Science.gov

Sample records for hydrology conceptual model

  1. 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

  2. Dynamic Multicriteria Evaluation of Conceptual Hydrological Models

    NASA Astrophysics Data System (ADS)

    de Vos, N. J.; Rientjes, T. H.; Fenicia, F.; Gupta, H. V.

    2007-12-01

    Accurate and precise forecasts of river streamflows are crucial for successful management of water resources and under the threat of hydrological extremes such as floods and droughts. Conceptual rainfall-runoff models are the most popular approach in flood forecasting. However, the calibration and evaluation of such models is often oversimplified by the use of performance statistics that largely ignore the dynamic character of a watershed system. This research aims to find novel ways of model evaluation by identifying periods of hydrologic similarity and customizing evaluation within each period using multiple criteria. A dynamic approach to hydrologic model identification, calibration and testing can be realized by applying clustering algorithms (e.g., Self-Organizing Map, Fuzzy C-means algorithm) to hydrological data. These algorithms are able to identify clusters in the data that represent periods of hydrological similarity. In this way, dynamic catchment system behavior can be simplified within the clusters that are identified. Although clustering requires a number of subjective choices, new insights into the hydrological functioning of a catchment can be obtained. Finally, separate model multi-criteria calibration and evaluation is performed for each of the clusters. Such a model evaluation procedure shows to be reliable and gives much-needed feedback on exactly where certain model structures fail. Several clustering algorithms were tested on two data sets of meso-scale and large-scale catchments. The results show that the clustering algorithms define categories that reflect hydrological process understanding: dry/wet seasons, rising/falling hydrograph limbs, precipitation-driven/ non-driven periods, etc. The results of various clustering algorithms are compared and validated using expert knowledge. Calibration results on a conceptual hydrological model show that the common practice of single-criteria calibration over the complete time series fails to perform

  3. Optimal combinations of specialized conceptual hydrological models

    NASA Astrophysics Data System (ADS)

    Kayastha, Nagendra; Lal Shrestha, Durga; Solomatine, Dimitri

    2010-05-01

    In hydrological modelling it is a usual practice to use a single lumped conceptual model for hydrological simulations at all regimes. However often the simplicity of the modelling paradigm leads to errors in represent all the complexity of the physical processes in the catchment. A solution could be to model various hydrological processes separately by differently parameterized models, and to combine them. Different hydrological models have varying performance in reproducing catchment response. Generally it cannot be represented precisely in different segments of the hydrograph: some models performed well in simulating the peak flows, while others do well in capturing the low flows. Better performance can be achieved if a model being applied to the catchment using different model parameters that are calibrated using criteria favoring high or low flows. In this work we use a modular approach to simulate hydrology of a catchment, wherein multiple models are applied to replicate the catchment responses and each "specialist" model is calibrated according to a specific objective function which is chosen in a way that forces the model to capture certain aspects of the hydrograph, and outputs of models are combined using so-called "fuzzy committee". Such multi-model approach has been already previously implemented in the development of data driven and conceptual models (Fenicia et al., 2007), but its perfomance was considered only during the calibration period. In this study we tested an application to conceptual models in both calibration and verification period. In addition, we tested the sensitivity of the result to the use of different weightings used in the objective functions formulations, and memberbship functions used in the committee. The study was carried out for Bagamati catchment in Nepal and Brue catchment in United Kingdoms with the MATLAB-based implementation of HBV model. Multi-objective evolutionary optimization genetic algorithm (Deb, 2001) was used to

  4. Climate model uncertainty versus conceptual geological uncertainty in hydrological modeling

    NASA Astrophysics Data System (ADS)

    Sonnenborg, T. O.; Seifert, D.; Refsgaard, J. C.

    2015-09-01

    Projections of climate change impact are associated with a cascade of uncertainties including in CO2 emission scenarios, climate models, downscaling and impact models. The relative importance of the individual uncertainty sources is expected to depend on several factors including the quantity that is projected. In the present study the impacts of climate model uncertainty and geological model uncertainty on hydraulic head, stream flow, travel time and capture zones are evaluated. Six versions of a physically based and distributed hydrological model, each containing a unique interpretation of the geological structure of the model area, are forced by 11 climate model projections. Each projection of future climate is a result of a GCM-RCM model combination (from the ENSEMBLES project) forced by the same CO2 scenario (A1B). The changes from the reference period (1991-2010) to the future period (2081-2100) in projected hydrological variables are evaluated and the effects of geological model and climate model uncertainties are quantified. The results show that uncertainty propagation is context-dependent. While the geological conceptualization is the dominating uncertainty source for projection of travel time and capture zones, the uncertainty due to the climate models is more important for groundwater hydraulic heads and stream flow.

  5. Climate model uncertainty vs. conceptual geological uncertainty in hydrological modeling

    NASA Astrophysics Data System (ADS)

    Sonnenborg, T. O.; Seifert, D.; Refsgaard, J. C.

    2015-04-01

    Projections of climate change impact are associated with a cascade of uncertainties including CO2 emission scenario, climate model, downscaling and impact model. The relative importance of the individual uncertainty sources is expected to depend on several factors including the quantity that is projected. In the present study the impacts of climate model uncertainty and geological model uncertainty on hydraulic head, stream flow, travel time and capture zones are evaluated. Six versions of a physically based and distributed hydrological model, each containing a unique interpretation of the geological structure of the model area, are forced by 11 climate model projections. Each projection of future climate is a result of a GCM-RCM model combination (from the ENSEMBLES project) forced by the same CO2 scenario (A1B). The changes from the reference period (1991-2010) to the future period (2081-2100) in projected hydrological variables are evaluated and the effects of geological model and climate model uncertainties are quantified. The results show that uncertainty propagation is context dependent. While the geological conceptualization is the dominating uncertainty source for projection of travel time and capture zones, the uncertainty on the climate models is more important for groundwater hydraulic heads and stream flow.

  6. Misrepresentation and amendment of soil moisture in conceptual hydrological modelling

    NASA Astrophysics Data System (ADS)

    Zhuo, Lu; Han, Dawei

    2016-04-01

    Although many conceptual models are very effective in simulating river runoff, their soil moisture schemes are generally not realistic in comparison with the reality (i.e., getting the right answers for the wrong reasons). This study reveals two significant misrepresentations in those models through a case study using the Xinanjiang model which is representative of many well-known conceptual hydrological models. The first is the setting of the upper limit of its soil moisture at the field capacity, due to the 'holding excess runoff' concept (i.e., runoff begins on repletion of its storage to the field capacity). The second is neglect of capillary rise of water movement. A new scheme is therefore proposed to overcome those two issues. The amended model is as effective as its original form in flow modelling, but represents more logically realistic soil water processes. The purpose of the study is to enable the hydrological model to get the right answers for the right reasons. Therefore, the new model structure has a better capability in potentially assimilating soil moisture observations to enhance its real-time flood forecasting accuracy. The new scheme is evaluated in the Pontiac catchment of the USA through a comparison with satellite observed soil moisture. The correlation between the XAJ and the observed soil moisture is enhanced significantly from 0.64 to 0.70. In addition, a new soil moisture term called SMDS (Soil Moisture Deficit to Saturation) is proposed to complement the conventional SMD (Soil Moisture Deficit).

  7. Doing hydrology forwards: Using field experimental data to inform a conceptual model of landscape driven hydrologic connectivity

    NASA Astrophysics Data System (ADS)

    Marshall, L. A.; Smith, T. J.; McGlynn, B. L.; Jencso, K. G.

    2011-12-01

    Given the known tradeoffs between hydrologic model complexity, efficiency, and predictive uncertainty there is an increasing desire to identify conceptual catchment models that accurately reflect catchment processes whilst preserving model identifiability. These models should specify the relationship between catchment form (including landscape topography, vegetation patterns, and stream networks) and hydrologic functioning (including streamflow patterns). We present a new hydrologic modeling approach that uses the distribution of landscape elements along the stream network as a template by which landscape-scale hydrologic connectivity and catchment runoff can be simulated. Here, we define hydrologic connectivity as the transient hydrological linkages between landscape elements and the stream. Our conceptualization emphasizes the importance of hydrologic connections between hillslope-riparian-stream (HRS) zones. Observations indicate that it is the frequency of these HRS hydrologic connections that drive aggregate catchment runoff response, rather than the magnitude of flux at any one connection. We applied the model to the Stringer Creek watershed of the Tenderfoot Creek Experimental Forest (TCEF), located in central Montana, USA. Detailed field observations were used to inform the underpinnings of the model and to corroborate internal consistency of the model's simulations. The ability of the model to simulate internal dynamics without conditioning the parameters on these data indicate the potential of this model to be more convincingly extrapolated to other hydrologic conditions and tested at catchments of varying topographic structure. Current and future work is aimed at further developing the modeling approach and testing the limits of its applicability across space and time.

  8. Distributed hydrological models: comparison between TOPKAPI, a physically based model and TETIS, a conceptually based model

    NASA Astrophysics Data System (ADS)

    Ortiz, E.; Guna, V.

    2009-04-01

    The present work aims to carry out a comparison between two distributed hydrological models, the TOPKAPI (Ciarapica and Todini, 1998; Todini and Ciarapica, 2001) and TETIS (Vélez, J. J.; Vélez J. I. and Francés, F, 2002) models, obtaining the hydrological solution computed on the basis of the same storm events. The first model is physically based and the second one is conceptually based. The analysis was performed on the 21,4 km2 Goodwin Creek watershed, located in Panola County, Mississippi. This watershed extensively monitored by the Agricultural Research Service (ARS) National Sediment Laboratory (NSL) has been chosen because it offers a complete database compiling precipitation (16 rain gauges), runoff (6 discharge stations) and GIS data. Three storm events were chosen to evaluate the performance of the two models: the first one was chosen to calibrate the models, and the other two to validate them. Both models performed a satisfactory hydrological response both in calibration and validation events. While for the TOPKAPI model it wasn't a real calibration, due to its really good performance with parameters modal values derived of watershed characteristics, for the TETIS model it has been necessary to perform a previous automatic calibration. This calibration was carried out using the data provided by the observed hydrograph, in order to adjust the modeĺs 9 correction factors. Keywords: TETIS, TOPKAPI, distributed models, hydrological response, ungauged basins.

  9. Understanding hydrological flow paths in conceptual catchment models using uncertainty and sensitivity analysis

    NASA Astrophysics Data System (ADS)

    Mockler, Eva M.; O'Loughlin, Fiachra E.; Bruen, Michael

    2016-05-01

    Increasing pressures on water quality due to intensification of agriculture have raised demands for environmental modeling to accurately simulate the movement of diffuse (nonpoint) nutrients in catchments. As hydrological flows drive the movement and attenuation of nutrients, individual hydrological processes in models should be adequately represented for water quality simulations to be meaningful. In particular, the relative contribution of groundwater and surface runoff to rivers is of interest, as increasing nitrate concentrations are linked to higher groundwater discharges. These requirements for hydrological modeling of groundwater contribution to rivers initiated this assessment of internal flow path partitioning in conceptual hydrological models. In this study, a variance based sensitivity analysis method was used to investigate parameter sensitivities and flow partitioning of three conceptual hydrological models simulating 31 Irish catchments. We compared two established conceptual hydrological models (NAM and SMARG) and a new model (SMART), produced especially for water quality modeling. In addition to the criteria that assess streamflow simulations, a ratio of average groundwater contribution to total streamflow was calculated for all simulations over the 16 year study period. As observations time-series of groundwater contributions to streamflow are not available at catchment scale, the groundwater ratios were evaluated against average annual indices of base flow and deep groundwater flow for each catchment. The exploration of sensitivities of internal flow path partitioning was a specific focus to assist in evaluating model performances. Results highlight that model structure has a strong impact on simulated groundwater flow paths. Sensitivity to the internal pathways in the models are not reflected in the performance criteria results. This demonstrates that simulated groundwater contribution should be constrained by independent data to ensure results

  10. A conceptual data model coupling with physically-based distributed hydrological models based on catchment discretization schemas

    NASA Astrophysics Data System (ADS)

    Liu, Yuanming; Zhang, Wanchang; Zhang, Zhijie

    2015-11-01

    In hydrology, the data types, spatio-temporal scales and formats for physically-based distributed hydrological models and the distributed data or parameters may be different before significant data pre-processing or may change during hydrological simulation run time. A data model is devoted to these problems for sophisticated numerical hydrological modeling procedures. In this paper, we propose a conceptual data model to interpret the comprehensive, universal and complex water environmental entities. We also present an innovative integration methodology to couple the data model with physically-based distributed hydrological models (DHMs) based on catchment discretization schemas. The data model provides a reasonable framework for researchers of organizing and pre-processing water environmental spatio-temporal datasets. It also facilitates seamless data flow fluid and dynamic by hydrological response units (HRUs) as the core between the object-oriented databases and physically-based distributed hydrological models.

  11. Elements of a flexible approach for conceptual hydrological modeling: 2. Application and experimental insights

    NASA Astrophysics Data System (ADS)

    Kavetski, Dmitri; Fenicia, Fabrizio

    2011-11-01

    In this article's companion paper, flexible approaches for conceptual hydrological modeling at the catchment scale were motivated, and the SUPERFLEX framework, based on generic model components, was introduced. In this article, the SUPERFLEX framework and the "fixed structure" GR4H model (an hourly version of the popular GR4J model) are applied to four hydrologically distinct experimental catchments in Europe and New Zealand. The estimated models are scrutinized using several diagnostic measures, ranging from statistical metrics, such as the statistical reliability and precision of the predictive distribution of streamflow, to more process-oriented diagnostics based on flow-duration curves and the correspondence between model states and groundwater piezometers. Model performance was clearly catchment specific, with a single fixed structure unable to accommodate intercatchment differences in hydrological behavior, including seasonality and thresholds. This highlights an important limitation of any "fixed" model structure. In the experimental catchments, the ability of competing model hypotheses to reproduce hydrological signatures of interest could be interpreted on the basis of independent fieldwork insights. The potential of flexible frameworks such as SUPERFLEX is then examined with respect to systematic and stringent hypothesis-testing in hydrological modeling, for characterizing catchment diversity, and, more generally, for aiding progress toward a more unified formulation of hydrological theory at the catchment scale. When interpreted in physical process-oriented terms, the flexible approach can also serve as a language for dialogue between modeler and experimentalist, facilitating the understanding, representation, and interpretation of catchment behavior.

  12. Elements of a flexible approach for conceptual hydrological modeling: 1. Motivation and theoretical development

    NASA Astrophysics Data System (ADS)

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

    2011-11-01

    This paper introduces a flexible framework for conceptual hydrological modeling, with two related objectives: (1) generalize and systematize the currently fragmented field of conceptual models and (2) provide a robust platform for understanding and modeling hydrological systems. In contrast to currently dominant "fixed" model applications, the flexible framework proposed here allows the hydrologist to hypothesize, build, and test different model structures using combinations of generic components. This is particularly useful for conceptual modeling at the catchment scale, where limitations in process understanding and data availability remain major research and operational challenges. The formulation of the model architecture and individual components to represent distinct aspects of catchment-scale function, such as storage, release, and transmission of water, is discussed. Several numerical strategies for implementing the model equations within a computationally robust framework are also presented. In the companion paper, the potential of the flexible framework is examined with respect to supporting more systematic and stringent hypothesis testing, for characterizing catchment diversity, and, more generally, for aiding progress toward more unified hydrological theory at the catchment scale.

  13. Ancient numerical daemons of conceptual hydrological modeling: 1. Fidelity and efficiency of time stepping schemes

    NASA Astrophysics Data System (ADS)

    Clark, Martyn P.; Kavetski, Dmitri

    2010-10-01

    A major neglected weakness of many current hydrological models is the numerical method used to solve the governing model equations. This paper thoroughly evaluates several classes of time stepping schemes in terms of numerical reliability and computational efficiency in the context of conceptual hydrological modeling. Numerical experiments are carried out using 8 distinct time stepping algorithms and 6 different conceptual rainfall-runoff models, applied in a densely gauged experimental catchment, as well as in 12 basins with diverse physical and hydroclimatic characteristics. Results show that, over vast regions of the parameter space, the numerical errors of fixed-step explicit schemes commonly used in hydrology routinely dwarf the structural errors of the model conceptualization. This substantially degrades model predictions, but also, disturbingly, generates fortuitously adequate performance for parameter sets where numerical errors compensate for model structural errors. Simply running fixed-step explicit schemes with shorter time steps provides a poor balance between accuracy and efficiency: in some cases daily-step adaptive explicit schemes with moderate error tolerances achieved comparable or higher accuracy than 15 min fixed-step explicit approximations but were nearly 10 times more efficient. From the range of simple time stepping schemes investigated in this work, the fixed-step implicit Euler method and the adaptive explicit Heun method emerge as good practical choices for the majority of simulation scenarios. In combination with the companion paper, where impacts on model analysis, interpretation, and prediction are assessed, this two-part study vividly highlights the impact of numerical errors on critical performance aspects of conceptual hydrological models and provides practical guidelines for robust numerical implementation.

  14. Hydrologic modelling for Lake Basaka: development and application of a conceptual water budget model.

    PubMed

    Dinka, Megersa O; Loiskandl, Willibald; Ndambuki, Julius M

    2014-09-01

    Quantification of fluxes of water into and out of terminal lakes like Basaka has fundamental challenges. This is due to the fact that accurate measurement and quantification of most of the parameters of a lake's hydrologic cycle are difficult. Furthermore, quantitative understanding of the hydrologic systems and hence, the data-intensive modelling is difficult in developing countries like Ethiopia due to limitation of sufficient recorded data. Therefore, formulation of a conceptual water balance model is extremely important as it presents a convenient analytical tool with simplified assumptions to simulate the magnitude of unknown fluxes. In the current study, a conceptual lake water balance model was systematically formulated, solved, calibrated, and validated successfully. Then, the surface water and groundwater interaction was quantified, and a mathematical relationship developed. The overall agreement between the observed and simulated lake stage at monthly time step was confirmed based on the standard performance parameters (R(2), MAE, RMSE, E(f)). The result showed that hydrological water balance of the lake is dominated by the groundwater (GW) component. The net GW flux in recent period (post-2000s) accounts about 56% of the total water inflow. Hence, GW plays a leading role in the hydrodynamics and existence of Lake Basaka and is mostly responsible for the expansion of the lake. Thus, identification of the potential sources/causes for the GW flux plays a leading role in order to limit the further expansion of the lake. Measurement of GW movement and exchange in the area is a high priority for future research. PMID:24816590

  15. Sensitivity of hydrological performance assessment analysis to variations in material properties, conceptual models, and ventilation models

    SciTech Connect

    Sobolik, S.R.; Ho, C.K.; Dunn, E.; Robey, T.H.; Cruz, W.T.

    1996-07-01

    The Yucca Mountain Site Characterization Project is studying Yucca Mountain in southwestern Nevada as a potential site for a high-level nuclear waste repository. Site characterization includes surface- based and underground testing. Analyses have been performed to support the design of an Exploratory Studies Facility (ESF) and the design of the tests performed as part of the characterization process, in order to ascertain that they have minimal impact on the natural ability of the site to isolate waste. The information in this report pertains to sensitivity studies evaluating previous hydrological performance assessment analyses to variation in the material properties, conceptual models, and ventilation models, and the implications of this sensitivity on previous recommendations supporting ESF design. This document contains information that has been used in preparing recommendations for Appendix I of the Exploratory Studies Facility Design Requirements document.

  16. Assimilating GRACE terrestrial water storage data into a conceptual hydrology model for the River Rhine

    NASA Astrophysics Data System (ADS)

    Widiastuti, E.; Steele-Dunne, S. C.; Gunter, B.; Weerts, A.; van de Giesen, N.

    2009-12-01

    Terrestrial water storage (TWS) is a key component of the terrestrial and global hydrological cycles, and plays a major role in the Earth’s climate. The Gravity Recovery and Climate Experiment (GRACE) twin satellite mission provided the first space-based dataset of TWS variations, albeit with coarse resolution and limited accuracy. Here, we examine the value of assimilating GRACE observations into a well-calibrated conceptual hydrology model of the Rhine river basin. In this study, the ensemble Kalman filter (EnKF) and smoother (EnKS) were applied to assimilate the GRACE TWS variation data into the HBV-96 rainfall run-off model, from February 2003 to December 2006. Two GRACE datasets were used, the DMT-1 models produced at TU Delft, and the CSR-RL04 models produced by UT-Austin . Each center uses its own data processing and filtering methods, yielding two different estimates of TWS variations and therefore two sets of assimilated TWS estimates. To validate the results, the model estimated discharge after the data assimilation was compared with measured discharge at several stations. As expected, the updated TWS was generally somewhere between the modeled and observed TWS in both experiments and the variance was also lower than both the prior error covariance and the assumed GRACE observation error. However, the impact on the discharge was found to depend heavily on the assimilation strategy used, in particular on how the TWS increments were applied to the individual storage terms of the hydrology model.

  17. Evolution of the conceptual model of unsaturated zone hydrology at Yucca Mountain, Nevada

    NASA Astrophysics Data System (ADS)

    Flint, Alan L.; Flint, Lorraine E.; Bodvarsson, Gudmundur S.; Kwicklis, Edward M.; Fabryka-Martin, June

    2001-06-01

    Yucca Mountain is an arid site proposed for consideration as the United States' first underground high-level radioactive waste repository. Low rainfall (approximately 170 mm/yr) and a thick unsaturated zone (500-1000 m) are important physical attributes of the site because the quantity of water likely to reach the waste and the paths and rates of movement of the water to the saturated zone under future climates would be major factors in controlling the concentrations and times of arrival of radionuclides at the surrounding accessible environment. The framework for understanding the hydrologic processes that occur at this site and that control how quickly water will penetrate through the unsaturated zone to the water table has evolved during the past 15 yr. Early conceptual models assumed that very small volumes of water infiltrated into the bedrock (0.5-4.5 mm/yr, or 2-3 percent of rainfall), that much of the infiltrated water flowed laterally within the upper nonwelded units because of capillary barrier effects, and that the remaining water flowed down faults with a small amount flowing through the matrix of the lower welded, fractured rocks. It was believed that the matrix had to be saturated for fractures to flow. However, accumulating evidence indicated that infiltration rates were higher than initially estimated, such as infiltration modeling based on neutron borehole data, bomb-pulse isotopes deep in the mountain, perched water analyses and thermal analyses. Mechanisms supporting lateral diversion did not apply at these higher fluxes, and the flux calculated in the lower welded unit exceeded the conductivity of the matrix, implying vertical flow of water in the high permeability fractures of the potential repository host rock, and disequilibrium between matrix and fracture water potentials. The development of numerical modeling methods and parameter values evolved concurrently with the conceptual model in order to account for the observed field data

  18. Evolution of the conceptual model of unsaturated zone hydrology at yucca mountain, nevada

    SciTech Connect

    Flint, A. L.; Flint, L. E.; Bodvarsson, G. S.; Kwicklis, E. M.; Fabryka-Martin, J.

    2001-02-01

    Yucca Mountain is an arid site proposed for consideration as the United States' first underground high-level radioactive waste repository. Low rainfall (approximately 170 mm/yr) and a thick unsaturated zone (500-1000 m) are important physical attributes of the site because the quantity of water likely to reach the waste and the paths and rates of movement of the water to the saturated zone under future climates would be major factors in controlling the concentrations and times of arrival of radionuclides at the surrounding accessible environment. The framework for understanding the hydrologic processes that occur at this site and that control how quickly water will penetrate through the unsaturated zone to the water table has evolved during the past 15 yr. Early conceptual models assumed that very small volumes of water infiltrated into the bedrock (0.5-4.5 mm/yr, or 2-3 percent of rainfall), that much of the infiltrated water flowed laterally within the upper nonwelded units because o f capillary barrier effects, and that the remaining water flowed down faults with a small amount flowing through the matrix of the lower welded, fractured rocks. It was believed that the matrix had to be saturated for fractures to show. However, accumulating evidence indicated that infiltration rates were higher than initially estimated, such as infiltration modeling based on neutron borehole data, bomb-pulse isotopes deep in the mountain, perched water analyses and thermal analyses. Mechanisms supporting lateral diversion did not apply at these higher fluxes, and the flux calculated in the lower welded unit exceeded the conductivity of the matrix, implying vertical flow of water into the high permeability fractures of the potential repository host rock, and disequilibrium between matrix and fracture water potentials. The development of numerical modeling methods and parameter values evolved concurrently with the conceptual model in order to account for the observed field data

  19. Evolution of the conceptual model of unsaturated zone hydrology at Yucca Mountain, Nevada

    USGS Publications Warehouse

    Flint, Alan L.; Flint, Lorraine E.; Bodvarsson, Gudmundur S.; Kwicklis, Edward M.; Fabryka-Martin, June

    2001-01-01

    Yucca Mountain is an arid site proposed for consideration as the United States’ first underground high-level radioactive waste repository. Low rainfall (approximately 170 mm/yr) and a thick unsaturated zone (500–1000 m) are important physical attributes of the site because the quantity of water likely to reach the waste and the paths and rates of movement of the water to the saturated zone under future climates would be major factors in controlling the concentrations and times of arrival of radionuclides at the surrounding accessible environment. The framework for understanding the hydrologic processes that occur at this site and that control how quickly water will penetrate through the unsaturated zone to the water table has evolved during the past 15 yr. Early conceptual models assumed that very small volumes of water infiltrated into the bedrock (0.5–4.5 mm/yr, or 2–3 percent of rainfall), that much of the infiltrated water flowed laterally within the upper nonwelded units because of capillary barrier effects, and that the remaining water flowed down faults with a small amount flowing through the matrix of the lower welded, fractured rocks. It was believed that the matrix had to be saturated for fractures to flow. However, accumulating evidence indicated that infiltration rates were higher than initially estimated, such as infiltration modeling based on neutron borehole data, bomb-pulse isotopes deep in the mountain, perched water analyses and thermal analyses. Mechanisms supporting lateral diversion did not apply at these higher fluxes, and the flux calculated in the lower welded unit exceeded the conductivity of the matrix, implying vertical flow of water in the high permeability fractures of the potential repository host rock, and disequilibrium between matrix and fracture water potentials. The development of numerical modeling methods and parameter values evolved concurrently with the conceptual model in order to account for the observed field data

  20. A conceptual, linear reservoir runoff model to investigate melt season changes in cirque glacier hydrology

    NASA Astrophysics Data System (ADS)

    Hannah, David M.; Gurnell, Angela M.

    2001-06-01

    This paper presents a conceptual, linear reservoir runoff model and applies it to a small glacierized cirque basin in the French Pyrénées over the 1995 melt season. A series of modelling experiments are undertaken: (i) to explore the response of diurnal hydrograph form to seasonal changes in surface meltwater recharge and glacier storage and routing processes and (ii) to investigate the possible structure of the hydrological system of this remnant glacier. High resolution, spatially- and temporally distributed observations of snow and ice-melt (and precipitation records) are used to estimate bulk meltwater inputs, which feed into a lumped meltwater drainage model. Empirical hydrograph recession limb analysis provides a basis to identify the most likely 'structure' of the glacier's hydrological system. This structure is then represented in the model by two ('fast' and 'slow') linear reservoirs. Although fast reservoir storage coefficients show only a moderate decline (13.00-5.25 h), the proportion of bulk meltwater entering this reservoir increases as the glacier snowline retreats and the slow reservoir storage coefficient decreases (45.00-17.75 h); consequently modelled hydrographs become increasingly peaked over the ablation season. Later in the melt season, the drainage system is mathematically best represented as a single reservoir (with a storage coefficient of 6.00-8.25 h) due to meltwater production occurring mainly in the lower-mid ablation zone, reduction in the extent (capacity) of the slower storage areas, and/or integration of the slow and fast pathways. In terms of glacier hydrology, the modelling experiments suggest that the fast reservoir represents ice-melt draining into a semi-distributed system beneath the lower glacier and the slow reservoir represents a snowpack-fed distributed system below the upper glacier. The nature of storage and routing within the hydrological system and the degree to which these processes are significant in determining

  1. Hydrological hysteresis and its value for assessing process consistency in catchment conceptual models

    NASA Astrophysics Data System (ADS)

    Fovet, O.; Ruiz, L.; Hrachowitz, M.; Faucheux, M.; Gascuel-Odoux, C.

    2015-01-01

    While most hydrological models reproduce the general flow dynamics, they frequently fail to adequately mimic system-internal processes. In particular, the relationship between storage and discharge, which often follows annual hysteretic patterns in shallow hard-rock aquifers, is rarely considered in modelling studies. One main reason is that catchment storage is difficult to measure, and another one is that objective functions are usually based on individual variables time series (e.g. the discharge). This reduces the ability of classical procedures to assess the relevance of the conceptual hypotheses associated with models. We analysed the annual hysteric patterns observed between stream flow and water storage both in the saturated and unsaturated zones of the hillslope and the riparian zone of a headwater catchment in French Brittany (Environmental Research Observatory ERO AgrHys (ORE AgrHys)). The saturated-zone storage was estimated using distributed shallow groundwater levels and the unsaturated-zone storage using several moisture profiles. All hysteretic loops were characterized by a hysteresis index. Four conceptual models, previously calibrated and evaluated for the same catchment, were assessed with respect to their ability to reproduce the hysteretic patterns. The observed relationship between stream flow and saturated, and unsaturated storages led us to identify four hydrological periods and emphasized a clearly distinct behaviour between riparian and hillslope groundwaters. Although all the tested models were able to produce an annual hysteresis loop between discharge and both saturated and unsaturated storage, the integration of a riparian component led to overall improved hysteretic signatures, even if some misrepresentation remained. Such a system-like approach is likely to improve model selection.

  2. Hydrological annual hysteresis: functional signature for assessing the consistency of catchment conceptual models?

    NASA Astrophysics Data System (ADS)

    Fovet, Ophelie; Laurent, Ruiz; Markus, Hrachowitz; Chantal, Gascuel-Odoux

    2015-04-01

    While most hydrological models reproduce the general flow dynamics, they frequently fail to adequately mimic system internal processes. In particular, the relationship between storage and discharge, which often follows annual hysteretic patterns in shallow hard-rock aquifers, is rarely considered in modelling studies. One main reason is that catchment storage is difficult to measure and another one is that objective functions are usually based on individual variables time series (e.g. the discharge). This reduces the ability of classical procedures to assess the relevance of the conceptual hypotheses associated with models. In this study, the annual hysteric patterns observed between stream flow and water storage is analysed both in the saturated and unsaturated zones of the hillslope and the riparian zone of a headwater catchment in French Brittany (ORE AgrHys). The saturated zone storage was estimated using distributed shallow groundwater levels and the unsaturated zone storage using several moisture profiles. All hysteretic loops were characterized by a hysteresis index. Four conceptual models, previously calibrated and evaluated for the same catchment, were assessed with respect to their ability to reproduce the hysteretic patterns. The observed relationship between stream flow, saturated, and unsaturated storages led to identify four hydrological periods and emphasized a clearly distinct behaviour between riparian and hillslope groundwaters. Although all the tested models were able to produce an annual hysteresis loop between discharge and both saturated and unsaturated storage, integration of a riparian component led to overall improved hysteretic signatures, even if some misrepresentation remained. Such systems-like approach is likely to improve model selection.

  3. Hydrological hysteresis in catchments and its value for assessing process consistency in conceptual models

    NASA Astrophysics Data System (ADS)

    Fovet, O.; Ruiz, L.; Hrachowitz, M.; Faucheux, M.; Gascuel-Odoux, C.

    2014-05-01

    While most hydrological models reproduce the general flow dynamics, they frequently fail to adequately mimic system internal processes. In particular, the relationship between storage and discharge, which often follows annual hysteretic patterns in shallow hard-rock aquifers, is rarely considered in modelling studies. One main reason is that catchment storage is difficult to measure and another one is that objective functions are usually based on individual variables time series (e.g. the discharge). This reduces the ability of classical procedures to assess the relevance of the conceptual hypotheses associated with models. We analyzed the annual hysteric patterns observed between stream flow and water storage both in the saturated and unsaturated zones of the hillslope and the riparian zone of a headwater catchment in French Brittany (ORE AgrHys). The saturated zone storage was estimated using distributed shallow groundwater levels and the unsaturated zone storage using several moisture profiles. All hysteretic loops were characterized by a hysteresis index. Four conceptual models, previously calibrated and evaluated for the same catchment, were assessed with respect to their ability to reproduce the hysteretic patterns. The observed relationship between stream flow, saturated, and unsaturated storages led to identify four hydrological periods and emphasized a clearly distinct behaviour between riparian and hillslope groundwaters. Although all the tested models were able to produce an annual hysteresis loop between discharge and both saturated and unsaturated storage, integration of a riparian component led to overall improved hysteretic signatures, even if some misrepresentation remained. Such systems-like approach is likely to improve model selection.

  4. Imposing constraints on parameter values of a conceptual hydrological model using baseflow response

    NASA Astrophysics Data System (ADS)

    Dunn, S. M.

    Calibration of conceptual hydrological models is frequently limited by a lack of data about the area that is being studied. The result is that a broad range of parameter values can be identified that will give an equally good calibration to the available observations, usually of stream flow. The use of total stream flow can bias analyses towards interpretation of rapid runoff, whereas water quality issues are more frequently associated with low flow condition. This paper demonstrates how model distinctions between surface an sub-surface runoff can be used to define a likelihood measure based on the sub-surface (or baseflow) response. This helps to provide more information about the model behaviour, constrain the acceptable parameter sets and reduce uncertainty in streamflow prediction. A conceptual model, DIY, is applied to two contrasting catchments in Scotland, the Ythan and the Carron Valley. Parameter ranges and envelopes of prediction are identified using criteria based on total flow efficiency, baseflow efficiency and combined efficiencies. The individual parameter ranges derived using the combined efficiency measures still cover relatively wide bands, but are better constrained for the Carron than the Ythan. This reflects the fact that hydrological behaviour in the Carron is dominated by a much flashier surface response than in the Ythan. Hence, the total flow efficiency is more strongly controlled by surface runoff in the Carron and there is a greater contrast with the baseflow efficiency. Comparisons of the predictions using different efficiency measures for the Ythan also suggest that there is a danger of confusing parameter uncertainties with data and model error, if inadequate likelihood measures are defined.

  5. Reducing structural uncertainty in conceptual hydrological modelling in the semi-arid Andes

    NASA Astrophysics Data System (ADS)

    Hublart, P.; Ruelland, D.; Dezetter, A.; Jourde, H.

    2015-05-01

    The use of lumped, conceptual models in hydrological impact studies requires placing more emphasis on the uncertainty arising from deficiencies and/or ambiguities in the model structure. This study provides an opportunity to combine a multiple-hypothesis framework with a multi-criteria assessment scheme to reduce structural uncertainty in the conceptual modelling of a mesoscale Andean catchment (1515 km2) over a 30-year period (1982-2011). The modelling process was decomposed into six model-building decisions related to the following aspects of the system behaviour: snow accumulation and melt, runoff generation, redistribution and delay of water fluxes, and natural storage effects. Each of these decisions was provided with a set of alternative modelling options, resulting in a total of 72 competing model structures. These structures were calibrated using the concept of Pareto optimality with three criteria pertaining to streamflow simulations and one to the seasonal dynamics of snow processes. The results were analyzed in the four-dimensional (4-D) space of performance measures using a fuzzy c-means clustering technique and a differential split sample test, leading to identify 14 equally acceptable model hypotheses. A filtering approach was then applied to these best-performing structures in order to minimize the overall uncertainty envelope while maximizing the number of enclosed observations. This led to retain eight model hypotheses as a representation of the minimum structural uncertainty that could be obtained with this modelling framework. Future work to better consider model predictive uncertainty should include a proper assessment of parameter equifinality and data errors, as well as the testing of new or refined hypotheses to allow for the use of additional auxiliary observations.

  6. Reducing structural uncertainty in conceptual hydrological modeling in the semi-arid Andes

    NASA Astrophysics Data System (ADS)

    Hublart, P.; Ruelland, D.; Dezetter, A.; Jourde, H.

    2014-10-01

    The use of lumped, conceptual models in hydrological impact studies requires placing more emphasis on the uncertainty arising from deficiencies and/or ambiguities in the model structure. This study provides an opportunity to combine a multiple-hypothesis framework with a multi-criteria assessment scheme to reduce structural uncertainty in the conceptual modeling of a meso-scale Andean catchment (1515 km2) over a 30 year period (1982-2011). The modeling process was decomposed into six model-building decisions related to the following aspects of the system behavior: snow accumulation and melt, runoff generation, redistribution and delay of water fluxes, and natural storage effects. Each of these decisions was provided with a set of alternative modeling options, resulting in a total of 72 competing model structures. These structures were calibrated using the concept of Pareto optimality with three criteria pertaining to streamflow simulations and one to the seasonal dynamics of snow processes. The results were analyzed in the four-dimensional space of performance measures using a fuzzy c-means clustering technique and a differential split sample test, leading to identify 14 equally acceptable model hypotheses. A filtering approach was then applied to these best-performing structures in order to minimize the overall uncertainty envelope while maximizing the number of enclosed observations. This led to retain 8 model hypotheses as a representation of the minimum structural uncertainty that could be obtained with this modeling framework. Future work to better consider model predictive uncertainty should include a proper assessment of parameter equifinality and data errors, as well as the testing of new or refined hypotheses to allow for the use of additional auxiliary observations.

  7. Conceptual hydrologic model of flow in the unsaturated zone, Yucca Mountain, Nevada

    USGS Publications Warehouse

    Montazer, P.M.; Wilson, W.E.

