are simulated in a holistic framework that integrates component models representing rainfall-runoff, river routing, reservoir operation, flow diversion and water use processes. We illustrate the approach in a case study of the Cutzamala water system (CWS) in Mexico, a complex inter-basin water transfer system supplying the Mexico City Metropolitan Area (MCMA). The human-hydrologic system model for CWS (CUTZSIM) is evaluated in terms of streamflow and reservoir storages measured across the CWS and to water supplied for MCMA. The CUTZSIM improves the representation of hydrology and river-operation interaction and, in so doing, advances evaluation of system-wide water management consequences under altered climatic and demand regimes. The integrated modeling framework enables evaluation and simulation of model errors throughout the river basin, including errors in representation of the human component processes. Heretofore, model error evaluation, predictive error intervals and the resultant improved understanding have been limited to hydrologic processes. The general framework represents an initial step towards fuller understanding and prediction of the many and varied processes that determine the hydrologic fluxes and state variables in real river basins.

  11. Modeling non-linear growth responses to temperature and hydrology in wetland trees

    NASA Astrophysics Data System (ADS)

    Keim, R.; Allen, S. T.

    2016-12-01

    Growth responses of wetland trees to flooding and climate variations are difficult to model because they depend on multiple, apparently interacting factors, but are a critical link in hydrological control of wetland carbon budgets. To more generally understand tree growth to hydrological forcing, we modeled non-linear responses of tree ring growth to flooding and climate at sub-annual time steps, using Vaganov-Shashkin response functions. We calibrated the model to six baldcypress tree-ring chronologies from two hydrologically distinct sites in southern Louisiana, and tested several hypotheses of plasticity in wetlands tree responses to interacting environmental variables. The model outperformed traditional multiple linear regression. More importantly, optimized response parameters were generally similar among sites with varying hydrological conditions, suggesting generality to the functions. Model forms that included interacting responses to multiple forcing factors were more effective than were single response functions, indicating the principle of a single limiting factor is not correct in wetlands and both climatic and hydrological variables must be considered in predicting responses to hydrological or climate change.

  12. Hydrological Modeling of the Jiaoyi Watershed (China) Using HSPF Model

    PubMed Central

    Yan, Chang-An; Zhang, Wanchang; Zhang, Zhijie

    2014-01-01

    A watershed hydrological model, hydrological simulation program-Fortran (HSPF), was applied to simulate the spatial and temporal variation of hydrological processes in the Jiaoyi watershed of Huaihe River Basin, the heaviest shortage of water resources and polluted area in China. The model was calibrated using the years 2001–2004 and validated with data from 2005 to 2006. Calibration and validation results showed that the model generally simulated mean monthly and daily runoff precisely due to the close matching hydrographs between simulated and observed runoff, as well as the excellent evaluation indicators such as Nash-Sutcliffe efficiency (NSE), coefficient of correlation (R 2), and the relative error (RE). The similar simulation results between calibration and validation period showed that all the calibrated parameters had a certain representation in Jiaoyi watershed. Additionally, the simulation in rainy months was more accurate than the drought months. Another result in this paper was that HSPF was also capable of estimating the water balance components reasonably and realistically in space through the whole watershed. The calibrated model can be used to explore the effects of climate change scenarios and various watershed management practices on the water resources and water environment in the basin. PMID:25013863

  13. WEB-DHM: A distributed biosphere hydrological model developed by coupling a simple biosphere scheme with a hillslope hydrological model

    USDA-ARS?s Scientific Manuscript database

    The coupling of land surface models and hydrological models potentially improves the land surface representation, benefiting both the streamflow prediction capabilities as well as providing improved estimates of water and energy fluxes into the atmosphere. In this study, the simple biosphere model 2...

  14. Advances in Applications of Hierarchical Bayesian Methods with Hydrological Models

    NASA Astrophysics Data System (ADS)

    Alexander, R. B.; Schwarz, G. E.; Boyer, E. W.

    2017-12-01

    Mechanistic and empirical watershed models are increasingly used to inform water resource decisions. Growing access to historical stream measurements and data from in-situ sensor technologies has increased the need for improved techniques for coupling models with hydrological measurements. Techniques that account for the intrinsic uncertainties of both models and measurements are especially needed. Hierarchical Bayesian methods provide an efficient modeling tool for quantifying model and prediction uncertainties, including those associated with measurements. Hierarchical methods can also be used to explore spatial and temporal variations in model parameters and uncertainties that are informed by hydrological measurements. We used hierarchical Bayesian methods to develop a hybrid (statistical-mechanistic) SPARROW (SPAtially Referenced Regression On Watershed attributes) model of long-term mean annual streamflow across diverse environmental and climatic drainages in 18 U.S. hydrological regions. Our application illustrates the use of a new generation of Bayesian methods that offer more advanced computational efficiencies than the prior generation. Evaluations of the effects of hierarchical (regional) variations in model coefficients and uncertainties on model accuracy indicates improved prediction accuracies (median of 10-50%) but primarily in humid eastern regions, where model uncertainties are one-third of those in arid western regions. Generally moderate regional variability is observed for most hierarchical coefficients. Accounting for measurement and structural uncertainties, using hierarchical state-space techniques, revealed the effects of spatially-heterogeneous, latent hydrological processes in the "localized" drainages between calibration sites; this improved model precision, with only minor changes in regional coefficients. Our study can inform advances in the use of hierarchical methods with hydrological models to improve their integration with stream

  15. [Agro-household livelihood vulnerability and influence factors of ethnic villages under different geomorphology backgrounds.

    PubMed

    Han, Wen Wen; Liu, Xiao Peng; Pei, Yin Bao; An, Qiong; Li, Yong Hong

    2016-04-22

    The vulnerability and influence factors of agro-household livelihood in Haiyuan County, Ningxia were empirically analyzed utilizing set pair analysis and obstacle degree model, based on field survey data of impoverished agro-households in 2014. Results showed that vulnerability of agro-household livelihood in Haiyuan County was high in general while it exhibited geomorphological and ethnical differences. Vulnerability of agro-households livelihood in plain areas, valleys and intermountain depression areas were lower than that in earth-rock areas, loess ridge areas and moderately high mountain landform areas. Moreover, vulnerability of agro-household livelihood was higher in mixed Hui and Han ethnic villages than in mono Hui or Han ethnic villages. The villagers' lacking of necessities and the stress of sensitive external geographical environment were considered to be the fundamental reasons of vulnerability of agro-household livelihood. The unreasonable livelihood structure and the unvariant livelihood strategy caused the long-term accumulation of livelihood vulnerabi-lity. The nature of the local environment, which was not easy to change, decreased the accessibility of poverty alleviation resources. Building a clear village water rights allocation system, the implementation of counterpart-assistance to educate impoverished families, increasing investment in improving the diversities of means of living, developing the chains of comprehensive commodity market among villages, were necessary to improve the response capability of agro-household livelihood. The management of vulnerability of agro-household livelihood should put the 'Extending Roads to Every Village Project' on a more prominent position in the 'Extending Radio and TV Broadcasting Coverage to Every Village Project'. Furthermore, the combination of meteorological disaster prevention and insurance enterprise disaster reduction should be sought, and the agricultural production insurance system should be

  16. Impact of vegetation dynamics on hydrological processes in a semi-arid basin by using a land surface-hydrology coupled model

    NASA Astrophysics Data System (ADS)

    Jiao, Yang; Lei, Huimin; Yang, Dawen; Huang, Maoyi; Liu, Dengfeng; Yuan, Xing

    2017-08-01

    Land surface models (LSMs) are widely used to understand the interactions between hydrological processes and vegetation dynamics, which is important for the attribution and prediction of regional hydrological variations. However, most LSMs have large uncertainties in their representations of eco-hydrological processes due to deficiencies in hydrological parameterizations. In this study, the Community Land Model version 4 (CLM4) LSM was modified with an advanced runoff generation and flow routing scheme, resulting in a new land surface-hydrology coupled model, CLM-GBHM. Both models were implemented in the Wudinghe River Basin (WRB), which is a semi-arid basin located in the middle reaches of the Yellow River, China. Compared with CLM, CLM-GBHM increased the Nash Sutcliffe efficiency for daily river discharge simulation (1965-1969) from -0.03 to 0.23 and reduced the relative bias in water table depth simulations (2010-2012) from 32.4% to 13.4%. The CLM-GBHM simulations with static, remotely sensed and model-predicted vegetation conditions showed that the vegetation in the WRB began to recover in the 2000s due to the Grain for Green Program but had not reached the same level of vegetation cover as regions in natural eco-hydrological equilibrium. Compared with a simulation using remotely sensed vegetation cover, the simulation with a dynamic vegetation model that considers only climate-induced change showed a 10.3% increase in evapotranspiration, a 47.8% decrease in runoff, and a 62.7% and 71.3% deceleration in changing trend of the outlet river discharge before and after the year 2000, respectively. This result suggests that both natural and anthropogenic factors should be incorporated in dynamic vegetation models to better simulate the eco-hydrological cycle.

  17. eWaterCycle: A high resolution global hydrological model

    NASA Astrophysics Data System (ADS)

    van de Giesen, Nick; Bierkens, Marc; Drost, Niels; Hut, Rolf; Sutanudjaja, Edwin

    2014-05-01

    In 2013, the eWaterCycle project was started, which has the ambitious goal to run a high resolution global hydrological model. Starting point was the PCR-GLOBWB built by Utrecht University. The software behind this model will partially be re-engineered in order to enable to run it in a High Performance Computing (HPC) environment. The aim is to have a spatial resolution of 1km x 1km. The idea is also to run the model in real-time and forecasting mode, using data assimilation. An on-demand hydraulic model will be available for detailed flow and flood forecasting in support of navigation and disaster management. The project faces a set of scientific challenges. First, to enable the model to run in a HPC environment, model runs were analyzed to examine on which parts of the program most CPU time was spent. These parts were re-coded in Open MPI to allow for parallel processing. Different parallelization strategies are thinkable. In our case, it was decided to use watershed logic as a first step to distribute the analysis. There is rather limited recent experience with HPC in hydrology and there is much to be learned and adjusted, both on the hydrological modeling side and the computer science side. For example, an interesting early observation was that hydrological models are, due to their localized parameterization, much more memory intensive than models of sister-disciplines such as meteorology and oceanography. Because it would be deadly to have to swap information between CPU and hard drive, memory management becomes crucial. A standard Ensemble Kalman Filter (enKF) would, for example, have excessive memory demands. To circumvent these problems, an alternative to the enKF was developed that produces equivalent results. This presentation shows the most recent results from the model, including a 5km x 5km simulation and a proof of concept for the new data assimilation approach. Finally, some early ideas about financial sustainability of an operational global

  18. Generation of multi annual land use and crop rotation data for regional agro-ecosystem modeling

    NASA Astrophysics Data System (ADS)

    Waldhoff, G.; Lussem, U.; Sulis, M.; Bareth, G.

    2017-12-01

    For agro-ecosystem modeling on a regional scale with systems like the Community Land Model (CLM), detailed crop type and crop rotation information on the parcel-level is of key importance. Only with this, accurate assessments of the fluxes associated with the succession of crops and their management are possible. However, sophisticated agro-ecosystem modeling for large regions is only feasible at grid resolutions, which are much coarser than the spatial resolution of modern land use maps (usually ca. 30 m). As a result, much of the original information content of the maps has to be dismissed during resampling. Here we present our mapping approach for the Rur catchment (located in the west of Germany), which was developed to address these demands and issues. We integrated remote sensing and geographic information system (GIS) methods to classify multi temporal images of (e.g.) Landsat, RapidEye and Sentinel-2 to generate annual crop maps for the years 2008-2017 at 15 m spatial resolution (accuracy always ca. 90 %). A key aspect of our method is the consideration of crop phenology for the data selection and the analysis. In a GIS, the annul crop maps were integrated to a crop sequence dataset from which the major crop rotations were derived (based on the 10-years). To retain the multi annual crop succession and crop area information at coarser grid resolutions, cell-based land use fractions, including other land use classes were calculated for each year and for various target cell sizes (1-32 arc seconds). The resulting datasets contain the contribution (in percent) of every land use class to each cell. Our results show that parcels with the major crop types can be differentiated with a high accuracy and on an annual basis. The analysis of the crop sequence data revealed a very large number of different crop rotations, but only relatively few crop rotations cover larger areas. This strong diversity emphasizes the importance of information on crop rotations to reduce

  19. Development and comparison of Bayesian modularization method in uncertainty assessment of hydrological models

    NASA Astrophysics Data System (ADS)

    Li, L.; Xu, C.-Y.; Engeland, K.

    2012-04-01

    With respect to model calibration, parameter estimation and analysis of uncertainty sources, different approaches have been used in hydrological models. Bayesian method is one of the most widely used methods for uncertainty assessment of hydrological models, which incorporates different sources of information into a single analysis through Bayesian theorem. However, none of these applications can well treat the uncertainty in extreme flows of hydrological models' simulations. This study proposes a Bayesian modularization method approach in uncertainty assessment of conceptual hydrological models by considering the extreme flows. It includes a comprehensive comparison and evaluation of uncertainty assessments by a new Bayesian modularization method approach and traditional Bayesian models using the Metropolis Hasting (MH) algorithm with the daily hydrological model WASMOD. Three likelihood functions are used in combination with traditional Bayesian: the AR (1) plus Normal and time period independent model (Model 1), the AR (1) plus Normal and time period dependent model (Model 2) and the AR (1) plus multi-normal model (Model 3). The results reveal that (1) the simulations derived from Bayesian modularization method are more accurate with the highest Nash-Sutcliffe efficiency value, and (2) the Bayesian modularization method performs best in uncertainty estimates of entire flows and in terms of the application and computational efficiency. The study thus introduces a new approach for reducing the extreme flow's effect on the discharge uncertainty assessment of hydrological models via Bayesian. Keywords: extreme flow, uncertainty assessment, Bayesian modularization, hydrological model, WASMOD

  20. Hydrological responses to dynamically and statistically downscaled climate model output

    USGS Publications Warehouse

    Wilby, R.L.; Hay, L.E.; Gutowski, W.J.; Arritt, R.W.; Takle, E.S.; Pan, Z.; Leavesley, G.H.; Clark, M.P.

    2000-01-01

    Daily rainfall and surface temperature series were simulated for the Animas River basin, Colorado using dynamically and statistically downscaled output from the National Center for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) re-analysis. A distributed hydrological model was then applied to the downscaled data. Relative to raw NCEP output, downscaled climate variables provided more realistic stimulations of basin scale hydrology. However, the results highlight the sensitivity of modeled processes to the choice of downscaling technique, and point to the need for caution when interpreting future hydrological scenarios.

  1. Numerical modeling of the agricultural-hydrologic system in Punjab, India

    NASA Astrophysics Data System (ADS)

    Nyblade, M.; Russo, T. A.; Zikatanov, L.; Zipp, K.

    2017-12-01

    The goal of food security for India's growing population is threatened by the decline in freshwater resources due to unsustainable water use for irrigation. The issue is acute in parts of Punjab, India, where small landholders produce a major quantity of India's food with declining groundwater resources. To further complicate this problem, other regions of the state are experiencing groundwater logging and salinization, and are reliant on canal systems for fresh water delivery. Due to the lack of water use records, groundwater consumption for this study is estimated with available data on crop yields, climate, and total canal water delivery. The hydrologic and agricultural systems are modeled using appropriate numerical methods and software. This is a state-wide hydrologic numerical model of Punjab that accounts for multiple aquifer layers, agricultural water demands, and interactions between the surface canal system and groundwater. To more accurately represent the drivers of agricultural production and therefore water use, we couple an economic crop optimization model with the hydrologic model. These tools will be used to assess and optimize crop choice scenarios based on farmer income, food production, and hydrologic system constraints. The results of these combined models can be used to further understand the hydrologic system response to government crop procurement policies and climate change, and to assess the effectiveness of possible water conservation solutions.

  2. Parameterization guidelines and considerations for hydrologic models

    Treesearch

     R. W. Malone; G. Yagow; C. Baffaut; M.W  Gitau; Z. Qi; Devendra Amatya; P.B.   Parajuli; J.V. Bonta; T.R.  Green

    2015-01-01

     Imparting knowledge of the physical processes of a system to a model and determining a set of parameter values for a hydrologic or water quality model application (i.e., parameterization) are important and difficult tasks. An exponential...

  3. Research on Multi Hydrological Models Applicability and Modelling Data Uncertainty Analysis for Flash Flood Simulation in Hilly Area

    NASA Astrophysics Data System (ADS)

    Ye, L.; Wu, J.; Wang, L.; Song, T.; Ji, R.

    2017-12-01

    Flooding in small-scale watershed in hilly area is characterized by short time periods and rapid rise and recession due to the complex underlying surfaces, various climate type and strong effect of human activities. It is almost impossible for a single hydrological model to describe the variation of flooding in both time and space accurately for all the catchments in hilly area because the hydrological characteristics can vary significantly among different catchments. In this study, we compare the performance of 5 hydrological models with varying degrees of complexity for simulation of flash flood for 14 small-scale watershed in China in order to find the relationship between the applicability of the hydrological models and the catchments characteristics. Meanwhile, given the fact that the hydrological data is sparse in hilly area, the effect of precipitation data, DEM resolution and their interference on the uncertainty of flood simulation is also illustrated. In general, the results showed that the distributed hydrological model (HEC-HMS in this study) performed better than the lumped hydrological models. Xinajiang and API models had good simulation for the humid catchments when long-term and continuous rainfall data is provided. Dahuofang model can simulate the flood peak well while the runoff generation module is relatively poor. In addition, the effect of diverse modelling data on the simulations is not simply superposed, and there is a complex interaction effect among different modelling data. Overall, both the catchment hydrological characteristics and modelling data situation should be taken into consideration in order to choose the suitable hydrological model for flood simulation for small-scale catchment in hilly area.

  4. Modeling the hydrologic impacts of forest harvesting on Florida flatwoods

    Treesearch

    Ge Sun; Hans Rierkerk; Nicholas B. Comerford

    1998-01-01

    The great temporal and spatial variability of pine flatwoods hydrology suggests traditional short-term field methods may not be effective in evaluating the hydrologic effects of forest management. The flatwoods model was developed, calibrated and validated specifically for the cypress wetland-pine upland landscape. The model was applied to two typical flatwoods sites...

  5. A fully integrated SWAT-MODFLOW hydrologic model

    USDA-ARS?s Scientific Manuscript database

    The Soil and Water Assessment Tool (SWAT) and MODFLOW models are being used worldwide for managing surface and groundwater water resources. The SWAT models hydrological processes occurring at the surface including shallow aquifers, while MODFLOW simulate groundwater processes. However, neither SWAT ...

  6. Spatially-Distributed Stream Flow and Nutrient Dynamics Simulations Using the Component-Based AgroEcoSystem-Watershed (AgES-W) Model

    NASA Astrophysics Data System (ADS)

    Ascough, J. C.; David, O.; Heathman, G. C.; Smith, D. R.; Green, T. R.; Krause, P.; Kipka, H.; Fink, M.

    2010-12-01

    Cedar Creek watershed (CCW) in northeastern Indiana, USA was selected for application of the OMS3-based AgroEcoSystem-Watershed (AgES-W) model. AgES-W performance for stream flow and N loading was assessed using Nash-Sutcliffe model efficiency (ENS) and percent bias (PBIAS) model evaluation statistics. Comparisons of daily and average monthly simulated and observed stream flow and N loads for the 1997-2005 simulation period resulted in PBIAS and ENS values that were similar or better than those reported in the literature for SWAT stream flow and N loading predictions at a similar scale. The results show that the AgES-W model was able to reproduce the hydrological and N dynamics of the CCW with sufficient quality, and should serve as a foundation upon which to better quantify additional water quality indicators (e.g., sediment transport and P dynamics) at the watershed scale.

  7. Agricultural Model for the Nile Basin Decision Support System

    NASA Astrophysics Data System (ADS)

    van der Bolt, Frank; Seid, Abdulkarim

    2014-05-01

    To analyze options for increasing food supply in the Nile basin the Nile Agricultural Model (AM) was developed. The AM includes state-of-the-art descriptions of biophysical, hydrological and economic processes and realizes a coherent and consistent integration of hydrology, agronomy and economics. The AM covers both the agro-ecological domain (water, crop productivity) and the economic domain (food supply, demand, and trade) and allows to evaluate the macro-economic and hydrological impacts of scenarios for agricultural development. Starting with the hydrological information from the NileBasin-DSS the AM calculates the available water for agriculture, the crop production and irrigation requirements with the FAO-model AquaCrop. With the global commodity trade model MAGNET scenarios for land development and conversion are evaluated. The AM predicts consequences for trade, food security and development based on soil and water availability, crop allocation, food demand and food policy. The model will be used as a decision support tool to contribute to more productive and sustainable agriculture in individual Nile countries and the whole region.

  8. Modeling Hydrological Services in Shade Grown Coffee Systems: Case Study of the Pico Duarte Region of the Dominican Republic

    NASA Astrophysics Data System (ADS)

    Erickson, J. D.; Gross, L.; Agosto Filion, N.; Bagstad, K.; Voigt, B. G.; Johnson, G.

    2010-12-01

    The modification of hydrologic systems in coffee-dominated landscapes varies widely according to the degree of shade trees incorporated in coffee farms. Compared to mono-cropping systems, shade coffee can produce both on- and off-farm benefits in the form of soil retention, moderation of sediment transport, and lower hydropower generating costs. The Pico Duarte Coffee Region and surrounding Madres de Las Aguas (Mother of Waters) Conservation Area in the Dominican Republic is emblematic of the challenges and opportunities of ecosystem service management in coffee landscapes. Shade coffee poly-cultures in the region play an essential role in ensuring ecosystem function to conserve water resources, as well as provide habitat for birds, sequester carbon, and provide consumptive resources to households. To model the provision, use, and flow of ecosystem services from coffee farms in the region, an application of the Artificial Intelligence for Ecosystem Services (ARIES) model was developed with particular focus on sediment regulation. ARIES incorporates an array of techniques from data mining, image analysis, neural networks, Bayesian statistics, information theory, and expert systems to model the production, delivery, and demand for ecosystem services. Geospatial data on slope, soils, and vegetation cover is combined with on-farm data collection of coffee production, tree diversity, and intercropping of household food. Given hydropower production and river recreation in the region, the management of sedimentation through on-farm practices has substantial, currently uncompensated value that has received recent attention as the foundation for a payment for ecosystem services system. Scenario analysis of the implications of agro-forestry management choices on farmer livelihoods and the multiple beneficiaries of farm-provided hydrological services provide a foundation for ongoing discussions in the region between local, national, and international interests.

  9. Hydrological Modeling in the Bull Run Watershed in Support of a Piloting Utility Modeling Applications (PUMA) Project

    NASA Astrophysics Data System (ADS)

    Nijssen, B.; Chiao, T. H.; Lettenmaier, D. P.; Vano, J. A.

    2016-12-01

    Hydrologic models with varying complexities and structures are commonly used to evaluate the impact of climate change on future hydrology. While the uncertainties in future climate projections are well documented, uncertainties in streamflow projections associated with hydrologic model structure and parameter estimation have received less attention. In this study, we implemented and calibrated three hydrologic models (the Distributed Hydrology Soil Vegetation Model (DHSVM), the Precipitation-Runoff Modeling System (PRMS), and the Variable Infiltration Capacity model (VIC)) for the Bull Run watershed in northern Oregon using consistent data sources and best practice calibration protocols. The project was part of a Piloting Utility Modeling Applications (PUMA) project with the Portland Water Bureau (PWB) under the umbrella of the Water Utility Climate Alliance (WUCA). Ultimately PWB would use the model evaluation to select a model to perform in-house climate change analysis for Bull Run Watershed. This presentation focuses on the experimental design of the comparison project, project findings and the collaboration between the team at the University of Washington and at PWB. After calibration, the three models showed similar capability to reproduce seasonal and inter-annual variations in streamflow, but differed in their ability to capture extreme events. Furthermore, the annual and seasonal hydrologic sensitivities to changes in climate forcings differed among models, potentially attributable to different model representations of snow and vegetation processes.

  10. Coupled atmosphere-biophysics-hydrology models for environmental modeling

    USGS Publications Warehouse

    Walko, R.L.; Band, L.E.; Baron, Jill S.; Kittel, T.G.F.; Lammers, R.; Lee, T.J.; Ojima, D.; Pielke, R.A.; Taylor, C.; Tague, C.; Tremback, C.J.; Vidale, P.L.

    2000-01-01

    The formulation and implementation of LEAF-2, the Land Ecosystem–Atmosphere Feedback model, which comprises the representation of land–surface processes in the Regional Atmospheric Modeling System (RAMS), is described. LEAF-2 is a prognostic model for the temperature and water content of soil, snow cover, vegetation, and canopy air, and includes turbulent and radiative exchanges between these components and with the atmosphere. Subdivision of a RAMS surface grid cell into multiple areas of distinct land-use types is allowed, with each subgrid area, or patch, containing its own LEAF-2 model, and each patch interacts with the overlying atmospheric column with a weight proportional to its fractional area in the grid cell. A description is also given of TOPMODEL, a land hydrology model that represents surface and subsurface downslope lateral transport of groundwater. Details of the incorporation of a modified form of TOPMODEL into LEAF-2 are presented. Sensitivity tests of the coupled system are presented that demonstrate the potential importance of the patch representation and of lateral water transport in idealized model simulations. Independent studies that have applied LEAF-2 and verified its performance against observational data are cited. Linkage of RAMS and TOPMODEL through LEAF-2 creates a modeling system that can be used to explore the coupled atmosphere–biophysical–hydrologic response to altered climate forcing at local watershed and regional basin scales.

  11. Attaining insight into interactions between hydrologic model parameters and geophysical attributes for national-scale model parameter estimation

    NASA Astrophysics Data System (ADS)

    Mizukami, N.; Clark, M. P.; Newman, A. J.; Wood, A.; Gutmann, E. D.

    2017-12-01

    Estimating spatially distributed model parameters is a grand challenge for large domain hydrologic modeling, especially in the context of hydrologic model applications such as streamflow forecasting. Multi-scale Parameter Regionalization (MPR) is a promising technique that accounts for the effects of fine-scale geophysical attributes (e.g., soil texture, land cover, topography, climate) on model parameters and nonlinear scaling effects on model parameters. MPR computes model parameters with transfer functions (TFs) that relate geophysical attributes to model parameters at the native input data resolution and then scales them using scaling functions to the spatial resolution of the model implementation. One of the biggest challenges in the use of MPR is identification of TFs for each model parameter: both functional forms and geophysical predictors. TFs used to estimate the parameters of hydrologic models typically rely on previous studies or were derived in an ad-hoc, heuristic manner, potentially not utilizing maximum information content contained in the geophysical attributes for optimal parameter identification. Thus, it is necessary to first uncover relationships among geophysical attributes, model parameters, and hydrologic processes (i.e., hydrologic signatures) to obtain insight into which and to what extent geophysical attributes are related to model parameters. We perform multivariate statistical analysis on a large-sample catchment data set including various geophysical attributes as well as constrained VIC model parameters at 671 unimpaired basins over the CONUS. We first calibrate VIC model at each catchment to obtain constrained parameter sets. Additionally, parameter sets sampled during the calibration process are used for sensitivity analysis using various hydrologic signatures as objectives to understand the relationships among geophysical attributes, parameters, and hydrologic processes.

  12. Modular modeling system for building distributed hydrologic models with a user-friendly software package

    NASA Astrophysics Data System (ADS)

    Wi, S.; Ray, P. A.; Brown, C.

    2015-12-01

    A software package developed to facilitate building distributed hydrologic models in a modular modeling system is presented. The software package provides a user-friendly graphical user interface that eases its practical use in water resources-related research and practice. The modular modeling system organizes the options available to users when assembling models according to the stages of hydrological cycle, such as potential evapotranspiration, soil moisture accounting, and snow/glacier melting processes. The software is intended to be a comprehensive tool that simplifies the task of developing, calibrating, validating, and using hydrologic models through the inclusion of intelligent automation to minimize user effort, and reduce opportunities for error. Processes so far automated include the definition of system boundaries (i.e., watershed delineation), climate and geographical input generation, and parameter calibration. Built-in post-processing toolkits greatly improve the functionality of the software as a decision support tool for water resources system management and planning. Example post-processing toolkits enable streamflow simulation at ungauged sites with predefined model parameters, and perform climate change risk assessment by means of the decision scaling approach. The software is validated through application to watersheds representing a variety of hydrologic regimes.

  13. On the Use of Models in Hydrology.

    ERIC Educational Resources Information Center

    de Marsily, G.

    1994-01-01

    This discussion article addresses the nature of models used in hydrology. It proposes a minimalist classification of models into two categories: models built on data from observations of the processes involved, and those for which there are no observation data on any of these processes, at the scale of interest. (LZ)

  14. Modelling water use in global hydrological models: review, challenges and directions

    NASA Astrophysics Data System (ADS)

    Bierkens, M. F.; de Graaf, I.; Wada, Y.; Wanders, N.; Van Beek, L. P.

    2017-12-01

    During the late 1980s and early 1990s, awareness of the shortage of global water resources lead to the first detailed global water resources assessments using regional statistics of water use and observations of meteorological and hydrological variables. Shortly thereafter, the first macroscale hydrological models (MHM) appeared. In these models, blue water (i.e., surface water and renewable groundwater) availability was calculated by accumulating runoff over a stream network and comparing it with population densities or with estimated water demand for agriculture, industry and households. In this talk we review the evolution of human impact modelling in global land models with a focus on global water resources, touching upon developments of the last 15 years: i.e. calculating human water scarcity; estimating groundwater depletion; adding dams and reservoirs; fully integrating water use (demand, withdrawal, consumption, return flow) in the hydrology; simulating the effects of land use change. We show example studies for each of these steps. We identify We identify major challenges that hamper the further development of integrated water resources modelling. Examples of these are: 1) simulating reservoir operations; 2) including local infrastructure and redistribution; 3) using the correct allocations rules; 4) projecting future water demand and water use. For each of these challenges we signify promising directions for further research.

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

    NASA Astrophysics Data System (ADS)

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

    2018-02-01

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

  16. Adaptable Web Modules to Stimulate Active Learning in Engineering Hydrology using Data and Model Simulations of Three Regional Hydrologic Systems

    NASA Astrophysics Data System (ADS)

    Habib, E. H.; Tarboton, D. G.; Lall, U.; Bodin, M.; Rahill-Marier, B.; Chimmula, S.; Meselhe, E. A.; Ali, A.; Williams, D.; Ma, Y.

    2013-12-01

    The hydrologic community has long recognized the need for broad reform in hydrologic education. A paradigm shift is critically sought in undergraduate hydrology and water resource education by adopting context-rich, student-centered, and active learning strategies. Hydrologists currently deal with intricate issues rooted in complex natural ecosystems containing a multitude of interconnected processes. Advances in the multi-disciplinary field include observational settings such as Critical Zone and Water, Sustainability and Climate Observatories, Hydrologic Information Systems, instrumentation and modeling methods. These research advances theory and practices call for similar efforts and improvements in hydrologic education. The typical, text-book based approach in hydrologic education has focused on specific applications and/or unit processes associated with the hydrologic cycle with idealizations, rather than the contextual relations in the physical processes and the spatial and temporal dynamics connecting climate and ecosystems. An appreciation of the natural variability of these processes will lead to graduates with the ability to develop independent learning skills and understanding. This appreciation cannot be gained in curricula where field components such as observational and experimental data are deficient. These types of data are also critical when using simulation models to create environments that support this type of learning. Additional sources of observations in conjunction with models and field data are key to students understanding of the challenges associated with using models to represent such complex systems. Recent advances in scientific visualization and web-based technologies provide new opportunities for the development of active learning techniques utilizing ongoing research. The overall goal of the current study is to develop visual, case-based, data and simulation driven learning experiences to instructors and students through a web

  17. Nonlinear Prediction Model for Hydrologic Time Series Based on Wavelet Decomposition

    NASA Astrophysics Data System (ADS)

    Kwon, H.; Khalil, A.; Brown, C.; Lall, U.; Ahn, H.; Moon, Y.

    2005-12-01

    Traditionally forecasting and characterizations of hydrologic systems is performed utilizing many techniques. Stochastic linear methods such as AR and ARIMA and nonlinear ones such as statistical learning theory based tools have been extensively used. The common difficulty to all methods is the determination of sufficient and necessary information and predictors for a successful prediction. Relationships between hydrologic variables are often highly nonlinear and interrelated across the temporal scale. A new hybrid approach is proposed for the simulation of hydrologic time series combining both the wavelet transform and the nonlinear model. The present model employs some merits of wavelet transform and nonlinear time series model. The Wavelet Transform is adopted to decompose a hydrologic nonlinear process into a set of mono-component signals, which are simulated by nonlinear model. The hybrid methodology is formulated in a manner to improve the accuracy of a long term forecasting. The proposed hybrid model yields much better results in terms of capturing and reproducing the time-frequency properties of the system at hand. Prediction results are promising when compared to traditional univariate time series models. An application of the plausibility of the proposed methodology is provided and the results conclude that wavelet based time series model can be utilized for simulating and forecasting of hydrologic variable reasonably well. This will ultimately serve the purpose of integrated water resources planning and management.

  18. Improved hydrological-model design by integrating nutrient and water flow

    NASA Astrophysics Data System (ADS)

    Arheimer, B.; Lindstrom, G.

    2013-12-01

    The potential of integrating hydrologic and nutrient concentration data to better understand patterns of catchment response and to better design hydrological modeling was explored using a national multi-basin model system for Sweden, called ';S-HYPE'. The model system covers more than 450 000 km2 and produce daily values of nutrient concentration and water discharge in 37 000 catchments from 1961 and onwards. It is based on the processed-based and semi-distributed HYdrological Predictions for the Environment (HYPE) code. The model is used operationally for assessments of water status or climate change impacts and for forecasts by the national warning service of floods, droughts and fire. The first model was launched in 2008, but S-HYPE is continuously improved and released in new versions every second year. Observations are available in 400 sites for daily water discharge and some 900 sites for monthly grab samples of nutrient concentrations. The latest version (2012) has an average NSE for water discharge of 0.7 and an average relative error of 5%, including both regulated and unregulated rivers with catchments from ten to several thousands of km2 and various landuse. The daily relative errors of nutrient concentrations are on average 20% for total Nitrogen and 35% for total Phosphorus. This presentation will give practical examples of how the nutrient data has been used to trace errors or inadequate parameter values in the hydrological model. Since 2008 several parts of the model structure has been reconsidered both in the source code, parameter values and input data of catchment characteristics. In this process water quality has been guiding much of the overall model design of catchment hydrological functions and routing along the river network. The model structure has thus been developed iteratively when evaluating results and checking time-series. Examples of water quality driven improvements will be given for estimation of vertical flow paths, such as

  19. Treatments of Precipitation Inputs to Hydrologic Models

    USDA-ARS?s Scientific Manuscript database

    Hydrological models are used to assess many water resources problems from agricultural use and water quality to engineering issues. The success of these models are dependent on correct parameterization; the most sensitive being the rainfall input time series. These records can come from land-based ...

  20. Uncertainty analysis of hydrological modeling in a tropical area using different algorithms

    NASA Astrophysics Data System (ADS)

    Rafiei Emam, Ammar; Kappas, Martin; Fassnacht, Steven; Linh, Nguyen Hoang Khanh

    2018-01-01

    Hydrological modeling outputs are subject to uncertainty resulting from different sources of errors (e.g., error in input data, model structure, and model parameters), making quantification of uncertainty in hydrological modeling imperative and meant to improve reliability of modeling results. The uncertainty analysis must solve difficulties in calibration of hydrological models, which further increase in areas with data scarcity. The purpose of this study is to apply four uncertainty analysis algorithms to a semi-distributed hydrological model, quantifying different source of uncertainties (especially parameter uncertainty) and evaluate their performance. In this study, the Soil and Water Assessment Tools (SWAT) eco-hydrological model was implemented for the watershed in the center of Vietnam. The sensitivity of parameters was analyzed, and the model was calibrated. The uncertainty analysis for the hydrological model was conducted based on four algorithms: Generalized Likelihood Uncertainty Estimation (GLUE), Sequential Uncertainty Fitting (SUFI), Parameter Solution method (ParaSol) and Particle Swarm Optimization (PSO). The performance of the algorithms was compared using P-factor and Rfactor, coefficient of determination (R 2), the Nash Sutcliffe coefficient of efficiency (NSE) and Percent Bias (PBIAS). The results showed the high performance of SUFI and PSO with P-factor>0.83, R-factor <0.56 and R 2>0.91, NSE>0.89, and 0.18model use for policy or management decisions.

  1. Estimating parameter values of a socio-hydrological flood model

    NASA Astrophysics Data System (ADS)

    Holkje Barendrecht, Marlies; Viglione, Alberto; Kreibich, Heidi; Vorogushyn, Sergiy; Merz, Bruno; Blöschl, Günter

    2018-06-01

    Socio-hydrological modelling studies that have been published so far show that dynamic coupled human-flood models are a promising tool to represent the phenomena and the feedbacks in human-flood systems. So far these models are mostly generic and have not been developed and calibrated to represent specific case studies. We believe that applying and calibrating these type of models to real world case studies can help us to further develop our understanding about the phenomena that occur in these systems. In this paper we propose a method to estimate the parameter values of a socio-hydrological model and we test it by applying it to an artificial case study. We postulate a model that describes the feedbacks between floods, awareness and preparedness. After simulating hypothetical time series with a given combination of parameters, we sample few data points for our variables and try to estimate the parameters given these data points using Bayesian Inference. The results show that, if we are able to collect data for our case study, we would, in theory, be able to estimate the parameter values for our socio-hydrological flood model.

  2. Production of single cell protein from agro-waste using Rhodococcus opacus.

    PubMed

    Mahan, Kristina M; Le, Rosemary K; Wells, Tyrone; Anderson, Seth; Yuan, Joshua S; Stoklosa, Ryan J; Bhalla, Aditya; Hodge, David B; Ragauskas, Arthur J

    2018-06-18

    Livestock and fish farming are rapidly growing industries facing the simultaneous pressure of increasing production demands and limited protein required to produce feed. Bacteria that can convert low-value non-food waste streams into singe cell protein (SCP) present an intriguing route for rapid protein production. The oleaginous bacterium Rhodococcus opacus serves as a model organism for understanding microbial lipid production. SCP production has not been explored using an organism from this genus. In the present research, R. opacus strains DSM 1069 and PD630 were fed three agro-waste streams: (1) orange pulp, juice, and peel; (2) lemon pulp, juice, and peel; and (3) corn stover effluent, to determine if these low-cost substrates would be suitable for producing a value-added product, SCP for aquafarming or livestock feed. Both strains used agro-waste carbon sources as a growth substrate to produce protein-rich cell biomass suggesting that that R. opacus can be used to produce SCP using agro-wastes as low-cost substrates.

  3. Data Services in Support of High Performance Computing-Based Distributed Hydrologic Models

    NASA Astrophysics Data System (ADS)

    Tarboton, D. G.; Horsburgh, J. S.; Dash, P. K.; Gichamo, T.; Yildirim, A. A.; Jones, N.

    2014-12-01

    We have developed web-based data services to support the application of hydrologic models on High Performance Computing (HPC) systems. The purposes of these services are to provide hydrologic researchers, modelers, water managers, and users access to HPC resources without requiring them to become HPC experts and understanding the intrinsic complexities of the data services, so as to reduce the amount of time and effort spent in finding and organizing the data required to execute hydrologic models and data preprocessing tools on HPC systems. These services address some of the data challenges faced by hydrologic models that strive to take advantage of HPC. Needed data is often not in the form needed by such models, requiring researchers to spend time and effort on data preparation and preprocessing that inhibits or limits the application of these models. Another limitation is the difficult to use batch job control and queuing systems used by HPC systems. We have developed a REST-based gateway application programming interface (API) for authenticated access to HPC systems that abstracts away many of the details that are barriers to HPC use and enhances accessibility from desktop programming and scripting languages such as Python and R. We have used this gateway API to establish software services that support the delineation of watersheds to define a modeling domain, then extract terrain and land use information to automatically configure the inputs required for hydrologic models. These services support the Terrain Analysis Using Digital Elevation Model (TauDEM) tools for watershed delineation and generation of hydrology-based terrain information such as wetness index and stream networks. These services also support the derivation of inputs for the Utah Energy Balance snowmelt model used to address questions such as how climate, land cover and land use change may affect snowmelt inputs to runoff generation. To enhance access to the time varying climate data used to

  4. Spatial calibration and temporal validation of flow for regional scale hydrologic modeling

    USDA-ARS?s Scientific Manuscript database

    Physically based regional scale hydrologic modeling is gaining importance for planning and management of water resources. Calibration and validation of such regional scale model is necessary before applying it for scenario assessment. However, in most regional scale hydrologic modeling, flow validat...

  5. Modeling Feedbacks Between Individual Human Decisions and Hydrology Using Interconnected Physical and Social Models

    NASA Astrophysics Data System (ADS)

    Murphy, J.; Lammers, R. B.; Proussevitch, A. A.; Ozik, J.; Altaweel, M.; Collier, N. T.; Alessa, L.; Kliskey, A. D.

    2014-12-01

    The global hydrological cycle intersects with human decision making at multiple scales, from dams and irrigation works to the taps in individuals' homes. Residential water consumers are commonly encouraged to conserve; these messages are heard against a background of individual values and conceptions about water quality, uses, and availability. The degree to which these values impact the larger-hydrological dynamics, the way that changes in those values have impacts on the hydrological cycle through time, and the feedbacks by which water availability and quality in turn shape those values, are not well explored. To investigate this domain we employ a global-scale water balance model (WBM) coupled with a social-science-grounded agent-based model (ABM). The integration of a hydrological model with an agent-based model allows us to explore driving factors in the dynamics in coupled human-natural systems. From the perspective of the physical hydrologist, the ABM offers a richer means of incorporating the human decisions that drive the hydrological system; from the view of the social scientist, a physically-based hydrological model allows the decisions of the agents to play out against constraints faithful to the real world. We apply the interconnected models to a study of Tucson, Arizona, USA, and its role in the larger Colorado River system. Our core concept is Technology-Induced Environmental Distancing (TIED), which posits that layers of technology can insulate consumers from direct knowledge of a resource. In Tucson, multiple infrastructure and institutional layers have arguably increased the conceptual distance between individuals and their water supply, offering a test case of the TIED framework. Our coupled simulation allows us to show how the larger system transforms a resource with high temporal and spatial variability into a consumer constant, and the effects of this transformation on the regional system. We use this to explore how pricing, messaging, and

  6. Upscaling from research watersheds: an essential stage of trustworthy general-purpose hydrologic model building

    NASA Astrophysics Data System (ADS)

    McNamara, J. P.; Semenova, O.; Restrepo, P. J.

    2011-12-01

    Highly instrumented research watersheds provide excellent opportunities for investigating hydrologic processes. A danger, however, is that the processes observed at a particular research watershed are too specific to the watershed and not representative even of the larger scale watershed that contains that particular research watershed. Thus, models developed based on those partial observations may not be suitable for general hydrologic use. Therefore demonstrating the upscaling of hydrologic process from research watersheds to larger watersheds is essential to validate concepts and test model structure. The Hydrograph model has been developed as a general-purpose process-based hydrologic distributed system. In its applications and further development we evaluate the scaling of model concepts and parameters in a wide range of hydrologic landscapes. All models, either lumped or distributed, are based on a discretization concept. It is common practice that watersheds are discretized into so called hydrologic units or hydrologic landscapes possessing assumed homogeneous hydrologic functioning. If a model structure is fixed, the difference in hydrologic functioning (difference in hydrologic landscapes) should be reflected by a specific set of model parameters. Research watersheds provide the possibility for reasonable detailed combining of processes into some typical hydrologic concept such as hydrologic units, hydrologic forms, and runoff formation complexes in the Hydrograph model. And here by upscaling we imply not the upscaling of a single process but upscaling of such unified hydrologic functioning. The simulation of runoff processes for the Dry Creek research watershed, Idaho, USA (27 km2) was undertaken using the Hydrograph model. The information on the watershed was provided by Boise State University and included a GIS database of watershed characteristics and a detailed hydrometeorological observational dataset. The model provided good simulation results in

  7. Impacts of correcting the inter-variable correlation of climate model outputs on hydrological modeling

    NASA Astrophysics Data System (ADS)

    Chen, Jie; Li, Chao; Brissette, François P.; Chen, Hua; Wang, Mingna; Essou, Gilles R. C.

    2018-05-01

    Bias correction is usually implemented prior to using climate model outputs for impact studies. However, bias correction methods that are commonly used treat climate variables independently and often ignore inter-variable dependencies. The effects of ignoring such dependencies on impact studies need to be investigated. This study aims to assess the impacts of correcting the inter-variable correlation of climate model outputs on hydrological modeling. To this end, a joint bias correction (JBC) method which corrects the joint distribution of two variables as a whole is compared with an independent bias correction (IBC) method; this is considered in terms of correcting simulations of precipitation and temperature from 26 climate models for hydrological modeling over 12 watersheds located in various climate regimes. The results show that the simulated precipitation and temperature are considerably biased not only in the individual distributions, but also in their correlations, which in turn result in biased hydrological simulations. In addition to reducing the biases of the individual characteristics of precipitation and temperature, the JBC method can also reduce the bias in precipitation-temperature (P-T) correlations. In terms of hydrological modeling, the JBC method performs significantly better than the IBC method for 11 out of the 12 watersheds over the calibration period. For the validation period, the advantages of the JBC method are greatly reduced as the performance becomes dependent on the watershed, GCM and hydrological metric considered. For arid/tropical and snowfall-rainfall-mixed watersheds, JBC performs better than IBC. For snowfall- or rainfall-dominated watersheds, however, the two methods behave similarly, with IBC performing somewhat better than JBC. Overall, the results emphasize the advantages of correcting the P-T correlation when using climate model-simulated precipitation and temperature to assess the impact of climate change on watershed

  8. Comparison of global optimization approaches for robust calibration of hydrologic model parameters

    NASA Astrophysics Data System (ADS)

    Jung, I. W.

    2015-12-01

    Robustness of the calibrated parameters of hydrologic models is necessary to provide a reliable prediction of future performance of watershed behavior under varying climate conditions. This study investigated calibration performances according to the length of calibration period, objective functions, hydrologic model structures and optimization methods. To do this, the combination of three global optimization methods (i.e. SCE-UA, Micro-GA, and DREAM) and four hydrologic models (i.e. SAC-SMA, GR4J, HBV, and PRMS) was tested with different calibration periods and objective functions. Our results showed that three global optimization methods provided close calibration performances under different calibration periods, objective functions, and hydrologic models. However, using the agreement of index, normalized root mean square error, Nash-Sutcliffe efficiency as the objective function showed better performance than using correlation coefficient and percent bias. Calibration performances according to different calibration periods from one year to seven years were hard to generalize because four hydrologic models have different levels of complexity and different years have different information content of hydrological observation. Acknowledgements This research was supported by a grant (14AWMP-B082564-01) from Advanced Water Management Research Program funded by Ministry of Land, Infrastructure and Transport of Korean government.

  9. Modeling winter hydrological processes under differing climatic conditions: Modifying WEPP

    NASA Astrophysics Data System (ADS)

    Dun, Shuhui

    Water erosion is a serious and continuous environmental problem worldwide. In cold regions, soil freeze and thaw has great impacts on infiltration and erosion. Rain or snowmelt on a thawing soil can cause severe water erosion. Of equal importance is snow accumulation and snowmelt, which can be the predominant hydrological process in areas of mid- to high latitudes and forested watersheds. Modelers must properly simulate winter processes to adequately represent the overall hydrological outcome and sediment and chemical transport in these areas. Modeling winter hydrology is presently lacking in water erosion models. Most of these models are based on the functional Universal Soil Loss Equation (USLE) or its revised forms, e.g., Revised USLE (RUSLE). In RUSLE a seasonally variable soil erodibility factor (K) was used to account for the effects of frozen and thawing soil. Yet the use of this factor requires observation data for calibration, and such a simplified approach cannot represent the complicated transient freeze-thaw processes and their impacts on surface runoff and erosion. The Water Erosion Prediction Project (WEPP) watershed model, a physically-based erosion prediction software developed by the USDA-ARS, has seen numerous applications within and outside the US. WEPP simulates winter processes, including snow accumulation, snowmelt, and soil freeze-thaw, using an approach based on mass and energy conservation. However, previous studies showed the inadequacy of the winter routines in the WEPP model. Therefore, the objectives of this study were: (1) To adapt a modeling approach for winter hydrology based on mass and energy conservation, and to implement this approach into a physically-oriented hydrological model, such as WEPP; and (2) To assess this modeling approach through case applications to different geographic conditions. A new winter routine was developed and its performance was evaluated by incorporating it into WEPP (v2008.9) and then applying WEPP to

  10. Calibration process of highly parameterized semi-distributed hydrological model

    NASA Astrophysics Data System (ADS)

    Vidmar, Andrej; Brilly, Mitja

    2017-04-01

    Hydrological phenomena take place in the hydrological system, which is governed by nature, and are essentially stochastic. These phenomena are unique, non-recurring, and changeable across space and time. Since any river basin with its own natural characteristics and any hydrological event therein, are unique, this is a complex process that is not researched enough. Calibration is a procedure of determining the parameters of a model that are not known well enough. Input and output variables and mathematical model expressions are known, while only some parameters are unknown, which are determined by calibrating the model. The software used for hydrological modelling nowadays is equipped with sophisticated algorithms for calibration purposes without possibility to manage process by modeler. The results are not the best. We develop procedure for expert driven process of calibration. We use HBV-light-CLI hydrological model which has command line interface and coupling it with PEST. PEST is parameter estimation tool which is used widely in ground water modeling and can be used also on surface waters. Process of calibration managed by expert directly, and proportionally to the expert knowledge, affects the outcome of the inversion procedure and achieves better results than if the procedure had been left to the selected optimization algorithm. First step is to properly define spatial characteristic and structural design of semi-distributed model including all morphological and hydrological phenomena, like karstic area, alluvial area and forest area. This step includes and requires geological, meteorological, hydraulic and hydrological knowledge of modeler. Second step is to set initial parameter values at their preferred values based on expert knowledge. In this step we also define all parameter and observation groups. Peak data are essential in process of calibration if we are mainly interested in flood events. Each Sub Catchment in the model has own observations group

  11. Determining hydrological changes in a small Arctic treeline basin using cold regions hydrological modelling and a pseudo-global warming approach

    NASA Astrophysics Data System (ADS)

    Krogh, S. A.; Pomeroy, J. W.

    2017-12-01

    Increasing temperatures are producing higher rainfall ratios, shorter snow-covered periods, permafrost thaw, more shrub coverage, more northerly treelines and greater interaction between groundwater and surface flow in Arctic basins. How these changes will impact the hydrology of the Arctic treeline environment represents a great challenge. To diagnose the future hydrology along the current Arctic treeline, a physically based cold regions model was used to simulate the hydrology of a small basin near Inuvik, Northwest Territories, Canada. The hydrological model includes hydrological processes such as snow redistribution and sublimation by wind, canopy interception of snow/rain and sublimation/evaporation, snowmelt energy balance, active layer freeze/thaw, infiltration into frozen and unfrozen soils, evapotranspiration, horizontal flow through organic terrain and snowpack, subsurface flow and streamflow routing. The model was driven with weather simulated by a high-resolution (4 km) numerical weather prediction model under two scenarios: (1) control run, using ERA-Interim boundary conditions (2001-2013) and (2) future, using a Pseudo-Global Warming (PGW) approach based on the RCP8.5 projections perturbing the control run. Transient changes in vegetation based on recent observations and ecological expectations were then used to re-parameterise the model. Historical hydrological simulations were validated against daily streamflow, snow water equivalent and active layer thickness records, showing the model's suitability in this environment. Strong annual warming ( 6 °C) and more precipitation ( 20%) were simulated by the PGW scenario, with winter precipitation and fall temperature showing the largest seasonal increase. The joint impact of climate and transient vegetation changes on snow accumulation and redistribution, evapotranspiration, active layer development, runoff generation and hydrograph characteristics are analyzed and discussed.

  12. Hydrologic Model Selection using Markov chain Monte Carlo methods

    NASA Astrophysics Data System (ADS)

    Marshall, L.; Sharma, A.; Nott, D.

    2002-12-01

    Estimation of parameter uncertainty (and in turn model uncertainty) allows assessment of the risk in likely applications of hydrological models. Bayesian statistical inference provides an ideal means of assessing parameter uncertainty whereby prior knowledge about the parameter is combined with information from the available data to produce a probability distribution (the posterior distribution) that describes uncertainty about the parameter and serves as a basis for selecting appropriate values for use in modelling applications. Widespread use of Bayesian techniques in hydrology has been hindered by difficulties in summarizing and exploring the posterior distribution. These difficulties have been largely overcome by recent advances in Markov chain Monte Carlo (MCMC) methods that involve random sampling of the posterior distribution. This study presents an adaptive MCMC sampling algorithm which has characteristics that are well suited to model parameters with a high degree of correlation and interdependence, as is often evident in hydrological models. The MCMC sampling technique is used to compare six alternative configurations of a commonly used conceptual rainfall-runoff model, the Australian Water Balance Model (AWBM), using 11 years of daily rainfall runoff data from the Bass river catchment in Australia. The alternative configurations considered fall into two classes - those that consider model errors to be independent of prior values, and those that model the errors as an autoregressive process. Each such class consists of three formulations that represent increasing levels of complexity (and parameterisation) of the original model structure. The results from this study point both to the importance of using Bayesian approaches in evaluating model performance, as well as the simplicity of the MCMC sampling framework that has the ability to bring such approaches within the reach of the applied hydrological community.

  13. Impact of vegetation dynamics on hydrological processes in a semi-arid basin by using a land surface-hydrology coupled model

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Jiao, Yang; Lei, Huimin; Yang, Dawen

    Land surface models (LSMs) are widely used to understand the interactions between hydrological processes and vegetation dynamics, which is important for the attribution and prediction of regional hydrological variations. However, most LSMs have large uncertainties in their representations of ecohydrological processes due to deficiencies in hydrological parameterizations. In this study, the Community Land Model version 4 (CLM4) LSM was modified with an advanced runoff generation and flow routing scheme, resulting in a new land surface-hydrology coupled model, CLM-GBHM. Both models were implemented in the Wudinghe River Basin (WRB), which is a semi-arid basin located in the middle reaches of themore » Yellow River, China. Compared with CLM, CLM-GBHM increased the Nash Sutcliffe efficiency for daily river discharge simulation (1965–1969) from 0.03 to 0.23 and reduced the relative bias in water table depth simulations (2010–2012) from 32.4% to 13.4%. The CLM-GBHM simulations with static, remotely sensed and model-predicted vegetation conditions showed that the vegetation in the WRB began to recover in the 2000s due to the Grain for Green Program but had not reached the same level of vegetation cover as regions in natural eco-hydrological equilibrium. Compared with a simulation using remotely sensed vegetation cover, the simulation with a dynamic vegetation model that considers only climate-induced change showed a 10.3% increase in evapotranspiration, a 47.8% decrease in runoff, and a 62.7% and 71.3% deceleration in changing trend of the outlet river discharge before and after the year 2000, respectively. This result suggests that both natural and anthropogenic factors should be incorporated in dynamic vegetation models to better simulate the eco-hydrological cycle.« less

  14. Potential for Remotely Sensed Soil Moisture Data in Hydrologic Modeling

    NASA Technical Reports Server (NTRS)

    Engman, Edwin T.

    1997-01-01

    Many hydrologic processes display a unique signature that is detectable with microwave remote sensing. These signatures are in the form of the spatial and temporal distributions of surface soil moisture and portray the spatial heterogeneity of hydrologic processes and properties that one encounters in drainage basins. The hydrologic processes that may be detected include ground water recharge and discharge zones, storm runoff contributing areas, regions of potential and less than potential ET, and information about the hydrologic properties of soils and heterogeneity of hydrologic parameters. Microwave remote sensing has the potential to detect these signatures within a basin in the form of volumetric soil moisture measurements in the top few cm. These signatures should provide information on how and where to apply soil physical parameters in distributed and lumped parameter models and how to subdivide drainage basins into hydrologically similar sub-basins.

  15. Agro-ecoregionalization of Iowa using multivariate geographical clustering

    Treesearch

    Carol L. Williams; William W. Hargrove; Matt Leibman; David E. James

    2008-01-01

    Agro-ecoregionalization is categorization of landscapes for use in crop suitability analysis, strategic agroeconomic development, risk analysis, and other purposes. Past agro-ecoregionalizations have been subjective, expert opinion driven, crop specific, and unsuitable for statistical extrapolation. Use of quantitative analytical methods provides an opportunity for...

  16. The Impact of Microwave-Derived Surface Soil Moisture on Watershed Hydrological Modeling

    NASA Technical Reports Server (NTRS)

    ONeill, P. E.; Hsu, A. Y.; Jackson, T. J.; Wood, E. F.; Zion, M.

    1997-01-01

    The usefulness of incorporating microwave-derived soil moisture information in a semi-distributed hydrological model was demonstrated for the Washita '92 experiment in the Little Washita River watershed in Oklahoma. Initializing the hydrological model with surface soil moisture fields from the ESTAR airborne L-band microwave radiometer on a single wet day at the start of the study period produced more accurate model predictions of soil moisture than a standard hydrological initialization with streamflow data over an eight-day soil moisture drydown.

  17. Multivariate Probabilistic Analysis of an Hydrological Model

    NASA Astrophysics Data System (ADS)

    Franceschini, Samuela; Marani, Marco

    2010-05-01

    Model predictions derived based on rainfall measurements and hydrological model results are often limited by the systematic error of measuring instruments, by the intrinsic variability of the natural processes and by the uncertainty of the mathematical representation. We propose a means to identify such sources of uncertainty and to quantify their effects based on point-estimate approaches, as a valid alternative to cumbersome Montecarlo methods. We present uncertainty analyses on the hydrologic response to selected meteorological events, in the mountain streamflow-generating portion of the Brenta basin at Bassano del Grappa, Italy. The Brenta river catchment has a relatively uniform morphology and quite a heterogeneous rainfall-pattern. In the present work, we evaluate two sources of uncertainty: data uncertainty (the uncertainty due to data handling and analysis) and model uncertainty (the uncertainty related to the formulation of the model). We thus evaluate the effects of the measurement error of tipping-bucket rain gauges, the uncertainty in estimating spatially-distributed rainfall through block kriging, and the uncertainty associated with estimated model parameters. To this end, we coupled a deterministic model based on the geomorphological theory of the hydrologic response to probabilistic methods. In particular we compare the results of Monte Carlo Simulations (MCS) to the results obtained, in the same conditions, using Li's Point Estimate Method (LiM). The LiM is a probabilistic technique that approximates the continuous probability distribution function of the considered stochastic variables by means of discrete points and associated weights. This allows to satisfactorily reproduce results with only few evaluations of the model function. The comparison between the LiM and MCS results highlights the pros and cons of using an approximating method. LiM is less computationally demanding than MCS, but has limited applicability especially when the model

  18. Assessing the site-specific impacts of climate change on hydrology, soil erosion and crop yields in the Loess Plateau of China

    USDA-ARS?s Scientific Manuscript database

    Climate changes can have great impacts on fragile agro-ecosystems in the Loess Plateau of China, which is one of the most severely eroded regions in the world. The objective of this study is to assess the site-specific impacts of projected climate change scenarios for 2010-2039 on hydrology, soil l...