    1984-01-01

    The unsaturated volcanic tuffs beneath Yucca Mountain, Nevada, are being evaluated as a host rock for a potential repository for high-level radioactive waste. A conceptual hydrologic model is proposed to describe the flow of fluids through these rocks. Thickness of the unsaturated zone is about 500 to 750 meters and consists of three welded units interlayered with two nonwelded units. Compared to nonwelded units, welded units have low matrix porosities and permeabilities, high fracture densities, and high bulk hydraulic conductivities. The principal repository area is bounded by normal fault zones. Of the average annual precipitation of 150 millimeters per year, 0.5 to 4.5 millimeters per year becomes net infiltration. Percolation through the matrix of the welded units is principally vertical and is less than 1 millimeter per year. Percolation through nonwelded units occurs both vertically and laterally and has variable rates (0.1 to 100 millimeters per year). Fracture flow is predominant in the uppermost welded unit during intense pulses of infiltration, but is insignificant in the welded unit that forms the potential host rock. Lateral flow in the upper nonwelded unit, enhanced by existence of a capillary barrier, probably is the factor controlling the low fluxes in the host rock and relatively high fluxes in the structural features. (USGS)

  8. Quantification of uncertainties related to the regional application of a conceptual hydrological model in Benin (West Africa)

    NASA Astrophysics Data System (ADS)

    Bormann, H.; Diekkrüger, B.

    2003-04-01

    A conceptual model is presented to simulate the water fluxes of regional catchments in Benin (West Africa). The model is applied in the framework of the IMPETUS project (an integrated approach to the efficient management of scarce water resources in West Africa) which aims to assess the effects of environmental and anthropogenic changes on the regional hydrological processes and on the water availability in Benin. In order to assess the effects of decreasing precipitation and increasing human activities on the hydrological processes in the upper Ouémé valley, a scenario analysis is performed to predict possible changes. Therefore a regional hydrological model is proposed which reproduces the recent hydrological processes, and which is able to consider the changes of landscape properties.The study presented aims to check the validity of the conceptual and lumped model under the conditions of the subhumid tree savannah and therefore analyses the importance of possible sources of uncertainty. Main focus is set on the uncertainties caused by input data, model parameters and model structure. As the model simulates the water fluxes at the catchment outlet of the Térou river (3133 km2) in a sufficient quality, first results of a scenario analysis are presented. Changes of interest are the expected future decrease in amount and temporal structure of the precipitation (e.g. minus X percent precipitation during the whole season versus minus X percent precipitation in the end of the rainy season, alternatively), the decrease in soil water storage capacity which is caused by erosion, and the increasing consumption of ground water for drinking water and agricultural purposes. Resuming from the results obtained, the perspectives of lumped and conceptual models are discussed with special regard to available management options of this kind of models. Advantages and disadvantages compared to alternative model approaches (process based, physics based) are discussed.

  9. Impact of Temporal Data Resolution on Parameter Inference and Model Identification in Conceptual Hydrological Modeling: Insights from an Experimental Catchment

    NASA Astrophysics Data System (ADS)

    Fenicia, F.; Kavetski, D.; Clark, M.

    2010-12-01

    A major issue in hydrological and broader environmental modeling is the uncertainty in the observed data, in particular, the effects of sparse data sampling and averaging to temporal and spatial scales that well exceed those of many hydrological dynamics of interest. This study presents quantitative and qualitative insights into the time scale dependencies of hydrological parameters, predictions and their uncertainties, and examines the impact of the time resolution of the calibration data on the identifiable system complexity. Data from an experimental basin (Weierbach, Luxembourg) is used to analyze four conceptual models of varying complexity, over time scales of 30 min to 3 days, using several combinations of numerical implementations and inference equations. Large spurious time scale trends arise in the parameter estimates when unreliable time stepping approximations are employed, and/or when the heteroscedasticity of the model residual errors is ignored. Conversely, the use of robust numerics and more adequate (albeit still imperfect) likelihood functions markedly stabilizes the time scale dependencies and improves the identifiability of increasingly complex model structures. Parameters describing slowflow remained essentially constant over the range of sub-hourly to daily scales considered here, while parameters describing quickflow converged towards increasingly precise and stable estimates as the data resolution approached the characteristic time scale of these faster processes. These results are consistent with theoretical expectations based on numerical error analysis and data-averaging considerations. Additional diagnostics confirmed the improved ability of the more complex models to reproduce distinct signatures in the observed data. More broadly, this study provides insights into the information content of data and, through robust numerical and statistical techniques, furthers the utilization of dense-resolution data and experimental insights to

  10. Investigating the relationship between a soils classification and the spatial parameters of a conceptual catchment-scale hydrological model

    NASA Astrophysics Data System (ADS)

    Dunn, S. M.; Lilly, A.

    2001-10-01

    There are now many examples of hydrological models that utilise the capabilities of Geographic Information Systems to generate spatially distributed predictions of behaviour. However, the spatial variability of hydrological parameters relating to distributions of soils and vegetation can be hard to establish. In this paper, the relationship between a soil hydrological classification Hydrology of Soil Types (HOST) and the spatial parameters of a conceptual catchment-scale model is investigated. A procedure involving inverse modelling using Monte-Carlo simulations on two catchments is developed to identify relative values for soil related parameters of the DIY model. The relative values determine the internal variability of hydrological processes as a function of the soil type. For three out of the four soil parameters studied, the variability between HOST classes was found to be consistent across two catchments when tested independently. Problems in identifying values for the fourth 'fast response distance' parameter have highlighted a potential limitation with the present structure of the model. The present assumption that this parameter can be related simply to soil type rather than topography appears to be inadequate. With the exclusion of this parameter, calibrated parameter sets from one catchment can be converted into equivalent parameter sets for the alternate catchment on the basis of their HOST distributions, to give a reasonable simulation of flow. Following further testing on different catchments, and modifications to the definition of the fast response distance parameter, the technique provides a methodology whereby it is possible to directly derive spatial soil parameters for new catchments.

  11. On the optimal design of experiments for conceptual and predictive discrimination of hydrologic system models

    NASA Astrophysics Data System (ADS)

    Kikuchi, C. P.; Ferré, T. P. A.; Vrugt, J. A.

    2015-06-01

    Experimental design and data collection constitute two main steps of the iterative research cycle (aka the scientific method). To help evaluate competing hypotheses, it is critical to ensure that the experimental design is appropriate and maximizes information retrieval from the system of interest. Scientific hypothesis testing is implemented by comparing plausible model structures (conceptual discrimination) and sets of predictions (predictive discrimination). This research presents a new Discrimination-Inference (DI) methodology to identify prospective data sets highly suitable for either conceptual or predictive discrimination. The DI methodology uses preposterior estimation techniques to evaluate the expected change in the conceptual or predictive probabilities, as measured by the Kullback-Leibler divergence. We present two case studies with increasing complexity to illustrate implementation of the DI for maximizing information withdrawal from a system of interest. The case studies show that highly informative data sets for conceptual discrimination are in general those for which between-model (conceptual) uncertainty is large relative to the within-model (parameter) uncertainty, and the redundancy between individual measurements in the set is minimized. The optimal data set differs if predictive, rather than conceptual, discrimination is the experimental design objective. Our results show that DI analyses highlight measurements that can be used to address critical uncertainties related to the prediction of interest. Finally, we find that the optimal data set for predictive discrimination is sensitive to the predictive grouping definition in ways that are not immediately apparent from inspection of the model structure and parameter values.

  12. Performance of a distributed semi-conceptual hydrological model under tropical watershed conditions

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Many hydrologic models have been developed to help manage natural resources all over the world. Nevertheless, most models have presented a high complexity in terms of data base requirements, as well as, many calibration parameters. This has resulted in serious difficulties to application in catchmen...

  13. Incorporating landscape classifications in hydrological conceptual models A case study for a central European meso-scale catchment

    NASA Astrophysics Data System (ADS)

    Gharari, S.; Hrachowitz, M.; Fenicia, F.; Savenije, H. H. G.

    2012-04-01

    Landscape classification into meaningful hydrological units has important implications for hydrological modeling. Conceptual hydrological models, such as HBV- type models, are most commonly designed to represent catchments in a lumped or semi-distributed way at best, i.e. treating them as single entities or sometimes accounting for topographical and land cover variability by introducing some level of stratification. These oversimplifications can frequently lead to substantial misrepresentations of flow generating processes in the catchments in question, as feedback processes between topography, land cover and hydrology in different landscape units can arguably lead to distinct hydrological patterns. By making use of readily available topographical information, hydrological units can be identified based on the concept of "Height above Nearest Drainage" (HAND; Rennó et al., 2008; Nobre et al., 2011). These hydrological units are characterized by different distinct hydrological behavior and can thus be assigned different model structures (Savenije, 2010). In this study we classified the Wark Catchment in Grand Duchy of Luxembourg which exhibits three distinct landscape units: plateau, wetland and hillslope using a 5-5 m2 DEM. A revised and extended version of HAND gave preliminary estimates of uncertainty in the landscape unit identification as they were implemented in a stochastic framework. As the transition thresholds between the landscape units are a priori unknown, they were calibrated against landscape units observed in the field using a single probability based objective function. As a result, each grid cell of the DEM was characterized by a certain probability of being a certain landscape unit, producing maps of dominant landscape and therefore hydrological units. The maps of the landscape classification using HAND and slope in a probabilistic framework were then used to determine the proportions of the three individual hydrological response units in the

  14. Impact of temporal data resolution on parameter inference and model identification in conceptual hydrological modeling: Insights from an experimental catchment

    NASA Astrophysics Data System (ADS)

    Kavetski, Dmitri; Fenicia, Fabrizio; Clark, Martyn P.

    2011-05-01

    This study presents quantitative and qualitative insights into the time scale dependencies of hydrological parameters, predictions and their uncertainties, and examines the impact of the time resolution of the calibration data on the identifiable system complexity. Data from an experimental basin (Weierbach, Luxembourg) is used to analyze four conceptual models of varying complexity, over time scales of 30 min to 3 days, using several combinations of numerical implementations and inference equations. Large spurious time scale trends arise in the parameter estimates when unreliable time-stepping approximations are employed and/or when the heteroscedasticity of the model residual errors is ignored. Conversely, the use of robust numerics and more adequate (albeit still clearly imperfect) likelihood functions markedly stabilizes and, in many cases, reduces the time scale dependencies and improves the identifiability of increasingly complex model structures. Parameters describing slow flow remained essentially constant over the range of subhourly to daily scales considered here, while parameters describing quick flow converged toward increasingly precise and stable estimates as the data resolution approached the characteristic time scale of these faster processes. These results are consistent with theoretical expectations based on numerical error analysis and data-averaging considerations. Additional diagnostics confirmed the improved ability of the more complex models to reproduce distinct signatures in the observed data. More broadly, this study provides insights into the information content of hydrological data and, by advocating careful attention to robust numericostatistical analysis and stringent process-oriented diagnostics, furthers the utilization of dense-resolution data and experimental insights to advance hypothesis-based hydrological modeling at the catchment scale.

  15. Snow hydrology of a headwater Arctic basin. 2. Conceptual analysis and computer modeling

    SciTech Connect

    Hinzman, L.D.; Kane, D.L. )

    1991-06-01

    Lack of hydrologic data in the Arctic, particularly during snowmelt, severely limits modeling strategy. Spring snowmelt in Imnavait watershed is a very brief event, usually lasting about 10 days. Peak flow normally occurs within the top 10 cm of the highly organic soil mat or on the surface. Snow damming of snowmelt runoff is an important mechanism which must be considered in the modeling process of small watersheds. These unique characteristics of Arctic hydrology will affect the methodology and performance of a hydrologic model. The HBV model was used in an investigation of the hydrologic regime of an Arctic watershed during the spring snowmelt period. From the analysis of five spring melt events the authors found that HBV can adequately predict soil moisture, evaporation, snow ablation and accumulation, and runoff. It models the volumes of snowmelt runoff well, but more data are needed to improve the determination of snowmelt initiation. Use of HBV as a predictive tool is dependent upon the quality of the meteorologic forecast data.

  16. Improving perceptual and conceptual hydrological models using data from small basins 2141

    Technology Transfer Automated Retrieval System (TEKTRAN)

    This paper demonstrates how data from a small experimental basin can be used to evaluate possible structures for a lumped hydrological model. Data collected at the Mahurangi experimental basin in New Zealand includes rainfall, streamflow and multi-depth soil moisture time-series data. We use this da...

  17. A Conceptual Model for Evaluating Hydrologic Connectivity in Geographically Isolated Wetlands

    EPA Science Inventory

    Knowledge about hydrologic connectivity between aquatic resources is critical to understanding and managing watershed hydrology and to the legal status of those resources. In particular, information is needed on the hydrologic connectivity and effects of geographically isolated ...

  18. What can hydrological time series variations tell about karst dynamics? A coupled statistical/conceptual modeling analysis.

    NASA Astrophysics Data System (ADS)

    Massei, N.; Duran, L. P.; Fournier, M.; Jardani, A.; Lecoq, N.

    2015-12-01

    In this research we study the capability of time series analysis approaches to extract meaningful components of karst spring hydrographs. In this aim we compare these statistical components to the internal components of a conceptual precipitation/discharge model based on the physical knowledge of the site studied. We used the conceptual modeling software KARSTMOD developed by the INSU/CNRS National Karst Observatory to model discharge at a small karst spring in Normandy (France). The model comprised four reservoirs E, L, M and C (interpreted as epikarst, high- inertia/highly capacitive matrix, fissure network and conduits), consistent with previous works showing the existence of a triple porosity in chalk of Normandy. KARSTMOD internal flow components were analyzed with correlation and Fourier spectral analysis, and compared to statistical components extracted from spring discharge by wavelet multiresolution analysis and Ensemble Empirical Mode Decomposition (EEMD). We could also analyze how the hydrological signal acquired its red noise statistical characteristics while water flow propagates into the conceptual model. The trend of the discharge signal, given by the residue of EEMD, appeared quite similar to the variation in reservoir L and well correlated to the variation of the water level within the aquifer. Exchanges between fissured matrix and conduits (reservoirs M and C) could be also investigated: a high frequency pressure pulse-controlled flow from C to M (intermittent recharge from the conduits) was identified, as well as fissured matrix flow likely to take place in the surroundings of the conduit network. Flow from reservoir M to reservoir C could be recovered by recombining wavelet components of spring discharge. This study demonstrated that statistical components extracted from a discharge signal of a karst spring can provide meaningful hydrological information. Comparison with a physics-based model would however be required in order to complement this

  19. Reliability of a conceptual hydrological model in a semi-arid Andean catchment facing water-use changes

    NASA Astrophysics Data System (ADS)

    Hublart, P.; Ruelland, D.; García De Cortázar Atauri, I.; Ibacache, A.

    2015-06-01

    This paper explores the reliability of low-flow simulations by conceptual models in a semi-arid, Andean catchment (30° S) facing climate variability and water-use changes. Depending on water availability, a significant part of surface water resources are diverted to meet irrigation requirements. In return, these water withdrawals are likely to influence the hydrological behavior of the catchment. The value of model-based analyses thus relies on our ability to adequately represent the complex interactions between climate variability, human-induced flow perturbations and crop water use. In this study, a parsimonious hydrological model (GR4J) including a snow routine was combined with a model of irrigation water-use (IWU) to provide a new, 6-parameter model of the catchment behavior (called GR4J/IWU). The original, 4-parameter GR4J model and the 6-parameter GR6J model were also used as benchmarks to evaluate the usefulness of explicitly accounting for water abstractions. Calibration and validation of these three models were performed successively over two different 5-year periods representing contrasted water-use and climate conditions. Overall, the GR4J/IWU model provided better simulations than the GR4J and GR6J models over both periods. Further research is required to quantify the predictive uncertainty associated with model structures, parameters and inputs.

  20. MESSI: An engineering tool for conceptual hydrological modeling using SUPERFLEX, MOSCEM and GLUE

    NASA Astrophysics Data System (ADS)

    van Osnabrugge, Bart; Mondeel, Herman; Hrachowitz, Markus

    2014-05-01

    The progress of hydrology as a science is mentioned quite often and indeed lots of theoretical research is done to improving hydrological rainfall-runoff (RR) modeling. At the same time however, it is concluded that engineering practice lags behind on this scientific progress by at least a couple of years. In this research, it is investigated how this gap can be closed. An engineering tool is developed called Model Ensemble, Sampling, Selection and Interpretation (MESSI) and tested in the engineering environment. The tool uses the model hypothesis framework SUPERFLEX to build an 'a-priori' ensemble of possible model structures for the case at hand. Then, the Multi-objective Shuffled Complex Evolution Metropolis algorithm (MOSCEM) is used for sampling of the parameter space. Finally, the Generalized Likelihood Uncertainty Estimation (GLUE) methodology is used to select a posterior ensemble which is then interpreted using the Pareto front and generated uncertainty bounds. During the trial it was found that MESSI provides a plug-and-play method which is able to provide catchment process information, a mathematical optimal model and a measure of uncertainty based on the observation. Most important, it is shown that with a little effort new techniques can be brought directly to the engineering arena which will improve the interaction between the scientist and the engineer.

  1. Parameterization of soil moisture-heat transfer processes for conceptual hydrologic models

    NASA Astrophysics Data System (ADS)

    Koren, V.

    2003-04-01

    Recent developments in land surface modeling have significantly improved representation of cold season processes in atmospheric models. However, a conceptual representation of a soil profile in commonly used watershed models complicates the implementation of physically-based heat/moisture transfer models that require numerical integration over the soil profile. This study is focused on developing and testing a procedure to transform layer-structured heat-moisture states into reservoir-type states used by watershed models, and vice versa. The Sacramento Soil Moisture Accounting model (SAC-SMA) is used to estimate soil moisture states and runoff components, and a layer integrated form of the heat transfer equation is used to estimate soil temperature and unfrozen water states. The SAC-SMA storages, represented as totals of tension and free water plus a moisture below wilting point, are recalculated into a number of soil layers using soil texture data. Three or four layers are usually used with much higher resolution in the upper zone. At each time step, SAC-SMA liquid water storage changes due to rainfall/snowmelt are estimated and transformed into soil profile moisture states of the heat transfer numerical scheme. The heat transfer component then splits the total water content into frozen and liquid water portions, which are then converted back into SAC-SMA states. A conceptual parameterization is used to account for changes in percolation and runoff components due to frozen ground effects. Parameterization was tested using a number of sites in the Northwest of the US when soil temperature measurements were available at few soil layers. Only daily precipitation and air temperature data were used in simulations. Solid and liquid soil moisture contents, and soil temperature at five layers were simulated for 3--5 years. Test results suggested that a conceptual representation of soil moisture fluxes combined with a physically-based heat transfer model provided

  2. Information on Hydrologic Conceptual Models, Parameters, Uncertainty Analysis, and Data Sources for Dose Assessments at Decommissioning Sites

    SciTech Connect

    Meyer, Philip D.; Gee, Glendon W.; Nicholson, Thomas J.

    2000-02-28

    This report addresses issues related to the analysis of uncertainty in dose assessments conducted as part of decommissioning analyses. The analysis is limited to the hydrologic aspects of the exposure pathway involving infiltration of water at the ground surface, leaching of contaminants, and transport of contaminants through the groundwater to a point of exposure. The basic conceptual models and mathematical implementations of three dose assessment codes are outlined along with the site-specific conditions under which the codes may provide inaccurate, potentially nonconservative results. In addition, the hydrologic parameters of the codes are identified and compared. A methodology for parameter uncertainty assessment is outlined that considers the potential data limitations and modeling needs of decommissioning analyses. This methodology uses generic parameter distributions based on national or regional databases, sensitivity analysis, probabilistic modeling, and Bayesian updating to incorporate site-specific information. Data sources for best-estimate parameter values and parameter uncertainty information are also reviewed. A follow-on report will illustrate the uncertainty assessment methodology using decommissioning test cases.

  3. Simultaneous Assimilation of Multiple Data into a Conceptual Rainfall-Runoff Model using Variational Methods for Hydrological Forecasting Applications

    NASA Astrophysics Data System (ADS)

    Schwanenberg, D.; Alvarado Montero, R.; Sensoy Sorman, A.; Krahe, P.

    2015-12-01

    Data assimilation methods applied to hydrological applications have primarily focused on assimilating streamflow and, more recently, soil moisture observations. Few cases actually assimilate both observations, and even fewer incorporate additional observations into the assimilation procedure. This is despite extensive developments in remote sensing information. Most research on data assimilation has focused on the implementation of sequential assimilation using Kalman filters. We present an alternative approach using variational methods based on Moving Horizon Estimation (MHE) to simultaneously assimilate streamflow data and remote sensing information obtained from the Satellite Application Facility on Support to Operational Hydrology and Water Management (H-SAF) community, namely snow-covered area, snow water equivalent and soil moisture. This approach enables a highly flexible formulation of distance metrics for the introduction of noise into the model and the agreement between simulated and observed variables. The application of MHE on data assimilation is tested at two data-dense test sites in Germany and one data-sparse environment in Turkey. The assessment of results is based on the lead time performance of state variables of the conceptual rainfall-runoff model, i.e. not limited to the performance of streamflow forecast but also applicable to snow and soil moisture forecast skills. Results show a potential improvement on the performance of the forecasted streamflow when using a perfect time series of state variables generated through the simulation of the conceptual rainfall-runoff model HBV. The assimilation of H-SAF data, in combination with streamflow, reduces the performance of the forecasted streamflow compared to the assimilation using only streamflow data. However, other forecasted quantities such as the snow water equivalent or soil moisture are improved. Recommendations based on the test cases are given following the length of the assimilation

  4. Multi-response calibration of a conceptual hydrological model in the semiarid catchment of Wadi al Arab, Jordan

    NASA Astrophysics Data System (ADS)

    Rödiger, T.; Geyer, S.; Mallast, U.; Merz, R.; Krause, P.; Fischer, C.; Siebert, C.

    2014-02-01

    A key factor for sustainable management of groundwater systems is the accurate estimation of groundwater recharge. Hydrological models are common tools for such estimations and widely used. As such models need to be calibrated against measured values, the absence of adequate data can be problematic. We present a nested multi-response calibration approach for a semi-distributed hydrological model in the semi-arid catchment of Wadi al Arab in Jordan, with sparsely available runoff data. The basic idea of the calibration approach is to use diverse observations in a nested strategy, in which sub-parts of the model are calibrated to various observation data types in a consecutive manner. First, the available different data sources have to be screened for information content of processes, e.g. if data sources contain information on mean values, spatial or temporal variability etc. for the entire catchment or only sub-catchments. In a second step, the information content has to be mapped to relevant model components, which represent these processes. Then the data source is used to calibrate the respective subset of model parameters, while the remaining model parameters remain unchanged. This mapping is repeated for other available data sources. In that study the gauged spring discharge (GSD) method, flash flood observations and data from the chloride mass balance (CMB) are used to derive plausible parameter ranges for the conceptual hydrological model J2000g. The water table fluctuation (WTF) method is used to validate the model. Results from modelling using a priori parameter values from literature as a benchmark are compared. The estimated recharge rates of the calibrated model deviate less than ±10% from the estimates derived from WTF method. Larger differences are visible in the years with high uncertainties in rainfall input data. The performance of the calibrated model during validation produces better results than applying the model with only a priori parameter

  5. Constraining a semi-distributed, conceptual hydrological model on evaporation - a case study for the Kulpawn River Basin, Ghana

    NASA Astrophysics Data System (ADS)

    Nijzink, Remko C.; Savenije, Hubert H. G.; Hrachowitz, Markus

    2016-04-01

    Hydrological models are typically calibrated on stream flow observations. However, such data are frequently not available. In addition, in many parts of the world not stream flow, but rather evaporation and transpiration are the largest fluxes from hydrological systems. Nevertheless, models trained to evaporation data are rare and typically rely on evaporation estimates that were themselves also derived from models, thereby considerably reducing the robustness of such approaches. In this study, we test the power of alternative approaches to constrain semi-distributed, conceptual models with information on evaporation in the absence of stream flow data. By gradually increasing the constraining information, the analysis is designed in a stepwise way. Both, the models and the relevance of the added information are evaluated for each step. As a first step, a large set of random parameter sets from uniform prior distributions is generated. Subsequently, parameter sets that cannot produce model outputs that satisfy the added constraints are discarded. The information content of these constraints will be gradually increased by making use of the Budyko framework: (1) the model has to reproduce the long-term average actual evaporation of the system, as indicated by the position in the Budyko framework, (2) the model, similarly, has to reproduce the long-term average seasonal variations of actual evaporation, (3) the model has to reproduce the temporal variations of evaporation, e.g. differences between 5-year mean evaporation of different periods, as indicated by different positions in the Budyko framework. As a last step, the model's temporal dynamics in the root zone moisture content are constrained by comparing it to time series of the NDII (Normalized Difference Infrared Index), which has recently been shown to be a close proxy for plant available water in the root zone and, thus, for transpiration rates ( Sriwongsitanon et al., 2015). The value of the information

  6. Regime shifts under forcing of non-stationary attractors: Conceptual model and case studies in hydrologic systems

    NASA Astrophysics Data System (ADS)

    Park, Jeryang; Rao, P. Suresh C.

    2014-11-01

    We present here a conceptual model and analysis of complex systems using hypothetical cases of regime shifts resulting from temporal non-stationarity in attractor strengths, and then present selected published cases to illustrate such regime shifts in hydrologic systems (shallow aquatic ecosystems; water table shifts; soil salinization). Complex systems are dynamic and can exist in two or more stable states (or regimes). Temporal variations in state variables occur in response to fluctuations in external forcing, which are modulated by interactions among internal processes. Combined effects of external forcing and non-stationary strengths of alternative attractors can lead to shifts from original to alternate regimes. In systems with bi-stable states, when the strengths of two competing attractors are constant in time, or are non-stationary but change in a linear fashion, regime shifts are found to be temporally stationary and only controlled by the characteristics of the external forcing. However, when attractor strengths change in time non-linearly or vary stochastically, regime shifts in complex systems are characterized by non-stationary probability density functions (pdfs). We briefly discuss implications and challenges to prediction and management of hydrologic complex systems.

  7. Corruption of accuracy and efficiency of Markov chain Monte Carlo simulation by inaccurate numerical implementation of conceptual hydrologic models

    NASA Astrophysics Data System (ADS)

    Schoups, G.; Vrugt, J. A.; Fenicia, F.; van de Giesen, N. C.

    2010-10-01

    Conceptual rainfall-runoff models have traditionally been applied without paying much attention to numerical errors induced by temporal integration of water balance dynamics. Reliance on first-order, explicit, fixed-step integration methods leads to computationally cheap simulation models that are easy to implement. Computational speed is especially desirable for estimating parameter and predictive uncertainty using Markov chain Monte Carlo (MCMC) methods. Confirming earlier work of Kavetski et al. (2003), we show here that the computational speed of first-order, explicit, fixed-step integration methods comes at a cost: for a case study with a spatially lumped conceptual rainfall-runoff model, it introduces artificial bimodality in the marginal posterior parameter distributions, which is not present in numerically accurate implementations of the same model. The resulting effects on MCMC simulation include (1) inconsistent estimates of posterior parameter and predictive distributions, (2) poor performance and slow convergence of the MCMC algorithm, and (3) unreliable convergence diagnosis using the Gelman-Rubin statistic. We studied several alternative numerical implementations to remedy these problems, including various adaptive-step finite difference schemes and an operator splitting method. Our results show that adaptive-step, second-order methods, based on either explicit finite differencing or operator splitting with analytical integration, provide the best alternative for accurate and efficient MCMC simulation. Fixed-step or adaptive-step implicit methods may also be used for increased accuracy, but they cannot match the efficiency of adaptive-step explicit finite differencing or operator splitting. Of the latter two, explicit finite differencing is more generally applicable and is preferred if the individual hydrologic flux laws cannot be integrated analytically, as the splitting method then loses its advantage.

  8. A Revised Conceptual Model for Hydrologic Controls on Stream Nitrate Concentrations (Invited)

    NASA Astrophysics Data System (ADS)

    Duncan, J. M.; Band, L. E.

    2013-12-01

    Long term weekly sampling of stream chemistry at Pond Branch, MD USA, a 37ha forested watershed in the Piedmont physiographic province, has revealed recurrent summer peaks in nitrate concentrations and loads. The timing and magnitude of nitrogen export has been associated with factors ranging from catchment initial and boundary conditions, ecosystem, and edaphic factors. However, at weekly temporal resolution, only seasonal inferences can be drawn as to the combination of biogeochemical and hydrological processes that create these patterns. This work examines the role of hydro-climatic variability on in-stream nitrate concentration using high temporal resolution sensor data. By examining periods of time throughout the growing season (early, mid, and late) we investigate how the combined roles of net nitrate production and hydrologic transport are controlled by hydro-climatic conditions. Pond Branch appears to shift from a nitrate supply driven to a transport driven system over the course of the growing season. At least one of the relatively large rises in 2011 in nitrate export occured at baseflow, over a period of just four days, which was coincident with increases in riparian zone soil oxygen. We show that the frequency of rainfall events could control the amount of nitrate that can accumulate in near-stream variable source regions in early summer and that by mid-summer, when net nitrate production is maximized and consumption is constant, rainfall magnitude and duration control flushing. The research suggests that nitrate concentration-discharge relationships are time variable over very short durations and load estimation techniques should evolve to include the diel structure in data.

  9. Hydrological models are mediating models

    NASA Astrophysics Data System (ADS)

    Babel, L. V.; Karssenberg, D.

    2013-08-01

    Despite the increasing role of models in hydrological research and decision-making processes, only few accounts of the nature and function of models exist in hydrology. Earlier considerations have traditionally been conducted while making a clear distinction between physically-based and conceptual models. A new philosophical account, primarily based on the fields of physics and economics, transcends classes of models and scientific disciplines by considering models as "mediators" between theory and observations. The core of this approach lies in identifying models as (1) being only partially dependent on theory and observations, (2) integrating non-deductive elements in their construction, and (3) carrying the role of instruments of scientific enquiry about both theory and the world. The applicability of this approach to hydrology is evaluated in the present article. Three widely used hydrological models, each showing a different degree of apparent physicality, are confronted to the main characteristics of the "mediating models" concept. We argue that irrespective of their kind, hydrological models depend on both theory and observations, rather than merely on one of these two domains. Their construction is additionally involving a large number of miscellaneous, external ingredients, such as past experiences, model objectives, knowledge and preferences of the modeller, as well as hardware and software resources. We show that hydrological models convey the role of instruments in scientific practice by mediating between theory and the world. It results from these considerations that the traditional distinction between physically-based and conceptual models is necessarily too simplistic and refers at best to the stage at which theory and observations are steering model construction. The large variety of ingredients involved in model construction would deserve closer attention, for being rarely explicitly presented in peer-reviewed literature. We believe that devoting

  10. Chance-constrained overland flow modeling for improving conceptual distributed hydrologic simulations based on scaling representation of sub-daily rainfall variability.

    PubMed

    Han, Jing-Cheng; Huang, Guohe; Huang, Yuefei; Zhang, Hua; Li, Zhong; Chen, Qiuwen

    2015-08-15

    Lack of hydrologic process representation at the short time-scale would lead to inadequate simulations in distributed hydrological modeling. Especially for complex mountainous watersheds, surface runoff simulations are significantly affected by the overland flow generation, which is closely related to the rainfall characteristics at a sub-time step. In this paper, the sub-daily variability of rainfall intensity was considered using a probability distribution, and a chance-constrained overland flow modeling approach was proposed to capture the generation of overland flow within conceptual distributed hydrologic simulations. The integrated modeling procedures were further demonstrated through a watershed of China Three Gorges Reservoir area, leading to an improved SLURP-TGR hydrologic model based on SLURP. Combined with rainfall thresholds determined to distinguish various magnitudes of daily rainfall totals, three levels of significance were simultaneously employed to examine the hydrologic-response simulation. Results showed that SLURP-TGR could enhance the model performance, and the deviation of runoff simulations was effectively controlled. However, rainfall thresholds were so crucial for reflecting the scaling effect of rainfall intensity that optimal levels of significance and rainfall threshold were 0.05 and 10 mm, respectively. As for the Xiangxi River watershed, the main runoff contribution came from interflow of the fast store. Although slight differences of overland flow simulations between SLURP and SLURP-TGR were derived, SLURP-TGR was found to help improve the simulation of peak flows, and would improve the overall modeling efficiency through adjusting runoff component simulations. Consequently, the developed modeling approach favors efficient representation of hydrological processes and would be expected to have a potential for wide applications. PMID:25889540

  11. A conceptual socio-hydrological model of the co-evolution of humans and water: case study of the Tarim River basin, western China

    NASA Astrophysics Data System (ADS)

    Liu, D.; Tian, F.; Lin, M.; Sivapalan, M.

    2015-02-01

    The complex interactions and feedbacks between humans and water are critically important issues but remain poorly understood in the newly proposed discipline of socio-hydrology (Sivapalan et al., 2012). An exploratory model with the appropriate level of simplification can be valuable for improving our understanding of the co-evolution and self-organization of socio-hydrological systems driven by interactions and feedbacks operating at different scales. In this study, a simplified conceptual socio-hydrological model based on logistic growth curves is developed for the Tarim River basin in western China and is used to illustrate the explanatory power of such a co-evolutionary model. The study area is the main stream of the Tarim River, which is divided into two modeling units. The socio-hydrological system is composed of four sub-systems, i.e., the hydrological, ecological, economic, and social sub-systems. In each modeling unit, the hydrological equation focusing on water balance is coupled to the other three evolutionary equations to represent the dynamics of the social sub-system (denoted by population), the economic sub-system (denoted by irrigated crop area ratio), and the ecological sub-system (denoted by natural vegetation cover), each of which is expressed in terms of a logistic growth curve. Four feedback loops are identified to represent the complex interactions among different sub-systems and different spatial units, of which two are inner loops occurring within each separate unit and the other two are outer loops linking the two modeling units. The feedback mechanisms are incorporated into the constitutive relations for model parameters, i.e., the colonization and mortality rates in the logistic growth curves that are jointly determined by the state variables of all sub-systems. The co-evolution of the Tarim socio-hydrological system is then analyzed with this conceptual model to gain insights into the overall system dynamics and its sensitivity to the

  12. Using combined hydrological variables for extracting functional signatures of catchments to better assess the acceptability of model structures in conceptual catchment modelling

    NASA Astrophysics Data System (ADS)

    Fovet, O.; Hrachowitz, M.; RUIZ, L.; Gascuel-odoux, C.; Savenije, H.

    2013-12-01

    While most hydrological models reproduce the general flow dynamics of a system, they frequently fail to adequately mimic system internal processes. This is likely to make them inadequate to simulate solutes transport. For example, the hysteresis between storage and discharge, which is often observed in shallow hard-rock aquifers, is rarely well reproduced by models. One main reason is that this hysteresis has little weight in the calibration because objective functions are based on time series of individual variables. This reduces the ability of classical calibration/validation procedures to assess the relevance of the conceptual hypothesis associated with hydrological models. Calibrating models on variables derived from the combination of different individual variables (like stream discharge and groundwater levels) is a way to insure that models will be accepted based on their consistency. Here we therefore test the value of this more systems-like approach to test different hypothesis on the behaviour of a small experimental low-land catchment in French Brittany (ORE AgrHys) where a high hysteresis is observed on the stream flow vs. shallow groundwater level relationship. Several conceptual models were applied to this site, and calibrated using objective functions based on metrics of this hysteresis. The tested model structures differed with respect to the storage function in each reservoir, the storage-discharge function in each reservoir, the deep loss expressions (as constant or variable fraction), the number of reservoirs (from 1 to 4) and their organization (parallel, series). The observed hysteretic groundwater level-discharge relationship was not satisfactorily reproduced by most of the tested models except for the most complex ones. Those were thus more consistent, their underlying hypotheses are probably more realistic even though their performance for simulating observed stream flow was decreased. Selecting models based on such systems-like approach is

  13. Conceptual Model of Hydrologic and Thermal Conditions of the Eastbank Aquifer System near Rocky Reach Dam, Douglas County, Washington

    USGS Publications Warehouse

    van Heeswijk, Marijke; Cox, Stephen E.; Huffman, Raegan L.; Curran, Christopher A.

    2008-01-01

    2006 and seasonal pumpage patterns were relatively stable, reported trends of increasing temperatures of water pumped by the hatchery well field are most likely explained by increasing trends in river temperatures. Most of the water pumped by the hatchery well field recharges in an area west to southwest of the well field about 2 months prior to the time it is pumped from the aquifer. The northern extent of the hatchery well field may pump some colder water from a bedrock depression to the north and west of the well field. The conceptual model of hydrologic and thermal conditions is supported by analyses of historical water temperatures, water-level data collected on July 18, 2007, and dissolved-constituent and bacterial concentrations in samples collected on August 20?22, 2007.

  14. Incorporating expert knowledge in calibrating a complex hydrological conceptual model: A FLEX-TOPO case study for a central European meso-scale catchment

    NASA Astrophysics Data System (ADS)

    Gharari, Shervan; Hrachowitz, Markus; Fenicia, Fabrizio; Gao, Hongkai; Euser, Tanja; Savenije, Huub

    2013-04-01

    Catchments are open systems meaning that it is impossible to find out the exact boundary conditions of the real system spatially and temporarily. Therefore models are essential tools in capturing system behavior spatially and extrapolating it temporarily for prediction. In recent years conceptual models have been in the center of attention rather than so called physically based models which are often over-parameterized and encounter difficulties for up-scaling of small scale processes. Conceptual models however are heavily dependent on calibration as one or more of their parameters can typically not be physically measured at the catchment scale. Parallel to the evolution of modeling attempts, our understanding of rainfall/runoff models increased due to improvements of measurement techniques. Heavily instrumented catchments have been studied, and measured system responses have been modeled for testing a priori hypothesis of system function. Although our understanding of how catchments may work has increased the lessons learned from the case specific studies remain locally valid and are not widely used in model calibration and development. In this study we try to constrain parameters of a complex conceptual model built on landscape units classified according to their hydrological functions, based on our logical considerations and general lessons from previous studies across the globe for the Luxembourgish meso-scale Wark catchment. The classified landscapes were used to assign different model structures to the individual hydrological response units. As an example deep percolation was defined as dominant process for plateaus, while rapid subsurface flow as dominant process for hillslope, and saturation overland flow as dominant process for wetlands. The modeled runoffs from each hydrological unit were combined in a parallel set-up to proportionally contribute to the total catchment runoff. The hydrological units are, in addition, linked by a common groundwater

  15. Incorporating expert knowledge in a complex hydrological conceptual model: A FLEX-TOPO case study for a central European meso-scale catchment

    NASA Astrophysics Data System (ADS)

    Gharari, S.; Hrachowitz, M.; Fenicia, F.; Gao, H.; Savenije, H.

    2013-12-01

    Models are essential tools in capturing system behavior, catchments, spatially and extrapolating it temporarily for prediction. In recent years conceptual models have been in the center of attention rather than so called physically based models which are often over-parameterized and encounter difficulties for up-scaling of small scale processes. Conceptual models however are heavily dependent on calibration as one or more of their parameters can typically not be physically measured at the catchment scale. In this study we try to constrain parameters of a complex conceptual model built on landscape units classified according to their hydrological functions, based on our logical considerations and general lessons from previous studies across the globe for the Luxembourgish meso-scale Wark catchment. The classified landscapes were used to assign different model structures to the individual hydrological response units. As an example deep percolation was defined as dominant process for plateaus, while rapid subsurface flow as dominant process for hillslope, and saturation overland flow as dominant process for wetlands. The modeled runoffs from each hydrological unit were combined in a parallel set-up to proportionally contribute to the total catchment runoff. The hydrological units are, in addition, linked by a common groundwater reservoir. The parallel hydrological units, although increasing the number of parameters, have the benefit of separate calibration. By stepwise calibration different mechanisms can be calibrated at periods when these mechanisms are active in isolation. For instance, the groundwater module is calibrated during dry season recession and the wetland module during isolated summer storms when the hillslopes are below the activation threshold. Moreover, one can constrain parameters by realistic conditions. As an example, the lag time of wetlands is likely to be shorter than the lag time of water traveling to the outlet from a plateau. Moreover, due to

  16. A Conceptual and Numerical Model for Thermal-Hydrological-Chemical Processes in the Yucca Mountain Drift Scale Test

    SciTech Connect

    Sonnenthal, Eric L.; Spycher, Nicolas F.; Conrad, Mark; Apps, John

    2003-07-01

    A numerical model was developed to predict the coupled thermal, hydrological, and chemical (THC) processes accompanying the Drift Scale Test (DST) at Yucca Mountain, NV. The DST has been closely monitored through the collection of gas, water, and mineral samples as well as thermal, hydrological, and mechanical measurements. A two-dimensional dual permeability model was developed to evaluate multiphase, multicomponent, reaction-transport processes in the fractured tuff. Comparisons between results using the TOUGHREACT code and measured water (e.g., pH, SiO2(aq), Na+, K+) and gas (CO2) compositions show that the model captures the chemical evolution in the DST. Non-reactive aqueous species (e.g., Cl) show strong dilution in fracture waters, indicating little fracture-matrix interaction. Silica concentrations are higher than in the initial pore water and show a trend of increasing reaction with fracture-lining silicates at higher temperatures. The narrow precipitation zone of predominantly amorphous silica observed above the heaters was also captured.

  17. Development of the Conceptual Models for Chemical Conditions and Hydrology Used in the 1996 Performance Assessment for the Waste Isolation Pilot Plant

    SciTech Connect

    LARSON, KURT W

    2000-05-24

    The Waste Isolation Pilot Plant (WIPP) is a US Department of Energy (DOE) facility for the permanent disposal of defense-related transuranic (TRU) waste. US Environmental Protection Agency (EPA) regulations specify that the DOE must demonstrate on a sound basis that the WIPP disposal system will effectively contain long-lived alpha-emitting radionuclides within its boundaries for 10,000 years following closure. In 1996, the DOE submitted the ''40 CFR Part 191 Compliance Certification Application for the Waste Isolation Pilot Plant'' (CCA) to the EPA. The CCA proposed that the WIPP site complies with EPA's regulatory requirements. Contained within the CCA are descriptions of the scientific research conducted to characterize the properties of the WIPP site and the probabilistic performance assessment (PA) conducted to predict the containment properties of the WIPP disposal system. In May 1998, the EPA certified that the TRU waste disposal at the WIPP complies with its regulations. Waste disposal operations at WIPP commenced on March 28, 1999. The 1996 WIPP PA model of the disposal system included conceptual and mathematical representations of key hydrologic and geochemical processes. These key processes were identified over a 22-year period involving data collection, data interpretation, computer models, and sensitivity studies to evaluate the importance of uncertainty and of processes that were difficult to evaluate by other means. Key developments in the area of geochemistry were the evaluation of gas generation mechanisms in the repository; development of a model of chemical conditions in the repository and actinide concentrations in brine; selecting MgO backfill and demonstrating its effects experimentally; and determining the chemical retardation capability of the Culebra. Key developments in the area of hydrology were evacuating the potential for groundwater to dissolve the Salado Formation (the repository host formation), development of a regional model for

  18. A Conceptual Approach to Assimilating Remote Sensing Data to Improve Soil Moisture Profile Estimates in a Surface Flux/Hydrology Model. 2; Aggregation

    NASA Technical Reports Server (NTRS)

    Schamschula, Marius; Crosson, William L.; Inguva, Ramarao; Yates, Thomas; Laymen, Charles A.; Caulfield, John

    1998-01-01

    This is a follow up on the preceding presentation by Crosson. The grid size for remote microwave measurements is much coarser than the hydrological model computational grids. To validate the hydrological models with measurements we propose mechanisms to aggregate the hydrological model outputs for soil moisture to allow comparison with measurements. Weighted neighborhood averaging methods are proposed to facilitate the comparison. We will also discuss such complications as misalignment, rotation and other distortions introduced by a generalized sensor image.

  19. 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.

  20. Hydrological mobilization of mercury and dissolved organic carbon in a snow-dominated, forested watershed: Conceptualization and modeling

    NASA Astrophysics Data System (ADS)

    Schelker, J.; Burns, D. A.; Weiler, M.; Laudon, H.

    2011-03-01

    The mobilization of mercury and dissolved organic carbon (DOC) during snowmelt often accounts for a major fraction of the annual loads. We studied the role of hydrological connectivity of riparian wetlands and upland/wetland transition zones to surface waters on the mobilization of Hg and DOC in Fishing Brook, a headwater of the Adirondack Mountains, New York. Stream water total mercury (THg) concentrations varied strongly (mean = 2.25 ± 0.5 ng L-1), and the two snowmelt seasons contributed 40% (2007) and 48% (2008) of the annual load. Methyl mercury (MeHg) concentrations ranged up to 0.26 ng L-1, and showed an inverse log relationship with discharge. TOPMODEL-simulated saturated area corresponded well with wetland areas, and the application of a flow algorithm based elevation-above-creek approach suggests that most wetlands become well connected during high flow. The dynamics of simulated saturated area and soil storage deficit were able to explain a large part of the variation of THg concentrations (r2 = 0.53 to 0.72). In contrast, the simulations were not able to explain DOC variations and DOC and THg concentrations were not correlated. These results indicate that all three constituents, THg, MeHg, and DOC, follow different patterns at the outlet: (1) the mobilization of THg is primarily controlled by the saturation state of the catchment, (2) the dilution of MeHg suggests flushing from a supply limited pool, and (3) DOC dynamics follow a pattern different from THg dynamics, which likely results from differing gain and/or loss processes for THg and/or DOC within the Fishing Brook catchment.

  1. Hydrological mobilization of mercury and dissolved organic carbon in a snow-dominated, forested watershed: Conceptualization and modeling

    USGS Publications Warehouse

    Schelker, J.; Burns, Douglas A.; Weiler, M.; Laudon, H.

    2011-01-01

    The mobilization of mercury and dissolved organic carbon (DOC) during snowmelt often accounts for a major fraction of the annual loads. We studied the role of hydrological connectivity of riparian wetlands and upland/wetland transition zones to surface waters on the mobilization of Hg and DOC in Fishing Brook, a headwater of the Adirondack Mountains, New York. Stream water total mercury (THg) concentrations varied strongly (mean = 2.25 ?? 0.5 ng L -1), and the two snowmelt seasons contributed 40% (2007) and 48% (2008) of the annual load. Methyl mercury (MeHg) concentrations ranged up to 0.26 ng L-1, and showed an inverse log relationship with discharge. TOPMODEL-simulated saturated area corresponded well with wetland areas, and the application of a flow algorithm based elevation-above-creek approach suggests that most wetlands become well connected during high flow. The dynamics of simulated saturated area and soil storage deficit were able to explain a large part of the variation of THg concentrations (r2 = 0.53 to 0.72). In contrast, the simulations were not able to explain DOC variations and DOC and THg concentrations were not correlated. These results indicate that all three constituents, THg, MeHg, and DOC, follow different patterns at the outlet: (1) the mobilization of THg is primarily controlled by the saturation state of the catchment, (2) the dilution of MeHg suggests flushing from a supply limited pool, and (3) DOC dynamics follow a pattern different from THg dynamics, which likely results from differing gain and/or loss processes for THg and/or DOC within the Fishing Brook catchment. Copyright 2011 by the American Geophysical Union.

  2. A Conceptual Approach to Assimilating Remote Sensing Data to Improve Soil Moisture Profile Estimates in a Surface Flux/Hydrology Model. 3; Disaggregation

    NASA Technical Reports Server (NTRS)

    Caulfield, John; Crosson, William L.; Inguva, Ramarao; Laymon, Charles A.; Schamschula, Marius

    1998-01-01

    This is a followup on the preceding presentation by Crosson and Schamschula. The grid size for remote microwave measurements is much coarser than the hydrological model computational grids. To validate the hydrological models with measurements we propose mechanisms to disaggregate the microwave measurements to allow comparison with outputs from the hydrological models. Weighted interpolation and Bayesian methods are proposed to facilitate the comparison. While remote measurements occur at a large scale, they reflect underlying small-scale features. We can give continuing estimates of the small scale features by correcting the simple 0th-order, starting with each small-scale model with each large-scale measurement using a straightforward method based on Kalman filtering.

  3. Multi-criteria evaluation of hydrological models

    NASA Astrophysics Data System (ADS)

    Rakovec, Oldrich; Clark, Martyn; Weerts, Albrecht; Hill, Mary; Teuling, Ryan; Uijlenhoet, Remko

    2013-04-01

    Over the last years, there is a tendency in the hydrological community to move from the simple conceptual models towards more complex, physically/process-based hydrological models. This is because conceptual models often fail to simulate the dynamics of the observations. However, there is little agreement on how much complexity needs to be considered within the complex process-based models. One way to proceed to is to improve understanding of what is important and unimportant in the models considered. The aim of this ongoing study is to evaluate structural model adequacy using alternative conceptual and process-based models of hydrological systems, with an emphasis on understanding how model complexity relates to observed hydrological processes. Some of the models require considerable execution time and the computationally frugal sensitivity analysis, model calibration and uncertainty quantification methods are well-suited to providing important insights for models with lengthy execution times. The current experiment evaluates two version of the Framework for Understanding Structural Errors (FUSE), which both enable running model inter-comparison experiments. One supports computationally efficient conceptual models, and the second supports more-process-based models that tend to have longer execution times. The conceptual FUSE combines components of 4 existing conceptual hydrological models. The process-based framework consists of different forms of Richard's equations, numerical solutions, groundwater parameterizations and hydraulic conductivity distribution. The hydrological analysis of the model processes has evolved from focusing only on simulated runoff (final model output), to also including other criteria such as soil moisture and groundwater levels. Parameter importance and associated structural importance are evaluated using different types of sensitivity analyses techniques, making use of both robust global methods (e.g. Sobol') as well as several

  4. Conceptual IT model

    NASA Astrophysics Data System (ADS)

    Arnaoudova, Kristina; Stanchev, Peter

    2015-11-01

    The business processes are the key asset for every organization. The design of the business process models is the foremost concern and target among an organization's functions. Business processes and their proper management are intensely dependent on the performance of software applications and technology solutions. The paper is attempt for definition of new Conceptual model of IT service provider, it could be examined as IT focused Enterprise model, part of Enterprise Architecture (EA) school.

  5. PATHS groundwater hydrologic model

    SciTech Connect

    Nelson, R.W.; Schur, J.A.

    1980-04-01

    A preliminary evaluation capability for two-dimensional groundwater pollution problems was developed as part of the Transport Modeling Task for the Waste Isolation Safety Assessment Program (WISAP). Our approach was to use the data limitations as a guide in setting the level of modeling detail. PATHS Groundwater Hydrologic Model is the first level (simplest) idealized hybrid analytical/numerical model for two-dimensional, saturated groundwater flow and single component transport; homogeneous geology. This document consists of the description of the PATHS groundwater hydrologic model. The preliminary evaluation capability prepared for WISAP, including the enhancements that were made because of the authors' experience using the earlier capability is described. Appendixes A through D supplement the report as follows: complete derivations of the background equations are provided in Appendix A. Appendix B is a comprehensive set of instructions for users of PATHS. It is written for users who have little or no experience with computers. Appendix C is for the programmer. It contains information on how input parameters are passed between programs in the system. It also contains program listings and test case listing. Appendix D is a definition of terms.

  6. Socio-Hydrology: Conceptual and Methodological Challenges in the Bidirectional Coupling of Human and Water Systems

    NASA Astrophysics Data System (ADS)

    Scott, C. A.

    2014-12-01

    This presentation reviews conceptual advances in the emerging field of socio-hydrology that focuses on coupled human and water systems. An important current challenge is how to better couple the bidirectional influences between human and water systems, which lead to emergent dynamics. The interactions among (1) the structure and dynamics of systems with (2) human values and norms lead to (3) outcomes, which in turn influence subsequent interactions. Human influences on hydrological systems are relatively well understood, chiefly resulting from developments in the field of water resources. The ecosystem-service concept of cultural value has expanded understanding of decision-making beyond economic rationality criteria. Hydrological impacts on social processes are less well developed conceptually, but this is changing with growing attention to vulnerability, adaptation, and resilience, particularly in the face of climate change. Methodological limitations, especially in characterizing the range of human responses to hydrological events and drivers, still pose challenges to modeling bidirectional human-water influences. Evidence from multiple case studies, synthesized in more broadly generic syndromes, helps surmount these methodological limitations and offers the potential to improve characterization and quantification of socio-hydrological systems.

  7. Understanding the Dynamics of Socio-Hydrological Environment: a Conceptual Framework

    NASA Astrophysics Data System (ADS)

    Woyessa, Y.; Welderufael, W.; Edossa, D.

    2011-12-01

    Human actions affect ecological systems and the services they provide through various activities, such as land use, water use, pollution and climate change. Climate change is perhaps one of the most important sustainable development challenges that threaten to undo many of the development efforts being made to reach the targets set for the Millennium Development Goals. Understanding the change of ecosystems under different scenarios of climate and biophysical conditions could assist in bringing the issue of ecosystem services into decision making process. Similarly, the impacts of land use change on ecosystems and biodiversity have received considerable attention from ecologists and hydrologists alike. Land use change in a catchment can impact on water supply by altering hydrological processes, such as infiltration, groundwater recharge, base flow and direct runoff. In the past a variety of models were used for predicting land-use changes. Recently the focus has shifted away from using mathematically oriented models to agent-based modelling (ABM) approach to simulate land use scenarios. A conceptual framework is being developed which integrates climate change scenarios and the human dimension of land use decision into a hydrological model in order to assess its impacts on the socio-hydrological dynamics of a river basin. The following figures present the framework for the analysis and modelling of the socio-hydrological dynamics. Keywords: climate change, land use, river basin

  8. Modeling the Interactions between Hydrological Extremes, Water Management and Society.

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

    Over the past years, several studies have focused on exploring human impacts on the hydrological regime. Even though the dominant hydrological processes are mostly well understood, there are still several challenges related to modeling the coevolution of human impacts on (and responses to) hydrological extremes, such as floods and droughts. Some initial modeling attempts have proved to capture the essential dynamics emerging from two-way feedbacks between hydrological and social processes. However, they have predominantly focused on flooding. This research aims to develop a new conceptual model unraveling the interplay between hydrological extremes (floods and droughts) and human societies in a changing climate. In particular, this socio-hydrological model aims at understanding, and predicting the dynamics of coupled human-water systems to explain and capture how the occurrence of hydrological extremes changes water management approach, and how such a change (in turn) mitigates the impacts of hydrological extremes. The conceptual model is then applied to a case study to test its ability in simulating the dynamics emerging from the interplay between hydrological and social processes.

  9. 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.

  10. A Conceptual Approach to Assimilating Remote Sensing Data to Improve Soil Moisture Profile Estimates in a Surface Flux/Hydrology Model. Part 1; Overview

    NASA Technical Reports Server (NTRS)

    Crosson, William L.; Laymon, Charles A.; Inguva, Ramarao; Schamschula, Marius; Caulfield, John

    1998-01-01

    advantage of radar is its much higher resolution than passive microwave systems, but it is currently hampered by surface roughness effects and the lack of a good algorithm based on a single frequency and single polarization. In addition, its repeat frequency is generally low (about 40 days). In the meantime, two new radiometers offer some hope for remote sensing of soil moisture from space. The Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI), launched in November 1997, possesses a 10.65 GHz channel and the Advanced Microwave Scanning Radiometer (AMSR) on both the ADEOS-11 and Earth Observing System AM-1 platforms to be launched in 1999 possesses a 6.9 GHz channel. Aside from issues about interference from vegetation, the coarse resolution of these data will provide considerable challenges pertaining to their application. The resolution of TMI is about 45 km and that of AMSR is about 70 km. These resolutions are grossly inconsistent with the scale of soil moisture processes and the spatial variability of factors that control soil moisture. Scale disparities such as these are forcing us to rethink how we assimilate data of various scales in hydrologic models. Of particular interest is how to assimilate soil moisture data by reconciling the scale disparity between what we can expect from present and future remote sensing measurements of soil moisture and modeling soil moisture processes. It is because of this disparity between the resolution of space-based sensors and the scale of data needed for capturing the spatial variability of soil moisture and related properties that remote sensing of soil moisture has not met with more widespread success. Within a single footprint of current sensors at the wavelengths optimal for this application, in most cases there is enormous heterogeneity in soil moisture created by differences in landcover, soils and topography, as well as variability in antecedent precipitation. It is difficult to interpret the meaning of 'mean

  11. Probabilistic graphs as a conceptual and computational tool in hydrology and water management

    NASA Astrophysics Data System (ADS)

    Schoups, Gerrit

    2014-05-01

    Originally developed in the fields of machine learning and artificial intelligence, probabilistic graphs constitute a general framework for modeling complex systems in the presence of uncertainty. The framework consists of three components: 1. Representation of the model as a graph (or network), with nodes depicting random variables in the model (e.g. parameters, states, etc), which are joined together by factors. Factors are local probabilistic or deterministic relations between subsets of variables, which, when multiplied together, yield the joint distribution over all variables. 2. Consistent use of probability theory for quantifying uncertainty, relying on basic rules of probability for assimilating data into the model and expressing unknown variables as a function of observations (via the posterior distribution). 3. Efficient, distributed approximation of the posterior distribution using general-purpose algorithms that exploit model structure encoded in the graph. These attributes make probabilistic graphs potentially useful as a conceptual and computational tool in hydrology and water management (and beyond). Conceptually, they can provide a common framework for existing and new probabilistic modeling approaches (e.g. by drawing inspiration from other fields of application), while computationally they can make probabilistic inference feasible in larger hydrological models. The presentation explores, via examples, some of these benefits.

  12. 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.

  13. Hydrology and ecology of pinyon-juniper woodlands: Conceptual framework and field studies

    SciTech Connect

    Wilcox, B.P.; Breshears, D.D.

    1994-09-01

    Pinyon-juniper woodlands represent an important ecosystem in the semiarid western United States. Concern over the sustainability of, and management approaches for, these woodlands is increasing. As in other semiarid environments, water dynamics and vegetation patterns in pinyon-juniper woodlands are highly interrelated. An understanding of these relationships can aid in evaluating various management strategies. In this paper we describe a conceptual framework designed to increase our understanding of water and vegetation in pinyon-juniper woodlands. The framework comprises five different scales, at each of which the landscape is divided into {open_quotes}functional units{close_quotes} on the basis of hydrologic characteristics. The hydrologic behavior of each unit and the connections between units are being evaluated using an extensive network of hydrological and ecological field studies on the Pajarito Plateau in northern New Mexico. Data from these studies, coupled with application of the conceptual model, have led to the development of a number of hypotheses concerning the interrelationships of water and vegetation in pinyon-juniper woodlands.

  14. Monthly Hydrological Model Evaluation through Mapping the Hydrological Pattern to Information Space

    NASA Astrophysics Data System (ADS)

    Pan, B.; Cong, Z.

    2014-12-01

    Conceptual and stochastic monthly hydrological models have been widely used for climatic change impact exploration and long-range stream flow forecast. With disparate philosophies and different but insufficient inputs, most of the existing models are capable of generating satisfying outputs, which reveals a relatively robust idiosyncrasy of hydrological pattern over monthly time scale. This research uses the epistemic-aleatory uncertainties evaluation framework to examine the information source sink terms and flows of 6 conceptual monthly water balance models and a seasonal autoregressive stochastic hydrologic model over 19 basins in Jiangxi Province, China and the experiment basins of MOPEX project. By using the stream technique of Lisp, we constructed two programming paradigms into which the hydrological models mentioned above could be fitted. We focus on detecting and explaining the best achievable predictive performances and data-revealed insufficient of the models in each paradigm, especially the hydrological meaning of the iteration variables in these models. Finally, we make an attempt to compare and connect these two paradigms against the backdrop of algorithmic information theory to help us form a better understanding of monthly hydrological pattern.

  15. TUWmodel: an educational hydrologic model in R

    NASA Astrophysics Data System (ADS)

    Parajka, J.; Rogger, M.; Kobler, U.; Salinas, J.; Nester, T.; Bloeschl, G.

    2013-12-01

    In order to show the advantages of using hydrologic models in R environment, particularly for educational purposes, we have implemented a conceptual rainfall-runoff model, originally written in Fortran language into R. This hydrologic model is used in many scientific studies and operational engineering applications in Austria. The model consisting of a snow, a soil moisture and a flow routing routine and run on a daily time step in a lumped or a semi-lumped way. The R environment allows to compile and use this model on different platforms and operating system, taking advantage of many additional routines already available in R (i.e. visualisation or optimisation tools). In this poster we present a set of examples that are used in a graduate level course on engineering hydrology at the Vienna University of Technology, which include: - Multi-objective calibration of the model; - Manual vs. automatic calibration; - Visualisation of model outputs and efficiencies; - Model application in ungauged catchments; - Operational runoff forecast. The flexibility of R is ideal for education, since students can easily play with the extensive list of existing functionalities and define new functions and extensions.

  16. Fuzzy conceptual rainfall runoff models

    NASA Astrophysics Data System (ADS)

    Özelkan, Ertunga C.; Duckstein, Lucien

    2001-11-01

    A fuzzy conceptual rainfall-runoff (CRR) framework is proposed herein to deal with those parameter uncertainties of conceptual rainfall-runoff models, that are related to data and/or model structure: with every element of the rainfall-runoff model assumed to be possibly uncertain, taken here as being fuzzy. First, the conceptual rainfall-runoff system is fuzzified and then different operational modes are formulated using fuzzy rules; second, the parameter identification aspect is examined using fuzzy regression techniques. In particular, bi-objective and tri-objective fuzzy regression models are applied in the case of linear conceptual rainfall-runoff models so that the decision maker may be able to trade off prediction vagueness (uncertainty) and the embedding outliers. For the non-linear models, a fuzzy least squares regression framework is applied to derive the model parameters. The methodology is illustrated using: (1) a linear conceptual rainfall-runoff model; (2) an experimental two-parameter model; and (3) a simplified version of the Sacramento soil moisture accounting model of the US National Weather Services river forecast system (SAC-SMA) known as the six-parameter model. It is shown that the fuzzy logic framework enables the decision maker to gain insight about the model sensitivity and the uncertainty stemming from the elements of the CRR model.

  17. Inverse distributed hydrological modelling of Alpine catchments

    NASA Astrophysics Data System (ADS)

    Kunstmann, H.; Krause, J.; Mayr, S.

    2006-06-01

    Even in physically based distributed hydrological models, various remaining parameters must be estimated for each sub-catchment. This can involve tremendous effort, especially when the number of sub-catchments is large and the applied hydrological model is computationally expensive. Automatic parameter estimation tools can significantly facilitate the calibration process. Hence, we combined the nonlinear parameter estimation tool PEST with the distributed hydrological model WaSiM. PEST is based on the Gauss-Marquardt-Levenberg method, a gradient-based nonlinear parameter estimation algorithm. WaSiM is a fully distributed hydrological model using physically based algorithms for most of the process descriptions. WaSiM was applied to the alpine/prealpine Ammer River catchment (southern Germany, 710 km2 in a 100×100 m2 horizontal resolution. The catchment is heterogeneous in terms of geology, pedology and land use and shows a complex orography (the difference of elevation is around 1600 m). Using the developed PEST-WaSiM interface, the hydrological model was calibrated by comparing simulated and observed runoff at eight gauges for the hydrologic year 1997 and validated for the hydrologic year 1993. For each sub-catchment four parameters had to be calibrated: the recession constants of direct runoff and interflow, the drainage density, and the hydraulic conductivity of the uppermost aquifer. Additionally, five snowmelt specific parameters were adjusted for the entire catchment. Altogether, 37 parameters had to be calibrated. Additional a priori information (e.g. from flood hydrograph analysis) narrowed the parameter space of the solutions and improved the non-uniqueness of the fitted values. A reasonable quality of fit was achieved. Discrepancies between modelled and observed runoff were also due to the small number of meteorological stations and corresponding interpolation artefacts in the orographically complex terrain. Application of a 2-dimensional numerical

  18. eLac - Conceptual Model for Flood Management

    NASA Astrophysics Data System (ADS)

    Rata, Marius; Florentin Draghia, Aurelian; Drobot, Radu; Matreata, Marius; Corbus, Ciprian

    2015-04-01

    This article reviews the conceptual model of the decision support system (DSS) for flood management activities introduced in the scope of e-LAC project. Following the general system architecture which has an emphasize on the water management decision processes, hydrologic and hydraulic models are introduced and discussed according to their specific DSS integration potential. Three directions are discussed in dedicated sections corresponding to the main modules defined in the conceptual model : the Water Basin Management Module (mainly implements the management decision flow, but manages also data exchange between hydrologic modeling module and hydraulic modeling module, allow real time visualization for hydrological data), the Hydrologic Modeling Module (manages all the modeling functionalities of rainfalls - runoff processes, providing continuous hydrologic forecasts with a variable time-step depending on the actual basin situation) and the Hydraulic Modeling Module (computes the flood's waves routing having as boundary upstream conditions the discharge hydrographs, generated both by catchment's upper area, river tributaries and inter-basins, respectively the rating curves, water level hydrograph or water surface slope as downstream condition). The GIS concepts are contextually reviewed based on their use as geospatial database for water management modeling, integration within hydrologic time courses, hydraulic modeling (from both software and management perspective), expert knowledge or mathematical modeling results (knowledge database, rules).

  19. Catchment classification by means of hydrological models

    NASA Astrophysics Data System (ADS)

    Hellebrand, Hugo; Ley, Rita; Casper, Markus

    2013-04-01

    An important hydrological objective is catchment classification that will serve as a basis for the regionalisation of discharge parameters or model parameters. The main task of this study is the development and assessment of two classification approaches with respect to their efficiency in catchment classification. The study area in western Germany comprises about 80 catchments that range in size from 8 km2 up to 1500 km2, covering a wide range of geological substrata, soils, landscapes and mean annual precipitation. In a first approach Self Organising Maps (SOMs) use discharge characteristics or catchment characteristics to classify the catchments of the study area. Next, a reference hydrological model calibrates the catchments of the study area and tests the possibilities of parameter transfer. Compared to the transfer of parameters outside a class, for most catchments the model performance improves when parameters within a class are transferred. Thus, it should be possible to distinguish catchment classes by means of a hydrological model. The classification results of the SOM are compared to the classification results of the reference hydrological model in order to determine the latter validity. The second approach builds on the first approach in such a way that it uses the Superflex Modelling Framework instead of only one reference model. Within this framework multiple conceptual model structures can be calibrated and adapted. Input data for each calibration of a catchment are hourly time series of runoff, precipitation and evaporation for at least eight years. The calibration of multiple models for each catchment and their comparison allows for the assessment of the influence of different model structures on model performance. Learning loops analyse model performance and adapt model structures accordingly with a view to performance improvement. The result of the modelling exercise is a best performing model structure for each catchment that serves as a basis

  20. Uses and limitations of the soil survey in hydrologic modeling

    NASA Astrophysics Data System (ADS)

    Brooks, E.; Boll, J.

    2009-12-01

    One of the greatest challenges in hydrologic modeling is characterizing the effects of soil structure of hydrologic flow paths in complex watersheds. The Predictions in Ungauged Basins (PUB) initiative is pushing scientists to come up with innovative ways to reduce model calibration and predictive uncertainty and improve process understanding. Some of these innovative approaches have included incorporating ‘soft data’ as information for developing conceptual watershed frameworks and guiding calibration. In this study we examine the uses and limitations of the soil survey in hydrologic modeling. County soil surveys were initiated in 1899 and now digital maps are available throughout most of the US. Although these surveys were initially meant to guide selection and development of land, these surveys now include a great wealth of information from specific physical properties to indicators of saturation and development of perched water tables. To what degree does the information in the soil survey improve understanding of dominant hydrologic processes in a watershed? At what point must a hydrologist exercise discretion in using this information? We will discuss the extent to which the soil survey can be used to 1.) conceptualize the basic hydrology of a watershed, 2.) provide input data to a process-based hydrologic model, and 3.) validate spatial predictions of runoff and erosion from distributed hydrologic models. We will demonstrate each of these uses through case studies from multiple ecological regions across the country.

  1. Analysis of Streamflow Predictive Uncertainty using Multiple Hydrologic Models in Climate Change Impact Study

    NASA Astrophysics Data System (ADS)

    Yang, P.; Najafi, M.; Moradkhani, H.

    2010-12-01

    Based on the statistically downscaled outputs from 8 global climate model projections and 2 emission scenarios we assess the uncertainties associated with GCMs and hydrologic models by means of multi-modeling. As there is no conceivable reason that any hydrologic model is performing better under all circumstances, four hydrologic models are selected for the hydrologic impact study: the Sacramento Soil Moisture Accounting (SAC-SMA) model, Conceptual HYdrologic MODel (HYMOD), Thornthwaite-Mather model (TM) and the Precipitation Runoff Modeling System (PRMS). Three objective functions are adopted to calibrate each model. The hydrologic model simulations are combined using the Bayesian Model Averaging (BMA) method. This study shows that the application of the BMA in analyzing the models ensemble is useful in minimizing the uncertainty in selecting the hydrologic model selection. It is also concluded that the hydrologic model uncertainty is considerably smaller than GCM uncertainty, except during the dry season.

  2. Grid-Xinanjiang Distributed Hydrologic Model

    NASA Astrophysics Data System (ADS)

    Li, Z.; Yao, C.; Yu, Z.

    2009-12-01

    The grid-based distributed Xinanjiang (Grid-Xinanjiang) model by combining the well-tested conceptual rainfall-runoff model and the physically based flow routing model has been developed for hydrologic processes simulation and flood forecasting. The DEM is utilized to derive the flow direction, routing sequencing, hillslope and channel slopes. The developed model includes canopy interception, direct channel precipitation, evapotranspiration, as well as runoff generation via saturation excess mechanism. The diffusion wave considering the influent of upstream inflow, direct channel precipitation and flow partition to the channels is developed to route the hillslope and channel flow on a cell basis. The Grid-Xinanjiang model is applied at a 1-km grid scale in a nested basin located in Huaihe basin, China. The basin with the drainage area of 2692.7 km2, contains five internal points where observed streamflow data are available, and is used to evaluate the developed model for its’ ability on the simulation of hydrologic processes within the basin. Calibration and verification of the Grid-Xinanjiang model are carried out at both daily and hourly time steps. The model is assessed by comparing streamflow and water stage simulation to observations at the basin outlet and gauging stations within the basin and also compared with these simulated with the original Xinanjiang model. The results indicate that the parameter estimation approach is efficient and the developed model can forecast the streamflow and stage hydrograph well.

  3. Conceptual models of information processing

    NASA Technical Reports Server (NTRS)

    Stewart, L. J.

    1983-01-01

    The conceptual information processing issues are examined. Human information processing is defined as an active cognitive process that is analogous to a system. It is the flow and transformation of information within a human. The human is viewed as an active information seeker who is constantly receiving, processing, and acting upon the surrounding environmental stimuli. Human information processing models are conceptual representations of cognitive behaviors. Models of information processing are useful in representing the different theoretical positions and in attempting to define the limits and capabilities of human memory. It is concluded that an understanding of conceptual human information processing models and their applications to systems design leads to a better human factors approach.

  4. Conceptual and Numerical Models for UZ Flow and Transport

    SciTech Connect

    H. Liu

    2000-03-03

    The purpose of this Analysis/Model Report (AMR) is to document the conceptual and numerical models used for modeling of unsaturated zone (UZ) fluid (water and air) flow and solute transport processes. This is in accordance with ''AMR Development Plan for U0030 Conceptual and Numerical Models for Unsaturated Zone (UZ) Flow and Transport Processes, Rev 00''. The conceptual and numerical modeling approaches described in this AMR are used for models of UZ flow and transport in fractured, unsaturated rock under ambient and thermal conditions, which are documented in separate AMRs. This AMR supports the UZ Flow and Transport Process Model Report (PMR), the Near Field Environment PMR, and the following models: Calibrated Properties Model; UZ Flow Models and Submodels; Mountain-Scale Coupled Processes Model; Thermal-Hydrologic-Chemical (THC) Seepage Model; Drift Scale Test (DST) THC Model; Seepage Model for Performance Assessment (PA); and UZ Radionuclide Transport Models.

  5. Complexity of groundwater models in catchment hydrological models

    NASA Astrophysics Data System (ADS)

    Attinger, Sabine; Herold, Christian; Kumar, Rohini; Mai, Juliane; Ross, Katharina; Samaniego, Luis; Zink, Matthias

    2015-04-01

    In catchment hydrological models, groundwater is usually modeled very simple: it is conceptualized as a linear reservoir that gets the water from the upper unsaturated zone reservoir and releases water to the river system as baseflow. The baseflow is only a minor component of the total river flow and groundwater reservoir parameters are therefore difficult to be inversely estimated by means of river flow data only. In addition, the modelled values of the absolute height of the water filling the groundwater reservoir - in other words the groundwater levels - are of limited meaning due to coarse or no spatial resolution of groundwater and due to the fact that only river flow data are used for the calibration. The talk focuses on the question: Which complexity in terms of model complexity and model resolution is necessary to characterize groundwater processes and groundwater responses adequately in distributed catchment hydrological models? Starting from a spatially distributed catchment hydrological model with a groundwater compartment that is conceptualized as a linear reservoir we stepwise increase the groundwater model complexity and its spatial resolution to investigate which resolution, which complexity and which data are needed to reproduce baseflow and groundwater level data adequately.

  6. Model Breaking Points Conceptualized

    ERIC Educational Resources Information Center

    Vig, Rozy; Murray, Eileen; Star, Jon R.

    2014-01-01

    Current curriculum initiatives (e.g., National Governors Association Center for Best Practices and Council of Chief State School Officers 2010) advocate that models be used in the mathematics classroom. However, despite their apparent promise, there comes a point when models break, a point in the mathematical problem space where the model cannot,…

  7. Play with hydrologic models in R

    NASA Astrophysics Data System (ADS)

    Viglione, A.; Parajka, J.; Nester, T.; Blöschl, G.

    2012-04-01

    The aim of this poster is to show the advantages of building hydrologic models using the R environment for educational purposes. As an example we consider a conceptual rainfall-runoff model (HBV type) that was originally written in the fortran language and is used in many scientific studies and practical engineering applications in Austria. A simplified version of the model was built into a R package and compiled for different platforms and operating systems. The model runs on a daily time step and consists of a snow routine, a soil moisture routine and a flow routing routine. In this poster we present a set of examples that have been used in a graduate level course on engineering hydrology at the Vienna University of Technology. These include: - Multi-objective calibration of the model; - Manual vs. automatic calibration; - Visualisation of model outputs and efficiency; - Model application in ungauged catchments; - Operational forecast. The flexibility of R is ideal for education, since students can easily play with the extensive list of existing functionalities and define new functions and extensions.

  8. Conceptualizing socio-hydrological drought processes: the rise and fall of the Ancient Maya civilization

    NASA Astrophysics Data System (ADS)

    Kuil, Linda; Carr, Gemma; Viglione, Alberto; Prskawetz, Alexia; Bloeschl, Guenter

    2016-04-01

    Different communities have followed different paths to arrive at their present situation as a consequence of the continuous, specific interactions between the hydrological and social system. The need to understand the current and future pathways to water security becomes more and more pressing, considering the increasingly delicate balance between water demand and water supply. To contribute to addressing this challenge, we examine the link between water stress and society through socio-hydrological modeling. Within the spirit of the Easter Island model by Brander and Taylor and drawing from the vulnerability literature, we conceptualize the interactions of an agricultural society with its environment. We apply the model to the case of the ancient Maya, a civilization who occupied the Maya Lowlands (parts of present day Mexico, Guatemala, Belize) from around 2000 BC to after AD 830. The hypothesis that modest drought periods played a major role in the fall of the society is explored. We are able to simulate plausible feedbacks and find that a modest reduction in rainfall is a necessary, but not a sufficient condition in order to observe a collapse of 80 percent of the population. Equally important are actual population density and the impact of drought on crop growth. The model shows that reservoirs allow the society to grow larger, but also that the vulnerability to drought increases.