  19. Eco-hydrological Modeling in the Framework of Climate Change

    NASA Astrophysics Data System (ADS)

    Fatichi, Simone; Ivanov, Valeriy Y.; Caporali, Enrica

    2010-05-01

    A blueprint methodology for studying climate change impacts, as inferred from climate models, on eco-hydrological dynamics at the plot and small catchment scale is presented. Input hydro-meteorological variables for hydrological and eco-hydrological models for present and future climates are reproduced using a stochastic downscaling technique and a weather generator, "AWE-GEN". The generated time series of meteorological variables for the present climate and an ensemble of possible future climates serve as input to a newly developed physically-based eco-hydrological model "Tethys-Chloris". An application of the proposed methodology is realized reproducing the current (1961-2000) and multiple future (2081-2100) climates for the location of Tucson (Arizona). A general reduction of precipitation and a significant increase of air temperature are inferred. The eco-hydrological model is successively applied to detect changes in water recharge and vegetation dynamics for a desert shrub ecosystem, typical of the semi-arid climate of south Arizona. Results for the future climate account for uncertainties in the downscaling and are produced in terms of probability density functions. A comparison of control and future scenarios is discussed in terms of changes in the hydrological balance components, energy fluxes, and indices of vegetation productivity. An appreciable effect of climate change can be observed in metrics of vegetation performance. The negative impact on vegetation due to amplification of water stress in a warmer and dryer climate is offset by a positive effect of carbon dioxide augment. This implies a positive shift in plant capabilities to exploit water. Consequently, the plant water use efficiency and rain use efficiency are expected to increase. Interesting differences in the long-term vegetation productivity are also observed for the ensemble of future climates. The reduction of precipitation and the substantial maintenance of vegetation cover ultimately

  20. Simulations of ecosystem hydrological processes using a unified multi-scale model

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Yang, Xiaofan; Liu, Chongxuan; Fang, Yilin

    2015-01-01

    This paper presents a unified multi-scale model (UMSM) that we developed to simulate hydrological processes in an ecosystem containing both surface water and groundwater. The UMSM approach modifies the Navier–Stokes equation by adding a Darcy force term to formulate a single set of equations to describe fluid momentum and uses a generalized equation to describe fluid mass balance. The advantage of the approach is that the single set of the equations can describe hydrological processes in both surface water and groundwater where different models are traditionally required to simulate fluid flow. This feature of the UMSM significantly facilitates modelling ofmore » hydrological processes in ecosystems, especially at locations where soil/sediment may be frequently inundated and drained in response to precipitation, regional hydrological and climate changes. In this paper, the UMSM was benchmarked using WASH123D, a model commonly used for simulating coupled surface water and groundwater flow. Disney Wilderness Preserve (DWP) site at the Kissimmee, Florida, where active field monitoring and measurements are ongoing to understand hydrological and biogeochemical processes, was then used as an example to illustrate the UMSM modelling approach. The simulations results demonstrated that the DWP site is subject to the frequent changes in soil saturation, the geometry and volume of surface water bodies, and groundwater and surface water exchange. All the hydrological phenomena in surface water and groundwater components including inundation and draining, river bank flow, groundwater table change, soil saturation, hydrological interactions between groundwater and surface water, and the migration of surface water and groundwater interfaces can be simultaneously simulated using the UMSM. Overall, the UMSM offers a cross-scale approach that is particularly suitable to simulate coupled surface and ground water flow in ecosystems with strong surface water and groundwater

  1. An approach to measure parameter sensitivity in watershed hydrological modelling

    EPA Science Inventory

    Hydrologic responses vary spatially and temporally according to watershed characteristics. In this study, the hydrologic models that we developed earlier for the Little Miami River (LMR) and Las Vegas Wash (LVW) watersheds were used for detail sensitivity analyses. To compare the...

  2. Advancements in Hydrology and Erosion Process Understanding and Post-Fire Hydrologic and Erosion Model Development for Semi-Arid Landscapes

    NASA Astrophysics Data System (ADS)

    Williams, C. Jason; Pierson, Frederick B.; Al-Hamdan, Osama Z.; Robichaud, Peter R.; Nearing, Mark A.; Hernandez, Mariano; Weltz, Mark A.; Spaeth, Kenneth E.; Goodrich, David C.

    2017-04-01

    Fire activity continues to increase in semi-arid regions around the globe. Private and governmental land management entities are challenged with predicting and mitigating post-fire hydrologic and erosion responses on these landscapes. For more than a decade, a team of scientists with the US Department of Agriculture has collaborated on extensive post-fire hydrologic field research and the application of field research to development of post-fire hydrology and erosion predictive technologies. Experiments funded through this research investigated the impacts of fire on vegetation and soils and the effects of these fire-induced changes on infiltration, runoff generation, erodibility, and soil erosion processes. The distribution of study sites spans diverse topography across grassland, shrubland, and woodland landscapes throughout the western United States. Knowledge gleaned from the extensive field experiments was applied to develop and enhance physically-based models for hillslope- to watershed-scale runoff and erosion prediction. Our field research and subsequent data syntheses have identified key knowledge gaps and challenges regarding post-fire hydrology and erosion modeling. Our presentation details some consistent trends across a diverse domain and varying landscape conditions based on our extensive field campaigns. We demonstrate how field data have advanced our understanding of post-fire hydrology and erosion for semi-arid landscapes and highlight remaining key knowledge gaps. Lastly, we briefly show how our well-replicated experimental methodologies have contributed to advancements in hydrologic and erosion model development for the post-fire environment.

  3. The Central Valley Hydrologic Model

    NASA Astrophysics Data System (ADS)

    Faunt, C.; Belitz, K.; Hanson, R. T.

    2009-12-01

    Historically, California’s Central Valley has been one of the most productive agricultural regions in the world. The Central Valley also is rapidly becoming an important area for California’s expanding urban population. In response to this competition for water, a number of water-related issues have gained prominence: conjunctive use, artificial recharge, hydrologic implications of land-use change, subsidence, and effects of climate variability. To provide information to stakeholders addressing these issues, the USGS made a detailed assessment of the Central Valley aquifer system that includes the present status of water resources and how these resources have changed over time. The principal product of this assessment is a tool, referred to as the Central Valley Hydrologic Model (CVHM), that simulates surface-water flows, groundwater flows, and land subsidence in response to stresses from human uses and from climate variability throughout the entire Central Valley. The CVHM utilizes MODFLOW combined with a new tool called “Farm Process” to simulate groundwater and surface-water flow, irrigated agriculture, land subsidence, and other key processes in the Central Valley on a monthly basis. This model was discretized horizontally into 20,000 1-mi2 cells and vertically into 10 layers ranging in thickness from 50 feet at the land surface to 750 feet at depth. A texture model constructed by using data from more than 8,500 drillers’ logs was used to estimate hydraulic properties. Unmetered pumpage and surface-water deliveries for 21 water-balance regions were simulated with the Farm Process. Model results indicate that human activities, predominately surface-water deliveries and groundwater pumping for irrigated agriculture, have dramatically influenced the hydrology of the Central Valley. These human activities have increased flow though the aquifer system by about a factor of six compared to pre-development conditions. The simulated hydrology reflects spatial

  4. Distributed Hydrologic Modeling Apps for Decision Support in the Cloud

    NASA Astrophysics Data System (ADS)

    Swain, N. R.; Latu, K.; Christiensen, S.; Jones, N.; Nelson, J.

    2013-12-01

    Advances in computation resources and greater availability of water resources data represent an untapped resource for addressing hydrologic uncertainties in water resources decision-making. The current practice of water authorities relies on empirical, lumped hydrologic models to estimate watershed response. These models are not capable of taking advantage of many of the spatial datasets that are now available. Physically-based, distributed hydrologic models are capable of using these data resources and providing better predictions through stochastic analysis. However, there exists a digital divide that discourages many science-minded decision makers from using distributed models. This divide can be spanned using a combination of existing web technologies. The purpose of this presentation is to present a cloud-based environment that will offer hydrologic modeling tools or 'apps' for decision support and the web technologies that have been selected to aid in its implementation. Compared to the more commonly used lumped-parameter models, distributed models, while being more intuitive, are still data intensive, computationally expensive, and difficult to modify for scenario exploration. However, web technologies such as web GIS, web services, and cloud computing have made the data more accessible, provided an inexpensive means of high-performance computing, and created an environment for developing user-friendly apps for distributed modeling. Since many water authorities are primarily interested in the scenario exploration exercises with hydrologic models, we are creating a toolkit that facilitates the development of a series of apps for manipulating existing distributed models. There are a number of hurdles that cloud-based hydrologic modeling developers face. One of these is how to work with the geospatial data inherent with this class of models in a web environment. Supporting geospatial data in a website is beyond the capabilities of standard web frameworks and it

  5. Diagnosis of the hydrology of a small Arctic basin at the tundra-taiga transition using a physically based hydrological model

    NASA Astrophysics Data System (ADS)

    Krogh, Sebastian A.; Pomeroy, John W.; Marsh, Philip

    2017-07-01

    A better understanding of cold regions hydrological processes and regimes in transitional environments is critical for predicting future Arctic freshwater fluxes under climate and vegetation change. A physically based hydrological model using the Cold Regions Hydrological Model platform was created for a small Arctic basin in the tundra-taiga transition region. The model represents snow redistribution and sublimation by wind and vegetation, snowmelt energy budget, evapotranspiration, subsurface flow through organic terrain, infiltration to frozen soils, freezing and thawing of soils, permafrost and streamflow routing. The model was used to reconstruct the basin water cycle over 28 years to understand and quantify the mass fluxes controlling its hydrological regime. Model structure and parameters were set from the current understanding of Arctic hydrology, remote sensing, field research in the basin and region, and calibration against streamflow observations. Calibration was restricted to subsurface hydraulic and storage parameters. Multi-objective evaluation of the model using observed streamflow, snow accumulation and ground freeze/thaw state showed adequate simulation. Significant spatial variability in the winter mass fluxes was found between tundra, shrubs and forested sites, particularly due to the substantial blowing snow redistribution and sublimation from the wind-swept upper basin, as well as sublimation of canopy intercepted snow from the forest (about 17% of snowfall). At the basin scale, the model showed that evapotranspiration is the largest loss of water (47%), followed by streamflow (39%) and sublimation (14%). The models streamflow performance sensitivity to a set of parameter was analysed, as well as the mean annual mass balance uncertainty associated with these parameters.

  6. Calibration by Hydrological Response Unit of a National Hydrologic Model to Improve Spatial Representation and Distribution of Parameters

    NASA Astrophysics Data System (ADS)

    Norton, P. A., II

    2015-12-01

    The U. S. Geological Survey is developing a National Hydrologic Model (NHM) to support consistent hydrologic modeling across the conterminous United States (CONUS). The Precipitation-Runoff Modeling System (PRMS) simulates daily hydrologic and energy processes in watersheds, and is used for the NHM application. For PRMS each watershed is divided into hydrologic response units (HRUs); by default each HRU is assumed to have a uniform hydrologic response. The Geospatial Fabric (GF) is a database containing initial parameter values for input to PRMS and was created for the NHM. The parameter values in the GF were derived from datasets that characterize the physical features of the entire CONUS. The NHM application is composed of more than 100,000 HRUs from the GF. Selected parameter values commonly are adjusted by basin in PRMS using an automated calibration process based on calibration targets, such as streamflow. Providing each HRU with distinct values that captures variability within the CONUS may improve simulation performance of the NHM. During calibration of the NHM by HRU, selected parameter values are adjusted for PRMS based on calibration targets, such as streamflow, snow water equivalent (SWE) and actual evapotranspiration (AET). Simulated SWE, AET, and runoff were compared to value ranges derived from multiple sources (e.g. the Snow Data Assimilation System, the Moderate Resolution Imaging Spectroradiometer (i.e. MODIS) Global Evapotranspiration Project, the Simplified Surface Energy Balance model, and the Monthly Water Balance Model). This provides each HRU with a distinct set of parameter values that captures the variability within the CONUS, leading to improved model performance. We present simulation results from the NHM after preliminary calibration, including the results of basin-level calibration for the NHM using: 1) default initial GF parameter values, and 2) parameter values calibrated by HRU.

  7. Parameterization guidelines and considerations for hydrologic models

    USDA-ARS?s Scientific Manuscript database

    Imparting knowledge of the physical processes of a system to a model and determining a set of parameter values for a hydrologic or water quality model application (i.e., parameterization) is an important and difficult task. An exponential increase in literature has been devoted to the use and develo...

  8. Hydrology of malaria: Model development and application to a Sahelian village

    NASA Astrophysics Data System (ADS)

    Bomblies, Arne; Duchemin, Jean-Bernard; Eltahir, Elfatih A. B.

    2008-12-01

    We present a coupled hydrology and entomology model for the mechanistic simulation of local-scale response of malaria transmission to hydrological and climatological determinants in semiarid, desert fringe environments. The model is applied to the Sahel village of Banizoumbou, Niger, to predict interannual variability in malaria vector mosquito populations that lead to variations in malaria transmission. Using a high-resolution, small-scale distributed hydrology model that incorporates remotely sensed data for land cover and topography, we simulate the formation and persistence of the pools constituting the primary breeding habitat of Anopheles gambiae s.l. mosquitoes, the principal regional malaria vector mosquitoes. An agent-based mosquito population model is coupled to the distributed hydrology model, with aquatic-stage and adult-stage components. Through a dependence of aquatic-stage mosquito development and adult emergence on pool persistence, we model small-scale hydrology as a dominant control of mosquito abundance. For each individual adult mosquito, the model tracks attributes relevant to population dynamics and malaria transmission, which are updated as mosquitoes interact with their environment, humans, and animals. Weekly field observations were made in 2005 and 2006. A 16% increase in rainfall between the two years was accompanied by a 132% increase in mosquito abundance between 2005 and 2006. The model reproduces mosquito population variability at seasonal and interannual timescales and highlights individual pool persistence as a dominant control. Future developments of the presented model can be used in the evaluation of impacts of climate change on malaria, as well as the a priori evaluation of environmental management-based interventions.

  9. Assessing climate change impact by integrated hydrological modelling

    NASA Astrophysics Data System (ADS)

    Lajer Hojberg, Anker; Jørgen Henriksen, Hans; Olsen, Martin; der Keur Peter, van; Seaby, Lauren Paige; Troldborg, Lars; Sonnenborg, Torben; Refsgaard, Jens Christian

    2013-04-01

    Future climate may have a profound effect on the freshwater cycle, which must be taken into consideration by water management for future planning. Developments in the future climate are nevertheless uncertain, thus adding to the challenge of managing an uncertain system. To support the water managers at various levels in Denmark, the national water resources model (DK-model) (Højberg et al., 2012; Stisen et al., 2012) was used to propagate future climate to hydrological response under considerations of the main sources of uncertainty. The DK-model is a physically based and fully distributed model constructed on the basis of the MIKE SHE/MIKE11 model system describing groundwater and surface water systems and the interaction between the domains. The model has been constructed for the entire 43.000 km2 land area of Denmark only excluding minor islands. Future climate from General Circulation Models (GCM) was downscaled by Regional Climate Models (RCM) by a distribution-based scaling method (Seaby et al., 2012). The same dataset was used to train all combinations of GCM-RCMs and they were found to represent the mean and variance at the seasonal basis equally well. Changes in hydrological response were computed by comparing the short term development from the period 1990 - 2010 to 2021 - 2050, which is the time span relevant for water management. To account for uncertainty in future climate predictions, hydrological response from the DK-model using nine combinations of GCMs and RCMs was analysed for two catchments representing the various hydrogeological conditions in Denmark. Three GCM-RCM combinations displaying high, mean and low future impacts were selected as representative climate models for which climate impact studies were carried out for the entire country. Parameter uncertainty was addressed by sensitivity analysis and was generally found to be of less importance compared to the uncertainty spanned by the GCM-RCM combinations. Analysis of the simulations

  10. On the importance of methods in hydrological modelling. Perspectives from a case study

    NASA Astrophysics Data System (ADS)

    Fenicia, Fabrizio; Kavetski, Dmitri

    2017-04-01

    The hydrological community generally appreciates that developing any non-trivial hydrological model requires a multitude of modelling choices. These choices may range from a (seemingly) straightforward application of mass conservation, to the (often) guesswork-like selection of constitutive functions, parameter values, etc. The application of a model itself requires a myriad of methodological choices - the selection of numerical solvers, objective functions for model calibration, validation approaches, performance metrics, etc. Not unreasonably, hydrologists embarking on ever ambitious projects prioritize hydrological insight over the morass of methodological choices. Perhaps to emphasize "ideas" over "methods", some journals have even reduced the fontsize of the methodology sections of its articles. However, the very nature of modelling is that seemingly routine methodological choices can significantly affect the conclusions of case studies and investigations - making it dangerous to skimp over methodological details in an enthusiastic rush towards the next great hydrological idea. This talk shares modelling insights from a hydrological study of a 300 km2 catchment in Luxembourg, where the diversity of hydrograph dynamics observed at 10 locations begs the question of whether external forcings or internal catchment properties act as dominant controls on streamflow generation. The hydrological insights are fascinating (at least to us), but in this talk we emphasize the impact of modelling methodology on case study conclusions and recommendations. How did we construct our prior set of hydrological model hypotheses? What numerical solver was implemented and why was an objective function based on Bayesian theory deployed? And what would have happened had we omitted model cross-validation, or not used a systematic hypothesis testing approach?

  11. Integrating flood modelling in a hydrological catchment model: flow approximations and spatial resolution.

    NASA Astrophysics Data System (ADS)

    van den Bout, Bastian; Jetten, Victor

    2017-04-01

    Within hydrological models, flow approximations are commonly used to reduce computation time. The validity of these approximations is strongly determined by flow height, flow velocity, the spatial resolution of the model, and by the manner in which flow routing is implemented. The assumptions of these approximations can furthermore limit emergent behavior, and influence flow behavior under space-time scaling. In this presentation, the validity and performance of the kinematic, diffusive and dynamic flow approximations are investigated for use in a catchment-based flood model. Particularly, the validity during flood events and for varying spatial resolutions is investigated. The OpenLISEM hydrological model is extended to implement these flow approximations and channel flooding based on dynamic flow. The kinematic routing uses a predefined converging flow network, the diffusive and dynamic routing uses a 2D flow solution over a DEM. The channel flow in all cases is a 1D kinematic wave approximation. The flow approximations are used to recreate measured discharge in three catchments of different size in China, Spain and Italy, among which is the hydrograph of the 2003 flood event in the Fella river basin (Italy). Furthermore, spatial resolutions are varied for the flood simulation in order to investigate the influence of spatial resolution on these flow approximations. Results show that the kinematic, diffusive and dynamic flow approximation provide least to highest accuracy, respectively, in recreating measured temporal variation of the discharge. Kinematic flow, which is commonly used in hydrological modelling, substantially over-estimates hydrological connectivity in the simulations with a spatial resolution of below 30 meters. Since spatial resolutions of models have strongly increased over the past decades, usage of routed kinematic flow should be reconsidered. In the case of flood events, spatial modelling of kinematic flow substantially over

  12. On the hydrologic adjustment of climate-model projections: The potential pitfall of potential evapotranspiration

    USGS Publications Warehouse

    Milly, P.C.D.; Dunne, K.A.

    2011-01-01

    Hydrologic models often are applied to adjust projections of hydroclimatic change that come from climate models. Such adjustment includes climate-bias correction, spatial refinement ("downscaling"), and consideration of the roles of hydrologic processes that were neglected in the climate model. Described herein is a quantitative analysis of the effects of hydrologic adjustment on the projections of runoff change associated with projected twenty-first-century climate change. In a case study including three climate models and 10 river basins in the contiguous United States, the authors find that relative (i.e., fractional or percentage) runoff change computed with hydrologic adjustment more often than not was less positive (or, equivalently, more negative) than what was projected by the climate models. The dominant contributor to this decrease in runoff was a ubiquitous change in runoff (median 211%) caused by the hydrologic model's apparent amplification of the climate-model-implied growth in potential evapotranspiration. Analysis suggests that the hydrologic model, on the basis of the empirical, temperature-based modified Jensen-Haise formula, calculates a change in potential evapotranspiration that is typically 3 times the change implied by the climate models, which explicitly track surface energy budgets. In comparison with the amplification of potential evapotranspiration, central tendencies of other contributions from hydrologic adjustment (spatial refinement, climate-bias adjustment, and process refinement) were relatively small. The authors' findings highlight the need for caution when projecting changes in potential evapotranspiration for use in hydrologic models or drought indices to evaluate climatechange impacts on water. Copyright ?? 2011, Paper 15-001; 35,952 words, 3 Figures, 0 Animations, 1 Tables.

  13. Hydrological Modelling using HEC-HMS for Flood Risk Assessment of Segamat Town, Malaysia

    NASA Astrophysics Data System (ADS)

    Romali, N. S.; Yusop, Z.; Ismail, A. Z.

    2018-03-01

    This paper presents an assessment of the applicability of using Hydrologic Modelling System developed by the Hydrologic Engineering Center (HEC-HMS) for hydrological modelling of Segamat River. The objective of the model application is to assist in the assessment of flood risk by providing the peak flows of 2011 Segamat flood for the generation of flood mapping of Segamat town. The capability of the model was evaluated by comparing the historical observed data with the simulation results of the selected flood events. The model calibration and validation efficiency was verified using Nash-Sutcliffe model efficiency coefficient. The results demonstrate the interest to implement the hydrological model for assessing flood risk where the simulated peak flow result is in agreement with historical observed data. The model efficiency of the calibrated and validated exercises is 0.90 and 0.76 respectively, which is acceptable.

  14. Risk Assessment of Maize Drought Disaster in Agro-Pastoral Transitional Zone in North China

    NASA Astrophysics Data System (ADS)

    Jia, H.; Pan, D.

    2017-12-01

    Agricultural drought is one of the focuses of global concern and one of the natural disasters that affect the agriculture production mostly in China. Farming-pastoral zones in China are located in the monsoon fringe area, precipitation of which is extremely unstable, and drought occurs frequently. The agro-pastoral transitional zone in North China is one of the main producing areas of northern spring maize in northern China, and maize is the second largest grain crop in the region. An assessment of the risk of drought disaster in this region is therefore important in ensuring a reduction in such disasters and an increase in food security. A risk assessment model, EPIC (Environmental Policy Integrated Climate) model, for maize drought disasters based on the Erosion Productivity Impact Calculator crop model is proposed for areas with the topographic characteristics of agro-pastoral transitional zone in North China. The results showed that the hazard risk level for the maize zone of agro-pastoral transitional zone in North China is generally high. Most hazard index values were between 0.4 and 0.5, accounting for 48.77% of total study area. The high-risk areas were mainly distributed in Ordos Plateau (South of Inner Mongolia Autonomous region), South of Ningxia Hui Autonomous Region and Center of Gansu Province. These results provide a scientific basis and support for the reduction of agricultural drought disasters and an increase in food security in the agro-pastoral transitional zone in North China.

  15. Implications of the methodological choices for hydrologic portrayals of climate change over the contiguous United States: Statistically downscaled forcing data and hydrologic models

    USGS Publications Warehouse

    Mizukami, Naoki; Clark, Martyn P.; Gutmann, Ethan D.; Mendoza, Pablo A.; Newman, Andrew J.; Nijssen, Bart; Livneh, Ben; Hay, Lauren E.; Arnold, Jeffrey R.; Brekke, Levi D.

    2016-01-01

    Continental-domain assessments of climate change impacts on water resources typically rely on statistically downscaled climate model outputs to force hydrologic models at a finer spatial resolution. This study examines the effects of four statistical downscaling methods [bias-corrected constructed analog (BCCA), bias-corrected spatial disaggregation applied at daily (BCSDd) and monthly scales (BCSDm), and asynchronous regression (AR)] on retrospective hydrologic simulations using three hydrologic models with their default parameters (the Community Land Model, version 4.0; the Variable Infiltration Capacity model, version 4.1.2; and the Precipitation–Runoff Modeling System, version 3.0.4) over the contiguous United States (CONUS). Biases of hydrologic simulations forced by statistically downscaled climate data relative to the simulation with observation-based gridded data are presented. Each statistical downscaling method produces different meteorological portrayals including precipitation amount, wet-day frequency, and the energy input (i.e., shortwave radiation), and their interplay affects estimations of precipitation partitioning between evapotranspiration and runoff, extreme runoff, and hydrologic states (i.e., snow and soil moisture). The analyses show that BCCA underestimates annual precipitation by as much as −250 mm, leading to unreasonable hydrologic portrayals over the CONUS for all models. Although the other three statistical downscaling methods produce a comparable precipitation bias ranging from −10 to 8 mm across the CONUS, BCSDd severely overestimates the wet-day fraction by up to 0.25, leading to different precipitation partitioning compared to the simulations with other downscaled data. Overall, the choice of downscaling method contributes to less spread in runoff estimates (by a factor of 1.5–3) than the choice of hydrologic model with use of the default parameters if BCCA is excluded.

  16. Integrating predictive information into an agro-economic model to guide agricultural management

    NASA Astrophysics Data System (ADS)

    Zhang, Y.; Block, P.

    2016-12-01

    Skillful season-ahead climate predictions linked with responsive agricultural planning and management have the potential to reduce losses, if adopted by farmers, particularly for rainfed-dominated agriculture such as in Ethiopia. Precipitation predictions during the growing season in major agricultural regions of Ethiopia are used to generate predicted climate yield factors, which reflect the influence of precipitation amounts on crop yields and serve as inputs into an agro-economic model. The adapted model, originally developed by the International Food Policy Research Institute, produces outputs of economic indices (GDP, poverty rates, etc.) at zonal and national levels. Forecast-based approaches, in which farmers' actions are in response to forecasted conditions, are compared with no-forecast approaches in which farmers follow business as usual practices, expecting "average" climate conditions. The effects of farmer adoption rates, including the potential for reduced uptake due to poor predictions, and increasing forecast lead-time on economic outputs are also explored. Preliminary results indicate superior gains under forecast-based approaches.

  17. On the Hydrologic Adjustment of Climate-Model Projections: The Potential Pitfall of Potential Evapotranspiration

    USGS Publications Warehouse

    Milly, Paul C.D.; Dunne, Krista A.

    2011-01-01

    Hydrologic models often are applied to adjust projections of hydroclimatic change that come from climate models. Such adjustment includes climate-bias correction, spatial refinement ("downscaling"), and consideration of the roles of hydrologic processes that were neglected in the climate model. Described herein is a quantitative analysis of the effects of hydrologic adjustment on the projections of runoff change associated with projected twenty-first-century climate change. In a case study including three climate models and 10 river basins in the contiguous United States, the authors find that relative (i.e., fractional or percentage) runoff change computed with hydrologic adjustment more often than not was less positive (or, equivalently, more negative) than what was projected by the climate models. The dominant contributor to this decrease in runoff was a ubiquitous change in runoff (median -11%) caused by the hydrologic model’s apparent amplification of the climate-model-implied growth in potential evapotranspiration. Analysis suggests that the hydrologic model, on the basis of the empirical, temperature-based modified Jensen–Haise formula, calculates a change in potential evapotranspiration that is typically 3 times the change implied by the climate models, which explicitly track surface energy budgets. In comparison with the amplification of potential evapotranspiration, central tendencies of other contributions from hydrologic adjustment (spatial refinement, climate-bias adjustment, and process refinement) were relatively small. The authors’ findings highlight the need for caution when projecting changes in potential evapotranspiration for use in hydrologic models or drought indices to evaluate climate-change impacts on water.

  18. Assessment of Required Accuracy of Digital Elevation Data for Hydrologic Modeling

    NASA Technical Reports Server (NTRS)

    Kenward, T.; Lettenmaier, D. P.

    1997-01-01

    The effect of vertical accuracy of Digital Elevation Models (DEMs) on hydrologic models is evaluated by comparing three DEMs and resulting hydrologic model predictions applied to a 7.2 sq km USDA - ARS watershed at Mahantango Creek, PA. The high resolution (5 m) DEM was resempled to a 30 m resolution using method that constrained the spatial structure of the elevations to be comparable with the USGS and SIR-C DEMs. This resulting 30 m DEM was used as the reference product for subsequent comparisons. Spatial fields of directly derived quantities, such as elevation differences, slope, and contributing area, were compared to the reference product, as were hydrologic model output fields derived using each of the three DEMs at the common 30 m spatial resolution.

  19. One-day offset in daily hydrologic modeling: An exploration of the issue in automatic model calibration

    USDA-ARS?s Scientific Manuscript database

    The literature of daily hydrologic modelling illustrates that daily simulation models are incapable of accurately representing hydrograph timing due to relationships between precipitation and watershed hydrologic response. For watersheds with a time of concentration less than 24 hrs and a late day p...

  20. Towards a regional climate model coupled to a comprehensive hydrological model

    NASA Astrophysics Data System (ADS)

    Rasmussen, S. H.; Drews, M.; Christensen, J. H.; Butts, M. B.; Jensen, K. H.; Refsgaard, J.; Hydrological ModellingAssessing Climate Change Impacts At Different Scales (Hyacints)

    2010-12-01

    When planing new ground water abstractions wells, building areas, roads or other land use activities information about expected future groundwater table location for the lifetime of the construction may be critical. The life time of an abstraction well can be expected to be more than 50 years, while if for buildings may be up to 100 years or more. The construction of an abstraction well is expensive and it is important to know if clean groundwater is available for its expected life time. The future groundwater table is depending on the future climate. With climate change the hydrology is expected to change as well. Traditionally, this assessment has been done by driving hydrological models with output from a climate model. In this way feedback between the groundwater hydrology and the climate is neglected. Neglecting this feedback can lead to imprecise or wrong results. The goal of this work is to couple the regional climate model HIRHAM (Christensen et al. 2006) to the hydrological model MIKE SHE (Graham and Butts, 2006). The coupling exploits the new OpenMI technology that provides a standardized interface to define, describe and transfer data on a time step basis between software components that run simultaneously (Gregersen et al., 2007). HIRHAM runs on a UNIX platform whereas MIKE SHE and OpenMI are under WINDOWS. Therefore the first critical task has been to develop an effective communication link between the platforms. The first step towards assessing the coupled models performance are addressed by looking at simulated land-surface atmosphere feedback through variables such as evapotranspiration, sensible heat flux and soil moisture content. Christensen, O.B., Drews, M., Christensen, J.H., Dethloff, K., Ketelsen, K., Hebestadt, I. and Rinke, A. (2006) The HIRHAM Regional Climate Model. Version 5; DMI Scientific Report 0617. Danish Meteorological Institute. Graham, D.N. and Butts, M.B. (2005) Flexible, integrated watershed modelling with MIKE SHE, In

  1. Models of atmosphere-ecosystem-hydrology interactions: Approaches and testing

    NASA Technical Reports Server (NTRS)

    Schimel, David S.

    1992-01-01

    Interactions among the atmosphere, terrestrial ecosystems, and the hydrological cycle have been the subject of investigation for many years, although most of the research has had a regional focus. The topic is broad, including the effects of climate and hydrology on vegetation, the effects of vegetation on hydrology, the effects of the hydrological cycle on the atmosphere, and interactions of the cycles via material flux such as solutes and trace gases. The intent of this paper is to identify areas of critical uncertainty, discuss modeling approaches to resolving those problems, and then propose techniques for testing. I consider several interactions specifically to illustrate the range of problems. These areas are as follows: (1) cloud parameterizations and the land surface, (2) soil moisture, and (3) the terrestrial carbon cycle.

  2. Benchmarking hydrological model predictive capability for UK River flows and flood peaks.

    NASA Astrophysics Data System (ADS)

    Lane, Rosanna; Coxon, Gemma; Freer, Jim; Wagener, Thorsten

    2017-04-01

    Data and hydrological models are now available for national hydrological analyses. However, hydrological model performance varies between catchments, and lumped, conceptual models are not able to produce adequate simulations everywhere. This study aims to benchmark hydrological model performance for catchments across the United Kingdom within an uncertainty analysis framework. We have applied four hydrological models from the FUSE framework to 1128 catchments across the UK. These models are all lumped models and run at a daily timestep, but differ in the model structural architecture and process parameterisations, therefore producing different but equally plausible simulations. We apply FUSE over a 20 year period from 1988-2008, within a GLUE Monte Carlo uncertainty analyses framework. Model performance was evaluated for each catchment, model structure and parameter set using standard performance metrics. These were calculated both for the whole time series and to assess seasonal differences in model performance. The GLUE uncertainty analysis framework was then applied to produce simulated 5th and 95th percentile uncertainty bounds for the daily flow time-series and additionally the annual maximum prediction bounds for each catchment. The results show that the model performance varies significantly in space and time depending on catchment characteristics including climate, geology and human impact. We identify regions where models are systematically failing to produce good results, and present reasons why this could be the case. We also identify regions or catchment characteristics where one model performs better than others, and have explored what structural component or parameterisation enables certain models to produce better simulations in these catchments. Model predictive capability was assessed for each catchment, through looking at the ability of the models to produce discharge prediction bounds which successfully bound the observed discharge. These results

  3. Local control on precipitation in a fully coupled climate-hydrology model.

    PubMed

    Larsen, Morten A D; Christensen, Jens H; Drews, Martin; Butts, Michael B; Refsgaard, Jens C

    2016-03-10

    The ability to simulate regional precipitation realistically by climate models is essential to understand and adapt to climate change. Due to the complexity of associated processes, particularly at unresolved temporal and spatial scales this continues to be a major challenge. As a result, climate simulations of precipitation often exhibit substantial biases that affect the reliability of future projections. Here we demonstrate how a regional climate model (RCM) coupled to a distributed hydrological catchment model that fully integrates water and energy fluxes between the subsurface, land surface, plant cover and the atmosphere, enables a realistic representation of local precipitation. Substantial improvements in simulated precipitation dynamics on seasonal and longer time scales is seen for a simulation period of six years and can be attributed to a more complete treatment of hydrological sub-surface processes including groundwater and moisture feedback. A high degree of local influence on the atmosphere suggests that coupled climate-hydrology models have a potential for improving climate projections and the results further indicate a diminished need for bias correction in climate-hydrology impact studies.

  4. Local control on precipitation in a fully coupled climate-hydrology model

    PubMed Central

    Larsen, Morten A. D.; Christensen, Jens H.; Drews, Martin; Butts, Michael B.; Refsgaard, Jens C.

    2016-01-01

    The ability to simulate regional precipitation realistically by climate models is essential to understand and adapt to climate change. Due to the complexity of associated processes, particularly at unresolved temporal and spatial scales this continues to be a major challenge. As a result, climate simulations of precipitation often exhibit substantial biases that affect the reliability of future projections. Here we demonstrate how a regional climate model (RCM) coupled to a distributed hydrological catchment model that fully integrates water and energy fluxes between the subsurface, land surface, plant cover and the atmosphere, enables a realistic representation of local precipitation. Substantial improvements in simulated precipitation dynamics on seasonal and longer time scales is seen for a simulation period of six years and can be attributed to a more complete treatment of hydrological sub-surface processes including groundwater and moisture feedback. A high degree of local influence on the atmosphere suggests that coupled climate-hydrology models have a potential for improving climate projections and the results further indicate a diminished need for bias correction in climate-hydrology impact studies. PMID:26960564

  5. Use of output from high-resolution atmospheric models in landscape-scale hydrologic models: An assessment

    USGS Publications Warehouse

    Hostetler, S.W.; Giorgi, F.

    1993-01-01

    In this paper we investigate the feasibility of coupling regional climate models (RCMs) with landscape-scale hydrologic models (LSHMs) for studies of the effects of climate on hydrologic systems. The RCM used is the National Center for Atmospheric Research/Pennsylvania State University mesoscale model (MM4). Output from two year-round simulations (1983 and 1988) over the western United States is used to drive a lake model for Pyramid Lake in Nevada and a streamfiow model for Steamboat Creek in Oregon. Comparisons with observed data indicate that MM4 is able to produce meteorologic data sets that can be used to drive hydrologic models. Results from the lake model simulations indicate that the use of MM4 output produces reasonably good predictions of surface temperature and evaporation. Results from the streamflow simulations indicate that the use of MM4 output results in good simulations of the seasonal cycle of streamflow, but deficiencies in simulated wintertime precipitation resulted in underestimates of streamflow and soil moisture. Further work with climate (multiyear) simulations is necessary to achieve a complete analysis, but the results from this study indicate that coupling of LSHMs and RCMs may be a useful approach for evaluating the effects of climate change on hydrologic systems.

  6. Hydrological-niche models predict water plant functional group distributions in diverse wetland types.

    PubMed

    Deane, David C; Nicol, Jason M; Gehrig, Susan L; Harding, Claire; Aldridge, Kane T; Goodman, Abigail M; Brookes, Justin D

    2017-06-01

    Human use of water resources threatens environmental water supplies. If resource managers are to develop policies that avoid unacceptable ecological impacts, some means to predict ecosystem response to changes in water availability is necessary. This is difficult to achieve at spatial scales relevant for water resource management because of the high natural variability in ecosystem hydrology and ecology. Water plant functional groups classify species with similar hydrological niche preferences together, allowing a qualitative means to generalize community responses to changes in hydrology. We tested the potential for functional groups in making quantitative prediction of water plant functional group distributions across diverse wetland types over a large geographical extent. We sampled wetlands covering a broad range of hydrogeomorphic and salinity conditions in South Australia, collecting both hydrological and floristic data from 687 quadrats across 28 wetland hydrological gradients. We built hydrological-niche models for eight water plant functional groups using a range of candidate models combining different surface inundation metrics. We then tested the predictive performance of top-ranked individual and averaged models for each functional group. Cross validation showed that models achieved acceptable predictive performance, with correct classification rates in the range 0.68-0.95. Model predictions can be made at any spatial scale that hydrological data are available and could be implemented in a geographical information system. We show the response of water plant functional groups to inundation is consistent enough across diverse wetland types to quantify the probability of hydrological impacts over regional spatial scales. © 2017 by the Ecological Society of America.

  7. Integrating predictive information into an agro-economic model to guide agricultural planning

    NASA Astrophysics Data System (ADS)

    Block, Paul; Zhang, Ying; You, Liangzhi

    2017-04-01

    Seasonal climate forecasts can inform long-range planning, including water resources utilization and allocation, however quantifying the value of this information on the economy is often challenging. For rain-fed farmers, skillful season-ahead predictions may lead to superior planning, as compared to business as usual strategies, resulting in additional benefits or reduced losses. In this study, regional-level probabilistic precipitation forecasts of the major rainy season in Ethiopia are fed into an agro-economic model, adapted from the International Food Policy Research Institute, to evaluate economic outcomes (GDP, poverty rates, etc.) as compared with a no-forecast approach. Based on forecasted conditions, farmers can select various actions: adjusting crop area and crop type, purchasing drought resistant seed, or applying additional fertilizer. Preliminary results favor the forecast-based approach, particularly through crop area reallocation.

  8. Comprehensive Representation of Hydrologic and Geomorphic Process Coupling in Numerical Models: Internal Dynamics and Basin Evolution

    NASA Astrophysics Data System (ADS)

    Istanbulluoglu, E.; Vivoni, E. R.; Ivanov, V. Y.; Bras, R. L.

    2005-12-01

    Landscape morphology has an important control on the spatial and temporal organization of basin hydrologic response to climate forcing, affecting soil moisture redistribution as well as vegetation function. On the other hand, erosion, driven by hydrology and modulated by vegetation, produces landforms over geologic time scales that reflect characteristic signatures of the dominant land forming process. Responding to extreme climate events or anthropogenic disturbances of the land surface, infrequent but rapid forms of erosion (e.g., arroyo development, landsliding) can modify topography such that basin hydrology is significantly influenced. Despite significant advances in both hydrologic and geomorphic modeling over the past two decades, the dynamic interactions between basin hydrology, geomorphology and terrestrial ecology are not adequately captured in current model frameworks. In order to investigate hydrologic-geomorphic-ecologic interactions at the basin scale we present initial efforts in integrating the CHILD landscape evolution model (Tucker et al. 2001) with the tRIBS hydrology model (Ivanov et al. 2004), both developed in a common software environment. In this talk, we present preliminary results of the numerical modeling of the coupled evolution of basin hydro-geomorphic response and resulting landscape morphology in two sets of examples. First, we discuss the long-term evolution of both the hydrologic response and the resulting basin morphology from an initially uplifted plateau. In the second set of modeling experiments, we implement changes in climate and land-use to an existing topography and compare basin hydrologic response to the model results when landscape form is fixed (e.g. no coupling between hydrology and geomorphology). Model results stress the importance of internal basin dynamics, including runoff generation mechanisms and hydrologic states, in shaping hydrologic response as well as the importance of employing comprehensive

  9. Identifying Hydrologic Processes in Agricultural Watersheds Using Precipitation-Runoff Models

    USGS Publications Warehouse

    Linard, Joshua I.; Wolock, David M.; Webb, Richard M.T.; Wieczorek, Michael

    2009-01-01

    Understanding the fate and transport of agricultural chemicals applied to agricultural fields will assist in designing the most effective strategies to prevent water-quality impairments. At a watershed scale, the processes controlling the fate and transport of agricultural chemicals are generally understood only conceptually. To examine the applicability of conceptual models to the processes actually occurring, two precipitation-runoff models - the Soil and Water Assessment Tool (SWAT) and the Water, Energy, and Biogeochemical Model (WEBMOD) - were applied in different agricultural settings of the contiguous United States. Each model, through different physical processes, simulated the transport of water to a stream from the surface, the unsaturated zone, and the saturated zone. Models were calibrated for watersheds in Maryland, Indiana, and Nebraska. The calibrated sets of input parameters for each model at each watershed are discussed, and the criteria used to validate the models are explained. The SWAT and WEBMOD model results at each watershed conformed to each other and to the processes identified in each watershed's conceptual hydrology. In Maryland the conceptual understanding of the hydrology indicated groundwater flow was the largest annual source of streamflow; the simulation results for the validation period confirm this. The dominant source of water to the Indiana watershed was thought to be tile drains. Although tile drains were not explicitly simulated in the SWAT model, a large component of streamflow was received from lateral flow, which could be attributed to tile drains. Being able to explicitly account for tile drains, WEBMOD indicated water from tile drains constituted most of the annual streamflow in the Indiana watershed. The Nebraska models indicated annual streamflow was composed primarily of perennial groundwater flow and infiltration-excess runoff, which conformed to the conceptual hydrology developed for that watershed. The hydrologic

  10. A priori discretization error metrics for distributed hydrologic modeling applications

    NASA Astrophysics Data System (ADS)

    Liu, Hongli; Tolson, Bryan A.; Craig, James R.; Shafii, Mahyar

    2016-12-01

    Watershed spatial discretization is an important step in developing a distributed hydrologic model. A key difficulty in the spatial discretization process is maintaining a balance between the aggregation-induced information loss and the increase in computational burden caused by the inclusion of additional computational units. Objective identification of an appropriate discretization scheme still remains a challenge, in part because of the lack of quantitative measures for assessing discretization quality, particularly prior to simulation. This study proposes a priori discretization error metrics to quantify the information loss of any candidate discretization scheme without having to run and calibrate a hydrologic model. These error metrics are applicable to multi-variable and multi-site discretization evaluation and provide directly interpretable information to the hydrologic modeler about discretization quality. The first metric, a subbasin error metric, quantifies the routing information loss from discretization, and the second, a hydrological response unit (HRU) error metric, improves upon existing a priori metrics by quantifying the information loss due to changes in land cover or soil type property aggregation. The metrics are straightforward to understand and easy to recode. Informed by the error metrics, a two-step discretization decision-making approach is proposed with the advantage of reducing extreme errors and meeting the user-specified discretization error targets. The metrics and decision-making approach are applied to the discretization of the Grand River watershed in Ontario, Canada. Results show that information loss increases as discretization gets coarser. Moreover, results help to explain the modeling difficulties associated with smaller upstream subbasins since the worst discretization errors and highest error variability appear in smaller upstream areas instead of larger downstream drainage areas. Hydrologic modeling experiments under

  11. Flash flood warning based on fully dynamic hydrology modelling

    NASA Astrophysics Data System (ADS)

    Pejanovic, Goran; Petkovic, Slavko; Cvetkovic, Bojan; Nickovic, Slobodan

    2016-04-01

    Numerical hydrologic modeling has achieved limited success in the past due to, inter alia, lack of adequate input data. Over the last decade, data availability has improved substantially. For modelling purposes, high-resolution data on topography, river routing, and land cover and soil features have meanwhile become available, as well as the observations such as radar precipitation information. In our study, we have implemented the HYPROM model (Hydrology Prognostic Model) to predict a flash flood event at a smaller-scale basin in Southern Serbia. HYPROM is based on the full set of governing equations for surface hydrological dynamics, in which momentum components, along with the equation of mass continuity, are used as full prognostic equations. HYPROM also includes a river routing module serving as a collector for the extra surface water. Such approach permits appropriate representation of different hydrology scales ranging from flash floods to flows of large and slow river basins. The use of full governing equations, if not appropriately parameterized, may lead to numerical instability systems when the surface water in a model is vanishing. To resolve these modelling problems, an unconditionally stable numerical scheme and a method for height redistribution avoiding shortwave height noise have been developed in HYPROM, which achieve numerical convergence of u, v and h when surface water disappears. We have applied HYPROM, driven by radar-estimated precipitation, to predict flash flooding occurred over smaller and medium-size river basins. Two torrential rainfall cases have been simulated to check the accuracy of the model: the exceptional flooding of May 2014 in Western Serbia, and the convective flash flood of January 2015 in Southern Serbia. The second episode has been successfully predicted by HYPROM in terms of timing and intensity six hours before the event occurred. Such flash flood warning system is in preparation to be operationally implemented in the

  12. Subglacial Hydrology Model Intercomparison Project (SHMIP)

    NASA Astrophysics Data System (ADS)

    Werder, Mauro A.; de Fleurian, Basile; Creyts, Timothy T.; Damsgaard, Anders; Delaney, Ian; Dow, Christine F.; Gagliardini, Olivier; Hoffman, Matthew J.; Seguinot, Julien; Sommers, Aleah; Irarrazaval Bustos, Inigo; Downs, Jakob

    2017-04-01

    The SHMIP project is the first intercomparison project of subglacial drainage models (http://shmip.bitbucket.org). Its synthetic test suites and evaluation were designed such that any subglacial hydrology model producing effective pressure can participate. In contrast to ice deformation, the physical processes of subglacial hydrology (which in turn impacts basal sliding of glaciers) are poorly known. A further complication is that different glacial and geological settings can lead to different drainage physics. The aim of the project is therefore to qualitatively compare the outputs of the participating models for a wide range of water forcings and glacier geometries. This will allow to put existing studies, which use different drainage models, into context and will allow new studies to select the most suitable model for the problem at hand. We present the results from the just completed intercomparison exercise. Twelve models participated: eight 2D and four 1D models; nine include both an efficient and inefficient system, the other three one of the systems; all but two models use R-channels as efficient system, and/or a linked-cavity like inefficient system, one exception uses porous layers with different characteristic for each of the systems, the other exception is based on canals. The main variable used for the comparison is effective pressure, as that is a direct proxy for basal sliding of glaciers. The models produce large differences in the effective pressure fields, in particular for higher water input scenarios. This shows that the selection of a subglacial drainage model will likely impact the conclusions of a study significantly.

  13. HYDROLOGY AND SEDIMENT MODELING USING THE BASINS NON-POINT SOURCE MODEL

    EPA Science Inventory

    The Non-Point Source Model (Hydrologic Simulation Program-Fortran, or HSPF) within the EPA Office of Water's BASINS watershed modeling system was used to simulate streamflow and total suspended solids within Contentnea Creek, North Carolina, which is a tributary of the Neuse Rive...

  14. “Black Swans” of Hydrology: Can our Models Address the Science of Hydrologic Change?

    NASA Astrophysics Data System (ADS)

    Kumar, P.

    2009-12-01

    Coupled models of terrestrial hydrology and climate have grown in complexity leading to better understanding of the coupling between the hydrosphere, biosphere, and the climate system. During the past two decades, these models have evolved through generational changes as they have grown in sophistication in their ability to resolve spatial heterogeneity as well as vegetation dynamics and biogeochemistry. These developments have, in part, been driven by data collection efforts ranging from focused field campaigns to long-term observational networks, advances in remote sensing and other measurement technologies, along with sophisticated estimation and assimilation methods. However, the hydrologic cycle is changing leading to unexpected and unanticipated behavior through emergent dynamics and patterns that are not part of the historical milieu. Is there a new thinking that is needed to address this challenge? The goal of this talk is to draw from the modeling developments in the past two decades to foster a debate for moving forward.

  15. Towards an integrated model of floodplain hydrology representing feedbacks and anthropogenic effects

    NASA Astrophysics Data System (ADS)

    Andreadis, K.; Schumann, G.; Voisin, N.; O'Loughlin, F.; Tesfa, T. K.; Bates, P.

    2017-12-01

    The exchange of water between hillslopes, river channels and floodplain can be quite complex and the difficulty in capturing the mechanisms behind it is exacerbated by the impact of human activities such as irrigation and reservoir operations. Although there has been a vast body of work on modeling hydrological processes, most of the resulting models have been limited with regards to aspects of the coupled human-natural system. For example, hydrologic models that represent processes such as evapotranspiration, infiltration, interception and groundwater dynamics often neglect anthropogenic effects or do not adequately represent the inherently two-dimensional floodplain flow. We present an integrated modeling framework that is comprised of the Variable Infiltration Capacity (VIC) hydrology model, the LISFLOOD-FP hydrodynamic model, and the Water resources Management (WM) model. The VIC model solves the energy and water balance over a gridded domain and simulates a number of hydrologic features such as snow, frozen soils, lakes and wetlands, while also representing irrigation demand from cropland areas. LISFLOOD-FP solves an approximation of the Saint-Venant equations to efficiently simulate flow in river channels and the floodplain. The implementation of WM accommodates a variety of operating rules in reservoirs and withdrawals due to consumptive demands, allowing the successful simulation of regulated flow. The models are coupled so as to allow feedbacks between their corresponding processes, therefore providing the ability to test different hypotheses about the floodplain hydrology of large-scale basins. We test this integrated framework over the Zambezi River basin by simulating its hydrology from 2000-2010, and evaluate the results against remotely sensed observations. Finally, we examine the sensitivity of streamflow and water inundation to changes in reservoir operations, precipitation and temperature.

  16. Identifying influential data points in hydrological model calibration and their impact on streamflow predictions

    NASA Astrophysics Data System (ADS)

    Wright, David; Thyer, Mark; Westra, Seth

    2015-04-01

    Highly influential data points are those that have a disproportionately large impact on model performance, parameters and predictions. However, in current hydrological modelling practice the relative influence of individual data points on hydrological model calibration is not commonly evaluated. This presentation illustrates and evaluates several influence diagnostics tools that hydrological modellers can use to assess the relative influence of data. The feasibility and importance of including influence detection diagnostics as a standard tool in hydrological model calibration is discussed. Two classes of influence diagnostics are evaluated: (1) computationally demanding numerical "case deletion" diagnostics; and (2) computationally efficient analytical diagnostics, based on Cook's distance. These diagnostics are compared against hydrologically orientated diagnostics that describe changes in the model parameters (measured through the Mahalanobis distance), performance (objective function displacement) and predictions (mean and maximum streamflow). These influence diagnostics are applied to two case studies: a stage/discharge rating curve model, and a conceptual rainfall-runoff model (GR4J). Removing a single data point from the calibration resulted in differences to mean flow predictions of up to 6% for the rating curve model, and differences to mean and maximum flow predictions of up to 10% and 17%, respectively, for the hydrological model. When using the Nash-Sutcliffe efficiency in calibration, the computationally cheaper Cook's distance metrics produce similar results to the case-deletion metrics at a fraction of the computational cost. However, Cooks distance is adapted from linear regression with inherit assumptions on the data and is therefore less flexible than case deletion. Influential point detection diagnostics show great potential to improve current hydrological modelling practices by identifying highly influential data points. The findings of this

  17. Significant uncertainty in global scale hydrological modeling from precipitation data errors

    NASA Astrophysics Data System (ADS)

    Sperna Weiland, Frederiek C.; Vrugt, Jasper A.; van Beek, Rens (L.) P. H.; Weerts, Albrecht H.; Bierkens, Marc F. P.

    2015-10-01

    In the past decades significant progress has been made in the fitting of hydrologic models to data. Most of this work has focused on simple, CPU-efficient, lumped hydrologic models using discharge, water table depth, soil moisture, or tracer data from relatively small river basins. In this paper, we focus on large-scale hydrologic modeling and analyze the effect of parameter and rainfall data uncertainty on simulated discharge dynamics with the global hydrologic model PCR-GLOBWB. We use three rainfall data products; the CFSR reanalysis, the ERA-Interim reanalysis, and a combined ERA-40 reanalysis and CRU dataset. Parameter uncertainty is derived from Latin Hypercube Sampling (LHS) using monthly discharge data from five of the largest river systems in the world. Our results demonstrate that the default parameterization of PCR-GLOBWB, derived from global datasets, can be improved by calibrating the model against monthly discharge observations. Yet, it is difficult to find a single parameterization of PCR-GLOBWB that works well for all of the five river basins considered herein and shows consistent performance during both the calibration and evaluation period. Still there may be possibilities for regionalization based on catchment similarities. Our simulations illustrate that parameter uncertainty constitutes only a minor part of predictive uncertainty. Thus, the apparent dichotomy between simulations of global-scale hydrologic behavior and actual data cannot be resolved by simply increasing the model complexity of PCR-GLOBWB and resolving sub-grid processes. Instead, it would be more productive to improve the characterization of global rainfall amounts at spatial resolutions of 0.5° and smaller.

  18. Coupling of the simultaneous heat and water model with a distributed hydrological model and evaluation of the combined model in a cold region watershed

    USDA-ARS?s Scientific Manuscript database

    To represent the effects of frozen soil on hydrology in cold regions, a new physically based distributed hydrological model has been developed by coupling the simultaneous heat and water model (SHAW) with the geomorphology based distributed hydrological model (GBHM), under the framework of the water...

  19. Simulating the hydrologic cycle in coal mining subsidence areas with a distributed hydrologic model

    PubMed Central

    Wang, Jianhua; Lu, Chuiyu; Sun, Qingyan; Xiao, Weihua; Cao, Guoliang; Li, Hui; Yan, Lingjia; Zhang, Bo

    2017-01-01

    Large-scale ground subsidence caused by coal mining and subsequent water-filling leads to serious environmental problems and economic losses, especially in plains with a high phreatic water level. Clarifying the hydrologic cycle in subsidence areas has important practical value for environmental remediation, and provides a scientific basis for water resource development and utilisation of the subsidence areas. Here we present a simulation approach to describe interactions between subsidence area water (SW) and several hydrologic factors from the River-Subsidence-Groundwater Model (RSGM), which is developed based on the distributed hydrologic model. Analysis of water balance shows that the recharge of SW from groundwater only accounts for a small fraction of the total water source, due to weak groundwater flow in the plain. The interaction between SW and groundwater has an obvious annual cycle. The SW basically performs as a net source of groundwater in the wet season, and a net sink for groundwater in the dry season. The results show there is an average 905.34 million m3 per year of water available through the Huainan coal mining subsidence areas (HCMSs). If these subsidence areas can be integrated into water resource planning, the increasingly precarious water supply infrastructure will be strengthened. PMID:28106048

  20. An efficient agro-industrial complex in Almería (Spain): Towards an integrated and sustainable bioeconomy model.

    PubMed

    Egea, Francisco J; Torrente, Roberto G; Aguilar, Alfredo

    2018-01-25

    In the last ten years, bioeconomy strategies and policy-related bioeconomy initiatives have been developed all over the world. Some of them are currently in the process of translation into specific actions. In most cases, the approaches followed have been top-down policy-related initiatives, triggered by the public sector originating a dynamic which can bring together different bioeconomy stakeholders i.e. industry, academia, financial operators and farmers. This article describes a bottom-up situation with unique bioeconomy-related features that deserve specific attention. Over the last 40 years, Almería, in the south east of Spain, has developed one of the most efficient agro-industrial complexes in the world, evolving from a traditional and subsistence agriculture, to becoming the major vegetable exporter in the European Union (EU). This growth set aside issues such as sustainability, long-term perspectives on water resources or agricultural waste. However, societal concerns about a circular economy, as well as policy initiatives in the EU and in Spain on bioeconomy are changing the situation towards an integrated, efficient and sustainable bioeconomy system. Currently, the production chain demands innovations related to the use of biomass as source of bioproducts and bioenergy in order to remain competitive. Some positive aspects are the relatively small size of the agro-industrial area, making transport and communications rapid and easy, and the existence of strong and dedicated academic and financial institutions. This article outlines the current efforts and initiatives to couple the existing successful agro-industrial complex with that of a fully sustainable bioeconomy model. Copyright © 2017 Elsevier B.V. All rights reserved.

  1. The added value of remote sensing products in constraining hydrological models

    NASA Astrophysics Data System (ADS)

    Nijzink, Remko C.; Almeida, Susana; Pechlivanidis, Ilias; Capell, René; Gustafsson, David; Arheimer, Berit; Freer, Jim; Han, Dawei; Wagener, Thorsten; Sleziak, Patrik; Parajka, Juraj; Savenije, Hubert; Hrachowitz, Markus

    2017-04-01

    The calibration of a hydrological model still depends on the availability of streamflow data, even though more additional sources of information (i.e. remote sensed data products) have become more widely available. In this research, the model parameters of four different conceptual hydrological models (HYPE, HYMOD, TUW, FLEX) were constrained with remotely sensed products. The models were applied over 27 catchments across Europe to cover a wide range of climates, vegetation and landscapes. The fluxes and states of the models were correlated with the relevant products (e.g. MOD10A snow with modelled snow states), after which new a-posteriori parameter distributions were determined based on a weighting procedure using conditional probabilities. Briefly, each parameter was weighted with the coefficient of determination of the relevant regression between modelled states/fluxes and products. In this way, final feasible parameter sets were derived without the use of discharge time series. Initial results show that improvements in model performance, with regard to streamflow simulations, are obtained when the models are constrained with a set of remotely sensed products simultaneously. In addition, we present a more extensive analysis to assess a model's ability to reproduce a set of hydrological signatures, such as rising limb density or peak distribution. Eventually, this research will enhance our understanding and recommendations in the use of remotely sensed products for constraining conceptual hydrological modelling and improving predictive capability, especially for data sparse regions.

  2. Modelling of different enzyme productions by solid-state fermentation on several agro-industrial residues.

    PubMed

    Diaz, Ana Belen; Blandino, Ana; Webb, Colin; Caro, Ildefonso

    2016-11-01

    A simple kinetic model, with only three fitting parameters, for several enzyme productions in Petri dishes by solid-state fermentation is proposed in this paper, which may be a valuable tool for simulation of this type of processes. Basically, the model is able to predict temporal fungal enzyme production by solid-state fermentation on complex substrates, maximum enzyme activity expected and time at which these maxima are reached. In this work, several fermentations in solid state were performed in Petri dishes, using four filamentous fungi grown on different agro-industrial residues, measuring xylanase, exo-polygalacturonase, cellulose and laccase activities over time. Regression coefficients after fitting experimental data to the proposed model turned out to be quite high in all cases. In fact, these results are very interesting considering, on the one hand, the simplicity of the model and, on the other hand, that enzyme activities correspond to different enzymes, produced by different fungi on different substrates.

  3. Improved Ground Hydrology Calculations for Global Climate Models (GCMs): Soil Water Movement and Evapotranspiration.

    NASA Astrophysics Data System (ADS)

    Abramopoulos, F.; Rosenzweig, C.; Choudhury, B.