  9. Hydrological modelling of urbanized catchments: A review and future directions

    NASA Astrophysics Data System (ADS)

    Salvadore, Elga; Bronders, Jan; Batelaan, Okke

    2015-10-01

    In recent years, the conceptual detail of hydrological models has dramatically increased as a result of improved computational techniques and the availability of spatially-distributed digital data. Nevertheless modelling spatially-distributed hydrological processes can be challenging, particularly in strongly heterogeneous urbanized areas. Multiple interactions occur between urban structures and the water system at various temporal and spatial scales. So far, no universal methodology exists for simulating the urban water system at catchment scale. This paper reviews the state of the art on the scientific knowledge and practice of modelling the urban hydrological system at the catchment scale, with the purpose of identifying current limitations and defining a blueprint for future modelling advances. We compare conceptual descriptions of urban physical hydrological processes on basis of a selection of 43 modelling approaches. The complexity of the urban water system at the catchment scale results in an incomplete understanding of the interaction between urban and natural hydrological systems, and in a high degree of uncertainty. Data availability is still a strong limitation since current modelling practice recognizes the need for high spatial and temporal resolution. Spatio-temporal gaps exist between the physical scales of hydrological processes and the resolution of applied models. Therefore urban hydrology is often simplified either as a study of surface runoff over impervious surfaces or hydraulics of piped systems. Many approaches target very specific objectives and the level of detail in representing physical processes is not consistent. Based on our analysis, we propose a blueprint for a highly complex integrated urban hydrological model. We regard flexibility, in terms of model structure and data assimilation, as the key characteristic for overcoming these limitations. We advocate the use of modular, process-based approaches, which are flexible and adaptable

  10. 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

  11. Conceptual dynamical models for turbulence.

    PubMed

    Majda, Andrew J; Lee, Yoonsang

    2014-05-01

    Understanding the complexity of anisotropic turbulent processes in engineering and environmental fluid flows is a formidable challenge with practical significance because energy often flows intermittently from the smaller scales to impact the largest scales in these flows. Conceptual dynamical models for anisotropic turbulence are introduced and developed here which, despite their simplicity, capture key features of vastly more complicated turbulent systems. These conceptual models involve a large-scale mean flow and turbulent fluctuations on a variety of spatial scales with energy-conserving wave-mean-flow interactions as well as stochastic forcing of the fluctuations. Numerical experiments with a six-dimensional conceptual dynamical model confirm that these models capture key statistical features of vastly more complex anisotropic turbulent systems in a qualitative fashion. These features include chaotic statistical behavior of the mean flow with a sub-Gaussian probability distribution function (pdf) for its fluctuations whereas the turbulent fluctuations have decreasing energy and correlation times at smaller scales, with nearly Gaussian pdfs for the large-scale fluctuations and fat-tailed non-Gaussian pdfs for the smaller-scale fluctuations. This last feature is a manifestation of intermittency of the small-scale fluctuations where turbulent modes with small variance have relatively frequent extreme events which directly impact the mean flow. The dynamical models introduced here potentially provide a useful test bed for algorithms for prediction, uncertainty quantification, and data assimilation for anisotropic turbulent systems. PMID:24753605

  12. Conceptual dynamical models for turbulence

    PubMed Central

    Majda, Andrew J.; Lee, Yoonsang

    2014-01-01

    Understanding the complexity of anisotropic turbulent processes in engineering and environmental fluid flows is a formidable challenge with practical significance because energy often flows intermittently from the smaller scales to impact the largest scales in these flows. Conceptual dynamical models for anisotropic turbulence are introduced and developed here which, despite their simplicity, capture key features of vastly more complicated turbulent systems. These conceptual models involve a large-scale mean flow and turbulent fluctuations on a variety of spatial scales with energy-conserving wave–mean-flow interactions as well as stochastic forcing of the fluctuations. Numerical experiments with a six-dimensional conceptual dynamical model confirm that these models capture key statistical features of vastly more complex anisotropic turbulent systems in a qualitative fashion. These features include chaotic statistical behavior of the mean flow with a sub-Gaussian probability distribution function (pdf) for its fluctuations whereas the turbulent fluctuations have decreasing energy and correlation times at smaller scales, with nearly Gaussian pdfs for the large-scale fluctuations and fat-tailed non-Gaussian pdfs for the smaller-scale fluctuations. This last feature is a manifestation of intermittency of the small-scale fluctuations where turbulent modes with small variance have relatively frequent extreme events which directly impact the mean flow. The dynamical models introduced here potentially provide a useful test bed for algorithms for prediction, uncertainty quantification, and data assimilation for anisotropic turbulent systems. PMID:24753605

  13. CONCEPTUAL MODELS FOR WATERSHED AND REGIONAL ASSESSMENTS

    EPA Science Inventory

    Conceptual models, as defined here, describe and illustrate the relationships between ecological receptors, the stressors to which they may be exposed, and the potential sources of the those stressors within a particular area or ecosystem. This document describes conceptual model...

  14. A physical interpretation of hydrologic model complexity

    NASA Astrophysics Data System (ADS)

    Moayeri, MohamadMehdi; Pande, Saket

    2015-04-01

    It is intuitive that instability of hydrological system representation, in the sense of how perturbations in input forcings translate into perturbation in a hydrologic response, may depend on its hydrological characteristics. Responses of unstable systems are thus complex to model. We interpret complexity in this context and define complexity as a measure of instability in hydrological system representation. We provide algorithms to quantify model complexity in this context. We use Sacramento soil moisture accounting model (SAC-SMA) parameterized for MOPEX basins and quantify complexities of corresponding models. Relationships between hydrologic characteristics of MOPEX basins such as location, precipitation seasonality index, slope, hydrologic ratios, saturated hydraulic conductivity and NDVI and respective model complexities are then investigated. We hypothesize that complexities of basin specific SAC-SMA models correspond to aforementioned hydrologic characteristics, thereby suggesting that model complexity, in the context presented here, may have a physical interpretation.

  15. Attribution of hydrologic trends using integrated hydrologic and economic models

    NASA Astrophysics Data System (ADS)

    Maneta, M. P.; Brugger, D. R.; Silverman, N. L.

    2014-12-01

    Hydrologic change has been detected in many regions of the world in the form of trends in annual streamflows, varying depths to the regional water table, or other alterations of the hydrologic balance. Most models used to investigate these changes implement sophisticated descriptions of the physical system but use simplified descriptions of the socioeconomic system. These simplifications come in the form of prescribed water diversions and land use change scenarios, which provide little insight into coupled natural-human systems and have limited predictive capabilities. We present an integrated model that adds realism to the description of the hydrologic system in agricultural regions by incorporating a component that updates the allocation of land and water to crops in response to hydroclimatic (water available) and economic conditions (prices of commodities and agricultural inputs). This component assumes that farmers allocate resources to maximize their net revenues, thus justifying the use of optimality conditions to constrain the parameters of an empirical production function that captures the economic behavior of farmers. Because the model internalizes the feedback between climate, agricultural markets, and farming activity into the hydrologic system, it can be used to understand to what extent human economic activity can exacerbate or buffer the regional hydrologic impacts of climate change in agricultural regions. It can also help in the attribution of causes of hydrologic change. These are important issues because local policy and management cannot solve climate change, but they can address land use and agricultural water use. We demonstrate the model in a case study.

  16. Conceptual Models for Search Engines

    NASA Astrophysics Data System (ADS)

    Hendry, D. G.; Efthimiadis, E. N.

    Search engines have entered popular culture. They touch people in diverse private and public settings and thus heighten the importance of such important social matters as information privacy and control, censorship, and equitable access. To fully benefit from search engines and to participate in debate about their merits, people necessarily appeal to their understandings for how they function. In this chapter we examine the conceptual understandings that people have of search engines by performing a content analysis on the sketches that 200 undergraduate and graduate students drew when asked to draw a sketch of how a search engine works. Analysis of the sketches reveals a diverse range of conceptual approaches, metaphors, representations, and misconceptions. On the whole, the conceptual models articulated by these students are simplistic. However, students with higher levels of academic achievement sketched more complete models. This research calls attention to the importance of improving students' technical knowledge of how search engines work so they can be better equipped to develop and advocate policies for how search engines should be embedded in, and restricted from, various private and public information settings.

  17. A conceptual, distributed snow redistribution model

    NASA Astrophysics Data System (ADS)

    Frey, S.; Holzmann, H.

    2015-11-01

    When applying conceptual hydrological models using a temperature index approach for snowmelt to high alpine areas often accumulation of snow during several years can be observed. Some of the reasons why these "snow towers" do not exist in nature are vertical and lateral transport processes. While snow transport models have been developed using grid cell sizes of tens to hundreds of square metres and have been applied in several catchments, no model exists using coarser cell sizes of 1 km2, which is a common resolution for meso- and large-scale hydrologic modelling (hundreds to thousands of square kilometres). In this paper we present an approach that uses only gravity and snow density as a proxy for the age of the snow cover and land-use information to redistribute snow in alpine basins. The results are based on the hydrological modelling of the Austrian Inn Basin in Tyrol, Austria, more specifically the Ötztaler Ache catchment, but the findings hold for other tributaries of the river Inn. This transport model is implemented in the distributed rainfall-runoff model COSERO (Continuous Semi-distributed Runoff). The results of both model concepts with and without consideration of lateral snow redistribution are compared against observed discharge and snow-covered areas derived from MODIS satellite images. By means of the snow redistribution concept, snow accumulation over several years can be prevented and the snow depletion curve compared with MODIS (Moderate Resolution Imaging Spectroradiometer) data could be improved, too. In a 7-year period the standard model would lead to snow accumulation of approximately 2900 mm SWE (snow water equivalent) in high elevated regions whereas the updated version of the model does not show accumulation and does also predict discharge with more accuracy leading to a Kling-Gupta efficiency of 0.93 instead of 0.9. A further improvement can be shown in the comparison of MODIS snow cover data and the calculated depletion curve, where

  18. 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.

  19. Towards methodical modelling: Differences between the structure and output dynamics of multiple conceptual models

    NASA Astrophysics Data System (ADS)

    Knoben, Wouter; Woods, Ross; Freer, Jim

    2016-04-01

    Conceptual hydrologic models consist of a certain arrangement of spatial and temporal dynamics consisting of stores, fluxes and transformation functions, depending on the modeller's choices and intended use. They have the advantages of being computationally efficient, being relatively easy model structures to reconfigure and having relatively low input data demands. This makes them well-suited for large-scale and large-sample hydrology, where appropriately representing the dominant hydrologic functions of a catchment is a main concern. Given these requirements, the number of parameters in the model cannot be too high, to avoid equifinality and identifiability issues. This limits the number and level of complexity of dominant hydrologic processes the model can represent. Specific purposes and places thus require a specific model and this has led to an abundance of conceptual hydrologic models. No structured overview of these models exists and there is no clear method to select appropriate model structures for different catchments. This study is a first step towards creating an overview of the elements that make up conceptual models, which may later assist a modeller in finding an appropriate model structure for a given catchment. To this end, this study brings together over 30 past and present conceptual models. The reviewed model structures are simply different configurations of three basic model elements (stores, fluxes and transformation functions), depending on the hydrologic processes the models are intended to represent. Differences also exist in the inner workings of the stores, fluxes and transformations, i.e. the mathematical formulations that describe each model element's intended behaviour. We investigate the hypothesis that different model structures can produce similar behavioural simulations. This can clarify the overview of model elements by grouping elements which are similar, which can improve model structure selection.

  20. 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.

  1. toolkit computational mesh conceptual model.

    SciTech Connect

    Baur, David G.; Edwards, Harold Carter; Cochran, William K.; Williams, Alan B.; Sjaardema, Gregory D.

    2010-03-01

    The Sierra Toolkit computational mesh is a software library intended to support massively parallel multi-physics computations on dynamically changing unstructured meshes. This domain of intended use is inherently complex due to distributed memory parallelism, parallel scalability, heterogeneity of physics, heterogeneous discretization of an unstructured mesh, and runtime adaptation of the mesh. Management of this inherent complexity begins with a conceptual analysis and modeling of this domain of intended use; i.e., development of a domain model. The Sierra Toolkit computational mesh software library is designed and implemented based upon this domain model. Software developers using, maintaining, or extending the Sierra Toolkit computational mesh library must be familiar with the concepts/domain model presented in this report.

  2. Ensemble evaluation of hydrological model hypotheses

    NASA Astrophysics Data System (ADS)

    Krueger, Tobias; Freer, Jim; Quinton, John N.; MacLeod, Christopher J. A.; Bilotta, Gary S.; Brazier, Richard E.; Butler, Patricia; Haygarth, Philip M.

    2010-07-01

    It is demonstrated for the first time how model parameter, structural and data uncertainties can be accounted for explicitly and simultaneously within the Generalized Likelihood Uncertainty Estimation (GLUE) methodology. As an example application, 72 variants of a single soil moisture accounting store are tested as simplified hypotheses of runoff generation at six experimental grassland field-scale lysimeters through model rejection and a novel diagnostic scheme. The fields, designed as replicates, exhibit different hydrological behaviors which yield different model performances. For fields with low initial discharge levels at the beginning of events, the conceptual stores considered reach their limit of applicability. Conversely, one of the fields yielding more discharge than the others, but having larger data gaps, allows for greater flexibility in the choice of model structures. As a model learning exercise, the study points to a "leaking" of the fields not evident from previous field experiments. It is discussed how understanding observational uncertainties and incorporating these into model diagnostics can help appreciate the scale of model structural error.

  3. A visual interface for the SUPERFLEX hydrological modelling framework

    NASA Astrophysics Data System (ADS)

    Gao, H.; Fenicia, F.; Kavetski, D.; Savenije, H. H. G.

    2012-04-01

    The SUPERFLEX framework is a modular modelling system for conceptual hydrological modelling at the catchment scale. This work reports the development of a visual interface for the SUPERFLEX model. This aims to enhance the communication between the hydrologic experimentalists and modelers, in particular further bridging the gap between the field soft data and the modeler's knowledge. In collaboration with field experimentalists, modelers can visually and intuitively hypothesize different model architectures and combinations of reservoirs, select from a library of constructive functions to describe the relationship between reservoirs' storage and discharge, specify the shape of lag functions and, finally, set parameter values. The software helps hydrologists take advantage of any existing insights into the study site, translate it into a conceptual hydrological model and implement it within a computationally robust algorithm. This tool also helps challenge and contrast competing paradigms such as the "uniqueness of place" vs "one model fits all". Using this interface, hydrologists can test different hypotheses and model representations, and stepwise build deeper understanding of the watershed of interest.

  4. 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

  5. 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.

  6. Application of hydrologic forecast model.

    PubMed

    Hua, Xu; Hengxin, Xue; Zhiguo, Chen

    2012-01-01

    In order to overcome the shortcoming of the solution may be trapped into the local minimization in the traditional TSK (Takagi-Sugeno-Kang) fuzzy inference training, this paper attempts to consider the TSK fuzzy system modeling approach based on the visual system principle and the Weber law. This approach not only utilizes the strong capability of identifying objects of human eyes, but also considers the distribution structure of the training data set in parameter regulation. In order to overcome the shortcoming of it adopting the gradient learning algorithm with slow convergence rate, a novel visual TSK fuzzy system model based on evolutional learning is proposed by introducing the particle swarm optimization algorithm. The main advantage of this method lies in its very good optimization, very strong noise immunity and very good interpretability. The new method is applied to long-term hydrological forecasting examples. The simulation results show that the method is feasible and effective, the new method not only inherits the advantages of traditional visual TSK fuzzy models but also has the better global convergence and accuracy than the traditional model. PMID:22699326

  7. A Conceptual Data Model of Datum Systems

    PubMed Central

    McCaleb, Michael R.

    1999-01-01

    A new conceptual data model that addresses the geometric dimensioning and tolerancing concepts of datum systems, datums, datum features, datum targets, and the relationships among these concepts, is presented. Additionally, a portion of a related data model, Part 47 of STEP (ISO 10303-47), is reviewed and a comparison is made between it and the new conceptual data model.

  8. Test plan for hydrologic modeling of protective barriers

    SciTech Connect

    Fayer, M.J.

    1990-03-01

    Pacific Northwest Laboratory prepared this test plan for the Model Applications and Validation Task of the Hanford Protective Barriers Program, which is managed by Westinghouse Hanford Company. The objectives of this plan are to outline the conceptual hydrologic model of protective barriers, discuss the available computer codes, describe the interrelationships between the modeling task and the other tasks of the Protective Barriers Program, present the barrier modeling tests, and estimate the schedule and costs of the hydrologic modeling task for planning purposes by the Protective Barriers Program. The purpose of the tests is to validate models that will be used to confirm the long-term performance of the barrier in minimizing drainage. A second purpose of the tests is to provide information to other parts of the Protective Barriers Program that require such information. 26 refs., 2 figs., 3 tabs.

  9. 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

  10. Conceptual and logical level of database modeling

    NASA Astrophysics Data System (ADS)

    Hunka, Frantisek; Matula, Jiri

    2016-06-01

    Conceptual and logical levels form the top most levels of database modeling. Usually, ORM (Object Role Modeling) and ER diagrams are utilized to capture the corresponding schema. The final aim of business process modeling is to store its results in the form of database solution. For this reason, value oriented business process modeling which utilizes ER diagram to express the modeling entities and relationships between them are used. However, ER diagrams form the logical level of database schema. To extend possibilities of different business process modeling methodologies, the conceptual level of database modeling is needed. The paper deals with the REA value modeling approach to business process modeling using ER-diagrams, and derives conceptual model utilizing ORM modeling approach. Conceptual model extends possibilities for value modeling to other business modeling approaches.

  11. Geographically isolated wetlands and watershed hydrology: A modified model analysis

    NASA Astrophysics Data System (ADS)

    Evenson, Grey R.; Golden, Heather E.; Lane, Charles R.; D'Amico, Ellen

    2015-10-01

    Geographically isolated wetlands (GIWs) are defined as wetlands that are completely surrounded by uplands. While GIWs are therefore spatially isolated, field-based studies have observed a continuum of hydrologic connections between these systems and other surface waters. Yet few studies have quantified the watershed-scale aggregate effects of GIWs on downstream hydrology. Further, existing modeling approaches to evaluate GIW effects at a watershed scale have utilized conceptual or spatially disaggregated wetland representations. Working towards wetland model representations that use spatially explicit approaches may improve current scientific understanding concerning GIW effects on the downstream hydrograph. The objective of this study was to quantify the watershed-scale aggregate effects of GIWs on downstream hydrology while emphasizing a spatially explicit representation of GIWs and GIW connectivity relationships. We constructed a hydrologic model for a ∼202 km2 watershed in the Coastal Plain of North Carolina, USA, a watershed with a substantial population of GIWs, using the Soil and Water Assessment Tool (SWAT). We applied a novel representation of GIWs within the model, facilitated by an alternative hydrologic response unit (HRU) definition and modifications to the SWAT source code that extended the model's "pothole" representation. We then executed a series of scenarios to assess the downstream hydrologic effect of various distributions of GIWs within the watershed. Results suggest that: (1) GIWs have seasonally dependent effects on baseflow; (2) GIWs mitigate peak flows; and (3) The presence of GIWs on the landscape impacts the watershed water balance. This work demonstrates a means of GIW simulation with improved spatial detail while showing that GIWs, in-aggregate, have a substantial effect on downstream hydrology in the studied watershed.

  12. 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).

  13. RECURSIVE PARAMETER ESTIMATION OF HYDROLOGIC MODELS

    EPA Science Inventory

    Proposed is a nonlinear filtering approach to recursive parameter estimation of conceptual watershed response models in state-space form. he conceptual model state is augmented by the vector of free parameters which are to be estimated from input-output data, and the extended Kal...

  14. Snow Hydrology in a General Circulation Model.

    NASA Astrophysics Data System (ADS)

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

    1994-08-01

    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 snow pack. 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.

  15. 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.

  16. Impact of the use of two different hydrological models on scores of hydrological ensemble forecasts

    NASA Astrophysics Data System (ADS)

    Ramos, M. H.; Thirel, G.; Andréassian, V.; Martin, E.

    2009-04-01

    The aim of this study is two-fold. Firstly, a comparative analysis is conducted to assess the quality of streamflow forecasts issued by two different modelling conceptualizations of catchment response, both driven by the same weather ensemble prediction system. Secondly, the results are jointly investigated with a view to providing guidance on the operational use of ensemble forecast products for flood warning at national hydrologic forecasting services. The study is based on weather forecasts from the ensemble prediction system PEARP of Météo-France, which was originally developed to better predict high impact storms in France. PEARP forecasts are based on the global spectral ARPEGE model zoomed over France. Initial perturbations are generated by the singular vector technique. The model runs 11 perturbed members for a forecast range of 60 hours. In this study, the two hydrological modelling approaches used are: 1) the coupled physically-based hydro-meteorological model SAFRAN-ISBA-MODCOU developed at Météo-France and based on a fully distributed catchment model, and 2) the GRPE forecasting system developed at Cemagref and based on a lumped soil-moisture-accounting type rainfall-runoff model. Both models were set up and tested on about 1000 catchments in France. For this study, a common subset of about 250 gauging stations representative of a wide range of upstream areas and hydro-meteorological conditions was selected. The discharges simulated by both systems are compared over an 18-month period (March 2005-September 2006). Skill scores are then computed for the first two days of forecast range and the performance of both hydrologic ensemble forecasting systems is assessed. The results of this experiment are examined with a focus on the setting up of a fully operational product in real-time hydrological forecasting. The combined use of forecasts issued by different systems is a demand of French operational forecasting service to better guide flood warning

  17. What have we learned by applying the data driven modelling techniques in the field of hydrological modelling?

    NASA Astrophysics Data System (ADS)

    Stravs, Luka; Brilly, Mitja

    2010-05-01

    Hydrologic data analysis and hydrologic modelling have become major techniques in hydrology and are used for building hydrologic models to generate synthetic hydrologic records, to forecast hydrologic events, to detect trends and shifts in hydrologic records and to fill in missing data and extend the data sets. Well known, praised and widely used are the so-called conceptual models that are based on the prior theoretical knowledge of all the hydrological processes in the form of theoretically developed or empirically derived equations. A modeller needs a lot of detailed data like river network, land cover, soil characteristics and other geographical data or topographical maps to sucessfully calibrate a conceptual model. The availability of all of the aforementioned data can present quite a significant problem in the process of modelling. On the basis of different approaches to the inclusion of geographical, topographical and other data in conceptual models, we distinguish between distributed, semi-distributed and lumped conceptual models. Empirical, mostly black box models simply connecting input and output hydrolgical data have also been widely used in the field of hydrology, especially in the hydrological praxis. Data driven modelling on the other hand is based on the analysis of the data characterising the system being modelled, which in most cases means finding the best type of model or combination of those to connect the input and output data characterising the system being modelled, while the assumptions or learning about the physical bases of the system being modelled are not the top priority. Also, there is still a lot of scepticism among many hydrologists regarding the usage of data driven modelling techniques in hydrology, because the development of the models from the data is usually seen as a computational exercise and is not related to physical principles and mathematical reasoning. This presentation will give a quick overview of more and less

  18. Conceptual Model of the Klamath Falls, Oregon Geothermal Area

    SciTech Connect

    Prucha, R.H.; Benson, S.M.; Witherspoon, P.A.

    1987-01-20

    Over the last 50 years significant amounts of data have been obtained from the Klamath Falls geothermal resource. To date, the complexity of the system has stymied researchers, leading to the development of only very generalized hydrogeologic and geothermal models of the area. Recently, the large quantity of available temperature data have been re-evaluated, revealing new information on subsurface heat flow and locations of faults in the system. These inferences are supported by borehole, geochemical, geophysical, and hydrologic data. Based on re-evaluation of all available data, a detailed conceptual model for the Klamath Falls geothermal resource is proposed. 1 tab., 8 figs., 21 refs.

  19. Conceptual model of the Klamath Falls, Oregon geothermal area

    SciTech Connect

    Prucha, R.H.; Benson, S.M.; Witherspoon, P.A.

    1987-01-01

    Over the last 50 years significant amounts of data have been obtained from the Klamath Falls geothermal resource. To date, the complexity of the system has stymied researchers, leading to the development of only very generalized hydrogeologic and geothermal models of the area. Recently, the large quantity of available temperature data have been re-evaluated, revealing new information on subsurface heat flow and locations of faults in the system. These inferences are supported by borehole, geochemical, geophysical, and hydrologic data. Based on re-evaluation of all available data, a detailed conceptual model for the Klamath Falls geothermal resource is proposed.

  20. Data Mining of Hydrological Model Performances

    NASA Astrophysics Data System (ADS)

    Vitolo, Claudia; Buytaert, Wouter

    2013-04-01

    Multi-objective criteria have long been used to infer hydrological simulations and fit the natural world. On the other hand, modelling frameworks are also becoming more and more popular as identification of the processes occurring in a catchment is still a very uncertain matter. In theory, multi-objective criteria and multi-model frameworks should be used in combination so that the 'representation' of the catchment is fitted to the observations, not only the simulated results. In practise those approaches are highly computationally demanding. The modeller is often obliged to find a compromise reducing either the number of objective functions or model structures taken into consideration. This compromise is becoming obsolete using parallel computing. In the present study we investigate the extend to which model selection algorithms and regionalisation techniques can be improved by such facilities and highlight the challenges that still need to be addressed. The model simulations are obtained using an ensemble of conceptual lumped models (FUSE by Clark et al. 2008), but techniques and suggestions are of general use and applicable to any modelling frameworks. In particular we developed a novel model selection algorithm tuned to drastically reduce the subjectivity in the analysis. The procedure was automated and coupled with redundancy reduction techniques such as PCA and Cluster Analysis. Results show that the actual model 'representation' has the shape of a set of complementing model structures. It is also possible to capture intra-annum dynamics of the response as the algorithm recognises subtle variations in the selected model structures in different seasons. Similar variations can be found analysing different catchments. This suggests the same methodology would be suitable for analysing spatial patterns in the distribution of suitable model structures and maybe long term dynamics in relation with expedited climate modifications. Although the mentioned methodology

  1. Inter-comparison of subglacial hydrological models

    NASA Astrophysics Data System (ADS)

    de Fleurian, Basile; Werder, Mauro

    2016-04-01

    The recent emergence of a number of subglacial hydrological models allows us to obtain theoretical insights on basal processes; for instance on the coupling between water pressure and the sliding of glaciers. In ice-flow models, it is relatively clear what the simulated physics ought to be. Conversely, the physical processes incorporated into subglacial hydrology models are diverse as it is yet unclear which ones are of relevance for a particular setting. An inter-comparison of hydrology models will therefore need a somewhat different approach to the one used in the many ice-flow model inter-comparisons (EISMINT, ISMIP, etc.). Here, we present a set of experiments that will allow the comparison of the behavior of different hydrology models. The design of the benchmark aims at allowing the participation of a wide range of models based on different physical approaches. We aim at evaluating the models with a focus on the effective pressure which has the most impact on the dynamics of glaciers. The aim of this inter-comparison is to provide modellers with the necessary data to make an informed decision on which subglacial hydrology model to use for a particular study.

  2. Accelerating advances in continental domain hydrologic modeling

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

    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.

  3. Uncertainty of the hydrological response to climate change conditions; 605 basins, 3 hydrological models, 5 climate models, 5 hydrological variables

    NASA Astrophysics Data System (ADS)

    Melsen, Lieke; Mizukami, Naoki; Newman, Andrew; Clark, Martyn; Teuling, Adriaan

    2016-04-01

    Many studies investigated the effect of a changing climate on the hydrological response of a catchment and uncertainty of the effect coming from hydrologic modelling (e.g., forcing, hydrologic model structures, and parameters). However, most past studies used only a single or a small number of catchments. To go beyond the case-study, and to assess the uncertainty involved in modelling the hydrological impact of climate change more comprehensively, we studied 605 basins over a wide range of climate regimes throughout the contiguous USA. We used three different widely-used hydrological models (VIC, HBV, SAC), which we forced with five distinct climate model outputs. The hydrological models have been run for a base period (1986-2008) for which observations were available, and for a future period (2070-2099). Instead of calibrating each hydrological model for each basin, the model has been run with a parameter sample (varying from 1600 to 1900 samples dependent on the number of free parameters in the model). Five hydrological states and fluxes were stored; discharge, evapotranspiration, soil moisture, SWE and snow melt, and 15 different metrics and signatures have been obtained for each model run. With the results, we conduct a sensitivity analysis over the change in signatures from the future period compared to the base period. In this way, we can identify the parameters that are responsible for certain projected changes, and identify the processes responsible for this change. By using three different models, in which VIC is most distinctive in including explicit vegetation parameters, we can compare different process representations and the effect on the projected hydrological change.

  4. Vegetation Dynamics And Soil Moisture: Consequences For Hydrologic Modeling

    NASA Astrophysics Data System (ADS)

    Guardiola-Claramonte, M.; Troch, P. A.

    2007-12-01

    Current global population growth and economical development accelerates land cover conversion in many parts of the world. Introducing non-native species and woody species encroachment, with different water demands, can affect the partitioning of hydrological fluxes. The impacts on the hydrologic cycle at local to regional scales are poorly understood. The present study investigates the hydrologic implications of land use conversion from native vegetation to rubber. We first compare the vegetation dynamics of rubber (Hevea brasiliensis), a non- native specie in Southeast Asia, to the other main vegetation types in the study area. The experimental catchment, Nam Ken (69km 2), is located in the Xishuangbanna Prefecture (21 °N, 100 °E), in the south of Yunnan province in South China. From 2005 to 2006, we collected continuous records of 2 m deep soil moisture profiles in four different land covers (tea, secondary forest, grassland and rubber), and measured surface radiation in tea and rubber canopies. Our observations show that root water uptake by rubber during the dry season is controlled by the change of day-length, whereas water demand of the native vegetation starts with the arrival of the first monsoon rainfall. The different root water uptake dynamics of rubber result in distinct depletion of deeper layer soil moisture. Traditional evapotranspiration and soil moisture models are unable to simulate this specific behavior, thus a different conceptual model is needed to predict hydrologic changes due to land use conversion in the area.

  5. Hydrologic modeling in dynamic catchments: A data assimilation approach

    NASA Astrophysics Data System (ADS)

    Pathiraja, S.; Marshall, L.; Sharma, A.; Moradkhani, H.

    2016-05-01

    The transferability of conceptual hydrologic models in time is often limited by both their structural deficiencies and adopted parameterizations. Adopting a stationary set of model parameters ignores biases introduced by the data used to derive them, as well as any future changes to catchment conditions. Although time invariance of model parameters is one of the hallmarks of a high quality hydrologic model, very few (if any) models can achieve this due to their inherent limitations. It is therefore proposed to consider parameters as potentially time varying quantities, which can evolve according to signals in hydrologic observations. In this paper, we investigate the potential for Data Assimilation (DA) to detect known temporal patterns in model parameters from streamflow observations. It is shown that the success of the DA algorithm is strongly dependent on the method used to generate background (or prior) parameter ensembles (also referred to as the parameter evolution model). A range of traditional parameter evolution techniques are considered and found to be problematic when multiple parameters with complex time variations are estimated simultaneously. Two alternative methods are proposed, the first is a Multilayer approach that uses the EnKF to estimate hyperparameters of the temporal structure, based on apriori knowledge of the form of nonstationarity. The second is a Locally Linear approach that uses local linear estimation and requires no assumptions of the form of parameter nonstationarity. Both are shown to provide superior results in a range of synthetic case studies, when compared to traditional parameter evolution techniques.

  6. 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

    conceptualizations of hydrology in modeling landscape evolution.

  7. 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)

  8. 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

  9. Committee of machine learning predictors of hydrological models uncertainty

    NASA Astrophysics Data System (ADS)

    Kayastha, Nagendra; Solomatine, Dimitri

    2014-05-01

    In prediction of uncertainty based on machine learning methods, the results of various sampling schemes namely, Monte Carlo sampling (MCS), generalized likelihood uncertainty estimation (GLUE), Markov chain Monte Carlo (MCMC), shuffled complex evolution metropolis algorithm (SCEMUA), differential evolution adaptive metropolis (DREAM), particle swarm optimization (PSO) and adaptive cluster covering (ACCO)[1] used to build a predictive models. These models predict the uncertainty (quantiles of pdf) of a deterministic output from hydrological model [2]. Inputs to these models are the specially identified representative variables (past events precipitation and flows). The trained machine learning models are then employed to predict the model output uncertainty which is specific for the new input data. For each sampling scheme three machine learning methods namely, artificial neural networks, model tree, locally weighted regression are applied to predict output uncertainties. The problem here is that different sampling algorithms result in different data sets used to train different machine learning models which leads to several models (21 predictive uncertainty models). There is no clear evidence which model is the best since there is no basis for comparison. A solution could be to form a committee of all models and to sue a dynamic averaging scheme to generate the final output [3]. This approach is applied to estimate uncertainty of streamflows simulation from a conceptual hydrological model HBV in the Nzoia catchment in Kenya. [1] N. Kayastha, D. L. Shrestha and D. P. Solomatine. Experiments with several methods of parameter uncertainty estimation in hydrological modeling. Proc. 9th Intern. Conf. on Hydroinformatics, Tianjin, China, September 2010. [2] D. L. Shrestha, N. Kayastha, and D. P. Solomatine, and R. Price. Encapsulation of parameteric uncertainty statistics by various predictive machine learning models: MLUE method, Journal of Hydroinformatic, in press

  10. Improving hydrology models for a changing climate

    NASA Astrophysics Data System (ADS)

    Palus, Shannon

    2014-12-01

    Changes over time in the relationship between rainfall and catchment runoff pose a significant challenge for hydrological models, which are often calibrated under the assumption that the future relationship will be consistent with that of the past. In a recent paper, Westra et al. outlined a method for diagnosing, interpreting, and improving the capacity of models to develop predictions under such conditions.

  11. Treatments of Precipitation Inputs to Hydrologic Models

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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 ...

  12. Pursuing the method of multiple working hypotheses for hydrological modeling

    NASA Astrophysics Data System (ADS)

    Clark, M. P.; Kavetski, D.; Fenicia, F.

    2012-12-01

    Ambiguities in the representation of environmental processes have manifested themselves in a plethora of hydrological models, differing in almost every aspect of their conceptualization and implementation. The current overabundance of models is symptomatic of an insufficient scientific understanding of environmental dynamics at the catchment scale, which can be attributed to difficulties in measuring and representing the heterogeneity encountered in natural systems. This presentation advocates using the method of multiple working hypotheses for systematic and stringent testing of model alternatives in hydrology. We discuss how the multiple hypothesis approach provides the flexibility to formulate alternative representations (hypotheses) describing both individual processes and the overall system. When combined with incisive diagnostics to scrutinize multiple model representations against observed data, this provides hydrologists with a powerful and systematic approach for model development and improvement. Multiple hypothesis frameworks also support a broader coverage of the model hypothesis space and hence improve the quantification of predictive uncertainty arising from system and component non-identifiabilities. As part of discussing the advantages and limitations of multiple hypothesis frameworks, we critically review major contemporary challenges in hydrological hypothesis-testing, including exploiting different types of data to investigate the fidelity of alternative process representations, accounting for model structure ambiguities arising from major uncertainties in environmental data, quantifying regional differences in dominant hydrological processes, and the grander challenge of understanding the self-organization and optimality principles that may functionally explain and describe the heterogeneities evident in most environmental systems. We assess recent progress in these research directions, and how new advances are possible using multiple hypothesis

  13. Pursuing the method of multiple working hypotheses for hydrological modeling

    NASA Astrophysics Data System (ADS)

    Clark, Martyn P.; Kavetski, Dmitri; Fenicia, Fabrizio

    2011-09-01

    Ambiguities in the representation of environmental processes have manifested themselves in a plethora of hydrological models, differing in almost every aspect of their conceptualization and implementation. The current overabundance of models is symptomatic of an insufficient scientific understanding of environmental dynamics at the catchment scale, which can be attributed to difficulties in measuring and representing the heterogeneity encountered in natural systems. This commentary advocates using the method of multiple working hypotheses for systematic and stringent testing of model alternatives in hydrology. We discuss how the multiple-hypothesis approach provides the flexibility to formulate alternative representations (hypotheses) describing both individual processes and the overall system. When combined with incisive diagnostics to scrutinize multiple model representations against observed data, this provides hydrologists with a powerful and systematic approach for model development and improvement. Multiple-hypothesis frameworks also support a broader coverage of the model hypothesis space and hence improve the quantification of predictive uncertainty arising from system and component nonidentifiabilities. As part of discussing the advantages and limitations of multiple-hypothesis frameworks, we critically review major contemporary challenges in hydrological hypothesis-testing, including exploiting different types of data to investigate the fidelity of alternative process representations, accounting for model structure ambiguities arising from major uncertainties in environmental data, quantifying regional differences in dominant hydrological processes, and the grander challenge of understanding the self-organization and optimality principles that may functionally explain and describe the heterogeneities evident in most environmental systems. We assess recent progress in these research directions, and how new advances are possible using multiple

  14. Hydrological Modeling and Repeatability with Brokering

    NASA Astrophysics Data System (ADS)

    Easton, Z. M.; Collick, A.; Srinivasan, R.; Braeckel, A.; Nativi, S.; McAlister, C.; Wright, D. J.; Khalsa, S. J. S.; Fuka, D.

    2014-12-01

    Data brokering aims to provide those in the hydrological sciences with access to relevant data to represent physical, biological, and chemical characteristics researchers need to accelerate discovery in their domain. Environmental models are useful tools to understand the behavior of hydrological systems. Unfortunately, parameterization of these models requires many different data sources from different disciplines (e.g., atmospheric, geoscience, ecology). In 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, more suitable data products exist. An added complexity is that various science communities have differing data formats, storage protocols and manipulation methods, which makes use by a non domain scientist difficult and time consuming. We propose 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 increases the efficiency with which data are collected, models are initialized, and results are analyzed. As an added benefit, it appears brokering significantly increases the repeatability of a study.

  15. Formalizing Linguistic Conventions for Conceptual Models

    NASA Astrophysics Data System (ADS)

    Becker, Jörg; Delfmann, Patrick; Herwig, Sebastian; Lis, Łukasz; Stein, Armin

    A precondition for the appropriate analysis of conceptual models is not only their syntactic correctness but also their semantic comparability. Assuring comparability is challenging especially when models are developed by different persons. Empirical studies show that such models can vary heavily, especially in model element naming, even if they express the same issue. In contrast to most ontology-driven approaches proposing the resolution of these differences ex-post, we introduce an approach that avoids naming differences in conceptual models already during modeling. Therefore we formalize naming conventions combining domain thesauri and phrase structures based on a lin-guistic grammar. This allows for guiding modelers automatically during the modeling process using standardized labels for model elements. Our approach is generic, making it applicable for any modeling language.

  16. Hydrological modelling in a "big data" era: a proof of concept of hydrological models as web services

    NASA Astrophysics Data System (ADS)

    Buytaert, Wouter; Vitolo, Claudia

    2013-04-01

    Dealing with the massive increase in global data availability of all sorts is increasingly being known as "big data" science. Indeed, largely leveraged by the internet, a new resource of data sets emerges that are so large and heterogeneous that they become awkward to work with. New algorithms, methods and models are needed to filter such data to find trends, test hypotheses, make predictions and quantify uncertainties. As a considerable share of the data relate to environmental processes (e.g., satellite images, distributed sensor networks), this evolution provides exciting challenges for environmental sciences, and hydrology in particular. Web-enabled models are a promising approach to process large and distributed data sets, and to provide tailored products for a variety of end-users. It will also allow hydrological models to be used as building blocks in larger earth system simulation systems. However, in order to do so we need to reconsider the ways that hydrological models are built, results are made available, and uncertainties are quantified. We present the results of an experimental proof of concept of a hydrological modelling web-service to process heterogeneous hydrological data sets. The hydrological model itself consists of a set of conceptual model routines implemented with on a common platform. This framework is linked to global and local data sets through web standards provided by the Open Geospatial Consortium, as well as to a web interface that enables an end-user to request stream flow simulations from a self-defined location. In essence, the proof-of-concept can be seen as an implementation of the "Models of Everywhere" concept introduced by Beven in 2007. Although the setup is operational and effectively simulates stream flow, we identify several bottlenecks for optimal hydrological simulation in a web-context. The major challenges we identify are related to (1) model selection; (2) uncertainty quantification, and (3) user interaction and

  17. Use of Numerical Groundwater Modeling to Evaluate Uncertainty in Conceptual Models of Recharge and Hydrostratigraphy

    SciTech Connect

    Pohlmann, Karl; Ye, Ming; Pohll, Greg; Chapman, Jenny

    2007-01-19

    Numerical groundwater models are based on conceptualizations of hydrogeologic systems that are by necessity developed from limited information and therefore are simplifications of real conditions. Each aspect (e.g. recharge, hydrostratigraphy, boundary conditions) of the groundwater model is often based on a single conceptual model that is considered to be the best representation given the available data. However, the very nature of their construction means that each conceptual model is inherently uncertain and the available information may be insufficient to refute plausible alternatives, thereby raising the possibility that the flow model is underestimating overall uncertainty. In this study we use the Death Valley Regional Flow System model developed by the U.S. Geological Survey as a framework to predict regional groundwater flow southward into Yucca Flat on the Nevada Test Site. An important aspect of our work is to evaluate the uncertainty associated with multiple conceptual models of groundwater recharge and subsurface hydrostratigraphy and quantify the impacts of this uncertainty on model predictions. In our study, conceptual model uncertainty arises from two sources: (1) alternative interpretations of the hydrostratigraphy in the northern portion of Yucca Flat where, owing to sparse data, the hydrogeologic system can be conceptualized in different ways, and (2) uncertainty in groundwater recharge in the region as evidenced by the existence of several independent approaches for estimating this aspect of the hydrologic system. The composite prediction of groundwater flow is derived from the regional model that formally incorporates the uncertainty in these alternative input models using the maximum likelihood Bayesian model averaging method. An assessment of the joint predictive uncertainty of the input conceptual models is also produced. During this process, predictions of the alternative models are weighted by model probability, which is the degree of

  18. An attempt of ensemble modelling of future hydrological regime for selected river basin.

    NASA Astrophysics Data System (ADS)

    Valainis, A.; Timuhin, A.; Bethers, U.

    2009-04-01

    Ensemble modelling of hydrological regime may refer to usage of different Regional Climate Models (RCMs) coupled with one hydrological model, or usage of one RCM coupled with multiple hydrological models. Our goal was to examine future flow regimes based on different hydrological models. We conducted a river basin study based on one particular subbasin (Berze) of the river Lielupe basin. Lielupe is a lowland river with basin area of 17000 sq.km, situated in Latvia and Lithuania. Area of chosen subbasin is approximately 1000 sq.km. Ensemble of hydrological models consisted of MIKE SHE, and MIKE BASIN by DHI, the runoff model embedded in RCM, and in-house FiBasin model. MIKE SHE is grid based distributed hydrological model coupled with MIKE 11 flow routing model. MIKE Basin has embedded, conceptual catchment based NAM model. FiBasin is spatially distributed, finite volume based hydrological model with hydraulic routing network. The RCM and climate change scenarios are provided by Prediction of Regional scenarios and Uncertainties for Defining European Climate change risks and Effects (PRUDENCE) project. Time period for climate change scenarios is 2071-2100. The different responses from climate change, using different calibration sets where evaluated. The uncertainty related to choice of hydrological models is evaluated. It is found that the choice of hydrological model can lead to uncertainty witch is comparable with the even to difference between the climate scenarios, or the climate change itself. This conclusion is valid for the area of study in which the expected change of the hydrological regime is rather small.

  19. Where and why do models fail? Perspectives from Oregon Hydrologic Landscape classification

    EPA Science Inventory

    A complete understanding of why rainfall-runoff models provide good streamflow predictions at catchments in some regions, but fail to do so in other regions, has still not been achieved. Here, we argue that a hydrologic classification system is a robust conceptual tool that is w...

  20. Models and data for hydrological analyses - lessons learned from uncertainty

    NASA Astrophysics Data System (ADS)

    Balin, D.; Parent, E.; Goetzinger, J.; Musy, A.; Bardossy, A.; Rode, M.

    2009-04-01

    Modelling has become an unavoidable step in the hydrological analyses. Intensive monitoring of experimental or representative catchments in different environments allowed identifying of dominant processes that further enabled the choice of an appropriate model structure to be used for simulation, forecast or scenario analyses. Progresses have been done in building different modelling structures (conceptual and physically based, lumped and distributed) that are now being extensively used at different scales, with different amounts of input data and together with different calibration procedures. The present study will analyse the role of uncertainty, in a Bayesian context, as a tool to learn how input data (discharge, soil moisture, chemistry, rainfall) could be used to evaluate two semi and fully distributed modelling structures (TOPMODEL and WASIM-ETH) in two different catchments: a small (2km2) one in the Swiss Plateau region (the Haute-Mentue catchment) and a medium (100km2) one in low range mountain in central Germany (Weisse Elster catchment).

  1. Inverse distributed hydrological modelling of alpine catchments

    NASA Astrophysics Data System (ADS)

    Kunstmann, H.; Krause, J.; Mayr, S.

    2005-12-01

    Even in physically based distributed hydrological models, various remaining parameters must be estimated for each sub-catchment. This can involve tremendous effort, especially when the number of sub-catchments is large and the applied hydrological model is computationally expensive. Automatic parameter estimation tools can significantly facilitate the calibration process. Hence, we combined the nonlinear parameter estimation tool PEST with the distributed hydrological model WaSiM. PEST is based on the Gauss-Marquardt-Levenberg method, a gradient-based nonlinear parameter estimation algorithm. WaSiM is a fully distributed hydrological model using physically based algorithms for most of the process descriptions. WaSiM was applied to the alpine/prealpine Ammer River catchment (southern Germany, 710 km2) in a 100×100 m2 horizontal resolution. The catchment is heterogeneous in terms of geology, pedology and land use and shows a complex orography (the difference of elevation is around 1600 m). Using the developed PEST-WaSiM interface, the hydrological model was calibrated by comparing simulated and observed runoff at eight gauges for the hydrologic year 1997 and validated for the hydrologic year 1993. For each sub-catchment four parameters had to be calibrated: the recession constants of direct runoff and interflow, the drainage density, and the hydraulic conductivity of the uppermost aquifer. Additionally, five snowmelt specific parameters were adjusted for the entire catchment. Altogether, 37 parameters had to be calibrated. Additional a priori information (e.g. from flood hydrograph analysis) narrowed the parameter space of the solutions and improved the non-uniqueness of the fitted values. A reasonable quality of fit was achieved. Discrepancies between modelled and observed runoff were also due to the small number of meteorological stations and corresponding interpolation artefacts in the orographically complex terrain. A detailed covariance analysis was performed

  2. Interplay of geomorphic and hydrogeologic features at reach- and channel unit-scales on riverbed hydrology and hydrochemistry: a conceptual model in the Lower Coal Measures, South Yorkshire, UK

    NASA Astrophysics Data System (ADS)

    Ibrahim, T. G.; Thornton, S. F.; Wainwright, J.

    2010-09-01

    A conceptual model of groundwater and surface-water interactions in areas of minor aquifers has been developed. It assesses the interplay of reach-scale subsurface flow paths (RSSF), controlled by the lateral extent of the alluvial valley, and channel unit-scale hyporheic flow paths (CUSHF), controlled by riffle and run/pool sequences, and their impacts on the spatial variability of riverbed flow and solute exchange. A network of riverbed mini-piezometers and multi-level samplers in different reach- and channel-unit scale settings of the River Don (South Yorkshire, UK) is monitored to: (1) estimate vertical hydraulic gradients (VHGs) and specific discharge; (2) discriminate subsurface flow paths from conservative natural tracers; and (3) deduce biogeochemical processes. In a constrained context (downstream end of the alluvial valley), RSSF discharge favours a homogeneous riverbed hydrochemistry with limited biogeochemical processes and shallow CUSHF. In an unconstrained (open alluvial valley) or asymmetric (bedrock outcropping on one bank) context, low VHGs favour deep CUSHF and a vertical stratification of RSSF. Reducing conditions intensify with depth, and superimpose with mixing in riffles. This good approximation of flow and solute behaviour in minor aquifers provides a practical framework to understand nutrient and contaminant fate and develop cost-effective monitoring programmes across the groundwater/surface-water interface.

  3. Leading Generative Groups: A Conceptual Model

    ERIC Educational Resources Information Center

    London, Manuel; Sobel-Lojeski, Karen A.; Reilly, Richard R.

    2012-01-01

    This article presents a conceptual model of leadership in generative groups. Generative groups have diverse team members who are expected to develop innovative solutions to complex, unstructured problems. The challenge for leaders of generative groups is to balance (a) establishing shared goals with recognizing members' vested interests, (b)…

  4. Self-Presentation: A Conceptualization and Model.

    ERIC Educational Resources Information Center

    Schlenker, Barry R.

    This paper provides a conceptual definition and model of self-presentational behavior. Self-presentation is defined as the attempt to control self-relevant images before real or imagined others. Several aspects of the definition are discussed along with the notion that people's self-presentations represent the choice of the most desirable images…

  5. A Conceptual Model of Rhetorical Community.

    ERIC Educational Resources Information Center

    Ehrenhaus, Peter

    A conceptual model of the rhetorical community that addresses the sociodramatic processes through which social order evolves, is maintained, can change, and is threatened is presented in this paper. Following an introduction, the paper identifies the various uses of rhetorical vision and rhetorical community that are found in fantasy theme…

  6. Administrator Training and Development: Conceptual Model.

    ERIC Educational Resources Information Center

    Boardman, Gerald R.

    A conceptual model for an individualized training program for school administrators integrates processes, characteristics, and tasks through theory training and application. Based on an application of contingency theory, it provides a system matching up administrative candidates' needs in three areas (administrative process, administrative…

  7. Modeling Soil Moisture Fields Using the Distributed Hydrologic Model MOBIDIC

    NASA Astrophysics Data System (ADS)

    Castillo, A. E.; Entekhabi, D.; Castelli, F.

    2011-12-01

    The Modello Bilancio Idrologico DIstributo e Continuo (MOBIDIC) is a fully-distributed physically-based basin hydrologic model [Castelli et al., 2009]. MOBIDIC represents watersheds using a system or reservoirs that interact through both mass and energy fluxes. The model uses a single-layered soil on a grid. For each grid element, soil moisture is conceptually partitioned into gravitational (free) and capillary-bound water. For computational parsimony, linear parameterization is used for infiltration rather than solving it using the nonlinear Richard's Equation. Previous applications of MOBIDIC assessed model performance based on streamflow which is a flux. In this study, the MOBIDIC simulated soil moisture, a state variable, is compared against observed values as well as values simulated by the legacy Simultaneous Heat and Water (SHAW) model [Flerchinger, 2000] which was chosen as the benchmark. Results of initial simulations with the original version of MOBIDIC prompted several model modifications such as changing the parameterization of evapotranspiration and adding capillary rise to make the model more robust in simulating the dynamics of soil moisture. In order to test the performance of the modified MOBIDIC, both short-term (a few weeks) and extended (multi-year) simulations were performed for 3 well-studied sites in the US: two sites are mountainous with deep groundwater table and semiarid climate, while the third site is fluvial with shallow groundwater table and temperate climate. For the multi-year simulations, both MOBIDIC and SHAW performed well in modeling the daily observed soil moisture. The simulations also illustrated the benefits of adding the capillary rise module and the other modifications introduced. Moreover, it was successfully demonstrated that MOBIDIC, with some conceptual approaches and some simplified parameterizations, can perform as good, if not better, than the more sophisticated SHAW model. References Castelli, F., G. Menduni, and B

  8. Exploring Information Theory for improving Hydrologic Model Performance

    NASA Astrophysics Data System (ADS)

    Martinez Baquero, G. F.; Gupta, H. V.

    2005-12-01

    For more than 30 years, Information Theory (IT) concepts have appeared in literature and practice of hydrology in several ways. Although these concepts are implicit in many practical applications and ideas, still the language and use are not widespread among the scientific community dedicated to study hydrologic processes. At the same time, new points of view, as the shown in this session, reflect the increasing availability of data and information with finer resolution. Equally, increasing computing capabilities, the development of more complex decision-making systems, and better forecasting tools impose on hydrologists new challenges related to the optimal use of data and the information that can be extracted from it. In our understanding, one of the approaches to address these challenges is to recognize that the notion of information is inherent to the problem of dealing with hydrologic data and the evaluation of its characteristics. The goal of this poster is to evaluate how IT can be used to generate a conceptual framework for assessing the performance of models against real data, and how these assessments can help us to increase our knowledge about the physical mechanisms involved.

  9. A Hypothesis-based Approach to Hydrological Model Development: The Case for Flexible Model Structures

    NASA Astrophysics Data System (ADS)

    Clark, M. P.; Kavetski, D.; Fenicia, F.

    2010-12-01

    Ambiguities in the appropriate representation of environmental processes have manifested themselves in a plethora of hydrological models, differing in almost every aspect of their conceptualization and implementation. This current overabundance of models is symptomatic of insufficient scientific understanding of environmental dynamics at the catchment scale, which can be attributed to difficulties in quantifying the impact of sub-catchment heterogeneities on the catchment’s hydrological response. In this presentation we advocate the use of flexible modeling frameworks during the development and subsequent refinement of catchment-scale hydrological models. We argue that the ability of flexible modeling frameworks to decompose a model into its constituent hypotheses, necessarily combined with incisive diagnostics to scrutinize these individual hypotheses against observed data, provides hydrologists with a very powerful and systematic approach for improving process representation in models. Flexible models also support a broader coverage of the model hypothesis space and hence facilitate a more comprehensive quantification of the predictive uncertainty associated with system and component non-identifiabilities that plague many model analyses. As part of our discussion of the advantages and limitations of flexible model frameworks, we critically review major contemporary challenges in hydrological hypothesis-testing, including exploiting data to investigate the fidelity of alternative process representations, accounting for model structure ambiguities arising from uncertainty in environmental data, and the challenge of understanding regional differences in dominant hydrological processes. We assess recent progress in these research directions, and how such progress can be exploited within flexible model applications to advance the community’s quest for more scientifically defensible catchment-scale hydrological models.

  10. Optimizing hydrological consistency by incorporating hydrological signatures into model calibration objectives

    NASA Astrophysics Data System (ADS)

    Shafii, Mahyar; Tolson, Bryan A.

    2015-05-01

    The simulated outcome of a calibrated hydrologic model should be hydrologically consistent with the measured response data. Hydrologic modelers typically calibrate models to optimize residual-based goodness-of-fit measures, e.g., the Nash-Sutcliffe efficiency measure, and then evaluate the obtained results with respect to hydrological signatures, e.g., the flow duration curve indices. The literature indicates that the consideration of a large number of hydrologic signatures has not been addressed in a full multiobjective optimization context. This research develops a model calibration methodology to achieve hydrological consistency using goodness-of-fit measures, many hydrological signatures, as well as a level of acceptability for each signature. The proposed framework relies on a scoring method that transforms any hydrological signature to a calibration objective. These scores are used to develop the hydrological consistency metric, which is maximized to obtain hydrologically consistent parameter sets during calibration. This consistency metric is implemented in different signature-based calibration formulations that adapt the sampling according to hydrologic signature values. These formulations are compared with the traditional formulations found in the literature for seven case studies. The results reveal that Pareto dominance-based multiobjective optimization yields the highest level of consistency among all formulations. Furthermore, it is found that the choice of optimization algorithms does not affect the findings of this research.

  11. Conceptual Models of Frontal Cyclones.

    ERIC Educational Resources Information Center

    Eagleman, Joe R.

    1981-01-01

    This discussion of weather models uses maps to illustrate the differences among three types of frontal cyclones (long wave, short wave, and troughs). Awareness of these cyclones can provide clues to atmospheric conditions which can lead toward accurate weather forecasting. (AM)

  12. A conceptual model for megaprogramming

    NASA Technical Reports Server (NTRS)

    Tracz, Will

    1990-01-01

    Megaprogramming is component-based software engineering and life-cycle management. Magaprogramming and its relationship to other research initiatives (common prototyping system/common prototyping language, domain specific software architectures, and software understanding) are analyzed. The desirable attributes of megaprogramming software components are identified and a software development model and resulting prototype megaprogramming system (library interconnection language extended by annotated Ada) are described.

  13. Improving subsurface hydrology in Earth System Models

    NASA Astrophysics Data System (ADS)

    Volk, J. M.; Clark, M. P.; Swenson, S. C.; Lawrence, D. M.; Tyler, S. W.

    2015-12-01

    Hydrologic processes that govern storage and transport of soil water and groundwater can have strong dynamic relationships with biogeochemical and atmospheric processes. This understanding has lead to a push to improve subsurface hydrologic parametrization in Earth System Models. Here we present results related to improving the implementation of soil moisture distribution, groundwater recharge/discharge, and subsurface drainage in the Community Land Model (CLM) which is the land surface model in the Community Earth System Model. First we identified geo-climatically different locations around the world to develop test cases. For each case we compare the vertical soil moisture distribution from the different implementations of 1D Richards equation, considering the boundary conditions, the treatment of the groundwater sink term, the vertical discretization, and the time stepping schemes. Generally, large errors in the hydrologic mass balance within the soil column occur when there is a large vertical gradient in soil moisture or when there is a shallow water table within a soil column. We then test the sensitivity of the algorithmic parameters that control temporal discretization and error tolerance of the adaptive time-stepping scheme to help optimize its computational efficiency. In addition, we vary the spatial discretization of soil layers (i.e. quantity of layers and their thicknesses) to better understand the sensitivity of vertical discretization of soil columns on soil moisture variability in ESMs. We present multivariate and multi-scale evaluation for the different model options and suggest ways to move forward with future model improvements.

  14. The conceptualization model problem—surprise

    NASA Astrophysics Data System (ADS)

    Bredehoeft, John

    2005-03-01

    The foundation of model analysis is the conceptual model. Surprise is defined as new data that renders the prevailing conceptual model invalid; as defined here it represents a paradigm shift. Limited empirical data indicate that surprises occur in 20-30% of model analyses. These data suggest that groundwater analysts have difficulty selecting the appropriate conceptual model. There is no ready remedy to the conceptual model problem other than (1) to collect as much data as is feasible, using all applicable methods—a complementary data collection methodology can lead to new information that changes the prevailing conceptual model, and (2) for the analyst to remain open to the fact that the conceptual model can change dramatically as more information is collected. In the final analysis, the hydrogeologist makes a subjective decision on the appropriate conceptual model. The conceptualization problem does not render models unusable. The problem introduces an uncertainty that often is not widely recognized. Conceptual model uncertainty is exacerbated in making long-term predictions of system performance. C'est le modèle conceptuel qui se trouve à base d'une analyse sur un modèle. On considère comme une surprise lorsque le modèle est invalidé par des données nouvelles; dans les termes définis ici la surprise est équivalente à un change de paradigme. Des données empiriques limitées indiquent que les surprises apparaissent dans 20 à 30% des analyses effectuées sur les modèles. Ces données suggèrent que l'analyse des eaux souterraines présente des difficultés lorsqu'il s'agit de choisir le modèle conceptuel approprié. Il n'existe pas un autre remède au problème du modèle conceptuel que: (1) rassembler autant des données que possible en utilisant toutes les méthodes applicables—la méthode des données complémentaires peut conduire aux nouvelles informations qui vont changer le modèle conceptuel, et (2) l'analyste doit rester ouvert au fait

  15. Simultaneous calibration of hydrological models in geographical space

    NASA Astrophysics Data System (ADS)

    Bárdossy, András; Huang, Yingchun; Wagener, Thorsten

    2016-07-01

    Hydrological models are usually calibrated for selected catchments individually using specific performance criteria. This procedure assumes that the catchments show individual behavior. As a consequence, the transfer of model parameters to other ungauged catchments is problematic. In this paper, the possibility of transferring part of the model parameters was investigated. Three different conceptual hydrological models were considered. The models were restructured by introducing a new parameter η which exclusively controls water balances. This parameter was considered as individual to each catchment. All other parameters, which mainly control the dynamics of the discharge (dynamical parameters), were considered for spatial transfer. Three hydrological models combined with three different performance measures were used in three different numerical experiments to investigate this transferability. The first numerical experiment, involving individual calibration of the models for 15 selected MOPEX catchments, showed that it is difficult to identify which catchments share common dynamical parameters. Parameters of one catchment might be good for another catchment but not the opposite. In the second numerical experiment, a common spatial calibration strategy was used. It was explicitly assumed that the catchments share common dynamical parameters. This strategy leads to parameters which perform well on all catchments. A leave-one-out common calibration showed that in this case a good parameter transfer to ungauged catchments can be achieved. In the third numerical experiment, the common calibration methodology was applied for 96 catchments. Another set of 96 catchments was used to test the transfer of common dynamical parameters. The results show that even a large number of catchments share similar dynamical parameters. The performance is worse than those obtained by individual calibration, but the transfer to ungauged catchments remains possible. The performance of the

  16. Towards Better Coupling of Hydrological Simulation Models

    NASA Astrophysics Data System (ADS)

    Penton, D.; Stenson, M.; Leighton, B.; Bridgart, R.

    2012-12-01

    Standards for model interoperability and scientific workflow software provide techniques and tools for coupling hydrological simulation models. However, model builders are yet to realize the benefits of these and continue to write ad hoc implementations and scripts. Three case studies demonstrate different approaches to coupling models, the first using tight interfaces (OpenMI), the second using a scientific workflow system (Trident) and the third using a tailored execution engine (Delft Flood Early Warning System - Delft-FEWS). No approach was objectively better than any other approach. The foremost standard for coupling hydrological models is the Open Modeling Interface (OpenMI), which defines interfaces for models to interact. An implementation of the OpenMI standard involves defining interchange terms and writing a .NET/Java wrapper around the model. An execution wrapper such as OatC.GUI or Pipistrelle executes the models. The team built two OpenMI implementations for eWater Source river system models. Once built, it was easy to swap river system models. The team encountered technical challenges with versions of the .Net framework (3.5 calling 4.0) and with the performance of the execution wrappers when running daily simulations. By design, the OpenMI interfaces are general, leaving significant decisions around the semantics of the interfaces to the implementer. Increasingly, scientific workflow tools such as Kepler, Taverna and Trident are able to replace custom scripts. These tools aim to improve the provenance and reproducibility of processing tasks. In particular, Taverna and the myExperiment website have had success making many bioinformatics workflows reusable and sharable. The team constructed Trident activities for hydrological software including IQQM, REALM and eWater Source. They built an activity generator for model builders to build activities for particular river systems. The models were linked at a simulation level, without any daily time

  17. 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

  18. Enhancements for Hydrological Modeling in ESMF

    NASA Astrophysics Data System (ADS)

    Deluca, C.; Oehmke, R.; Neckels, D.; Theurich, G.; O'Kuinghttons, R.; de Fainchtein, R.; Murphy, S.; Dunlap, R.

    2008-12-01

    Hydrological systems connect Earth's global physical phenomena with the local environmental impacts that affect our food, health, finances, and homes. The scales and processes that hydrological modelers must span are reflected in the challenges of developing infrastructure for this community. The basic requirements - the need to assemble and couple model components, the need for efficient I/O, the need for integrated visualization, analysis, and data services - are shared with other domains, such as climate and space weather. Where hydrology goes beyond other domains is in its terrific heterogeneity. The diversity of models, data structures, grids, computing platforms, computing languages, and specialized sub-domains involved is daunting. It's not surprising that the hydrological community has spawned a variety of different integrative efforts and frameworks, with distinctly different approaches. This talk will outline how the Earth System Modeling Framework (ESMF), which began in realm of high performance computing for the climate and weather domain, has begun to address the needs of hydrological modelers. We will describe ESMF's new mesh and observational data stream data structures, which join its structured grids and lower-level, index-space constructs as options for data representation, and the flexible, parallel regridding services that can interpolate data between them. The ESMF team is exploring a service oriented architecture approach to computing language and platform diversity, and to interfacing with other standard frameworks. We have also implemented C interfaces for optimized coupling between C and Fortran codes on traditional high performance computing platforms. To address the variety of components available, distributed communities, and integration with data and other services, ESMF has been exhancing its ability to store and write standard component and field metadata, and to link that metadata with full-service science portals. This enables

  19. 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

  20. 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 E.

    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

  1. Testing conceptual and physically based soil hydrology schemes against observations for the Amazon Basin

    NASA Astrophysics Data System (ADS)

    Guimberteau, M.; Ducharne, A.; Ciais, P.; Boisier, J. P.; Peng, S.; De Weirdt, M.; Verbeeck, H.

    2014-06-01

    This study analyzes the performance of the two soil hydrology schemes of the land surface model ORCHIDEE in estimating Amazonian hydrology and phenology for five major sub-basins (Xingu, Tapajós, Madeira, Solimões and Negro), during the 29-year period 1980-2008. A simple 2-layer scheme with a bucket topped by an evaporative layer is compared to an 11-layer diffusion scheme. The soil schemes are coupled with a river routing module and a process model of plant physiology, phenology and carbon dynamics. The simulated water budget and vegetation functioning components are compared with several data sets at sub-basin scale. The use of the 11-layer soil diffusion scheme does not significantly change the Amazonian water budget simulation when compared to the 2-layer soil scheme (+3.1 and -3.0% in evapotranspiration and river discharge, respectively). However, the higher water-holding capacity of the soil and the physically based representation of runoff and drainage in the 11-layer soil diffusion scheme result in more dynamic soil water storage variation and improved simulation of the total terrestrial water storage when compared to GRACE satellite estimates. The greater soil water storage within the 11-layer scheme also results in increased dry-season evapotranspiration (+0.5 mm d-1, +17%) and improves river discharge simulation in the southeastern sub-basins such as the Xingu. Evapotranspiration over this sub-basin is sustained during the whole dry season with the 11-layer soil diffusion scheme, whereas the 2-layer scheme limits it after only 2 dry months. Lower plant drought stress simulated by the 11-layer soil diffusion scheme leads to better simulation of the seasonal cycle of photosynthesis (GPP) when compared to a GPP data-driven model based on eddy covariance and satellite greenness measurements. A dry-season length between 4 and 7 months over the entire Amazon Basin is found to be critical in distinguishing differences in hydrological feedbacks between the

  2. 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

  3. Uncertainty and the Conceptual Site Model

    NASA Astrophysics Data System (ADS)

    Price, V.; Nicholson, T. J.

    2007-12-01

    Our focus is on uncertainties in the underlying conceptual framework upon which all subsequent steps in numerical and/or analytical modeling efforts depend. Experienced environmental modelers recognize the value of selecting an optimal conceptual model from several competing site models, but usually do not formally explore possible alternative models, in part due to incomplete or missing site data, as well as relevant regional data for establishing boundary conditions. The value in and approach for developing alternative conceptual site models (CSM) is demonstrated by analysis of case histories. These studies are based on reported flow or transport modeling in which alternative site models are formulated using data that were not available to, or not used by, the original modelers. An important concept inherent to model abstraction of these alternative conceptual models is that it is "Far better an approximate answer to the right question, which is often vague, than the exact answer to the wrong question, which can always be made precise." (Tukey, 1962) The case histories discussed here illustrate the value of formulating alternative models and evaluating them using site-specific data: (1) Charleston Naval Site where seismic characterization data allowed significant revision of the CSM and subsequent contaminant transport modeling; (2) Hanford 300-Area where surface- and ground-water interactions affecting the unsaturated zone suggested an alternative component to the site model; (3) Savannah River C-Area where a characterization report for a waste site within the modeled area was not available to the modelers, but provided significant new information requiring changes to the underlying geologic and hydrogeologic CSM's used; (4) Amargosa Desert Research Site (ADRS) where re-interpretation of resistivity sounding data and water-level data suggested an alternative geologic model. Simple 2-D spreadsheet modeling of the ADRS with the revised CSM provided an improved

  4. Operational hydrological ensemble forecasts in France, taking into account rainfall and hydrological model uncertainties.

    NASA Astrophysics Data System (ADS)

    Mathevet, T.; Garavaglia, F.; Gailhard, J.; Garçon, R.; Dubus, L.

    2009-09-01

    In operational conditions, the actual quality of meteorological and hydrological forecasts do not allow decision-making in a certain future. In this context, meteorological and hydrological ensemble forecasts allow a better representation of forecasts uncertainties. Compared to classical deterministic forecasts, ensemble forecasts improve the human expertise of hydrological forecasts, which is essential to synthesize available informations, coming from different meteorological and hydrological models and human experience. In this paper, we present a hydrological ensemble forecasting system under development at EDF (French Hydropower Company). Our results were updated, taking into account a longer rainfall forecasts archive. Our forecasting system both takes into account rainfall forecasts uncertainties and hydrological model forecasts uncertainties. Hydrological forecasts were generated using the MORDOR model (Andreassian et al., 2006), developed at EDF and used on a daily basis in operational conditions on a hundred of watersheds. Two sources of rainfall forecasts were used : one is based on ECMWF forecasts, another is based on an analogues approach (Obled et al., 2002). Two methods of hydrological model forecasts uncertainty estimation were used : one is based on the use of equifinal parameter sets (Beven & Binley, 1992), the other is based on the statistical modelisation of the hydrological forecast empirical uncertainty (Montanari et al., 2004 ; Schaefli et al., 2007). Daily operational hydrological 7-day ensemble forecasts during 4 years (from 2005 to 2008) in few alpine watersheds were evaluated. Finally, we present a way to combine rainfall and hydrological model forecast uncertainties to achieve a good probabilistic calibration. Our results show that the combination of ECMWF and analogues-based rainfall forecasts allow a good probabilistic calibration of rainfall forecasts. They show also that the statistical modeling of the hydrological forecast empirical

  5. How simple can a distributed hydrological model be?

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

    It is well known that lumped conceptual models can often reproduce catchment streamflow response with about a 'handful' of model parameters. But what is the appropriate complexity of a distributed hydrological model, in order to reproduce the distinct streamflow response of heterogeneous internal subcatchments? Is the number of identifiable parameters proportional to the number of stream gauges? Into how many pieces should the catchment be broken-up? And which model structures are best suited to represent the behavior of particular landscape units? We investigated these questions in a case study based on the Attert basin in Luxembourg, where 10 subcatchments with clean and mixed geologies and land use manifested different rainfall-runoff behavior. The hydrological response of individual subcatchments was well represented using a range of lumped models with 4-8 parameters. We then attempted to simulate the 10 streamflow time series simultaneously, using a distributed model. Existing distributed models are often perceived to be over-parameterized. In order to avoid this problem, model development followed an iterative hypothesis-testing process. We developed, calibrated and compared alternative model variants, differing in the landscape classification approach, and in the structure of components intended to represent individual landscape elements. Decisions such as how to break-up the catchment, and which structure to assign to distinct landscape elements were found to significantly influence the model's predictive performance. In the present case, we determined that a geology-based landscape classification provided the best characterization of the observed differences in streamflow responses. In addition, we found that the individual geological units could be represented by remarkably simple model structures. The overall complexity of the distributed model was of about two 'handfuls' (10) of model parameters.

  6. Proving the ecosystem value through hydrological modelling

    NASA Astrophysics Data System (ADS)

    Dorner, W.; Spachinger, K.; Porter, M.; Metzka, R.

    2008-11-01

    Ecosystems provide valuable functions. Also natural floodplains and river structures offer different types of ecosystem functions such as habitat function, recreational area and natural detention. From an economic stand point the loss (or rehabilitation) of these natural systems and their provided natural services can be valued as a damage (or benefit). Consequently these natural goods and services must be economically valued in project assessments e.g. cost-benefit-analysis or cost comparison. Especially in smaller catchments and river systems exists significant evidence that natural flood detention reduces flood risk and contributes to flood protection. Several research projects evaluated the mitigating effect of land use, river training and the loss of natural flood plains on development, peak and volume of floods. The presented project analysis the hypothesis that ignoring natural detention and hydrological ecosystem services could result in economically inefficient solutions for flood protection and mitigation. In test areas, subcatchments of the Danube in Germany, a combination of hydrological and hydrodynamic models with economic evaluation techniques was applied. Different forms of land use, river structure and flood protection measures were assed and compared from a hydrological and economic point of view. A hydrodynamic model was used to simulate flows to assess the extent of flood affected areas and damages to buildings and infrastructure as well as to investigate the impacts of levees and river structure on a local scale. These model results provided the basis for an economic assessment. Different economic valuation techniques, such as flood damage functions, cost comparison method and substation-approach were used to compare the outcomes of different hydrological scenarios from an economic point of view and value the ecosystem service. The results give significant evidence that natural detention must be evaluated as part of flood mitigation projects

  7. A Conceptual Model of Learning Networks

    NASA Astrophysics Data System (ADS)

    Koper, Rob

    In the TENCompetence project a set of UML models (Booch et al. 1999) have been developed to specify the core concepts for Learning Networks Services that support professional competence development. The three most important, high-level models are (a) the use case model, (b) the conceptual model, and (c) the domain model. The first model identifies the primary use cases we need in order to support professional competence development. The second model describes the concept of competence and competence development from a theoretical point of view. What is a competence? How does it relate to the cognitive system of an actor? How are competences developed? The third model is a UML Domain Model that defines, among other things, the components of a Learning Network, defines the concepts and relationships between the concepts in a Learning Network and provides a starting point for the design of the overall architecture for Learning Network Services, including the data model.

  8. A contemporary conceptual model of hypochondriasis.

    PubMed

    Abramowitz, Jonathan S; Schwartz, Stefanie A; Whiteside, Stephen P

    2002-12-01

    Hypochondriasis (HC), which involves preoccupation with the fear of having a serious illness despite appropriate medical examination, is often encountered in medical settings. The most conspicuous feature of this disorder is seeking excessive reassurance from physicians, medical references, or self-inspection; however, many patients also fear they will receive upsetting information if evaluated and thus avoid consultations and remain preoccupied with physiologic events, believing they are physically ill. Thus, HC causes personal suffering for the patient and practical and cost management problems for professionals across fields of clinical practice. The past 2 decades have seen considerable improvement in the understanding and treatment of HC. In this article, we review a contemporary conceptual model of HC and an effective form of treatment called cognitive-behavioral therapy that is derived from this model. Recommendations for presenting this conceptualization to patients and encouraging proper treatment are also discussed. PMID:12479520

  9. An analogue conceptual rainfall-runoff model for educational purposes

    NASA Astrophysics Data System (ADS)

    Herrnegger, Mathew; Riedl, Michael; Schulz, Karsten

    2016-04-01

    Conceptual rainfall-runoff models, in which runoff processes are modelled with a series of connected linear and non-linear reservoirs, remain widely applied tools in science and practice. Additionally, the concept is appreciated in teaching due to its somewhat simplicity in explaining and exploring hydrological processes of catchments. However, when a series of reservoirs are used, the model system becomes highly parametrized and complex and the traceability of the model results becomes more difficult to explain to an audience not accustomed to numerical modelling. Since normally the simulations are performed with a not visible digital code, the results are also not easily comprehensible. This contribution therefore presents a liquid analogue model, in which a conceptual rainfall-runoff model is reproduced by a physical model. This consists of different acrylic glass containers representing different storage components within a catchment, e.g. soil water or groundwater storage. The containers are equipped and connected with pipes, in which water movement represents different flow processes, e.g. surface runoff, percolation or base flow. Water from a storage container is pumped to the upper part of the model and represents effective rainfall input. The water then flows by gravity through the different pipes and storages. Valves are used for controlling the flows within the analogue model, comparable to the parameterization procedure in numerical models. Additionally, an inexpensive microcontroller-based board and sensors are used to measure storage water levels, with online visualization of the states as time series data, building a bridge between the analogue and digital world. The ability to physically witness the different flows and water levels in the storages makes the analogue model attractive to the audience. Hands-on experiments can be performed with students, in which different scenarios or catchment types can be simulated, not only with the analogue but

  10. The influence of conceptual model structure on model performance: a comparative study for 237 French catchments

    NASA Astrophysics Data System (ADS)

    van Esse, W. R.; Perrin, C.; Booij, M. J.; Augustijn, D. C. M.; Fenicia, F.; Lobligeois, F.