    1988-09-01

    A physically based ground hydrology model is developed to improve the land-surface sensible and latent heat calculations in global climate models (GCMs). The processes of transpiration, evaporation from intercepted precipitation and dew, evaporation from bare soil, infiltration, soil water flow, and runoff are explicitly included in the model. The amount of detail in the hydrologic calculations is restricted to a level appropriate for use in a GCM, but each of the aforementioned processes is modeled on the basis of the underlying physical principles. Data from the Goddard Institute for Space Studies (GISS) GCM are used as inputs for off-line tests of the ground hydrology model in four 8° × 10° regions (Brazil, Sahel, Sahara, and India). Soil and vegetation input parameters are calculated as area-weighted means over the 8° × 10° gridhox. This compositing procedure is tested by comparing resulting hydrological quantities to ground hydrology model calculations performed on the 1° × 1° cells which comprise the 8° × 10° gridbox. Results show that the compositing procedure works well except in the Sahel where lower soil water levels and a heterogeneous land surface produce more variability in hydrological quantities, indicating that a resolution better than 8° × 10° is needed for that region. Modeled annual and diurnal hydrological cycles compare well with observations for Brazil, where real world data are available. The sensitivity of the ground hydrology model to several of its input parameters was tested; it was found to be most sensitive to the fraction of land covered by vegetation and least sensitive to the soil hydraulic conductivity and matric potential.

  4. Representing northern peatland microtopography and hydrology within the Community Land Model

    DOE PAGES

    Shi, Xiaoying; Thornton, Peter E.; Ricciuto, Daniel M.; ...

    2015-11-12

    Predictive understanding of northern peatland hydrology is a necessary precursor to understanding the fate of massive carbon stores in these systems under the influence of present and future climate change. Current models have begun to address microtopographic controls on peatland hydrology, but none have included a prognostic calculation of peatland water table depth for a vegetated wetland, independent of prescribed regional water tables. We introduce here a new configuration of the Community Land Model (CLM) which includes a fully prognostic water table calculation for a vegetated peatland. Our structural and process changes to CLM focus on modifications needed to representmore » the hydrologic cycle of bogs environment with perched water tables, as well as distinct hydrologic dynamics and vegetation communities of the raised hummock and sunken hollow microtopography characteristic of peatland bogs. The modified model was parameterized and independently evaluated against observations from an ombrotrophic raised-dome bog in northern Minnesota (S1-Bog), the site for the Spruce and Peatland Responses Under Climatic and Environmental Change experiment (SPRUCE). Simulated water table levels compared well with site-level observations. The new model predicts hydrologic changes in response to planned warming at the SPRUCE site. At present, standing water is commonly observed in bog hollows after large rainfall events during the growing season, but simulations suggest a sharp decrease in water table levels due to increased evapotranspiration under the most extreme warming level, nearly eliminating the occurrence of standing water in the growing season. Simulated soil energy balance was strongly influenced by reduced winter snowpack under warming simulations, with the warming influence on soil temperature partly offset by the loss of insulating snowpack in early and late winter. Furthermore, the new model provides improved predictive capacity for seasonal hydrological

  5. Representing northern peatland microtopography and hydrology within the Community Land Model

    DOE PAGES

    Shi, X.; Thornton, P. E.; Ricciuto, D. M.; ...

    2015-02-20

    Predictive understanding of northern peatland hydrology is a necessary precursor to understanding the fate of massive carbon stores in these systems under the influence of present and future climate change. Current models have begun to address microtopographic controls on peatland hydrology, but none have included a prognostic calculation of peatland water table depth for a vegetated wetland, independent of prescribed regional water tables. We introduce here a new configuration of the Community Land Model (CLM) which includes a fully prognostic water table calculation for a vegetated peatland. Our structural and process changes to CLM focus on modifications needed to representmore » the hydrologic cycle of bogs environment with perched water tables, as well as distinct hydrologic dynamics and vegetation communities of the raised hummock and sunken hollow microtopography characteristic of peatland bogs. The modified model was parameterized and independently evaluated against observations from an ombrotrophic raised-dome bog in northern Minnesota (S1-Bog), the site for the Spruce and Peatland Responses Under Climatic and Environmental Change experiment (SPRUCE). Simulated water table levels compared well with site-level observations. The new model predicts significant hydrologic changes in response to planned warming at the SPRUCE site. At present, standing water is commonly observed in bog hollows after large rainfall events during the growing season, but simulations suggest a sharp decrease in water table levels due to increased evapotranspiration under the most extreme warming level, nearly eliminating the occurrence of standing water in the growing season. Simulated soil energy balance was strongly influenced by reduced winter snowpack under warming simulations, with the warming influence on soil temperature partly offset by the loss of insulating snowpack in early and late winter. The new model provides improved predictive capacity for seasonal hydrological

  6. A Four-Stage Hybrid Model for Hydrological Time Series Forecasting

    PubMed Central

    Di, Chongli; Yang, Xiaohua; Wang, Xiaochao

    2014-01-01

    Hydrological time series forecasting remains a difficult task due to its complicated nonlinear, non-stationary and multi-scale characteristics. To solve this difficulty and improve the prediction accuracy, a novel four-stage hybrid model is proposed for hydrological time series forecasting based on the principle of ‘denoising, decomposition and ensemble’. The proposed model has four stages, i.e., denoising, decomposition, components prediction and ensemble. In the denoising stage, the empirical mode decomposition (EMD) method is utilized to reduce the noises in the hydrological time series. Then, an improved method of EMD, the ensemble empirical mode decomposition (EEMD), is applied to decompose the denoised series into a number of intrinsic mode function (IMF) components and one residual component. Next, the radial basis function neural network (RBFNN) is adopted to predict the trend of all of the components obtained in the decomposition stage. In the final ensemble prediction stage, the forecasting results of all of the IMF and residual components obtained in the third stage are combined to generate the final prediction results, using a linear neural network (LNN) model. For illustration and verification, six hydrological cases with different characteristics are used to test the effectiveness of the proposed model. The proposed hybrid model performs better than conventional single models, the hybrid models without denoising or decomposition and the hybrid models based on other methods, such as the wavelet analysis (WA)-based hybrid models. In addition, the denoising and decomposition strategies decrease the complexity of the series and reduce the difficulties of the forecasting. With its effective denoising and accurate decomposition ability, high prediction precision and wide applicability, the new model is very promising for complex time series forecasting. This new forecast model is an extension of nonlinear prediction models. PMID:25111782

  7. A four-stage hybrid model for hydrological time series forecasting.

    PubMed

    Di, Chongli; Yang, Xiaohua; Wang, Xiaochao

    2014-01-01

    Hydrological time series forecasting remains a difficult task due to its complicated nonlinear, non-stationary and multi-scale characteristics. To solve this difficulty and improve the prediction accuracy, a novel four-stage hybrid model is proposed for hydrological time series forecasting based on the principle of 'denoising, decomposition and ensemble'. The proposed model has four stages, i.e., denoising, decomposition, components prediction and ensemble. In the denoising stage, the empirical mode decomposition (EMD) method is utilized to reduce the noises in the hydrological time series. Then, an improved method of EMD, the ensemble empirical mode decomposition (EEMD), is applied to decompose the denoised series into a number of intrinsic mode function (IMF) components and one residual component. Next, the radial basis function neural network (RBFNN) is adopted to predict the trend of all of the components obtained in the decomposition stage. In the final ensemble prediction stage, the forecasting results of all of the IMF and residual components obtained in the third stage are combined to generate the final prediction results, using a linear neural network (LNN) model. For illustration and verification, six hydrological cases with different characteristics are used to test the effectiveness of the proposed model. The proposed hybrid model performs better than conventional single models, the hybrid models without denoising or decomposition and the hybrid models based on other methods, such as the wavelet analysis (WA)-based hybrid models. In addition, the denoising and decomposition strategies decrease the complexity of the series and reduce the difficulties of the forecasting. With its effective denoising and accurate decomposition ability, high prediction precision and wide applicability, the new model is very promising for complex time series forecasting. This new forecast model is an extension of nonlinear prediction models.

  8. Newtonian Nudging For A Richards Equation-based Distributed Hydrological Model

    NASA Astrophysics Data System (ADS)

    Paniconi, C.; Marrocu, M.; Putti, M.; Verbunt, M.

    In this study a relatively simple data assimilation method has been implemented in a relatively complex hydrological model. The data assimilation technique is Newtonian relaxation or nudging, in which model variables are driven towards observations by a forcing term added to the model equations. The forcing term is proportional to the difference between simulation and observation (relaxation component) and contains four-dimensional weighting functions that can incorporate prior knowledge about the spatial and temporal variability and characteristic scales of the state variable(s) being assimilated. The numerical model couples a three-dimensional finite element Richards equation solver for variably saturated porous media and a finite difference diffusion wave approximation based on digital elevation data for surface water dynamics. We describe the implementation of the data assimilation algorithm for the coupled model and report on the numerical and hydrological performance of the resulting assimila- tion scheme. Nudging is shown to be successful in improving the hydrological sim- ulation results, and it introduces little computational cost, in terms of CPU and other numerical aspects of the model's behavior, in some cases even improving numerical performance compared to model runs without nudging. We also examine the sensitiv- ity of the model to nudging term parameters including the spatio-temporal influence coefficients in the weighting functions. Overall the nudging algorithm is quite flexi- ble, for instance in dealing with concurrent observation datasets, gridded or scattered data, and different state variables, and the implementation presented here can be read- ily extended to any features not already incorporated. Moreover the nudging code and tests can serve as a basis for implementation of more sophisticated data assimilation techniques in a Richards equation-based hydrological model.

  9. Shuttle radar DEM hydrological correction for erosion modelling in small catchments

    NASA Astrophysics Data System (ADS)

    Jarihani, Ben; Sidle, Roy; Bartley, Rebecca

    2016-04-01

    Digital Elevation Models (DEMs) that accurately replicate both landscape form and processes are critical to support modelling of environmental processes. Catchment and hillslope scale runoff and sediment processes (i.e., patterns of overland flow, infiltration, subsurface stormflow and erosion) are all topographically mediated. In remote and data-scarce regions, high resolution DEMs (LiDAR) are often not available, and moderate to course resolution digital elevation models (e.g., SRTM) have difficulty replicating detailed hydrological patterns, especially in relatively flat landscapes. Several surface reconditioning algorithms (e.g., Smoothing) and "Stream burning" techniques (e.g., Agree or ANUDEM), in conjunction with representation of the known stream networks, have been used to improve DEM performance in replicating known hydrology. Detailed stream network data are not available at regional and national scales, but can be derived at local scales from remotely-sensed data. This research explores the implication of high resolution stream network data derived from Google Earth images for DEM hydrological correction, instead of using course resolution stream networks derived from topographic maps. The accuracy of implemented method in producing hydrological-efficient DEMs were assessed by comparing the hydrological parameters derived from modified DEMs and limited high-resolution airborne LiDAR DEMs. The degree of modification is dominated by the method used and availability of the stream network data. Although stream burning techniques improve DEMs hydrologically, these techniques alter DEM characteristics that may affect catchment boundaries, stream position and length, as well as secondary terrain derivatives (e.g., slope, aspect). Modification of a DEM to better reflect known hydrology can be useful, however, knowledge of the magnitude and spatial pattern of the changes are required before using a DEM for subsequent analyses.

  10. On the Usefulness of Hydrologic Landscapes for Hydrologic Modeling and Water Management

    EPA Science Inventory

    Hydrologic Landscapes (HLs) are units that can be used in aggregate to describe the watershed-scale hydrologic response of an area through use of physical and climatic properties. The HL assessment unit is a useful classification tool to relate and transfer hydrologically meaning...

  11. On the Usefulness of Hydrologic Landscapes on Hydrologic Model calibration and Selection

    EPA Science Inventory

    Hydrologic Landscapes (HLs) are units that can be used in aggregate to describe the watershed-scale hydrologic response of an area through use of physical and climatic properties. The HL assessment unit is a useful classification tool to relate and transfer hydrologically meaning...

  12. Digital hydrologic networks supporting applications related to spatially referenced regression modeling

    USGS Publications Warehouse

    Brakebill, John W.; Wolock, David M.; Terziotti, Silvia

    2011-01-01

    Digital hydrologic networks depicting surface-water pathways and their associated drainage catchments provide a key component to hydrologic analysis and modeling. Collectively, they form common spatial units that can be used to frame the descriptions of aquatic and watershed processes. In addition, they provide the ability to simulate and route the movement of water and associated constituents throughout the landscape. Digital hydrologic networks have evolved from derivatives of mapping products to detailed, interconnected, spatially referenced networks of water pathways, drainage areas, and stream and watershed characteristics. These properties are important because they enhance the ability to spatially evaluate factors that affect the sources and transport of water-quality constituents at various scales. SPAtially Referenced Regressions On Watershed attributes (SPARROW), a process-based ⁄ statistical model, relies on a digital hydrologic network in order to establish relations between quantities of monitored contaminant flux, contaminant sources, and the associated physical characteristics affecting contaminant transport. Digital hydrologic networks modified from the River Reach File (RF1) and National Hydrography Dataset (NHD) geospatial datasets provided frameworks for SPARROW in six regions of the conterminous United States. In addition, characteristics of the modified RF1 were used to update estimates of mean-annual streamflow. This produced more current flow estimates for use in SPARROW modeling.

  13. The application of remote sensing to the development and formulation of hydrologic planning models

    NASA Technical Reports Server (NTRS)

    Fowler, T. R.; Castruccio, P. A.; Loats, H. L., Jr.

    1977-01-01

    The development of a remote sensing model and its efficiency in determining parameters of hydrologic models are reviewed. Procedures for extracting hydrologic data from LANDSAT imagery, and the visual analysis of composite imagery are presented. A hydrologic planning model is developed and applied to determine seasonal variations in watershed conditions. The transfer of this technology to a user community and contract arrangements are discussed.

  14. MERINOVA: Meteorological risks as drivers of environmental innovation in agro-ecosystem management

    NASA Astrophysics Data System (ADS)

    Gobin, Anne; Oger, Robert; Marlier, Catherine; Van De Vijver, Hans; Vandermeulen, Valerie; Van Huylenbroeck, Guido; Zamani, Sepideh; Curnel, Yannick; Mettepenningen, Evi

    2013-04-01

    The BELSPO funded project 'MERINOVA' deals with risks associated with extreme weather phenomena and with risks of biological origin such as pests and diseases. The major objectives of the proposed project are to characterise extreme meteorological events, assess the impact on Belgian agro-ecosystems, characterise their vulnerability and resilience to these events, and explore innovative adaptation options to agricultural risk management. The project comprises of five major parts that reflect the chain of risks: (i) Hazard: Assessing the likely frequency and magnitude of extreme meteorological events by means of probability density functions; (ii) Impact: Analysing the potential bio-physical and socio-economic impact of extreme weather events on agro-ecosystems in Belgium using process-based modelling techniques commensurate with the regional scale; (iii) Vulnerability: Identifying the most vulnerable agro-ecosystems using fuzzy multi-criteria and spatial analysis; (iv) Risk Management: Uncovering innovative risk management and adaptation options using actor-network theory and fuzzy cognitive mapping techniques; and, (v) Communication: Communicating to research, policy and practitioner communities using web-based techniques. The different tasks of the MERINOVA project require expertise in several scientific disciplines: meteorology, statistics, spatial database management, agronomy, bio-physical impact modelling, socio-economic modelling, actor-network theory, fuzzy cognitive mapping techniques. These expertises are shared by the four scientific partners who each lead one work package. The MERINOVA project will concentrate on promoting a robust and flexible framework by demonstrating its performance across Belgian agro-ecosystems, and by ensuring its relevance to policy makers and practitioners. Impacts developed from physically based models will not only provide information on the state of the damage at any given time, but also assist in understanding the links

  15. A priori discretization quality metrics for distributed hydrologic modeling applications

    NASA Astrophysics Data System (ADS)

    Liu, Hongli; Tolson, Bryan; Craig, James; Shafii, Mahyar; Basu, Nandita

    2016-04-01

    In distributed hydrologic modelling, a watershed is treated as a set of small homogeneous units that address the spatial heterogeneity of the watershed being simulated. The ability of models to reproduce observed spatial patterns firstly depends on the spatial discretization, which is the process of defining homogeneous units in the form of grid cells, subwatersheds, or hydrologic response units etc. It is common for hydrologic modelling studies to simply adopt a nominal or default discretization strategy without formally assessing alternative discretization levels. This approach lacks formal justifications and is thus problematic. More formalized discretization strategies are either a priori or a posteriori with respect to building and running a hydrologic simulation model. A posteriori approaches tend to be ad-hoc and compare model calibration and/or validation performance under various watershed discretizations. The construction and calibration of multiple versions of a distributed model can become a seriously limiting computational burden. Current a priori approaches are more formalized and compare overall heterogeneity statistics of dominant variables between candidate discretization schemes and input data or reference zones. While a priori approaches are efficient and do not require running a hydrologic model, they do not fully investigate the internal spatial pattern changes of variables of interest. Furthermore, the existing a priori approaches focus on landscape and soil data and do not assess impacts of discretization on stream channel definition even though its significance has been noted by numerous studies. The primary goals of this study are to (1) introduce new a priori discretization quality metrics considering the spatial pattern changes of model input data; (2) introduce a two-step discretization decision-making approach to compress extreme errors and meet user-specified discretization expectations through non-uniform discretization threshold

  16. Is there a `universal' dynamic zero-parameter hydrological model? Evaluation of a dynamic Budyko model in US and India

    NASA Astrophysics Data System (ADS)

    Patnaik, S.; Biswal, B.; Sharma, V. C.

    2017-12-01

    River flow varies greatly in space and time, and the single biggest challenge for hydrologists and ecologists around the world is the fact that most rivers are either ungauged or poorly gauged. Although it is relatively easier to predict long-term average flow of a river using the `universal' zero-parameter Budyko model, lack of data hinders short-term flow prediction at ungauged locations using traditional hydrological models as they require observed flow data for model calibration. Flow prediction in ungauged basins thus requires a dynamic 'zero-parameter' hydrological model. One way to achieve this is to regionalize a dynamic hydrological model's parameters. However, a regionalization method based zero-parameter dynamic hydrological model is not `universal'. An alternative attempt was made recently to develop a zero-parameter dynamic model by defining an instantaneous dryness index as a function of antecedent rainfall and solar energy inputs with the help of a decay function and using the original Budyko function. The model was tested first in 63 US catchments and later in 50 Indian catchments. The median Nash-Sutcliffe efficiency (NSE) was found to be close to 0.4 in both the cases. Although improvements need to be incorporated in order to use the model for reliable prediction, the main aim of this study was to rather understand hydrological processes. The overall results here seem to suggest that the dynamic zero-parameter Budyko model is `universal.' In other words natural catchments around the world are strikingly similar to each other in the way they respond to hydrologic inputs; we thus need to focus more on utilizing catchment similarities in hydrological modelling instead of over parameterizing our models.

  17. Remote sensing inputs to landscape models which predict future spatial land use patterns for hydrologic models

    NASA Technical Reports Server (NTRS)

    Miller, L. D.; Tom, C.; Nualchawee, K.

    1977-01-01

    A tropical forest area of Northern Thailand provided a test case of the application of the approach in more natural surroundings. Remote sensing imagery subjected to proper computer analysis has been shown to be a very useful means of collecting spatial data for the science of hydrology. Remote sensing products provide direct input to hydrologic models and practical data bases for planning large and small-scale hydrologic developments. Combining the available remote sensing imagery together with available map information in the landscape model provides a basis for substantial improvements in these applications.

  18. Modeling Subsurface Hydrology in Floodplains

    NASA Astrophysics Data System (ADS)

    Evans, Cristina M.; Dritschel, David G.; Singer, Michael B.

    2018-03-01

    Soil-moisture patterns in floodplains are highly dynamic, owing to the complex relationships between soil properties, climatic conditions at the surface, and the position of the water table. Given this complexity, along with climate change scenarios in many regions, there is a need for a model to investigate the implications of different conditions on water availability to riparian vegetation. We present a model, HaughFlow, which is able to predict coupled water movement in the vadose and phreatic zones of hydraulically connected floodplains. Model output was calibrated and evaluated at six sites in Australia to identify key patterns in subsurface hydrology. This study identifies the importance of the capillary fringe in vadose zone hydrology due to its water storage capacity and creation of conductive pathways. Following peaks in water table elevation, water can be stored in the capillary fringe for up to months (depending on the soil properties). This water can provide a critical resource for vegetation that is unable to access the water table. When water table peaks coincide with heavy rainfall events, the capillary fringe can support saturation of the entire soil profile. HaughFlow is used to investigate the water availability to riparian vegetation, producing daily output of water content in the soil over decadal time periods within different depth ranges. These outputs can be summarized to support scientific investigations of plant-water relations, as well as in management applications.

  19. Copula Entropy coupled with Wavelet Neural Network Model for Hydrological Prediction

    NASA Astrophysics Data System (ADS)

    Wang, Yin; Yue, JiGuang; Liu, ShuGuang; Wang, Li

    2018-02-01

    Artificial Neural network(ANN) has been widely used in hydrological forecasting. in this paper an attempt has been made to find an alternative method for hydrological prediction by combining Copula Entropy(CE) with Wavelet Neural Network(WNN), CE theory permits to calculate mutual information(MI) to select Input variables which avoids the limitations of the traditional linear correlation(LCC) analysis. Wavelet analysis can provide the exact locality of any changes in the dynamical patterns of the sequence Coupled with ANN Strong non-linear fitting ability. WNN model was able to provide a good fit with the hydrological data. finally, the hybrid model(CE+WNN) have been applied to daily water level of Taihu Lake Basin, and compared with CE ANN, LCC WNN and LCC ANN. Results showed that the hybrid model produced better results in estimating the hydrograph properties than the latter models.

  20. Improving evapotranspiration processes in distrubing hydrological models using Remote Sensing derived ET products.

    NASA Astrophysics Data System (ADS)

    Abitew, T. A.; van Griensven, A.; Bauwens, W.

    2015-12-01

    Evapotranspiration is the main process in hydrology (on average around 60%), though has not received as much attention in the evaluation and calibration of hydrological models. In this study, Remote Sensing (RS) derived Evapotranspiration (ET) is used to improve the spatially distributed processes of ET of SWAT model application in the upper Mara basin (Kenya) and the Blue Nile basin (Ethiopia). The RS derived ET data is obtained from recently compiled global datasets (continuously monthly data at 1 km resolution from MOD16NBI,SSEBop,ALEXI,CMRSET models) and from regionally applied Energy Balance Models (for several cloud free days). The RS-RT data is used in different forms: Method 1) to evaluate spatially distributed evapotransiration model resultsMethod 2) to calibrate the evotranspiration processes in hydrological modelMethod 3) to bias-correct the evapotranpiration in hydrological model during simulation after changing the SWAT codesAn inter-comparison of the RS-ET products shows that at present there is a significant bias, but at the same time an agreement on the spatial variability of ET. The ensemble mean of different ET products seems the most realistic estimation and was further used in this study.The results show that:Method 1) the spatially mapped evapotranspiration of hydrological models shows clear differences when compared to RS derived evapotranspiration (low correlations). Especially evapotranspiration in forested areas is strongly underestimated compared to other land covers.Method 2) Calibration allows to improve the correlations between the RS and hydrological model results to some extent.Method 3) Bias-corrections are efficient in producing (sesonal or annual) evapotranspiration maps from hydrological models which are very similar to the patterns obtained from RS data.Though the bias-correction is very efficient, it is advised to improve the model results by better representing the ET processes by improved plant/crop computations, improved

  1. Developing a hydrological model in the absence of field data

    NASA Astrophysics Data System (ADS)

    Sproles, E. A.; Orrego Nelson, C.; Kerr, T.; Lopez Aspe, D.

    2014-12-01

    We present two runoff models that use remotely-sensed snow cover products from the Moderate Resolution Imaging Spectrometer (MODIS) as the first order hydrologic input. These simplistic models are the first step in developing an operational model for the Elqui River watershed located in northern Central Chile (30°S). In this semi-arid region, snow and glacier melt are the dominant hydrologic inputs where annual precipitation is limited to three or four winter events. Unfortunately winter access to the Andean Cordillera where snow accumulates is limited. While a monitoring network to measure snow where it accumulates in the upper elevations is under development, management decisions regarding water resources cannot wait. The two models we present differ in structure. The first applies a Monte Carlo approach to determine relationships between lagged changes in monthly snow cover frequency and monthly discharge. The second is a modified degree-day melt model, utilizing the MODIS snow cover product to determine where and when snow melt occurs. These models are not watershed specific and are applicable in other regions where snow dominates hydrologic inputs, but measurements are minimal.

  2. Impact of multicollinearity on small sample hydrologic regression models

    NASA Astrophysics Data System (ADS)

    Kroll, Charles N.; Song, Peter

    2013-06-01

    Often hydrologic regression models are developed with ordinary least squares (OLS) procedures. The use of OLS with highly correlated explanatory variables produces multicollinearity, which creates highly sensitive parameter estimators with inflated variances and improper model selection. It is not clear how to best address multicollinearity in hydrologic regression models. Here a Monte Carlo simulation is developed to compare four techniques to address multicollinearity: OLS, OLS with variance inflation factor screening (VIF), principal component regression (PCR), and partial least squares regression (PLS). The performance of these four techniques was observed for varying sample sizes, correlation coefficients between the explanatory variables, and model error variances consistent with hydrologic regional regression models. The negative effects of multicollinearity are magnified at smaller sample sizes, higher correlations between the variables, and larger model error variances (smaller R2). The Monte Carlo simulation indicates that if the true model is known, multicollinearity is present, and the estimation and statistical testing of regression parameters are of interest, then PCR or PLS should be employed. If the model is unknown, or if the interest is solely on model predictions, is it recommended that OLS be employed since using more complicated techniques did not produce any improvement in model performance. A leave-one-out cross-validation case study was also performed using low-streamflow data sets from the eastern United States. Results indicate that OLS with stepwise selection generally produces models across study regions with varying levels of multicollinearity that are as good as biased regression techniques such as PCR and PLS.

  3. Coupled geophysical-hydrological modeling of controlled NAPL spill

    NASA Astrophysics Data System (ADS)

    Kowalsky, M. B.; Majer, E.; Peterson, J. E.; Finsterle, S.; Mazzella, A.

    2006-12-01

    Past studies have shown reasonable sensitivity of geophysical data for detecting or monitoring the movement of non-aqueous phase liquids (NAPLs) in the subsurface. However, heterogeneity in subsurface properties and in NAPL distribution commonly results in non-unique data interpretation. Combining multiple geophysical data types and incorporating constraints from hydrological models will potentially decrease the non-uniqueness in data interpretation and aid in site characterization. Large-scale laboratory experiments have been conducted over several years to evaluate the use of various geophysical methods, including ground-penetrating radar (GPR), seismic, and electrical methods, for monitoring controlled spills of tetrachloroethylene (PCE), a hazardous industrial solvent that is pervasive in the subsurface. In the current study, we consider an experiment in which PCE was introduced into a large tank containing a heterogeneous distribution of sand and clay mixtures, and allowed to migrate while time-lapse geophysical data were collected. We consider two approaches for interpreting the surface GPR and crosswell seismic data. The first approach involves (a) waveform inversion of the surface GPR data using a non-gradient based optimization algorithm to estimate the dielectric constant distributions and (b) conversion of crosswell seismic travel times to acoustic velocity distributions; the dielectric constant and acoustic velocity distributions are then related to NAPL saturation using appropriate petrophysical models. The second approach takes advantage of a recently developed framework for coupled hydrological-geophysical modeling, providing a hydrological constraint on interpretation of the geophysical data and additionally resulting in quantitative estimates of the most relevant hydrological parameters that determine NAPL behavior in the system. Specifically, we simulate NAPL migration using the multiphase multicomponent flow simulator TOUGH2 with a 2-D radial

  4. [Agro-ecosystem ammonia emission in Sichuan-Chongqing region].

    PubMed

    Li, Fu-chun; Han, Shen-hui; Yang, Jun; Zhang, Xu; Li, Ru-yan; Wei, Yuan-song; Fan, Mao-hong

    2009-10-15

    Ammonia (NH3) emission from agro-ecosystem in the Sichuan-Chongqing region during 1990-2004, was estimated by the regional nitrogen cycling model IAP-N. The county level agricultural activities data were used, and Sichuan-Chongqing region was divided into four sub-areas by the geographical characteristics , environment and local climatic conditions and administrative division. The results showed that average annual ammonia emissions (in nitrogen gauge) in 1990-1994, 1995-1999, 2000-2004 were 626.7, 670.5 and 698.8 Gg x a(-1) respectively. The ammonia emission appeared increasing trend, whereas, the contribution of various ammonia sources presented little change. For instance, in 2000-2004, the contributions of NH3 emission from fertilized cropland, manure management system and field residues burning to the total ammonia emission of agro-ecosystem in the Sichuan-Chongqing region were 53%, 46% and 1%, equals to 374.9, 318.2 and 5.6 Gg x a(-1) respectively. But the contributions were variable in different regions. Ammonia emission was primarily induced by fertilized cropland in Chengdu plain and Chongqing hilly area, whereas, in northwest sub-region of Sichuan province was manure management system. The geographical distribution of ammonia emission from agro-ecosystem in the Sichuan-Chongqing region was generally "east high and west low". Ammonia emissions in sub-regions of Chongqing hilly area, Chengdu plain, southwest and northwest sub-regions were 165.6, 408.8, 85.9 and 38.8 Gg x a(-1), respectively, during 2000-2004. At the same time, ammonia density were 20 and 28 kg x (hm2 x a)(-1) in sub-regions of the Chongqing hilly area and the Chengdu plain, whereas, 9.1 and 1.6 kg x (hm2 x a)(-1) in southwest and northwest sub-regions, respectively. The results will provide a scientific basis for making fertilizer effectively applied and mitigate NH3 and GHG emissions from agro-ecosystem of Sichuan-Chongqing region.

  5. Conceptualizing Peatlands in a Physically-Based Spatially Distributed Hydrologic Model

    NASA Astrophysics Data System (ADS)

    Downer, Charles; Wahl, Mark

    2017-04-01

    In as part of a research effort focused on climate change effects on permafrost near Fairbanks, Alaska, it became apparent that peat soils, overlain by thick sphagnum moss, had a considerable effect on the overall hydrology. Peatlands represent a confounding mixture of vegetation, soils, and water that present challenges for conceptualizing and parametrizing hydrologic models. We employed the Gridded Surface Subsurface Hydrologic Analysis Model (GSSHA) in our analysis of the Caribou Poker Creek Experimental Watershed (CPCRW). GSSHA is a physically-based, spatially distributed, watershed model developed by the U.S. Army to simulate important streamflow-generating processes (Downer and Ogden, 2004). The model enables simulation of surface water and groundwater interactions, as well as soil temperature and frozen ground effects on subsurface water movement. The test site is a 104 km2 basin located in the Yukon-Tanana Uplands of the Northern Plateaus Physiographic Province centered on 65˚10' N latitude and 147˚30' W longitude. The area lies above the Chattanika River floodplain and is characterized by rounded hilltops with gentle slopes and alluvium-floored valleys having minimal relief (Wahrhaftig, 1965) underlain by a mica shist of the Birch Creek formation (Rieger et al., 1972). The region has a cold continental climate characterized by short warm summers and long cold winters. Observed stream flows indicated significant groundwater contribution with sustained base flows even during dry periods. A site visit exposed the presence of surface water flows indicating a mixed basin that would require both surface and subsurface simulation capability to properly capture the response. Soils in the watershed are predominately silt loam underlain by shallow fractured bedrock. Throughout much of the basin, a thick layer of live sphagnum moss and fine peat covers the ground surface. A restrictive layer of permafrost is found on north facing slopes. The combination of thick

  6. Some thoughts on building, evaluating and constraining hydrologic models from catchment to continental scales

    NASA Astrophysics Data System (ADS)

    Wagener, Thorsten

    2017-04-01

    We increasingly build and apply hydrologic models that simulate systems beyond the catchment scale. Such models run at regional, national or even continental scales. They therefore offer opportunities for new scientific insights, for example by enabling comparative hydrology or connectivity studies, and for water management, where we might better understand changes to water resources from larger scale activities like agriculture or from hazards such as droughts. However, these models also require us to rethink how we build and evaluate them given that some of the unsolved problems from the catchment scale have not gone away. So what role should such models play in scientific advancement in hydrology? What problems do we still have to resolve before they can fulfill their role? What opportunities for solving these problems are there, but have not yet been utilized? I will provide some thoughts on these issues in the context of the IAHS Panta Rhei initiative and the scientific challenges it has set out for hydrology (Montanari et al., 2013, Hydrological Sciences Journal; McMillan et al., 2016, Hydrological Sciences Journal).

  7. Multi-metric calibration of hydrological model to capture overall flow regimes

    NASA Astrophysics Data System (ADS)

    Zhang, Yongyong; Shao, Quanxi; Zhang, Shifeng; Zhai, Xiaoyan; She, Dunxian

    2016-08-01

    Flow regimes (e.g., magnitude, frequency, variation, duration, timing and rating of change) play a critical role in water supply and flood control, environmental processes, as well as biodiversity and life history patterns in the aquatic ecosystem. The traditional flow magnitude-oriented calibration of hydrological model was usually inadequate to well capture all the characteristics of observed flow regimes. In this study, we simulated multiple flow regime metrics simultaneously by coupling a distributed hydrological model with an equally weighted multi-objective optimization algorithm. Two headwater watersheds in the arid Hexi Corridor were selected for the case study. Sixteen metrics were selected as optimization objectives, which could represent the major characteristics of flow regimes. Model performance was compared with that of the single objective calibration. Results showed that most metrics were better simulated by the multi-objective approach than those of the single objective calibration, especially the low and high flow magnitudes, frequency and variation, duration, maximum flow timing and rating. However, the model performance of middle flow magnitude was not significantly improved because this metric was usually well captured by single objective calibration. The timing of minimum flow was poorly predicted by both the multi-metric and single calibrations due to the uncertainties in model structure and input data. The sensitive parameter values of the hydrological model changed remarkably and the simulated hydrological processes by the multi-metric calibration became more reliable, because more flow characteristics were considered. The study is expected to provide more detailed flow information by hydrological simulation for the integrated water resources management, and to improve the simulation performances of overall flow regimes.

  8. Review article: Hydrological modeling in glacierized catchments of central Asia - status and challenges

    NASA Astrophysics Data System (ADS)

    Chen, Yaning; Li, Weihong; Fang, Gonghuan; Li, Zhi

    2017-02-01

    Meltwater from glacierized catchments is one of the most important water supplies in central Asia. Therefore, the effects of climate change on glaciers and snow cover will have increasingly significant consequences for runoff. Hydrological modeling has become an indispensable research approach to water resources management in large glacierized river basins, but there is a lack of focus in the modeling of glacial discharge. This paper reviews the status of hydrological modeling in glacierized catchments of central Asia, discussing the limitations of the available models and extrapolating these to future challenges and directions. After reviewing recent efforts, we conclude that the main sources of uncertainty in assessing the regional hydrological impacts of climate change are the unreliable and incomplete data sets and the lack of understanding of the hydrological regimes of glacierized catchments of central Asia. Runoff trends indicate a complex response to changes in climate. For future variation of water resources, it is essential to quantify the responses of hydrologic processes to both climate change and shrinking glaciers in glacierized catchments, and scientific focus should be on reducing uncertainties linked to these processes.

  9. Parallelization of a Fully-Distributed Hydrologic Model using Sub-basin Partitioning

    NASA Astrophysics Data System (ADS)

    Vivoni, E. R.; Mniszewski, S.; Fasel, P.; Springer, E.; Ivanov, V. Y.; Bras, R. L.

    2005-12-01

    A primary obstacle towards advances in watershed simulations has been the limited computational capacity available to most models. The growing trend of model complexity, data availability and physical representation has not been matched by adequate developments in computational efficiency. This situation has created a serious bottleneck which limits existing distributed hydrologic models to small domains and short simulations. In this study, we present novel developments in the parallelization of a fully-distributed hydrologic model. Our work is based on the TIN-based Real-time Integrated Basin Simulator (tRIBS), which provides continuous hydrologic simulation using a multiple resolution representation of complex terrain based on a triangulated irregular network (TIN). While the use of TINs reduces computational demand, the sequential version of the model is currently limited over large basins (>10,000 km2) and long simulation periods (>1 year). To address this, a parallel MPI-based version of the tRIBS model has been implemented and tested using high performance computing resources at Los Alamos National Laboratory. Our approach utilizes domain decomposition based on sub-basin partitioning of the watershed. A stream reach graph based on the channel network structure is used to guide the sub-basin partitioning. Individual sub-basins or sub-graphs of sub-basins are assigned to separate processors to carry out internal hydrologic computations (e.g. rainfall-runoff transformation). Routed streamflow from each sub-basin forms the major hydrologic data exchange along the stream reach graph. Individual sub-basins also share subsurface hydrologic fluxes across adjacent boundaries. We demonstrate how the sub-basin partitioning provides computational feasibility and efficiency for a set of test watersheds in northeastern Oklahoma. We compare the performance of the sequential and parallelized versions to highlight the efficiency gained as the number of processors increases

  10. Significance of hydrological model choice and land use changes when doing climate change impact assessment

    NASA Astrophysics Data System (ADS)

    Bjørnholt Karlsson, Ida; Obel Sonnenborg, Torben; Refsgaard, Jens Christian; Høgh Jensen, Karsten

    2014-05-01

    Uncertainty in impact studies arises both from Global Climate Models (GCM), emission projections, statistical downscaling, Regional Climate Models (RCM), hydrological models and calibration techniques (Refsgaard et al. 2013). Some of these uncertainties have been evaluated several times in the literature; however few studies have investigated the effect of hydrological model choice on the assessment results (Boorman & Sefton 1997; Jiang et al. 2007; Bastola et al. 2011). These studies have found that model choice results in large differences, up to 70%, in the predicted discharge changes depending on the climate input. The objective of the study is to investigate the impact of climate change on hydrology of the Odense catchment, Denmark both in response to (a) different climate projections (GCM-RCM combinations); (b) different hydrological models and (c) different land use scenarios. This includes: 1. Separation of the climate model signal; the hydrological model signal and the land use signal 2. How do the different hydrological components react under different climate and land use conditions for the different models 3. What land use scenario seems to provide the best adaptation for the challenges of the different future climate change scenarios from a hydrological perspective? Four climate models from the ENSEMBLES project (Hewitt & Griggs 2004): ECHAM5 - HIRHAM5, ECHAM5 - RCA3, ARPEGE - RM5.1 and HadCM3 - HadRM3 are used, assessing the climate change impact in three periods: 1991-2010 (present), 2041-2060 (near future) and 2081-2100 (far future). The four climate models are used in combination with three hydrological models with different conceptual layout: NAM, SWAT and MIKE SHE. Bastola, S., C. Murphy and J. Sweeney (2011). "The role of hydrological modelling uncertainties in climate change impact assessments of Irish river catchments." Advances in Water Resources 34: 562-576. Boorman, D. B. and C. E. M. Sefton (1997). "Recognising the uncertainty in the

  11. Pursuing realistic hydrologic model under SUPERFLEX framework in a semi-humid catchment in China

    NASA Astrophysics Data System (ADS)

    Wei, Lingna; Savenije, Hubert H. G.; Gao, Hongkai; Chen, Xi

    2016-04-01

    Model realism is pursued perpetually by hydrologists for flood and drought prediction, integrated water resources management and decision support of water security. "Physical-based" distributed hydrologic models are speedily developed but they also encounter unneglectable challenges, for instance, computational time with low efficiency and parameters uncertainty. This study step-wisely tested four conceptual hydrologic models under the framework of SUPERFLEX in a small semi-humid catchment in southern Huai River basin of China. The original lumped FLEXL has hypothesized model structure of four reservoirs to represent canopy interception, unsaturated zone, subsurface flow of fast and slow components and base flow storage. Considering the uneven rainfall in space, the second model (FLEXD) is developed with same parameter set for different rain gauge controlling units. To reveal the effect of topography, terrain descriptor of height above the nearest drainage (HAND) combined with slope is applied to classify the experimental catchment into two landscapes. Then the third one (FLEXTOPO) builds different model blocks in consideration of the dominant hydrologic process corresponding to the topographical condition. The fourth one named FLEXTOPOD integrating the parallel framework of FLEXTOPO in four controlled units is designed to interpret spatial variability of rainfall patterns and topographic features. Through pairwise comparison, our results suggest that: (1) semi-distributed models (FLEXD and FLEXTOPOD) taking precipitation spatial heterogeneity into account has improved model performance with parsimonious parameter set, and (2) hydrologic model architecture with flexibility to reflect perceived dominant hydrologic processes can include the local terrain circumstances for each landscape. Hence, the modeling actions are coincided with the catchment behaviour and close to the "reality". The presented methodology is regarding hydrologic model as a tool to test our

  12. Improving flood forecasting capability of physically based distributed hydrological models by parameter optimization

    NASA Astrophysics Data System (ADS)

    Chen, Y.; Li, J.; Xu, H.

    2016-01-01

    Physically based distributed hydrological models (hereafter referred to as PBDHMs) divide the terrain of the whole catchment into a number of grid cells at fine resolution and assimilate different terrain data and precipitation to different cells. They are regarded to have the potential to improve the catchment hydrological process simulation and prediction capability. In the early stage, physically based distributed hydrological models are assumed to derive model parameters from the terrain properties directly, so there is no need to calibrate model parameters. However, unfortunately the uncertainties associated with this model derivation are very high, which impacted their application in flood forecasting, so parameter optimization may also be necessary. There are two main purposes for this study: the first is to propose a parameter optimization method for physically based distributed hydrological models in catchment flood forecasting by using particle swarm optimization (PSO) algorithm and to test its competence and to improve its performances; the second is to explore the possibility of improving physically based distributed hydrological model capability in catchment flood forecasting by parameter optimization. In this paper, based on the scalar concept, a general framework for parameter optimization of the PBDHMs for catchment flood forecasting is first proposed that could be used for all PBDHMs. Then, with the Liuxihe model as the study model, which is a physically based distributed hydrological model proposed for catchment flood forecasting, the improved PSO algorithm is developed for the parameter optimization of the Liuxihe model in catchment flood forecasting. The improvements include adoption of the linearly decreasing inertia weight strategy to change the inertia weight and the arccosine function strategy to adjust the acceleration coefficients. This method has been tested in two catchments in southern China with different sizes, and the results show

  13. Improving flood forecasting capability of physically based distributed hydrological model by parameter optimization

    NASA Astrophysics Data System (ADS)

    Chen, Y.; Li, J.; Xu, H.

    2015-10-01

    Physically based distributed hydrological models discrete the terrain of the whole catchment into a number of grid cells at fine resolution, and assimilate different terrain data and precipitation to different cells, and are regarded to have the potential to improve the catchment hydrological processes simulation and prediction capability. In the early stage, physically based distributed hydrological models are assumed to derive model parameters from the terrain properties directly, so there is no need to calibrate model parameters, but unfortunately, the uncertanties associated with this model parameter deriving is very high, which impacted their application in flood forecasting, so parameter optimization may also be necessary. There are two main purposes for this study, the first is to propose a parameter optimization method for physically based distributed hydrological models in catchment flood forecasting by using PSO algorithm and to test its competence and to improve its performances, the second is to explore the possibility of improving physically based distributed hydrological models capability in cathcment flood forecasting by parameter optimization. In this paper, based on the scalar concept, a general framework for parameter optimization of the PBDHMs for catchment flood forecasting is first proposed that could be used for all PBDHMs. Then, with Liuxihe model as the study model, which is a physically based distributed hydrological model proposed for catchment flood forecasting, the improverd Particle Swarm Optimization (PSO) algorithm is developed for the parameter optimization of Liuxihe model in catchment flood forecasting, the improvements include to adopt the linear decreasing inertia weight strategy to change the inertia weight, and the arccosine function strategy to adjust the acceleration coefficients. This method has been tested in two catchments in southern China with different sizes, and the results show that the improved PSO algorithm could be

  14. Subgrid spatial variability of soil hydraulic functions for hydrological modelling

    NASA Astrophysics Data System (ADS)

    Kreye, Phillip; Meon, Günter

    2016-07-01

    State-of-the-art hydrological applications require a process-based, spatially distributed hydrological model. Runoff characteristics are demanded to be well reproduced by the model. Despite that, the model should be able to describe the processes at a subcatchment scale in a physically credible way. The objective of this study is to present a robust procedure to generate various sets of parameterisations of soil hydraulic functions for the description of soil heterogeneity on a subgrid scale. Relations between Rosetta-generated values of saturated hydraulic conductivity (Ks) and van Genuchten's parameters of soil hydraulic functions were statistically analysed. An universal function that is valid for the complete bandwidth of Ks values could not be found. After concentrating on natural texture classes, strong correlations were identified for all parameters. The obtained regression results were used to parameterise sets of hydraulic functions for each soil class. The methodology presented in this study is applicable on a wide range of spatial scales and does not need input data from field studies. The developments were implemented into a hydrological modelling system.

  15. Using the cloud to speed-up calibration of watershed-scale hydrologic models (Invited)

    NASA Astrophysics Data System (ADS)

    Goodall, J. L.; Ercan, M. B.; Castronova, A. M.; Humphrey, M.; Beekwilder, N.; Steele, J.; Kim, I.

    2013-12-01

    This research focuses on using the cloud to address computational challenges associated with hydrologic modeling. One example is calibration of a watershed-scale hydrologic model, which can take days of execution time on typical computers. While parallel algorithms for model calibration exist and some researchers have used multi-core computers or clusters to run these algorithms, these solutions do not fully address the challenge because (i) calibration can still be too time consuming even on multicore personal computers and (ii) few in the community have the time and expertise needed to manage a compute cluster. Given this, another option for addressing this challenge that we are exploring through this work is the use of the cloud for speeding-up calibration of watershed-scale hydrologic models. The cloud used in this capacity provides a means for renting a specific number and type of machines for only the time needed to perform a calibration model run. The cloud allows one to precisely balance the duration of the calibration with the financial costs so that, if the budget allows, the calibration can be performed more quickly by renting more machines. Focusing specifically on the SWAT hydrologic model and a parallel version of the DDS calibration algorithm, we show significant speed-up time across a range of watershed sizes using up to 256 cores to perform a model calibration. The tool provides a simple web-based user interface and the ability to monitor the calibration job submission process during the calibration process. Finally this talk concludes with initial work to leverage the cloud for other tasks associated with hydrologic modeling including tasks related to preparing inputs for constructing place-based hydrologic models.

  16. The Rangeland Hydrology and Erosion Model

    NASA Astrophysics Data System (ADS)

    Nearing, M. A.

    2016-12-01

    The Rangeland Hydrology and Erosion Model (RHEM) is a process-based model that was designed to address rangelands conditions. RHEM is designed for government agencies, land managers and conservationists who need sound, science-based technology to model, assess, and predict runoff and erosion rates on rangelands and to assist in evaluating rangeland conservation practices effects. RHEM is an event-based model that estimates runoff, erosion, and sediment delivery rates and volumes at the spatial scale of the hillslope and the temporal scale of as single rainfall event. It represents erosion processes under normal and fire-impacted rangeland conditions. Moreover, it adopts a new splash erosion and thin sheet-flow transport equation developed from rangeland data, and it links the model hydrologic and erosion parameters with rangeland plant community by providing a new system of parameter estimation equations based on 204 plots at 49 rangeland sites distributed across 15 western U.S. states. A dynamic partial differential sediment continuity equation is used to model the total detachment rate of concentrated flow and rain splash and sheet flow. RHEM is also designed to be used as a calculator, or "engine", within other watershed scale models. From the research perspective RHEM acts as a vehicle for incorporating new scientific findings from rangeland infiltration, runoff, and erosion studies. Current applications of the model include: 1) a web site for general use (conservation planning, research, etc.), 2) National Resource Inventory reports to Congress, 3) as a computational engine within watershed scale models (e.g., KINEROS, HEC), 4) Ecological Site & State and Transition Descriptions, 5) proposed in 2015 to become part of the NRCS Desktop applications for field offices.

  17. The U.S. Geological Survey Coal Hydrology Program and the potential of hydrologic models for impact assessments

    USGS Publications Warehouse

    Doyle, W. Harry

    1981-01-01

    A requirement of Public Law 95-87, the Surface Mining Control and Reclamation Act of 1977, is the understanding of the hydrology in actual and proposed surface-mined areas. Surface-water data for small specific-sites and for larger areas such as adjacent and general areas are needed also to satisfy the hydrologic requirements of the Act. The Act specifies that surface-water modeling techniques may be used to generate the data and information. The purpose of this report is to describe how this can be achieved for smaller watersheds. This report also characterizes 12 ' state-of-the-art ' strip-mining assessment models that are to be tested with data from two data-intensive studies involving small watersheds in Tennessee and Indiana. Watershed models are best applied to small watersheds with specific-site data. Extending the use of modeling techniques to larger watersheds remains relatively untested, and to date the upper limits for application have not been established. The U.S. Geological Survey is currently collecting regional hydrologic data in the major coal provinces of the United States and this data will be used to help satisfy the ' general-area ' data requirements of the Act. This program is reviewed and described in this report. (USGS)

  18. Newtonian nudging for a Richards equation-based distributed hydrological model

    NASA Astrophysics Data System (ADS)

    Paniconi, Claudio; Marrocu, Marino; Putti, Mario; Verbunt, Mark

    The objective of data assimilation is to provide physically consistent estimates of spatially distributed environmental variables. In this study a relatively simple data assimilation method has been implemented in a relatively complex hydrological model. The data assimilation technique is Newtonian relaxation or nudging, in which model variables are driven towards observations by a forcing term added to the model equations. The forcing term is proportional to the difference between simulation and observation (relaxation component) and contains four-dimensional weighting functions that can incorporate prior knowledge about the spatial and temporal variability and characteristic scales of the state variable(s) being assimilated. The numerical model couples a three-dimensional finite element Richards equation solver for variably saturated porous media and a finite difference diffusion wave approximation based on digital elevation data for surface water dynamics. We describe the implementation of the data assimilation algorithm for the coupled model and report on the numerical and hydrological performance of the resulting assimilation scheme. Nudging is shown to be successful in improving the hydrological simulation results, and it introduces little computational cost, in terms of CPU and other numerical aspects of the model's behavior, in some cases even improving numerical performance compared to model runs without nudging. We also examine the sensitivity of the model to nudging term parameters including the spatio-temporal influence coefficients in the weighting functions. Overall the nudging algorithm is quite flexible, for instance in dealing with concurrent observation datasets, gridded or scattered data, and different state variables, and the implementation presented here can be readily extended to any of these features not already incorporated. Moreover the nudging code and tests can serve as a basis for implementation of more sophisticated data assimilation

  19. Coupling Cellular Automata Land Use Change with Distributed Hydrologic Models

    NASA Astrophysics Data System (ADS)

    Shu, L.; Duffy, C.

    2017-12-01

    There has been extensive research on LUC modeling with broad applications to simulating urban growth and changing demographic patterns across multiple scales. The importance of land conversion is a critical issue in watershed scale studies and is generally not treated in most watershed modeling approaches. In this study we apply spatially explicit hydrologic and landuse change models and the Conestoga Watershed in Lancaster County, Pennsylvania. The Penn State Integrated Hydrologic Model (PIHM) partitions the water balance in space and time over the urban catchment, the coupled Cellular Automata Land Use Change model (CALUC) dynamically simulates the evolution of land use classes based on physical measures associated with population change and land use demand factors. The CALUC model is based on iteratively applying discrete rules to each individual spatial cell. The essence the CA modeling involves calculation of the Transition Potential (TP) for conversion of a grid cell from one land use class to another. This potential includes five factors: random perturbation, suitability, accessibility, neighborhood effect, inertia effects and zonal factors. In spite of simplicity, this CALUC model has been shown to be very effective for simulating LUC leading to the emergence of complex spatial patterns. The components of TP are derived from present land use data for landuse reanalysis and for realistic future land use scenarios. For the CALUC we use early-settlement (circa 1790) initial land class values and final or present-day (2010) land classes to calibrate the model. CALUC- PIHM dynamically simulates the hydrologic response of conversion from pre-settlement to present landuse. The simulations highlight the capability and value of dynamic coupling of catchment hydrology with land use change over long time periods. Analysis of the simulation uses various metrics such as the distributed water balance, flow duration curves, etc. to show how deforestation, urbanization and

  20. Modelling hydrological responses of Nerbioi River Basin to Climate Change

    NASA Astrophysics Data System (ADS)

    Mendizabal, Maddalen; Moncho, Roberto; Chust, Guillem; Torp, Peter

    2010-05-01

    Future climate change will affect aquatic systems on various pathways. Regarding the hydrological cycle, which is a very important pathway, changes in hydrometeorological variables (air temperature, precipitation, evapotranspiration) in first order impact discharges. The fourth report assessment of the Intergovernmental Panel for Climate Change indicates there is evidence that the recent warming of the climate system would result in more frequent extreme precipitation events, increased winter flood likelihoods, increased and widespread melting of snow and ice, longer and more widespread droughts, and rising sea level. Available research and climate model outputs indicate a range of hydrological impacts with likely to very likely probabilities (67 to 99%). For example, it is likely that up to 20% of the world population will live in areas where river flood potential could increase by the 2080s. In Spain, within the Atlantic basin, the hydrological variability will increase in the future due to the intensification of the positive phase of the North Atlantic Oscillation (NAO) index. This might cause flood frequency decreases, but its magnitude does not decrease. The generation of flood, its duration and magnitude are closely linked to changes in winter precipitation. The climatic conditions and relief of the Iberian Peninsula favour the generation of floods. In Spain, floods had historically strong socio-economic impacts, with more than 1525 victims in the past five decades. This upward trend of hydrological variability is expected to remain in the coming decades (medium uncertainty) when the intensification of the positive phase of the NAO index (MMA, 2006) is considered. In order to adapt or minimize climate change impacts in water resources, it is necessary to use climate projections as well as hydrological modelling tools. The main objective of this paper is to evaluate and assess the hydrological response to climate changes in flow conditions in Nerbioi river

  1. The Hydrology of Malaria: Model Development and Application to a Sahelian Village

    NASA Astrophysics Data System (ADS)

    Bomblies, A.; Duchemin, J.; Eltahir, E. A.

    2008-12-01

    We present a coupled hydrology and entomology model for the mechanistic simulation of local-scale response of malaria transmission to hydrological and climatological determinants in semi-arid, desert fringe environments. The model is applied to the Sahel village of Banizoumbou, Niger, to predict interannual variability in malaria vector mosquito populations which lead to variations in malaria transmission. Using a high-resolution, small-scale distributed hydrology model that incorporates remotely-sensed data for land cover and topography, we simulate the formation and persistence of the pools constituting the primary breeding habitat of Anopheles gambiae s.l. mosquitoes, the principal regional malaria vector mosquitoes. An agent-based mosquito population model is coupled to the distributed hydrology model, with aquatic stage and adult stage components. For each individual adult mosquito, the model tracks attributes relevant to population dynamics and malaria transmission, which are updated as mosquitoes interact with their environment, humans, and animals. Weekly field observations were made in 2005 and 2006. The model reproduces mosquito population variability at seasonal and interannual time scales, and highlights individual pool persistence as a dominant control. Future developments to the presented model can be used in the evaluation of impacts of climate change on malaria, as well as the a priori evaluation of environmental management-based interventions.

  2. Effects of dynamic agricultural decision making in an ecohydrological model

    NASA Astrophysics Data System (ADS)

    Reichenau, T. G.; Krimly, T.; Schneider, K.

    2012-04-01

    Due to various interdependencies between the cycles of water, carbon, nitrogen, and energy the impacts of climate change on ecohydrological systems can only be investigated in an integrative way. Furthermore, the human intervention in the environmental processes makes the system even more complex. On the one hand human impact affects natural systems. On the other hand the changing natural systems have a feedback on human decision making. One of the most important examples for this kind of interaction can be found in the agricultural sector. Management dates (planting, fertilization, harvesting) are chosen based on meteorological conditions and yield expectations. A faster development of crops under a warmer climate causes shorter cropping seasons. The choice of crops depends on their profitability, which is mainly determined by market prizes, the agro-political framework, and the (climate dependent) crop yield. This study investigates these relations for the district Günzburg located in the Upper Danube catchment in southern Germany. The modeling system DANUBIA was used to perform dynamically coupled simulations of plant growth, surface and soil hydrological processes, soil nitrogen transformations, and agricultural decision making. The agro-economic model simulates decisions on management dates (based on meteorological conditions and the crops' development state), on fertilization intensities (based on yield expectations), and on choice of crops (based on profitability). The environmental models included in DANUBIA are to a great extent process based to enable its use in a climate change scenario context. Scenario model runs until 2058 were performed using an IPCC A1B forcing. In consecutive runs, dynamic crop management, dynamic crop selection, and a changing agro-political framework were activated. Effects of these model features on hydrological and ecological variables were analyzed separately by comparing the results to a model run with constant crop

  3. A Socio-hydrological Flood Model for the Elbe

    NASA Astrophysics Data System (ADS)

    Barendrecht, M.; Viglione, A.; Kreibich, H.; Vorogushyn, S.; Merz, B.; Bloeschl, G.

    2017-12-01

    Long-term feedbacks between humans and floods may lead to complex phenomena such as coping strategies, levee effects, call effects, adaptation effects, and poverty traps. Dynamic coupled human-flood models are a promising tool to represent such phenomena and the feedbacks leading to them. These socio-hydrological models may play an important role in integrated flood risk management when they are applied to real world case studies. They can help develop hypotheses about the phenomena that have been observed in the case study of interest, by describing the interactions between the social and hydrological variables as well as other relevant variables, such as economic, environmental, political or technical, that play a role in the system. We discuss the case of Dresden where the 2002 flood, which was preceded by a period without floods but was less severe, resulted in a higher damage than the 2013 flood, which was preceded by the 2002 flood and a couple of less severe floods. The lower damage in 2013 may be explained by the fact that society has become aware of the flood risk and has adapted to it. Developing and applying a socio-hydrological flood model to the case of Dresden can help discover whether it is possible that the lower damage is caused by an adaptation effect, or if there are other feedbacks that can explain the observed phenomenon.

  4. Digital Hydrologic Networks Supporting Applications Related to Spatially Referenced Regression Modeling

    USGS Publications Warehouse

    Brakebill, J.W.; Wolock, D.M.; Terziotti, S.E.

    2011-01-01

    Digital hydrologic networks depicting surface-water pathways and their associated drainage catchments provide a key component to hydrologic analysis and modeling. Collectively, they form common spatial units that can be used to frame the descriptions of aquatic and watershed processes. In addition, they provide the ability to simulate and route the movement of water and associated constituents throughout the landscape. Digital hydrologic networks have evolved from derivatives of mapping products to detailed, interconnected, spatially referenced networks of water pathways, drainage areas, and stream and watershed characteristics. These properties are important because they enhance the ability to spatially evaluate factors that affect the sources and transport of water-quality constituents at various scales. SPAtially Referenced Regressions On Watershed attributes (SPARROW), a process-based/statistical model, relies on a digital hydrologic network in order to establish relations between quantities of monitored contaminant flux, contaminant sources, and the associated physical characteristics affecting contaminant transport. Digital hydrologic networks modified from the River Reach File (RF1) and National Hydrography Dataset (NHD) geospatial datasets provided frameworks for SPARROW in six regions of the conterminous United States. In addition, characteristics of the modified RF1 were used to update estimates of mean-annual streamflow. This produced more current flow estimates for use in SPARROW modeling. ?? 2011 American Water Resources Association. This article is a U.S. Government work and is in the public domain in the USA.