    2013-04-01

    In hydrological studies models with a fixed structure are commonly used. For various reasons, these models do not always perform well. As an alternative, a flexible modelling approach could be followed, where the identification of the model structure is part of the model set-up procedure. In this study, the performance of twelve different conceptual model structures from the SUPERFLEX framework with varying complexity and the fixed model structure of GR4H were compared on a large set of 237 French catchments. The results showed that in general the flexible approach performs better than the fixed approach. However, the flexible approach has a higher chance of inconsistent results when implemented on two different periods. The same holds for more complex model structures. When for practical reasons a fixed model structure is preferred, this study shows that models with parallel reservoirs and a power function to describe the reservoir outflow perform best. In general, conceptual hydrological models perform better on large or wet catchments than on small or dry catchments. The model structures performed poorly when there was a climatic difference between the calibration and validation period, for catchments with flashy flows or disturbances in low flow measurements.

  11. Urban Hydrology and Water Quality Modeling - Resolution Modeling Comparison for Water Quantity and Quality

    NASA Astrophysics Data System (ADS)

    Fry, T. J.; Maxwell, R. M.

    2014-12-01

    Urbanization presents challenging water resource problems for communities worldwide. The hydromodifications associated with urbanization results in increased runoff rates and volumes and increased peak flows. These hydrologic changes can lead to increased erosion and stream destabilization, decreased evapotranspiration, decreased ground water recharge, increases in pollutant loading, and localized anthropogenic climate change or Urban Heat Islands. Stormwater represents a complex and dynamic component of the urban water cycle that requires careful mitigation. With the implementation of Phase II rules under the CWA, stormwater management is shifting from a drainage-efficiency focus to a natural systems focus. The natural system focus, referred to as Low Impact Development (LID), or Green Infrastructure, uses best management practices (BMPs) to reduce the impacts caused by urbanization hydromodification. Large-scale patterns of stormwater runoff from urban environments are complex and it is unclear what the large-scale impacts of green infrastructure are on the water cycle. High resolution physically based hydrologic models can be used to more accurately simulate the urban hydrologic cycle. These types of models tend to be more dynamic and allow for greater flexibility in evaluating and accounting for various hydrologic processes in the urban environment that may be lost with lower resolution conceptual models. We propose to evaluate the effectiveness of high resolution models to accurately represent and determine the urban hydrologic cycle with the overall goal of being able to accurately assess the impacts of LID BMPs in urban environments. We propose to complete a rigorous model intercomparison between ParFlow and FLO-2D. Both of these models can be scaled to higher resolutions, allow for rainfall to be spatially and temporally input, and solve the shallow water equations. Each model is different in the way it accounts for infiltration, initial abstraction losses

  12. Modeling the hydrological behavior of a karst spring using a nonlinear reservoir-pipe model

    NASA Astrophysics Data System (ADS)

    Chang, Yong; Wu, Jichun; Jiang, Guanghui

    2015-08-01

    Karst aquifers are commonly simulated based on conceptual models. However, most karst conceptual models hardly consider the function of turbulent conduits. The conduit network acts as the main draining passage of the karst aquifer and may also have a strong influence on the hydrological processes, especially during storm events. A conceptual model with a nonlinear reservoir and a turbulent pipe (representing the conduit system) in series is proposed according to the basic structure of a typical karst aquifer, to simulate the karst spring. The model indicates whether the spring discharge is influenced by the turbulent pipe; this not only depends on the parameters of the nonlinear reservoir and turbulent pipe, but also depends on the volume of spring discharge itself. Even though the spring discharge is strongly influenced by the turbulent pipe during the storm, this influence decreases with the rainfall intensity and volume of spring discharge. In addition, an `evapotranspiration store' is used to consider the moisture loss through evapotranspiration and to calculate the effective rainfall on the proposed model. Then, this simple conceptual model is used to simulate a karst spring (named S31) near Guilin city, China, with satisfactory results, especially with respect to discharge peaks and recession curves of the spring under storm conditions. The proposed model is also compared with the Vensim model of similar complexity, which has been applied to the same spring catchment. The comparison shows the superiority and better performance of the nonlinear reservoir-pipe model.

  13. The influence of conceptual model structure on model performance: a comparative study for 237 French catchments

    NASA Astrophysics Data System (ADS)

    van Esse, W. R.; Perrin, C.; Booij, M. J.; Augustijn, D. C. M.; Fenicia, F.; Kavetski, D.; Lobligeois, F.

    2013-10-01

    Models with a fixed structure are widely used in hydrological studies and operational applications. For various reasons, these models do not always perform well. As an alternative, flexible modelling approaches allow the identification and refinement of the model structure as part of the modelling process. In this study, twelve different conceptual model structures from the SUPERFLEX framework are compared with the fixed model structure GR4H, using a large set of 237 French catchments and discharge-based performance metrics. The results show that, in general, the flexible approach performs better than the fixed approach. However, the flexible approach has a higher chance of inconsistent results when calibrated on two different periods. When analysing the subset of 116 catchments where the two approaches produce consistent performance over multiple time periods, their average performance relative to each other is almost equivalent. From the point of view of developing a well-performing fixed model structure, the findings favour models with parallel reservoirs and a power function to describe the reservoir outflow. In general, conceptual hydrological models perform better on larger and/or wetter catchments than on smaller and/or drier catchments. The model structures performed poorly when there were large climatic differences between the calibration and validation periods, in catchments with flashy flows, and in catchments with unexplained variations in low flow measurements.

  14. 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

  15. Modeling residual hydrologic errors with Bayesian inference

    NASA Astrophysics Data System (ADS)

    Smith, Tyler; Marshall, Lucy; Sharma, Ashish

    2015-09-01

    Hydrologic modelers are confronted with the challenge of producing estimates of the uncertainty associated with model predictions across an array of catchments and hydrologic flow regimes. Formal Bayesian approaches are commonly employed for parameter calibration and uncertainty analysis, but are often criticized for making strong assumptions about the nature of model residuals via the likelihood function that may not be well satisfied (or even checked). This technical note outlines a residual error model (likelihood function) specification framework that aims to provide guidance for the application of more appropriate residual error models through a nested approach that is both flexible and extendible. The framework synthesizes many previously employed residual error models and has been applied to four synthetic datasets (of differing error structure) and a real dataset from the Black River catchment in Queensland, Australia. Each residual error model was investigated and assessed under a top-down approach focused on its ability to properly characterize the errors. The results of these test applications indicate that a multifaceted assessment strategy is necessary to determine the adequacy of an individual likelihood function.

  16. Updated Conceptual Model for the 300 Area Uranium Groundwater Plume

    SciTech Connect

    Zachara, John M.; Freshley, Mark D.; Last, George V.; Peterson, Robert E.; Bjornstad, Bruce N.

    2012-11-01

    The 300 Area uranium groundwater plume in the 300-FF-5 Operable Unit is residual from past discharge of nuclear fuel fabrication wastes to a number of liquid (and solid) disposal sites. The source zones in the disposal sites were remediated by excavation and backfilled to grade, but sorbed uranium remains in deeper, unexcavated vadose zone sediments. In spite of source term removal, the groundwater plume has shown remarkable persistence, with concentrations exceeding the drinking water standard over an area of approximately 1 km2. The plume resides within a coupled vadose zone, groundwater, river zone system of immense complexity and scale. Interactions between geologic structure, the hydrologic system driven by the Columbia River, groundwater-river exchange points, and the geochemistry of uranium contribute to persistence of the plume. The U.S. Department of Energy (DOE) recently completed a Remedial Investigation/Feasibility Study (RI/FS) to document characterization of the 300 Area uranium plume and plan for beginning to implement proposed remedial actions. As part of the RI/FS document, a conceptual model was developed that integrates knowledge of the hydrogeologic and geochemical properties of the 300 Area and controlling processes to yield an understanding of how the system behaves and the variables that control it. Recent results from the Hanford Integrated Field Research Challenge site and the Subsurface Biogeochemistry Scientific Focus Area Project funded by the DOE Office of Science were used to update the conceptual model and provide an assessment of key factors controlling plume persistence.

  17. A Conceptual Model For Effluent-Dependent Riverine Environments

    NASA Astrophysics Data System (ADS)

    Murphy, M. T.; Meyerhoff, R. D.; Osterkamp, W. R.; Smith, E. L.; Hawkins, R. H.

    2001-12-01

    The Arid West Water Quality Research Project (WQRP) is a multi-year, EPA-funded scientific endeavor directed by the Pima County, Wastewater Management Department in southern Arizona and focussed upon several interconnected ecological questions. These questions are crucial to water quality management in the arid and semi arid western US. A key component has been the ecological, hydrological and geomorphological investigation of habitat created by the discharge of treated effluent into ephemeral streams. Such environments are fundamentally different from the dry streams or rivers they displace; however, they are clearly not the perennial streams they superficially resemble. Under Arizona State regulations, such streams can bear the use designation of "Effluent Dependent Waters," or EDWs. Before this investigation, a hydrological/ecological conceptual model for these unique ecosystems had not been published. We have constructed one for general review that is designed to direct future work in the WQRP. The project investigated ten representative, yet contrasting EDW sites distributed throughout arid areas of the western US, to gather both historical and reconnaissance level field data, including in-stream and riparian, habitat and morphometric fluvial data. In most cases, the cross sectional area of the prior channel is oversized relative to the discharge of the introduced effluent. Where bed control is absent, the channels are incised downstream of the discharge point, further suggesting a disequilibrium between the channel and the regulated effluent flow. Several of the studied stream systems primarily convey storm water and are aggradational, exhibiting braided or anastomizing channels, high energy bedforms, and spatially dynamic interfluves. Active channels are formed in response to individual storm events and can be highly dynamic in both location and cross-sectional morphology. This poses a geomorphological challenge in the selection of a discharge point. We

  18. An operational GLS model for hydrologic regression

    USGS Publications Warehouse

    Tasker, Gary D.; Stedinger, J.R.

    1989-01-01

    Recent Monte Carlo studies have documented the value of generalized least squares (GLS) procedures to estimate empirical relationships between streamflow statistics and physiographic basin characteristics. This paper presents a number of extensions of the GLS method that deal with realities and complexities of regional hydrologic data sets that were not addressed in the simulation studies. These extensions include: (1) a more realistic model of the underlying model errors; (2) smoothed estimates of cross correlation of flows; (3) procedures for including historical flow data; (4) diagnostic statistics describing leverage and influence for GLS regression; and (5) the formulation of a mathematical program for evaluating future gaging activities. ?? 1989.

  19. Physical models for classroom teaching in hydrology

    NASA Astrophysics Data System (ADS)

    Rodhe, A.

    2012-09-01

    Hydrology teaching benefits from the fact that many important processes can be illustrated and explained with simple physical models. A set of mobile physical models has been developed and used during many years of lecturing at basic university level teaching in hydrology. One model, with which many phenomena can be demonstrated, consists of a 1.0-m-long plexiglass container containing an about 0.25-m-deep open sand aquifer through which water is circulated. The model can be used for showing the groundwater table and its influence on the water content in the unsaturated zone and for quantitative determination of hydraulic properties such as the storage coefficient and the saturated hydraulic conductivity. It is also well suited for discussions on the runoff process and the significance of recharge and discharge areas for groundwater. The flow paths of water and contaminant dispersion can be illustrated in tracer experiments using fluorescent or colour dye. This and a few other physical models, with suggested demonstrations and experiments, are described in this article. The finding from using models in classroom teaching is that it creates curiosity among the students, promotes discussions and most likely deepens the understanding of the basic processes.

  20. Modeling of surface microtopography and its impacts on hydrologic processes

    NASA Astrophysics Data System (ADS)

    Habtezion, Noah Lebassi

    Understanding the impacts of surface microtopography on hydrologic processes is critical. The objectives of this thesis research are: (1) to evaluate the effects of DEM resolution on microtopographic characteristics, hydrologic connectivity, and modeling of hydrologic processes; and (2) to assess the influences of multiple rainfall events on surface and subsurface hydrologic processes with the use of a puddle-to-puddle (P2P) modeling system. The change in DEM resolution has a significant effect on how surface microtopography is depicted, which in turn alters the hydrologic response of a topographic surface. The smoothing of reduced DEM resolution tends to enhance hydrologic connectivity, reduce the depression storage and infiltration, and increase surface runoff. Temporal rainfall distribution results in spatio-temporal variations in soil water dynamics, depression storage, infiltration, hydrologic connectivity, and surface runoff. The reduction in ponding time and infiltration, and the enhancement of hydrologic connectivity further caused earlier and greater surface runoff generation.

  1. 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.

  2. Hybrid Modelling Approach to Prairie hydrology: Fusing Data-driven and Process-based Hydrological Models

    NASA Astrophysics Data System (ADS)

    Mekonnen, B.; Nazemi, A.; Elshorbagy, A.; Mazurek, K.; Putz, G.

    2012-04-01

    Modeling the hydrological response in prairie regions, characterized by flat and undulating terrain, and thus, large non-contributing areas, is a known challenge. The hydrological response (runoff) is the combination of the traditional runoff from the hydrologically contributing area and the occasional overflow from the non-contributing area. This study provides a unique opportunity to analyze the issue of fusing the Soil and Water Assessment Tool (SWAT) and Artificial Neural Networks (ANNs) in a hybrid structure to model the hydrological response in prairie regions. A hybrid SWAT-ANN model is proposed, where the SWAT component and the ANN module deal with the effective (contributing) area and the non-contributing area, respectively. The hybrid model is applied to the case study of Moose Jaw watershed, located in southern Saskatchewan, Canada. As an initial exploration, a comparison between ANN and SWAT models is established based on addressing the daily runoff (streamflow) prediction accuracy using multiple error measures. This is done to identify the merits and drawbacks of each modeling approach. It has been found out that the SWAT model has better performance during the low flow periods but with degraded efficiency during periods of high flows. The case is different for the ANN model as ANNs exhibit improved simulation during high flow periods but with biased estimates during low flow periods. The modelling results show that the new hybrid SWAT-ANN model is capable of exploiting the strengths of both SWAT and ANN models in an integrated framrwork. The new hybrid SWAT-ANN model simulates daily runoff quite satisfactorily with NSE measures of 0.80 and 0.83 during calibration and validation periods, respectively. Furthermore, an experimental assessment was performed to identify the effects of the ANN training method on the performance of the hybrid model as well as the parametric identifiability. Overall, the results obtained in this study suggest that the fusion

  3. Modeling hydrologic and ecologic responses using a new eco-hydrological model for identification of droughts

    NASA Astrophysics Data System (ADS)

    Sawada, Yohei; Koike, Toshio; Jaranilla-Sanchez, Patricia Ann

    2014-07-01

    Drought severely damages water and agricultural resources, and both hydrological and ecological responses are important for its understanding. First, precipitation deficit induces soil moisture deficiency and high plant water stress causing agricultural droughts. Second, hydrological drought characterized by deficit of river discharge and groundwater follows agricultural drought. However, contributions of vegetation dynamics to these processes at basin scale have not been quantified. To address this issue, we develop an eco-hydrological model that can calculate river discharge, groundwater, energy flux, and vegetation dynamics as diagnostic variables at basin scale within a distributed hydrological modeling framework. The model is applied to drought analysis in the Medjerda River basin. From model inputs and outputs, we calculate drought indices for different drought types. The model shows reliable accuracy in reproducing observed river discharge in long-term (19 year) simulation. Moreover, the drought index calculated from the model-estimated annual peak of leaf area index correlates well (correlation coefficient r = 0.89) with the drought index from nationwide annual crop production, which demonstrates that the modeled leaf area index is capable of representing agricultural droughts related to historical food shortages. We show that vegetation dynamics have a more rapid response to meteorological droughts than river discharge and groundwater dynamics in the Medjerda basin because vegetation dynamics are sensitive to soil moisture in surface layers, whereas soil moisture in deeper layers strongly contributes to streamflow and groundwater level. Our modeling framework can contribute to analyze drought progress, although analyses for other climate conditions are needed.

  4. Evaluating spatial patterns in hydrological modeling

    NASA Astrophysics Data System (ADS)

    Koch, Julian; Stisen, Simon; Høgh Jensen, Karsten

    2014-05-01

    Recent advances in hydrological modeling towards fully distributed grid based model codes, increased availability of spatially distributed data (remote sensing and intensive field studies) and more computational power allow a shift towards a spatial model evaluation away from the traditional aggregated evaluation. The consideration of spatially aggregated observations, in form of river discharge, in the evaluation process does not ensure a correct simulation of catchment-inherent distributed variables. The integration of spatial data and hydrological models is limited due to a lack of suitable metrics to evaluate similarity of spatial patterns. This study is engaged with the development of a novel set of performance metrics that capture spatial patterns and go beyond global statistics. The metrics are required to be easy, flexible and especially targeted to compare observed and simulated spatial patterns of hydrological variables. Four quantitative methodologies for comparing spatial patterns are brought forward: (1) A fuzzy set approach that incorporates both fuzziness of location and fuzziness of category. (2) Kappa statistic that expresses the similarity between two maps based on a contingency table (error matrix). (3) An extended version of (2) by considering both fuzziness in location and fuzziness in category. (4) Increasing the information content of a single cell by aggregating neighborhood cells at different window sizes; then computing mean and standard deviation. The identified metrics are tested on observed and simulated land surface temperature maps in a groundwater dominated catchment in western Denmark. The observed data originates from the MODIS satellite and MIKE SHE, a coupled and fully distributed hydrological model, serves as the modelling tool. Synthetic land surface temperature maps are generated to further address strengths and weaknesses of the metrics. The metrics are tested in different parameter optimizing frameworks, where they are

  5. A multicomponent coupled model of glacier hydrology

    NASA Astrophysics Data System (ADS)

    Flowers, Gwenn Elizabeth

    Multiple lines of evidence suggest a causal link between subglacial hydrology and phenomena such as fast-flowing ice. This evidence includes a measured correlation between water under alpine glaciers and their motion, the presence of saturated sediment beneath Antaxctic ice streams, and geologic signatures of enhanced paleo-ice flow over deformable substrates. The complexity of the glacier bed as a three-component mixture presents an obstacle to unraveling these conundra. Inadequate representations of hydrology, in part, prevent us from closing the gap between empirical descriptions and a comprehensive consistent framework for understanding the dynamics of glacierized systems. I have developed a distributed numerical model that solves equations governing glacier surface runoff, englacial water transport, subglacial drainage, and subsurface groundwater flow. Ablation and precipitation drive the surface model through a temperature-index parameterization. Water is permitted to flow over and off the glacier, or to the bed through a system of crevasses, pipes, and fractures. A macroporous sediment horizon transports subglacial water to the ice margin or to an underlying aquifer. Governing equations are derived from the law of mass conservation and are expressed as a balance between the internal redistribution of water and external sources. Each of the four model components is represented as a two-dimensional, vertically-integrated layer that communicates with its neighbors through water exchange. Stacked together, these layers approximate a three-dimensional system. I tailor the model to Trapridge Glacier, where digital maps of the surface and bed have been derived from ice-penetrating radar data. Observations of subglacial water pressure provide additional constraints on model parameters and a basis for comparison of simulations with real data. Three classical idealizations of glacier geometry are used for simple model experiments. Equilibrium tests emphasize geometric

  6. Attributing spatial patterns of hydrological model performance

    NASA Astrophysics Data System (ADS)

    Eisner, S.; Malsy, M.; Flörke, M.

    2013-12-01

    Global hydrological models and land surface models are used to understand and simulate the global terrestrial water cycle. They are, in particular, applied to assess the current state of global water resources, to identify anthropogenic pressures on the global water system, and to assess impacts of global and climate change on water resources. Especially in data-scarce regions, the growing availability of remote sensing products, e.g. GRACE estimates of changes in terrestrial water storage, evaporation or soil moisture estimates, has added valuable information to force and constrain these models as they facilitate the calibration and validation of simulated states and fluxes other than stream flow at large spatial scales. Nevertheless, observed discharge records provide important evidence to evaluate the quality of water availability estimates and to quantify the uncertainty associated with these estimates. Most large scale modelling approaches are constrained by simplified physical process representations and they implicitly rely on the assumption that the same model structure is valid and can be applied globally. It is therefore important to understand why large scale hydrological models perform good or poor in reproducing observed runoff and discharge fields in certain regions, and to explore and explain spatial patterns of model performance. We present an extensive evaluation of the global water model WaterGAP (Water - Global Assessment and Prognosis) to simulate 20th century discharges. The WaterGAP modeling framework comprises a hydrology model and several water use models and operates in its current version, WaterGAP3, on a 5 arc minute global grid and . Runoff generated on the individual grid cells is routed along a global drainage direction map taking into account retention in natural surface water bodies, i.e. lakes and wetlands, as well as anthropogenic impacts, i.e. flow regulation and water abstraction for agriculture, industry and domestic purposes as

  7. Multi-Objective Calibration of Conceptual and Artificial Neural Network Models for Improved Runoff Forecasting

    NASA Astrophysics Data System (ADS)

    de Vos, N. J.; Rientjes, T. H.; Gupta, H. V.

    2006-12-01

    The forecasting of river discharges and water levels requires models that simulate the transformation of rainfall on a watershed into the runoff. The most popular approach to this complex modeling issue is to use conceptual hydrological models. In recent years, however, data-driven model alternatives have gained significant attention. Such models extract and re-use information that is implicit in hydrological data and do not directly take into account the physical laws that underlie rainfall-runoff processes. In this study, we have made a comparison between a conceptual hydrological model and the popular data-driven approach of Artificial Neural Network (ANN) modeling. ANNs use flexible model structures that simulate rainfall-runoff processes by mapping the transformation from system input and/or system states (e.g., rainfall, evaporation, soil moisture content) to system output (e.g. river discharge). Special attention was paid to the procedure of calibration of both approaches. Singular objective functions based on squared-error-based performance measures, such as the Mean Squared Error (MSE) are commonly used in rainfall-runoff modeling. However, not all differences between modeled and observed hydrograph characteristics can be adequately expressed by a single performance measure. Nowadays it is acknowledged that the calibration of rainfall-runoff models is inherently multi-objective. Therefore, Multi-Objective Evolutionary Algorithms (MOEAs) were tested as alternatives to traditional single-objective algorithms for calibration of both a conceptual and an ANN model for forecasting runoff. The MOEAs compare favorably to traditional single-objective methods in terms of performance, and they shed more light on the trade-offs between various objective functions. Additionally, the distribution of model parameter values gives insights into model parameter uncertainty and model structural deficiencies. Summarizing, the current study presents interesting and promising

  8. Hydrogeologic framework, hydrology, and refined conceptual model of groundwater flow for Coastal Plain aquifers at the Standard Chlorine of Delaware, Inc. Superfund Site, New Castle County, Delaware, 2005-12

    USGS Publications Warehouse

    Brayton, Michael J.; Cruz, Roberto M.; Myers, Luke; Degnan, James R.; Raffensperger, Jeff P.

    2015-01-01

    The regional hydrogeologic framework indicates that the site is underlain by Coastal Plain sediments of the Columbia, Merchantville, and Potomac Formations. Two primary aquifers underlying the site, the Columbia and the upper Potomac, are separated by the Merchantville Formation confining unit. Local groundwater flow in the surficial (Columbia) aquifer is controlled by topography and generally flows northward and discharges to nearby surface water. Regional flow within the Potomac aquifer is towards the southeast, and is strongly influenced by major water withdrawals locally. Previous investigations at the site indicated that contaminants, primarily benzene and chlorinated benzene compounds, were present in the Columbia aquifer in most locations; however, there were only limited detections in the upper Potomac aquifer as of 2004. From 2005 through 2012, the USGS designed a monitoring network, assisted with exploratory drilling, collected data at monitoring wells, conducted geophysical surveys, evaluated water-level responses in wells during pumping of a production well, and evaluated major aquifer withdrawals. Data collected through these efforts were used to refine the local conceptual flow system. The refined conceptual flow system for the site includes: (a) identification of gaps in confining units in the study area, (b) identification and correlation of multiple water-bearing sand intervals within the upper Potomac Formation, (c) connections between groundwater and surface water, (d) connections between shallow and deeper groundwater, (e) new water-level (or potentiometric surface) maps and inferred flow directions, and (f) identification of major local pumping well influences. The implications of the revised conceptual flow system on the occurrence and movement of site contaminants are that the resulting detection of contaminants in the upper Potomac aquifer at specific well locations can be attributed primarily to either advective lateral transport, direct

  9. Hydrology

    ERIC Educational Resources Information Center

    Sharp, John M., Jr.

    1978-01-01

    The past year saw a re-emphasis on the practical aspects of hydrology due to regional drought patterns, urban flooding, and agricultural and energy demands on water resources. Highlights of hydrologic symposia, publications, and events are included. (MA)

  10. Improving Hydrology in Land Ice Models

    NASA Astrophysics Data System (ADS)

    Price, Stephen; Flowers, Gwenn; Schoof, Christian

    2011-05-01

    Community Earth System Model Land Ice Working Group Meeting; Boulder, Colorado, 13 January 2011 ; Recent observations indicate that mass loss from glaciers and ice sheets (“land ice”) is increasing. The drivers of these changes are not well understood, and modeling the land ice response to them remains challenging. As a result, the Intergovernmental Panel on Climate Change explicitly avoided speculating on 21st-century sea level rise from ice dynamical processes in its fourth assessment report. The mismatch between observations of land ice change and model skill at mimicking those changes is behind recent efforts to develop next-generation land ice models. Necessary improvements to existing models include improved dynamics, coupling to climate models, and better representations of important boundary conditions and physical processes. Basal sliding, the primary control on the rate of land ice delivery to the oceans, is one such boundary condition that is largely controlled by land ice hydrology.

  11. Hydrological improvements for nutrient and pollutant emission modeling in large scale catchments

    NASA Astrophysics Data System (ADS)

    Höllering, S.; Ihringer, J.

    2012-04-01

    An estimation of emissions and loads of nutrients and pollutants into European water bodies with as much accuracy as possible depends largely on the knowledge about the spatially and temporally distributed hydrological runoff patterns. An improved hydrological water balance model for the pollutant emission model MoRE (Modeling of Regionalized Emissions) (IWG, 2011) has been introduced, that can form an adequate basis to simulate discharge in a hydrologically differentiated, land-use based way to subsequently provide the required distributed discharge components. First of all the hydrological model had to comply both with requirements of space and time in order to calculate sufficiently precise the water balance on the catchment scale spatially distributed in sub-catchments and with a higher temporal resolution. Aiming to reproduce seasonal dynamics and the characteristic hydrological regimes of river catchments a daily (instead of a yearly) time increment was applied allowing for a more process oriented simulation of discharge dynamics, volume and therefore water balance. The enhancement of the hydrological model became also necessary to potentially account for the hydrological functioning of catchments in regard to scenarios of e.g. a changing climate or alterations of land use. As a deterministic, partly physically based, conceptual hydrological watershed and water balance model the Precipitation Runoff Modeling System (PRMS) (USGS, 2009) was selected to improve the hydrological input for MoRE. In PRMS the spatial discretization is implemented with sub-catchments and so called hydrologic response units (HRUs) which are the hydrotropic, distributed, finite modeling entities each having a homogeneous runoff reaction due to hydro-meteorological events. Spatial structures and heterogeneities in sub-catchments e.g. urbanity, land use and soil types were identified to derive hydrological similarities and classify in different urban and rural HRUs. In this way the

  12. Conceptual hydrogeological model of a coastal hydrosystem in the mediterranean

    NASA Astrophysics Data System (ADS)

    Mitropapas, Anastasios; Pouliaris, Christos; Apostolopoulos, Georgios; Vasileiou, Eleni; Schüth, Christoph; Vienken, Thomas; Dietrich, Peter; Kallioras, Andreas

    2016-04-01

    Groundwater resources management in the Mediterranean basin is an issue of paramount importance that becomes a necessity in the case of the coastal hydrosystems. Coastal aquifers are considered very sensitive ecosystems that are subject to several stresses being of natural or anthropogenic origin. The coastal hydrosystem of Lavrion can be used as a reference site that incorporates multi-disciplinary environmental problems, which are typical for Circum-Mediterranean. This study presents the synthesis of a wide range of field activities within the area of Lavrion including the monitoring of water resources within all hydrologic zones (surface, unsaturated and saturated) and geophysical (invasive and non-invasive) surveys. Different monitoring approaches -targeting to the collection of hydrochemical, geophysical, geological, hydrological data- were applied, that proved to provide a sound characterization of the groundwater flows within the coastal karstic system in connection to the surrounding water bodies of the study area. The above are used as input parameters process during the development of the conceptual model of the coastal hydrosystem of Lavrion. Key-words: Coastal hydrosystems, Mediterranean basin, seawater intrusion

  13. A simple hydrologic model for rapid prediction of runoff from ungauged coastal catchments

    NASA Astrophysics Data System (ADS)

    Wan, Yongshan; Konyha, Kenneth

    2015-09-01

    We developed a lumped conceptual rainfall-runoff model for rapid prediction of runoff generated in the unique hydrological setting with flat terrain, sandy soils, high groundwater table, and a dense drainage canal network in south Florida. The model is conceptualized as rainfall and evapotranspiration filling and emptying the root zone and excess rainfall recharging three storage zones. Outflows from these storage zones, routed with parallel arrangement of three linear reservoirs, represent different flow components of catchment runoff, i.e., slow drainage (shallow subsurface flow), medium drainage (interflow and saturation excess overland flow), and fast drainage (direct runoff from impervious urban areas or from water table management in agricultural land). The model is parsimonious with eight model parameters along with two optional water management parameters. A regionalization study was conducted through model parameterization to achieve target hydrological behavior of typical land uses, which are the most significant basin descriptor affecting catchment hydrology in south Florida. Cross validation with 16 gauged basins dominated by urban, agricultural, and natural lands, respectively, indicated that the model provides an effective tool for rapid prediction of runoff in ungauged basins using the regionalized model parameters. A case study is presented, involving application of the model to support real-time adaptive management to hydrological operations for protection of estuarine ecosystems.

  14. Conceptual models for cumulative risk assessment.

    PubMed

    Linder, Stephen H; Sexton, Ken

    2011-12-01

    In the absence of scientific consensus on an appropriate theoretical framework, cumulative risk assessment and related research have relied on speculative conceptual models. We argue for the importance of theoretical backing for such models and discuss 3 relevant theoretical frameworks, each supporting a distinctive "family" of models. Social determinant models postulate that unequal health outcomes are caused by structural inequalities; health disparity models envision social and contextual factors acting through individual behaviors and biological mechanisms; and multiple stressor models incorporate environmental agents, emphasizing the intermediary role of these and other stressors. The conclusion is that more careful reliance on established frameworks will lead directly to improvements in characterizing cumulative risk burdens and accounting for disproportionate adverse health effects. PMID:22021317

  15. Improving the representation of hydrologic processes in Earth System Models

    NASA Astrophysics Data System (ADS)

    Clark, Martyn P.; Fan, Ying; Lawrence, David M.; Adam, Jennifer C.; Bolster, Diogo; Gochis, David J.; Hooper, Richard P.; Kumar, Mukesh; Leung, L. Ruby; Mackay, D. Scott; Maxwell, Reed M.; Shen, Chaopeng; Swenson, Sean C.; Zeng, Xubin

    2015-08-01

    Many of the scientific and societal challenges in understanding and preparing for global environmental change rest upon our ability to understand and predict the water cycle change at large river basin, continent, and global scales. However, current large-scale land models (as a component of Earth System Models, or ESMs) do not yet reflect the best hydrologic process understanding or utilize the large amount of hydrologic observations for model testing. This paper discusses the opportunities and key challenges to improve hydrologic process representations and benchmarking in ESM land models, suggesting that (1) land model development can benefit from recent advances in hydrology, both through incorporating key processes (e.g., groundwater-surface water interactions) and new approaches to describe multiscale spatial variability and hydrologic connectivity; (2) accelerating model advances requires comprehensive hydrologic benchmarking in order to systematically evaluate competing alternatives, understand model weaknesses, and prioritize model development needs, and (3) stronger collaboration is needed between the hydrology and ESM modeling communities, both through greater engagement of hydrologists in ESM land model development, and through rigorous evaluation of ESM hydrology performance in research watersheds or Critical Zone Observatories. Such coordinated efforts in advancing hydrology in ESMs have the potential to substantially impact energy, carbon, and nutrient cycle prediction capabilities through the fundamental role hydrologic processes play in regulating these cycles.

  16. 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.

  17. Applicability of Hydrologic Landscapes for Model Calibration at the Watershed Scale in the Pacific Northwest

    EPA Science Inventory

    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 tec...

  18. Our evolving conceptual model of the coastal eutrophication problem

    USGS Publications Warehouse

    Cloern, James E.

    2001-01-01

    A primary focus of coastal science during the past 3 decades has been the question: How does anthropogenic nutrient enrichment cause change in the structure or function of nearshore coastal ecosystems? This theme of environmental science is recent, so our conceptual model of the coastal eutrophication problem continues to change rapidly. In this review, I suggest that the early (Phase I) conceptual model was strongly influenced by limnologists, who began intense study of lake eutrophication by the 1960s. The Phase I model emphasized changing nutrient input as a signal, and responses to that signal as increased phytoplankton biomass and primary production, decomposition of phytoplankton-derived organic matter, and enhanced depletion of oxygen from bottom waters. Coastal research in recent decades has identified key differences in the responses of lakes and coastal-estuarine ecosystems to nutrient enrichment. The contemporary (Phase II) conceptual model reflects those differences and includes explicit recognition of (1) system-specific attributes that act as a filter to modulate the responses to enrichment (leading to large differences among estuarine-coastal systems in their sensitivity to nutrient enrichment); and (2) a complex suite of direct and indirect responses including linked changes in: water transparency, distribution of vascular plants and biomass of macroalgae, sediment biogeochemistry and nutrient cycling, nutrient ratios and their regulation of phytoplankton community composition, frequency of toxic/harmful algal blooms, habitat quality for metazoans, reproduction/growth/survival of pelagic and benthic invertebrates, and subtle changes such as shifts in the seasonality of ecosystem functions. Each aspect of the Phase II model is illustrated here with examples from coastal ecosystems around the world. In the last section of this review I present one vision of the next (Phase III) stage in the evolution of our conceptual model, organized around 5

  19. Conceptual Frameworks in the Doctoral Research Process: A Pedagogical Model

    ERIC Educational Resources Information Center

    Berman, Jeanette; Smyth, Robyn

    2015-01-01

    This paper contributes to consideration of the role of conceptual frameworks in the doctoral research process. Through reflection on the two authors' own conceptual frameworks for their doctoral studies, a pedagogical model has been developed. The model posits the development of a conceptual framework as a core element of the doctoral…

  20. A Structural Equation Model of Conceptual Change in Physics

    ERIC Educational Resources Information Center

    Taasoobshirazi, Gita; Sinatra, Gale M.

    2011-01-01

    A model of conceptual change in physics was tested on introductory-level, college physics students. Structural equation modeling was used to test hypothesized relationships among variables linked to conceptual change in physics including an approach goal orientation, need for cognition, motivation, and course grade. Conceptual change in physics…

  1. Conceptual Understanding of Climate Change with a Simple Climate Model

    NASA Astrophysics Data System (ADS)

    Dommenget, Dietmar; Floeter, Janine

    2010-05-01

    The future climate change projections are essentially based on coupled general circulation model (CGCM) simulations, which give a distinct global warming pattern with arctic winter amplification, an equilibrium land-sea warming contrast and an inter-hemispheric warming gradient. While these simulations are the most important tool of the Intergovernmental Panel on Climate Change (IPCC) predictions, the conceptual understanding of these predicted structures of climate change and the causes of their uncertainties is very difficult to reach if only based on these highly complex CGCM simulations. In the study presented here we will introduce a very simple, globally resolved energy balance (GREB) model, which is capable of simulating the main characteristics of global warming. The model shall give a bridge between the strongly simplified energy balance models and the fully coupled 4-dimensional complex CGCMs. It provides a fast tool for the conceptual understanding and development of hypotheses for climate change studies and teaching. It is based on the surface energy balance by very simple representations of solar and thermal radiation, the atmospheric hydrological cycle, sensible turbulent heat flux, the transport by the mean atmospheric circulation and heat exchange with the deeper ocean. It can be run on any PC computer and compute 200yrs climate scenarios within minutes. The simple model's climate sensitivity and the spatial structure of the warming pattern are within the uncertainties of the IPCC models simulations. It is capable of simulating the arctic winter amplification, the equilibrium land-sea warming contrast and the inter-hemispheric warming gradient with good agreement to the IPCC models in amplitude and structure.

  2. 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

  3. Upscaling Empirically Based Conceptualisations to Model Tropical Dominant Hydrological Processes for Historical Land Use Change

    NASA Astrophysics Data System (ADS)

    Toohey, R.; Boll, J.; Brooks, E.; Jones, J.

    2009-12-01

    Surface runoff and percolation to ground water are two hydrological processes of concern to the Atlantic slope of Costa Rica because of their impacts on flooding and drinking water contamination. As per legislation, the Costa Rican Government funds land use management from the farm to the regional scale to improve or conserve hydrological ecosystem services. In this study, we examined how land use (e.g., forest, coffee, sugar cane, and pasture) affects hydrological response at the point, plot (1 m2), and the field scale (1-6ha) to empirically conceptualize the dominant hydrological processes in each land use. Using our field data, we upscaled these conceptual processes into a physically-based distributed hydrological model at the field, watershed (130 km2), and regional (1500 km2) scales. At the point and plot scales, the presence of macropores and large roots promoted greater vertical percolation and subsurface connectivity in the forest and coffee field sites. The lack of macropores and large roots, plus the addition of management artifacts (e.g., surface compaction and a plough layer), altered the dominant hydrological processes by increasing lateral flow and surface runoff in the pasture and sugar cane field sites. Macropores and topography were major influences on runoff generation at the field scale. Also at the field scale, antecedent moisture conditions suggest a threshold behavior as a temporal control on surface runoff generation. However, in this tropical climate with very intense rainstorms, annual surface runoff was less than 10% of annual precipitation at the field scale. Significant differences in soil and hydrological characteristics observed at the point and plot scales appear to have less significance when upscaled to the field scale. At the point and plot scales, percolation acted as the dominant hydrological process in this tropical environment. However, at the field scale for sugar cane and pasture sites, saturation-excess runoff increased as

  4. A Conceptual Model of Referee Efficacy

    PubMed Central

    Guillén, Félix; Feltz, Deborah L.