  5. Reducing equifinality of hydrological models by integrating Functional Streamflow Disaggregation

    NASA Astrophysics Data System (ADS)

    Lüdtke, Stefan; Apel, Heiko; Nied, Manuela; Carl, Peter; Merz, Bruno

    2014-05-01

    A universal problem of the calibration of hydrological models is the equifinality of different parameter sets derived from the calibration of models against total runoff values. This is an intrinsic problem stemming from the quality of the calibration data and the simplified process representation by the model. However, discharge data contains additional information which can be extracted by signal processing methods. An analysis specifically developed for the disaggregation of runoff time series into flow components is the Functional Streamflow Disaggregation (FSD; Carl & Behrendt, 2008). This method is used in the calibration of an implementation of the hydrological model SWIM in a medium sized watershed in Thailand. FSD is applied to disaggregate the discharge time series into three flow components which are interpreted as base flow, inter-flow and surface runoff. In addition to total runoff, the model is calibrated against these three components in a modified GLUE analysis, with the aim to identify structural model deficiencies, assess the internal process representation and to tackle equifinality. We developed a model dependent (MDA) approach calibrating the model runoff components against the FSD components, and a model independent (MIA) approach comparing the FSD of the model results and the FSD of calibration data. The results indicate, that the decomposition provides valuable information for the calibration. Particularly MDA highlights and discards a number of standard GLUE behavioural models underestimating the contribution of soil water to river discharge. Both, MDA and MIA yield to a reduction of the parameter ranges by a factor up to 3 in comparison to standard GLUE. Based on these results, we conclude that the developed calibration approach is able to reduce the equifinality of hydrological model parameterizations. The effect on the uncertainty of the model predictions is strongest by applying MDA and shows only minor reductions for MIA. Besides

  6. Estimating the Uncertain Mathematical Structure of Hydrological Model via Bayesian Data Assimilation

    NASA Astrophysics Data System (ADS)

    Bulygina, N.; Gupta, H.; O'Donell, G.; Wheater, H.

    2008-12-01

    The structure of hydrological model at macro scale (e.g. watershed) is inherently uncertain due to many factors, including the lack of a robust hydrological theory at the macro scale. In this work, we assume that a suitable conceptual model for the hydrologic system has already been determined - i.e., the system boundaries have been specified, the important state variables and input and output fluxes to be included have been selected, and the major hydrological processes and geometries of their interconnections have been identified. The structural identification problem then is to specify the mathematical form of the relationships between the inputs, state variables and outputs, so that a computational model can be constructed for making simulations and/or predictions of system input-state-output behaviour. We show how Bayesian data assimilation can be used to merge both prior beliefs in the form of pre-assumed model equations with information derived from the data to construct a posterior model. The approach, entitled Bayesian Estimation of Structure (BESt), is used to estimate a hydrological model for a small basin in England, at hourly time scales, conditioned on the assumption of 3-dimensional state - soil moisture storage, fast and slow flow stores - conceptual model structure. Inputs to the system are precipitation and potential evapotranspiration, and outputs are actual evapotranspiration and streamflow discharge. Results show the difference between prior and posterior mathematical structures, as well as provide prediction confidence intervals that reflect three types of uncertainty: due to initial conditions, due to input and due to mathematical structure.

  7. Assessment of terrestrial water contributions to polar motion from GRACE and hydrological models

    NASA Astrophysics Data System (ADS)

    Jin, S. G.; Hassan, A. A.; Feng, G. P.

    2012-12-01

    The hydrological contribution to polar motion is a major challenge in explaining the observed geodetic residual of non-atmospheric and non-oceanic excitations since hydrological models have limited input of comprehensive global direct observations. Although global terrestrial water storage (TWS) estimated from the Gravity Recovery and Climate Experiment (GRACE) provides a new opportunity to study the hydrological excitation of polar motion, the GRACE gridded data are subject to the post-processing de-striping algorithm, spatial gridded mapping and filter smoothing effects as well as aliasing errors. In this paper, the hydrological contributions to polar motion are investigated and evaluated at seasonal and intra-seasonal time scales using the recovered degree-2 harmonic coefficients from all GRACE spherical harmonic coefficients and hydrological models data with the same filter smoothing and recovering methods, including the Global Land Data Assimilation Systems (GLDAS) model, Climate Prediction Center (CPC) model, the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis products and European Center for Medium-Range Weather Forecasts (ECMWF) operational model (opECMWF). It is shown that GRACE is better in explaining the geodetic residual of non-atmospheric and non-oceanic polar motion excitations at the annual period, while the models give worse estimates with a larger phase shift or amplitude bias. At the semi-annual period, the GRACE estimates are also generally closer to the geodetic residual, but with some biases in phase or amplitude due mainly to some aliasing errors at near semi-annual period from geophysical models. For periods less than 1-year, the hydrological models and GRACE are generally worse in explaining the intraseasonal polar motion excitations.

  8. On the effects of adaptive reservoir operating rules in hydrological physically-based models

    NASA Astrophysics Data System (ADS)

    Giudici, Federico; Anghileri, Daniela; Castelletti, Andrea; Burlando, Paolo

    2017-04-01

    Recent years have seen a significant increase of the human influence on the natural systems both at the global and local scale. Accurately modeling the human component and its interaction with the natural environment is key to characterize the real system dynamics and anticipate future potential changes to the hydrological regimes. Modern distributed, physically-based hydrological models are able to describe hydrological processes with high level of detail and high spatiotemporal resolution. Yet, they lack in sophistication for the behavior component and human decisions are usually described by very simplistic rules, which might underperform in reproducing the catchment dynamics. In the case of water reservoir operators, these simplistic rules usually consist of target-level rule curves, which represent the average historical level trajectory. Whilst these rules can reasonably reproduce the average seasonal water volume shifts due to the reservoirs' operation, they cannot properly represent peculiar conditions, which influence the actual reservoirs' operation, e.g., variations in energy price or water demand, dry or wet meteorological conditions. Moreover, target-level rule curves are not suitable to explore the water system response to climate and socio economic changing contexts, because they assume a business-as-usual operation. In this work, we quantitatively assess how the inclusion of adaptive reservoirs' operating rules into physically-based hydrological models contribute to the proper representation of the hydrological regime at the catchment scale. In particular, we contrast target-level rule curves and detailed optimization-based behavioral models. We, first, perform the comparison on past observational records, showing that target-level rule curves underperform in representing the hydrological regime over multiple time scales (e.g., weekly, seasonal, inter-annual). Then, we compare how future hydrological changes are affected by the two modeling

  9. Improving the realism of hydrologic model through multivariate parameter estimation

    NASA Astrophysics Data System (ADS)

    Rakovec, Oldrich; Kumar, Rohini; Attinger, Sabine; Samaniego, Luis

    2017-04-01

    Increased availability and quality of near real-time observations should improve understanding of predictive skills of hydrological models. Recent studies have shown the limited capability of river discharge data alone to adequately constrain different components of distributed model parameterizations. In this study, the GRACE satellite-based total water storage (TWS) anomaly is used to complement the discharge data with an aim to improve the fidelity of mesoscale hydrologic model (mHM) through multivariate parameter estimation. The study is conducted in 83 European basins covering a wide range of hydro-climatic regimes. The model parameterization complemented with the TWS anomalies leads to statistically significant improvements in (1) discharge simulations during low-flow period, and (2) evapotranspiration estimates which are evaluated against independent (FLUXNET) data. Overall, there is no significant deterioration in model performance for the discharge simulations when complemented by information from the TWS anomalies. However, considerable changes in the partitioning of precipitation into runoff components are noticed by in-/exclusion of TWS during the parameter estimation. A cross-validation test carried out to assess the transferability and robustness of the calibrated parameters to other locations further confirms the benefit of complementary TWS data. In particular, the evapotranspiration estimates show more robust performance when TWS data are incorporated during the parameter estimation, in comparison with the benchmark model constrained against discharge only. This study highlights the value for incorporating multiple data sources during parameter estimation to improve the overall realism of hydrologic model and its applications over large domains. Rakovec, O., Kumar, R., Attinger, S. and Samaniego, L. (2016): Improving the realism of hydrologic model functioning through multivariate parameter estimation. Water Resour. Res., 52, http://dx.doi.org/10

  10. Predicting the natural flow regime: Models for assessing hydrological alteration in streams

    USGS Publications Warehouse

    Carlisle, D.M.; Falcone, J.; Wolock, D.M.; Meador, M.R.; Norris, R.H.

    2009-01-01

    Understanding the extent to which natural streamflow characteristics have been altered is an important consideration for ecological assessments of streams. Assessing hydrologic condition requires that we quantify the attributes of the flow regime that would be expected in the absence of anthropogenic modifications. The objective of this study was to evaluate whether selected streamflow characteristics could be predicted at regional and national scales using geospatial data. Long-term, gaged river basins distributed throughout the contiguous US that had streamflow characteristics representing least disturbed or near pristine conditions were identified. Thirteen metrics of the magnitude, frequency, duration, timing and rate of change of streamflow were calculated using a 20-50 year period of record for each site. We used random forests (RF), a robust statistical modelling approach, to develop models that predicted the value for each streamflow metric using natural watershed characteristics. We compared the performance (i.e. bias and precision) of national- and regional-scale predictive models to that of models based on landscape classifications, including major river basins, ecoregions and hydrologic landscape regions (HLR). For all hydrologic metrics, landscape stratification models produced estimates that were less biased and more precise than a null model that accounted for no natural variability. Predictive models at the national and regional scale performed equally well, and substantially improved predictions of all hydrologic metrics relative to landscape stratification models. Prediction error rates ranged from 15 to 40%, but were 25% for most metrics. We selected three gaged, non-reference sites to illustrate how predictive models could be used to assess hydrologic condition. These examples show how the models accurately estimate predisturbance conditions and are sensitive to changes in streamflow variability associated with long-term land-use change. We also

  11. Evaluation of various agro-wastes for traditional black soap production.

    PubMed

    Taiwo, O E; Osinowo, F A

    2001-08-01

    The agricultural wastes, cocoa-pod husks, palm-bunch waste, sorghum chaff and groundnut shells, which are normally thrown away have been used in the production of black soap. Unlike other soaps which are made from oils and chemicals, black soap is made from oils and agro-wastes ashes. Chemical analysis indicated that the liquid extract from the ashes of the different agro-wastes used contained various amounts of potassium and sodium compounds. The most common ingredient in the agro-wastes was potassium carbonate. The amount of potassium carbonate was 56.73 +/- 0.16% in cocoa-pod ash, 43.15 +/- 0.13% in palm-bunch ash, 16.65 +/- 0.05% in groundnut shell ash and 12.40 +/- 0.08% in sorghum chaff ash. Soaps made from the agro-wastes ashes had excellent solubility, consistency, cleansing and lathering abilities.

  12. Regional Approach for Managing for Resilience Linking Ecosystem Services and Livelihood Strategies for Agro-Pastoral Communities in the Mongolian Steppe Ecosystem

    NASA Astrophysics Data System (ADS)

    Ojima, D. S.; Togtohyn, C.; Qi, J.; Galvin, K.

    2011-12-01

    Dramatic changes due to climate and land use dynamics in the Mongolian Plateau are affecting ecosystem services and agro-pastoral livelihoods in Mongolia and China. Recently, evaluation of pastoral systems, where humans depend on livestock and grassland ecosystem services, have demonstrated the vulnerability of the social-ecological system to climate change. Current social-ecological changes in ecosystem services are affecting land productivity and carrying capacity, land-atmosphere interactions, water resources, and livelihood strategies. Regional dust events, changes in hydrological cycle, and land use changes contribute to changing interactions between ecosystem and landscape processes which then affect social-ecological systems. The general trend involves greater intensification of resource exploitation at the expense of traditional patterns of extensive range utilization. Thus we expect climate-land use-land cover relationships to be crucially modified by the socio-economic forces. The analysis incorporates information of the socio-economic transitions taking place in the region which affect land-use, food security, and ecosystem dynamics. The region of study extends from the Mongolian plateau in Mongolia and China to the fertile northeast China plain. Sustainability of agro-pastoral systems in the region needs to integrate the impact of climate change on ecosystem services with socio-economic changes shaping the livelihood strategies of pastoral systems in the region. Adaptation strategies which incorporate landscape management provides a potential framework to link ecosystem services across space and time more effectively to meet the needs of agro-pastoral land use, herd quality, and herder's living standards. Under appropriate adaptation strategies agro-pastoralists will have the opportunity to utilize seasonal resources and enhance their ability to process and manufacture products from the available ecosystem services in these dynamic social

  13. Eco-hydrologic model cascades: Simulating land use and climate change impacts on hydrology, hydraulics and habitats for fish and macroinvertebrates.

    PubMed

    Guse, Björn; Kail, Jochem; Radinger, Johannes; Schröder, Maria; Kiesel, Jens; Hering, Daniel; Wolter, Christian; Fohrer, Nicola

    2015-11-15

    Climate and land use changes affect the hydro- and biosphere at different spatial scales. These changes alter hydrological processes at the catchment scale, which impact hydrodynamics and habitat conditions for biota at the river reach scale. In order to investigate the impact of large-scale changes on biota, a cascade of models at different scales is required. Using scenario simulations, the impact of climate and land use change can be compared along the model cascade. Such a cascade of consecutively coupled models was applied in this study. Discharge and water quality are predicted with a hydrological model at the catchment scale. The hydraulic flow conditions are predicted by hydrodynamic models. The habitat suitability under these hydraulic and water quality conditions is assessed based on habitat models for fish and macroinvertebrates. This modelling cascade was applied to predict and compare the impacts of climate- and land use changes at different scales to finally assess their effects on fish and macroinvertebrates. Model simulations revealed that magnitude and direction of change differed along the modelling cascade. Whilst the hydrological model predicted a relevant decrease of discharge due to climate change, the hydraulic conditions changed less. Generally, the habitat suitability for fish decreased but this was strongly species-specific and suitability even increased for some species. In contrast to climate change, the effect of land use change on discharge was negligible. However, land use change had a stronger impact on the modelled nitrate concentrations affecting the abundances of macroinvertebrates. The scenario simulations for the two organism groups illustrated that direction and intensity of changes in habitat suitability are highly species-dependent. Thus, a joined model analysis of different organism groups combined with the results of hydrological and hydrodynamic models is recommended to assess the impact of climate and land use changes on

  14. Representing Northern Peatland Hydrology and Biogeochemistry with ALM Land Surface Model

    NASA Astrophysics Data System (ADS)

    Shi, X.; Ricciuto, D. M.; Thornton, P. E.; Hanson, P. J.; Xu, X.; Mao, J.; Warren, J.; Yuan, F.; Norby, R. J.; Sebestyen, S.; Griffiths, N.; Weston, D. J.; Walker, A.

    2017-12-01

    Northern peatlands are likely to be important in future carbon cycle-climate feedbacks due to their large carbon pool and vulnerability to hydrological change. Predictive understanding of northern peatland hydrology is a necessary precursor to understanding the fate of massive carbon stores in these systems under the influence of present and future climate change. Current models have begun to address microtopographic controls on peatland hydrology, but none have included a prognostic calculation of peatland water table depth for a vegetated wetland, independent of prescribed regional water tables. Firstly, we introduce a new configuration of the land model (ALM) of Accelerated Climate model for Energy (ACME), which includes a fully prognostic water table calculation for a vegetated peatland. Secondly, we couple our new hydrology treatment with vertically structured soil organic matter pool, and the addition of components from methane biogeochemistry. Thirdly, we introduce a new PFT for mosses and implement the water content dynamics and physiology of mosses. We inform and test our model based on SPRUCE experiment to get the reasonable results for the seasonal dynamics water table depths, water content dynamics and physiology of mosses, and correct soil carbon profiles. Then, we use our new model structure to test the how the water table depth and CH4 emission will respond to elevated CO2 and different warming scenarios.

  15. Prediction of Hydrologic Characteristics for Ungauged Catchments to Support Hydroecological Modeling

    NASA Astrophysics Data System (ADS)

    Bond, Nick R.; Kennard, Mark J.

    2017-11-01

    Hydrologic variability is a fundamental driver of ecological processes and species distribution patterns within river systems, yet the paucity of gauges in many catchments means that streamflow data are often unavailable for ecological survey sites. Filling this data gap is an important challenge in hydroecological research. To address this gap, we first test the ability to spatially extrapolate hydrologic metrics calculated from gauged streamflow data to ungauged sites as a function of stream distance and catchment area. Second, we examine the ability of statistical models to predict flow regime metrics based on climate and catchment physiographic variables. Our assessment focused on Australia's largest catchment, the Murray-Darling Basin (MDB). We found that hydrologic metrics were predictable only between sites within ˜25 km of one another. Beyond this, correlations between sites declined quickly. We found less than 40% of fish survey sites from a recent basin-wide monitoring program (n = 777 sites) to fall within this 25 km range, thereby greatly limiting the ability to utilize gauge data for direct spatial transposition of hydrologic metrics to biological survey sites. In contrast, statistical model-based transposition proved effective in predicting ecologically relevant aspects of the flow regime (including metrics describing central tendency, high- and low-flows intermittency, seasonality, and variability) across the entire gauge network (median R2 ˜ 0.54, range 0.39-0.94). Modeled hydrologic metrics thus offer a useful alternative to empirical data when examining biological survey data from ungauged sites. More widespread use of these statistical tools and modeled metrics could expand our understanding of flow-ecology relationships.

  16. Sensitivity of Hydrologic Response to Climate Model Debiasing Procedures

    NASA Astrophysics Data System (ADS)

    Channell, K.; Gronewold, A.; Rood, R. B.; Xiao, C.; Lofgren, B. M.; Hunter, T.

    2017-12-01

    Climate change is already having a profound impact on the global hydrologic cycle. In the Laurentian Great Lakes, changes in long-term evaporation and precipitation can lead to rapid water level fluctuations in the lakes, as evidenced by unprecedented change in water levels seen in the last two decades. These fluctuations often have an adverse impact on the region's human, environmental, and economic well-being, making accurate long-term water level projections invaluable to regional water resources management planning. Here we use hydrological components from a downscaled climate model (GFDL-CM3/WRF), to obtain future water supplies for the Great Lakes. We then apply a suite of bias correction procedures before propagating these water supplies through a routing model to produce lake water levels. Results using conventional bias correction methods suggest that water levels will decline by several feet in the coming century. However, methods that reflect the seasonal water cycle and explicitly debias individual hydrological components (overlake precipitation, overlake evaporation, runoff) imply that future water levels may be closer to their historical average. This discrepancy between debiased results indicates that water level forecasts are highly influenced by the bias correction method, a source of sensitivity that is commonly overlooked. Debiasing, however, does not remedy misrepresentation of the underlying physical processes in the climate model that produce these biases and contribute uncertainty to the hydrological projections. This uncertainty coupled with the differences in water level forecasts from varying bias correction methods are important for water management and long term planning in the Great Lakes region.

  17. Hydrologic Modeling in the Kenai River Watershed using Event Based Calibration

    NASA Astrophysics Data System (ADS)

    Wells, B.; Toniolo, H. A.; Stuefer, S. L.

    2015-12-01

    Understanding hydrologic changes is key for preparing for possible future scenarios. On the Kenai Peninsula in Alaska the yearly salmon runs provide a valuable stimulus to the economy. It is the focus of a large commercial fishing fleet, but also a prime tourist attraction. Modeling of anadromous waters provides a tool that assists in the prediction of future salmon run size. Beaver Creek, in Kenai, Alaska, is a lowlands stream that has been modeled using the Army Corps of Engineers event based modeling package HEC-HMS. With the use of historic precipitation and discharge data, the model was calibrated to observed discharge values. The hydrologic parameters were measured in the field or calculated, while soil parameters were estimated and adjusted during the calibration. With the calibrated parameter for HEC-HMS, discharge estimates can be used by other researches studying the area and help guide communities and officials to make better-educated decisions regarding the changing hydrology in the area and the tied economic drivers.

  18. Coupled land surface/hydrologic/atmospheric models

    NASA Technical Reports Server (NTRS)

    Pielke, Roger; Steyaert, Lou; Arritt, Ray; Lahtakia, Mercedes; Smith, Chris; Ziegler, Conrad; Soong, Su Tzai; Avissar, Roni; Wetzel, Peter; Sellers, Piers

    1993-01-01

    The topics covered include the following: prototype land cover characteristics data base for the conterminous United States; surface evapotranspiration effects on cumulus convection and implications for mesoscale models; the use of complex treatment of surface hydrology and thermodynamics within a mesoscale model and some related issues; initialization of soil-water content for regional-scale atmospheric prediction models; impact of surface properties on dryline and MCS evolution; a numerical simulation of heavy precipitation over the complex topography of California; representing mesoscale fluxes induced by landscape discontinuities in global climate models; emphasizing the role of subgrid-scale heterogeneity in surface-air interaction; and problems with modeling and measuring biosphere-atmosphere exchanges of energy, water, and carbon on large scales.

  19. Modelling hydrologic and hydrodynamic processes in basins with large semi-arid wetlands

    NASA Astrophysics Data System (ADS)

    Fleischmann, Ayan; Siqueira, Vinícius; Paris, Adrien; Collischonn, Walter; Paiva, Rodrigo; Pontes, Paulo; Crétaux, Jean-François; Bergé-Nguyen, Muriel; Biancamaria, Sylvain; Gosset, Marielle; Calmant, Stephane; Tanimoun, Bachir

    2018-06-01

    Hydrological and hydrodynamic models are core tools for simulation of large basins and complex river systems associated to wetlands. Recent studies have pointed towards the importance of online coupling strategies, representing feedbacks between floodplain inundation and vertical hydrology. Especially across semi-arid regions, soil-floodplain interactions can be strong. In this study, we included a two-way coupling scheme in a large scale hydrological-hydrodynamic model (MGB) and tested different model structures, in order to assess which processes are important to be simulated in large semi-arid wetlands and how these processes interact with water budget components. To demonstrate benefits from this coupling over a validation case, the model was applied to the Upper Niger River basin encompassing the Niger Inner Delta, a vast semi-arid wetland in the Sahel Desert. Simulation was carried out from 1999 to 2014 with daily TMPA 3B42 precipitation as forcing, using both in-situ and remotely sensed data for calibration and validation. Model outputs were in good agreement with discharge and water levels at stations both upstream and downstream of the Inner Delta (Nash-Sutcliffe Efficiency (NSE) >0.6 for most gauges), as well as for flooded areas within the Delta region (NSE = 0.6; r = 0.85). Model estimates of annual water losses across the Delta varied between 20.1 and 30.6 km3/yr, while annual evapotranspiration ranged between 760 mm/yr and 1130 mm/yr. Evaluation of model structure indicated that representation of both floodplain channels hydrodynamics (storage, bifurcations, lateral connections) and vertical hydrological processes (floodplain water infiltration into soil column; evapotranspiration from soil and vegetation and evaporation of open water) are necessary to correctly simulate flood wave attenuation and evapotranspiration along the basin. Two-way coupled models are necessary to better understand processes in large semi-arid wetlands. Finally, such coupled

  20. A soil-specific agro-ecological strategy for sustainable production in Argentina farm fields

    NASA Astrophysics Data System (ADS)

    Zamora, Martin; Barbera, Agustin; Castro-Franco, Mauricio; Hansson, Alejandro; Domenech, Marisa

    2017-04-01

    The continuous increment of frequencies and doses of pesticides, glyphosate and fertilizers, the deterioration of the structure, biotic balance and fertility of soils and the ground water pollution are characteristics of the current Argentinian agricultural model. In this context, agro-ecological innovations are needed to develop a real sustainable agriculture, enhancing the food supply. Precision agriculture technologies can strengthen the expansion of agro-ecological farming in experimental farm fields. The aim of this study was to propose a soil-specific agro-ecological strategy for sustainable production at field scale focused on the use of soil sensors and digital soil mapping techniques. This strategy has been developed in 15 hectares transition agro-ecological farm field, located at Barrow Experimental Station (Lat:-38.322844, Lon:-60.25572) Argentina. The strategy included five steps: (i) to measure apparent electrical conductivity (ECa) and elevation within agro-ecological farm field; (ii) to apply a clustering method using MULTISPATI-PCA algorithm to delimitate three soil-specific zones (Z1, Z2 and Z3); (iii) to determine three soil sampling points by zone, using conditioned Latin hypercube method, in addition to elevation and ECa as auxiliary information; (iv) to collect soil samples at 2-10 cm depth in each point and to determine in laboratory: total organic carbon content (TOC), cation-exchange capacity (CEC), pH and phosphorus availability (P-Bray). In addition, soil bulk density (SBD) was measured at 0-20 cm depth. Finally, (v) according to each soil-specific zone, a management strategy was recommended. Important differences in soil properties among zones could suggest that the strategy developed was able to apply an agro ecological soil-specific practice management. pH and P-Bray were significantly (p<0.05) higher in Z1 than in Z2 and Z3. TOC did not show significant difference among zones, but it was higher in Z2. CEC was significantly (p<0

  1. Effects of different regional climate model resolution and forcing scales on projected hydrologic changes

    NASA Astrophysics Data System (ADS)

    Mendoza, Pablo A.; Mizukami, Naoki; Ikeda, Kyoko; Clark, Martyn P.; Gutmann, Ethan D.; Arnold, Jeffrey R.; Brekke, Levi D.; Rajagopalan, Balaji

    2016-10-01

    We examine the effects of regional climate model (RCM) horizontal resolution and forcing scaling (i.e., spatial aggregation of meteorological datasets) on the portrayal of climate change impacts. Specifically, we assess how the above decisions affect: (i) historical simulation of signature measures of hydrologic behavior, and (ii) projected changes in terms of annual water balance and hydrologic signature measures. To this end, we conduct our study in three catchments located in the headwaters of the Colorado River basin. Meteorological forcings for current and a future climate projection are obtained at three spatial resolutions (4-, 12- and 36-km) from dynamical downscaling with the Weather Research and Forecasting (WRF) regional climate model, and hydrologic changes are computed using four different hydrologic model structures. These projected changes are compared to those obtained from running hydrologic simulations with current and future 4-km WRF climate outputs re-scaled to 12- and 36-km. The results show that the horizontal resolution of WRF simulations heavily affects basin-averaged precipitation amounts, propagating into large differences in simulated signature measures across model structures. The implications of re-scaled forcing datasets on historical performance were primarily observed on simulated runoff seasonality. We also found that the effects of WRF grid resolution on projected changes in mean annual runoff and evapotranspiration may be larger than the effects of hydrologic model choice, which surpasses the effects from re-scaled forcings. Scaling effects on projected variations in hydrologic signature measures were found to be generally smaller than those coming from WRF resolution; however, forcing aggregation in many cases reversed the direction of projected changes in hydrologic behavior.

  2. Strategies for Large Scale Implementation of a Multiscale, Multiprocess Integrated Hydrologic Model

    NASA Astrophysics Data System (ADS)

    Kumar, M.; Duffy, C.

    2006-05-01

    Distributed models simulate hydrologic state variables in space and time while taking into account the heterogeneities in terrain, surface, subsurface properties and meteorological forcings. Computational cost and complexity associated with these model increases with its tendency to accurately simulate the large number of interacting physical processes at fine spatio-temporal resolution in a large basin. A hydrologic model run on a coarse spatial discretization of the watershed with limited number of physical processes needs lesser computational load. But this negatively affects the accuracy of model results and restricts physical realization of the problem. So it is imperative to have an integrated modeling strategy (a) which can be universally applied at various scales in order to study the tradeoffs between computational complexity (determined by spatio- temporal resolution), accuracy and predictive uncertainty in relation to various approximations of physical processes (b) which can be applied at adaptively different spatial scales in the same domain by taking into account the local heterogeneity of topography and hydrogeologic variables c) which is flexible enough to incorporate different number and approximation of process equations depending on model purpose and computational constraint. An efficient implementation of this strategy becomes all the more important for Great Salt Lake river basin which is relatively large (~89000 sq. km) and complex in terms of hydrologic and geomorphic conditions. Also the types and the time scales of hydrologic processes which are dominant in different parts of basin are different. Part of snow melt runoff generated in the Uinta Mountains infiltrates and contributes as base flow to the Great Salt Lake over a time scale of decades to centuries. The adaptive strategy helps capture the steep topographic and climatic gradient along the Wasatch front. Here we present the aforesaid modeling strategy along with an associated

  3. One multi-media environmental system with linkage between meteorology/ hydrology/ air quality models and water quality model

    NASA Astrophysics Data System (ADS)

    Tang, C.; Lynch, J. A.; Dennis, R. L.

    2016-12-01

    The biogeochemical processing of nitrogen and associated pollutants is driven by meteorological and hydrological processes in conjunction with pollutant loading. There are feedbacks between meteorology and hydrology that will be affected by land-use change and climate change. Changes in meteorology will affect pollutant deposition. It is important to account for those feedbacks and produce internally consistent simulations of meteorology, hydrology, and pollutant loading to drive the (watershed/water quality) biogeochemical models. In this study, the ecological response to emission reductions in streams in the Potomac watershed was evaluated. Firstly, we simulated the deposition by using the fully coupled Weather Research & Forecasting (WRF) model and the Community Multiscale Air Quality (CAMQ) model; secondly, we created the hydrological data by the offline linked Variable Infiltration Capacity (VIC) model and the WRF model. Lastly, we investigated the water quality by one comprehensive/environment model, namely the linkage of CMAQ, WRF, VIC and the Model of Acidification of Groundwater In Catchment (MAGIC) model from 2002 to 2010.The simulated results (such as NO3, SO4, and SBC) fit well to the observed values. The linkage provides a generally accurate, well-tested tool for evaluating sensitivities to varying meteorology and environmental changes on acidification and other biogeochemical processes, with capability to comprehensively explore strategic policy and management design.

  4. Inter-model variability in hydrological extremes projections for Amazonian sub-basins

    NASA Astrophysics Data System (ADS)

    Andres Rodriguez, Daniel; Garofolo, Lucas; Lázaro de Siqueira Júnior, José; Samprogna Mohor, Guilherme; Tomasella, Javier

    2014-05-01

    Irreducible uncertainties due to knowledge's limitations, chaotic nature of climate system and human decision-making process drive uncertainties in Climate Change projections. Such uncertainties affect the impact studies, mainly when associated to extreme events, and difficult the decision-making process aimed at mitigation and adaptation. However, these uncertainties allow the possibility to develop exploratory analyses on system's vulnerability to different sceneries. The use of different climate model's projections allows to aboard uncertainties issues allowing the use of multiple runs to explore a wide range of potential impacts and its implications for potential vulnerabilities. Statistical approaches for analyses of extreme values are usually based on stationarity assumptions. However, nonstationarity is relevant at the time scales considered for extreme value analyses and could have great implications in dynamic complex systems, mainly under climate change transformations. Because this, it is required to consider the nonstationarity in the statistical distribution parameters. We carried out a study of the dispersion in hydrological extremes projections using climate change projections from several climate models to feed the Distributed Hydrological Model of the National Institute for Spatial Research, MHD-INPE, applied in Amazonian sub-basins. This model is a large-scale hydrological model that uses a TopModel approach to solve runoff generation processes at the grid-cell scale. MHD-INPE model was calibrated for 1970-1990 using observed meteorological data and comparing observed and simulated discharges by using several performance coeficients. Hydrological Model integrations were performed for present historical time (1970-1990) and for future period (2010-2100). Because climate models simulate the variability of the climate system in statistical terms rather than reproduce the historical behavior of climate variables, the performances of the model's runs

  5. Multi-model ensemble hydrological simulation using a BP Neural Network for the upper Yalongjiang River Basin, China

    NASA Astrophysics Data System (ADS)

    Li, Zhanjie; Yu, Jingshan; Xu, Xinyi; Sun, Wenchao; Pang, Bo; Yue, Jiajia

    2018-06-01

    Hydrological models are important and effective tools for detecting complex hydrological processes. Different models have different strengths when capturing the various aspects of hydrological processes. Relying on a single model usually leads to simulation uncertainties. Ensemble approaches, based on multi-model hydrological simulations, can improve application performance over single models. In this study, the upper Yalongjiang River Basin was selected for a case study. Three commonly used hydrological models (SWAT, VIC, and BTOPMC) were selected and used for independent simulations with the same input and initial values. Then, the BP neural network method was employed to combine the results from the three models. The results show that the accuracy of BP ensemble simulation is better than that of the single models.

  6. Parameter Set Cloning Based on Catchment Similarity for Large-scale Hydrologic Modeling

    NASA Astrophysics Data System (ADS)

    Liu, Z.; Kaheil, Y.; McCollum, J.

    2016-12-01

    Parameter calibration is a crucial step to ensure the accuracy of hydrological models. However, streamflow gauges are not available everywhere for calibrating a large-scale hydrologic model globally. Thus, assigning parameters appropriately for regions where the calibration cannot be performed directly has been a challenge for large-scale hydrologic modeling. Here we propose a method to estimate the model parameters in ungauged regions based on the values obtained through calibration in areas where gauge observations are available. This parameter set cloning is performed according to a catchment similarity index, a weighted sum index based on four catchment characteristic attributes. These attributes are IPCC Climate Zone, Soil Texture, Land Cover, and Topographic Index. The catchments with calibrated parameter values are donors, while the uncalibrated catchments are candidates. Catchment characteristic analyses are first conducted for both donors and candidates. For each attribute, we compute a characteristic distance between donors and candidates. Next, for each candidate, weights are assigned to the four attributes such that higher weights are given to properties that are more directly linked to the hydrologic dominant processes. This will ensure that the parameter set cloning emphasizes the dominant hydrologic process in the region where the candidate is located. The catchment similarity index for each donor - candidate couple is then created as the sum of the weighted distance of the four properties. Finally, parameters are assigned to each candidate from the donor that is "most similar" (i.e. with the shortest weighted distance sum). For validation, we applied the proposed method to catchments where gauge observations are available, and compared simulated streamflows using the parameters cloned by other catchments to the results obtained by calibrating the hydrologic model directly using gauge data. The comparison shows good agreement between the two models

  7. An intermediate-scale model for thermal hydrology in low-relief permafrost-affected landscapes

    DOE PAGES

    Jan, Ahmad; Coon, Ethan T.; Painter, Scott L.; ...

    2017-07-10

    Integrated surface/subsurface models for simulating the thermal hydrology of permafrost-affected regions in a warming climate have recently become available, but computational demands of those new process-rich simu- lation tools have thus far limited their applications to one-dimensional or small two-dimensional simulations. We present a mixed-dimensional model structure for efficiently simulating surface/subsurface thermal hydrology in low-relief permafrost regions at watershed scales. The approach replaces a full three-dimensional system with a two-dimensional overland thermal hydrology system and a family of one-dimensional vertical columns, where each column represents a fully coupled surface/subsurface thermal hydrology system without lateral flow. The system is then operatormore » split, sequentially updating the overland flow system without sources and the one-dimensional columns without lateral flows. We show that the app- roach is highly scalable, supports subcycling of different processes, and compares well with the corresponding fully three-dimensional representation at significantly less computational cost. Those advances enable recently developed representations of freezing soil physics to be coupled with thermal overland flow and surface energy balance at scales of 100s of meters. Furthermore developed and demonstrated for permafrost thermal hydrology, the mixed-dimensional model structure is applicable to integrated surface/subsurface thermal hydrology in general.« less

  8. Quantification of effective plant rooting depth: advancing global hydrological modelling

    NASA Astrophysics Data System (ADS)

    Yang, Y.; Donohue, R. J.; McVicar, T.

    2017-12-01

    Plant rooting depth (Zr) is a key parameter in hydrological and biogeochemical models, yet the global spatial distribution of Zr is largely unknown due to the difficulties in its direct measurement. Moreover, Zr observations are usually only representative of a single plant or several plants, which can differ greatly from the effective Zr over a modelling unit (e.g., catchment or grid-box). Here, we provide a global parameterization of an analytical Zr model that balances the marginal carbon cost and benefit of deeper roots, and produce a climatological (i.e., 1982-2010 average) global Zr map. To test the Zr estimates, we apply the estimated Zr in a highly transparent hydrological model (i.e., the Budyko-Choudhury-Porporato (BCP) model) to estimate mean annual actual evapotranspiration (E) across the globe. We then compare the estimated E with both water balance-based E observations at 32 major catchments and satellite grid-box retrievals across the globe. Our results show that the BCP model, when implemented with Zr estimated herein, optimally reproduced the spatial pattern of E at both scales and provides improved model outputs when compared to BCP model results from two already existing global Zr datasets. These results suggest that our Zr estimates can be effectively used in state-of-the-art hydrological models, and potentially biogeochemical models, where the determination of Zr currently largely relies on biome type-based look-up tables.

  9. Automatic Calibration of a Semi-Distributed Hydrologic Model Using Particle Swarm Optimization

    NASA Astrophysics Data System (ADS)

    Bekele, E. G.; Nicklow, J. W.

    2005-12-01

    Hydrologic simulation models need to be calibrated and validated before using them for operational predictions. Spatially-distributed hydrologic models generally have a large number of parameters to capture the various physical characteristics of a hydrologic system. Manual calibration of such models is a very tedious and daunting task, and its success depends on the subjective assessment of a particular modeler, which includes knowledge of the basic approaches and interactions in the model. In order to alleviate these shortcomings, an automatic calibration model, which employs an evolutionary optimization technique known as Particle Swarm Optimizer (PSO) for parameter estimation, is developed. PSO is a heuristic search algorithm that is inspired by social behavior of bird flocking or fish schooling. The newly-developed calibration model is integrated to the U.S. Department of Agriculture's Soil and Water Assessment Tool (SWAT). SWAT is a physically-based, semi-distributed hydrologic model that was developed to predict the long term impacts of land management practices on water, sediment and agricultural chemical yields in large complex watersheds with varying soils, land use, and management conditions. SWAT was calibrated for streamflow and sediment concentration. The calibration process involves parameter specification, whereby sensitive model parameters are identified, and parameter estimation. In order to reduce the number of parameters to be calibrated, parameterization was performed. The methodology is applied to a demonstration watershed known as Big Creek, which is located in southern Illinois. Application results show the effectiveness of the approach and model predictions are significantly improved.

  10. Modeling Hydrological Processes in New Mexico-Texas-Mexico Border Region

    NASA Astrophysics Data System (ADS)

    Samimi, M.; Jahan, N. T.; Mirchi, A.

    2017-12-01

    Efficient allocation of limited water resources to competing use sectors is becoming increasingly critical for water-scarce regions. Understanding natural and anthropogenic processes affecting hydrological processes is key for efficient water management. We used Soil and Water Assessment Tool (SWAT) to model governing hydrologic processes in New Mexico-Texas-Mexico border region. Our study area includes the Elephant Butte Irrigation District (EBID), which manages water resources to support irrigated agriculture. The region is facing water resources challenges associated with chronic water scarcity, over-allocation, diminishing water supply, and growing water demand. Agricultural activities rely on conjunctive use of Rio Grande River water supply and groundwater withdrawal. The model is calibrated and validated under baseline conditions in the arid and semi-arid climate in order to evaluate potential impacts of climate change on the agricultural sector and regional water availability. We highlight the importance of calibrating the crop growth parameters, evapotranspiration, and groundwater recharge to provide a realistic representation of the hydrological processes and water availability in the region. Furthermore, limitations of the model and its utility to inform stakeholders will be discussed.

  11. A Smallholder Socio-hydrological Modelling Framework

    NASA Astrophysics Data System (ADS)

    Pande, S.; Savenije, H.; Rathore, P.

    2014-12-01

    Small holders are farmers who own less than 2 ha of farmland. They often have low productivity and thus remain at subsistence level. A fact that nearly 80% of Indian farmers are smallholders, who merely own a third of total farmlands and belong to the poorest quartile, but produce nearly 40% of countries foodgrains underlines the importance of understanding the socio-hydrology of a small holder. We present a framework to understand the socio-hydrological system dynamics of a small holder. It couples the dynamics of 6 main variables that are most relevant at the scale of a small holder: local storage (soil moisture and other water storage), capital, knowledge, livestock production, soil fertility and grass biomass production. The model incorporates rule-based adaptation mechanisms (for example: adjusting expenditures on food and fertilizers, selling livestocks etc.) of small holders when they face adverse socio-hydrological conditions, such as low annual rainfall, higher intra-annual variability in rainfall or variability in agricultural prices. It allows us to study sustainability of small holder farming systems under various settings. We apply the framework to understand the socio-hydrology of small holders in Aurangabad, Maharashtra, India. This district has witnessed suicides of many sugarcane farmers who could not extricate themselves out of the debt trap. These farmers lack irrigation and are susceptible to fluctuating sugar prices and intra-annual hydroclimatic variability. This presentation discusses two aspects in particular: whether government interventions to absolve the debt of farmers is enough and what is the value of investing in local storages that can buffer intra-annual variability in rainfall and strengthening the safety-nets either by creating opportunities for alternative sources of income or by crop diversification.

  12. IASMHYN: A web tool for mapping Soil Water Budget and agro-hydrological assessment trough the integration of monitoring and remote sensing data

    NASA Astrophysics Data System (ADS)

    Bagli, Stefano; Pistocchi, Alberto; Mazzoli, Paolo; Borga, Marco; Bertoldi, Giacomo; Brenner, Johannes; Luzzi, Valerio

    2016-04-01

    Climate change, increasing pressure on farmland to satisfy the growing demand, and need to ensure environmental quality for agriculture in order to be competitive require an increasing capacity of water management. In this context, web-based for forecasting and monitoring the hydrological conditions of topsoil can be an effective means to save water, maximize crop protection and reduce soil loss and the leaching of pollutants. Such tools need to be targeted to the users and be accessible in a simple way in order to allow adequate take up in the practice. IASMHYN "Improved management of Agricultural Systems by Monitoring and Hydrological evaluation" is a web mapping service designed to provide and update on a daily basis the main water budget variables for farmland management. A beta version of the tool is available at www.gecosistema.com/iasmhyn . IASMHYN is an instrument for "second level monitoring" that takes into account accurate hydro-meteorological information's from ground stations and remote sensing sources, and turns them into practically usable decision variables for precision farming, making use of geostatistical analysis and hydrological models The main routines embedded in IASMYHN exclusively use open source libraries (R packages and Python), to perform following operations: (1) Automatic acquisition of observed data, both from ground stations and remote sensing, concerning precipitation (RADAR) and temperature (MODIS-LST) available from various sources; (2) Interpolation of acquisitions through regression kriging in order to spatially map the meteorological data; (3) Run of hydrological models to obtain spatial information of hydrological soil variables of immediate interest in agriculture. The real time results that are produced are available trough a web interface and provide the user with spatial maps and time series of the following variables, supporting decision on irrigation, soil protection from erosion, pollution risk of groundwater and

  13. Delineating floodplain and upload areas for hydrologic models: A comparison of methods

    USDA-ARS?s Scientific Manuscript database

    A spatially distributed representation of basin hydrology and transport processes in eco-hydrological models facilitates the identification of critical source areas and the placement of management and conservation measures. Floodplains are critical landscape features that differ from neighboring up...

  14. Hydrological and pesticide transfer modeling in a tropical volcanic watershed with the WATPPASS model

    NASA Astrophysics Data System (ADS)

    Mottes, Charles; Lesueur-Jannoyer, Magalie; Charlier, Jean-Baptiste; Carles, Céline; Guéné, Mathilde; Le Bail, Marianne; Malézieux, Eric

    2015-10-01

    Simulation of flows and pollutant transfers in heterogeneous media is widely recognized to be a remaining frontier in hydrology research. We present a new modeling approach to simulate agricultural pollutions in watersheds: WATPPASS, a model for Watershed Agricultural Techniques and Pesticide Practices ASSessment. It is designed to assess mean pesticide concentrations and loads that result from the use of pesticides in horticultural watersheds located on heterogeneous subsoil. WATPPASS is suited for small watershed with significant groundwater flows and complex aquifer systems. The model segments the watershed into fields with independent hydrological and pesticide transfers at the ground surface. Infiltrated water and pesticides are routed toward outlet using a conceptual reservoir model. We applied WATPPASS on a heterogeneous tropical volcanic watershed of Martinique in the French West Indies. We carried out and hydrological analysis that defined modeling constraints: (i) a spatial variability of runoff/infiltration partitioning according to land use, and (ii) a predominance of groundwater flow paths in two overlapping aquifers under permeable soils (50-60% of annual flows). We carried out simulations on a 550 days period at a daily time step for hydrology (Nashsqrt > 0.75). Weekly concentrations and loads of a persistent organic pesticide (chlordecone) were simulated for 67 weeks to evaluate the modeling approach. Pesticide simulations without specific calibration detected the mean long-term measured concentration, leading to a good quantification of the cumulative loads (5% error), but failed to represent the concentration peaks at the correct timing. Nevertheless, we succeed in adjusting the model structure to better represent the temporal dynamic of pesticide concentrations. This modification requires a proper evaluation on an independent dataset. Finally, WATPPASS is a compromise between complexity and easiness of use that makes it suited for cropping system

  15. Global U(1 ) Y⊗BRST symmetry and the LSS theorem: Ward-Takahashi identities governing Green's functions, on-shell T -matrix elements, and the effective potential in the scalar sector of the spontaneously broken extended Abelian Higgs model

    NASA Astrophysics Data System (ADS)

    Lynn, Bryan W.; Starkman, Glenn D.

    2017-09-01

    The weak-scale U (1 )Y Abelian Higgs model (AHM) is the simplest spontaneous symmetry breaking (SSB) gauge theory: a scalar ϕ =1/√{2 }(H +i π )≡1/√{2 }H ˜ei π ˜/⟨H ⟩ and a vector Aμ. The extended AHM (E-AHM) adds certain heavy (MΦ2,Mψ2˜MHeavy2≫⟨H ⟩2˜mWeak2 ) spin S =0 scalars Φ and S =1/2 fermions ψ . In Lorenz gauge, ∂μAμ=0 , the SSB AHM (and E-AHM) has a global U (1 )Y conserved physical current, but no conserved charge. As shown by T. W. B. Kibble, the Goldstone theorem applies, so π ˜ is a massless derivatively coupled Nambu-Goldstone boson (NGB). Proof of all-loop-orders renormalizability and unitarity for the SSB case is tricky because the Becchi-Rouet-Stora-Tyutin (BRST)-invariant Lagrangian is not U (1 )Y symmetric. Nevertheless, Slavnov-Taylor identities guarantee that on-shell T-matrix elements of physical states Aμ,ϕ , Φ , ψ (but not ghosts ω , η ¯ ) are independent of anomaly-free local U (1 )Y gauge transformations. We observe here that they are therefore also independent of the usual anomaly-free U (1 )Y global/rigid transformations. It follows that the associated global current, which is classically conserved only up to gauge-fixing terms, is exactly conserved for amplitudes of physical states in the AHM and E-AHM. We identify corresponding "undeformed" [i.e. with full global U (1 )Y symmetry] Ward-Takahashi identities (WTI). The proof of renormalizability and unitarity, which relies on BRST invariance, is undisturbed. In Lorenz gauge, two towers of "1-soft-pion" SSB global WTI govern the ϕ -sector, and represent a new global U (1 )Y⊗BRST symmetry not of the Lagrangian but of the physics. The first gives relations among off-shell Green's functions, yielding powerful constraints on the all-loop-orders ϕ -sector SSB E-AHM low-energy effective Lagrangian and an additional global shift symmetry for the NGB: π ˜→π ˜+⟨H ⟩θ . A second tower, governing on-shell T-matrix elements, replaces the old Adler

  16. Evaluating Satellite-based Rainfall Estimates for Basin-scale Hydrologic Modeling

    NASA Astrophysics Data System (ADS)

    Yilmaz, K. K.; Hogue, T. S.; Hsu, K.; Gupta, H. V.; Mahani, S. E.; Sorooshian, S.

    2003-12-01

    The reliability of any hydrologic simulation and basin outflow prediction effort depends primarily on the rainfall estimates. The problem of estimating rainfall becomes more obvious in basins with scarce or no rain gauges. We present an evaluation of satellite-based rainfall estimates for basin-scale hydrologic modeling with particular interest in ungauged basins. The initial phase of this study focuses on comparison of mean areal rainfall estimates from ground-based rain gauge network, NEXRAD radar Stage-III, and satellite-based PERSIANN (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks) and their influence on hydrologic model simulations over several basins in the U.S. Six-hourly accumulations of the above competing mean areal rainfall estimates are used as input to the Sacramento Soil Moisture Accounting Model. Preliminary experiments for the Leaf River Basin in Mississippi, for the period of March 2000 - June 2002, reveals that seasonality plays an important role in the comparison. There is an overestimation during the summer and underestimation during the winter in satellite-based rainfall with respect to the competing rainfall estimates. The consequence of this result on the hydrologic model is that simulated discharge underestimates the major observed peak discharges during early spring for the basin under study. Future research will entail developing correction procedures, which depend on different factors such as seasonality, geographic location and basin size, for satellite-based rainfall estimates over basins with dense rain gauge network and/or radar coverage. Extension of these correction procedures to satellite-based rainfall estimates over ungauged basins with similar characteristics has the potential for reducing the input uncertainty in ungauged basin modeling efforts.

  17. Reducing hydrologic model uncertainty in monthly streamflow predictions using multimodel combination

    NASA Astrophysics Data System (ADS)

    Li, Weihua; Sankarasubramanian, A.

    2012-12-01

    Model errors are inevitable in any prediction exercise. One approach that is currently gaining attention in reducing model errors is by combining multiple models to develop improved predictions. The rationale behind this approach primarily lies on the premise that optimal weights could be derived for each model so that the developed multimodel predictions will result in improved predictions. A new dynamic approach (MM-1) to combine multiple hydrological models by evaluating their performance/skill contingent on the predictor state is proposed. We combine two hydrological models, "abcd" model and variable infiltration capacity (VIC) model, to develop multimodel streamflow predictions. To quantify precisely under what conditions the multimodel combination results in improved predictions, we compare multimodel scheme MM-1 with optimal model combination scheme (MM-O) by employing them in predicting the streamflow generated from a known hydrologic model (abcd model orVICmodel) with heteroscedastic error variance as well as from a hydrologic model that exhibits different structure than that of the candidate models (i.e., "abcd" model or VIC model). Results from the study show that streamflow estimated from single models performed better than multimodels under almost no measurement error. However, under increased measurement errors and model structural misspecification, both multimodel schemes (MM-1 and MM-O) consistently performed better than the single model prediction. Overall, MM-1 performs better than MM-O in predicting the monthly flow values as well as in predicting extreme monthly flows. Comparison of the weights obtained from each candidate model reveals that as measurement errors increase, MM-1 assigns weights equally for all the models, whereas MM-O assigns higher weights for always the best-performing candidate model under the calibration period. Applying the multimodel algorithms for predicting streamflows over four different sites revealed that MM-1 performs

  18. Representing northern peatland microtopography and hydrology within the Community Land Model

    Treesearch

    X. Shi; P.E. Thornton; D.M. Ricciuto; P J. Hanson; J. Mao; Stephen Sebestyen; N.A. Griffiths; G. Bisht

    2015-01-01

    Predictive understanding of northern peatland hydrology is a necessary precursor to understanding the fate of massive carbon stores in these systems under the influence of present and future climate change. Current models have begun to address microtopographic controls on peatland hydrology, but none have included a prognostic calculation of peatland water table depth...

  19. Moving university hydrology education forward with geoinformatics, data and modeling approaches

    NASA Astrophysics Data System (ADS)

    Merwade, V.; Ruddell, B. L.

    2012-02-01

    In this opinion paper, we review recent literature related to data and modeling driven instruction in hydrology, and present our findings from surveying the hydrology education community in the United States. This paper presents an argument that that Data and Modeling Driven Geoscience Cybereducation (DMDGC) approaches are valuable for teaching the conceptual and applied aspects of hydrology, as a part of the broader effort to improve Science, Technology, Engineering, and Mathematics (STEM) education at the university level. The authors have undertaken a series of surveys and a workshop involving the community of university hydrology educators to determine the state of the practice of DMDGC approaches to hydrology. We identify the most common tools and approaches currently utilized, quantify the extent of the adoption of DMDGC approaches in the university hydrology classroom, and explain the community's views on the challenges and barriers preventing DMDGC approaches from wider use. DMDGC approaches are currently emphasized at the graduate level of the curriculum, and only the most basic modeling and visualization tools are in widespread use. The community identifies the greatest barriers to greater adoption as a lack of access to easily adoptable curriculum materials and a lack of time and training to learn constantly changing tools and methods. The community's current consensus is that DMDGC approaches should emphasize conceptual learning, and should be used to complement rather than replace lecture-based pedagogies. Inadequate online material-publication and sharing systems, and a lack of incentives for faculty to develop and publish materials via such systems, is also identified as a challenge. Based on these findings, we suggest that a number of steps should be taken by the community to develop the potential of DMDGC in university hydrology education, including formal development and assessment of curriculum materials integrating lecture-format and DMDGC

  20. Xanthos – A Global Hydrologic Model

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Li, Xinya; Vernon, Chris R.; Hejazi, Mohamad I.

    Xanthos is an open-source hydrologic model, written in Python, designed to quantify and analyse global water availability. Xanthos simulates historical and future global water availability on a monthly time step at a spatial resolution of 0.5 geographic degrees. Xanthos was designed to be extensible and used by scientists that study global water supply and work with the Global Change Assessment Model (GCAM). Xanthos uses a user-defined configuration file to specify model inputs, outputs and parameters. Xanthos has been tested using actual global data sets and the model is able to provide historical observations and future estimates of renewable freshwater resourcesmore » in the form of total runoff.« less

  1. Xanthos – A Global Hydrologic Model

    DOE PAGES

    Li, Xinya; Vernon, Chris R.; Hejazi, Mohamad I.; ...

    2017-09-11

    Xanthos is an open-source hydrologic model, written in Python, designed to quantify and analyse global water availability. Xanthos simulates historical and future global water availability on a monthly time step at a spatial resolution of 0.5 geographic degrees. Xanthos was designed to be extensible and used by scientists that study global water supply and work with the Global Change Assessment Model (GCAM). Xanthos uses a user-defined configuration file to specify model inputs, outputs and parameters. Xanthos has been tested using actual global data sets and the model is able to provide historical observations and future estimates of renewable freshwater resourcesmore » in the form of total runoff.« less

  2. Balancing the stochastic description of uncertainties as a function of hydrologic model complexity

    NASA Astrophysics Data System (ADS)

    Del Giudice, D.; Reichert, P.; Albert, C.; Kalcic, M.; Logsdon Muenich, R.; Scavia, D.; Bosch, N. S.; Michalak, A. M.

    2016-12-01

    Uncertainty analysis is becoming an important component of forecasting water and pollutant fluxes in urban and rural environments. Properly accounting for errors in the modeling process can help to robustly assess the uncertainties associated with the inputs (e.g. precipitation) and outputs (e.g. runoff) of hydrological models. In recent years we have investigated several Bayesian methods to infer the parameters of a mechanistic hydrological model along with those of the stochastic error component. The latter describes the uncertainties of model outputs and possibly inputs. We have adapted our framework to a variety of applications, ranging from predicting floods in small stormwater systems to nutrient loads in large agricultural watersheds. Given practical constraints, we discuss how in general the number of quantities to infer probabilistically varies inversely with the complexity of the mechanistic model. Most often, when evaluating a hydrological model of intermediate complexity, we can infer the parameters of the model as well as of the output error model. Describing the output errors as a first order autoregressive process can realistically capture the "downstream" effect of inaccurate inputs and structure. With simpler runoff models we can additionally quantify input uncertainty by using a stochastic rainfall process. For complex hydrologic transport models, instead, we show that keeping model parameters fixed and just estimating time-dependent output uncertainties could be a viable option. The common goal across all these applications is to create time-dependent prediction intervals which are both reliable (cover the nominal amount of validation data) and precise (are as narrow as possible). In conclusion, we recommend focusing both on the choice of the hydrological model and of the probabilistic error description. The latter can include output uncertainty only, if the model is computationally-expensive, or, with simpler models, it can separately account

  3. Statistical analysis and ANN modeling for predicting hydrological extremes under climate change scenarios: the example of a small Mediterranean agro-watershed.

    PubMed

    Kourgialas, Nektarios N; Dokou, Zoi; Karatzas, George P

    2015-05-01

    The purpose of this study was to create a modeling management tool for the simulation of extreme flow events under current and future climatic conditions. This tool is a combination of different components and can be applied in complex hydrogeological river basins, where frequent flood and drought phenomena occur. The first component is the statistical analysis of the available hydro-meteorological data. Specifically, principal components analysis was performed in order to quantify the importance of the hydro-meteorological parameters that affect the generation of extreme events. The second component is a prediction-forecasting artificial neural network (ANN) model that simulates, accurately and efficiently, river flow on an hourly basis. This model is based on a methodology that attempts to resolve a very difficult problem related to the accurate estimation of extreme flows. For this purpose, the available measurements (5 years of hourly data) were divided in two subsets: one for the dry and one for the wet periods of the hydrological year. This way, two ANNs were created, trained, tested and validated for a complex Mediterranean river basin in Crete, Greece. As part of the second management component a statistical downscaling tool was used for the creation of meteorological data according to the higher and lower emission climate change scenarios A2 and B1. These data are used as input in the ANN for the forecasting of river flow for the next two decades. The final component is the application of a meteorological index on the measured and forecasted precipitation and flow data, in order to assess the severity and duration of extreme events. Copyright © 2015 Elsevier Ltd. All rights reserved.

  4. Hydrological and water quality processes simulation by the integrated MOHID model

    NASA Astrophysics Data System (ADS)

    Epelde, Ane; Antiguedad, Iñaki; Brito, David; Eduardo, Jauch; Neves, Ramiro; Sauvage, Sabine; Sánchez-Pérez, José Miguel

    2016-04-01

    Different modelling approaches have been used in recent decades to study the water quality degradation caused by non-point source pollution. In this study, the MOHID fully distributed and physics-based model has been employed to simulate hydrological processes and nitrogen dynamics in a nitrate vulnerable zone: the Alegria River watershed (Basque Country, Northern Spain). The results of this study indicate that the MOHID code is suitable for hydrological processes simulation at the watershed scale, as the model shows satisfactory performance at simulating the discharge (with NSE: 0.74 and 0.76 during calibration and validation periods, respectively). The agronomical component of the code, allowed the simulation of agricultural practices, which lead to adequate crop yield simulation in the model. Furthermore, the nitrogen exportation also shows satisfactory performance (with NSE: 0.64 and 0.69 during calibration and validation periods, respectively). While the lack of field measurements do not allow to evaluate the nutrient cycling processes in depth, it has been observed that the MOHID model simulates the annual denitrification according to general ranges established for agricultural watersheds (in this study, 9 kg N ha-1 year-1). In addition, the model has simulated coherently the spatial distribution of the denitrification process, which is directly linked to the simulated hydrological conditions. Thus, the model has localized the highest rates nearby the discharge zone of the aquifer and also where the aquifer thickness is low. These results evidence the strength of this model to simulate watershed scale hydrological processes as well as the crop production and the agricultural activity derived water quality degradation (considering both nutrient exportation and nutrient cycling processes).

  5. Alternative socio-centric approach for model validation - a way forward for socio-hydrology

    NASA Astrophysics Data System (ADS)

    van Emmerik, Tim; Elshafei, Yasmina; Mahendran, Roobavannan; Kandasamy, Jaya; Pande, Saket; Sivapalan, Murugesu

    2017-04-01

    To better understand and mitigate the impacts of humans on the water cycle, the importance of studying the co-evolution of coupled human-water systems has been recognized. Because of its unique system dynamics, the Murrumbidgee river basin (part of the larger Murray-Darlin basin, Australia) is one of the main study areas in the emerging field of socio-hydrology. In recent years, various historical and modeling studies have contributed to gaining a better understanding of this system's behavior. Kandasamy et al. (2014) performed a historical study on the development of this human-water coupled system. They identified four eras, providing a historical context of the observed "pendulum" swing between first an exclusive focus on agricultural development, followed by increasing environmental awareness, subsequent efforts to mitigate, and finally to restore environmental health. A modeling effort by Van Emmerik et al. (2014) focused on reconstructing hydrological, economical, and societal dynamics and their feedbacks. A measure of changing societal values was included by introducing environmental awareness as an endogenously modeled variable, which resulted in capturing the co-evolution between economic development and environmental health. Later work by Elshafei et al. (2015) modeled and analyzed the two-way feedbacks of land use management and land degradation in two other Australian coupled systems. A composite variable, community sensitivity, was used to measure changing community sentiment, such that the model was capable of isolating the two-way feedbacks in the coupled system. As socio-hydrology adopts a holistic approach, it is often required to introduce (hydrologically) unconventional variables, such as environmental awareness or community sensitivity. It is the subject of ongoing debate how such variables can be validated, as there is no standardized data set available from hydrological or statistical agencies. Recent research (Wei et al. 2017) has provided

  6. HESS Opinions: The complementary merits of competing modelling philosophies in hydrology

    NASA Astrophysics Data System (ADS)

    Hrachowitz, Markus; Clark, Martyn P.