    2010-01-01

    This paper presents a conceptual model of referee efficacy, defines the concept, proposes sources of referee specific efficacy information, and suggests consequences of having high or low referee efficacy. Referee efficacy is defined as the extent to which referees believe they have the capacity to perform successfully in their job. Referee efficacy beliefs are hypothesized to be influenced by mastery experiences, referee knowledge/education, support from significant others, physical/mental preparedness, environmental comfort, and perceived anxiety. In turn, referee efficacy beliefs are hypothesized to influence referee performance, referee stress, athlete rule violations, athlete satisfaction, and co-referee satisfaction. PMID:21713174

  5. Facet Modelling: An Approach to Flexible and Integrated Conceptual Modelling.

    ERIC Educational Resources Information Center

    Opdahl, Andreas L.; Sindre, Guttorm

    1997-01-01

    Identifies weaknesses of conceptual modelling languages for the problem domain of information systems (IS) development. Outlines an approach called facet modelling of real-world problem domains to deal with the complexity of contemporary analysis problems. Shows how facet models can be defined and visualized; discusses facet modelling in relation…

  6. Propulsion System Models for Rotorcraft Conceptual Design

    NASA Technical Reports Server (NTRS)

    Johnson, Wayne

    2014-01-01

    The conceptual design code NDARC (NASA Design and Analysis of Rotorcraft) was initially implemented to model conventional rotorcraft propulsion systems, consisting of turboshaft engines burning jet fuel, connected to one or more rotors through a mechanical transmission. The NDARC propulsion system representation has been extended to cover additional propulsion concepts, including electric motors and generators, rotor reaction drive, turbojet and turbofan engines, fuel cells and solar cells, batteries, and fuel (energy) used without weight change. The paper describes these propulsion system components, the architecture of their implementation in NDARC, and the form of the models for performance and weight. Requirements are defined for improved performance and weight models of the new propulsion system components. With these new propulsion models, NDARC can be used to develop environmentally-friendly rotorcraft designs.

  7. Bayesian analysis of input uncertainty in hydrological modeling: 2. Application

    NASA Astrophysics Data System (ADS)

    Kavetski, Dmitri; Kuczera, George; Franks, Stewart W.

    2006-03-01

    The Bayesian total error analysis (BATEA) methodology directly addresses both input and output errors in hydrological modeling, requiring the modeler to make explicit, rather than implicit, assumptions about the likely extent of data uncertainty. This study considers a BATEA assessment of two North American catchments: (1) French Broad River and (2) Potomac basins. It assesses the performance of the conceptual Variable Infiltration Capacity (VIC) model with and without accounting for input (precipitation) uncertainty. The results show the considerable effects of precipitation errors on the predicted hydrographs (especially the prediction limits) and on the calibrated parameters. In addition, the performance of BATEA in the presence of severe model errors is analyzed. While BATEA allows a very direct treatment of input uncertainty and yields some limited insight into model errors, it requires the specification of valid error models, which are currently poorly understood and require further work. Moreover, it leads to computationally challenging highly dimensional problems. For some types of models, including the VIC implemented using robust numerical methods, the computational cost of BATEA can be reduced using Newton-type methods.

  8. Simultaneous calibration of hydrological models in geographical space

    NASA Astrophysics Data System (ADS)

    Bárdossy, A.; Huang, Y.; Wagener, T.

    2015-10-01

    Hydrological models are usually calibrated for selected catchments individually using specific performance criteria. This procedure assumes that the catchments show individual behavior. As a consequence, the transfer of model parameters to other ungauged catchments is problematic. In this paper, the possibility of transferring part of the model parameters was investigated. Three different conceptual hydrological models were considered. The models were restructured by introducing a new parameter η which exclusively controls water balances. This parameter was considered as individual to each catchment. All other parameters, which mainly control the dynamics of the discharge (dynamical parameters), were considered for spatial transfer. Three hydrological models combined with three different performance measures were used in four different numerical experiments to investigate this transferability. The first numerical experiment, individual calibration of the models for 15 selected MOPEX catchments, showed that it is difficult to identify which catchments share common dynamical parameters. Parameters of one catchment might be good for another catchment but not reversed. In the second numerical experiment, a common spatial calibration strategy was used. It was explicitly assumed that the catchments share common dynamical parameters. This strategy leads to parameters which perform well on all catchments. A leave one out common calibration showed that in this case a good parameter transfer to ungauged catchments can be achieved. In the third numerical experiment, the common calibration methodology was applied for 96 catchments. Another set of 96 catchments were used to test the transfer of common dynamical parameters. The results show that even a large number of catchments share similar dynamical parameters. The performance is worse than those obtained by individual calibration, but the transfer to ungauged catchments remains possible. The performance of the common

  9. Importance of incorporating agriculture in conceptual rainfall-runoff models

    NASA Astrophysics Data System (ADS)

    de Boer-Euser, Tanja; Hrachowitz, Markus; Winsemius, Hessel; Savenije, Hubert

    2016-04-01

    Incorporating spatially variable information is a frequently discussed option to increase the performance of (semi-)distributed conceptual rainfall-runoff models. One of the methods to do this is by using this spatially variable information to delineate Hydrological Response Units (HRUs) within a catchment. In large parts of Europe the original forested land cover is replaced by an agricultural land cover. This change in land cover probably affects the dominant runoff processes in the area, for example by increasing the Hortonian overland flow component, especially on the flatter and higher elevated parts of the catchment. A change in runoff processes implies a change in HRUs as well. A previous version of our model distinguished wetlands (areas close to the stream) from the remainder of the catchment. However, this configuration was not able to reproduce all fast runoff processes, both in summer as in winter. Therefore, this study tests whether the reproduction of fast runoff processes can be improved by incorporating a HRU which explicitly accounts for the effect of agriculture. A case study is carried out in the Ourthe catchment in Belgium. For this case study the relevance of different process conceptualisations is tested stepwise. Among the conceptualisations are Hortonian overland flow in summer and winter, reduced infiltration capacity due to a partly frozen soil and the relative effect of rainfall and snow smelt in case of this frozen soil. The results show that the named processes can make a large difference on event basis, especially the Hortonian overland flow in summer and the combination of rainfall and snow melt on (partly) frozen soil in winter. However, differences diminish when the modelled period of several years is evaluated based on standard metrics like Nash-Sutcliffe Efficiency. These results emphasise on one hand the importance of incorporating the effects of agricultural in conceptual models and on the other hand the importance of more event

  10. Introduction of LL-IV Distributed Hydrological Model and Applications in DMIP-II

    NASA Astrophysics Data System (ADS)

    Li, L.; Zhang, H.; Yang, M.; Nicholson, A.

    2011-12-01

    Watershed hydrological models are an important tool for understanding hydrological processes on the earth, and they have been developed from empirical models to stochastic models, to lumped conceptual models, and finally to distributed conceptual models. Among them, the distributed hydrological model with physical bases is a great milestone in the development of hydrological models. The Hydrology Laboratory of the US National Weather Service paid high attention to the applications of distributed hydrological models. This department has proposed the Distributed Model Intercomparison Projects (DMIP-I and DMIP-II) since 2001, which made a major contribution to the development of distributed hydrological models. This paper introduces the development of the LL (Lan Li) distributed hydrological model, which produced satisfactory results in both DMIP-I and DIMP-II. LL-IV is the latest version of the LL distributed hydrological model and its basic equations and structures are detailed in this paper. LL-IV, for the first time, derives convection-diffusion equations for the interflow (in both saturated and unsaturated conditions) and underground flow. In addition, this model describes soil humidity, evaporation from soil, infiltration, overland flow, stream flow etc. by convection-diffusion equations. The advantages of using convection-diffusion equations in LL-IV to represent water cycle process for either the vertical change in a single grid or water interchange between grids are as follows: (1) Convection-diffusion equations require fewer variables compared with St. Venant equations. Whole and continuous data of the velocity and water stage, for example, are not usually available for most watersheds, which limits the application of distributed hydrological model. For LL-IV, however, these data are not always necessary when simulating. (2) LL-IV improves computational efficiency and requires less memory space by using convection-diffusion equations which focus mainly on

  11. Does model performance improve with complexity? A case study with three hydrological models

    NASA Astrophysics Data System (ADS)

    Orth, Rene; Staudinger, Maria; Seneviratne, Sonia I.; Seibert, Jan; Zappa, Massimiliano

    2015-04-01

    In recent decades considerable progress has been made in climate model development. Following the massive increase in computational power, models became more sophisti- cated. At the same time also simple conceptual models have advanced. In this study we validate and compare three hydrological models of different complexity to investigate whether their performance varies accordingly. For this purpose we use runoff and also soil moisture measurements, which allow a truly independent validation, from several sites across Switzerland. The models are calibrated in similar ways with the same runoff data. Our results show that the more complex models HBV and PREVAH outperform the simple water balance model (SWBM) in case of runoff but not for soil moisture. Furthermore the most sophisticated PREVAH model shows an added value compared to the HBV model only in case of soil moisture. Focusing on extreme events we find generally improved performance of the SWBM during drought conditions and degraded agreement with observations during wet extremes. For the more complex models we find the opposite behavior, probably because they were primarily developed for predic- tion of runoff extremes. As expected given their complexity, HBV and PREVAH have more problems with over-fitting. All models show a tendency towards better perfor- mance in lower altitudes as opposed to (pre-)alpine sites. The results vary considerably across the investigated sites. In contrast, the different metrics we consider to estimate the agreement between models and observations lead to similar conclusions, indicating that the performance of the considered models is similar at different time scales as well as for anomalies and long-term means. We conclude that added complexity does not necessarily lead to improved performance of hydrological models, and that performance can vary greatly depending on the considered hydrological variable (e.g. runoff vs. soil moisture) or hydrological conditions (floods vs

  12. Does model performance improve with complexity? A case study with three hydrological models

    NASA Astrophysics Data System (ADS)

    Orth, Rene; Staudinger, Maria; Seneviratne, Sonia I.; Seibert, Jan; Zappa, Massimiliano

    2015-04-01

    In recent decades considerable progress has been made in climate model development. Following the massive increase in computational power, models became more sophisticated. At the same time also simple conceptual models have advanced. In this study we validate and compare three hydrological models of different complexity to investigate whether their performance varies accordingly. For this purpose we use runoff and also soil moisture measurements, which allow a truly independent validation, from several sites across Switzerland. The models are calibrated in similar ways with the same runoff data. Our results show that the more complex models HBV and PREVAH outperform the simple water balance model (SWBM) in case of runoff but not for soil moisture. Furthermore the most sophisticated PREVAH model shows an added value compared to the HBV model only in case of soil moisture. Focusing on extreme events we find generally improved performance of the SWBM during drought conditions and degraded agreement with observations during wet extremes. For the more complex models we find the opposite behavior, probably because they were primarily developed for prediction of runoff extremes. As expected given their complexity, HBV and PREVAH have more problems with over-fitting. All models show a tendency towards better performance in lower altitudes as opposed to (pre-) alpine sites. The results vary considerably across the investigated sites. In contrast, the different metrics we consider to estimate the agreement between models and observations lead to similar conclusions, indicating that the performance of the considered models is similar at different time scales as well as for anomalies and long-term means. We conclude that added complexity does not necessarily lead to improved performance of hydrological models, and that performance can vary greatly depending on the considered hydrological variable (e.g. runoff vs. soil moisture) or hydrological conditions (floods vs. droughts).

  13. 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.

  14. Integrating remote sensing, geographic information systems and global positioning system techniques with hydrological modeling

    NASA Astrophysics Data System (ADS)

    Thakur, Jay Krishna; Singh, Sudhir Kumar; Ekanthalu, Vicky Shettigondahalli

    2016-03-01

    Integration of remote sensing (RS), geographic information systems (GIS) and global positioning system (GPS) are emerging research areas in the field of groundwater hydrology, resource management, environmental monitoring and during emergency response. Recent advancements in the fields of RS, GIS, GPS and higher level of computation will help in providing and handling a range of data simultaneously in a time- and cost-efficient manner. This review paper deals with hydrological modeling, uses of remote sensing and GIS in hydrological modeling, models of integrations and their need and in last the conclusion. After dealing with these issues conceptually and technically, we can develop better methods and novel approaches to handle large data sets and in a better way to communicate information related with rapidly decreasing societal resources, i.e. groundwater.

  15. 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

  16. 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

  17. CONCEPTUAL MODELS FOR THE LASSEN HYDROTHERMAL SYSTEM.

    USGS Publications Warehouse

    Ingebritsen, S.E.; Sorey, M.L.

    1987-01-01

    The Lassen hydrothermal system, like a number of other systems in regions of moderate to great topographic relief, includes steam-heated features at higher elevations and high-chloride springs at lower elevations, connected to and fed by a single circulation system at depth. Two conceptual models for such systems are presented. They are similar in several ways: however, there are basic differences in terms of the nature and extent of vapor-dominated conditions beneath the steam-heated features. For some Lassen-like systems, these differences could have environmental and economic implications. Available data do not make it possible to establish a single preferred model for the Lassen system, and the actual system is complex enough that both models may apply to different parts of the system.

  18. A conceptual holding model for veterinary applications.

    PubMed

    Ferrè, Nicola; Kuhn, Werner; Rumor, Massimo; Marangon, Stefano

    2014-05-01

    Spatial references are required when geographical information systems (GIS) are used for the collection, storage and management of data. In the veterinary domain, the spatial component of a holding (of animals) is usually defined by coordinates, and no other relevant information needs to be interpreted or used for manipulation of the data in the GIS environment provided. Users trying to integrate or reuse spatial data organised in such a way, frequently face the problem of data incompatibility and inconsistency. The root of the problem lies in differences with respect to syntax as well as variations in the semantic, spatial and temporal representations of the geographic features. To overcome these problems and to facilitate the inter-operability of different GIS, spatial data must be defined according to a \\"schema\\" that includes the definition, acquisition, analysis, access, presentation and transfer of such data between different users and systems. We propose an application \\"schema\\" of holdings for GIS applications in the veterinary domain according to the European directive framework (directive 2007/2/EC--INSPIRE). The conceptual model put forward has been developed at two specific levels to produce the essential and the abstract model, respectively. The former establishes the conceptual linkage of the system design to the real world, while the latter describes how the system or software works. The result is an application \\"schema\\" that formalises and unifies the information-theoretic foundations of how to spatially represent a holding in order to ensure straightforward information-sharing within the veterinary community. PMID:24893036

  19. Data Modeling & the Infrastructural Nature of Conceptual Tools

    ERIC Educational Resources Information Center

    Lesh, Richard; Caylor, Elizabeth; Gupta, Shweta

    2007-01-01

    The goal of this paper is to demonstrate the infrastructural nature of many modern conceptual technologies. The focus of this paper is on conceptual tools associated with elementary types of data modeling. We intend to show a variety of ways in which these conceptual tools not only express thinking, but also mold and shape thinking. And those ways…

  20. 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

  1. Hydrological model uncertainty assessment in southern Africa

    NASA Astrophysics Data System (ADS)

    Hughes, D. A.; Kapangaziwiri, E.; Sawunyama, T.

    2010-06-01

    The importance of hydrological uncertainty analysis has been emphasized in recent years and there is an urgent need to incorporate uncertainty estimation into water resources assessment procedures used in the southern Africa region. The region is characterized by a paucity of accurate data and limited human resources, but the need for informed development decisions is critical to social and economic development. One of the main sources of uncertainty is related to the estimation of the parameters of hydrological models. This paper proposes a framework for establishing parameter values, exploring parameter inter-dependencies and setting parameter uncertainty bounds for a monthly time-step rainfall-runoff model (Pitman model) that is widely used in the region. The method is based on well-documented principles of sensitivity and uncertainty analysis, but recognizes the limitations that exist within the region (data scarcity and accuracy, model user attitudes, etc.). Four example applications taken from different climate and physiographic regions of South Africa illustrate that the methods are appropriate for generating behavioural stream flow simulations which include parameter uncertainty. The parameters that dominate the model response and their degree of uncertainty vary between regions. Some of the results suggest that the uncertainty bounds will be too wide for effective water resources decision making. Further work is required to reduce some of the subjectivity in the methods and to investigate other approaches for constraining the uncertainty. The paper recognizes that probability estimates of uncertainty and methods to include input climate data uncertainties need to be incorporated into the framework in the future.

  2. Modeling hydrologic processes at the residential scale

    NASA Astrophysics Data System (ADS)

    Xiao, Q.; McPherson, G.; Simpson, J.; Ustin, S.

    2003-12-01

    In California, urbanization has led to polluted runoff, flooding during winter, and water shortages during summer. There is growing interest in application of microscale hydrologic solutions that eliminate storm runoff and conserve water at the source. In this study, a physically-based numerical model was developed to better understand hydrologic processes at the residential scale and the interaction of these processes among different Best Management Practices (BMPs). This model calculates all in-flow and out-flow using an hourly interval over a full year or for specific storm events. Water enters the system via precipitation and irrigation and leaves the system via evapotranspiration, surface and subsurface runoff, and from percolation to groundwater. The model was applied to two single-family residential parcels in Los Angeles. Two years of data collected from the control and treatment sites were used to calibrate and validate the model. More than 97% of storm runoff to the street was eliminated with installation of low-cost BMPs (i.e., rain gutters that direct roof runoff to a lawn retention basin and a driveway interceptor that directs runoff to a drywell in the lawn retention basin). Evaluated individually, the driveway interceptor was the most effective BMP for storm runoff reduction (65%), followed by the rain gutter installation (28%), and lawn converted to retention basin (12%). Installation of an 11 m3 cistern did not substantially reduce runoff, but did provide storage for 9% of annual irrigation demand. Simulated landscape irrigation demand was reduced 53% by increasing efficiency through use of a drip irrigation system for shrubs, and adjusting monthly application rates based on evapotranspirational water demand. The model showed that infiltration and surface runoff processes were particularly sensitive to the soil's physical properties and its effective depth. If the existing loam soil were replaced by clay soil annual runoff discharge to the street

  3. Adapting hydrological model structure to catchment characteristics: A large-sample experiment

    NASA Astrophysics Data System (ADS)

    Addor, Nans; Clark, Martyn P.; Nijssen, Bart

    2016-04-01

    Current hydrological modeling frameworks do not offer a clear way to systematically investigate the relationship between model complexity and model fidelity. The characterization of this relationship has so far relied on comparisons of different modules within the same model or comparisons of entirely different models. This lack of granularity in the differences between the model constructs makes it difficult to pinpoint model features that contribute to good simulations and means that the number of models or modeling hypotheses evaluated is usually small. Here we use flexible modeling frameworks to comprehensively and systematically compare modeling alternatives across the continuum of model complexity. A key goal is to explore which model structures are most adequate for catchments in different hydroclimatic conditions. Starting from conceptual models based on the Framework for Understanding Structural Errors (FUSE), we progressively increase model complexity by replacing conceptual formulations by physically explicit ones (process complexity) and by refining model spatial resolution (spatial complexity) using the newly developed Structure for Unifying Multiple Modeling Alternatives (SUMMA). To investigate how to best reflect catchment characteristics using model structure, we rely on a recently released data set of 671 catchments in the continuous United States. Instead of running hydrological simulations in every catchment, we use clustering techniques to define catchment clusters, run hydrological simulations for representative members of each cluster, develop hypotheses (e.g., when specific process representations have useful explanatory power) and test these hypotheses using other members of the cluster. We thus refine our catchment clustering based on insights into dominant hydrological processes gained from our modeling approach. With this large-sample experiment, we seek to uncover trade-offs between realism and practicality, and formulate general

  4. Turnaround Time Modeling for Conceptual Rocket Engines

    NASA Technical Reports Server (NTRS)

    Nix, Michael; Staton, Eric J.

    2004-01-01

    Recent years have brought about a paradigm shift within NASA and the Space Launch Community regarding the performance of conceptual design. Reliability, maintainability, supportability, and operability are no longer effects of design; they have moved to the forefront and are affecting design. A primary focus of this shift has been a planned decrease in vehicle turnaround time. Potentials for instituting this decrease include attacking the issues of removing, refurbishing, and replacing the engines after each flight. less, it is important to understand the operational affects of an engine on turnaround time, ground support personnel and equipment. One tool for visualizing this relationship involves the creation of a Discrete Event Simulation (DES). A DES model can be used to run a series of trade studies to determine if the engine is meeting its requirements, and, if not, what can be altered to bring it into compliance. Using DES, it is possible to look at the ways in which labor requirements, parallel maintenance versus serial maintenance, and maintenance scheduling affect the overall turnaround time. A detailed DES model of the Space Shuttle Main Engines (SSME) has been developed. Trades may be performed using the SSME Processing Model to see where maintenance bottlenecks occur, what the benefits (if any) are of increasing the numbers of personnel, or the number and location of facilities, in addition to trades previously mentioned, all with the goal of optimizing the operational turnaround time and minimizing operational cost. The SSME Processing Model was developed in such a way that it can easily be used as a foundation for developing DES models of other operational or developmental reusable engines. Performing a DES on a developmental engine during the conceptual phase makes it easier to affect the design and make changes to bring about a decrease in turnaround time and costs.

  5. Can citizen-based observations be assimilated in hydrological models to improve flood prediction?

    NASA Astrophysics Data System (ADS)

    Mazzoleni, Maurizio; Alfonso, Leonardo; Solomatine, Dimitri P.

    2015-04-01

    In the recent years, the continued technological improvement has stimulated the spread of low-cost sensors that can be used to measure hydrological variables by citizens in a more spatially distributed way than classic static physical sensors. However, such measurements have the main characteristics to have irregular arrival time and variable uncertainty. This study presents a Kalman filter based method to integrate citizen-based observations into hydrological models in order to improve flood prediction. The methodology is applied in the Brue catchment, South West of England. In order to estimate the response of the catchment to a given flood event, a lumped conceptual hydrological model is implemented. The measured precipitation values are used as perfect forecast input in the hydrological model. Synthetic streamflow values are used in this study due to the fact that citizen-based observations coming at irregular time steps are not available. The results of this study pointed out how increasing the number of uncertain citizen-based observations within two model time steps can improve the model accuracy leading to a better flood forecast. Therefore, observations uncertainty influences the model accuracy more than the irregular moments in which the streamflow observations are assimilated into the hydrological model. This study is part of the FP7 European Project WeSenseIt Citizen Water Observatory (http://wesenseit.eu/).

  6. Evaluating Conceptual Site Models with Multicomponent Reactive Transport Modeling

    NASA Astrophysics Data System (ADS)

    Dai, Z.; Heffner, D.; Price, V.; Temples, T. J.; Nicholson, T. J.

    2005-05-01

    Modeling ground-water flow and multicomponent reactive chemical transport is a useful approach for testing conceptual site models and assessing the design of monitoring networks. A graded approach with three conceptual site models is presented here with a field case of tetrachloroethene (PCE) transport and biodegradation near Charleston, SC. The first model assumed a one-layer homogeneous aquifer structure with semi-infinite boundary conditions, in which an analytical solution of the reactive solute transport can be obtained with BIOCHLOR (Aziz et al., 1999). Due to the over-simplification of the aquifer structure, this simulation cannot reproduce the monitoring data. In the second approach we used GMS to develop the conceptual site model, a layer-cake multi-aquifer system, and applied a numerical module (MODFLOW and RT3D within GMS) to solve the flow and reactive transport problem. The results were better than the first approach but still did not fit the plume well because the geological structures were still inadequately defined. In the third approach we developed a complex conceptual site model by interpreting log and seismic survey data with Petra and PetraSeis. We detected a major channel and a younger channel, through the PCE source area. These channels control the local ground-water flow direction and provide a preferential chemical transport pathway. Results using the third conceptual site model agree well with the monitoring concentration data. This study confirms that the bias and uncertainty from inadequate conceptual models are much larger than those introduced from an inadequate choice of model parameter values (Neuman and Wierenga, 2003; Meyer et al., 2004). Numerical modeling in this case provides key insight into the hydrogeology and geochemistry of the field site for predicting contaminant transport in the future. Finally, critical monitoring points and performance indicator parameters are selected for future monitoring to confirm system

  7. Uncertainty Analysis of the Ensemble Hydrological Forecasts in the Coupled Meteorological-Hydrological Modelling Environment

    NASA Astrophysics Data System (ADS)

    Xuan, Y.; Cluckie, I. D.

    2006-12-01

    The advances in meso-scale numerical weather predication render hydrologists the capability to incorporate high-resolution NWP directly into flood forecasting systems in order to obtain an extended lead time. However, such a direct application of rainfall outputs from the NWP model can contribute considerable uncertainties to the final river flow forecasts as the uncertainties inherent in the NWP are propagated into hydrological domains and can also be highlighted by the scaling process. In this research, the ensemble hydrological forecasts driven by the ensemble weather prediction are investigated in an effort trying to understand both the potential and the implication of the ensemble rainfall inputs to the hydrological modelling systems in terms of uncertainty propagation. A data-rich catchment facilitated with dense rainguage network as well as high resolution weather radar was chosen to run the ensemble hydrological simulations of a distributed hydrological model driven by the high resolution NWP predictions. The uncertainties of the amount and the location/timing of the rainfall prediction are discussed whith the results showing that: (1) the hydrological model driven by the short-range NWP can produce forecasts comparable with those from a raingauge-driven one; (2) the ensemble hydrological forecast is able to disseminate abundant information with regard to the nature of the weather system and the confidence of the forecast itself; and (3) the uncertainties as well as systematical biases sometimes are significantly large and, as such, extra efforts need to be made to improve the quality of such a system.

  8. Constraining hydrologic models using thermal analysis

    SciTech Connect

    Doughty, Christine; Karasaki, Kenzi

    2002-12-12

    Starting with regional geographic, geologic, hydrologic, geophysical, and meteorological data for the Tono area in Gifu, Japan, we develop a numerical model to simulate subsurface flow and transport in a 4 km by 6 km by 3 km thick fractured granite rock mass overlain by sedimentary layers. Individual fractures are not modeled explicitly. Rather, continuum permeability and porosity distributions are assigned stochastically, based on well-test data and fracture density measurements. The primary goal of the study is to simulate steady-state groundwater flow through the site, then calculate travel times to the model boundaries from specified monitoring points. The lateral boundaries of the model follow topographic features such as ridgelines and rivers. Assigning lateral boundary conditions is a major point of uncertainty in model construction. We evaluate two models with opposing boundary conditions: mostly closed and mostly open boundaries. The two models show vastly different spatial distributions of groundwater flow, so we would like to find a means of choosing the more realistic model. Surface recharge is much larger for the closed model, but field recharge data are of too limited spatial extent to provide a definitive model constraint. Temperature profiles in 16 boreholes show consistent trends with conduction-dominated (linear) temperature profiles below depths of about 300 m. The open and closed models predict strongly different temperature versus depth profiles; with the closed model showing a strong convective signature produced by widespread surface recharge effects to the depth. The open model shows more linear temperature profiles, better agreeing with measurements from the field. Based on this data we can eliminate from consideration the closed model, at least in its present form in which surface recharge penetrates deep into the model.

  9. Combined effects of climate models, hydrological model structures and land use scenarios on hydrological impacts of climate change

    NASA Astrophysics Data System (ADS)

    Karlsson, Ida B.; Sonnenborg, Torben O.; Refsgaard, Jens Christian; Trolle, Dennis; Børgesen, Christen Duus; Olesen, Jørgen E.; Jeppesen, Erik; Jensen, Karsten H.

    2016-04-01

    Impact studies of the hydrological response of future climate change are important for the water authorities when risk assessment, management and adaptation to a changing climate are carried out. The objective of this study was to model the combined effect of land use and climate changes on hydrology for a 486 km2 catchment in Denmark and to evaluate the sensitivity of the results to the choice of hydrological model. Three hydrological models, NAM, SWAT and MIKE SHE, were constructed and calibrated using similar methods. Each model was forced with results from four climate models and four land use scenarios. The results revealed that even though the hydrological models all showed similar performance during calibration, the mean discharge response to climate change varied up to 30%, and the variations were even higher for extreme events (1th and 99th percentile). Land use changes appeared to cause little change in mean hydrological responses and little variation between hydrological models. Differences in hydrological model responses to land use were, however, significant for extremes due to dissimilarities in hydrological model structure and process equations. The climate model choice remained the dominant factor for mean discharge, low and high flows as well as hydraulic head at the end of the century.

  10. Improvements of Physically-Based Hydrological Modelling using the ACRU Agro-Hydrological Modelling System

    NASA Astrophysics Data System (ADS)

    Bonifacio, C. M. T.; Kienzle, S. W.; Xu, W.; Zhang, J.

    2014-12-01

    The uncertainty of future water availability due to climate change in the Upper Oldman River Basin in Alberta, Canada, and downstream users is considered in this study. A changing climate can significantly perturb hydrological response within a region, thereby affecting the available water resources within southern Alberta. The ACRU agro-hydrological modelling system is applied to simulate historical (1950-2010) and future (2041-2070) streamflows and volumes of a major irrigation reservoir. Like many highly complex, process-based distributed models, major limitations include the data availability and data quality at finer spatial resolutions. With the use of a scripting language, certain limitations can be greatly reduced. Three phases of the project will be emphasized. First, the assimilation of solar radiation, relative humidity, sunshine hours and wind speed daily data into the Canadian 10KM daily climate data that contains daily precipitation, maximum and minimum temperature data for the period 1950-2010, so as to enable potential evapotranspiration calculations using the Penman-Monteith equation. Second, the downscaling of five regional climate model (RCM) data to match the 10KM spatial resolution was undertaken. Third, a total of 1722 hydrological response units (HRUs) were delineated within the 4403 km2 large upper Oldman River Basin. In all phases of model input data parameterization and calibration, the automation of known external procedures greatly decreased erroneous model inputs and increased the efficiency of validating the quality of input data to be used within the ACRU model.

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

    NASA Astrophysics Data System (ADS)

    Reusser, D. E.; Buytaert, W.; Vitolo, C.

    2012-04-01

    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. As an example, hydrological libraries could contain: 1. Major representations of hydrological processes such as infiltration, sub-surface runoff and routing algorithms. 2. Scaling functions, for instance to combine remote sensing precipitation fields with rain gauge data 3. Data consistency checks 4. Performance measures. Here we present a beginning for such a library implemented in the high level data programming language R. Currently, Top-model, the abc-Model, HBV, a multi-model ensamble called FUSE, data import routines for WaSiM-ETH as well basic visualization and evaluation tools are implemented. Care is taken to make functions and models compatible with other existing frameworks in hydrology, such as for example Hydromad.

  12. On Developing a Conceptual Modeling Framework for Nitrate Transport in the Subsurface

    NASA Astrophysics Data System (ADS)

    Dwivedi, D.; Mohanty, B. P.

    2012-12-01

    Nitrate is the most ubiquitous contaminant in groundwater. Once nitrate enters the subsurface environment, it is subjected to a variety of coupled hydrological, geochemical, and biological processes. There is significant uncertainty associated with geochemical and microbiological processes due to a lack of easily available data and reactive heterogeneity of the subsurface systems. Since most hydrologic analyses focus exclusively on the optimization of model parameters and ignore inadequate model structure (structural uncertainty), we present a conceptual framework that incorporates different model structures for complex biogeochemical processes. We simulate nitrate transport using a conceptual modeling framework where physical processes (e.g., advection, dispersion) are modeled as deterministic partial differential equations, while bio-chemical processes (e.g., nitrification) are modeled as stochastic differential equations. We focus here on capturing the influence of bio-chemical processes under deterministic hydrological feedbacks on nitrate transport in a 1-D soil column. We also provide an understanding of the nitrate dynamics under perturbed conditions of soil temperature and pH. Results demonstrate that the predictions of ammonium, nitrite, and nitrate by the conceptual modeling framework are in agreement with the analytical solution. Moreover, the conceptual model provides a broader view of the integrated system behavior as it simulates bio-chemical processes in a stochastic framework. Uncertainty analysis shows that there is higher uncertainty in predicting ammonium concentrations in the soil column as compared to nitrate and nitrite concentrations. Soil temperature variations cause nitrification rates to vary along the soil profile and consecutively, nitrate concentrations arrive earlier at greater depths, and ammonium concentrations are smaller along the soil profile. In addition, soil pH variations cause ammonium concentrations reach deeper in the column.

  13. Debates—Perspectives on socio-hydrology: Modeling flood risk as a public policy problem

    NASA Astrophysics Data System (ADS)

    Gober, Patricia; Wheater, Howard S.

    2015-06-01

    Socio-hydrology views human activities as endogenous to water system dynamics; it is the interaction between human and biophysical processes that threatens the viability of current water systems through positive feedbacks and unintended consequences. Di Baldassarre et al. implement socio-hydrology as a flood risk problem using the concept of social memory as a vehicle to link human perceptions to flood damage. Their mathematical model has heuristic value in comparing potential flood damages in green versus technological societies. It can also support communities in exploring the potential consequences of policy decisions and evaluating critical policy tradeoffs, for example, between flood protection and economic development. The concept of social memory does not, however, adequately capture the social processes whereby public perceptions are translated into policy action, including the pivotal role played by the media in intensifying or attenuating perceived flood risk, the success of policy entrepreneurs in keeping flood hazard on the public agenda during short windows of opportunity for policy action, and different societal approaches to managing flood risk that derive from cultural values and economic interests. We endorse the value of seeking to capture these dynamics in a simplified conceptual framework, but favor a broader conceptualization of socio-hydrology that includes a knowledge exchange component, including the way modeling insights and scientific results are communicated to floodplain managers. The social processes used to disseminate the products of socio-hydrological research are as important as the research results themselves in determining whether modeling is used for real-world decision making.

  14. A hydrological model of New Zealand

    NASA Astrophysics Data System (ADS)

    Woods, R. A.; Tarboton, D. G.; Ibbitt, R. P.; Wild, M.; Henderson, R. D.; Turner, R.

    2003-04-01

    We present initial results from a hydrological model of New Zealand, using Topnet, a variant of TOPMODEL, linked to a kinematic wave channel network routing algorithm. This model run uses daily timesteps for the period 1985-2001, and subdivides the country into approximately 35,000 sub-catchments of 7-10 sq km each. The sub-catchments are linked by 55,000 river reaches, which route sub-catchment runoff. The model subcatchments and reaches are defined automatically by DEM analyses, and initial estimates of model parameters are defined by GIS overlay, coupled with purpose-built model assembly code, and lookup tables for model parameters. A daily simulation for 1 year over New Zealand takes two hours on a standard desktop computer. The model is forced by gridded daily rainfall and temperature data, and it calculates daily water balance for each of the sub-catchments (rain, evaporation, throughfall, infiltration, soil drainage, surface runoff, subsurface runoff, and changes in storage in the canopy, root zone, and saturated storage), as well as daily flows in each river reach. The model as currently implemented does not include snow, glaciers, or deep groundwater flow (i.e. across sub-catchment boundaries). The first applications of the model are for developing an annual water balance of New Zealand for the period 1994-2001, at the regional scale, and for driving a high-spatial resolution, daily time-stepping national erosion model. We are moving to further applications for water resource modeling (e.g. impact of abstraction and/or storage), and for flood forecasting, using hourly rainfall from a mesoscale atmospheric model.

  15. A conceptual framework for assessing cumulative impacts on the hydrology of nontidal wetlands

    USGS Publications Warehouse

    Winter, T.C.

    1988-01-01

    Wetlands occur in geologic and hydrologic settings that enhance the accumulation or retention of water. Regional slope, local relief, and permeability of the land surface are major controls on the formation of wetlands by surface-water sources. However, these landscape features also have significant control over groundwater flow systems, which commonly play a role in the formation of wetlands. Because the hydrologic system is a continuum, any modification of one component will have an effect on contiguous components. Disturbances commonly affecting the hydrologic system as it relates to wetlands include weather modification, alteration of plant communities, storage of surface water, road construction, drainage of surface water and soil water, alteration of groundwater recharge and discharge areas, and pumping of groundwater. Assessments of the cumulative effects of one or more of these disturbances on the hydrologic system as related to wetlands must take into account uncertainty in the measurements and in the assumptions that are made in hydrologic studies. For example, it may be appropriate to assume that regional groundwater flow systems are recharged in uplands and discharged in lowlands. However, a similar assumption commonly does not apply on a local scale, because of the spatial and temporal dynamics of groundwater recharge. Lack of appreciation of such hydrologic factors can lead to misunderstanding of the hydrologic function of wetlands within various parts of the landscape and mismanagement of wetland ecosystems. ?? 1988 Springer-Verlag New York Inc.