    2017-08-01

    In hydrology, two somewhat competing philosophies form the basis of most process-based models. At one endpoint of this continuum are detailed, high-resolution descriptions of small-scale processes that are numerically integrated to larger scales (e.g. catchments). At the other endpoint of the continuum are spatially lumped representations of the system that express the hydrological response via, in the extreme case, a single linear transfer function. Many other models, developed starting from these two contrasting endpoints, plot along this continuum with different degrees of spatial resolutions and process complexities. A better understanding of the respective basis as well as the respective shortcomings of different modelling philosophies has the potential to improve our models. In this paper we analyse several frequently communicated beliefs and assumptions to identify, discuss and emphasize the functional similarity of the seemingly competing modelling philosophies. We argue that deficiencies in model applications largely do not depend on the modelling philosophy, although some models may be more suitable for specific applications than others and vice versa, but rather on the way a model is implemented. Based on the premises that any model can be implemented at any desired degree of detail and that any type of model remains to some degree conceptual, we argue that a convergence of modelling strategies may hold some value for advancing the development of hydrological models.

  7. Marrying Hydrological Modelling and Integrated Assessment for the needs of Water Resource Management

    NASA Astrophysics Data System (ADS)

    Croke, B. F. W.; Blakers, R. S.; El Sawah, S.; Fu, B.; Guillaume, J. H. A.; Kelly, R. A.; Patrick, M. J.; Ross, A.; Ticehurst, J.; Barthel, R.; Jakeman, A. J.

    2014-09-01

    This paper discusses the integration of hydrology with other disciplines using an Integrated Assessment (IA) and modelling approach to the management and allocation of water resources. Recent developments in the field of socio-hydrology aim to develop stronger relationships between hydrology and the human dimensions of Water Resource Management (WRM). This should build on an existing wealth of knowledge and experience of coupled human-water systems. To further strengthen this relationship and contribute to this broad body of knowledge, we propose a strong and durable "marriage" between IA and hydrology. The foundation of this marriage requires engagement with appropriate concepts, model structures, scales of analyses, performance evaluation and communication - and the associated tools and models that are needed for pragmatic deployment or operation. To gain insight into how this can be achieved, an IA case study in water allocation in the Lower Namoi catchment, NSW, Australia is presented.

  8. The implementation and validation of improved landsurface hydrology in an atmospheric general circulation model

    NASA Technical Reports Server (NTRS)

    Johnson, Kevin D.; Entekhabi, Dara; Eagleson, Peter S.

    1991-01-01

    Landsurface hydrological parameterizations are implemented in the NASA Goddard Institute for Space Studies (GISS) General Circulation Model (GCM). These parameterizations are: (1) runoff and evapotranspiration functions that include the effects of subgrid scale spatial variability and use physically based equations of hydrologic flux at the soil surface, and (2) a realistic soil moisture diffusion scheme for the movement of water in the soil column. A one dimensional climate model with a complete hydrologic cycle is used to screen the basic sensitivities of the hydrological parameterizations before implementation into the full three dimensional GCM. Results of the final simulation with the GISS GCM and the new landsurface hydrology indicate that the runoff rate, especially in the tropics is significantly improved. As a result, the remaining components of the heat and moisture balance show comparable improvements when compared to observations. The validation of model results is carried from the large global (ocean and landsurface) scale, to the zonal, continental, and finally the finer river basin scales.

  9. Advancing reservoir operation description in physically based hydrological models

    NASA Astrophysics Data System (ADS)

    Anghileri, Daniela; Giudici, Federico; Castelletti, Andrea; Burlando, Paolo

    2016-04-01

    Last decades have seen significant advances in our capacity of characterizing and reproducing hydrological processes within physically based models. Yet, when the human component is considered (e.g. reservoirs, water distribution systems), the associated decisions are generally modeled with very simplistic rules, which might underperform in reproducing the actual operators' behaviour on a daily or sub-daily basis. For example, reservoir operations are usually described by a target-level rule curve, which represents the level that the reservoir should track during normal operating conditions. The associated release decision is determined by the current state of the reservoir relative to the rule curve. This modeling approach can reasonably reproduce the seasonal water volume shift due to reservoir operation. Still, it cannot capture more complex decision making processes in response, e.g., to the fluctuations of energy prices and demands, the temporal unavailability of power plants or varying amount of snow accumulated in the basin. In this work, we link a physically explicit hydrological model with detailed hydropower behavioural models describing the decision making process by the dam operator. In particular, we consider two categories of behavioural models: explicit or rule-based behavioural models, where reservoir operating rules are empirically inferred from observational data, and implicit or optimization based behavioural models, where, following a normative economic approach, the decision maker is represented as a rational agent maximising a utility function. We compare these two alternate modelling approaches on the real-world water system of Lake Como catchment in the Italian Alps. The water system is characterized by the presence of 18 artificial hydropower reservoirs generating almost 13% of the Italian hydropower production. Results show to which extent the hydrological regime in the catchment is affected by different behavioural models and reservoir

  10. Hydrologic Modeling and Parameter Estimation under Data Scarcity for Java Island, Indonesia

    NASA Astrophysics Data System (ADS)

    Yanto, M.; Livneh, B.; Rajagopalan, B.; Kasprzyk, J. R.

    2015-12-01

    The Indonesian island of Java is routinely subjected to intense flooding, drought and related natural hazards, resulting in severe social and economic impacts. Although an improved understanding of the island's hydrology would help mitigate these risks, data scarcity issues make the modeling challenging. To this end, we developed a hydrological representation of Java using the Variable Infiltration Capacity (VIC) model, to simulate the hydrologic processes of several watersheds across the island. We measured the model performance using Nash-Sutcliffe Efficiency (NSE) at monthly time step. Data scarcity and quality issues for precipitation and streamflow warranted the application of a quality control procedure to data ensure consistency among watersheds resulting in 7 watersheds. To optimize the model performance, the calibration parameters were estimated using Borg Multi Objective Evolutionary Algorithm (Borg MOEA), which offers efficient searching of the parameter space, adaptive population sizing and local optima escape facility. The result shows that calibration performance is best (NSE ~ 0.6 - 0.9) in the eastern part of the domain and moderate (NSE ~ 0.3 - 0.5) in the western part of the island. The validation results are lower (NSE ~ 0.1 - 0.5) and (NSE ~ 0.1 - 0.4) in the east and west, respectively. We surmise that the presence of outliers and stark differences in the climate between calibration and validation periods in the western watersheds are responsible for low NSE in this region. In addition, we found that approximately 70% of total errors were contributed by less than 20% of total data. The spatial variability of model performance suggests the influence of both topographical and hydroclimatic controls on the hydrological processes. Most watersheds in eastern part perform better in wet season and vice versa for the western part. This modeling framework is one of the first attempts at comprehensively simulating the hydrology in this maritime, tropical

  11. Hydrologic and water quality terminology as applied to modeling

    USDA-ARS?s Scientific Manuscript database

    A survey of literature and examination in particular of terminology use in a previous special collection of modeling calibration and validation papers has been conducted to arrive at a list of consistent terminology recommended for writing about hydrologic and water quality model calibration and val...

  12. A Model-Model and Data-Model Comparison for the Early Eocene Hydrological Cycle

    NASA Technical Reports Server (NTRS)

    Carmichael, Matthew J.; Lunt, Daniel J.; Huber, Matthew; Heinemann, Malte; Kiehl, Jeffrey; LeGrande, Allegra; Loptson, Claire A.; Roberts, Chris D.; Sagoo, Navjit; Shields, Christine

    2016-01-01

    A range of proxy observations have recently provided constraints on how Earth's hydrological cycle responded to early Eocene climatic changes. However, comparisons of proxy data to general circulation model (GCM) simulated hydrology are limited and inter-model variability remains poorly characterised. In this work, we undertake an intercomparison of GCM-derived precipitation and P - E distributions within the extended EoMIP ensemble (Eocene Modelling Intercomparison Project; Lunt et al., 2012), which includes previously published early Eocene simulations performed using five GCMs differing in boundary conditions, model structure, and precipitation-relevant parameterisation schemes. We show that an intensified hydrological cycle, manifested in enhanced global precipitation and evaporation rates, is simulated for all Eocene simulations relative to the preindustrial conditions. This is primarily due to elevated atmospheric paleo-CO2, resulting in elevated temperatures, although the effects of differences in paleogeography and ice sheets are also important in some models. For a given CO2 level, globally averaged precipitation rates vary widely between models, largely arising from different simulated surface air temperatures. Models with a similar global sensitivity of precipitation rate to temperature (dP=dT ) display different regional precipitation responses for a given temperature change. Regions that are particularly sensitive to model choice include the South Pacific, tropical Africa, and the Peri-Tethys, which may represent targets for future proxy acquisition. A comparison of early and middle Eocene leaf-fossil-derived precipitation estimates with the GCM output illustrates that GCMs generally underestimate precipitation rates at high latitudes, although a possible seasonal bias of the proxies cannot be excluded. Models which warm these regions, either via elevated CO2 or by varying poorly constrained model parameter values, are most successful in simulating a

  13. Effect of Using Extreme Years in Hydrologic Model Calibration Performance

    NASA Astrophysics Data System (ADS)

    Goktas, R. K.; Tezel, U.; Kargi, P. G.; Ayvaz, T.; Tezyapar, I.; Mesta, B.; Kentel, E.

    2017-12-01

    Hydrological models are useful in predicting and developing management strategies for controlling the system behaviour. Specifically they can be used for evaluating streamflow at ungaged catchments, effect of climate change, best management practices on water resources, or identification of pollution sources in a watershed. This study is a part of a TUBITAK project named "Development of a geographical information system based decision-making tool for water quality management of Ergene Watershed using pollutant fingerprints". Within the scope of this project, first water resources in Ergene Watershed is studied. Streamgages found in the basin are identified and daily streamflow measurements are obtained from State Hydraulic Works of Turkey. Streamflow data is analysed using box-whisker plots, hydrographs and flow-duration curves focusing on identification of extreme periods, dry or wet. Then a hydrological model is developed for Ergene Watershed using HEC-HMS in the Watershed Modeling System (WMS) environment. The model is calibrated for various time periods including dry and wet ones and the performance of calibration is evaluated using Nash-Sutcliffe Efficiency (NSE), correlation coefficient, percent bias (PBIAS) and root mean square error. It is observed that calibration period affects the model performance, and the main purpose of the development of the hydrological model should guide calibration period selection. Acknowledgement: This study is funded by The Scientific and Technological Research Council of Turkey (TUBITAK) under Project Number 115Y064.

  14. Hydrologic behavior of model slopes with synthetic water repellent soils

    NASA Astrophysics Data System (ADS)

    Zheng, Shuang; Lourenço, Sérgio D. N.; Cleall, Peter J.; Chui, Ting Fong May; Ng, Angel K. Y.; Millis, Stuart W.

    2017-11-01

    In the natural environment, soil water repellency decreases infiltration, increases runoff, and increases erosion in slopes. In the built environment, soil water repellency offers the opportunity to develop granular materials with controllable wettability for slope stabilization. In this paper, the influence of soil water repellency on the hydrological response of slopes is investigated. Twenty-four flume tests were carried out in model slopes under artificial rainfall; soils with various wettability levels were tested, including wettable (Contact Angle, CA < 90°), subcritical water repellent (CA ∼ 90°) and water repellent (CA > 90°). Various rainfall intensities (30 mm/h and 70 mm/h), slope angles (20° and 40°) and relative compactions (70% and 90%) were applied to model the response of natural and man-made slopes to rainfall. To quantitatively assess the hydrological response, a number of measurements were made: runoff rate, effective rainfall rate, time to ponding, time to steady state, runoff acceleration, total water storage and wetting front rate. Overall, an increase in soil water repellency reduces infiltration and shortens the time for runoff generation, with the effects amplified for high rainfall intensity. Comparatively, the slope angle and relative compaction had only a minor contribution to the slope hydrology. The subcritical water repellent soils sustained infiltration for longer than both the wettable and water repellent soils, which presents an added advantage if they are to be used in the built environment as barriers. This study revealed substantial impacts of man-made or synthetically induced soil water repellency on the hydrological behavior of model slopes in controlled conditions. The results shed light on our understanding of hydrological processes in environments where the occurrence of natural soil water repellency is likely, such as slopes subjected to wildfires and in agricultural and forested slopes.

  15. Stimulation from Simulation? A Teaching Model of Hillslope Hydrology for Use on Microcomputers.

    ERIC Educational Resources Information Center

    Burt, Tim; Butcher, Dave

    1986-01-01

    The design and use of a simple computer model which simulates a hillslope hydrology is described in a teaching context. The model shows a relatively complex environmental system can be constructed on the basis of a simple but realistic theory, thus allowing students to simulate the hydrological response of real hillslopes. (Author/TRS)

  16. The application of remote sensing to the development and formulation of hydrologic planning models

    NASA Technical Reports Server (NTRS)

    Castruccio, P. A.; Loats, H. L., Jr.; Fowler, T. R.

    1976-01-01

    A hydrologic planning model is developed based on remotely sensed inputs. Data from LANDSAT 1 are used to supply the model's quantitative parameters and coefficients. The use of LANDSAT data as information input to all categories of hydrologic models requiring quantitative surface parameters for their effects functioning is also investigated.

  17. Evaluation of Potential Evapotranspiration from a Hydrologic Model on a National Scale

    NASA Astrophysics Data System (ADS)

    Hakala, Kirsti; Markstrom, Steven; Hay, Lauren

    2015-04-01

    The U.S. Geological Survey has developed a National Hydrologic Model (NHM) to support coordinated, comprehensive and consistent hydrologic model development and facilitate the application of simulations on the scale of the continental U.S. The NHM has a consistent geospatial fabric for modeling, consisting of over 100,000 hydrologic response units HRUs). Each HRU requires accurate parameter estimates, some of which are attained from automated calibration. However, improved calibration can be achieved by initially utilizing as many parameters as possible from national data sets. This presentation investigates the effectiveness of calculating potential evapotranspiration (PET) parameters based on mean monthly values from the NOAA PET Atlas. Additional PET products are then used to evaluate the PET parameters. Effectively utilizing existing national-scale data sets can simplify the effort in establishing a robust NHM.

  18. Evaluation of Potential Evapotranspiration from a Hydrologic Model on a National Scale

    NASA Astrophysics Data System (ADS)

    Hakala, K. A.; Hay, L.; Markstrom, S. L.

    2014-12-01

    The US Geological Survey has developed a National Hydrologic Model (NHM) to support coordinated, comprehensive and consistent hydrologic model development and facilitate the application of simulations on the scale of the continental US. The NHM has a consistent geospatial fabric for modeling, consisting of over 100,000 hydrologic response units (HRUs). Each HRU requires accurate parameter estimates, some of which are attained from automated calibration. However, improved calibration can be achieved by initially utilizing as many parameters as possible from national data sets. This presentation investigates the effectiveness of calculating potential evapotranspiration (PET) parameters based on mean monthly values from the NOAA PET Atlas. Additional PET products are then used to evaluate the PET parameters. Effectively utilizing existing national-scale data sets can simplify the effort in establishing a robust NHM.

  19. HYDROLOGIC MODEL UNCERTAINTY ASSOCIATED WITH SIMULATING FUTURE LAND-COVER/USE SCENARIOS: A RETROSPECTIVE ANALYSIS

    EPA Science Inventory

    GIS-based hydrologic modeling offers a convenient means of assessing the impacts associated with land-cover/use change for environmental planning efforts. Alternative future scenarios can be used as input to hydrologic models and compared with existing conditions to evaluate pot...

  20. Toward Global Real Time Hydrologic Modeling - An "Open" View From the Trenches

    NASA Astrophysics Data System (ADS)

    Nelson, J.

    2015-12-01

    Big Data has become a popular term to describe the exponential growth of data and related cyber infrastructure to process it so that better analysis can be performed and lead to improved decision-making. How are we doing in the hydrologic sciences? As part of a significant collaborative effort that brought together scientists from public, private, and academic organizations a new transformative hydrologic forecasting modeling infrastructure has been developed. How was it possible to go from deterministic hydrologic forecasts largely driven through manual interactions at 3600 stations to automated 15-day ensemble forecasts at 2.67 million stations? Earth observations of precipitation, temperature, moisture, and other atmospheric and land surface conditions form the foundation of global hydrologic forecasts, but this project demonstrates a critical component to harness these resources can be summed up in one word: OPEN. Whether it is open data sources, open software solutions with open standards, or just being open to collaborations and building teams across institutions, disciplines, and international boundaries, time and time again through my involvement in the development of a high-resolution real time global hydrologic forecasting model I have discovered that in every aspect the sum has always been greater than the parts. While much has been accomplished, much more remains to be done, but the most important lesson learned has been to the degree that we can remain open and work together, the greater our ability will be to use big data hydrologic modeling resources to solve the world's most vexing water related challenges. This presentation will demonstrate a transformational global real time hydrologic forecasting application based on downscaled ECMWF ensemble forecasts, RAPID routing, and Tethys Platform for cloud computing and visualization with discussions of the human and cyber infrastructure connections that make it successful and needs moving forward.

  1. Modeling the effect of land use change on hydrology of a forested watershed in coastal South Carolina.

    Treesearch

    Zhaohua Dai; Devendra M. Amatya; Ge Sun; Changsheng Li; Carl C. Trettin; Harbin Li

    2009-01-01

    Since hydrology is one of main factors controlling wetland functions, hydrologic models are useful for evaluating the effects of land use change on we land ecosystems. We evaluated two process-based hydrologic models with...

  2. Multi-Objective vs. Single Objective Calibration of a Hydrologic Model using Either Different Hydrologic Signatures or Complementary Data Sources

    NASA Astrophysics Data System (ADS)

    Mai, J.; Cuntz, M.; Zink, M.; Schaefer, D.; Thober, S.; Samaniego, L. E.; Shafii, M.; Tolson, B.

    2015-12-01

    Hydrologic models are traditionally calibrated against discharge. Recent studies have shown however, that only a few global model parameters are constrained using the integral discharge measurements. It is therefore advisable to use additional information to calibrate those models. Snow pack data, for example, could improve the parametrization of snow-related processes, which might be underrepresented when using only discharge. One common approach is to combine these multiple objectives into one single objective function and allow the use of a single-objective algorithm. Another strategy is to consider the different objectives separately and apply a Pareto-optimizing algorithm. Both methods are challenging in the choice of appropriate multiple objectives with either conflicting interests or the focus on different model processes. A first aim of this study is to compare the two approaches employing the mesoscale Hydrologic Model mHM at several distinct river basins over Europe and North America. This comparison will allow the identification of the single-objective solution on the Pareto front. It is elucidated if this position is determined by the weighting and scaling of the multiple objectives when combing them to the single objective. The principal second aim is to guide the selection of proper objectives employing sensitivity analyses. These analyses are used to determine if an additional information would help to constrain additional model parameters. The additional information are either multiple data sources or multiple signatures of one measurement. It is evaluated if specific discharge signatures can inform different parts of the hydrologic model. The results show that an appropriate selection of discharge signatures increased the number of constrained parameters by more than 50% compared to using only NSE of the discharge time series. It is further assessed if the use of these signatures impose conflicting objectives on the hydrologic model. The usage of

  3. Assessing Hydrologic Impacts of Land Configuration Changes Using an Integrated Hydrologic Model at the Rocky Flats Environmental Technology Site, Colorado

    NASA Astrophysics Data System (ADS)

    Prucha, R. H.; Dayton, C. S.; Hawley, C. M.

    2002-12-01

    The Rocky Flats Environmental Technology Site (RFETS) in Golden, Colorado, a former Department of Energy nuclear weapons manufacturing facility, is currently undergoing closure. The natural semi-arid interaction between surface and subsurface flow at RFETS is complex and complicated by the industrial modifications to the flow system. Using a substantial site data set, a distributed parameter, fully-integrated hydrologic model was developed to assess the hydrologic impact of different hypothetical site closure configurations on the current flow system and to better understand the integrated hydrologic behavior of the system. An integrated model with this level of detail has not been previously developed in a semi-arid area, and a unique, but comprehensive, approach was required to calibrate and validate the model. Several hypothetical scenarios were developed to simulate hydrologic effects of modifying different aspects of the site. For example, some of the simulated modifications included regrading the current land surface, changing the existing surface channel network, removing subsurface trenches and gravity drain flow systems, installing a slurry wall and geotechnical cover, changing the current vegetative cover, and converting existing buildings and pavement to permeable soil areas. The integrated flow model was developed using a rigorous physically-based code so that realistic design parameters can simulate these changes. This code also permitted evaluation of changes to complex integrated hydrologic system responses that included channelized and overland flow, pond levels, unsaturated zone storage, groundwater heads and flow directions, and integrated water balances for key areas. Results generally show that channel flow offsite decreases substantially for different scenarios, while groundwater heads generally increase within the reconfigured industrial area most of which is then discharged as evapotranspiration. These changes have significant implications to

  4. The benefits of daily data and scale up issues in hydrologic models-SWAT and CRAFT

    NASA Astrophysics Data System (ADS)

    Huang, Yumei; Quinn, Paul; Liang, Qiuhua; Adams, Russell

    2017-04-01

    When modelling the flow pathways for nutrient transport, the lack of good data and limitation of data resolution become the key cause of low quality output in various hydrologic models. The scale of catchment being studied would present the main issues of the sensitivity and uncertainty expected on the hydrologic modelling. Equally, the time step chosen is also important to nutrient dynamics. This study aims to evaluate the benefits of using both monthly and daily data in hydrologic models, and to address the issues of catchment scale when using the two hydrologic models, the Soil and Water Assessment Tool (SWAT), and Catchment Runoff Attenuation Flux Tool (CRAFT), by comparing the difference between SWAT and CRAFT in flow pathways and sediment transport. The models are different in terms of complexity, therefore the poster will discuss the strengths and weakness of the models. Also we can show the problems of calibration and how the models can be used to support catchment modelling.

  5. Hydrologic Modeling at the National Water Center: Operational Implementation of the WRF-Hydro Model to support National Weather Service Hydrology

    NASA Astrophysics Data System (ADS)

    Cosgrove, B.; Gochis, D.; Clark, E. P.; Cui, Z.; Dugger, A. L.; Fall, G. M.; Feng, X.; Fresch, M. A.; Gourley, J. J.; Khan, S.; Kitzmiller, D.; Lee, H. S.; Liu, Y.; McCreight, J. L.; Newman, A. J.; Oubeidillah, A.; Pan, L.; Pham, C.; Salas, F.; Sampson, K. M.; Smith, M.; Sood, G.; Wood, A.; Yates, D. N.; Yu, W.; Zhang, Y.

    2015-12-01

    The National Weather Service (NWS) National Water Center(NWC) is collaborating with the NWS National Centers for Environmental Prediction (NCEP) and the National Center for Atmospheric Research (NCAR) to implement a first-of-its-kind operational instance of the Weather Research and Forecasting (WRF)-Hydro model over the Continental United States (CONUS) and contributing drainage areas on the NWS Weather and Climate Operational Supercomputing System (WCOSS) supercomputer. The system will provide seamless, high-resolution, continuously cycling forecasts of streamflow and other hydrologic outputs of value from both deterministic- and ensemble-type runs. WRF-Hydro will form the core of the NWC national water modeling strategy, supporting NWS hydrologic forecast operations along with emergency response and water management efforts of partner agencies. Input and output from the system will be comprehensively verified via the NWC Water Resource Evaluation Service. Hydrologic events occur on a wide range of temporal scales, from fast acting flash floods, to long-term flow events impacting water supply. In order to capture this range of events, the initial operational WRF-Hydro configuration will feature 1) hourly analysis runs, 2) short-and medium-range deterministic forecasts out to two day and ten day horizons and 3) long-range ensemble forecasts out to 30 days. All three of these configurations are underpinned by a 1km execution of the NoahMP land surface model, with channel routing taking place on 2.67 million NHDPlusV2 catchments covering the CONUS and contributing areas. Additionally, the short- and medium-range forecasts runs will feature surface and sub-surface routing on a 250m grid, while the hourly analyses will feature this same 250m routing in addition to nudging-based assimilation of US Geological Survey (USGS) streamflow observations. A limited number of major reservoirs will be configured within the model to begin to represent the first-order impacts of

  6. A Distributed Hydrological model Forced by DIMP2 Data and the WRF Mesoscale model

    NASA Astrophysics Data System (ADS)

    Wayand, N. E.

    2010-12-01

    Forecasted warming over the next century will drastically reduce seasonal snowpack that provides 40% of the world’s drinking water. With increased climate warming, droughts may occur more frequently, which will increase society’s reliance on this same summer snowpack as a water supply. This study aims to reduce driving data errors that lead to poor simulations of snow ablation and accumulation, and streamflow. Results from the Distributed Hydrological Model Intercomparison Project Phase 2 (DMIP2) project using the Distributed Hydrology Soil and Vegetation Model (DHSVM) highlighted the critical need for accurate driving data that distributed models require. Currently, the meteorological driving data for distributed hydrological models commonly rely on interpolation techniques between a network of observational stations, as well as historical monthly means. This method is limited by two significant issues: snowpack is stored at high elevations, where interpolation techniques perform poorly due to sparse observations, and historic climatological means may be unsuitable in a changing climate. Mesoscale models may provide a physically-based approach to supplement surface observations over high-elevation terrain. Initial results have shown that while temperature lapse rates are well represented by multiple mesoscale models, significant precipitation biases are dependent on the particular model microphysics. We evaluate multiple methods of downscaling surface variables from the Weather and Research Forecasting (WRF) model that are then used to drive DHSVM over the North Fork American River basin in California. A comparison between each downscaled driving data set and paired DHSVM results to observations will determine how much improvement in simulated streamflow and snowpack are gained at the expense of each additional degree of downscaling. Our results from DMIP2 will be used as a benchmark for the best available DHSVM run using all available observational data. The

  7. Fusing Unmanned Aerial Vehicle Imagery with High Resolution Hydrologic Modeling (Invited)

    NASA Astrophysics Data System (ADS)

    Vivoni, E. R.; Pierini, N.; Schreiner-McGraw, A.; Anderson, C.; Saripalli, S.; Rango, A.

    2013-12-01

    After decades of development and applications, high resolution hydrologic models are now common tools in research and increasingly used in practice. More recently, high resolution imagery from unmanned aerial vehicles (UAVs) that provide information on land surface properties have become available for civilian applications. Fusing the two approaches promises to significantly advance the state-of-the-art in terms of hydrologic modeling capabilities. This combination will also challenge assumptions on model processes, parameterizations and scale as land surface characteristics (~0.1 to 1 m) may now surpass traditional model resolutions (~10 to 100 m). Ultimately, predictions from high resolution hydrologic models need to be consistent with the observational data that can be collected from UAVs. This talk will describe our efforts to develop, utilize and test the impact of UAV-derived topographic and vegetation fields on the simulation of two small watersheds in the Sonoran and Chihuahuan Deserts at the Santa Rita Experimental Range (Green Valley, AZ) and the Jornada Experimental Range (Las Cruces, NM). High resolution digital terrain models, image orthomosaics and vegetation species classification were obtained from a fixed wing airplane and a rotary wing helicopter, and compared to coarser analyses and products, including Light Detection and Ranging (LiDAR). We focus the discussion on the relative improvements achieved with UAV-derived fields in terms of terrain-hydrologic-vegetation analyses and summer season simulations using the TIN-based Real-time Integrated Basin Simulator (tRIBS) model. Model simulations are evaluated at each site with respect to a high-resolution sensor network consisting of six rain gauges, forty soil moisture and temperature profiles, four channel runoff flumes, a cosmic-ray soil moisture sensor and an eddy covariance tower over multiple summer periods. We also discuss prospects for the fusion of high resolution models with novel

  8. SPRUCE Representing Northern Peatland Microtopography and Hydrology within the Community Land Model: Modeling Archive

    DOE Data Explorer

    Shi, X. [Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tennessee, U.S.A.; Thornton, P. E. [Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tennessee, U.S.A.; Ricciuto, D. M. [Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tennessee, U.S.A.; Hanson, P. J. [Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tennessee, U.S.A.; Mao, J. [Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tennessee, U.S.A.; Sebestyen, S. [Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tennessee, U.S.A.; Griffiths, N. A. [Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tennessee, U.S.A.; Bisht, G. [Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tennessee, U.S.A.

    2016-09-01

    Here we provide model code, inputs, outputs and evaluation datasets for a new configuration of the Community Land Model (CLM) for SPRUCE, which includes a fully prognostic water table calculation for SPRUCE. Our structural and process changes to CLM focus on modifications needed to represent the hydrologic cycle of bogs environment with perched water tables, as well as distinct hydrologic dynamics and vegetation communities of the raised hummock and sunken hollow microtopography characteristic of SPRUCE and other peatland bogs. The modified model was parameterized and independently evaluated against observations from an ombrotrophic raised-dome bog in northern Minnesota (S1-Bog), the site for the Spruce and Peatland Responses Under Climatic and Environmental Change experiment (SPRUCE).

  9. How much expert knowledge is it worth to put in conceptual hydrological models?

    NASA Astrophysics Data System (ADS)

    Antonetti, Manuel; Zappa, Massimiliano

    2017-04-01

    Both modellers and experimentalists agree on using expert knowledge to improve our conceptual hydrological simulations on ungauged basins. However, they use expert knowledge differently for both hydrologically mapping the landscape and parameterising a given hydrological model. Modellers use generally very simplified (e.g. topography-based) mapping approaches and put most of the knowledge for constraining the model by defining parameter and process relational rules. In contrast, experimentalists tend to invest all their detailed and qualitative knowledge about processes to obtain a spatial distribution of areas with different dominant runoff generation processes (DRPs) as realistic as possible, and for defining plausible narrow value ranges for each model parameter. Since, most of the times, the modelling goal is exclusively to simulate runoff at a specific site, even strongly simplified hydrological classifications can lead to satisfying results due to equifinality of hydrological models, overfitting problems and the numerous uncertainty sources affecting runoff simulations. Therefore, to test to which extent expert knowledge can improve simulation results under uncertainty, we applied a typical modellers' modelling framework relying on parameter and process constraints defined based on expert knowledge to several catchments on the Swiss Plateau. To map the spatial distribution of the DRPs, mapping approaches with increasing involvement of expert knowledge were used. Simulation results highlighted the potential added value of using all the expert knowledge available on a catchment. Also, combinations of event types and landscapes, where even a simplified mapping approach can lead to satisfying results, were identified. Finally, the uncertainty originated by the different mapping approaches was compared with the one linked to meteorological input data and catchment initial conditions.

  10. Creating Data and Modeling Enabled Hydrology Instruction Using Collaborative Approach

    NASA Astrophysics Data System (ADS)

    Merwade, V.; Rajib, A.; Ruddell, B. L.; Fox, S.

    2017-12-01

    Hydrology instruction typically involves teaching of the hydrologic cycle and the processes associated with it such as precipitation, evapotranspiration, infiltration, runoff generation and hydrograph analysis. With the availability of observed and remotely sensed data related to many hydrologic fluxes, there is an opportunity to use these data for place based learning in hydrology classrooms. However, it is not always easy and possible for an instructor to complement an existing hydrology course with new material that requires both the time and technical expertise, which the instructor may not have. The work presented here describes an effort where students create the data and modeling driven instruction material as a part of their class assignment for a hydrology course at Purdue University. The data driven hydrology education project within Science Education Resources Center (SERC) is used as a platform to publish and share the instruction material so it can be used by future students in the same course or any other course anywhere in the world. Students in the class were divided into groups, and each group was assigned a topic such as precipitation, evapotranspiration, streamflow, flow duration curve and frequency analysis. Each student in the group was then asked to get data and do some analysis for an area with specific landuse characteristic such as urban, rural and agricultural. The student contribution were then organized into learning units such that someone can do a flow duration curve analysis or flood frequency analysis to see how it changes for rural area versus urban area. The hydrology education project within SERC cyberinfrastructure enables any other instructor to adopt this material as is or through modification to suit his/her place based instruction needs.

  11. A coupled synoptic-hydrological model for climate change impact assessment

    NASA Astrophysics Data System (ADS)

    Wilby, Robert; Greenfield, Brian; Glenny, Cathy

    1994-01-01

    A coupled atmospheric-hydrological model is presented. Sequences of daily rainfall occurrence for the 20 year period 1971-1990 at sites in the British Isles are related to the Lamb's Weather Types (LWT) by using conditional probabilities. Time series of circulation patterns and hence rainfall were then generated using a Markov representation of matrices of transition probabilities between weather types. The resultant precipitation data were used as input to a semidistributed catchment model to simulate daily flows. The combined model successfully reproduced aspects of the daily weather, precipitation and flow regimes. A range of synoptic scenarios were further investigated with particular reference to low flows in the River Coln, UK. The modelling approach represents a means of translating general circulation model (GCM) climate change predictions at the macro-scale into hydrological concerns at the catchment scale.

  12. A high-resolution European dataset for hydrologic modeling

    NASA Astrophysics Data System (ADS)

    Ntegeka, Victor; Salamon, Peter; Gomes, Goncalo; Sint, Hadewij; Lorini, Valerio; Thielen, Jutta

    2013-04-01

    There is an increasing demand for large scale hydrological models not only in the field of modeling the impact of climate change on water resources but also for disaster risk assessments and flood or drought early warning systems. These large scale models need to be calibrated and verified against large amounts of observations in order to judge their capabilities to predict the future. However, the creation of large scale datasets is challenging for it requires collection, harmonization, and quality checking of large amounts of observations. For this reason, only a limited number of such datasets exist. In this work, we present a pan European, high-resolution gridded dataset of meteorological observations (EFAS-Meteo) which was designed with the aim to drive a large scale hydrological model. Similar European and global gridded datasets already exist, such as the HadGHCND (Caesar et al., 2006), the JRC MARS-STAT database (van der Goot and Orlandi, 2003) and the E-OBS gridded dataset (Haylock et al., 2008). However, none of those provide similarly high spatial resolution and/or a complete set of variables to force a hydrologic model. EFAS-Meteo contains daily maps of precipitation, surface temperature (mean, minimum and maximum), wind speed and vapour pressure at a spatial grid resolution of 5 x 5 km for the time period 1 January 1990 - 31 December 2011. It furthermore contains calculated radiation, which is calculated by using a staggered approach depending on the availability of sunshine duration, cloud cover and minimum and maximum temperature, and evapotranspiration (potential evapotranspiration, bare soil and open water evapotranspiration). The potential evapotranspiration was calculated using the Penman-Monteith equation with the above-mentioned meteorological variables. The dataset was created as part of the development of the European Flood Awareness System (EFAS) and has been continuously updated throughout the last years. The dataset variables are used as

  13. A comparison of hydrologic models for ecological flows and water availability

    USGS Publications Warehouse

    Caldwell, Peter V; Kennen, Jonathan G.; Sun, Ge; Kiang, Julie E.; Butcher, John B; Eddy, Michelle C; Hay, Lauren E.; LaFontaine, Jacob H.; Hain, Ernie F.; Nelson, Stacy C; McNulty, Steve G

    2015-01-01

    Robust hydrologic models are needed to help manage water resources for healthy aquatic ecosystems and reliable water supplies for people, but there is a lack of comprehensive model comparison studies that quantify differences in streamflow predictions among model applications developed to answer management questions. We assessed differences in daily streamflow predictions by four fine-scale models and two regional-scale monthly time step models by comparing model fit statistics and bias in ecologically relevant flow statistics (ERFSs) at five sites in the Southeastern USA. Models were calibrated to different extents, including uncalibrated (level A), calibrated to a downstream site (level B), calibrated specifically for the site (level C) and calibrated for the site with adjusted precipitation and temperature inputs (level D). All models generally captured the magnitude and variability of observed streamflows at the five study sites, and increasing level of model calibration generally improved performance. All models had at least 1 of 14 ERFSs falling outside a +/−30% range of hydrologic uncertainty at every site, and ERFSs related to low flows were frequently over-predicted. Our results do not indicate that any specific hydrologic model is superior to the others evaluated at all sites and for all measures of model performance. Instead, we provide evidence that (1) model performance is as likely to be related to calibration strategy as it is to model structure and (2) simple, regional-scale models have comparable performance to the more complex, fine-scale models at a monthly time step.

  14. On modeling complex interplay in small-scale self-organized socio-hydrological systems

    NASA Astrophysics Data System (ADS)

    Muneepeerakul, Rachata

    2017-04-01

    Successful and sustainable socio-hydrological systems, as in any coupled natural human-systems, require effective governance, which depends on the existence of proper infrastructure (both hard and soft). Recent work has addressed systems in which resource users and the organization responsible for maintaining the infrastructure are separate entities. However, many socio-hydrological systems, especially in developing countries, are small and without such formal division of labor; rather, such division of labor typically arises from self-organization within the population. In this work, we modify and mathematically operationalize a conceptual framework by developing a system of differential equations that capture the strategic behavior within such a self-organized population, its interplay with infrastructure characteristics and hydrological dynamics, and feedbacks between these elements. The model yields a number of insightful conditions related to long-term sustainability and collapse of the socio-hydrological system in the form of relationships between biophysical and social factors. These relationships encapsulate nonlinear interactions of these factors. The modeling framework is grounded in a solid conceptual foundation upon which additional modifications and realism can be built for potential reconciliation between socio-hydrology with other related fields and further applications.

  15. Towards Improved High-Resolution Land Surface Hydrologic Reanalysis Using a Physically-Based Hydrologic Model and Data Assimilation

    NASA Astrophysics Data System (ADS)

    Shi, Y.; Davis, K. J.; Zhang, F.; Duffy, C.; Yu, X.

    2014-12-01

    A coupled physically based land surface hydrologic model, Flux-PIHM, has been developed by incorporating a land surface scheme into the Penn State Integrated Hydrologic Model (PIHM). The land surface scheme is adapted from the Noah land surface model. Flux-PIHM has been implemented and manually calibrated at the Shale Hills watershed (0.08 km2) in central Pennsylvania. Model predictions of discharge, point soil moisture, point water table depth, sensible and latent heat fluxes, and soil temperature show good agreement with observations. When calibrated only using discharge, and soil moisture and water table depth at one point, Flux-PIHM is able to resolve the observed 101 m scale soil moisture pattern at the Shale Hills watershed when an appropriate map of soil hydraulic properties is provided. A Flux-PIHM data assimilation system has been developed by incorporating EnKF for model parameter and state estimation. Both synthetic and real data assimilation experiments have been performed at the Shale Hills watershed. Synthetic experiment results show that the data assimilation system is able to simultaneously provide accurate estimates of multiple parameters. In the real data experiment, the EnKF estimated parameters and manually calibrated parameters yield similar model performances, but the EnKF method significantly decreases the time and labor required for calibration. The data requirements for accurate Flux-PIHM parameter estimation via data assimilation using synthetic observations have been tested. Results show that by assimilating only in situ outlet discharge, soil water content at one point, and the land surface temperature averaged over the whole watershed, the data assimilation system can provide an accurate representation of watershed hydrology. Observations of these key variables are available with national and even global spatial coverage (e.g., MODIS surface temperature, SMAP soil moisture, and the USGS gauging stations). National atmospheric reanalysis

  16. Flexibility on storage-release based distributed hydrologic modeling with object-oriented approach

    USDA-ARS?s Scientific Manuscript database

    With the availability of advanced hydrologic data in the public domain such as remotely sensed and climate change scenario data, there is a need for a modeling framework that is capable of using these data to simulate and extend hydrologic processes with multidisciplinary approaches for sustainable ...

  17. Study of Parameters And Methods of LL-Ⅳ Distributed Hydrological Model in DMIP2

    NASA Astrophysics Data System (ADS)

    Li, L.; Wu, J.; Wang, X.; Yang, C.; Zhao, Y.; Zhou, H.

    2008-05-01

    : The Physics-based distributed hydrological model is considered as an important developing period from the traditional experience-hydrology to the physical hydrology. The Hydrology Laboratory of the NOAA National Weather Service proposes the first and second phase of the Distributed Model Intercomparison Project (DMIP),that it is a great epoch-making work. LL distributed hydrological model has been developed to the fourth generation since it was established in 1997 on the Fengman-I district reservoir area (11000 km2).The LL-I distributed hydrological model was born with the applications of flood control system in the Fengman-I in China. LL-II was developed under the DMIP-I support, it is combined with GIS, RS, GPS, radar rainfall measurement.LL-III was established along with Applications of LL Distributed Model on Water Resources which was supported by the 973-projects of The Ministry of Science and Technology of the People's Republic of China. LL-Ⅳ was developed to face China's water problem. Combined with Blue River and the Baron Fork River basin of DMIP-II, the convection-diffusion equation of non-saturated and saturated seepage was derived from the soil water dynamics and continuous equation. In view of the technical characteristics of the model, the advantage of using convection-diffusion equation to compute confluence overall is longer period of predictable, saving memory space, fast budgeting, clear physical concepts, etc. The determination of parameters of hydrological model is the key, including experience coefficients and parameters of physical parameters. There are methods of experience, inversion, and the optimization to determine the model parameters, and each has advantages and disadvantages. This paper briefly introduces the LL-Ⅳ distribution hydrological model equations, and particularly introduces methods of parameters determination and simulation results on Blue River and Baron Fork River basin for DMIP-II. The soil moisture diffusion

  18. Integrated surface/subsurface permafrost thermal hydrology: Model formulation and proof-of-concept simulations

    DOE PAGES

    Painter, Scott L.; Coon, Ethan T.; Atchley, Adam L.; ...

    2016-08-11

    The need to understand potential climate impacts and feedbacks in Arctic regions has prompted recent interest in modeling of permafrost dynamics in a warming climate. A new fine-scale integrated surface/subsurface thermal hydrology modeling capability is described and demonstrated in proof-of-concept simulations. The new modeling capability combines a surface energy balance model with recently developed three-dimensional subsurface thermal hydrology models and new models for nonisothermal surface water flows and snow distribution in the microtopography. Surface water flows are modeled using the diffusion wave equation extended to include energy transport and phase change of ponded water. Variation of snow depth in themore » microtopography, physically the result of wind scour, is also modeled heuristically with a diffusion wave equation. The multiple surface and subsurface processes are implemented by leveraging highly parallel community software. Fully integrated thermal hydrology simulations on the tilted open book catchment, an important test case for integrated surface/subsurface flow modeling, are presented. Fine-scale 100-year projections of the integrated permafrost thermal hydrological system on an ice wedge polygon at Barrow Alaska in a warming climate are also presented. Finally, these simulations demonstrate the feasibility of microtopography-resolving, process-rich simulations as a tool to help understand possible future evolution of the carbon-rich Arctic tundra in a warming climate.« less

  19. Modeling the Hydrologic Processes of a Permeable Pavement ...

    EPA Pesticide Factsheets

    A permeable pavement system can capture stormwater to reduce runoff volume and flow rate, improve onsite groundwater recharge, and enhance pollutant controls within the site. A new unit process model for evaluating the hydrologic performance of a permeable pavement system has been developed in this study. The developed model can continuously simulate infiltration through the permeable pavement surface, exfiltration from the storage to the surrounding in situ soils, and clogging impacts on infiltration/exfiltration capacity at the pavement surface and the bottom of the subsurface storage unit. The exfiltration modeling component simulates vertical and horizontal exfiltration independently based on Darcy’s formula with the Green-Ampt approximation. The developed model can be arranged with physically-based modeling parameters, such as hydraulic conductivity, Manning’s friction flow parameters, saturated and field capacity volumetric water contents, porosity, density, etc. The developed model was calibrated using high-frequency observed data. The modeled water depths are well matched with the observed values (R2 = 0.90). The modeling results show that horizontal exfiltration through the side walls of the subsurface storage unit is a prevailing factor in determining the hydrologic performance of the system, especially where the storage unit is developed in a long, narrow shape; or with a high risk of bottom compaction and clogging. This paper presents unit

  20. An interdisciplinary swat ecohydrological model to define catchment-scale hydrologic partitioning

    NASA Astrophysics Data System (ADS)

    Shope, C. L.; Maharjan, G. R.; Tenhunen, J.; Seo, B.; Kim, K.; Riley, J.; Arnhold, S.; Koellner, T.; Ok, Y. S.; Peiffer, S.; Kim, B.; Park, J.-H.; Huwe, B.

    2013-06-01

    Land use and climate change have long been implicated in modifying ecosystem services, such as water quality and water yield, biodiversity, and agricultural production. To account for future effects on ecosystem services, the integration of physical, biological, economic, and social data over several scales must be implemented to assess the effects on natural resource availability and use. Our objective is to assess the capability of the SWAT model to capture short-duration monsoonal rainfall-runoff processes in complex mountainous terrain under rapid, event-driven processes in a monsoonal environment. To accomplish this, we developed a unique quality-control gap-filling algorithm for interpolation of high frequency meteorological data. We used a novel multi-location, multi-optimization calibration technique to improve estimations of catchment-wide hydrologic partitioning. We calibrated the interdisciplinary model to a combination of statistical, hydrologic, and plant growth metrics. In addition, we used multiple locations of different drainage area, aspect, elevation, and geologic substrata distributed throughout the catchment. Results indicate scale-dependent sensitivity of hydrologic partitioning and substantial influence of engineered features. While our model accurately reproduced observed discharge variability, the addition of hydrologic and plant growth objective functions identified the importance of culverts in catchment-wide flow distribution. The results of this study provide a valuable resource to describe landscape controls and their implication on discharge, sediment transport, and nutrient loading. This study also shows the challenges of applying the SWAT model to complex terrain and extreme environments. By incorporating anthropogenic features into modeling scenarios, we can greatly enhance our understanding of the hydroecological impacts on ecosystem services.

  1. Development and comparison in uncertainty assessment based Bayesian modularization method in hydrological modeling

    NASA Astrophysics Data System (ADS)

    Li, Lu; Xu, Chong-Yu; Engeland, Kolbjørn

    2013-04-01

    SummaryWith respect to model calibration, parameter estimation and analysis of uncertainty sources, various regression and probabilistic approaches are used in hydrological modeling. A family of Bayesian methods, which incorporates different sources of information into a single analysis through Bayes' theorem, is widely used for uncertainty assessment. However, none of these approaches can well treat the impact of high flows in hydrological modeling. This study proposes a Bayesian modularization uncertainty assessment approach in which the highest streamflow observations are treated as suspect information that should not influence the inference of the main bulk of the model parameters. This study includes a comprehensive comparison and evaluation of uncertainty assessments by our new Bayesian modularization method and standard Bayesian methods using the Metropolis-Hastings (MH) algorithm with the daily hydrological model WASMOD. Three likelihood functions were used in combination with standard Bayesian method: the AR(1) plus Normal model independent of time (Model 1), the AR(1) plus Normal model dependent on time (Model 2) and the AR(1) plus Multi-normal model (Model 3). The results reveal that the Bayesian modularization method provides the most accurate streamflow estimates measured by the Nash-Sutcliffe efficiency and provide the best in uncertainty estimates for low, medium and entire flows compared to standard Bayesian methods. The study thus provides a new approach for reducing the impact of high flows on the discharge uncertainty assessment of hydrological models via Bayesian method.

  2. Evaluation TRMM Rainfall Data In Hydrological Modeling For An Ungaged In Lhasa River Basin

    NASA Astrophysics Data System (ADS)

    Ji, H. J.; Liu, J.

    2017-12-01

    Evaluation TRMM Rainfall Data In Hydrological Modeling For An Ungaged In Lhasa River BasinHaijuan Ji1* Jintao Liu1,2 Shanshan Xu1___________________ 1College of Hydrology and Water Resources, Hohai University, Nanjing 210098, People's Republic of China 2State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing 210098, People's Republic of China ___________________ * Corresponding author. Tel.: +86-025-83786973; Fax: +86-025-83786606. E-mail address: Hhu201510@163.com (H.J. Ji). Abstract: The Tibetan Plateau plays an important role in regulating the regional hydrological processes due to its high elevations and being the headwaters of many major Asian river basins. If familiar with the distribution of hydrological characteristics, will help us improve the level of development and utilization the water resources. However, there exist glaciers and snow with few sites. It is significance for us to understand the glacier and snow hydrological process in order to recognize the evolution of water resources in the Tibetan. This manuscript takes Lhasa River as the study area, taking use of ground, remote sensing and assimilation data, taking advantage of high precision TRMM precipitation data and MODIS snow cover data, first, according to the data from ground station evaluation of TRMM data in the application of the accuracy of the Lhasa River, and based on MODIS data fusion of multi source microwave snow making cloudless snow products, which are used for discriminant and analysis glacier and snow regulation mechanism on day scale, add snow and glacier unit into xinanjing model, this model can simulate the study region's runoff evolution, parameter sensitivity even spatial variation of hydrological characteristics the next ten years on region grid scale. The results of hydrological model in Lhasa River can simulate the glacier and snow runoff variation in high cold region better, to enhance the predictive ability of the spring

  3. Modelling exploration of non-stationary hydrological system

    NASA Astrophysics Data System (ADS)

    Kim, Kue Bum; Kwon, Hyun-Han; Han, Dawei

    2015-04-01

    Traditional hydrological modelling assumes that the catchment does not change with time (i.e., stationary conditions) which means the model calibrated for the historical period is valid for the future period. However, in reality, due to change of climate and catchment conditions this stationarity assumption may not be valid in the future. It is a challenge to make the hydrological model adaptive to the future climate and catchment conditions that are not observable at the present time. In this study a lumped conceptual rainfall-runoff model called IHACRES was applied to a catchment in southwest England. Long observation data from 1961 to 2008 were used and seasonal calibration (in this study only summer period is further explored because it is more sensitive to climate and land cover change than the other three seasons) has been done since there are significant seasonal rainfall patterns. We expect that the model performance can be improved by calibrating the model based on individual seasons. The data is split into calibration and validation periods with the intention of using the validation period to represent the future unobserved situations. The success of the non-stationary model will depend not only on good performance during the calibration period but also the validation period. Initially, the calibration is based on changing the model parameters with time. Methodology is proposed to adapt the parameters using the step forward and backward selection schemes. However, in the validation both the forward and backward multiple parameter changing models failed. One problem is that the regression with time is not reliable since the trend may not be in a monotonic linear relationship with time. The second issue is that changing multiple parameters makes the selection process very complex which is time consuming and not effective in the validation period. As a result, two new concepts are explored. First, only one parameter is selected for adjustment while the other

  4. One-Water Hydrologic Flow Model (MODFLOW-OWHM)

    USGS Publications Warehouse

    Hanson, Randall T.; Boyce, Scott E.; Schmid, Wolfgang; Hughes, Joseph D.; Mehl, Steffen W.; Leake, Stanley A.; Maddock, Thomas; Niswonger, Richard G.

    2014-01-01

    The One-Water Hydrologic Flow Model (MF-OWHM) is a MODFLOW-based integrated hydrologic flow model (IHM) that is the most complete version, to date, of the MODFLOW family of hydrologic simulators needed for the analysis of a broad range of conjunctive-use issues. Conjunctive use is the combined use of groundwater and surface water. MF-OWHM allows the simulation, analysis, and management of nearly all components of human and natural water movement and use in a physically-based supply-and-demand framework. MF-OWHM is based on the Farm Process for MODFLOW-2005 (MF-FMP2) combined with Local Grid Refinement (LGR) for embedded models to allow use of the Farm Process (FMP) and Streamflow Routing (SFR) within embedded grids. MF-OWHM also includes new features such as the Surface-water Routing Process (SWR), Seawater Intrusion (SWI), and Riparian Evapotrasnpiration (RIP-ET), and new solvers such as Newton-Raphson (NWT) and nonlinear preconditioned conjugate gradient (PCGN). This IHM also includes new connectivities to expand the linkages for deformation-, flow-, and head-dependent flows. Deformation-dependent flows are simulated through the optional linkage to simulated land subsidence with a vertically deforming mesh. Flow-dependent flows now include linkages between the new SWR with SFR and FMP, as well as connectivity with embedded models for SFR and FMP through LGR. Head-dependent flows now include a modified Hydrologic Flow Barrier Package (HFB) that allows optional transient HFB capabilities, and the flow between any two layers that are adjacent along a depositional or erosional boundary or displaced along a fault. MF-OWHM represents a complete operational hydrologic model that fully links the movement and use of groundwater, surface water, and imported water for consumption by irrigated agriculture, but also of water used in urban areas and by natural vegetation. Supply and demand components of water use are analyzed under demand-driven and supply

  5. Development of a coupled model of a distributed hydrological model and a rice growth model for optimizing irrigation schedule

    NASA Astrophysics Data System (ADS)

    Tsujimoto, Kumiko; Homma, Koki; Koike, Toshio; Ohta, Tetsu

    2013-04-01

    A coupled model of a distributed hydrological model and a rice growth model was developed in this study. The distributed hydrological model used in this study is the Water and Energy Budget-based Distributed Hydrological Model (WEB-DHM) developed by Wang et al. (2009). This model includes a modified SiB2 (Simple Biosphere Model, Sellers et al., 1996) and the Geomorphology-Based Hydrological Model (GBHM) and thus it can physically calculate both water and energy fluxes. The rice growth model used in this study is the Simulation Model for Rice-Weather relations (SIMRIW) - rainfed developed by Homma et al. (2009). This is an updated version of the original SIMRIW (Horie et al., 1987) and can calculate rice growth by considering the yield reduction due to water stress. The purpose of the coupling is the integration of hydrology and crop science to develop a tool to support decision making 1) for determining the necessary agricultural water resources and 2) for allocating limited water resources to various sectors. The efficient water use and optimal water allocation in the agricultural sector are necessary to balance supply and demand of limited water resources. In addition, variations in available soil moisture are the main reasons of variations in rice yield. In our model, soil moisture and the Leaf Area Index (LAI) are calculated inside SIMRIW-rainfed so that these variables can be simulated dynamically and more precisely based on the rice than the more general calculations is the original WEB-DHM. At the same time by coupling SIMRIW-rainfed with WEB-DHM, lateral flow of soil water, increases in soil moisture and reduction of river discharge due to the irrigation, and its effects on the rice growth can be calculated. Agricultural information such as planting date, rice cultivar, fertilization amount are given in a fully distributed manner. The coupled model was validated using LAI and soil moisture in a small basin in western Cambodia (Sangker River Basin). This

  6. The One-Water Hydrologic Flow Model - The next generation in fully integrated hydrologic simulation software

    NASA Astrophysics Data System (ADS)

    Boyce, S. E.; Hanson, R. T.

    2015-12-01

    The One-Water Hydrologic Flow Model (MF-OWHM) is a MODFLOW-based integrated hydrologic flow model that is the most complete version, to date, of the MODFLOW family of hydrologic simulators needed for the analysis of a broad range of conjunctive-use issues. MF-OWHM fully links the movement and use of groundwater, surface water, and imported water for consumption by agriculture and natural vegetation on the landscape, and for potable and other uses within a supply-and-demand framework. MF-OWHM is based on the Farm Process for MODFLOW-2005 combined with Local Grid Refinement, Streamflow Routing, Surface-water Routing Process, Seawater Intrusion, Riparian Evapotranspiration, and the Newton-Raphson solver. MF-OWHM also includes linkages for deformation-, flow-, and head-dependent flows; additional observation and parameter options for higher-order calibrations; and redesigned code for facilitation of self-updating models and faster simulation run times. The next version of MF-OWHM, currently under development, will include a new surface-water operations module that simulates dynamic reservoir operations, the conduit flow process for karst aquifers and leaky pipe networks, a new subsidence and aquifer compaction package, and additional features and enhancements to enable more integration and cross communication between traditional MODFLOW packages. By retaining and tracking the water within the hydrosphere, MF-OWHM accounts for "all of the water everywhere and all of the time." This philosophy provides more confidence in the water accounting by the scientific community and provides the public a foundation needed to address wider classes of problems such as evaluation of conjunctive-use alternatives and sustainability analysis, including potential adaptation and mitigation strategies, and best management practices. By Scott E. Boyce and Randall T. Hanson

  7. Wavelet-based multiscale performance analysis: An approach to assess and improve hydrological models

    NASA Astrophysics Data System (ADS)

    Rathinasamy, Maheswaran; Khosa, Rakesh; Adamowski, Jan; ch, Sudheer; Partheepan, G.; Anand, Jatin; Narsimlu, Boini

    2014-12-01

    The temporal dynamics of hydrological processes are spread across different time scales and, as such, the performance of hydrological models cannot be estimated reliably from global performance measures that assign a single number to the fit of a simulated time series to an observed reference series. Accordingly, it is important to analyze model performance at different time scales. Wavelets have been used extensively in the area of hydrological modeling for multiscale analysis, and have been shown to be very reliable and useful in understanding dynamics across time scales and as these evolve in time. In this paper, a wavelet-based multiscale performance measure for hydrological models is proposed and tested (i.e., Multiscale Nash-Sutcliffe Criteria and Multiscale Normalized Root Mean Square Error). The main advantage of this method is that it provides a quantitative measure of model performance across different time scales. In the proposed approach, model and observed time series are decomposed using the Discrete Wavelet Transform (known as the à trous wavelet transform), and performance measures of the model are obtained at each time scale. The applicability of the proposed method was explored using various case studies-both real as well as synthetic. The synthetic case studies included various kinds of errors (e.g., timing error, under and over prediction of high and low flows) in outputs from a hydrologic model. The real time case studies investigated in this study included simulation results of both the process-based Soil Water Assessment Tool (SWAT) model, as well as statistical models, namely the Coupled Wavelet-Volterra (WVC), Artificial Neural Network (ANN), and Auto Regressive Moving Average (ARMA) methods. For the SWAT model, data from Wainganga and Sind Basin (India) were used, while for the Wavelet Volterra, ANN and ARMA models, data from the Cauvery River Basin (India) and Fraser River (Canada) were used. The study also explored the effect of the

  8. Full implementation of a distributed hydrological model based on check dam trapped sediment volumes

    NASA Astrophysics Data System (ADS)

    Bussi, Gianbattista; Francés, Félix

    2014-05-01

    Lack of hydrometeorological data is one of the most compelling limitations to the implementation of distributed environmental models. Mediterranean catchments, in particular, are characterised by high spatial variability of meteorological phenomena and soil characteristics, which may prevents from transferring model calibrations from a fully gauged catchment to a totally o partially ungauged one. For this reason, new sources of data are required in order to extend the use of distributed models to non-monitored or low-monitored areas. An important source of information regarding the hydrological and sediment cycle is represented by sediment deposits accumulated at the bottom of reservoirs. Since the 60s, reservoir sedimentation volumes were used as proxy data for the estimation of inter-annual total sediment yield rates, or, in more recent years, as a reference measure of the sediment transport for sediment model calibration and validation. Nevertheless, the possibility of using such data for constraining the calibration of a hydrological model has not been exhaustively investigated so far. In this study, the use of nine check dam reservoir sedimentation volumes for hydrological and sedimentological model calibration and spatio-temporal validation was examined. Check dams are common structures in Mediterranean areas, and are a potential source of spatially distributed information regarding both hydrological and sediment cycle. In this case-study, the TETIS hydrological and sediment model was implemented in a medium-size Mediterranean catchment (Rambla del Poyo, Spain) by taking advantage of sediment deposits accumulated behind the check dams located in the catchment headwaters. Reservoir trap efficiency was taken into account by coupling the TETIS model with a pond trap efficiency model. The model was calibrated by adjusting some of its parameters in order to reproduce the total sediment volume accumulated behind a check dam. Then, the model was spatially validated

  9. Modeling Pre- and Post- Wildfire Hydrologic Response to Vegetation Change in the Valles Caldera National Preserve, NM

    NASA Astrophysics Data System (ADS)

    Gregory, A. E.; Benedict, K. K.; Zhang, S.; Savickas, J.

    2017-12-01

    Large scale, high severity wildfires in forests have become increasingly prevalent in the western United States due to fire exclusion. Although past work has focused on the immediate consequences of wildfire (ie. runoff magnitude and debris flow), little has been done to understand the post wildfire hydrologic consequences of vegetation regrowth. Furthermore, vegetation is often characterized by static parameterizations within hydrological models. In order to understand the temporal relationship between hydrologic processes and revegetation, we modularized and partially automated the hydrologic modeling process to increase connectivity between remotely sensed data, the Virtual Watershed Platform (a data management resource, called the VWP), input meteorological data, and the Precipitation-Runoff Modeling System (PRMS). This process was used to run simulations in the Valles Caldera of NM, an area impacted by the 2011 Las Conchas Fire, in PRMS before and after the Las Conchas to evaluate hydrologic process changes. The modeling environment addressed some of the existing challenges faced by hydrological modelers. At present, modelers are somewhat limited in their ability to push the boundaries of hydrologic understanding. Specific issues faced by modelers include limited computational resources to model processes at large spatial and temporal scales, data storage capacity and accessibility from the modeling platform, computational and time contraints for experimental modeling, and the skills to integrate modeling software in ways that have not been explored. By taking an interdisciplinary approach, we were able to address some of these challenges by leveraging the skills of hydrologic, data, and computer scientists; and the technical capabilities provided by a combination of on-demand/high-performance computing, distributed data, and cloud services. The hydrologic modeling process was modularized to include options for distributing meteorological data, parameter space

  10. Modeling summer month hydrological drought probabilities in the United States using antecedent flow conditions

    USGS Publications Warehouse

    Austin, Samuel H.; Nelms, David L.

    2017-01-01

    Climate change raises concern that risks of hydrological drought may be increasing. We estimate hydrological drought probabilities for rivers and streams in the United States (U.S.) using maximum likelihood logistic regression (MLLR). Streamflow data from winter months are used to estimate the chance of hydrological drought during summer months. Daily streamflow data collected from 9,144 stream gages from January 1, 1884 through January 9, 2014 provide hydrological drought streamflow probabilities for July, August, and September as functions of streamflows during October, November, December, January, and February, estimating outcomes 5-11 months ahead of their occurrence. Few drought prediction methods exploit temporal links among streamflows. We find MLLR modeling of drought streamflow probabilities exploits the explanatory power of temporally linked water flows. MLLR models with strong correct classification rates were produced for streams throughout the U.S. One ad hoc test of correct prediction rates of September 2013 hydrological droughts exceeded 90% correct classification. Some of the best-performing models coincide with areas of high concern including the West, the Midwest, Texas, the Southeast, and the Mid-Atlantic. Using hydrological drought MLLR probability estimates in a water management context can inform understanding of drought streamflow conditions, provide warning of future drought conditions, and aid water management decision making.

  11. The ICARDA agro-climate tool

    USDA-ARS?s Scientific Manuscript database

    A Visual Basic agro-climate application by climatologists at the International Center for Agricultural Research in the Dry Areas and the U.S. Department of Agriculture is described here. The database from which the application derives climate information consists of weather generator parameters der...

  12. The ICARDA Agro-Climate Tool

    USDA-ARS?s Scientific Manuscript database

    A Visual Basic agro-climate application developed by climatologists at the International Center for Agricultural Research in the Dry Areas and the U.S. Department of Agriculture is described here. The database from which the application derives climate information consists of weather generator param...

  13. Assessment of NASA's Physiographic and Meteorological Datasets as Input to HSPF and SWAT Hydrological Models

    NASA Technical Reports Server (NTRS)

    Alacron, Vladimir J.; Nigro, Joseph D.; McAnally, William H.; OHara, Charles G.; Engman, Edwin Ted; Toll, David

    2011-01-01

    This paper documents the use of simulated Moderate Resolution Imaging Spectroradiometer land use/land cover (MODIS-LULC), NASA-LIS generated precipitation and evapo-transpiration (ET), and Shuttle Radar Topography Mission (SRTM) datasets (in conjunction with standard land use, topographical and meteorological datasets) as input to hydrological models routinely used by the watershed hydrology modeling community. The study is focused in coastal watersheds in the Mississippi Gulf Coast although one of the test cases focuses in an inland watershed located in northeastern State of Mississippi, USA. The decision support tools (DSTs) into which the NASA datasets were assimilated were the Soil Water & Assessment Tool (SWAT) and the Hydrological Simulation Program FORTRAN (HSPF). These DSTs are endorsed by several US government agencies (EPA, FEMA, USGS) for water resources management strategies. These models use physiographic and meteorological data extensively. Precipitation gages and USGS gage stations in the region were used to calibrate several HSPF and SWAT model applications. Land use and topographical datasets were swapped to assess model output sensitivities. NASA-LIS meteorological data were introduced in the calibrated model applications for simulation of watershed hydrology for a time period in which no weather data were available (1997-2006). The performance of the NASA datasets in the context of hydrological modeling was assessed through comparison of measured and model-simulated hydrographs. Overall, NASA datasets were as useful as standard land use, topographical , and meteorological datasets. Moreover, NASA datasets were used for performing analyses that the standard datasets could not made possible, e.g., introduction of land use dynamics into hydrological simulations

  14. Information and complexity measures for hydrologic model evaluation

    USDA-ARS?s Scientific Manuscript database

    Hydrological models are commonly evaluated through the residual-based performance measures such as the root-mean square error or efficiency criteria. Such measures, however, do not evaluate the degree of similarity of patterns in simulated and measured time series. The objective of this study was to...

  15. Examination of Soil Moisture Retrieval Using SIR-C Radar Data and a Distributed Hydrological Model

    NASA Technical Reports Server (NTRS)

    Hsu, A. Y.; ONeill, P. E.; Wood, E. F.; Zion, M.

    1997-01-01

    A major objective of soil moisture-related hydrological-research during NASA's SIR-C/X-SAR mission was to determine and compare soil moisture patterns within humid watersheds using SAR data, ground-based measurements, and hydrologic modeling. Currently available soil moisture-inversion methods using active microwave data are only accurate when applied to bare and slightly vegetated surfaces. Moreover, as the surface dries down, the number of pixels that can provide estimated soil moisture by these radar inversion methods decreases, leading to less accuracy and, confidence in the retrieved soil moisture fields at the watershed scale. The impact of these errors in microwave- derived soil moisture on hydrological modeling of vegetated watersheds has yet to be addressed. In this study a coupled water and energy balance model operating within a topographic framework is used to predict surface soil moisture for both bare and vegetated areas. In the first model run, the hydrological model is initialized using a standard baseflow approach, while in the second model run, soil moisture values derived from SIR-C radar data are used for initialization. The results, which compare favorably with ground measurements, demonstrate the utility of combining radar-derived surface soil moisture information with basin-scale hydrological modeling.

  16. Physically Based Mountain Hydrological Modelling using Reanalysis Data in Patagonia

    NASA Astrophysics Data System (ADS)

    Krogh, S.; Pomeroy, J. W.; McPhee, J. P.

    2013-05-01

    Remote regions in South America are often characterized by insufficient observations of meteorology for robust hydrological model operation. Yet water resources must be quantified, understood and predicted in order to develop effective water management policies. Here, we developed a physically based hydrological model for a major river in Patagonia using the modular Cold Regions Hydrological Modelling Platform (CRHM) in order to better understand hydrological processes leading to streamflow generation in this remote region. The Baker River -with the largest mean annual streamflow in Chile-, drains snowy mountains, glaciers, wet forests, peat and semi-arid pampas into a large lake. Meteorology over the basin is poorly monitored in that there are no high elevation weather stations and stations at low elevations are sparsely distributed, only measure temperature and rainfall and are poorly maintained. Streamflow in the basin is gauged at several points where there are high quality hydrometric stations. In order to quantify the impact of meteorological data scarcity on prediction, two additional data sources were used: the ERA-Interim (ECMWF Re-analyses) and CFSR (Climate Forecast System Reanalysis) atmospheric reanalyses. Precipitation temporal distribution and magnitude from the models and observations were compared and the reanalysis data was found to have about three times the number of days with precipitation than the observations did. Better synchronization between measured peak streamflows and modeled precipitation was found compared to observed precipitation. These differences are attributed to: (i) lack of any snowfall observations (so precipitation records does not consider snowfall events) and (ii) available rainfall observations are all located at low altitude (<500 m a.s.l), and miss the occurrence of high altitude precipitation events. CRHM parameterization was undertaken by using local physiographic and vegetation characteristics where available and

  17. Development of an Integrated Hydrologic Modeling System for Rainfall-Runoff Simulation

    NASA Astrophysics Data System (ADS)

    Lu, B.; Piasecki, M.

    2008-12-01

    This paper aims to present the development of an integrated hydrological model which involves functionalities of digital watershed processing, online data retrieval, hydrologic simulation and post-event analysis. The proposed system is intended to work as a back end to the CUAHSI HIS cyberinfrastructure developments. As a first step into developing this system, a physics-based distributed hydrologic model PIHM (Penn State Integrated Hydrologic Model) is wrapped into OpenMI(Open Modeling Interface and Environment ) environment so as to seamlessly interact with OpenMI compliant meteorological models. The graphical user interface is being developed from the openGIS application called MapWindows which permits functionality expansion through the addition of plug-ins. . Modules required to set up through the GUI workboard include those for retrieving meteorological data from existing database or meteorological prediction models, obtaining geospatial data from the output of digital watershed processing, and importing initial condition and boundary condition. They are connected to the OpenMI compliant PIHM to simulate rainfall-runoff processes and includes a module for automatically displaying output after the simulation. Online databases are accessed through the WaterOneFlow web services, and the retrieved data are either stored in an observation database(OD) following the schema of Observation Data Model(ODM) in case for time series support, or a grid based storage facility which may be a format like netCDF or a grid-based-data database schema . Specific development steps include the creation of a bridge to overcome interoperability issue between PIHM and the ODM, as well as the embedding of TauDEM (Terrain Analysis Using Digital Elevation Models) into the model. This module is responsible for developing watershed and stream network using digital elevation models. Visualizing and editing geospatial data is achieved by the usage of MapWinGIS, an ActiveX control developed

  18. Sensitivity analysis for the coupling of a subglacial hydrology model with a 3D ice-sheet model.

    NASA Astrophysics Data System (ADS)

    Bertagna, L.; Perego, M.; Gunzburger, M.; Hoffman, M. J.; Price, S. F.

    2017-12-01

    When studying the movement of ice sheets, one of the most important factors that influence the velocity of the ice is the amount of friction against the bedrock. Usually, this is modeled by a friction coefficient that may depend on the bed geometry and other quantities, such as the temperature and/or water pressure at the ice-bedrock interface. These quantities are often assumed to be known (either by indirect measurements or by means of parameter estimation) and constant in time. Here, we present a 3D computational model for the simulation of the ice dynamics which incorporates a 2D model proposed by Hewitt (2011) for the subglacial water pressure. The hydrology model is fully coupled with the Blatter-Pattyn model for the ice sheet flow, as the subglacial water pressure appears in the expression for the ice friction coefficient, and the ice velocity appears as a source term in the hydrology model. We will present results on real geometries, and perform a sensitivity analysis with respect to the hydrology model parameters.

  19. Development of a Coupled Hydrological/Sediment Yield Model for a Watershed at Regional Level

    NASA Technical Reports Server (NTRS)

    Rajbhandaril, Narayan; Crosson, William; Tsegaye, Teferi; Coleman, Tommy; Liu, Yaping; Soman, Vishwas

    1998-01-01

    Development of a hydrologic model for the study of environmental conservation requires a comprehensive understanding of individual-storm affecting hydrologic and sedimentologic processes. The hydrologic models that we are currently coupling are the Simulator for Hydrology and Energy Exchange at the Land Surface (SHEELS) and the Distributed Runoff Model (DRUM). SHEELS runs continuously to estimate surface energy fluxes and sub-surface soil water fluxes, while DRUM operates during and following precipitation events to predict surface runoff and peak flow through channel routing. The lateral re-distribution of surface water determined by DRUM is passed to SHEELS, which then adjusts soil water contents throughout the profile. The model SHEELS is well documented in Smith et al. (1993) and Laymen and Crosson (1995). The model DRUM is well documented in Vieux et al. (1990) and Vieux and Gauer (1994). The coupled hydrologic model, SHEELS/DRUM, does not simulate sedimentologic processes. The simulation of the sedimentologic process is important for environmental conservation planning and management. Therefore, we attempted to develop a conceptual frame work for coupling a sediment yield model with SHEELS/DRUM to estimate individual-storm sediment yield from a watershed at a regional level. The sediment yield model that will be used for this study is the Universal Soil Loss Equation (USLE) with some modifications to enable the model to predict individual-storm sediment yield. The predicted sediment yield does not include wind erosion and erosion caused by irrigation and snow melt. Units used for this study are those given by Foster et al. (1981) for SI units.

  20. Operational Testing of Satellite based Hydrological Model (SHM)

    NASA Astrophysics Data System (ADS)

    Gaur, Srishti; Paul, Pranesh Kumar; Singh, Rajendra; Mishra, Ashok; Gupta, Praveen Kumar; Singh, Raghavendra P.

    2017-04-01

    Incorporation of the concept of transposability in model testing is one of the prominent ways to check the credibility of a hydrological model. Successful testing ensures ability of hydrological models to deal with changing conditions, along with its extrapolation capacity. For a newly developed model, a number of contradictions arises regarding its applicability, therefore testing of credibility of model is essential to proficiently assess its strength and limitations. This concept emphasizes to perform 'Hierarchical Operational Testing' of Satellite based Hydrological Model (SHM), a newly developed surface water-groundwater coupled model, under PRACRITI-2 program initiated by Space Application Centre (SAC), Ahmedabad. SHM aims at sustainable water resources management using remote sensing data from Indian satellites. It consists of grid cells of 5km x 5km resolution and comprises of five modules namely: Surface Water (SW), Forest (F), Snow (S), Groundwater (GW) and Routing (ROU). SW module (functions in the grid cells with land cover other than forest and snow) deals with estimation of surface runoff, soil moisture and evapotranspiration by using NRCS-CN method, water balance and Hragreaves method, respectively. The hydrology of F module is dependent entirely on sub-surface processes and water balance is calculated based on it. GW module generates baseflow (depending on water table variation with the level of water in streams) using Boussinesq equation. ROU module is grounded on a cell-to-cell routing technique based on the principle of Time Variant Spatially Distributed Direct Runoff Hydrograph (SDDH) to route the generated runoff and baseflow by different modules up to the outlet. For this study Subarnarekha river basin, flood prone zone of eastern India, has been chosen for hierarchical operational testing scheme which includes tests under stationary as well as transitory conditions. For this the basin has been divided into three sub-basins using three flow

  1. Calibration of hydrological model with programme PEST

    NASA Astrophysics Data System (ADS)

    Brilly, Mitja; Vidmar, Andrej; Kryžanowski, Andrej; Bezak, Nejc; Šraj, Mojca

    2016-04-01

    PEST is tool based on minimization of an objective function related to the root mean square error between the model output and the measurement. We use "singular value decomposition", section of the PEST control file, and Tikhonov regularization method for successfully estimation of model parameters. The PEST sometimes failed if inverse problems were ill-posed, but (SVD) ensures that PEST maintains numerical stability. The choice of the initial guess for the initial parameter values is an important issue in the PEST and need expert knowledge. The flexible nature of the PEST software and its ability to be applied to whole catchments at once give results of calibration performed extremely well across high number of sub catchments. Use of parallel computing version of PEST called BeoPEST was successfully useful to speed up calibration process. BeoPEST employs smart slaves and point-to-point communications to transfer data between the master and slaves computers. The HBV-light model is a simple multi-tank-type model for simulating precipitation-runoff. It is conceptual balance model of catchment hydrology which simulates discharge using rainfall, temperature and estimates of potential evaporation. Version of HBV-light-CLI allows the user to run HBV-light from the command line. Input and results files are in XML form. This allows to easily connecting it with other applications such as pre and post-processing utilities and PEST itself. The procedure was applied on hydrological model of Savinja catchment (1852 km2) and consists of twenty one sub-catchments. Data are temporary processed on hourly basis.

  2. Towards real-time assimilation of crowdsourced observations in hydrological modeling

    NASA Astrophysics Data System (ADS)

    Mazzoleni, Maurizio; Verlaan, Martin; Alfonso, Leonardo; Norbiato, Daniele; Monego, Martina; Ferri, Michele; Solomatine, Dimitri

    2016-04-01

    The continued technological advances have stimulated the spread of low-cost sensors that can be used by citizens to provide crowdsourced observations (CO) of different hydrological variables. An example of such low-cost sensors is a staff gauge connected to a QR code on which people can read the water level indication and send the measurement via a mobile phone application. The goal of this study is to assess the combined effect of the assimilation of CO coming from a distributed network of low-cost sensors, and the existing streamflow observations from physical sensors, on the performance of a semi-distributed hydrological model. The methodology is applied to the Bacchiglione catchment, North East of Italy, where an early warning system is used by the Alto Adriatico Water Authority to issue forecasted water level along the river network which cross important cities such as Vicenza and Padua. In this study, forecasted precipitation values are used as input in the hydrological model to estimate the simulated streamflow hydrograph used as boundary condition for the hydraulic model. Observed precipitation values are used to generate realistic synthetic streamflow values with various characteristics of arrival frequency and accuracy, to simulate CO coming at irregular time steps. These observations are assimilated into the semi-distributed model using a Kalman filter based method. The results of this study show that CO, asynchronous in time and with variable accuracy, can still improve flood prediction when integrated in hydrological models. When both physical and low-cost sensors are located at the same places, the assimilation of CO gives the same model improvement than the assimilation of physical observations only for high number of non-intermittent sensors. However, the integration of observations from low-cost sensors and single physical sensors can improve the flood prediction even when small a number of intermittent CO are available. This study is part of the

  3. Plant adaptive behaviour in hydrological models (Invited)

    NASA Astrophysics Data System (ADS)

    van der Ploeg, M. J.; Teuling, R.

    2013-12-01

    Models that will be able to cope with future precipitation and evaporation regimes need a solid base that describes the essence of the processes involved [1]. Micro-behaviour in the soil-vegetation-atmosphere system may have a large impact on patterns emerging at larger scales. A complicating factor in the micro-behaviour is the constant interaction between vegetation and geology in which water plays a key role. The resilience of the coupled vegetation-soil system critically depends on its sensitivity to environmental changes. As a result of environmental changes vegetation may wither and die, but such environmental changes may also trigger gene adaptation. Constant exposure to environmental stresses, biotic or abiotic, influences plant physiology, gene adaptations, and flexibility in gene adaptation [2-6]. Gene expression as a result of different environmental conditions may profoundly impact drought responses across the same plant species. Differences in response to an environmental stress, has consequences for the way species are currently being treated in models (single plant to global scale). In particular, model parameters that control root water uptake and plant transpiration are generally assumed to be a property of the plant functional type. Assigning plant functional types does not allow for local plant adaptation to be reflected in the model parameters, nor does it allow for correlations that might exist between root parameters and soil type. Models potentially provide a means to link root water uptake and transport to large scale processes (e.g. Rosnay and Polcher 1998, Feddes et al. 2001, Jung 2010), especially when powered with an integrated hydrological, ecological and physiological base. We explore the experimental evidence from natural vegetation to formulate possible alternative modeling concepts. [1] Seibert, J. 2000. Multi-criteria calibration of a conceptual runoff model using a genetic algorithm. Hydrology and Earth System Sciences 4(2): 215

  4. A method for coupling a parameterization of the planetary boundary layer with a hydrologic model

    NASA Technical Reports Server (NTRS)

    Lin, J. D.; Sun, Shu Fen

    1986-01-01

    Deardorff's parameterization of the planetary boundary layer is adapted to drive a hydrologic model. The method converts the atmospheric conditions measured at the anemometer height at one site to the mean values in the planetary boundary layer; it then uses the planetary boundary layer parameterization and the hydrologic variables to calculate the fluxes of momentum, heat and moisture at the atmosphere-land interface for a different site. A simplified hydrologic model is used for a simulation study of soil moisture and ground temperature on three different land surface covers. The results indicate that this method can be used to drive a spatially distributed hydrologic model by using observed data available at a meteorological station located on or nearby the site.

  5. Impact of different satellite soil moisture products on the predictions of a continuous distributed hydrological model

    NASA Astrophysics Data System (ADS)

    Laiolo, P.; Gabellani, S.; Campo, L.; Silvestro, F.; Delogu, F.; Rudari, R.; Pulvirenti, L.; Boni, G.; Fascetti, F.; Pierdicca, N.; Crapolicchio, R.; Hasenauer, S.; Puca, S.

    2016-06-01

    The reliable estimation of hydrological variables in space and time is of fundamental importance in operational hydrology to improve the flood predictions and hydrological cycle description. Nowadays remotely sensed data can offer a chance to improve hydrological models especially in environments with scarce ground based data. The aim of this work is to update the state variables of a physically based, distributed and continuous hydrological model using four different satellite-derived data (three soil moisture products and a land surface temperature measurement) and one soil moisture analysis to evaluate, even with a non optimal technique, the impact on the hydrological cycle. The experiments were carried out for a small catchment, in the northern part of Italy, for the period July 2012-June 2013. The products were pre-processed according to their own characteristics and then they were assimilated into the model using a simple nudging technique. The benefits on the model predictions of discharge were tested against observations. The analysis showed a general improvement of the model discharge predictions, even with a simple assimilation technique, for all the assimilation experiments; the Nash-Sutcliffe model efficiency coefficient was increased from 0.6 (relative to the model without assimilation) to 0.7, moreover, errors on discharge were reduced up to the 10%. An added value to the model was found in the rainfall season (autumn): all the assimilation experiments reduced the errors up to the 20%. This demonstrated that discharge prediction of a distributed hydrological model, which works at fine scale resolution in a small basin, can be improved with the assimilation of coarse-scale satellite-derived data.

  6. Stochastic Residual-Error Analysis For Estimating Hydrologic Model Predictive Uncertainty

    EPA Science Inventory

    A hybrid time series-nonparametric sampling approach, referred to herein as semiparametric, is presented for the estimation of model predictive uncertainty. The methodology is a two-step procedure whereby a distributed hydrologic model is first calibrated, then followed by brute ...

  7. Development of a biosphere hydrological model considering vegetation dynamics and its evaluation at basin scale under climate change

    NASA Astrophysics Data System (ADS)

    Li, Qiaoling; Ishidaira, Hiroshi

    2012-01-01

    SummaryThe biosphere and hydrosphere are intrinsically coupled. The scientific question is if there is a substantial change in one component such as vegetation cover, how will the other components such as transpiration and runoff generation respond, especially under climate change conditions? Stand-alone hydrological models have a detailed description of hydrological processes but do not sufficiently parameterize vegetation as a dynamic component. Dynamic global vegetation models (DGVMs) are able to simulate transient structural changes in major vegetation types but do not simulate runoff generation reliably. Therefore, both hydrological models and DGVMs have their limitations as well as advantages for addressing this question. In this study a biosphere hydrological model (LPJH) is developed by coupling a prominent DGVM (Lund-Postdam-Jena model referred to as LPJ) with a stand-alone hydrological model (HYMOD), with the objective of analyzing the role of vegetation in the hydrological processes at basin scale and evaluating the impact of vegetation change on the hydrological processes under climate change. The application and validation of the LPJH model to four basins representing a variety of climate and vegetation conditions shows that the performance of LPJH is much better than that of the original LPJ and is similar to that of stand-alone hydrological models for monthly and daily runoff simulation at the basin scale. It is argued that the LPJH model gives more reasonable hydrological simulation since it considers both the spatial variability of soil moisture and vegetation dynamics, which make the runoff generation mechanism more reliable. As an example, it is shown that changing atmospheric CO 2 content alone would result in runoff increases in humid basins and decreases in arid basins. Theses changes are mainly attributable to changes in transpiration driven by vegetation dynamics, which are not simulated in stand-alone hydrological models. Therefore LPJH

  8. Setting up a hydrological model based on global data for the Ayeyarwady basin in Myanmar

    NASA Astrophysics Data System (ADS)

    ten Velden, Corine; Sloff, Kees; Nauta, Tjitte

    2017-04-01

    The use of global datasets in local hydrological modelling can be of great value. It opens up the possibility to include data for areas where local data is not or only sparsely available. In hydrological modelling the existence of both static physical data such as elevation and land use, and dynamic meteorological data such as precipitation and temperature, is essential for setting up a hydrological model, but often such data is difficult to obtain at the local level. For the Ayeyarwady catchment in Myanmar a distributed hydrological model (Wflow: https://github.com/openstreams/wflow) was set up with only global datasets, as part of a water resources study. Myanmar is an emerging economy, which has only recently become more receptive to foreign influences. It has a very limited hydrometeorological measurement network, with large spatial and temporal gaps, and data that are of uncertain quality and difficult to obtain. The hydrological model was thus set up based on resampled versions of the SRTM digital elevation model, the GlobCover land cover dataset and the HWSD soil dataset. Three global meteorological datasets were assessed and compared for use in the hydrological model: TRMM, WFDEI and MSWEP. The meteorological datasets were assessed based on their conformity with several precipitation station measurements, and the overall model performance was assessed by calculating the NSE and RVE based on discharge measurements of several gauging stations. The model was run for the period 1979-2012 on a daily time step, and the results show an acceptable applicability of the used global datasets in the hydrological model. The WFDEI forcing dataset gave the best results, with a NSE of 0.55 at the outlet of the model and a RVE of 8.5%, calculated over the calibration period 2006-2012. As a general trend the modelled discharge at the upstream stations tends to be underestimated, and at the downstream stations slightly overestimated. The quality of the discharge measurements

  9. Hydrological modelling of the Chaohe Basin in China: Statistical model formulation and Bayesian inference

    NASA Astrophysics Data System (ADS)

    Yang, Jing; Reichert, Peter; Abbaspour, Karim C.; Yang, Hong

    2007-07-01

    SummaryCalibration of hydrologic models is very difficult because of measurement errors in input and response, errors in model structure, and the large number of non-identifiable parameters of distributed models. The difficulties even increase in arid regions with high seasonal variation of precipitation, where the modelled residuals often exhibit high heteroscedasticity and autocorrelation. On the other hand, support of water management by hydrologic models is important in arid regions, particularly if there is increasing water demand due to urbanization. The use and assessment of model results for this purpose require a careful calibration and uncertainty analysis. Extending earlier work in this field, we developed a procedure to overcome (i) the problem of non-identifiability of distributed parameters by introducing aggregate parameters and using Bayesian inference, (ii) the problem of heteroscedasticity of errors by combining a Box-Cox transformation of results and data with seasonally dependent error variances, (iii) the problems of autocorrelated errors, missing data and outlier omission with a continuous-time autoregressive error model, and (iv) the problem of the seasonal variation of error correlations with seasonally dependent characteristic correlation times. The technique was tested with the calibration of the hydrologic sub-model of the Soil and Water Assessment Tool (SWAT) in the Chaohe Basin in North China. The results demonstrated the good performance of this approach to uncertainty analysis, particularly with respect to the fulfilment of statistical assumptions of the error model. A comparison with an independent error model and with error models that only considered a subset of the suggested techniques clearly showed the superiority of the approach based on all the features (i)-(iv) mentioned above.

  10. Wetland Hydrology | Science Inventory | US EPA

    EPA Pesticide Factsheets

    This chapter discusses the state of the science in wetland hydrology by touching upon the major hydraulic and hydrologic processes in these complex ecosystems, their measurement/estimation techniques, and modeling methods. It starts with the definition of wetlands, their benefits and types, and explains the role and importance of hydrology on wetland functioning. The chapter continues with the description of wetland hydrologic terms and related estimation and modeling techniques. The chapter provides a quick but valuable information regarding hydraulics of surface and subsurface flow, groundwater seepage/discharge, and modeling groundwater/surface water interactions in wetlands. Because of the aggregated effects of the wetlands at larger scales and their ecosystem services, wetland hydrology at the watershed scale is also discussed in which we elaborate on the proficiencies of some of the well-known watershed models in modeling wetland hydrology. This chapter can serve as a useful reference for eco-hydrologists, wetland researchers and decision makers as well as watershed hydrology modelers. In this chapter, the importance of hydrology for wetlands and their functional role are discussed. Wetland hydrologic terms and the major components of water budget in wetlands and how they can be estimated/modeled are also presented. Although this chapter does not provide a comprehensive coverage of wetland hydrology, it provides a quick understanding of the basic co

  11. Hydrological modelling in sandstone rocks watershed

    NASA Astrophysics Data System (ADS)

    Ponížilová, Iva; Unucka, Jan

    2015-04-01

    The contribution is focused on the modelling of surface and subsurface runoff in the Ploučnice basin. The used rainfall-runoff model is HEC-HMS comprising of the method of SCS CN curves and a recession method. The geological subsurface consisting of sandstone is characterised by reduced surface runoff and, on the contrary, it contributes to subsurface runoff. The aim of this paper is comparison of the rate of influence of sandstone on reducing surface runoff. The recession method for subsurface runoff was used to determine the subsurface runoff. The HEC-HMS model allows semi- and fully distributed approaches to schematisation of the watershed and rainfall situations. To determine the volume of runoff the method of SCS CN curves is used, which results depend on hydrological conditions of the soils. The rainfall-runoff model assuming selection of so-called methods of event of the SCS-CN type is used to determine the hydrograph and peak flow rate based on simulation of surface runoff in precipitation exceeding the infiltration capacity of the soil. The recession method is used to solve the baseflow (subsurface) runoff. The method is based on the separation of hydrograph to direct runoff and subsurface or baseflow runoff. The study area for the simulation of runoff using the method of SCS CN curves to determine the hydrological transformation is the Ploučnice basin. The Ploučnice is a hydrologically significant river in the northern part of the Czech Republic, it is a right tributary of the Elbe river with a total basin area of 1.194 km2. The average value of CN curves for the Ploučnice basin is 72. The geological structure of the Ploučnice basin is predominantly formed by Mesozoic sandstone. Despite significant initial loss of rainfall the basin response to the causal rainfall was demonstrated by a rapid rise of the surface runoff from the watershed and reached culmination flow. Basically, only surface runoff occures in the catchment during the initial phase of

  12. GLOFRIM - A globally applicable framework for integrated hydrologic-hydrodynamic inundation modelling

    NASA Astrophysics Data System (ADS)

    Hoch, J. M.; Neal, J. C.; Baart, F.; Van Beek, L. P.; Winsemius, H.; Bates, P. D.; Bierkens, M. F.

    2017-12-01

    Currently, many approaches to provide detailed flood hazard and risk estimates are built upon specific hydrologic or hydrodynamic model routines. By applying these routines in stand-alone mode important processes can however not accurately be described. For instance, global hydrologic models run at coarse spatial resolution, not supporting the detailed simulation of flood hazard. Hydrodynamic models excel in the computations of open water flow dynamics, but dependent on specific runoff or observed discharge as input. In most cases hydrodynamic models are forced at the boundaries and thus cannot account for water sources within the model domain, limiting the simulation of inundation dynamics to reaches fed by upstream boundaries. Recently, Hoch et al. (HESS, 2017) coupled PCR-GLOBWB (PCR) with the hydrodynamic model Delft3D Flexible Mesh (DFM). By means of the Basic Model Interface both models were connected on a cell-by-cell basis, allowing for spatially explicit coupling. Model results showed that discharge simulations can profit from model coupling compared to stand-alone runs. As model results of a coupled simulation depend on the quality of the models, it would be worthwhile to allow a suite of models to be coupled. To facilitate this, we present GLOFRIM, a globally applicable framework for integrated hydrologic-hydrodynamic inundation modelling. In the current version coupling between PCR and both DFM and LISFLOOD-FP (LFP) can be established (Hoch et al., GMDD, 2017). First results show that differences between both hydrodynamic models are present in the timing of peak discharge which is most likely due to differences in channel-floodplain interactions and bathymetry processing. Having benchmarked inundation extent, LFP and DFM agree for around half of the inundated area which is attributable to variations in grid size. Results also indicate that, despite using identical boundary conditions and forcing, the schematization itself as well as internal processes

  13. Predicting the global warming potential of agro-ecosystems

    NASA Astrophysics Data System (ADS)

    Lehuger, S.; Gabrielle, B.; Larmanou, E.; Laville, P.; Cellier, P.; Loubet, B.

    2007-04-01

    Nitrous oxide, carbon dioxide and methane are the main biogenic greenhouse gases (GHG) contributing to the global warming potential (GWP) of agro-ecosystems. Evaluating the impact of agriculture on climate thus requires a capacity to predict the net exchanges of these gases in an integrated manner, as related to environmental conditions and crop management. Here, we used two year-round data sets from two intensively-monitored cropping systems in northern France to test the ability of the biophysical crop model CERES-EGC to simulate GHG exchanges at the plot-scale. The experiments involved maize and rapeseed crops on a loam and rendzina soils, respectively. The model was subsequently extrapolated to predict CO2 and N2O fluxes over an entire crop rotation. Indirect emissions (IE) arising from the production of agricultural inputs and from cropping operations were also added to the final GWP. One experimental site (involving a wheat-maize-barley rotation on a loamy soil) was a net source of GHG with a GWP of 350 kg CO2-C eq ha-1 yr-1, of which 75% were due to IE and 25% to direct N2O emissions. The other site (involving an oilseed rape-wheat-barley rotation on a rendzina) was a net sink of GHG for -250 kg CO2-C eq ha-1 yr-1, mainly due to a higher predicted C sequestration potential and C return from crops. Such modelling approach makes it possible to test various agronomic management scenarios, in order to design productive agro-ecosystems with low global warming impact.

  14. Feedback loops and temporal misalignment in component-based hydrologic modeling

    NASA Astrophysics Data System (ADS)

    Elag, Mostafa M.; Goodall, Jonathan L.; Castronova, Anthony M.

    2011-12-01

    In component-based modeling, a complex system is represented as a series of loosely integrated components with defined interfaces and data exchanges that allow the components to be coupled together through shared boundary conditions. Although the component-based paradigm is commonly used in software engineering, it has only recently been applied for modeling hydrologic and earth systems. As a result, research is needed to test and verify the applicability of the approach for modeling hydrologic systems. The objective of this work was therefore to investigate two aspects of using component-based software architecture for hydrologic modeling: (1) simulation of feedback loops between components that share a boundary condition and (2) data transfers between temporally misaligned model components. We investigated these topics using a simple case study where diffusion of mass is modeled across a water-sediment interface. We simulated the multimedia system using two model components, one for the water and one for the sediment, coupled using the Open Modeling Interface (OpenMI) standard. The results were compared with a more conventional numerical approach for solving the system where the domain is represented by a single multidimensional array. Results showed that the component-based approach was able to produce the same results obtained with the more conventional numerical approach. When the two components were temporally misaligned, we explored the use of different interpolation schemes to minimize mass balance error within the coupled system. The outcome of this work provides evidence that component-based modeling can be used to simulate complicated feedback loops between systems and guidance as to how different interpolation schemes minimize mass balance error introduced when components are temporally misaligned.

  15. Modeled hydrologic metrics show links between hydrology and the functional composition of stream assemblages.

    PubMed

    Patrick, Christopher J; Yuan, Lester L

    2017-07-01

    Flow alteration is widespread in streams, but current understanding of the effects of differences in flow characteristics on stream biological communities is incomplete. We tested hypotheses about the effect of variation in hydrology on stream communities by using generalized additive models to relate watershed information to the values of different flow metrics at gauged sites. Flow models accounted for 54-80% of the spatial variation in flow metric values among gauged sites. We then used these models to predict flow metrics in 842 ungauged stream sites in the mid-Atlantic United States that were sampled for fish, macroinvertebrates, and environmental covariates. Fish and macroinvertebrate assemblages were characterized in terms of a suite of metrics that quantified aspects of community composition, diversity, and functional traits that were expected to be associated with differences in flow characteristics. We related modeled flow metrics to biological metrics in a series of stressor-response models. Our analyses identified both drying and base flow instability as explaining 30-50% of the observed variability in fish and invertebrate community composition. Variations in community composition were related to variations in the prevalence of dispersal traits in invertebrates and trophic guilds in fish. The results demonstrate that we can use statistical models to predict hydrologic conditions at bioassessment sites, which, in turn, we can use to estimate relationships between flow conditions and biological characteristics. This analysis provides an approach to quantify the effects of spatial variation in flow metrics using readily available biomonitoring data. © 2017 by the Ecological Society of America.

  16. Probabilistic hydrological nowcasting using radar based nowcasting techniques and distributed hydrological models: application in the Mediterranean area

    NASA Astrophysics Data System (ADS)

    Poletti, Maria Laura; Pignone, Flavio; Rebora, Nicola; Silvestro, Francesco

    2017-04-01

    The exposure of the urban areas to flash-floods is particularly significant to Mediterranean coastal cities, generally densely-inhabited. Severe rainfall events often associated to intense and organized thunderstorms produced, during the last century, flash-floods and landslides causing serious damages to urban areas and in the worst events led to human losses. The temporal scale of these events has been observed strictly linked to the size of the catchments involved: in the Mediterranean area a great number of catchments that pass through coastal cities have a small drainage area (less than 100 km2) and a corresponding hydrologic response timescale in the order of a few hours. A suitable nowcasting chain is essential for the on time forecast of this kind of events. In fact meteorological forecast systems are unable to predict precipitation at the scale of these events, small both at spatial (few km) and temporal (hourly) scales. Nowcasting models, covering the time interval of the following two hours starting from the observation try to extend the predictability limits of the forecasting models in support of real-time flood alert system operations. This work aims to present the use of hydrological models coupled with nowcasting techniques. The nowcasting model PhaSt furnishes an ensemble of equi-probable future precipitation scenarios on time horizons of 1-3 h starting from the most recent radar observations. The coupling of the nowcasting model PhaSt with the hydrological model Continuum allows to forecast the flood with a few hours in advance. In this way it is possible to generate different discharge prediction for the following hours and associated return period maps: these maps can be used as a support in the decisional process for the warning system.

  17. Application of remote sensing to hydrology. [for the formulation of watershed behavior models

    NASA Technical Reports Server (NTRS)

    Ambaruch, R.; Simmons, J. W.

    1973-01-01

    Streamflow forecasting and hydrologic modelling are considered in a feasibility assessment of using the data produced by remote observation from space and/or aircraft to reduce the time and expense normally involved in achieving the ability to predict the hydrological behavior of an ungaged watershed. Existing watershed models are described, and both stochastic and parametric techniques are discussed towards the selection of a suitable simulation model. Technical progress and applications are reported and recommendations are made for additional research.

  18. Improved ground hydrology calculations for global climate models (GCMs) - Soil water movement and evapotranspiration

    NASA Technical Reports Server (NTRS)

    Abramopoulos, F.; Rosenzweig, C.; Choudhury, B.

    1988-01-01

    A physically based ground hydrology model is presented that includes the processes of transpiration, evaporation from intercepted precipitation and dew, evaporation from bare soil, infiltration, soil water flow, and runoff. Data from the Goddard Institute for Space Studies GCM were used as inputs for off-line tests of the model in four 8 x 10 deg regions, including Brazil, Sahel, Sahara, and India. Soil and vegetation input parameters were caculated as area-weighted means over the 8 x 10 deg gridbox; the resulting hydrological quantities were compared to ground hydrology model calculations performed on the 1 x 1 deg cells which comprise the 8 x 10 deg gridbox. Results show that the compositing procedure worked well except in the Sahel, where low soil water levels and a heterogeneous land surface produce high variability in hydrological quantities; for that region, a resolution better than 8 x 10 deg is needed.

  19. The impacts of precipitation amount simulation on hydrological modeling in Nordic watersheds

    NASA Astrophysics Data System (ADS)

    Li, Zhi; Brissette, Fancois; Chen, Jie

    2013-04-01

    Stochastic modeling of daily precipitation is very important for hydrological modeling, especially when no observed data are available. Precipitation is usually modeled by two component model: occurrence generation and amount simulation. For occurrence simulation, the most common method is the first-order two-state Markov chain due to its simplification and good performance. However, various probability distributions have been reported to simulate precipitation amount, and spatiotemporal differences exist in the applicability of different distribution models. Therefore, assessing the applicability of different distribution models is necessary in order to provide more accurate precipitation information. Six precipitation probability distributions (exponential, Gamma, Weibull, skewed normal, mixed exponential, and hybrid exponential/Pareto distributions) are directly and indirectly evaluated on their ability to reproduce the original observed time series of precipitation amount. Data from 24 weather stations and two watersheds (Chute-du-Diable and Yamaska watersheds) in the province of Quebec (Canada) are used for this assessment. Various indices or statistics, such as the mean, variance, frequency distribution and extreme values are used to quantify the performance in simulating the precipitation and discharge. Performance in reproducing key statistics of the precipitation time series is well correlated to the number of parameters of the distribution function, and the three-parameter precipitation models outperform the other models, with the mixed exponential distribution being the best at simulating daily precipitation. The advantage of using more complex precipitation distributions is not as clear-cut when the simulated time series are used to drive a hydrological model. While the advantage of using functions with more parameters is not nearly as obvious, the mixed exponential distribution appears nonetheless as the best candidate for hydrological modeling. The

  20. Integrating a reservoir regulation scheme into a spatially distributed hydrological model

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Zhao, Gang; Gao, Huilin; Naz, Bibi S.

    2016-12-01

    During the past several decades, numerous reservoirs have been built across the world for a variety of purposes such as flood control, irrigation, municipal/industrial water supplies, and hydropower generation. Consequently, natural streamflow timing and magnitude have been altered significantly by reservoir operations. In addition, the hydrological cycle can be modified by land use/land cover and climate changes. To understand the fine scale feedback between hydrological processes and water management decisions, a distributed hydrological model embedded with a reservoir component is of desire. In this study, a multi-purpose reservoir module with predefined complex operational rules was integrated into the Distributed Hydrologymore » Soil Vegetation Model (DHSVM). Conditional operating rules, which are designed to reduce flood risk and enhance water supply reliability, were adopted in this module. The performance of the integrated model was tested over the upper Brazos River Basin in Texas, where two U.S. Army Corps of Engineers reservoirs, Lake Whitney and Aquilla Lake, are located. The integrated DHSVM model was calibrated and validated using observed reservoir inflow, outflow, and storage data. The error statistics were summarized for both reservoirs on a daily, weekly, and monthly basis. Using the weekly reservoir storage for Lake Whitney as an example, the coefficients of determination (R2) and the Nash-Sutcliff Efficiency (NSE) are 0.85 and 0.75, respectively. These results suggest that this reservoir module has promise for use in sub-monthly hydrological simulations. Enabled with the new reservoir component, the DHSVM model provides a platform to support adaptive water resources management under the impacts of evolving anthropogenic activities and substantial environmental changes.« less

  1. Parameterization and Uncertainty Analysis of SWAT model in Hydrological Simulation of Chaohe River Basin

    NASA Astrophysics Data System (ADS)

    Jie, M.; Zhang, J.; Guo, B. B.

    2017-12-01

    As a typical distributed hydrological model, the SWAT model also has a challenge in calibrating parameters and analysis their uncertainty. This paper chooses the Chaohe River Basin China as the study area, through the establishment of the SWAT model, loading the DEM data of the Chaohe river basin, the watershed is automatically divided into several sub-basins. Analyzing the land use, soil and slope which are on the basis of the sub-basins and calculating the hydrological response unit (HRU) of the study area, after running SWAT model, the runoff simulation values in the watershed are obtained. On this basis, using weather data, known daily runoff of three hydrological stations, combined with the SWAT-CUP automatic program and the manual adjustment method are used to analyze the multi-site calibration of the model parameters. Furthermore, the GLUE algorithm is used to analyze the parameters uncertainty of the SWAT model. Through the sensitivity analysis, calibration and uncertainty study of SWAT, the results indicate that the parameterization of the hydrological characteristics of the Chaohe river is successful and feasible which can be used to simulate the Chaohe river basin.

  2. A WorkFlow Engine Oriented Modeling System for Hydrologic Sciences

    NASA Astrophysics Data System (ADS)

    Lu, B.; Piasecki, M.

    2009-12-01

    In recent years the use of workflow engines for carrying out modeling and data analyses tasks has gained increased attention in the science and engineering communities. Tasks like processing raw data coming from sensors and passing these raw data streams to filters for QA/QC procedures possibly require multiple and complicated steps that need to be repeated over and over again. A workflow sequence that carries out a number of steps of various complexity is an ideal approach to deal with these tasks because the sequence can be stored, called up and repeated over again and again. This has several advantages: for one it ensures repeatability of processing steps and with that provenance, an issue that is increasingly important in the science and engineering communities. It also permits the hand off of lengthy and time consuming tasks that can be error prone to a chain of processing actions that are carried out automatically thus reducing the chance for error on the one side and freeing up time to carry out other tasks on the other hand. This paper aims to present the development of a workflow engine embedded modeling system which allows to build up working sequences for carrying out numerical modeling tasks regarding to hydrologic science. Trident, which facilitates creating, running and sharing scientific data analysis workflows, is taken as the central working engine of the modeling system. Current existing functionalities of the modeling system involve digital watershed processing, online data retrieval, hydrologic simulation and post-event analysis. They are stored as sequences or modules respectively. The sequences can be invoked to implement their preset tasks in orders, for example, triangulating a watershed from raw DEM. Whereas the modules encapsulated certain functions can be selected and connected through a GUI workboard to form sequences. This modeling system is demonstrated by setting up a new sequence for simulating rainfall-runoff processes which

  3. Wetland Hydrology

    EPA Science Inventory

    This chapter discusses the state of the science in wetland hydrology by touching upon the major hydraulic and hydrologic processes in these complex ecosystems, their measurement/estimation techniques, and modeling methods. It starts with the definition of wetlands, their benefit...

  4. Translating hydrologically-relevant variables from the ice sheet model SICOPOLIS to the Greenland Analog Project hydrologic modeling domain

    NASA Astrophysics Data System (ADS)

    Vallot, Dorothée; Applegate, Patrick; Pettersson, Rickard

    2013-04-01

    Projecting future climate and ice sheet development requires sophisticated models and extensive field observations. Given the present state of our knowledge, it is very difficult to say what will happen with certainty. Despite the ongoing increase in atmospheric greenhouse gas concentrations, the possibility that a new ice sheet might form over Scandinavia in the far distant future cannot be excluded. The growth of a new Scandinavian Ice Sheet would have important consequences for buried nuclear waste repositories. The Greenland Analogue Project, initiated by the Swedish Nuclear Fuel and Waste Management Company (SKB), is working to assess the effects of a possible future ice sheet on groundwater flow by studying a constrained domain in Western Greenland by field measurements (including deep bedrock drilling in front of the ice sheet) combined with numerical modeling. To address the needs of the GAP project, we interpolated results from an ensemble of ice sheet model runs to the smaller and more finely resolved modeling domain used in the GAP project's hydrologic modeling. Three runs have been chosen with three fairly different positive degree-day factors among those that reproduced the modern ice margin at the borehole position. The interpolated results describe changes in hydrologically-relevant variables over two time periods, 115 ka to 80 ka, and 20 ka to 1 ka. In the first of these time periods, the ice margin advances over the model domain; in the second time period, the ice margin retreats over the model domain. The spatially-and temporally dependent variables that we treated include the ice thickness, basal melting rate, surface mass balance, basal temperature, basal thermal regime (frozen or thawed), surface temperature, and basal water pressure. The melt flux is also calculated.

  5. ENHANCING HYDROLOGICAL SIMULATION PROGRAM - FORTRAN MODEL CHANNEL HYDRAULIC REPRESENTATION

    EPA Science Inventory

    The Hydrological Simulation Program– FORTRAN (HSPF) is a comprehensive watershed model that employs depth-area - volume - flow relationships known as the hydraulic function table (FTABLE) to represent the hydraulic characteristics of stream channel cross-sections and reservoirs. ...

  6. GIS/RS-based Integrated Eco-hydrologic Modeling in the East River Basin, South China

    NASA Astrophysics Data System (ADS)

    Wang, Kai

    Land use/cover change (LUCC) has significantly altered the hydrologic system in the East River (Dongjiang) Basin. Quantitative modeling of hydrologic impacts of LUCC is of great importance for water supply, drought monitoring and integrated water resources management. An integrated eco-hydrologic modeling system of Distributed Monthly Water Balance Model (DMWBM), Surface Energy Balance System (SEBS) was developed with aid of GIS/RS to quantify LUCC, to conduct physically-based ET (evapotranspiration) mapping and to predict hydrologic impacts of LUCC. To begin with, in order to evaluate LUCC, understand implications of LUCC and provide boundary condition for the integrated eco-hydrologic modeling, firstly the long-term vegetation dynamics was investigated based on Normalized Difference Vegetation Index (NDVI) data, and then LUCC was analyzed with post-classification methods and finally LUCC prediction was conducted based on Markov chain model. The results demonstrate that the vegetation activities decreased significantly in summer over the years. Moreover, there were significant changes in land use/cover over the past two decades. Particularly there was a sharp increase of urban and built-up area and a significant decrease of grassland and cropland. All these indicate that human activities are intensive in the East River Basin and provide valuable information for constructing scenarios for studying hydrologic impacts of LUCC. The physically-remote-sensing-based Surface Energy Balance System (SEBS) was employed to estimate areal actual ET for a large area rather than traditional point measurements . The SEBS was enhanced for application in complex vegetated area. Then the inter-comparison with complimentary ET model and distributed monthly water balance model was made to validate the enhanced SEBS (ESEBS). The application and test of ESEBS show that it has a good accuracy both monthly and annually and can be effectively applied in the East River Basin. The results of

  7. Impact of spatio-temporal scale of adjustment on variational assimilation of hydrologic and hydrometeorological data in operational distributed hydrologic models

    NASA Astrophysics Data System (ADS)

    Lee, H.; Seo, D.; McKee, P.; Corby, R.

    2009-12-01

    One of the large challenges in data assimilation (DA) into distributed hydrologic models is to reduce the large degrees of freedom involved in the inverse problem to avoid overfitting. To assess the sensitivity of the performance of DA to the dimensionality of the inverse problem, we design and carry out real-world experiments in which the control vector in variational DA (VAR) is solved at different scales in space and time, e.g., lumped, semi-distributed, and fully-distributed in space, and hourly, 6 hourly, etc., in time. The size of the control vector is related to the degrees of freedom in the inverse problem. For the assessment, we use the prototype 4-dimenational variational data assimilator (4DVAR) that assimilates streamflow, precipitation and potential evaporation data into the NWS Hydrology Laboratory’s Research Distributed Hydrologic Model (HL-RDHM). In this talk, we present the initial results for a number of basins in Oklahoma and Texas.

  8. Modeling alpine grasslands with two integrated hydrologic models: a comparison of the different process representation in CATHY and GEOtop

    NASA Astrophysics Data System (ADS)

    Camporese, M.; Bertoldi, G.; Bortoli, E.; Wohlfahrt, G.

    2017-12-01

    Integrated hydrologic surface-subsurface models (IHSSMs) are increasingly used as prediction tools to solve simultaneously states and fluxes in and between multiple terrestrial compartments (e.g., snow cover, surface water, groundwater), in an attempt to tackle environmental problems in a holistic approach. Two such models, CATHY and GEOtop, are used in this study to investigate their capabilities to reproduce hydrological processes in alpine grasslands. The two models differ significantly in the complexity of the representation of the surface energy balance and the solution of Richards equation for water flow in the variably saturated subsurface. The main goal of this research is to show how these differences in process representation can lead to different predictions of hydrologic states and fluxes, in the simulation of an experimental site located in the Venosta Valley (South Tyrol, Italy). Here, a large set of relevant hydrological data (e.g., evapotranspiration, soil moisture) has been collected, with ground and remote sensing observations. The area of interest is part of a Long-Term Ecological Research (LTER) site, a mountain steep, heterogeneous slope, where the predominant land use types are meadow, pasture, and forest. The comparison between data and model predictions, as well as between simulations with the two IHSSMs, contributes to advance our understanding of the tradeoffs between different complexities in modeĺs process representation, model accuracy, and the ability to explain observed hydrological dynamics in alpine environments.

  9. Predicting hydrological response to forest changes by simple statistical models: the selection of the best indicator of forest changes with a hydrological perspective

    NASA Astrophysics Data System (ADS)

    Ning, D.; Zhang, M.; Ren, S.; Hou, Y.; Yu, L.; Meng, Z.

    2017-01-01

    Forest plays an important role in hydrological cycle, and forest changes will inevitably affect runoff across multiple spatial scales. The selection of a suitable indicator for forest changes is essential for predicting forest-related hydrological response. This study used the Meijiang River, one of the headwaters of the Poyang Lake as an example to identify the best indicator of forest changes for predicting forest change-induced hydrological responses. Correlation analysis was conducted first to detect the relationships between monthly runoff and its predictive variables including antecedent monthly precipitation and indicators for forest changes (forest coverage, vegetation indices including EVI, NDVI, and NDWI), and by use of the identified predictive variables that were most correlated with monthly runoff, multiple linear regression models were then developed. The model with best performance identified in this study included two independent variables -antecedent monthly precipitation and NDWI. It indicates that NDWI is the best indicator of forest change in hydrological prediction while forest coverage, the most commonly used indicator of forest change is insignificantly related to monthly runoff. This highlights the use of vegetation index such as NDWI to indicate forest changes in hydrological studies. This study will provide us with an efficient way to quantify the hydrological impact of large-scale forest changes in the Meijiang River watershed, which is crucial for downstream water resource management and ecological protection in the Poyang Lake basin.

  10. Enhancing a socio-hydrological modelling framework through field observations: a case study in India

    NASA Astrophysics Data System (ADS)

    den Besten, Nadja; Pande, Saket; Savenije, Huub H. G.

    2016-04-01

    Recently a smallholder socio-hydrological modelling framework was proposed and deployed to understand the underlying dynamics of Agrarian Crisis in Maharashtra state of India. It was found that cotton and sugarcane smallholders whom lack irrigation and storage techniques are most susceptible to distress. This study further expands the application of the modelling framework to other crops that are abundant in the state of Maharashtra, such as Paddy, Jowar and Soyabean to assess whether the conclusions on the possible causes behind smallholder distress still hold. Further, a fieldwork will be undertaken in March 2016 in the district of Pune. During the fieldwork 50 smallholders will be interviewed in which socio-hydrological assumptions on hydrology and capital equations and corresponding closure relationships, incorporated the current model, will be put to test. Besides the assumptions, the questionnaires will be used to better understand the hydrological reality of the farm holders, in terms of water usage and storage capacity. In combination with historical records on the smallholders' socio-economic data acquired over the last thirty years available through several NGOs in the region, socio-hydrological realism of the modelling framework will be enhanced. The preliminary outcomes of a desktop study show the possibilities of a water-centric modelling framework in understanding the constraints on smallholder farming. The results and methods described can be a first step guiding following research on the modelling framework: a start in testing the framework in multiple rural locations around the globe.

  11. Physically-based distributed hydrologic modeling of tropical catchments: Hypothesis testing on model formation and runoff generation

    NASA Astrophysics Data System (ADS)

    Abebe, N. A.; Ogden, F. L.

    2011-12-01

    Watersheds vary in their nature based on their geographic location, altitude, climate, geology, soils, and land use/land cover. These variations lead to differences in the conceptualization and formulation of hydrological models intended to represent the expected hydrological processes in a given catchment. Watersheds in the tropics are characterized by intensive and persistent biological activity and a large amount of rainfall. Our study focuses on the Agua Salud project catchments located in the Panama Canal Watershed, Panama, which have steep rolling topography, deep soils derived from weathered bedrock, and limited exposed bedrock. These catchments are also highly affected by soil cracks, decayed tree roots and animal burrows that form a network of preferential flow paths. One hypothesis is that these macropores conduct interflow during heavy rainfall, when a transient perched water table forms at a depth where the vertical hydraulic conductivity is significantly reduced near the bottom of the bioturbation layer. We have developed a physics-based, spatially distributed, multi-layered hydrologic model to simulate the dominant flow processes, including overland flow, channel flow, vertical matrix and non-Richards film flow, lateral downslope saturated matrix and non-Darcian pipe flow in the bioturbation layer and deep saturated groundwater flow. In our model formulation, we use the model to examine a variety of hydrological processes which we anticipate may occur. Emphasis is given to the modeling of the soil moisture dynamics in the bioturbation layer, development of lateral preferential flow and activation of the macropores and exchange of water at the interface between a bioturbation layer and a second layer below it. We consider interactions between surface water, ground water, channel water and perched water in the riparian zone cells with the aim of understanding likely runoff generation mechanisms. Results show that inclusion of as many different flow

  12. GIS embedded hydrological modeling: the SID&GRID project

    NASA Astrophysics Data System (ADS)

    Borsi, I.; Rossetto, R.; Schifani, C.

    2012-04-01

    The SID&GRID research project, started April 2010 and funded by Regione Toscana (Italy) under the POR FSE 2007-2013, aims to develop a Decision Support System (DSS) for water resource management and planning based on open source and public domain solutions. In order to quantitatively assess water availability in space and time and to support the planning decision processes, the SID&GRID solution consists of hydrological models (coupling 3D existing and newly developed surface- and ground-water and unsaturated zone modeling codes) embedded in a GIS interface, applications and library, where all the input and output data are managed by means of DataBase Management System (DBMS). A graphical user interface (GUI) to manage, analyze and run the SID&GRID hydrological models based on open source gvSIG GIS framework (Asociación gvSIG, 2011) and a Spatial Data Infrastructure to share and interoperate with distributed geographical data is being developed. Such a GUI is thought as a "master control panel" able to guide the user from pre-processing spatial and temporal data, running the hydrological models, and analyzing the outputs. To achieve the above-mentioned goals, the following codes have been selected and are being integrated: 1. Postgresql/PostGIS (PostGIS, 2011) for the Geo Data base Management System; 2. gvSIG with Sextante (Olaya, 2011) geo-algorithm library capabilities and Grass tools (GRASS Development Team, 2011) for the desktop GIS; 3. Geoserver and Geonetwork to share and discover spatial data on the web according to Open Geospatial Consortium; 4. new tools based on the Sextante GeoAlgorithm framework; 5. MODFLOW-2005 (Harbaugh, 2005) groundwater modeling code; 6. MODFLOW-LGR (Mehl and Hill 2005) for local grid refinement; 7. VSF (Thoms et al., 2006) for the variable saturated flow component; 8. new developed routines for overland flow; 9. new algorithms in Jython integrated in gvSIG to compute the net rainfall rate reaching the soil surface, as input for

  13. Development of efficient and cost-effective distributed hydrological modeling tool MWEasyDHM based on open-source MapWindow GIS

    NASA Astrophysics Data System (ADS)

    Lei, Xiaohui; Wang, Yuhui; Liao, Weihong; Jiang, Yunzhong; Tian, Yu; Wang, Hao

    2011-09-01

    Many regions are still threatened with frequent floods and water resource shortage problems in China. Consequently, the task of reproducing and predicting the hydrological process in watersheds is hard and unavoidable for reducing the risks of damage and loss. Thus, it is necessary to develop an efficient and cost-effective hydrological tool in China as many areas should be modeled. Currently, developed hydrological tools such as Mike SHE and ArcSWAT (soil and water assessment tool based on ArcGIS) show significant power in improving the precision of hydrological modeling in China by considering spatial variability both in land cover and in soil type. However, adopting developed commercial tools in such a large developing country comes at a high cost. Commercial modeling tools usually contain large numbers of formulas, complicated data formats, and many preprocessing or postprocessing steps that may make it difficult for the user to carry out simulation, thus lowering the efficiency of the modeling process. Besides, commercial hydrological models usually cannot be modified or improved to be suitable for some special hydrological conditions in China. Some other hydrological models are open source, but integrated into commercial GIS systems. Therefore, by integrating hydrological simulation code EasyDHM, a hydrological simulation tool named MWEasyDHM was developed based on open-source MapWindow GIS, the purpose of which is to establish the first open-source GIS-based distributed hydrological model tool in China by integrating modules of preprocessing, model computation, parameter estimation, result display, and analysis. MWEasyDHM provides users with a friendly manipulating MapWindow GIS interface, selectable multifunctional hydrological processing modules, and, more importantly, an efficient and cost-effective hydrological simulation tool. The general construction of MWEasyDHM consists of four major parts: (1) a general GIS module for hydrological analysis, (2) a

  14. Total Nitrogen Concentrations in Surface Water of Typical Agro- and Forest Ecosystems in China, 2004-2009

    PubMed Central

    Xu, Zhiwei; Zhang, Xinyu; Xie, Juan; Yuan, Guofu; Tang, Xinzhai; Sun, Xiaomin; Yu, Guirui

    2014-01-01

    We assessed the total nitrogen (N) concentrations of 28 still surface water (lake and pond), and 42 flowing surface water (river), monitoring sites under 29 typical terrestrial ecosystems of the Chinese Ecosystem Research Network (CERN) using monitoring data collected between 2004 and 2009. The results showed that the median total N concentrations of still surface water were significantly higher in the agro- (1.5 mg·L−1) and oasis agro- ecosystems (1.8 mg·L−1) than in the forest ecosystems (1.0 mg·L−1). This was also the case for flowing surface water, with total N concentrations of 2.4 mg·L−1, 1.8 mg·L−1 and 0.5 mg·L−1 for the agro-, oasis agro- and forest ecosystems, respectively. In addition, more than 50% of the samples in agro- and oasis agro- ecosystems were seriously polluted (>1.0 mg·L−1) by N. Spatial analysis showed that the total N concentrations in northern and northwestern regions were higher than those in the southern region for both still and flowing surface waters under agro- and oasis agro- ecosystems, with more than 50% of samples exceeding 1.0 mg·L−1 (the Class III limit of the Chinese National Quality Standards for Surface Waters) in surface water in the northern region. Nitrogen pollution in agro- ecosystems is mainly due to fertilizer applications, while the combination of fertilizer and irrigation exacerbates nitrogen pollution in oasis agro- ecosystems. PMID:24667701

  15. Definition of Hydrologic Response Units in Depression Plagued Digital Elevation Models

    NASA Astrophysics Data System (ADS)

    Lindsay, J. B.; Creed, I. F.

    2002-12-01

    Definition of hydrologic response units using digital elevation models (DEMs) is sensitive to the occurrence of topographic depressions. Real depressions can be important to the hydrology and biogeochemistry a catchment, often coinciding with areas of surface saturation. Artifact depressions, in contrast, result in digital "black holes", artificially truncating the hydrologic flow lengths and altering hydrologic flow directions, parameters that are often used in defining hydrologic response units. Artifact depressions must be removed from DEMs prior to definition of hydrologic response units. Depression filling or depression trenching techniques can be used to remove these artifacts. Depression trenching methods are often considered more appropriate because they preserve the topographic variability within a depression thus avoiding the creation of spurious flat areas. Current trenching algorithms are relatively slow and unable to process very large or noisy DEMs. A new trenching algorithm that overcomes these limitations is described. The algorithm does not require finding depression catchments or outlets, nor does it need special handling for nested depressions. Therefore, artifacts can be removed from large or noisy DEMs efficiently, while minimizing the number of grid elevations requiring modification. The resulting trench is a monotonically descending path starting from the lowest point in a depression, passing through the depression's outlet, and ending at a point of lower elevation outside the depression. The importance of removing artifact depressions is demonstrated by showing hydrologic response units both before and after the removal of artifact depressions from the DEM.

  16. On the use of three hydrological models as hypotheses to investigate the behaviour of a small Mediterranean catchment

    NASA Astrophysics Data System (ADS)

    Ruiz Pérez, Guiomar; Latron, Jérôme; Llorens, Pilar; Gallart, Francesc; Francés, Félix

    2017-04-01

    Selecting an adequate hydrological model is the first step to carry out a rainfall-runoff modelling exercise. A hydrological model is a hypothesis of catchment functioning, encompassing a description of dominant hydrological processes and predicting how these processes interact to produce the catchment's response to external forcing. Current research lines emphasize the importance of multiple working hypotheses for hydrological modelling instead of only using a single model. In line with this philosophy, here different hypotheses were considered and analysed to simulate the nonlinear response of a small Mediterranean catchment and to progress in the analysis of its hydrological behaviour. In particular, three hydrological models were considered representing different potential hypotheses: two lumped models called LU3 and LU4, and one distributed model called TETIS. To determine how well each specific model performed and to assess whether a model was more adequate than another, we raised three complementary tests: one based on the analysis of residual errors series, another based on a sensitivity analysis and the last one based on using multiple evaluation criteria associated to the concept of Pareto frontier. This modelling approach, based on multiple working hypotheses, helped to improve our perceptual model of the catchment behaviour and, furthermore, could be used as a guidance to improve the performance of other environmental models.

  17. Assessment of an improved hydrological loading model from space geodesy: case study in South America

    NASA Astrophysics Data System (ADS)

    Nicolas, Joëlle; Boy, Jean-Paul; Durand, Frédéric; Mémin, Anthony

    2017-04-01

    Loading effects are crustal deformations induced by ocean, atmosphere and continental water mass redistributions. In this study we focus on hydrological loading effect monitored by space geodesy and in particular by GNSS and GRACE. Classically, hydrological loading models take into account snow and soil-moisture but don't consider surface waters (rivers, lakes…). As a result, huge discrepancies between GPS observations and those models arise around large rivers such as the Amazon where nearly half of the vertical signal cannot be explained by the combination of atmospheric, oceanic and hydrological loading models. To better resolve the hydrological signal, we improve the continental water storage models computed from soil-moisture and snow GLDAS/Noah or MERRA data sets by including surface water runoff. We investigate how continental water storage model improvements are supported by GNSS and GRACE observations in South America main river basins: Amazon, Orinoco and Parana. In this area the hydrological effects are among the largest in the world mainly due to the river level variations. We present the results of time series analyses with spectral and principal component analysis (PCA) methods. We extract the dominant spatio-temporal annual mode. We also identify and characterize the spatio-temporal changes in the annual hydrology signal, which is the key to a better understanding of the water cycle variations of those major rivers. We demonstrate that it is crucial to take into account the river contribution in fluid signatures before investigating high-frequency variability and episodic events.

  18. Performance measures and criteria for hydrologic and water quality models

    USDA-ARS?s Scientific Manuscript database

    Performance measures and criteria are essential for model calibration and validation. This presentation will include a summary of one of the papers that will be included in the 2014 Hydrologic and Water Quality Model Calibration & Validation Guidelines Special Collection of the ASABE Transactions. T...

  19. Hydrological Relevant Parameters from Remote Sensing - Spatial Modelling Input and Validation Basis

    NASA Astrophysics Data System (ADS)

    Hochschild, V.

    2012-12-01

    This keynote paper will demonstrate how multisensoral remote sensing data is used as spatial input for mesoscale hydrological modeling as well as for sophisticated validation purposes. The tasks of Water Resources Management are subject as well as the role of remote sensing in regional catchment modeling. Parameters derived from remote sensing discussed in this presentation will be land cover, topographical information from digital elevation models, biophysical vegetation parameters, surface soil moisture, evapotranspiration estimations, lake level measurements, determination of snow covered area, lake ice cycles, soil erosion type, mass wasting monitoring, sealed area, flash flood estimation. The actual possibilities of recent satellite and airborne systems are discussed, as well as the data integration into GIS and hydrological modeling, scaling issues and quality assessment will be mentioned. The presentation will provide an overview of own research examples from Germany, Tibet and Africa (Ethiopia, South Africa) as well as other international research activities. Finally the paper gives an outlook on upcoming sensors and concludes the possibilities of remote sensing in hydrology.

  20. HydroShare: A Platform for Collaborative Data and Model Sharing in Hydrology

    NASA Astrophysics Data System (ADS)

    Tarboton, D. G.; Idaszak, R.; Horsburgh, J. S.; Ames, D. P.; Goodall, J. L.; Couch, A.; Hooper, R. P.; Dash, P. K.; Stealey, M.; Yi, H.; Bandaragoda, C.; Castronova, A. M.

    2017-12-01

    HydroShare is an online, collaboration system for sharing of hydrologic data, analytical tools, and models. It supports the sharing of and collaboration around "resources" which are defined by standardized content types for data formats and models commonly used in hydrology. With HydroShare you can: Share your data and models with colleagues; Manage who has access to the content that you share; Share, access, visualize and manipulate a broad set of hydrologic data types and models; Use the web services application programming interface (API) to program automated and client access; Publish data and models and obtain a citable digital object identifier (DOI); Aggregate your resources into collections; Discover and access data and models published by others; Use web apps to visualize, analyze and run models on data in HydroShare. This presentation will describe the functionality and architecture of HydroShare highlighting its use as a virtual environment supporting education and research. HydroShare has components that support: (1) resource storage, (2) resource exploration, and (3) web apps for actions on resources. The HydroShare data discovery, sharing and publishing functions as well as HydroShare web apps provide the capability to analyze data and execute models completely in the cloud (servers remote from the user) overcoming desktop platform limitations. The HydroShare GIS app provides a basic capability to visualize spatial data. The HydroShare JupyterHub Notebook app provides flexible and documentable execution of Python code snippets for analysis and modeling in a way that results can be shared among HydroShare users and groups to support research collaboration and education. We will discuss how these developments can be used to support different types of educational efforts in Hydrology where being completely web based is of value in an educational setting as students can all have access to the same functionality regardless of their computer.

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  2. Investigating impacts of natural and human-induced environmental changes on hydrological processes and flood hazards using a GIS-based hydrological/hydraulic model and remote sensing data

    NASA Astrophysics Data System (ADS)

    Wang, Lei

    Natural and human-induced environmental changes have been altering the earth's surface and hydrological processes, and thus directly contribute to the severity of flood hazards. To understand these changes and their impacts, this research developed a GIS-based hydrological and hydraulic modeling system, which incorporates state-of-the-art remote sensing data to simulate flood under various scenarios. The conceptual framework and technical issues of incorporating multi-scale remote sensing data have been addressed. This research develops an object-oriented hydrological modeling framework. Compared with traditional lumped or cell-based distributed hydrological modeling frameworks, the object-oriented framework allows basic spatial hydrologic units to have various size and irregular shape. This framework is capable of assimilating various GIS and remotely-sensed data with different spatial resolutions. It ensures the computational efficiency, while preserving sufficient spatial details of input data and model outputs. Sensitivity analysis and comparison of high resolution LIDAR DEM with traditional USGS 30m resolution DEM suggests that the use of LIDAR DEMs can greatly reduce uncertainty in calibration of flow parameters in the hydrologic model and hence increase the reliability of modeling results. In addition, subtle topographic features and hydrologic objects like surface depressions and detention basins can be extracted from the high resolution LiDAR DEMs. An innovative algorithm has been developed to efficiently delineate surface depressions and detention basins from LiDAR DEMs. Using a time series of Landsat images, a retrospective analysis of surface imperviousness has been conducted to assess the hydrologic impact of urbanization. The analysis reveals that with rapid urbanization the impervious surface has been increased from 10.1% to 38.4% for the case study area during 1974--2002. As a result, the peak flow for a 100-year flood event has increased by 20% and

  3. Quantifying human impact on hydrological drought using an Earth System Model

    NASA Astrophysics Data System (ADS)

    van Huijgevoort, Marjolein; Chaney, Nathaniel; Malyshev, Sergey; Shevliakova, Elena; Milly, Chris

    2017-04-01

    Predicting the human impact on the present and future hydrological cycle remains a significant scientific challenge. Anthropogenic impact includes water management practices like diverting water for irrigation, abstraction of groundwater, and reservoirs. Hydrological extremes, in particular, are heavily affected by water management practices, due to the existing stress on the system during droughts and floods. Therefore, to prepare adaptation plans for hydrological extremes in the future, it is essential to account for water management and other human influences in Earth System Models. In this study we have implemented water management practices in the state-of-the-art GFDL land model, which includes terrestrial water, energy, and carbon balances. Both irrigation practices and reservoirs have been added in the land surface model component of the model. Irrigation amounts are determined from the soil water balance, the evaporative demand of the vegetation and fractional coverage of croplands. The resulting water demand is fulfilled by abstractions from surface water and groundwater. Reservoir outflow is dynamically coupled to the downstream water demand and available reservoir storage. Retrospective model simulations over the contiguous United States indicate a strong human influence on hydrological drought. A water management attribution analysis shows a significant impact on the water availability, mostly in the Midwest of the United States and California. Implementation of reservoirs alters the flow regime, thereby decreasing the short-term drought impact, however, in the case of multi-year drought, impacts are delayed due to the dependency on the reservoir outflow. Irrigation, on the other hand, decreases the water availability in rivers due to increased evapotranspiration leading to a higher drought impact. The average increase in evapotranspiration amounted up to 2 mm/day for cropland areas in California and Texas. Overall, the results show the importance of

  4. Satellite altimetry and hydrologic modeling of poorly-gauged tropical watershed

    NASA Astrophysics Data System (ADS)

    Sulistioadi, Yohanes Budi

    Fresh water resources are critical for daily human consumption. Therefore, a continuous monitoring effort over their quantity and quality is instrumental. One important model for water quantity monitoring is the rainfall-runoff model, which represents the response of a watershed to the variability of precipitation, thus estimating the discharge of a channel (Bedient and Huber, 2002, Beven, 2012). Remote sensing and satellite geodetic observations are capable to provide critical hydrological parameters, which can be used to support hydrologic modeling. For the case of satellite radar altimetry, limited temporal resolutions (e.g., satellite revisit period) prohibit the use of this method for a short (less than weekly) interval monitoring of water level or discharge. On the other hand, the current satellite radar altimeter footprints limit the water level measurement for rivers wider than 1 km (Birkett, 1998, Birkett et al., 2002). Some studies indeed reported successful retrieval of water level for small-size rivers as narrow as 80 m (Kuo and Kao, 2011, Michailovsky et al., 2012); however, the processing of current satellite altimetry signals for small water bodies to retrieve accurate water levels, remains challenging. To address this scientific challenge, this study poses two main objectives: (1) to monitor small (40--200 m width) and medium-sized (200--800 m width) rivers and lakes using satellite altimetry through identification and choice of the over-water radar waveforms corresponding to the appropriately waveform-retracked water level; and (2) to develop a rainfall-runoff hydrological model to represent the response of mesoscale watershed to the variability of precipitation. Both studies address the humid tropics of Southeast Asia, specifically in Indonesia, where similar studies do not yet exist. This study uses the Level 2 radar altimeter measurements generated by European Space Agency's (ESA's) Envisat (Environmental Satellite) mission. The first study

  5. A Model for Wetland Hydrology: Description and Validation

    Treesearch

    R.S. Mansell; S.A. Bloom; Ge Sun

    2000-01-01

    WETLANDS, a multidimensional model describing water flow in variably saturated soil and evapotranspiration, was used to simulate successfully 3-years of local hydrology for a cypress pond located within a relatively flat Coastal Plain pine forest landscape. Assumptions included negligible net regional groundwater flow and radially symmetric local flow impinging on a...

  6. Modeling and verification of process parameters for the production of tannase by Aspergillus oryzae under submerged fermentation using agro-wastes.

    PubMed

    Varadharajan, Venkatramanan; Vadivel, Sudhan Shanmuga; Ramaswamy, Arulvel; Sundharamurthy, Venkatesaprabhu; Chandrasekar, Priyadharshini

    2017-01-01

    Tannase production by Aspergillus oryzae using various agro-wastes as substrates by submerged fermentation was studied in this research. The microbe was isolated from degrading corn kernel obtained from the corn fields at Tiruchengode, India. The microbial identification was done using 18S rRNA gene analysis. The agro-wastes chosen for the study were pomegranate rind, Cassia auriculata flower, black gram husk, and tea dust. The process parameters chosen for optimization study were substrate concentration, pH, temperature, and incubation period. During one variable at a time optimization, the pomegranate rind extract produced maximum tannase activity of 138.12 IU/mL and it was chosen as the best substrate for further experiments. The quadratic model was found to be the effective model for prediction of tannase production by A. oryzae. The optimized conditions predicted by response surface methodology (RSM) with genetic algorithm (GA) were 1.996% substrate concentration, pH of 4.89, temperature of 34.91 °C, and an incubation time of 70.65 H with maximum tannase activity of 138.363 IU/mL. The confirmatory experiment under optimized conditions showed tannase activity of 139.22 IU/mL. Hence, RSM-GA pair was successfully used in this study to optimize the process parameters required for the production of tannase using pomegranate rind. © 2015 International Union of Biochemistry and Molecular Biology, Inc.

  7. Synchronising data sources and filling gaps by global hydrological modelling

    NASA Astrophysics Data System (ADS)

    Pimentel, Rafael; Crochemore, Louise; Hasan, Abdulghani; Pineda, Luis; Isberg, Kristina; Arheimer, Berit

    2017-04-01

    The advances in remote sensing in the last decades combined with the creation of different open hydrological databases have generated a very large amount of useful information for global hydrological modelling. Working with this huge number of datasets to set up a global hydrological model can constitute challenges such as multiple data formats and big heterogeneity on spatial and temporal resolutions. Different initiatives have made effort to homogenize some of these data sources, i.e. GRDC (Global Runoff Data Center), HYDROSHEDS (SHuttle Elevation Derivatives at multiple Scales), GLWD (Global Lake and Wetland Database) for runoff, watershed delineation and water bodies respectively. However, not all the related issues are covered or homogenously solved at the global scale and new information is continuously available to complete the current ones. This work presents synchronising efforts to make use of different global data sources needed to set up the semi-distributed hydrological model HYPE (Hydrological Predictions for the Environment) at the global scale. These data sources included: topography for watershed delineation, gauging stations of river flow, and extention of lakes, flood plains and land cover classes. A new database with approximately 100 000 subbasins, with an average area of 1000 km2, was created. Subbasin delineation was done combining Global Width Database for Large River (GWD-LR), SRTM high-resolution elevation data and a number of forced points of interest (gauging station of river flow, lakes, reservoirs, urban areas, nuclear plants and areas with high risk of flooding). Regarding flow data, the locations of GRDC stations were checked or placed along the river network when necessary, and completed with available information from national water services in data-sparse regions. A screening of doublet stations and associated time series was necessary to efficiently combine the two types of data sources. A total number about 21 000 stations were

  8. Using the SWAT model to improve process descriptions and define hydrologic partitioning in South Korea

    NASA Astrophysics Data System (ADS)

    Shope, C. L.; Maharjan, G. R.; Tenhunen, J.; Seo, B.; Kim, K.; Riley, J.; Arnhold, S.; Koellner, T.; Ok, Y. S.; Peiffer, S.; Kim, B.; Park, J.-H.; Huwe, B.

    2014-02-01

    Watershed-scale modeling can be a valuable tool to aid in quantification of water quality and yield; however, several challenges remain. In many watersheds, it is difficult to adequately quantify hydrologic partitioning. Data scarcity is prevalent, accuracy of spatially distributed meteorology is difficult to quantify, forest encroachment and land use issues are common, and surface water and groundwater abstractions substantially modify watershed-based processes. Our objective is to assess the capability of the Soil and Water Assessment Tool (SWAT) model to capture event-based and long-term monsoonal rainfall-runoff processes in complex mountainous terrain. To accomplish this, we developed a unique quality-control, gap-filling algorithm for interpolation of high-frequency meteorological data. We used a novel multi-location, multi-optimization calibration technique to improve estimations of catchment-wide hydrologic partitioning. The interdisciplinary model was calibrated to a unique combination of statistical, hydrologic, and plant growth metrics. Our results indicate scale-dependent sensitivity of hydrologic partitioning and substantial influence of engineered features. The addition of hydrologic and plant growth objective functions identified the importance of culverts in catchment-wide flow distribution. While this study shows the challenges of applying the SWAT model to complex terrain and extreme environments; by incorporating anthropogenic features into modeling scenarios, we can enhance our understanding of the hydroecological impact.

  9. Hydrologic modeling of Guinale River Basin using HEC-HMS and synthetic aperture radar

    NASA Astrophysics Data System (ADS)

    Bien, Ferdinand E.; Plopenio, Joanaviva C.

    2017-09-01

    This paper presents the methods and results of hydrologic modeling of Guinale river basin through the use of HEC-HMS software and Synthetic Aperture Radar Digital Elevation Model (SAR DEM). Guinale River Basin is located in the province of Albay, Philippines which is one of the river basins covered by the Ateneo de Naga University (ADNU) Phil-LiDAR 1. This research project was funded by the Department of Science and Technology (DOST) through the Philippine Council for Industry, Energy and Emerging Technology Research and Development (PCIEERD). Its objectives are to simulate the hydrologic model of Guinale River basin using HEC-HMS software and SAR DEM. Its basin covers an area of 165.395 sq.km. and the hydrologic model was calibrated using the storm event typhoon Nona (international name Melor). Its parameter had undergone a series of optimization processes of HEC-HMS software in order to produce an acceptable level of model efficiency. The Nash-Sutcliffe (E), Percent Bias and Standard Deviation Ratio were used to measure the model efficiency, giving values of 0.880, 0.260 and 0.346 respectively which resulted to a "very good" performance rating of the model. The flood inundation model was simulated using Legazpi Rainfall Intensity Duration Frequency Curves (RIDF) and HEC-RAS software developed by the US Army corps of Engineers (USACE). This hydrologic model will provide the Municipal Disaster Risk Reduction Management Office (MDRRMO), Local Government units (LGUs) and the community a tool for the prediction of runoff in the area.

  10. Towards a more holistic sustainability assessment framework for agro-bioenergy systems — A review

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Arodudu, Oludunsin, E-mail: Oludunsin.Arodudu@zalf.de; Potsdam University, Institute of Earth and Environmental Sciences, Karl-Liebknecht-Straße 24-25, 14476 Potsdam, Golm; Helming, Katharina

    The use of life cycle assessment (LCA) as a sustainability assessment tool for agro-bioenergy system usually has an industrial agriculture bias. Furthermore, LCA generally has often been criticized for being a decision maker tool which may not consider decision takers perceptions. They are lacking in spatial and temporal depth, and unable to assess sufficiently some environmental impact categories such as biodiversity, land use etc. and most economic and social impact categories, e.g. food security, water security, energy security. This study explored tools, methodologies and frameworks that can be deployed individually, as well as in combination with each other for bridgingmore » these methodological gaps in application to agro-bioenergy systems. Integrating agronomic options, e.g. alternative farm power, tillage, seed sowing options, fertilizer, pesticide, irrigation into the boundaries of LCAs for agro-bioenergy systems will not only provide an alternative agro-ecological perspective to previous LCAs, but will also lead to the derivation of indicators for assessment of some social and economic impact categories. Deploying life cycle thinking approaches such as energy return on energy invested-EROEI, human appropriation of net primary production-HANPP, net greenhouse gas or carbon balance-NCB, water footprint individually and in combination with each other will also lead to further derivation of indicators suitable for assessing relevant environmental, social and economic impact categories. Also, applying spatio-temporal simulation models has a potential for improving the spatial and temporal depths of LCA analysis.« less

  11. High resolution weather data for urban hydrological modelling and impact assessment, ICT requirements and future challenges

    NASA Astrophysics Data System (ADS)

    ten Veldhuis, Marie-claire; van Riemsdijk, Birna

    2013-04-01

    Hydrological analysis of urban catchments requires high resolution rainfall and catchment information because of the small size of these catchments, high spatial variability of the urban fabric, fast runoff processes and related short response times. Rainfall information available from traditional radar and rain gauge networks does no not meet the relevant scales of urban hydrology. A new type of weather radars, based on X-band frequency and equipped with Doppler and dual polarimetry capabilities, promises to provide more accurate rainfall estimates at the spatial and temporal scales that are required for urban hydrological analysis. Recently, the RAINGAIN project was started to analyse the applicability of this new type of radars in the context of urban hydrological modelling. In this project, meteorologists and hydrologists work closely together in several stages of urban hydrological analysis: from the acquisition procedure of novel and high-end radar products to data acquisition and processing, rainfall data retrieval, hydrological event analysis and forecasting. The project comprises of four pilot locations with various characteristics of weather radar equipment, ground stations, urban hydrological systems, modelling approaches and requirements. Access to data processing and modelling software is handled in different ways in the pilots, depending on ownership and user context. Sharing of data and software among pilots and with the outside world is an ongoing topic of discussion. The availability of high resolution weather data augments requirements with respect to the resolution of hydrological models and input data. This has led to the development of fully distributed hydrological models, the implementation of which remains limited by the unavailability of hydrological input data. On the other hand, if models are to be used in flood forecasting, hydrological models need to be computationally efficient to enable fast responses to extreme event conditions. This

  12. Improving Simulations of Extreme Flows by Coupling a Physically-based Hydrologic Model with a Machine Learning Model

    NASA Astrophysics Data System (ADS)

    Mohammed, K.; Islam, A. S.; Khan, M. J. U.; Das, M. K.

    2017-12-01

    With the large number of hydrologic models presently available along with the global weather and geographic datasets, streamflows of almost any river in the world can be easily modeled. And if a reasonable amount of observed data from that river is available, then simulations of high accuracy can sometimes be performed after calibrating the model parameters against those observed data through inverse modeling. Although such calibrated models can succeed in simulating the general trend or mean of the observed flows very well, more often than not they fail to adequately simulate the extreme flows. This causes difficulty in tasks such as generating reliable projections of future changes in extreme flows due to climate change, which is obviously an important task due to floods and droughts being closely connected to people's lives and livelihoods. We propose an approach where the outputs of a physically-based hydrologic model are used as an input to a machine learning model to try and better simulate the extreme flows. To demonstrate this offline-coupling approach, the Soil and Water Assessment Tool (SWAT) was selected as the physically-based hydrologic model, the Artificial Neural Network (ANN) as the machine learning model and the Ganges-Brahmaputra-Meghna (GBM) river system as the study area. The GBM river system, located in South Asia, is the third largest in the world in terms of freshwater generated and forms the largest delta in the world. The flows of the GBM rivers were simulated separately in order to test the performance of this proposed approach in accurately simulating the extreme flows generated by different basins that vary in size, climate, hydrology and anthropogenic intervention on stream networks. Results show that by post-processing the simulated flows of the SWAT models with ANN models, simulations of extreme flows can be significantly improved. The mean absolute errors in simulating annual maximum/minimum daily flows were minimized from 4967

  13. Development of a hydrological model for simulation of runoff from catchments unbounded by ridge lines

    NASA Astrophysics Data System (ADS)

    Vema, Vamsikrishna; Sudheer, K. P.; Chaubey, I.

    2017-08-01

    Watershed hydrological models are effective tools for simulating the hydrological processes in the watershed. Although there are a plethora of hydrological models, none of them can be directly applied to make water conservation decisions in irregularly bounded areas that do not confirm to topographically defined ridge lines. This study proposes a novel hydrological model that can be directly applied to any catchment, with or without ridge line boundaries. The model is based on the water balance concept, and a linear function concept to approximate the cross-boundary flow from upstream areas to the administrative catchment under consideration. The developed model is tested in 2 watersheds - Riesel Experimental Watershed and a sub-basin of Cedar Creek Watershed in Texas, USA. Hypothetical administrative catchments that did not confirm to the location of ridge lines were considered for verifying the efficacy of the model for hydrologic simulations. The linear function concept used to account the cross boundary flow was based on the hypothesis that the flow coming from outside the boundary to administrative area was proportional to the flow generated in the boundary grid cell. The model performance was satisfactory with an NSE and r2 of ≥0.80 and a PBIAS of <25 in all the cases. The simulated hydrographs for the administrative catchments of the watersheds were in good agreement with the observed hydrographs, indicating a satisfactory performance of the model in the administratively bounded areas.

  14. Coupled hydrologic and hydraulic modeling of Upper Niger River Basin

    NASA Astrophysics Data System (ADS)

    Fleischmann, Ayan; Siqueira, Vinícius; Paris, Adrien; Collischonn, Walter; Paiva, Rodrigo; Gossett, Marielle; Pontes, Paulo; Calmant, Stephane; Biancamaria, Sylvain; Crétaux, Jean-François; Tanimoune, Bachir

    2017-04-01

    The Upper Niger Basin is located in Western Africa, flowing from Guinea Highlands towards the Sahel region. In this area lies the seasonally inundated Niger Inland Delta, which supports important environmental services such as habitats for wildlife, climate and flood regulation, as well as large fishery and agricultural areas. In this study, we present the application of MGB-IPH large scale hydrologic and hydrodynamic model for the Upper Niger Basin, totaling c.a. 650,000 km2 and set up until the city of Niamey in Niger. The model couples hydrological vertical balance and runoff generation with hydrodynamic flood wave propagation, by allowing infiltration from floodplains into soil column as well as representing backwater effects and floodplain storage throughout flat areas such as the Inland Delta. The model is forced with TRMM 3B42 daily precipitation and Climate Research Unit (CRU) climatology for the period 2000-2010, and was calibrated against in-situ discharge gauges and validated with in-situ water level, remotely sensed estimations of flooded areas (classification of MODIS imagery) and satellite altimetry (JASON-2 mission). Model results show good predictions for calibrated daily discharge and validated water level and altimetry at stations both upstream and downstream of the delta (Nash-Sutcliffe Efficiency>0.7 for all stations), as well as for flooded areas within the delta region (ENS=0.5; r2=0.8), allowing a good representation of flooding dynamics basinwide and simulation of flooding behavior of both perennial (e.g., Niger main stem) and ephemeral rivers (e.g., Niger Red Flood tributaries in Sahel). Coupling between hydrology and hydrodynamic processes indicates an important feedback between floodplain and soil water storage that allows high evapotranspiration rates even after the flood passage around the inner delta area. Also, representation of water retention in floodplain channels and distributaries in the inner delta (e.g., Diaka river

  15. 7Be and hydrological model for more efficient implementation of erosion control measure

    NASA Astrophysics Data System (ADS)

    Al-Barri, Bashar; Bode, Samuel; Blake, William; Ryken, Nick; Cornelis, Wim; Boeckx, Pascal

    2014-05-01

    Increased concern about the on-site and off-site impacts of soil erosion in agricultural and forested areas has endorsed interest in innovative methods to assess in an unbiased way spatial and temporal soil erosion rates and redistribution patterns. Hence, interest in precisely estimating the magnitude of the problem and therefore applying erosion control measures (ECM) more efficiently. The latest generation of physically-based hydrological models, which fully couple overland flow and subsurface flow in three dimensions, permit implementing ECM in small and large scales more effectively if coupled with a sediment transport algorithm. While many studies focused on integrating empirical or numerical models based on traditional erosion budget measurements into 3D hydrological models, few studies evaluated the efficiency of ECM on watershed scale and very little attention is given to the potentials of environmental Fallout Radio-Nuclides (FRNs) in such applications. The use of FRN tracer 7Be in soil erosion/deposition research proved to overcome many (if not all) of the problems associated with the conventional approaches providing reliable data for efficient land use management. This poster will underline the pros and cones of using conventional methods and 7Be tracers to evaluate the efficiency of coconuts dams installed as ECM in experimental field in Belgium. It will also outline the potentials of 7Be in providing valuable inputs for evolving the numerical sediment transport algorithm needed for the hydrological model on field scale leading to assess the possibility of using this short-lived tracer as a validation tool for the upgraded hydrological model on watershed scale in further steps. Keywords: FRN, erosion control measures, hydrological modes

  16. Modelling hydrological processes and dissolved organic carbon dynamics in a rehabilitated Sphagnum-dominated peatland

    NASA Astrophysics Data System (ADS)

    Bernard-Jannin, Léonard; Binet, Stéphane; Gogo, Sébastien; Leroy, Fabien; Perdereau, Laurent; Laggoun-Défarge, Fatima

    2017-04-01

    Sphagnum-dominated peatlands represent a global major stock of carbon (C). Dissolved organic carbon (DOC) exports through runoff and leaching could reduce their potential C sink function and impact downstream water quality. DOC production in peatlands is strongly controlled by the hydrology, especially water table depth (WTD). Therefore, disturbances such as drainage can lead to increase DOC exports by lowering the WTD. Hydrological restoration (e.g. rewetting) can be undertaken to restore peatland functioning with an impact on DOC exports. The objective of this study is to assess the impact of drainage and rewetting on hydrological processes and their interactions with DOC dynamics in a Sphagnum dominated peatland. A hydrological model has been applied to a drained peatland (La Guette, France) which experienced a rewetting action on February 2014 and where WTD has been recorded in four piezometers at a 15 min time step since 2009. In addition, DOC concentrations in the peatland have been measured 6 times a year since 2014. The hydrological model is a WTD dependent reservoir model composed by two reservoirs representing the micro and macro porosity of the peatland (Binet et al., 2013). A DOC production module in both reservoirs was implemented based on temperature and WTD. The model was calibrated against WTD and DOC concentrations for each piezometer. The results show that the WTD in the study area is strongly affected by local meteorological conditions that could hide the effect of the rewetting action. The preliminary results evidenced that an additional source of water, identified as groundwater supply originating from the surrounding sandy layer aquifer, is necessary to maintain the water balance, especially during wet years (NS>0.8). Finally, the DOC module was able to describe DOC concentrations measured in the peatland and could be used to assess the impact of rewetting on DOC dynamics at different locations and to identify the factors of control of DOC

  17. The Use of Simulation Models in Teaching Geomorphology and Hydrology.

    ERIC Educational Resources Information Center

    Kirkby, Mike; Naden, Pam

    1988-01-01

    Learning about the physical environment from computer simulation models is discussed in terms of three stages: exploration, experimentation, and calibration. Discusses the effective use of models and presents two computer simulations written in BBC BASIC, STORFLO (for catchment hydrology) and SLOPEK (for hillslope evolution). (Author/GEA)

  18. Coupling large scale hydrologic-reservoir-hydraulic models for impact studies in data sparse regions

    NASA Astrophysics Data System (ADS)

    O'Loughlin, Fiachra; Neal, Jeff; Wagener, Thorsten; Bates, Paul; Freer, Jim; Woods, Ross; Pianosi, Francesca; Sheffied, Justin

    2017-04-01

    As hydraulic modelling moves to increasingly large spatial domains it has become essential to take reservoirs and their operations into account. Large-scale hydrological models have been including reservoirs for at least the past two decades, yet they cannot explicitly model the variations in spatial extent of reservoirs, and many reservoirs operations in hydrological models are not undertaken during the run-time operation. This requires a hydraulic model, yet to-date no continental scale hydraulic model has directly simulated reservoirs and their operations. In addition to the need to include reservoirs and their operations in hydraulic models as they move to global coverage, there is also a need to link such models to large scale hydrology models or land surface schemes. This is especially true for Africa where the number of river gauges has consistently declined since the middle of the twentieth century. In this study we address these two major issues by developing: 1) a coupling methodology for the VIC large-scale hydrological model and the LISFLOOD-FP hydraulic model, and 2) a reservoir module for the LISFLOOD-FP model, which currently includes four sets of reservoir operating rules taken from the major large-scale hydrological models. The Volta Basin, West Africa, was chosen to demonstrate the capability of the modelling framework as it is a large river basin ( 400,000 km2) and contains the largest man-made lake in terms of area (8,482 km2), Lake Volta, created by the Akosombo dam. Lake Volta also experiences a seasonal variation in water levels of between two and six metres that creates a dynamic shoreline. In this study, we first run our coupled VIC and LISFLOOD-FP model without explicitly modelling Lake Volta and then compare these results with those from model runs where the dam operations and Lake Volta are included. The results show that we are able to obtain variation in the Lake Volta water levels and that including the dam operations and Lake Volta

  19. Including hydrological self-regulating processes in peatland models: Effects on peatmoss drought projections.

    PubMed

    Nijp, Jelmer J; Metselaar, Klaas; Limpens, Juul; Teutschbein, Claudia; Peichl, Matthias; Nilsson, Mats B; Berendse, Frank; van der Zee, Sjoerd E A T M

    2017-02-15

    The water content of the topsoil is one of the key factors controlling biogeochemical processes, greenhouse gas emissions and biosphere - atmosphere interactions in many ecosystems, particularly in northern peatlands. In these wetland ecosystems, the water content of the photosynthetic active peatmoss layer is crucial for ecosystem functioning and carbon sequestration, and is sensitive to future shifts in rainfall and drought characteristics. Current peatland models differ in the degree in which hydrological feedbacks are included, but how this affects peatmoss drought projections is unknown. The aim of this paper was to systematically test whether the level of hydrological detail in models could bias projections of water content and drought stress for peatmoss in northern peatlands using downscaled projections for rainfall and potential evapotranspiration in the current (1991-2020) and future climate (2061-2090). We considered four model variants that either include or exclude moss (rain)water storage and peat volume change, as these are two central processes in the hydrological self-regulation of peatmoss carpets. Model performance was validated using field data of a peatland in northern Sweden. Including moss water storage as well as peat volume change resulted in a significant improvement of model performance, despite the extra parameters added. The best performance was achieved if both processes were included. Including moss water storage and peat volume change consistently reduced projected peatmoss drought frequency with >50%, relative to the model excluding both processes. Projected peatmoss drought frequency in the growing season was 17% smaller under future climate than current climate, but was unaffected by including the hydrological self-regulating processes. Our results suggest that ignoring these two fine-scale processes important in hydrological self-regulation of northern peatlands will have large consequences for projected climate change impact on

  20. Delineating wetland catchments and modeling hydrologic connectivity using lidar data and aerial imagery

    NASA Astrophysics Data System (ADS)

    Wu, Qiusheng; Lane, Charles R.

    2017-07-01

    In traditional watershed delineation and topographic modeling, surface depressions are generally treated as spurious features and simply removed from a digital elevation model (DEM) to enforce flow continuity of water across the topographic surface to the watershed outlets. In reality, however, many depressions in the DEM are actual wetland landscape features with seasonal to permanent inundation patterning characterized by nested hierarchical structures and dynamic filling-spilling-merging surface-water hydrological processes. Differentiating and appropriately processing such ecohydrologically meaningful features remains a major technical terrain-processing challenge, particularly as high-resolution spatial data are increasingly used to support modeling and geographic analysis needs. The objectives of this study were to delineate hierarchical wetland catchments and model their hydrologic connectivity using high-resolution lidar data and aerial imagery. The graph-theory-based contour tree method was used to delineate the hierarchical wetland catchments and characterize their geometric and topological properties. Potential hydrologic connectivity between wetlands and streams were simulated using the least-cost-path algorithm. The resulting flow network delineated potential flow paths connecting wetland depressions to each other or to the river network on scales finer than those available through the National Hydrography Dataset. The results demonstrated that our proposed framework is promising for improving overland flow simulation and hydrologic connectivity analysis.

  1. A GIS Tool for evaluating and improving NEXRAD and its application in distributed hydrologic modeling

    NASA Astrophysics Data System (ADS)

    Zhang, X.; Srinivasan, R.

    2008-12-01

    In this study, a user friendly GIS tool was developed for evaluating and improving NEXRAD using raingauge data. This GIS tool can automatically read in raingauge and NEXRAD data, evaluate the accuracy of NEXRAD for each time unit, implement several geostatistical methods to improve the accuracy of NEXRAD through raingauge data, and output spatial precipitation map for distributed hydrologic model. The geostatistical methods incorporated in this tool include Simple Kriging with varying local means, Kriging with External Drift, Regression Kriging, Co-Kriging, and a new geostatistical method that was newly developed by Li et al. (2008). This tool was applied in two test watersheds at hourly and daily temporal scale. The preliminary cross-validation results show that incorporating raingauge data to calibrate NEXRAD can pronouncedly change the spatial pattern of NEXRAD and improve its accuracy. Using different geostatistical methods, the GIS tool was applied to produce long term precipitation input for a distributed hydrologic model - Soil and Water Assessment Tool (SWAT). Animated video was generated to vividly illustrate the effect of using different precipitation input data on distributed hydrologic modeling. Currently, this GIS tool is developed as an extension of SWAT, which is used as water quantity and quality modeling tool by USDA and EPA. The flexible module based design of this tool also makes it easy to be adapted for other hydrologic models for hydrological modeling and water resources management.

  2. airGR: a suite of lumped hydrological models in an R-package

    NASA Astrophysics Data System (ADS)

    Coron, Laurent; Perrin, Charles; Delaigue, Olivier; Andréassian, Vazken; Thirel, Guillaume

    2016-04-01

    Lumped hydrological models are useful and convenient tools for research, engineering and educational purposes. They propose catchment-scale representations of the precipitation-discharge relationship. Thanks to their limited data requirements, they can be easily implemented and run. With such models, it is possible to simulate a number of hydrological key processes over the catchment with limited structural and parametric complexity, typically evapotranspiration, runoff, underground losses, etc. The Hydrology Group at Irstea (Antony) has been developing a suite of rainfall-runoff models over the past 30 years with the main objectives of designing models as efficient as possible in terms of streamflow simulation, applicable to a wide range of catchments and having low data requirements. This resulted in a suite of models running at different time steps (from hourly to annual) applicable for various issues including water balance estimation, forecasting, simulation of impacts and scenario testing. Recently, Irstea has developed an easy-to-use R-package (R Core Team, 2015), called airGR, to make these models widely available. It includes: - the water balance annual GR1A (Mouehli et al., 2006), - the monthly GR2M (Mouehli, 2003) models, - three versions of the daily model, namely GR4J (Perrin et al., 2003), GR5J (Le Moine, 2008) and GR6J (Pushpalatha et al., 2011), - the hourly GR4H model (Mathevet, 2005), - a degree-day snow module CemaNeige (Valéry et al., 2014). The airGR package has been designed to facilitate the use by non-expert users and allow the addition of evaluation criteria, models or calibration algorithms selected by the end-user. Each model core is coded in FORTRAN to ensure low computational time. The other package functions (i.e. mainly the calibration algorithm and the efficiency criteria) are coded in R. The package is already used for educational purposes. The presentation will detail the main functionalities of the package and present a case

  3. CEREF: A hybrid data-driven model for forecasting annual streamflow from a socio-hydrological system

    NASA Astrophysics Data System (ADS)

    Zhang, Hongbo; Singh, Vijay P.; Wang, Bin; Yu, Yinghao

    2016-09-01

    Hydrological forecasting is complicated by flow regime alterations in a coupled socio-hydrologic system, encountering increasingly non-stationary, nonlinear and irregular changes, which make decision support difficult for future water resources management. Currently, many hybrid data-driven models, based on the decomposition-prediction-reconstruction principle, have been developed to improve the ability to make predictions of annual streamflow. However, there exist many problems that require further investigation, the chief among which is the direction of trend components decomposed from annual streamflow series and is always difficult to ascertain. In this paper, a hybrid data-driven model was proposed to capture this issue, which combined empirical mode decomposition (EMD), radial basis function neural networks (RBFNN), and external forces (EF) variable, also called the CEREF model. The hybrid model employed EMD for decomposition and RBFNN for intrinsic mode function (IMF) forecasting, and determined future trend component directions by regression with EF as basin water demand representing the social component in the socio-hydrologic system. The Wuding River basin was considered for the case study, and two standard statistical measures, root mean squared error (RMSE) and mean absolute error (MAE), were used to evaluate the performance of CEREF model and compare with other models: the autoregressive (AR), RBFNN and EMD-RBFNN. Results indicated that the CEREF model had lower RMSE and MAE statistics, 42.8% and 7.6%, respectively, than did other models, and provided a superior alternative for forecasting annual runoff in the Wuding River basin. Moreover, the CEREF model can enlarge the effective intervals of streamflow forecasting compared to the EMD-RBFNN model by introducing the water demand planned by the government department to improve long-term prediction accuracy. In addition, we considered the high-frequency component, a frequent subject of concern in EMD

  4. Some Modeling Tools Available for Adaptive Management of South Florida Hydrology

    NASA Astrophysics Data System (ADS)

    Lal, W. A.; Van Zee, R. J.

    2002-05-01

    The hydrology of South Florida is a result of (1) the hydrology of the natural system; (2) the hydrology of the man made design components such as structures and levees designed to alter the natural hydrology; (3) influence of the operations imposed on the system using the design components. Successful restoration of the South Florida ecosystem depend not only on the design of the structural components, but also on its careful operation. The current discussion is focused on a number of optimal control methods that have recently become available to optimize restoration goals in the context of modeling. Optimal operation of the system can lessen stresses on some hydrological and ecological components. Careless operation can on the other hand lead to disastrous effects. Systems engineering and control theory have been used in the past to understand and operate simple systems such as the cruise control and the thermostat. Somewhat complex ones have been used to auto-pilot planes. The simplest control methods such as proportional and integral (PI) control are already used in the South Florida Water Management Model (SFWMM) for flood control and rain driven operations. The popular proportional-integral-differential (PID) control is widely used in industry for operational control of complex engineering systems. Some uses of PID control are investigated in the study. Other methods that an be used for operational control include Baysean methods, Kalman filtering and Neural network methods. A cursory evaluation of these methods is made in the discussion, along with the traditional methods used to operate complex engineering systems.

  5. The implementation and validation of improved land-surface hydrology in an atmospheric general circulation model

    NASA Technical Reports Server (NTRS)

    Johnson, Kevin D.; Entekhabi, Dara; Eagleson, Peter S.

    1993-01-01

    New land-surface hydrologic parameterizations are implemented into the NASA Goddard Institute for Space Studies (GISS) General Circulation Model (GCM). These parameterizations are: 1) runoff and evapotranspiration functions that include the effects of subgrid-scale spatial variability and use physically based equations of hydrologic flux at the soil surface and 2) a realistic soil moisture diffusion scheme for the movement of water and root sink in the soil column. A one-dimensional climate model with a complete hydrologic cycle is used to screen the basic sensitivities of the hydrological parameterizations before implementation into the full three-dimensional GCM. Results of the final simulation with the GISS GCM and the new land-surface hydrology indicate that the runoff rate, especially in the tropics, is significantly improved. As a result, the remaining components of the heat and moisture balance show similar improvements when compared to observations. The validation of model results is carried from the large global (ocean and land-surface) scale to the zonal, continental, and finally the regional river basin scales.

  6. Water regime of Playa Lakes from southern Spain: conditioning factors and hydrological modeling.

    PubMed

    Moral, Francisco; Rodriguez-Rodriguez, Miguel; Beltrán, Manuel; Benavente, José; Cifuentes, Victor Juan

    2013-07-01

    Andalusia's lowland countryside has a network of small geographically isolated playa lakes scattered across an area of 9000 km2 whose watersheds are mostly occupied by clayey rocks. The hydrological model proposed by the authors seeks to find equilibrium among usefulness, simplicity, and applicability to isolated playas in a semiarid context elsewhere. Based in such model, the authors have used monthly climatic data, water stage measurements, and the basin morphometry of a particular case (Los Jarales playa lake) to calibrate the soil water budget in the catchment and the water inputs from the watershed (runoff plus groundwater flow) at different scales, from monthly to daily. After the hydrologic model was calibrated, the authors implemented simulations with the goal of reproducing the past hydrological dynamics and forecasting water regime changes that would be caused by a modification of the wetland morphometry.

  7. Nitrogen Cycling from Increased Soil Organic Carbon Contributes Both Positively and Negatively to Ecosystem Services in Wheat Agro-Ecosystems

    PubMed Central

    Palmer, Jeda; Thorburn, Peter J.; Biggs, Jody S.; Dominati, Estelle J.; Probert, Merv E.; Meier, Elizabeth A.; Huth, Neil I.; Dodd, Mike; Snow, Val; Larsen, Joshua R.; Parton, William J.

    2017-01-01

    Soil organic carbon (SOC) is an important and manageable property of soils that impacts on multiple ecosystem services through its effect on soil processes such as nitrogen (N) cycling and soil physical properties. There is considerable interest in increasing SOC concentration in agro-ecosystems worldwide. In some agro-ecosystems, increased SOC has been found to enhance the provision of ecosystem services such as the provision of food. However, increased SOC may increase the environmental footprint of some agro-ecosystems, for example by increasing nitrous oxide emissions. Given this uncertainty, progress is needed in quantifying the impact of increased SOC concentration on agro-ecosystems. Increased SOC concentration affects both N cycling and soil physical properties (i.e., water holding capacity). Thus, the aim of this study was to quantify the contribution, both positive and negative, of increased SOC concentration on ecosystem services provided by wheat agro-ecosystems. We used the Agricultural Production Systems sIMulator (APSIM) to represent the effect of increased SOC concentration on N cycling and soil physical properties, and used model outputs as proxies for multiple ecosystem services from wheat production agro-ecosystems at seven locations around the world. Under increased SOC, we found that N cycling had a larger effect on a range of ecosystem services (food provision, filtering of N, and nitrous oxide regulation) than soil physical properties. We predicted that food provision in these agro-ecosystems could be significantly increased by increased SOC concentration when N supply is limiting. Conversely, we predicted no significant benefit to food production from increasing SOC when soil N supply (from fertiliser and soil N stocks) is not limiting. The effect of increasing SOC on N cycling also led to significantly higher nitrous oxide emissions, although the relative increase was small. We also found that N losses via deep drainage were minimally

  8. Nitrogen Cycling from Increased Soil Organic Carbon Contributes Both Positively and Negatively to Ecosystem Services in Wheat Agro-Ecosystems.

    PubMed

    Palmer, Jeda; Thorburn, Peter J; Biggs, Jody S; Dominati, Estelle J; Probert, Merv E; Meier, Elizabeth A; Huth, Neil I; Dodd, Mike; Snow, Val; Larsen, Joshua R; Parton, William J

    2017-01-01

    Soil organic carbon (SOC) is an important and manageable property of soils that impacts on multiple ecosystem services through its effect on soil processes such as nitrogen (N) cycling and soil physical properties. There is considerable interest in increasing SOC concentration in agro-ecosystems worldwide. In some agro-ecosystems, increased SOC has been found to enhance the provision of ecosystem services such as the provision of food. However, increased SOC may increase the environmental footprint of some agro-ecosystems, for example by increasing nitrous oxide emissions. Given this uncertainty, progress is needed in quantifying the impact of increased SOC concentration on agro-ecosystems. Increased SOC concentration affects both N cycling and soil physical properties (i.e., water holding capacity). Thus, the aim of this study was to quantify the contribution, both positive and negative, of increased SOC concentration on ecosystem services provided by wheat agro-ecosystems. We used the Agricultural Production Systems sIMulator (APSIM) to represent the effect of increased SOC concentration on N cycling and soil physical properties, and used model outputs as proxies for multiple ecosystem services from wheat production agro-ecosystems at seven locations around the world. Under increased SOC, we found that N cycling had a larger effect on a range of ecosystem services (food provision, filtering of N, and nitrous oxide regulation) than soil physical properties. We predicted that food provision in these agro-ecosystems could be significantly increased by increased SOC concentration when N supply is limiting. Conversely, we predicted no significant benefit to food production from increasing SOC when soil N supply (from fertiliser and soil N stocks) is not limiting. The effect of increasing SOC on N cycling also led to significantly higher nitrous oxide emissions, although the relative increase was small. We also found that N losses via deep drainage were minimally

  9. Review of Understanding of Earth's Hydrological Cycle: Observations, Theory and Modelling

    NASA Astrophysics Data System (ADS)

    Rast, Michael; Johannessen, Johnny; Mauser, Wolfram

    2014-05-01

    Water is our most precious and arguably most undervalued natural resource. It is essential for life on our planet, for food production and economic development. Moreover, water plays a fundamental role in shaping weather and climate. However, with the growing global population, the planet's water resources are constantly under threat from overuse and pollution. In addition, the effects of a changing climate are thought to be leading to an increased frequency of extreme weather causing floods, landslides and drought. The need to understand and monitor our environment and its resources, including advancing our knowledge of the hydrological cycle, has never been more important and apparent. The best approach to do so on a global scale is from space. This paper provides an overview of the major components of the hydrological cycle, the status of their observations from space and related data products and models for hydrological variable retrievals. It also lists the current and planned satellite missions contributing to advancing our understanding of the hydrological cycle on a global scale. Further details of the hydrological cycle are substantiated in several of the other papers in this Special Issue.

  10. Integrated landscape/hydrologic modeling tool for semiarid watersheds

    Treesearch

    Mariano Hernandez; Scott N. Miller

    2000-01-01

    An integrated hydrologic modeling/watershed assessment tool is being developed to aid in determining the susceptibility of semiarid landscapes to natural and human-induced changes across a range of scales. Watershed processes are by definition spatially distributed and are highly variable through time, and this approach is designed to account for their spatial and...

  11. Development of a "Hydrologic Equivalent Wetland" Concept for Modeling Cumulative Effects of Wetlands on Watershed Hydrology

    NASA Astrophysics Data System (ADS)

    Wang, X.; Liu, T.; Li, R.; Yang, X.; Duan, L.; Luo, Y.

    2012-12-01

    Wetlands are one of the most important watershed microtopographic features that affect, in combination rather than individually, hydrologic processes (e.g., routing) and the fate and transport of constituents (e.g., sediment and nutrients). Efforts to conserve existing wetlands and/or to restore lost wetlands require that watershed-level effects of wetlands on water quantity and water quality be quantified. Because monitoring approaches are usually cost or logistics prohibitive at watershed scale, distributed watershed models, such as the Soil and Water Assessment Tool (SWAT), can be a best resort if wetlands can be appropriately represented in the models. However, the exact method that should be used to incorporate wetlands into hydrologic models is the subject of much disagreement in the literature. In addition, there is a serious lack of information about how to model wetland conservation-restoration effects using such kind of integrated modeling approach. The objectives of this study were to: 1) develop a "hydrologic equivalent wetland" (HEW) concept; and 2) demonstrate how to use the HEW concept in SWAT to assess effects of wetland restoration within the Broughton's Creek watershed located in southwestern Manitoba of Canada, and of wetland conservation within the upper portion of the Otter Tail River watershed located in northwestern Minnesota of the United States. The HEWs were defined in terms of six calibrated parameters: the fraction of the subbasin area that drains into wetlands (WET_FR), the volume of water stored in the wetlands when filled to their normal water level (WET_NVOL), the volume of water stored in the wetlands when filled to their maximum water level (WET_MXVOL), the longest tributary channel length in the subbasin (CH_L1), Manning's n value for the tributary channels (CH_N1), and Manning's n value for the main channel (CH_N2). The results indicated that the HEW concept allows the nonlinear functional relations between watershed processes

  12. Modeling the effect of glacier recession on streamflow response using a coupled glacio-hydrological model

    DOE PAGES

    Frans, Chris D.; Clarke, Garry K. C.; Burns, P.; ...

    2014-02-27

    Here, we describe an integrated spatially distributed hydrologic and glacier dynamic model, and use it to investigate the effect of glacier recession on streamflow variations for the Upper Bow River basin, a tributary of the South Saskatchewan River. Several recent studies have suggested that observed decreases in summer flows in the South Saskatchewan River are partly due to the retreat of glaciers in the river's headwaters. Modeling the effect of glacier changes on streamflow response in river basins such as the South Saskatchewan is complicated due to the inability of most existing physically-based distributed hydrologic models to represent glacier dynamics.more » We compare predicted variations in glacier extent, snow water equivalent and streamflow discharge made with the integrated model with satellite estimates of glacier area and terminus position, observed streamflow and snow water equivalent measurements over the period of 1980 2007. Simulations with the coupled hydrology-glacier model reduce the uncertainty in streamflow predictions. Our results suggested that on average, the glacier melt contribution to the Bow River flow upstream of Lake Louise is about 30% in summer. For warm and dry years, however, the glacier melt contribution can be as large as 50% in August, whereas for cold years, it can be as small as 20% and the timing of glacier melt signature can be delayed by a month.« less

  13. Simultaneous Semi-Distributed Model Calibration Guided by Hydrologic Landscapes in the Pacific Northwest, USA

    EPA Science Inventory

    Modelling approaches to transfer hydrologically-relevant information from locations with streamflow measurements to locations without such measurements continues to be an active field of research for hydrologists. The Pacific Northwest Hydrologic Landscapes (PNW HL) provide a sol...

  14. Modeling the Hydrologic Processes of a Permeable Pavement System

    EPA Science Inventory

    A permeable pavement system can capture stormwater to reduce runoff volume and flow rate, improve onsite groundwater recharge, and enhance pollutant controls within the site. A new unit process model for evaluating the hydrologic performance of a permeable pavement system has be...

  15. Modeling of subglacial hydrological development following rapid supraglacial lake drainage.

    PubMed

    Dow, C F; Kulessa, B; Rutt, I C; Tsai, V C; Pimentel, S; Doyle, S H; van As, D; Lindbäck, K; Pettersson, R; Jones, G A; Hubbard, A

    2015-06-01

    The rapid drainage of supraglacial lakes injects substantial volumes of water to the bed of the Greenland ice sheet over short timescales. The effect of these water pulses on the development of basal hydrological systems is largely unknown. To address this, we develop a lake drainage model incorporating both (1) a subglacial radial flux element driven by elastic hydraulic jacking and (2) downstream drainage through a linked channelized and distributed system. Here we present the model and examine whether substantial, efficient subglacial channels can form during or following lake drainage events and their effect on the water pressure in the surrounding distributed system. We force the model with field data from a lake drainage site, 70 km from the terminus of Russell Glacier in West Greenland. The model outputs suggest that efficient subglacial channels do not readily form in the vicinity of the lake during rapid drainage and instead water is evacuated primarily by a transient turbulent sheet and the distributed system. Following lake drainage, channels grow but are not large enough to reduce the water pressure in the surrounding distributed system, unless preexisting channels are present throughout the domain. Our results have implications for the analysis of subglacial hydrological systems in regions where rapid lake drainage provides the primary mechanism for surface-to-bed connections. Model for subglacial hydrological analysis of rapid lake drainage eventsLimited subglacial channel growth during and following rapid lake drainagePersistence of distributed drainage in inland areas where channel growth is limited.

  16. Modeling of subglacial hydrological development following rapid supraglacial lake drainage

    PubMed Central

    Dow, C F; Kulessa, B; Rutt, I C; Tsai, V C; Pimentel, S; Doyle, S H; van As, D; Lindbäck, K; Pettersson, R; Jones, G A; Hubbard, A

    2015-01-01

    The rapid drainage of supraglacial lakes injects substantial volumes of water to the bed of the Greenland ice sheet over short timescales. The effect of these water pulses on the development of basal hydrological systems is largely unknown. To address this, we develop a lake drainage model incorporating both (1) a subglacial radial flux element driven by elastic hydraulic jacking and (2) downstream drainage through a linked channelized and distributed system. Here we present the model and examine whether substantial, efficient subglacial channels can form during or following lake drainage events and their effect on the water pressure in the surrounding distributed system. We force the model with field data from a lake drainage site, 70 km from the terminus of Russell Glacier in West Greenland. The model outputs suggest that efficient subglacial channels do not readily form in the vicinity of the lake during rapid drainage and instead water is evacuated primarily by a transient turbulent sheet and the distributed system. Following lake drainage, channels grow but are not large enough to reduce the water pressure in the surrounding distributed system, unless preexisting channels are present throughout the domain. Our results have implications for the analysis of subglacial hydrological systems in regions where rapid lake drainage provides the primary mechanism for surface-to-bed connections. Key Points Model for subglacial hydrological analysis of rapid lake drainage events Limited subglacial channel growth during and following rapid lake drainage Persistence of distributed drainage in inland areas where channel growth is limited PMID:26640746

  17. Applicability of Hydrologic Landscapes for Model Calibration ...

    EPA Pesticide Factsheets

    The Pacific Northwest Hydrologic Landscapes (PNW HL) at the assessment unit scale has provided a solid conceptual classification framework to relate and transfer hydrologically meaningful information between watersheds without access to streamflow time series. A collection of techniques were applied to the HL assessment unit composition in watersheds across the Pacific Northwest to aggregate the hydrologic behavior of the Hydrologic Landscapes from the assessment unit scale to the watershed scale. This non-trivial solution both emphasizes HL classifications within the watershed that provide that majority of moisture surplus/deficit and considers the relative position (upstream vs. downstream) of these HL classifications. A clustering algorithm was applied to the HL-based characterization of assessment units within 185 watersheds to help organize watersheds into nine classes hypothesized to have similar hydrologic behavior. The HL-based classes were used to organize and describe hydrologic behavior information about watershed classes and both predictions and validations were independently performed with regard to the general magnitude of six hydroclimatic signature values. A second cluster analysis was then performed using the independently calculated signature values as similarity metrics, and it was found that the six signature clusters showed substantial overlap in watershed class membership to those in the HL-based classes. One hypothesis set forward from thi

  18. Intercomparison of hydrological model structures and calibration approaches in climate scenario impact projections

    NASA Astrophysics Data System (ADS)

    Vansteenkiste, Thomas; Tavakoli, Mohsen; Ntegeka, Victor; De Smedt, Florimond; Batelaan, Okke; Pereira, Fernando; Willems, Patrick

    2014-11-01

    The objective of this paper is to investigate the effects of hydrological model structure and calibration on climate change impact results in hydrology. The uncertainty in the hydrological impact results is assessed by the relative change in runoff volumes and peak and low flow extremes from historical and future climate conditions. The effect of the hydrological model structure is examined through the use of five hydrological models with different spatial resolutions and process descriptions. These were applied to a medium sized catchment in Belgium. The models vary from the lumped conceptual NAM, PDM and VHM models over the intermediate detailed and distributed WetSpa model to the fully distributed MIKE SHE model. The latter model accounts for the 3D groundwater processes and interacts bi-directionally with a full hydrodynamic MIKE 11 river model. After careful and manual calibration of these models, accounting for the accuracy of the peak and low flow extremes and runoff subflows, and the changes in these extremes for changing rainfall conditions, the five models respond in a similar way to the climate scenarios over Belgium. Future projections on peak flows are highly uncertain with expected increases as well as decreases depending on the climate scenario. The projections on future low flows are more uniform; low flows decrease (up to 60%) for all models and for all climate scenarios. However, the uncertainties in the impact projections are high, mainly in the dry season. With respect to the model structural uncertainty, the PDM model simulates significantly higher runoff peak flows under future wet scenarios, which is explained by its specific model structure. For the low flow extremes, the MIKE SHE model projects significantly lower low flows in dry scenario conditions in comparison to the other models, probably due to its large difference in process descriptions for the groundwater component, the groundwater-river interactions. The effect of the model

  19. A Flexible Framework Hydrological Informatic Modeling System - HIMS

    NASA Astrophysics Data System (ADS)

    WANG, L.; Wang, Z.; Changming, L.; Li, J.; Bai, P.

    2017-12-01

    Simulating water cycling process temporally and spatially fitting for the characteristics of the study area was important for floods prediction and streamflow simulation with high accuracy, as soil properties, land scape, climate, and land managements were the critical factors influencing the non-linear relationship of rainfall-runoff at watershed scales. Most existing hydrological models cannot simulate water cycle process at different places with customized mechanisms with fixed single structure and mode. This study develops Hydro-Informatic Modeling System (HIMS) model with modular of each critical hydrological process with multiple choices for various scenarios to solve this problem. HIMS has the structure accounting for two runoff generation mechanisms of infiltration excess and saturation excess and estimated runoff with different methods including Time Variance Gain Model (TVGM), LCM which has good performance at ungauged areas, besides the widely used Soil Conservation Service-Curve Number (SCS-CN) method. Channel routing model contains the most widely used Muskingum, and kinematic wave equation with new solving method. HIMS model performance with its symbolic runoff generation model LCM was evaluated through comparison with the observed streamflow datasets of Lasha river watershed at hourly, daily, and monthly time steps. Comparisons between simulational and obervational streamflows were found with NSE higher than 0.87 and WE within ±20%. Water balance analysis about precipitation, streamflow, actual evapotranspiration (ET), and soil moisture change was conducted temporally at annual time step and it has been proved that HIMS model performance was reliable through comparison with literature results at the Lhasa River watershed.

  20. The benefits of using remotely sensed soil moisture in parameter identification of large-scale hydrological models

    NASA Astrophysics Data System (ADS)

    Wanders, N.; Bierkens, M. F. P.; de Jong, S. M.; de Roo, A.; Karssenberg, D.

    2014-08-01

    Large-scale hydrological models are nowadays mostly calibrated using observed discharge. As a result, a large part of the hydrological system, in particular the unsaturated zone, remains uncalibrated. Soil moisture observations from satellites have the potential to fill this gap. Here we evaluate the added value of remotely sensed soil moisture in calibration of large-scale hydrological models by addressing two research questions: (1) Which parameters of hydrological models can be identified by calibration with remotely sensed soil moisture? (2) Does calibration with remotely sensed soil moisture lead to an improved calibration of hydrological models compared to calibration based only on discharge observations, such that this leads to improved simulations of soil moisture content and discharge? A dual state and parameter Ensemble Kalman Filter is used to calibrate the hydrological model LISFLOOD for the Upper Danube. Calibration is done using discharge and remotely sensed soil moisture acquired by AMSR-E, SMOS, and ASCAT. Calibration with discharge data improves the estimation of groundwater and routing parameters. Calibration with only remotely sensed soil moisture results in an accurate identification of parameters related to land-surface processes. For the Upper Danube upstream area up to 40,000 km2, calibration on both discharge and soil moisture results in a reduction by 10-30% in the RMSE for discharge simulations, compared to calibration on discharge alone. The conclusion is that remotely sensed soil moisture holds potential for calibration of hydrological models, leading to a better simulation of soil moisture content throughout the catchment and a better simulation of discharge in upstream areas. This article was corrected on 15 SEP 2014. See the end of the full text for details.

  1. Integrated hydrologic and hydrodynamic modeling to assess water exchange in a data-scarce reservoir

    NASA Astrophysics Data System (ADS)

    Wu, Binbin; Wang, Guoqiang; Wang, Zhonggen; Liu, Changming; Ma, Jianming

    2017-12-01

    Integrated hydrologic and hydrodynamic modeling is useful in evaluating hydrodynamic characteristics (e.g. water exchange processes) in data-scarce water bodies, however, most studies lack verification of the hydrologic model. Here, water exchange (represented by water age) was investigated through integrated hydrologic and hydrodynamic modeling of the Hongfeng Reservoir, a poorly gauged reservoir in southwest China. The performance of the hydrologic model and parameter replacement among sub-basins with hydrological similarity was verified by historical data. Results showed that hydrological similarity based on the hierarchical cluster analysis and topographic index probability density distribution was reliable with satisfactory performance of parameter replacement. The hydrodynamic model was verified using daily water levels and water temperatures from 2009 and 2010. The water exchange processes in the Hongfeng Reservoir are very complex with temporal, vertical, and spatial variations. The temporal water age was primarily controlled by the variable inflow and outflow, and the maximum and minimum ages for the site near the dam were 406.10 d (15th June) and 90.74 d (3rd August), respectively, in 2010. Distinct vertical differences in water age showed that surface flow, interflow, and underflow appeared alternately, depending on the season and water depth. The worst water exchange situation was found in the central areas of the North Lake with the highest water ages in the bottom on both 15th June and 3rd August, in 2010. Comparison of the spatial water ages revealed that the more favorable hydraulic conditions on 3rd August mainly improved the water exchange in the dam areas and most areas of the South Lake, but had little effect on the bottom layers of the other deepest areas in the South and North Lakes. The presented framework can be applied in other data-scarce waterbodies worldwide to provide better understanding of water exchange processes.

  2. Parallelization of a hydrological model using the message passing interface

    USGS Publications Warehouse

    Wu, Yiping; Li, Tiejian; Sun, Liqun; Chen, Ji

    2013-01-01

    With the increasing knowledge about the natural processes, hydrological models such as the Soil and Water Assessment Tool (SWAT) are becoming larger and more complex with increasing computation time. Additionally, other procedures such as model calibration, which may require thousands of model iterations, can increase running time and thus further reduce rapid modeling and analysis. Using the widely-applied SWAT as an example, this study demonstrates how to parallelize a serial hydrological model in a Windows® environment using a parallel programing technology—Message Passing Interface (MPI). With a case study, we derived the optimal values for the two parameters (the number of processes and the corresponding percentage of work to be distributed to the master process) of the parallel SWAT (P-SWAT) on an ordinary personal computer and a work station. Our study indicates that model execution time can be reduced by 42%–70% (or a speedup of 1.74–3.36) using multiple processes (two to five) with a proper task-distribution scheme (between the master and slave processes). Although the computation time cost becomes lower with an increasing number of processes (from two to five), this enhancement becomes less due to the accompanied increase in demand for message passing procedures between the master and all slave processes. Our case study demonstrates that the P-SWAT with a five-process run may reach the maximum speedup, and the performance can be quite stable (fairly independent of a project size). Overall, the P-SWAT can help reduce the computation time substantially for an individual model run, manual and automatic calibration procedures, and optimization of best management practices. In particular, the parallelization method we used and the scheme for deriving the optimal parameters in this study can be valuable and easily applied to other hydrological or environmental models.

  3. EMTERNALITIES - THE CASE OF AGRO-ECOSYSTEMS

    EPA Science Inventory

    This paper deals with the role of ecosystem services prior to crop production and uses this example to introduce emternalites in agro-ecosystems. Emternalities are best viewed as the quasi counterpart of established economic externalities, except that they designate unassessed i...

  4. Diagnosing hydrological limitations of a Land Surface Model: application of JULES to a deep-groundwater chalk basin

    NASA Astrophysics Data System (ADS)

    Le Vine, N.; Butler, A.; McIntyre, N.; Jackson, C.

    2015-08-01

    Land Surface Models (LSMs) are prospective starting points to develop a global hyper-resolution model of the terrestrial water, energy and biogeochemical cycles. However, there are some fundamental limitations of LSMs related to how meaningfully hydrological fluxes and stores are represented. A diagnostic approach to model evaluation is taken here that exploits hydrological expert knowledge to detect LSM inadequacies through consideration of the major behavioural functions of a hydrological system: overall water balance, vertical water redistribution in the unsaturated zone, temporal water redistribution and spatial water redistribution over the catchment's groundwater and surface water systems. Three types of information are utilised to improve the model's hydrology: (a) observations, (b) information about expected response from regionalised data, and (c) information from an independent physics-based model. The study considers the JULES (Joint UK Land Environmental Simulator) LSM applied to a deep-groundwater chalk catchment in the UK. The diagnosed hydrological limitations and the proposed ways to address them are indicative of the challenges faced while transitioning to a global high resolution model of the water cycle.

  5. Diagnosing hydrological limitations of a land surface model: application of JULES to a deep-groundwater chalk basin

    NASA Astrophysics Data System (ADS)

    Le Vine, N.; Butler, A.; McIntyre, N.; Jackson, C.

    2016-01-01

    Land surface models (LSMs) are prospective starting points to develop a global hyper-resolution model of the terrestrial water, energy, and biogeochemical cycles. However, there are some fundamental limitations of LSMs related to how meaningfully hydrological fluxes and stores are represented. A diagnostic approach to model evaluation and improvement is taken here that exploits hydrological expert knowledge to detect LSM inadequacies through consideration of the major behavioural functions of a hydrological system: overall water balance, vertical water redistribution in the unsaturated zone, temporal water redistribution, and spatial water redistribution over the catchment's groundwater and surface-water systems. Three types of information are utilized to improve the model's hydrology: (a) observations, (b) information about expected response from regionalized data, and (c) information from an independent physics-based model. The study considers the JULES (Joint UK Land Environmental Simulator) LSM applied to a deep-groundwater chalk catchment in the UK. The diagnosed hydrological limitations and the proposed ways to address them are indicative of the challenges faced while transitioning to a global high resolution model of the water cycle.

  6. Evaluation of Hydrologic Simulations Developed Using Multi-Model Synthesis and Remotely-Sensed Data within a Portfolio of Calibration Strategies

    NASA Astrophysics Data System (ADS)

    Lafontaine, J.; Hay, L.; Markstrom, S. L.

    2016-12-01

    The United States Geological Survey (USGS) has developed a National Hydrologic Model (NHM) to support coordinated, comprehensive and consistent hydrologic model development, and facilitate the application of hydrologic simulations within the conterminous United States (CONUS). As many stream reaches in the CONUS are either not gaged, or are substantially impacted by water use or flow regulation, ancillary information must be used to determine reasonable parameter estimations for streamflow simulations. Hydrologic models for 1,576 gaged watersheds across the CONUS were developed to test the feasibility of improving streamflow simulations linking physically-based hydrologic models with remotely-sensed data products (i.e. snow water equivalent). Initially, the physically-based models were calibrated to measured streamflow data to provide a baseline for comparison across multiple calibration strategy tests. In addition, not all ancillary datasets are appropriate for application to all parts of the CONUS (e.g. snow water equivalent in the southeastern U.S., where snow is a rarity). As it is not expected that any one data product or model simulation will be sufficient for representing hydrologic behavior across the entire CONUS, a systematic evaluation of which data products improve hydrologic simulations for various regions across the CONUS was performed. The resulting portfolio of calibration strategies can be used to guide selection of an appropriate combination of modeled and measured information for hydrologic model development and calibration. In addition, these calibration strategies have been developed to be flexible so that new data products can be assimilated. This analysis provides a foundation to understand how well models work when sufficient streamflow data are not available and could be used to further inform hydrologic model parameter development for ungaged areas.

  7. Future discharge drought across climate regions around the world modelled with a synthetic hydrological modelling approach forced by three general circulation models

    NASA Astrophysics Data System (ADS)

    Wanders, N.; Van Lanen, H. A. J.

    2015-03-01

    Hydrological drought characteristics (drought in groundwater and streamflow) likely will change in the 21st century as a result of climate change. The magnitude and directionality of these changes and their dependency on climatology and catchment characteristics, however, is uncertain. In this study a conceptual hydrological model was forced by downscaled and bias-corrected outcome from three general circulation models for the SRES A2 emission scenario (GCM forced models), and the WATCH Forcing Data set (reference model). The threshold level method was applied to investigate drought occurrence, duration and severity. Results for the control period (1971-2000) show that the drought characteristics of each GCM forced model reasonably agree with the reference model for most of the climate types, suggesting that the climate models' results after post-processing produce realistic outcomes for global drought analyses. For the near future (2021-2050) and far future (2071-2100) the GCM forced models show a decrease in drought occurrence for all major climates around the world and increase of both average drought duration and deficit volume of the remaining drought events. The largest decrease in hydrological drought occurrence is expected in cold (D) climates where global warming results in a decreased length of the snow season and an increased precipitation. In the dry (B) climates the smallest decrease in drought occurrence is expected to occur, which probably will lead to even more severe water scarcity. However, in the extreme climate regions (desert and polar), the drought analysis for the control period showed that projections of hydrological drought characteristics are most uncertain. On a global scale the increase in hydrological drought duration and severity in multiple regions will lead to a higher impact of drought events, which should motivate water resource managers to timely anticipate the increased risk of more severe drought in groundwater and streamflow

  8. The evolution of process-based hydrologic models: historical challenges and the collective quest for physical realism

    NASA Astrophysics Data System (ADS)

    Clark, Martyn P.; Bierkens, Marc F. P.; Samaniego, Luis; Woods, Ross A.; Uijlenhoet, Remko; Bennett, Katrina E.; Pauwels, Valentijn R. N.; Cai, Xitian; Wood, Andrew W.; Peters-Lidard, Christa D.

    2017-07-01

    The diversity in hydrologic models has historically led to great controversy on the correct approach to process-based hydrologic modeling, with debates centered on the adequacy of process parameterizations, data limitations and uncertainty, and computational constraints on model analysis. In this paper, we revisit key modeling challenges on requirements to (1) define suitable model equations, (2) define adequate model parameters, and (3) cope with limitations in computing power. We outline the historical modeling challenges, provide examples of modeling advances that address these challenges, and define outstanding research needs. We illustrate how modeling advances have been made by groups using models of different type and complexity, and we argue for the need to more effectively use our diversity of modeling approaches in order to advance our collective quest for physically realistic hydrologic models.

  9. The evolution of process-based hydrologic models: historical challenges and the collective quest for physical realism

    NASA Astrophysics Data System (ADS)

    Clark, M. P.; Nijssen, B.; Wood, A.; Mizukami, N.; Newman, A. J.

    2017-12-01

    The diversity in hydrologic models has historically led to great controversy on the "correct" approach to process-based hydrologic modeling, with debates centered on the adequacy of process parameterizations, data limitations and uncertainty, and computational constraints on model analysis. In this paper, we revisit key modeling challenges on requirements to (1) define suitable model equations, (2) define adequate model parameters, and (3) cope with limitations in computing power. We outline the historical modeling challenges, provide examples of modeling advances that address these challenges, and define outstanding research needs. We illustrate how modeling advances have been made by groups using models of different type and complexity, and we argue for the need to more effectively use our diversity of modeling approaches in order to advance our collective quest for physically realistic hydrologic models.

  10. Hydrologic modeling for water resource assessment in a developing country: the Rwanda case study

    Treesearch

    Steve McNulty; Erika Cohen Mack; Ge Sun; Peter Caldwell

    2016-01-01

    Accurate water resources assessment using hydrologic models can be a challenge anywhere, but particularly for developing countries with limited financial and technical resources. Developing countries could most benefit from the water resource planning capabilities that hydrologic models can provide, but these countries are least likely to have the data needed to run ...

  11. Coupling hydrological modeling and support vector regression to model hydropeaking in alpine catchments.

    PubMed

    Chiogna, Gabriele; Marcolini, Giorgia; Liu, Wanying; Pérez Ciria, Teresa; Tuo, Ye

    2018-08-15

    Water management in the alpine region has an important impact on streamflow. In particular, hydropower production is known to cause hydropeaking i.e., sudden fluctuations in river stage caused by the release or storage of water in artificial reservoirs. Modeling hydropeaking with hydrological models, such as the Soil Water Assessment Tool (SWAT), requires knowledge of reservoir management rules. These data are often not available since they are sensitive information belonging to hydropower production companies. In this short communication, we propose to couple the results of a calibrated hydrological model with a machine learning method to reproduce hydropeaking without requiring the knowledge of the actual reservoir management operation. We trained a support vector machine (SVM) with SWAT model outputs, the day of the week and the energy price. We tested the model for the Upper Adige river basin in North-East Italy. A wavelet analysis showed that energy price has a significant influence on river discharge, and a wavelet coherence analysis demonstrated the improved performance of the SVM model in comparison to the SWAT model alone. The SVM model was also able to capture the fluctuations in streamflow caused by hydropeaking when both energy price and river discharge displayed a complex temporal dynamic. Copyright © 2018 Elsevier B.V. All rights reserved.

  12. Repurposing of open data through large scale hydrological modelling - hypeweb.smhi.se

    NASA Astrophysics Data System (ADS)

    Strömbäck, Lena; Andersson, Jafet; Donnelly, Chantal; Gustafsson, David; Isberg, Kristina; Pechlivanidis, Ilias; Strömqvist, Johan; Arheimer, Berit

    2015-04-01

    Hydrological modelling demands large amounts of spatial data, such as soil properties, land use, topography, lakes and reservoirs, ice and snow coverage, water management (e.g. irrigation patterns and regulations), meteorological data and observed water discharge in rivers. By using such data, the hydrological model will in turn provide new data that can be used for new purposes (i.e. re-purposing). This presentation will give an example of how readily available open data from public portals have been re-purposed by using the Hydrological Predictions for the Environment (HYPE) model in a number of large-scale model applications covering numerous subbasins and rivers. HYPE is a dynamic, semi-distributed, process-based, and integrated catchment model. The model output is launched as new Open Data at the web site www.hypeweb.smhi.se to be used for (i) Climate change impact assessments on water resources and dynamics; (ii) The European Water Framework Directive (WFD) for characterization and development of measure programs to improve the ecological status of water bodies; (iii) Design variables for infrastructure constructions; (iv) Spatial water-resource mapping; (v) Operational forecasts (1-10 days and seasonal) on floods and droughts; (vi) Input to oceanographic models for operational forecasts and marine status assessments; (vii) Research. The following regional domains have been modelled so far with different resolutions (number of subbasins within brackets): Sweden (37 000), Europe (35 000), Arctic basin (30 000), La Plata River (6 000), Niger River (800), Middle-East North-Africa (31 000), and the Indian subcontinent (6 000). The Hype web site provides several interactive web applications for exploring results from the models. The user can explore an overview of various water variables for historical and future conditions. Moreover the user can explore and download historical time series of discharge for each basin and explore the performance of the model

  13. Regionalization Study of Satellite based Hydrological Model (SHM) in Hydrologically Homogeneous River Basins of India

    NASA Astrophysics Data System (ADS)

    Kumari, Babita; Paul, Pranesh Kumar; Singh, Rajendra; Mishra, Ashok; Gupta, Praveen Kumar; Singh, Raghvendra P.

    2017-04-01

    A new semi-distributed conceptual hydrological model, namely Satellite based Hydrological Model (SHM), has been developed under 'PRACRITI-2' program of Space Application Centre (SAC), Ahmedabad for sustainable water resources management of India by using data from Indian Remote Sensing satellites. Entire India is divided into 5km x 5km grid cells and properties at the center of the cells are assumed to represent the property of the cells. SHM contains five modules namely surface water, forest, snow, groundwater and routing. Two empirical equations (SCS-CN and Hargreaves) and water balance method have been used in the surface water module; the forest module is based on the calculations of water balancing & dynamics of subsurface. 2-D Boussinesq equation is used for groundwater modelling which is solved using implicit finite-difference. The routing module follows a distributed routing approach which requires flow path and network with the key point of travel time estimation. The aim of this study is to evaluate the performance of SHM using regionalization technique which also checks the usefulness of a model in data scarce condition or for ungauged basins. However, homogeneity analysis is pre-requisite to regionalization. Similarity index (Φ) and hierarchical agglomerative cluster analysis are adopted to test the homogeneity in terms of physical attributes of three basins namely Brahmani (39,033 km km^2)), Baitarani (10,982 km km^2)) and Kangsabati (9,660 km km^2)) with respect to Subarnarekha (29,196 km km^2)) basin. The results of both homogeneity analysis show that Brahmani basin is the most homogeneous with respect to Subarnarekha river basin in terms of physical characteristics (land use land cover classes, soiltype and elevation). The calibration and validation of model parameters of Brahmani basin is in progress which are to be transferred into the SHM set up of Subarnarekha basin and results are to be compared with the results of calibrated and validated

  14. Spatial interpolation schemes of daily precipitation for hydrologic modeling

    USGS Publications Warehouse

    Hwang, Y.; Clark, M.R.; Rajagopalan, B.; Leavesley, G.

    2012-01-01

    Distributed hydrologic models typically require spatial estimates of precipitation interpolated from sparsely located observational points to the specific grid points. We compare and contrast the performance of regression-based statistical methods for the spatial estimation of precipitation in two hydrologically different basins and confirmed that widely used regression-based estimation schemes fail to describe the realistic spatial variability of daily precipitation field. The methods assessed are: (1) inverse distance weighted average; (2) multiple linear regression (MLR); (3) climatological MLR; and (4) locally weighted polynomial regression (LWP). In order to improve the performance of the interpolations, the authors propose a two-step regression technique for effective daily precipitation estimation. In this simple two-step estimation process, precipitation occurrence is first generated via a logistic regression model before estimate the amount of precipitation separately on wet days. This process generated the precipitation occurrence, amount, and spatial correlation effectively. A distributed hydrologic model (PRMS) was used for the impact analysis in daily time step simulation. Multiple simulations suggested noticeable differences between the input alternatives generated by three different interpolation schemes. Differences are shown in overall simulation error against the observations, degree of explained variability, and seasonal volumes. Simulated streamflows also showed different characteristics in mean, maximum, minimum, and peak flows. Given the same parameter optimization technique, LWP input showed least streamflow error in Alapaha basin and CMLR input showed least error (still very close to LWP) in Animas basin. All of the two-step interpolation inputs resulted in lower streamflow error compared to the directly interpolated inputs. ?? 2011 Springer-Verlag.

  15. Validating a spatially distributed hydrological model with soil morphology data

    NASA Astrophysics Data System (ADS)

    Doppler, T.; Honti, M.; Zihlmann, U.; Weisskopf, P.; Stamm, C.

    2013-10-01

    Spatially distributed hydrological models are popular tools in hydrology and they are claimed to be useful to support management decisions. Despite the high spatial resolution of the computed variables, calibration and validation is often carried out only on discharge time-series at specific locations due to the lack of spatially distributed reference data. Because of this restriction, the predictive power of these models, with regard to predicted spatial patterns, can usually not be judged. An example of spatial predictions in hydrology is the prediction of saturated areas in agricultural catchments. These areas can be important source areas for the transport of agrochemicals to the stream. We set up a spatially distributed model to predict saturated areas in a 1.2 km2 catchment in Switzerland with moderate topography. Around 40% of the catchment area are artificially drained. We measured weather data, discharge and groundwater levels in 11 piezometers for 1.5 yr. For broadening the spatially distributed data sets that can be used for model calibration and validation, we translated soil morphological data available from soil maps into an estimate of the duration of soil saturation in the soil horizons. We used redox-morphology signs for these estimates. This resulted in a data set with high spatial coverage on which the model predictions were validated. In general, these saturation estimates corresponded well to the measured groundwater levels. We worked with a model that would be applicable for management decisions because of its fast calculation speed and rather low data requirements. We simultaneously calibrated the model to the groundwater levels in the piezometers and discharge. The model was able to reproduce the general hydrological behavior of the catchment in terms of discharge and absolute groundwater levels. However, the accuracy of the groundwater level predictions was not high enough to be used for the prediction of saturated areas. The groundwater

  16. The Effect of Modeling and Visualization Resources on Student Understanding of Physical Hydrology

    ERIC Educational Resources Information Center

    Marshall, Jilll A.; Castillo, Adam J.; Cardenas, M. Bayani

    2015-01-01

    We investigated the effect of modeling and visualization resources on upper-division, undergraduate and graduate students' performance on an open-ended assessment of their understanding of physical hydrology. The students were enrolled in one of five sections of a physical hydrology course. In two of the sections, students completed homework…

  17. Modeling the hydrological and mechanical effect of roots on shallow landslides

    NASA Astrophysics Data System (ADS)

    Arnone, E.; Caracciolo, D.; Noto, L. V.; Preti, F.; Bras, R. L.

    2016-11-01

    This study proposes a new methodology for estimating the additional shear strength (or cohesion) exerted by vegetation roots on slope stability analysis within a coupled hydrological-stability model. The mechanical root cohesion is estimated within a Fiber Bundle Model framework that allows for the evaluation of the root strength as a function of stress-strain relationships of populations of fibers. The use of such model requires the knowledge of the root architecture. A branching topology model based on Leonardo's rule is developed, providing an estimation of the amount of roots and the distribution of diameters with depth. The proposed methodology has been implemented into an existing distributed hydrological-stability model able to simulate the dynamics of factor of safety as a function of soil moisture dynamics. The model also accounts for the hydrological effects of vegetation, which reduces soil water content via root water uptake, thus increasing the stability. The entire methodology has been tested in a synthetic hillslope with two configurations of vegetation type, i.e., trees and shrubs, which have been compared to a configuration without vegetation. The vegetation has been characterized using roots data of two mediterranean plant species. The results demonstrate the capabilities of the topological model in accurately reproducing the observed root structure of the analyzed species. For the environmental setting modeled, the effects of root uptake might be more significant than the mechanical reinforcement; the additional resistance depends strictly on the vegetation root depth. Finally, for the simulated climatic environment, landslides are seasonal, in agreement with past observations.

  18. Evaluating hydrological model performance using information theory-based metrics

    USDA-ARS?s Scientific Manuscript database

    The accuracy-based model performance metrics not necessarily reflect the qualitative correspondence between simulated and measured streamflow time series. The objective of this work was to use the information theory-based metrics to see whether they can be used as complementary tool for hydrologic m...

  19. A balanced water layer concept for subglacial hydrology in large scale ice sheet models

    NASA Astrophysics Data System (ADS)

    Goeller, S.; Thoma, M.; Grosfeld, K.; Miller, H.

    2012-12-01

    There is currently no doubt about the existence of a wide-spread hydrological network under the Antarctic ice sheet, which lubricates the ice base and thus leads to increased ice velocities. Consequently, ice models should incorporate basal hydrology to obtain meaningful results for future ice dynamics and their contribution to global sea level rise. Here, we introduce the balanced water layer concept, covering two prominent subglacial hydrological features for ice sheet modeling on a continental scale: the evolution of subglacial lakes and balance water fluxes. We couple it to the thermomechanical ice-flow model RIMBAY and apply it to a synthetic model domain inspired by the Gamburtsev Mountains, Antarctica. In our experiments we demonstrate the dynamic generation of subglacial lakes and their impact on the velocity field of the overlaying ice sheet, resulting in a negative ice mass balance. Furthermore, we introduce an elementary parametrization of the water flux-basal sliding coupling and reveal the predominance of the ice loss through the resulting ice streams against the stabilizing influence of less hydrologically active areas. We point out, that established balance flux schemes quantify these effects only partially as their ability to store subglacial water is lacking.

  20. Land-use change trajectories up to 2050. Insights from a global agro-economic model comparison

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Schmitz, Christoph; van Meijl, Hans; Kyle, G. Page

    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 comparison of global agro-economic models that have harmonized drivers of population, GDP, and biophysical yields. The comparison allows us to ask two research questions: (1) How much cropland will be used under different socioeconomic and climate change scenarios? (2) How can differences in model results be explained? The comparison includes four partial and six general equilibrium models that differ in how theymore » model land supply and amount of potentially available land. We analyze results of two different socioeconomic scenarios and three climate scenarios (one with constant climate). Most models (7 out of 10) project an increase of cropland of 10–25% by 2050 compared to 2005 (under constant climate), but one model projects a decrease. Pasture land expands in some models, which increase the treat on natural vegetation further. Across all models most of the cropland expansion takes place in South America and sub-Saharan Africa. In general, the strongest differences in model results are related to differences in the costs of land expansion, the endogenous productivity responses, and the assumptions about potential cropland.« less

  1. Informing a hydrological model of the Ogooué with multi-mission remote sensing data

    NASA Astrophysics Data System (ADS)

    Kittel, Cecile; Bauer-Gottwein, Peter; Nielsen, Karina; Tøttrup, Christian

    2017-04-01

    Knowledge on hydrological regimes of river basins is crucial for water management. However, data requirements often limit the applicability of hydrological models in basins with scarce in-situ data. Remote sensing provides a unique possibility to acquire information on hydrological variables in these basins. This study explores how multi-mission remote sensing data can inform a hydrological model. The Ogooué basin in Gabon is used as study area. No previous modelling efforts have been conducted for the basin and only historical flow and precipitation observations are available. Publicly available remote sensing observations are used to parametrize, force, calibrate and validate a hydrological model of the Ogooué. The modelling framework used in the study, is a lumped conceptual rainfall-runoff model based on the Budyko framework coupled to a Muskingum routing scheme. Precipitation is a crucial driver of the land-surface water balance, therefore two satellite-based rainfall estimates, Tropical Rainfall Measuring Mission (TRMM) product 3B42 version 7 and Famine Early Warning System - Rainfall Estimate (FEWS-RFE), are compared. The comparison shows good seasonal and spatial agreement between the products; however, TRMM consistently predicts significantly more precipitation: 1726 mm on average per year against 1556 mm for FEWS-RFE. Best modeling results are obtained with the TRMM precipitation forcing. Model calibration combines historical in-situ flow observations and GRACE total water storage observations using the Jet Propulsion Laboratory (JPL) mascon solution in a multi-objective approach. The two models are calibrated using flow duration curves and climatology benchmarks to overcome the lack of simultaneity between simulated and observed discharge. The objectives are aggregated into a global objective function, and the models are calibrated using the Shuffled Complex Evolution Algorithm. Water height observations from drifting orbit altimetry missions are

  2. Modelling past hydrology of an interfluve area in the Campine region (NE Belgium)

    NASA Astrophysics Data System (ADS)

    Leterme, Bertrand; Beerten, Koen; Gedeon, Matej; Vandersteen, Katrijn

    2015-04-01

    This study aims at hydrological model verification of a small lowland interfluve area (18.6 km²) in NE Belgium, for conditions that are different than today. We compare the current state with five reference periods in the past (AD 1500, 1770, 1854, 1909 and 1961) representing important stages of landscape evolution in the study area. Historical information and proxy data are used to derive conceptual model features and boundary conditions specific to each period: topography, surface water geometry (canal, drains and lakes), land use, soils, vegetation and climate. The influence of landscape evolution on the hydrological cycle is assessed using numerical simulations of a coupled unsaturated zone - groundwater model (HYDRUS-MODFLOW). The induced hydrological changes are assessed in terms of groundwater level, recharge, evapotranspiration, and surface water discharge. HYDRUS-MODFLOW coupling allows including important processes such as the groundwater contribution to evapotranspiration. Major land use change occurred between AD 1854 and 1909, with about 41% of the study area being converted from heath to coniferous forest, together with the development of a drainage network. Results show that this led to a significant decrease of groundwater recharge and lowering of the groundwater table. A limitation of the study lies in the comparison of simulated past hydrology with appropriate palaeo-records. Examples are given as how some indicators (groundwater head, swamp zones) can be used to tend to model validation. Quantifying the relative impact of land use and climate changes requires running sensitivity simulations where the models using alternative land use are run with the climate forcing of other periods. A few examples of such sensitivity runs are presented in order to compare the influence of land use and climate change on the study area hydrology.

  3. A new spatial snow distribution in hydrological models parameterized from observed spatial variability of precipitation.

    NASA Astrophysics Data System (ADS)

    Skaugen, Thomas; Weltzien, Ingunn

    2016-04-01

    The traditional catchment hydrological model with its many free calibration parameters is not a well suited tool for prediction under conditions for which is has not been calibrated. Important tasks for hydrological modelling such as prediction in ungauged basins and assessing hydrological effects of climate change are hence not solved satisfactory. In order to reduce the number of calibration parameters in hydrological models we have introduced a new model which uses a dynamic gamma distribution as the spatial frequency distribution of snow water equivalent (SWE). The parameters are estimated from observed spatial variability of precipitation and the magnitude of accumulation and melting events and are hence not subject to calibration. The relationship between spatial mean and variance of precipitation is found to follow a pattern where decreasing temporal correlation with increasing accumulation or duration of the event leads to a levelling off or even a decrease of the spatial variance. The new model for snow distribution is implemented in the, already parameter parsimonious, DDD (Distance Distribution Dynamics) hydrological model and was tested for 71 Norwegian catchments. We compared the new snow distribution model with the current operational snow distribution model where a fixed, calibrated coefficient of variation parameterizes a log-normal model for snow distribution. Results show that the precision of runoff simulations is equal, but that the new snow distribution model better simulates snow covered area (SCA) when compared with MODIS satellite derived snow cover. In addition, SWE is simulated more realistically in that seasonal snow is melted out and the building up of "snow towers" is prevented and hence spurious trends in SWE.

  4. Including policy and management in socio-hydrology models: initial conceptualizations

    NASA Astrophysics Data System (ADS)

    Hermans, Leon; Korbee, Dorien

    2017-04-01

    Socio-hydrology studies the interactions in coupled human-water systems. So far, the use of dynamic models that capture the direct feedback between societal and hydrological systems has been dominant. What has not yet been included with any particular emphasis, is the policy or management layer, which is a central element in for instance integrated water resources management (IWRM) or adaptive delta management (ADM). Studying the direct interactions between human-water systems generates knowledges that eventually helps influence these interactions in ways that may ensure better outcomes - for society and for the health and sustainability of water systems. This influence sometimes occurs through spontaneous emergence, uncoordinated by societal agents - private sector, citizens, consumers, water users. However, the term 'management' in IWRM and ADM also implies an additional coordinated attempt through various public actors. This contribution is a call to include the policy and management dimension more prominently into the research focus of the socio-hydrology field, and offers first conceptual variables that should be considered in attempts to include this policy or management layer in socio-hydrology models. This is done by drawing on existing frameworks to study policy processes throughout both planning and implementation phases. These include frameworks such as the advocacy coalition framework, collective learning and policy arrangements, which all emphasis longer-term dynamics and feedbacks between actor coalitions in strategic planning and implementation processes. A case about longter-term dynamics in the management of the Haringvliet in the Netherlands is used to illustrate the paper.

  5. The MERINOVA project: MEteorological RIsks as drivers of environmental inNOvation in Agro-ecosystem management

    NASA Astrophysics Data System (ADS)

    Gobin, Anne; Van de vijver, Hans; Zamani, Sepideh; Curnel, Yannick; Planchon, Viviane; Verspecht, Ann; Van Huylenbroeck, Guido

    2014-05-01

    Devastating weather-related events have captured the interest of the general public in Belgium. Extreme weather events such as droughts, heat waves and rain storms are projected to increase both in frequency and magnitude with climate change. Since more than half of the Belgian territory is managed by the agricultural sector, extreme events may have significant impacts on agro-ecosystem services and pose severe limitations to sustainable agricultural land management. The research hypothesis of the MERINOVA project is that meteorological risks act as drivers of environmental innovation in agro-ecosystem management. The major objectives are to characterise extreme meteorological events, assess the impact on Belgian agro-ecosystems, characterise their vulnerability and resilience to these events, and explore innovative adaptation options to agricultural risk management. The project comprises of five major parts that reflect the chain of risks: the hazard, its impact on different agro-ecosystems, vulnerability, risk management and risk communication. Impacts developed from physically based models not only provide information on the state of the damage at any given time, but also assist in understanding the links between different factors causing damage and determining bio-physical vulnerability. Socio-economic impacts enlarge the basis for vulnerability mapping, risk management and adaptation options. The perspective of rising risk-exposure is exacerbated further by more limits to aid received for agricultural damage and an overall reduction of direct income support to farmers. The main findings of each of these project building blocks will be communicated. MERINOVA provides for a robust and flexible framework by demonstrating its performance across Belgian agro-ecosystems, and by ensuring its relevance to policy makers and practitioners. A strong expert and end-user network is established to help disseminating and exploiting project results to meet user needs. The

  6. Hydrological processes and model representation: impact of soft data on calibration

    Treesearch

    J.G. Arnold; M.A. Youssef; H. Yen; M.J. White; A.Y. Sheshukov; A.M. Sadeghi; D.N. Moriasi; J.L. Steiner; Devendra Amatya; R.W. Skaggs; E.B. Haney; J. Jeong; M. Arabi; P.H. Gowda

    2015-01-01

    Hydrologic and water quality models are increasingly used to determine the environmental impacts of climate variability and land management. Due to differing model objectives and differences in monitored data, there are currently no universally accepted procedures for model calibration and validation in the literature. In an effort to develop accepted model calibration...

  7. Moving university hydrology education forward with community-based geoinformatics, data and modeling resources

    NASA Astrophysics Data System (ADS)

    Merwade, V.; Ruddell, B. L.

    2012-08-01

    In this opinion paper, we review recent literature related to data and modeling driven instruction in hydrology, and present our findings from surveying the hydrology education community in the United States. This paper presents an argument that that data and modeling driven geoscience cybereducation (DMDGC) approaches are essential for teaching the conceptual and applied aspects of hydrology, as a part of the broader effort to improve science, technology, engineering, and mathematics (STEM) education at the university level. The authors have undertaken a series of surveys and a workshop involving university hydrology educators to determine the state of the practice of DMDGC approaches to hydrology. We identify the most common tools and approaches currently utilized, quantify the extent of the adoption of DMDGC approaches in the university hydrology classroom, and explain the community's views on the challenges and barriers preventing DMDGC approaches from wider use. DMDGC approaches are currently emphasized at the graduate level of the curriculum, and only the most basic modeling and visualization tools are in widespread use. The community identifies the greatest barriers to greater adoption as a lack of access to easily adoptable curriculum materials and a lack of time and training to learn constantly changing tools and methods. The community's current consensus is that DMDGC approaches should emphasize conceptual learning, and should be used to complement rather than replace lecture-based pedagogies. Inadequate online material publication and sharing systems, and a lack of incentives for faculty to develop and publish materials via such systems, is also identified as a challenge. Based on these findings, we suggest that a number of steps should be taken by the community to develop the potential of DMDGC in university hydrology education, including formal development and assessment of curriculum materials, integrating lecture-format and DMDGC approaches

  8. Modeling the Hydrologic Response to Changes in Groundcover Conditions Caused by Fire Disturbances

    NASA Astrophysics Data System (ADS)

    Kikinzon, E.; Atchley, A. L.; Coon, E.; Middleton, R. S.

    2016-12-01

    Climate change and fire suppression increase wildfire activity, which alters ecosystem functions and can significantly impact hydrological response. Both wildfire and prescribed burns reduce groundcover, affect top layers of subsurface, and change the structure of overland flow pathways. To understand respective effects on surface and subsurface hydrology, it is imperative to accurately represent surface-subsurface interface pre and post-fire, and to model physical processes in groundcover components. We show mechanistic models used to describe physics in two key types of groundcover, litter and duff, in Advanced Terrestrial Simulator (ATS). Litter is considered to be a part of vegetative canopy covering the surface. It has associated water storage capacity, which allows simulating interception and drainage, and its thickness is used to evaluate surface roughness with potential effect of slowing overland flow compared to bare soil. Duff on the other hand is incorporated into the subsurface, thus requiring meshing and discretization capability to support complex geometries including pinchouts, which is necessary both for achieving desired mesh resolution and portraying bare soil patches without adversely affecting the time scale. As part of the subsurface, duff has its own hydrologic and water retention properties used to resolve infiltration and saturation limited runoff generation, run on, and infiltration processes. This enables the use of ATS for fine scale modeling of integrated hydrology with adequate representation of groundcover influence. To isolate the impact of changing groundcover, we consider a simple hill slope and study the hydrological response to varying amount and geometries of groundcover. To cover landscape characteristics produced by a wide variety of fire conditions, from high intensity to low intensity fire impacts, we simulate hydrologic response to precipitation events over a number of typical geometries and with fine control over amounts of

  9. [Correlation coefficient-based classification method of hydrological dependence variability: With auto-regression model as example].

    PubMed

    Zhao, Yu Xi; Xie, Ping; Sang, Yan Fang; Wu, Zi Yi

    2018-04-01

    Hydrological process evaluation is temporal dependent. Hydrological time series including dependence components do not meet the data consistency assumption for hydrological computation. Both of those factors cause great difficulty for water researches. Given the existence of hydrological dependence variability, we proposed a correlationcoefficient-based method for significance evaluation of hydrological dependence based on auto-regression model. By calculating the correlation coefficient between the original series and its dependence component and selecting reasonable thresholds of correlation coefficient, this method divided significance degree of dependence into no variability, weak variability, mid variability, strong variability, and drastic variability. By deducing the relationship between correlation coefficient and auto-correlation coefficient in each order of series, we found that the correlation coefficient was mainly determined by the magnitude of auto-correlation coefficient from the 1 order to p order, which clarified the theoretical basis of this method. With the first-order and second-order auto-regression models as examples, the reasonability of the deduced formula was verified through Monte-Carlo experiments to classify the relationship between correlation coefficient and auto-correlation coefficient. This method was used to analyze three observed hydrological time series. The results indicated the coexistence of stochastic and dependence characteristics in hydrological process.

  10. The evolution of process-based hydrologic models: historical challenges and the collective quest for physical realism

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Clark, Martyn P.; Bierkens, Marc F. P.; Samaniego, Luis

    The diversity in hydrologic models has historically led to great controversy on the correct approach to process-based hydrologic modeling, with debates centered on the adequacy of process parameterizations, data limitations and uncertainty, and computational constraints on model analysis. Here, we revisit key modeling challenges on requirements to (1) define suitable model equations, (2) define adequate model parameters, and (3) cope with limitations in computing power. We outline the historical modeling challenges, provide examples of modeling advances that address these challenges, and define outstanding research needs. We also illustrate how modeling advances have been made by groups using models of different type and complexity,more » and we argue for the need to more effectively use our diversity of modeling approaches in order to advance our collective quest for physically realistic hydrologic models.« less

  11. The evolution of process-based hydrologic models: historical challenges and the collective quest for physical realism

    DOE PAGES

    Clark, Martyn P.; Bierkens, Marc F. P.; Samaniego, Luis; ...

    2017-07-11

    The diversity in hydrologic models has historically led to great controversy on the correct approach to process-based hydrologic modeling, with debates centered on the adequacy of process parameterizations, data limitations and uncertainty, and computational constraints on model analysis. Here, we revisit key modeling challenges on requirements to (1) define suitable model equations, (2) define adequate model parameters, and (3) cope with limitations in computing power. We outline the historical modeling challenges, provide examples of modeling advances that address these challenges, and define outstanding research needs. We also illustrate how modeling advances have been made by groups using models of different type and complexity,more » and we argue for the need to more effectively use our diversity of modeling approaches in order to advance our collective quest for physically realistic hydrologic models.« less

  12. Groundwater modelling in conceptual hydrological models - introducing space

    NASA Astrophysics Data System (ADS)

    Boje, Søren; Skaugen, Thomas; Møen, Knut; Myrabø, Steinar

    2017-04-01

    The tiny Sæternbekken Minifelt (Muren) catchment (7500 m2) in Bærumsmarka, Norway, was during the 1990s, densely instrumented with more than a 100 observation points for measuring groundwater levels. The aim was to investigate the link between shallow groundwater dynamics and runoff. The DDD (Distance Distribution Dynamics) model is a newly developed rainfall-runoff model used operationally by the Norwegian Flood-Forecasting service at NVE. The model estimates the capacity of the subsurface reservoir at different levels of saturation and predicts overland flow. The subsurface in the DDD model has a 2-D representation that calculates the saturated and unsaturated soil moisture along a hillslope representing the entire catchment in question. The groundwater observations from more than two decades ago are used to verify assumptions of the subsurface reservoir in the DDD model and to validate its spatial representation of the subsurface reservoir. The Muren catchment will, during 2017, be re-instrumented in order to continue the work to bridge the gap between conceptual hydrological models, with typically single value or 0-dimension representation of the subsurface, and models with more realistic 2- or 3-dimension representation of the subsurface.

  13. Comparison and Validation of Hydrological E-Flow Methods through Hydrodynamic Modelling

    NASA Astrophysics Data System (ADS)

    Kuriqi, Alban; Rivaes, Rui; Sordo-Ward, Alvaro; Pinheiro, António N.; Garrote, Luis

    2017-04-01

    Flow regime determines physical habitat conditions and local biotic configuration. The development of environmental flow guidelines to support the river integrity is becoming a major concern in water resources management. In this study, we analysed two sites located in southern part of Portugal, respectively at Odelouca and Ocreza Rivers, characterised by the Mediterranean climate. Both rivers are almost in pristine condition, not regulated by dams or other diversion construction. This study presents an analysis of the effect on fish habitat suitability by the implementation of different hydrological e-flow methods. To conduct this study we employed certain hydrological e-flow methods recommended by the European Small Hydropower Association (ESHA). River hydrology assessment was based on approximately 30 years of mean daily flow data, provided by the Portuguese Water Information System (SNIRH). The biological data, bathymetry, physical and hydraulic features, and the Habitat Suitability Index for fish species were collected from extensive field works. We followed the Instream Flow Incremental Methodology (IFIM) to assess the flow-habitat relationship taking into account the habitat suitability of different instream flow releases. Initially, we analysed fish habitat suitability based on natural conditions, and we used it as reference condition for other scenarios considering the chosen hydrological e-flow methods. We accomplished the habitat modelling through hydrodynamic analysis by using River-2D model. The same methodology was applied to each scenario by considering as input the e-flows obtained from each of the hydrological method employed in this study. This contribution shows the significance of ecohydrological studies in establishing a foundation for water resources management actions. Keywords: ecohydrology, e-flow, Mediterranean rivers, river conservation, fish habitat, River-2D, Hydropower.

  14. Integrating a reservoir regulation scheme into a spatially distributed hydrological model

    DOE PAGES

    Zhao, Gang; Gao, Huili; Naz, Bibi S; ...

    2016-10-14

    During the past several decades, numerous reservoirs have been built across the world for a variety of purposes such as flood control, irrigation, municipal/industrial water supplies, and hydropower generation. Consequently, timing and magnitude of natural streamflows have been altered significantly by reservoir operations. In addition, the hydrological cycle can be modified by land-use/land-cover and climate changes. To understand the fine-scale feedback between hydrological processes and water management decisions, a distributed hydrological model embedded with a reservoir component is desired. In this study, a multi-purpose reservoir module with predefined complex operational rules was integrated into the Distributed Hydrology Soil Vegetation Modelmore » (DHSVM). Conditional operating rules, which are designed to reduce flood risk and enhance water supply reliability, were adopted in this module. The performance of the integrated model was tested over the upper Brazos River Basin in Texas, where two U.S. Army Corps of Engineers reservoirs, Lake Whitney and Aquilla Lake, are located. The integrated DHSVM was calibrated and validated using observed reservoir inflow, outflow, and storage data. The error statistics were summarized for both reservoirs on a daily, weekly, and monthly basis. Using the weekly reservoir storage for Lake Whitney as an example, the coefficient of determination (R 2) and the Nash-Sutcliff Efficiency (NSE) were 0.85 and 0.75, respectively. These results suggest that this reservoir module holds promise for use in sub-monthly hydrological simulations. Furthermore, with the new reservoir component, the DHSVM provides a platform to support adaptive water resources management under the impacts of evolving anthropogenic activities and substantial environmental changes.« less

  15. Integrating a reservoir regulation scheme into a spatially distributed hydrological model

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Zhao, Gang; Gao, Huili; Naz, Bibi S

    During the past several decades, numerous reservoirs have been built across the world for a variety of purposes such as flood control, irrigation, municipal/industrial water supplies, and hydropower generation. Consequently, timing and magnitude of natural streamflows have been altered significantly by reservoir operations. In addition, the hydrological cycle can be modified by land-use/land-cover and climate changes. To understand the fine-scale feedback between hydrological processes and water management decisions, a distributed hydrological model embedded with a reservoir component is desired. In this study, a multi-purpose reservoir module with predefined complex operational rules was integrated into the Distributed Hydrology Soil Vegetation Modelmore » (DHSVM). Conditional operating rules, which are designed to reduce flood risk and enhance water supply reliability, were adopted in this module. The performance of the integrated model was tested over the upper Brazos River Basin in Texas, where two U.S. Army Corps of Engineers reservoirs, Lake Whitney and Aquilla Lake, are located. The integrated DHSVM was calibrated and validated using observed reservoir inflow, outflow, and storage data. The error statistics were summarized for both reservoirs on a daily, weekly, and monthly basis. Using the weekly reservoir storage for Lake Whitney as an example, the coefficient of determination (R 2) and the Nash-Sutcliff Efficiency (NSE) were 0.85 and 0.75, respectively. These results suggest that this reservoir module holds promise for use in sub-monthly hydrological simulations. Furthermore, with the new reservoir component, the DHSVM provides a platform to support adaptive water resources management under the impacts of evolving anthropogenic activities and substantial environmental changes.« less

  16. Watershed Modeling Applications with the Open-Access Modular Distributed Watershed Educational Toolbox (MOD-WET) and Introductory Hydrology Textbook

    NASA Astrophysics Data System (ADS)

    Huning, L. S.; Margulis, S. A.

    2014-12-01

    Traditionally, introductory hydrology courses focus on hydrologic processes as independent or semi-independent concepts that are ultimately integrated into a watershed model near the end of the term. When an "off-the-shelf" watershed model is introduced in the curriculum, this approach can result in a potential disconnect between process-based hydrology and the inherent interconnectivity of processes within the water cycle. In order to curb this and reduce the learning curve associated with applying hydrologic concepts to complex real-world problems, we developed the open-access Modular Distributed Watershed Educational Toolbox (MOD-WET). The user-friendly, MATLAB-based toolbox contains the same physical equations for hydrological processes (i.e. precipitation, snow, radiation, evaporation, unsaturated flow, infiltration, groundwater, and runoff) that are presented in the companion e-textbook (http://aqua.seas.ucla.edu/margulis_intro_to_hydro_textbook.html) and taught in the classroom. The modular toolbox functions can be used by students to study individual hydrologic processes. These functions are integrated together to form a simple spatially-distributed watershed model, which reinforces a holistic understanding of how hydrologic processes are interconnected and modeled. Therefore when watershed modeling is introduced, students are already familiar with the fundamental building blocks that have been unified in the MOD-WET model. Extensive effort has been placed on the development of a highly modular and well-documented code that can be run on a personal computer within the commonly-used MATLAB environment. MOD-WET was designed to: 1) increase the qualitative and quantitative understanding of hydrological processes at the basin-scale and demonstrate how they vary with watershed properties, 2) emphasize applications of hydrologic concepts rather than computer programming, 3) elucidate the underlying physical processes that can often be obscured with a complicated

  17. Hydrologic Model Development and Calibration: Contrasting a Single- and Multi-Objective Approach for Comparing Model Performance

    NASA Astrophysics Data System (ADS)

    Asadzadeh, M.; Maclean, A.; Tolson, B. A.; Burn, D. H.

    2009-05-01

    Hydrologic model calibration aims to find a set of parameters that adequately simulates observations of watershed behavior, such as streamflow, or a state variable, such as snow water equivalent (SWE). There are different metrics for evaluating calibration effectiveness that involve quantifying prediction errors, such as the Nash-Sutcliffe (NS) coefficient and bias evaluated for the entire calibration period, on a seasonal basis, for low flows, or for high flows. Many of these metrics are conflicting such that the set of parameters that maximizes the high flow NS differs from the set of parameters that maximizes the low flow NS. Conflicting objectives are very likely when different calibration objectives are based on different fluxes and/or state variables (e.g., NS based on streamflow versus SWE). One of the most popular ways to balance different metrics is to aggregate them based on their importance and find the set of parameters that optimizes a weighted sum of the efficiency metrics. Comparing alternative hydrologic models (e.g., assessing model improvement when a process or more detail is added to the model) based on the aggregated objective might be misleading since it represents one point on the tradeoff of desired error metrics. To derive a more comprehensive model comparison, we solved a bi-objective calibration problem to estimate the tradeoff between two error metrics for each model. Although this approach is computationally more expensive than the aggregation approach, it results in a better understanding of the effectiveness of selected models at each level of every error metric and therefore provides a better rationale for judging relative model quality. The two alternative models used in this study are two MESH hydrologic models (version 1.2) of the Wolf Creek Research basin that differ in their watershed spatial discretization (a single Grouped Response Unit, GRU, versus multiple GRUs). The MESH model, currently under development by Environment

  18. Tracer-aided modelling to explore non-linearities in flow paths, hydrological connectivity and faecal contamination risk

    NASA Astrophysics Data System (ADS)

    Neill, A. J.; Tetzlaff, D.; Strachan, N.; Soulsby, C.

    2016-12-01

    The non-linearities of runoff generation processes are strongly influenced by the connectivity of hillslopes and channel networks, particularly where overland flow is an important runoff mechanism. Despite major advances in understanding hydrological connectivity and runoff generation, the role of connectivity in the contamination of potable water supplies by faecal pathogens from grazing animals remains unclear. This is a water quality issue with serious implications for public health. Here, we sought to understand the dynamics of hydrological connectivity, flow paths and linked faecal pathogen transport in a montane catchment in Scotland with high deer populations. We firstly calibrated, within an uncertainty framework, a parsimonious tracer-aided hydrological model to daily discharge and stream isotope data. The model, developed on the basis of past empirical and tracer studies, conceptualises the catchment as three interacting hydrological source areas (dynamic saturation zone, dynamic hillslope, and groundwater) for which water fluxes, water ages and storage-based connectivity can be simulated. We next coupled several faecal indicator organism (FIO; a common indicator of faecal pathogen contamination) behaviour and transport schemes to the robust hydrological models. A further calibration was then undertaken based on the ability of each coupled model to simulate daily FIO concentrations. This gave us a final set of coupled behavioural models from which we explored how in-stream FIO dynamics could be related to the changing connectivity between the three hydrological source areas, flow paths, water ages and consequent dominant runoff generation processes. We found that high levels of FIOs were transient and episodic, and strongly correlated with periods of high connectivity through overland flow. This non-linearity in connectivity and FIO flux was successfully captured within our dynamic, tracer-aided hydrological model.

  19. Evapotranspiration partitioning for three agro-ecosystems with contrasting moisture conditions: a comparison of an isotope method and a two-source model calculation

    NASA Astrophysics Data System (ADS)

    Wei, Z.; Lee, X.; Wen, X.; Xiao, W.

    2017-12-01

    Quantification of the contribution of transpiration (T) to evapotranspiration (ET) is a requirement for understanding changes in carbon assimilation and water cycling in a changing environment. So far, few studies have examined seasonal variability of T/ET and compared different ET partitioning methods under natural conditions across diverse agro-ecosystems. In this study, we apply a two-source model to partition ET for three agro-ecosystems (rice, wheat and corn). The model-estimated T/ET ranges from 0 to 1, with a near continuous increase over time in the early growing season when leaf area index (LAI) is less than 2.5 and then convergence towards a stable value beyond LAI of 2.5. The seasonal change in T/ET can be described well as a function of LAI, implying that LAI is a first-order factor affecting ET partitioning. The two-source model results show that the growing-season (May - September for rice, April - June for wheat and June to September for corn) T/ET is 0.50, 0.84 and 0.64, while an isotopic approach shows that T/ET is 0.74, 0.93 and 0.81 for rice, wheat and maize, respectively. The two-source model results are supported by soil lysimeter and eddy covariance measurements made during the same time period for wheat (0.87). Uncertainty analysis suggests that further improvements to the Craig-Gordon model prediction of the evaporation isotope composition and to measurement of the isotopic composition of ET are necessary to achieve accurate flux partitioning at the ecosystem scale using water isotopes as tracers.

  20. Ancient numerical daemons of conceptual hydrological modeling: 2. Impact of time stepping schemes on model analysis and prediction

    NASA Astrophysics Data System (ADS)

    Kavetski, Dmitri; Clark, Martyn P.

    2010-10-01

    Despite the widespread use of conceptual hydrological models in environmental research and operations, they remain frequently implemented using numerically unreliable methods. This paper considers the impact of the time stepping scheme on model analysis (sensitivity analysis, parameter optimization, and Markov chain Monte Carlo-based uncertainty estimation) and prediction. It builds on the companion paper (Clark and Kavetski, 2010), which focused on numerical accuracy, fidelity, and computational efficiency. Empirical and theoretical analysis of eight distinct time stepping schemes for six different hydrological models in 13 diverse basins demonstrates several critical conclusions. (1) Unreliable time stepping schemes, in particular, fixed-step explicit methods, suffer from troublesome numerical artifacts that severely deform the objective function of the model. These deformations are not rare isolated instances but can arise in any model structure, in any catchment, and under common hydroclimatic conditions. (2) Sensitivity analysis can be severely contaminated by numerical errors, often to the extent that it becomes dominated by the sensitivity of truncation errors rather than the model equations. (3) Robust time stepping schemes generally produce "better behaved" objective functions, free of spurious local optima, and with sufficient numerical continuity to permit parameter optimization using efficient quasi Newton methods. When implemented within a multistart framework, modern Newton-type optimizers are robust even when started far from the optima and provide valuable diagnostic insights not directly available from evolutionary global optimizers. (4) Unreliable time stepping schemes lead to inconsistent and biased inferences of the model parameters and internal states. (5) Even when interactions between hydrological parameters and numerical errors provide "the right result for the wrong reason" and the calibrated model performance appears adequate, unreliable