  16. On the effects of hydrological model structure on soil moisture data assimilation

    NASA Astrophysics Data System (ADS)

    Corato, Giovanni; Matgen, Patrick; Giustarini, Laura; Fenicia, Fabrizio

    2013-04-01

    Nowadays, satellite sensors allow obtaining soil moisture estimates at global scale with an adequate temporal and spatial resolution, thereby offering a theoretical chance to improve flood-forecasting systems based on rainfall-runoff models. In fact, the knowledge of antecedent soil moisture conditions plays a crucial role in predicting catchment response to rainfall events. In the literature, several studies have focused on the assimilation of soil moisture data into hydrological models. The results of these studies tend to show that an improvement in discharge and soil moisture forecasts can be obtained when the assimilated information originates from accurate in situ measurements. When dealing with the assimilation of remote sensing-derived soil moisture data, the reported results are more controversial. There is no doubt that the performances of soil moisture data assimilation studies depend on many factors: data assimilation scheme, hydrological model structure, accuracy and resolution of soil moisture data. As of today, these dependences are not well understood and the disparity of outcomes in past studies arguably reflects the differences in the design of the experiments. In this general context, the aim of this study is to investigate the effects of hydrological model structures on soil moisture data assimilation performance. The analysis focuses on the vertical "stratification" of the soil column in a conceptual hydrological model. We consider multiple structures that differ by the number of soil reservoirs and their respective sizes. The recently introduced SUPERFLEX hydrological modelling framework is used to this end. In fact, this framework allows building and modifying multiple hydrological models by combining three basic building blocks: reservoirs, lag functions and junctions. As a data assimilation scheme, the particle filter was considered. The area of interest is the Alzette catchment (1200 km2), located in Luxembourg, while the analysed period

  17. Identifiability analysis in conceptual sewer modelling.

    PubMed

    Kleidorfer, M; Leonhardt, G; Rauch, W

    2012-01-01

    For a sufficient calibration of an environmental model not only parameter sensitivity but also parameter identifiability is an important issue. In identifiability analysis it is possible to analyse whether changes in one parameter can be compensated by appropriate changes of the other ones within a given uncertainty range. Parameter identifiability is conditional to the information content of the calibration data and consequently conditional to a certain measurement layout (i.e. types of measurements, number and location of measurement sites, temporal resolution of measurements etc.). Hence the influence of number and location of measurement sites on the number of identifiable parameters can be investigated. In the present study identifiability analysis is applied to a conceptual model of a combined sewer system aiming to predict the combined sewer overflow emissions. Different measurement layouts are tested and it can be shown that only 13 of the most sensitive catchment areas (represented by the model parameter 'effective impervious area') can be identified when overflow measurements of the 20 highest overflows and the runoff to the waste water treatment plant are used for calibration. The main advantage of this method is very low computational costs as the number of required model runs equals the total number of model parameters. Hence, this method is a valuable tool when analysing large models with a long runtime and many parameters. PMID:22864432

  18. Flexibility on storage-release based distributed hydrologic modeling with object-oriented approach

    NASA Astrophysics Data System (ADS)

    Kang, Kwangmin; Merwade, Venkatesh; Chun, Jong Ahn; Timlin, Dennis

    2016-09-01

    With the availability of advanced hydrologic data in public domain such as remote 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 water resources management. To address this need, a storage-release based distributed hydrologic model (STORE DHM) is developed based on an object-oriented approach. The model is tested for demonstrating model flexibility and extensibility to know how to well integrate object-oriented approach to further hydrologic research issues, e.g., reconstructing missing precipitation in this study, without changing its main frame. Moreover, the STORE DHM is applied to simulate hydrological processes with multiple classes in the Nanticoke watershed. This study also describes a conceptual and structural framework of object-oriented inheritance and aggregation characteristics under the STORE DHM. In addition, NearestMP (missing value estimation based on nearest neighborhood regression) and KernelMP (missing value estimation based on Kernel Function) are proposed for evaluating STORE DHM flexibility. And then, STORE DHM runoff hydrographs compared with NearestMP and KernelMP runoff hydrographs. Overall results from these comparisons show promising hydrograph outputs generated by the proposed two classes. Consequently, this study suggests that STORE DHM with an object-oriented approach will be a comprehensive water resources modeling tools by adding additional classes for toward developing through its flexibility and extensibility.

  19. Hydrological Modelling of Ganga River basin.

    NASA Astrophysics Data System (ADS)

    Anand, J.; Gosain, A. K.; Khosa, R.

    2015-12-01

    Application of a hydrological model, Soil and Water Assessment Tool (SWAT) to the Ganga basin having a total drainage area of around 1.08 M sq. km extending over Tibet, Nepal, India and Bangladesh has been made. The model is calibrated to determine the spatial deviations in runoff at sub-basin level, and to capture the water balance of the river basin. Manual calibration approach was used for calibrating the SWAT model by following multi-step procedure to get to the realistic present situation as close as possible. Simulations were then further made with and without proposed future projects to obtain various scenarios. The various statistical parameters used for the evaluation of the monthly runoff simulation showed that SWAT performed well in mimicking the monthly stream flow for Ganga River basin. The model under predicted the flows in the non-perennial region during non-monsoon season, due to low rainfall and regulated flows and seepage taking place from the reservoirs. The impacts of the interventions, both existing as well as proposed, on the water balance of the basin were evaluated and quantified. The derived results suggest that there is a substantial reduction in overall water resources availability in the study basin on account of the current level of development and further, future developments, as are being proposed, may require a careful study of their potential impact on currently sanctioned water use. The present study showcases that efficacy of the model for simulating the stream flow is admirable.

  20. A conceptual model of intentional comfort touch.

    PubMed

    Connor, Ann; Howett, Maeve

    2009-06-01

    This article discusses the application and integration of intentional comfort touch as a holistic nursing practice. A review of the literature on touch and its related concepts is included. Although nurses use touch frequently in patient encounters, it is not always used intentionally or deliberately to enhance care. The article compares and contrasts intentional comfort touch with nonintentional or procedural touch. The use of intentional comfort touch in innovative clinical settings with diverse and at-risk populations is described. Based on clinical experiences and the current literature, a conceptual model of intentional comfort touch is proposed. The application of touch is discussed as is the meaning and importance of intentional touch for students, faculty, and patients. PMID:19443699

  1. 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

  2. An integrated hydrologic modeling framework for coupling SWAT with MODFLOW

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The Soil and Water Assessment Tool (SWAT), MODFLOW, and Energy Balance based Evapotranspiration (EB_ET) models are extensively used to estimate different components of the hydrological cycle. Surface and subsurface hydrological processes are modeled in SWAT but limited to the extent of shallow aquif...

  3. 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...

  4. Multi-Objective Calibrationo of Hydrologic Model Using Satellite Data

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Hydrologic modeling often involves a large number of parameters, some of which cannot be measured directly and may vary with land cover, soil or even seasons. Therefore parameter estimation is a critical step in applying a hydrologic model to any study area. Parameter estimation is typically done by...

  5. Modelling the hydrological cycle in assessments of climate change

    NASA Technical Reports Server (NTRS)

    Rind, D.; Rosenzweig, C.; Goldberg, R.

    1992-01-01

    The predictions of climate change studies depend crucially on the hydrological cycles embedded in the different models used. It is shown here that uncertainties in hydrological processes and inconsistencies in both climate and impact models limit confidence in current assessments of climate change. A future course of action to remedy this problem is suggested.

  6. A question driven socio-hydrological modeling process

    NASA Astrophysics Data System (ADS)

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

    2015-08-01

    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 and 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 the choice of modeling structure, scope, and detail. 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 and adaptive to the question context. We demonstrate its utility by exploring a question: 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 periods of water stress are more frequent but less drastic and the additive effect of small adjustments decreases the tendency of the system to overshoot available

  7. Stormwater infiltration trenches: a conceptual modelling approach.

    PubMed

    Freni, Gabriele; Mannina, Giorgio; Viviani, Gaspare

    2009-01-01

    In recent years, limitations linked to traditional urban drainage schemes have been pointed out and new approaches are developing introducing more natural methods for retaining and/or disposing of stormwater. These mitigation measures are generally called Best Management Practices or Sustainable Urban Drainage System and they include practices such as infiltration and storage tanks in order to reduce the peak flow and retain part of the polluting components. The introduction of such practices in urban drainage systems entails an upgrade of existing modelling frameworks in order to evaluate their efficiency in mitigating the impact of urban drainage systems on receiving water bodies. While storage tank modelling approaches are quite well documented in literature, some gaps are still present about infiltration facilities mainly dependent on the complexity of the involved physical processes. In this study, a simplified conceptual modelling approach for the simulation of the infiltration trenches is presented. The model enables to assess the performance of infiltration trenches. The main goal is to develop a model that can be employed for the assessment of the mitigation efficiency of infiltration trenches in an integrated urban drainage context. Particular care was given to the simulation of infiltration structures considering the performance reduction due to clogging phenomena. The proposed model has been compared with other simplified modelling approaches and with a physically based model adopted as benchmark. The model performed better compared to other approaches considering both unclogged facilities and the effect of clogging. On the basis of a long-term simulation of six years of rain data, the performance and the effectiveness of an infiltration trench measure are assessed. The study confirmed the important role played by the clogging phenomenon on such infiltration structures. PMID:19587416

  8. A Conceptual Modeling Approach for OLAP Personalization

    NASA Astrophysics Data System (ADS)

    Garrigós, Irene; Pardillo, Jesús; Mazón, Jose-Norberto; Trujillo, Juan

    Data warehouses rely on multidimensional models in order to provide decision makers with appropriate structures to intuitively analyze data with OLAP technologies. However, data warehouses may be potentially large and multidimensional structures become increasingly complex to be understood at a glance. Even if a departmental data warehouse (also known as data mart) is used, these structures would be also too complex. As a consequence, acquiring the required information is more costly than expected and decision makers using OLAP tools may get frustrated. In this context, current approaches for data warehouse design are focused on deriving a unique OLAP schema for all analysts from their previously stated information requirements, which is not enough to lighten the complexity of the decision making process. To overcome this drawback, we argue for personalizing multidimensional models for OLAP technologies according to the continuously changing user characteristics, context, requirements and behaviour. In this paper, we present a novel approach to personalizing OLAP systems at the conceptual level based on the underlying multidimensional model of the data warehouse, a user model and a set of personalization rules. The great advantage of our approach is that a personalized OLAP schema is provided for each decision maker contributing to better satisfy their specific analysis needs. Finally, we show the applicability of our approach through a sample scenario based on our CASE tool for data warehouse development.

  9. 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

  10. Hydrology

    ERIC Educational Resources Information Center

    Sharp, John M.

    1977-01-01

    Lists many recent research projects in hydrology, including flow in fractured media, improvements in remote-sensing techniques, effects of urbanization on water resources, and developments in drainage basins. (MLH)

  11. NADM Conceptual Model 1.0 -- A Conceptual Model for Geologic Map Information

    USGS Publications Warehouse

    North American Geologic Map Data Model (NADM) Steering Committee Data Model Design Team

    2004-01-01

    Executive Summary -- The NADM Data Model Design Team was established in 1999 by the North American Geologic Map Data Model Steering Committee (NADMSC) with the purpose of drafting a geologic map data model for consideration as a standard for developing interoperable geologic map-centered databases by state, provincial, and federal geological surveys. The model is designed to be a technology-neutral conceptual model that can form the basis for a web-based interchange format using evolving information technology (e.g., XML, RDF, OWL), and guide implementation of geoscience databases in a common conceptual framework. The intended purpose is to allow geologic information sharing between geologic map data providers and users, independent of local information system implementation. The model emphasizes geoscience concepts and relationships related to information presented on geologic maps. Design has been guided by an informal requirements analysis, documentation of existing databases, technology developments, and other standardization efforts in the geoscience and computer-science communities. A key aspect of the model is the notion that representation of the conceptual framework (ontology) that underlies geologic map data must be part of the model, because this framework changes with time and understanding, and varies between information providers. The top level of the model distinguishes geologic concepts, geologic representation concepts, and metadata. The geologic representation part of the model provides a framework for representing the ontology that underlies geologic map data through a controlled vocabulary, and for establishing the relationships between this vocabulary and a geologic map visualization or portrayal. Top-level geologic classes in the model are Earth material (substance), geologic unit (parts of the Earth), geologic age, geologic structure, fossil, geologic process, geologic relation, and geologic event.

  12. 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

  13. 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

  14. Improvement of Continuous Hydrologic Models and HMS SMA Parameters Reduction

    NASA Astrophysics Data System (ADS)

    Rezaeian Zadeh, Mehdi; Zia Hosseinipour, E.; Abghari, Hirad; Nikian, Ashkan; Shaeri Karimi, Sara; Moradzadeh Azar, Foad

    2010-05-01

    Hydrological models can help us to predict stream flows and associated runoff volumes of rainfall events within a watershed. There are many different reasons why we need to model the rainfall-runoff processes of for a watershed. However, the main reason is the limitation of hydrological measurement techniques and the costs of data collection at a fine scale. Generally, we are not able to measure all that we would like to know about a given hydrological systems. This is very particularly the case for ungauged catchments. Since the ultimate aim of prediction using models is to improve decision-making about a hydrological problem, therefore, having a robust and efficient modeling tool becomes an important factor. Among several hydrologic modeling approaches, continuous simulation has the best predictions because it can model dry and wet conditions during a long-term period. Continuous hydrologic models, unlike event based models, account for a watershed's soil moisture balance over a long-term period and are suitable for simulating daily, monthly, and seasonal streamflows. In this paper, we describe a soil moisture accounting (SMA) algorithm added to the hydrologic modeling system (HEC-HMS) computer program. As is well known in the hydrologic modeling community one of the ways for improving a model utility is the reduction of input parameters. The enhanced model developed in this study is applied to Khosrow Shirin Watershed, located in the north-west part of Fars Province in Iran, a data limited watershed. The HMS SMA algorithm divides the potential path of rainfall onto a watershed into five zones. The results showed that the output of HMS SMA is insensitive with the variation of many parameters such as soil storage and soil percolation rate. The study's objective is to remove insensitive parameters from the model input using Multi-objective sensitivity analysis. Keywords: Continuous Hydrologic Modeling, HMS SMA, Multi-objective sensitivity analysis, SMA Parameters

  15. Global scale hydrology - Advances in land surface modeling

    SciTech Connect

    Wood, E.F. )

    1991-01-01

    Research into global scale hydrology is an expanding area that includes researchers from the meteorology, climatology, ecology and hydrology communities. This paper reviews research in this area carried out in the United States during the last IUGG quadrennial period of 1987-1990. The review covers the representation of land-surface hydrologic processes for general circulation models (GCMs), sensitivity analysis of these representations on global hydrologic fields like precipitation, regional studies of climate that have global hydrologic implications, recent field studies and experiments whose aims are the improved understanding of land surface-atmospheric interactions, and the use of remotely sensed data for the further understanding of the spatial variability of surface hydrologic processes that are important at regional and global climate scales. 76 refs.

  16. Parameter dimensionality reduction of a conceptual model for streamflow prediction in Canadian, snowmelt dominated ungauged basins

    NASA Astrophysics Data System (ADS)

    Arsenault, Richard; Poissant, Dominique; Brissette, François

    2015-11-01

    This paper evaluated the effects of parametric reduction of a hydrological model on five regionalization methods and 267 catchments in the province of Quebec, Canada. The Sobol' variance-based sensitivity analysis was used to rank the model parameters by their influence on the model results and sequential parameter fixing was performed. The reduction in parameter correlations improved parameter identifiability, however this improvement was found to be minimal and was not transposed in the regionalization mode. It was shown that 11 of the HSAMI models' 23 parameters could be fixed with little or no loss in regionalization skill. The main conclusions were that (1) the conceptual lumped models used in this study did not represent physical processes sufficiently well to warrant parameter reduction for physics-based regionalization methods for the Canadian basins examined and (2) catchment descriptors did not adequately represent the relevant hydrological processes, namely snow accumulation and melt.

  17. A comparison of alternative multiobjective calibration strategies for hydrological modeling

    NASA Astrophysics Data System (ADS)

    Fenicia, Fabrizio; Savenije, Hubert H. G.; Matgen, Patrick; Pfister, Laurent

    2007-03-01

    A conceptual hydrological model structure contains several parameters that have to be estimated through matching observed and modeled watershed behavior in a calibration process. The requirement that a model simulation matches different aspects of system response at the same time has led the calibration problem toward a multiobjective approach. In this work we compare two multiobjective calibration approaches, each of which represents a different calibration philosophy. The first calibration approach is based on the concept of Pareto optimality and consists of calibrating all parameters with respect to a common set of objectives in one calibration stage. This approach results in a set of Pareto-optimal solutions representing the trade-offs between the selected calibration objectives. The second is a stepped calibration approach (SCA), which implies a stepwise calibration of sets of parameters that are associated with specific aspects of the system response. This approach replicates the steps followed by a hydrologist in manual calibration and develops a single solution. The comparison is performed considering the same set of objectives for the two approaches and two model structures of a different level of complexity. The difference in the two approaches, their reciprocal utility, and the practical implications involved in their application are analyzed and discussed using the Hesperange catchment case, an experimental basin in the Alzette River basin in Luxembourg. We show that the two approaches are not necessarily conflicting but can be complementary. The first approach provides useful information about the deficiencies of a model structure and therefore helps the model development, while the second attempts at determining a solution that is consistent with the data available. We also show that with increasing model complexity it becomes possible to reproduce the observations more accurately. As a result, the solutions for the different calibration objectives

  18. Hydrological appraisal of operational weather radar rainfall estimates in the context of different modelling structures

    NASA Astrophysics Data System (ADS)

    Zhu, D.; Xuan, Y.; Cluckie, I.

    2014-01-01

    Radar rainfall estimates have become increasingly available for hydrological modellers over recent years, especially for flood forecasting and warning over poorly gauged catchments. However, the impact of using radar rainfall as compared with conventional raingauge inputs, with respect to various hydrological model structures, remains unclear and yet to be addressed. In the study presented by this paper, we analysed the flow simulations of the upper Medway catchment of southeast England using the UK NIMROD radar rainfall estimates, using three hydrological models based upon three very different structures (e.g. a physically based distributed MIKE SHE model, a lumped conceptual model PDM and an event-based unit hydrograph model PRTF). We focused on the sensitivity of simulations in relation to the storm types and various rainfall intensities. The uncertainty in radar rainfall estimates, scale effects and extreme rainfall were examined in order to quantify the performance of the radar. We found that radar rainfall estimates were lower than raingauge measurements in high rainfall rates; the resolutions of radar rainfall data had insignificant impact at this catchment scale in the case of evenly distributed rainfall events but was obvious otherwise for high-intensity, localised rainfall events with great spatial heterogeneity. As to hydrological model performance, the distributed model had consistent reliable and good performance on peak simulation with all the rainfall types tested in this study.

  19. Hydrological appraisal of operational weather radar rainfall estimates in the context of different modelling structures

    NASA Astrophysics Data System (ADS)

    Zhu, D.; Xuan, Y.; Cluckie, I.

    2013-08-01

    Radar rainfall estimates have become increasingly available for hydrological modellers over recent years, especially for flood forecasting and warning over poorly gauged catchments. However, the impact of using radar rainfall as compared with conventional raingauge inputs, with respect to various hydrological model structures, remains unclear and yet to be addressed. In the study presented by this paper, we analysed the flow simulations of the Upper Medway catchment of Southeast England using the UK NIMROD radar rainfall estimates using three hydrological models based upon three very different structures, e.g. a physically based distributed MIKE SHE model, a lumped conceptual model PDM and an event-based unit hydrograph model PRTF. We focused on the sensitivity of simulations in relation to the storm types and various rainfall intensities. The uncertainty in radar-rainfall estimates, scale effects and extreme rainfall were examined in order to quantify the performance of the radar. We found that radar rainfall estimates were lower than raingauge measurements in high rainfall rates; the resolutions of radar rainfall data had insignificant impact at this catchment scale in the case of evenly distributed rainfall events but was obvious otherwise for high-intensity, localised rainfall events with great spatial heterogeneity. As to hydrological model performance, the distributed model had consistent reliable and good performance on peak simulation with all the rainfall types tested in this study.

  20. Precipitation-centered Conceptual Model for Sub-humid Uplands in Lampasas Cut Plains, TX

    NASA Astrophysics Data System (ADS)

    Potter, S. R.; Tu, M.; Wilcox, B. P.

    2011-12-01

    Conceptual understandings of dominant hydrological processes, system interactions and feedbacks, and external forcings operating within catchments often defy simple definition and explanation, especially catchments encompassing transition zones, degraded landscapes, rapid development, and where climate forcings exhibit large variations across time and space. However, it is precisely those areas for which understanding and knowledge are most needed to innovate sustainable management strategies and counter past management blunders and failed restoration efforts. The cut plain of central Texas is one such area. Complex geographic and climatic factors lead to spatially and temporally variable precipitation having frequent dry periods interrupted by intense high-volume precipitation. Fort Hood, an army post located in the southeast cut plain contains landscapes ranging from highly degraded to nearly pristine with a topography mainly comprised of flat-topped mesas separated by broad u-shaped valleys. To understand the hydrology of the area and responses to wet-dry cycles we analyzed 4-years of streamflow and rainfall from 8 catchments, sized between 1819 and 16,000 ha. Since aquifer recharge/discharge and surface stream-groundwater interactions are unimportant, we hypothesized a simple conceptual model driven by precipitation and radiative forcings and having stormflow, baseflow, ET, and two hypothetical storage components. The key storage component was conceptualized as a buffer that was highly integrated with the ET component and exerted controls on baseflow. Radiative energy controlled flux from the buffer to ET. We used the conceptual model in making a bimonthly hydrologic budget, which included buffer volumes and a deficit-surplus indicator. Through the analysis, we were led to speculate that buffer capacity plays key roles in these landscapes and even relatively minor changes in capacity, due to soil compaction for example, might lead to ecological shifts. The

  1. Ecohydrologic Response of a Wetland Indicator Species to Climate Change and Streamflow Regulation: A Conceptual Model

    NASA Astrophysics Data System (ADS)

    Ward, E. M.; Gorelick, S.

    2015-12-01

    The Peace-Athabasca Delta ("Delta") in northeastern Alberta, Canada, is a UNESCO World Heritage Site and a Ramsar Wetland of International Importance. Delta ecohydrology is expected to respond rapidly to upstream water demand and climate change, with earlier spring meltwater, decreased springtime peak flow, and a decline in springtime ice-jam flooding. We focus on changes in the population and distribution of muskrat (Ondatra zibethicus), an ecohydrologic indicator species. We present a conceptual model linking hydrology and muskrat ecology. Our conceptual model links seven modules representing (1) upstream water demand, (2) streamflow and snowmelt, (3) floods, (4) the water balance of floodplain lakes, (5) muskrat habitat suitability, (6) wetland vegetation, and (7) muskrat population dynamics predicted using an agent-based model. Our goal is to evaluate the effects of different climate change and upstream water demand scenarios on the abundance and distribution of Delta muskrat, from present-2100. Moving from the current conceptual model to a predictive quantitative model, we will rely on abundant existing data and Traditional Ecological Knowledge of muskrat and hydrology in the Delta.

  2. Hydrology

    NASA Astrophysics Data System (ADS)

    Brutsaert, Wilfried

    2005-08-01

    Water in its different forms has always been a source of wonder, curiosity and practical concern for humans everywhere. Hydrology - An Introduction presents a coherent introduction to the fundamental principles of hydrology, based on the course that Wilfried Brutsaert has taught at Cornell University for the last thirty years. Hydrologic phenomena are dealt with at spatial and temporal scales at which they occur in nature. The physics and mathematics necessary to describe these phenomena are introduced and developed, and readers will require a working knowledge of calculus and basic fluid mechanics. The book will be invaluable as a textbook for entry-level courses in hydrology directed at advanced seniors and graduate students in physical science and engineering. In addition, the book will be more broadly of interest to professional scientists and engineers in hydrology, environmental science, meteorology, agronomy, geology, climatology, oceanology, glaciology and other earth sciences. Emphasis on fundamentals Clarification of the underlying physical processes Applications of fluid mechanics in the natural environment

  3. Conceptual Model of Water Resources in the Kabul Basin, Afghanistan

    USGS Publications Warehouse

    Mack, Thomas J.; Akbari, M. Amin; Ashoor, M. Hanif; Chornack, Michael P.; Coplen, Tyler B.; Emerson, Douglas G.; Hubbard, Bernard E.; Litke, David W.; Michel, Robert L.; Plummer, L. Niel; Rezai, M. Taher; Senay, Gabriel B.; Verdin, James P.; Verstraeten, Ingrid M.

    2010-01-01

    The United States (U.S.) Geological Survey has been working with the Afghanistan Geological Survey and the Afghanistan Ministry of Energy and Water on water-resources investigations in the Kabul Basin under an agreement supported by the United States Agency for International Development. This collaborative investigation compiled, to the extent possible in a war-stricken country, a varied hydrogeologic data set and developed limited data-collection networks to assist with the management of water resources in the Kabul Basin. This report presents the results of a multidisciplinary water-resources assessment conducted between 2005 and 2007 to address questions of future water availability for a growing population and of the potential effects of climate change. Most hydrologic and climatic data-collection activities in Afghanistan were interrupted in the early 1980s as a consequence of war and civil strife and did not resume until 2003 or later. Because of the gap of more than 20 years in the record of hydrologic and climatic observations, this investigation has made considerable use of remotely sensed data and, where available, historical records to investigate the water resources of the Kabul Basin. Specifically, this investigation integrated recently acquired remotely sensed data and satellite imagery, including glacier and climatic data; recent climate-change analyses; recent geologic investigations; analysis of streamflow data; groundwater-level analysis; surface-water- and groundwater-quality data, including data on chemical and isotopic environmental tracers; and estimates of public-supply and agricultural water uses. The data and analyses were integrated by using a simplified groundwater-flow model to test the conceptual model of the hydrologic system and to assess current (2007) and future (2057) water availability. Recharge in the basin is spatially and temporally variable and generally occurs near streams and irrigated areas in the late winter and early

  4. Importance of temporal and spatial resolution on modelling hydrological extremes in a small catchment

    NASA Astrophysics Data System (ADS)

    Strouhal, L.; Seibert, J.; David, V.

    2012-04-01

    Under the conditions of changing climate the more frequent extremes in hydrological regime are expected. For the small watershed management it is therefore of big interest what the possible range of these changes could be, since it is essential for design of appropriate mitigation measures. An exemplary case study of possible impacts of the climate change was carried out. The conceptual model HBV was applied in a small hilly pre-alpine Rietholzbach catchment with the aim to assess the frequency and magnitude of hydrological extremes under different climatic conditions. The effect of the time and spatial distribution on the model output characteristics was also investigated. For impact evaluation a conceptual lumped model HBV was chosen because of its robustness, easy applicability for long-term simulations and perceptually straight-forward parameters. Two different modelling approaches were used, in the first one the catchment of interest was treated as a lumped system and in the other where it was divided into several subcatchments. As a first step HBV was applied to the historical data set to evaluate his performance and suitability for hydrological predictions. One half of the data time-series was used for HBV parameter calibration, the other one for model validation, wherefore several objective functions were used for goodness of fit evaluation. In order to obtain the range of changes in hydrological characteristics which can be expected due to the changing climate, two extreme scenarios were then applied to the catchment model. A standard daily step was used to obtain data for water balance and long-term droughts analysis and a study of applicability of the model with the hourly computational step was performed, so that occurrance of maximum discharges could be evaluated. The poster presents the model outcomes with focus on flood and long-drought characteristics. The uncertainty of the impacts is illustrated by the range of characteristics obtained from

  5. How far can we go in hydrological modelling without any knowledge of runoff formation processes?

    NASA Astrophysics Data System (ADS)

    Ayzel, Georgy

    2016-04-01

    Hydrological modelling is a challenging scientific issue for the last 50 years and tend to be it further because of the highest level of runoff formation processes complexity at the different spatio-temporal scales. Enormous number of modelling-related papers have submitted to the top-ranked journals every year, but in this publication speed race authors have pay increasing attention to the models and data they use by itself rather than underlying watershed processes. Great community effort of the free and open-source models sharing with high availability of hydrometeorological data sources led to conceptual shifting paradigm of hydrological science to the technical-oriented direction. In the third-world countries this shifting is more clear by the reason of field studies absence and obligatory requirement of practical significance of the research supported by the government funds. As a result we get a state of hydrological modelling discipline closer to the aim of high Nash-Sutcliffe efficiency (NSE) achievement rather than watershed processes understanding. Both lumped physically-based land-surface model SWAP (Soil Water - Atmosphere - Plants) and SCE-UA (Shuffled Complex Evolution method developed at The University of Arizona) technique for robust model parameters search were used for the runoff modelling of 323 MOPEX watersheds. No one special data analysis and expert knowledge-based decisions were not performed. Median value of NSE is 0.652 and 90% of watersheds have efficiency bigger than 0.5. Thus without any information of particular features of each watershed satisfactory modelling results were obtained. To prove our conclusions we build cutting-edge conceptual rainfall-runoff model based on decision trees and adaptive boosting machine learning algorithms for the one small watershed in USA. No one special data analysis or feature engineering was not performed too. Obtained results demonstrate great model prediction power both for learning and testing

  6. The quest for knowledge: to what extent can transparent modelling methodologies extract useful hydrological information?

    NASA Astrophysics Data System (ADS)

    Abrahart, R. J.; Ghani, N. Ab; Shamseldin, A. Y.

    2009-04-01

    The capabilities of two transparent modelling methodologies to extract useful hydrological information is reported. Experimental emulators were constructed in a controlled environment that comprised digital inputs and outputs for a simple conceptual rainfall-runoff model: the Xinanjiang Rainfall-Runoff Model (Zhao et al., 1980; Zhao, 1992). This model was designed for use in humid or semi-humid regions and is based on the concept of runoff formation on repletion of storage i.e. runoff is not produced until the soil moisture content of the aeration zone reaches field storage capacity and thereafter runoff equals rainfall excess without further loss. It has been applied with success to large areas including all of the agricultural, pastoral and forested lands [except for the loess] of China (Zhao & Liu, 1995, p.230). The model has a small number of parameters, its structure and components have strong physical meaning, and these factors in combination make it a popular tool for hydrological modelling. Two methods were used to develop a set of transparent emulators: ANFIS (Adaptive Neuro-Fuzzy Inference System) and GEP (Gene Expression Programming). The simplest form of the conceptual model that required four inputs and had no temporal component was examined. Model inputs comprised a set of uniform random distributions that had been computed in a statistical package and the cloning operation facilitated a direct comparison with the exact equation-based relationship. The potential of each tool to perform simple non-linear hydrological transformations is evaluated as is the power of each individual method to capture and communicate important aspects of a recognised non-linear hydrological modelling equation.

  7. Conceptualizing Telehealth in Nursing Practice: Advancing a Conceptual Model to Fill a Virtual Gap.

    PubMed

    Nagel, Daniel A; Penner, Jamie L

    2016-03-01

    Increasingly nurses use various telehealth technologies to deliver health care services; however, there has been a lag in research and generation of empirical knowledge to support nursing practice in this expanding field. One challenge to generating knowledge is a gap in development of a comprehensive conceptual model or theoretical framework to illustrate relationships of concepts and phenomena inherent to adoption of a broad range of telehealth technologies to holistic nursing practice. A review of the literature revealed eight published conceptual models, theoretical frameworks, or similar entities applicable to nursing practice. Many of these models focus exclusively on use of telephones and four were generated from qualitative studies, but none comprehensively reflect complexities of bridging nursing process and elements of nursing practice into use of telehealth. The purpose of this article is to present a review of existing conceptual models and frameworks, discuss predominant themes and features of these models, and present a comprehensive conceptual model for telehealth nursing practice synthesized from this literature for consideration and further development. This conceptual model illustrates characteristics of, and relationships between, dimensions of telehealth practice to guide research and knowledge development in provision of holistic person-centered care delivery to individuals by nurses through telehealth technologies. PMID:25858897

  8. A CONCEPTUAL FRAMEWORK FOR ASSESSING CUMULATIVE IMPACTS ON THE HYDROLOGY OF NON-TIDAL WETLANDS

    EPA Science Inventory

    Wetlands occur in geologic and hydrologic settings that enhance the accumulation or retention of water. egional slope, local relief, and permeability of the land surface are major controls on the formation of wetlands by surface-water sources. owever, these landscape features als...

  9. Comparing Sediment Yield Predictions from Different Hydrologic Modeling Schemes

    NASA Astrophysics Data System (ADS)

    Dahl, T. A.; Kendall, A. D.; Hyndman, D. W.

    2015-12-01

    Sediment yield, or the delivery of sediment from the landscape to a river, is a difficult process to accurately model. It is primarily a function of hydrology and climate, but influenced by landcover and the underlying soils. These additional factors make it much more difficult to accurately model than water flow alone. It is not intuitive what impact different hydrologic modeling schemes may have on the prediction of sediment yield. Here, two implementations of the Modified Universal Soil Loss Equation (MUSLE) are compared to examine the effects of hydrologic model choice. Both the Soil and Water Assessment Tool (SWAT) and the Landscape Hydrology Model (LHM) utilize the MUSLE for calculating sediment yield. SWAT is a lumped parameter hydrologic model developed by the USDA, which is commonly used for predicting sediment yield. LHM is a fully distributed hydrologic model developed primarily for integrated surface and groundwater studies at the watershed to regional scale. SWAT and LHM models were developed and tested for two large, adjacent watersheds in the Great Lakes region; the Maumee River and the St. Joseph River. The models were run using a variety of single model and ensemble downscaled climate change scenarios from the Coupled Model Intercomparison Project 5 (CMIP5). The initial results of this comparison are discussed here.

  10. Hydrological modeling of the Jiaoyi watershed (China) using HSPF model.

    PubMed

    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

  11. 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 (R2), 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

  12. 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

  13. Are Dynamically Evolving Models the Future of Hydrologic Modelling? A Data Assimilation Approach

    NASA Astrophysics Data System (ADS)

    Pathiraja, S. D.; Marshall, L. A.; Sharma, A.; Moradkhani, H.

    2014-12-01

    Can a single model adequately represent a catchment's runoff response? Is it possible to design a modelling framework that can adequately represent catchment processes now and in the future? These are just a few of the questions related to catchment modelling that continue to intrigue hydrologists. An appreciation of catchment non-stationarity is critical to answering these questions. However this has been given little consideration in the past. Typically a single model parameterisation is adopted and assumed to be adequate outside the period of calibration/validation. We present a novel method for dealing with catchment non stationarity that allows model parameterisations to evolve in time through a Data Assimilation framework. Data Assimilation for hydrologic parameter estimation has mainly focused on deriving a stationary parameter distribution. We investigate the potential for Data Assimilation to estimate time varying model parameters, an application which has not been examined before in the hydrologic sciences. This is undertaken using the popular Ensemble Kalman Filter with the Probability Distributed Model (PDM), a lumped conceptual hydrologic model. It is shown that careful consideration of the artificial parameter evolution step is critical in this context. A range of traditional artificial parameter evolution techniques are considered and found to be problematic when parameters exhibit temporal variability. A new hierarchical approach is presented that relies on a more meaningful description of parameter evolution to improve the prior parameter distribution. The hierarchical approach is applied to multiple known case studies and shown to produce superior results when compared to traditional parameter evolution techniques. This method provides a general framework for establishing dynamically evolving models that will be particularly useful for rapidly changing catchments.

  14. Assessment of Model Parameters Interdependency of a Conceptual Rainfall-Runoff Model

    NASA Astrophysics Data System (ADS)

    Das, T.; Bárdossy, A.; Zehe, E.

    2006-12-01

    Conceptual rainfall-runoff models are widely used tools in hydrology. Contrary to more complex physically- based distributed models, the required input data are readily available for most applications in the world. In addition to their modest data requirement, conceptual models are usually simple and relatively easy to apply. However, for partly or fully conceptual models, some parameters cannot be considered as physically measured quantities and thus have to be estimated on the basis of the available data and information. However, in the range of input data, it is often not possible to find one unique parameter set, i.e. a number of parameter sets can lead to similar model results (known as equifinality). Nevertheless, the model parameter sets which lead to equally good model performance may have interesting internal structures. The issue of equifinality following the internal model structures was investigated in this paper using two examples. The first example is one which uses a simple two parameter sediment transport model in a river. A large number of parameter pairs was generated randomly. The results indicated that they both can be taken from a wide interval of possible values which might lead to satisfactory model performance. However, a well structured set is obtained if one investigates the set of parameters as pairs. The second example was given by using model parameters of the modified HBV conceptual rainfall-runoff model. One hundred independent calibration runs for the HBV model were carried out. These runs were done using the automatic calibration procedure based on the simulated optimization algorithm; each run using a different, randomly selected initial seed value required for the calibration algorithm. No explicit dependence between the parameters was considered. The results demonstrated that parameters of rainfall-runoff models often can not be identified as individual values. A large set of possible parameters can lead to a similar model

  15. Conceptual model for heart failure disease management.

    PubMed

    Andrikopoulou, Efstathia; Abbate, Kariann; Whellan, David J

    2014-03-01

    The objective of this review is to propose a conceptual model for heart failure (HF) disease management (HFDM) and to define the components of an efficient HFDM plan in reference to this model. Articles that evaluated 1 or more of the following aspects of HFDM were reviewed: (1) outpatient clinic follow-up; (2) self-care interventions to enhance patient skills; and (3) remote evaluation of worsening HF either using structured telephone support (STS) or by monitoring device data (telemonitoring). The success of programs in reducing readmissions and mortality were mixed. Outpatient follow-up programs generally resulted in improved outcomes, including decreased readmissions. Based on 1 meta-analysis, specialty clinics improved outcomes and nonspecialty clinics did not. Results from self-care programs were inconsistent and might have been affected by patient cognitive status and educational level, and intervention intensity. Telemonitoring, despite initially promising meta-analyses demonstrating a decrease in the number and duration of HF-related readmissions and all-cause mortality rates at follow-up, has not been shown in randomized trials to consistently reduce readmissions or mortality. However, evidence from device monitoring trials in particular might have been influenced by technology and design issues that might be rectified in future trials. Results from the literature suggest that the ideal HFDM plan would include outpatient follow-up at an HF specialty clinic and continuous education to improve patient self-care. The end result of this plan would lead to better understanding on the part of the patient and improved patient ability to recognize and respond to signs of decompensation. PMID:24565255

  16. Calibration of GEOtop for a Mountainous Watershed—a Hydrological Land-Surface Model.

    NASA Astrophysics Data System (ADS)

    Fullhart, A. T.; Kelleners, T.

    2015-12-01

    GEOtop is a distributed finite-difference hydrological land-surface model with a built-in snow evolution package. Ongoing model calibrations and solutions are presented for a very small, low-order watershed within a forested mountain range at ~10,000 ft. elevation. The catchment has a hydrological budget that is dominated by snow input. During model calibration, potential configurations for spatial discretization and resolution are tested by comparison to field measurements—as are alternative soil properties and surface runoff parameters. Also demonstrated is the effect of variable geomorphology as it relates to the energy budget and the subsequent distribution of modeled outputs. Within the larger scope of the WYCEHG research group (i.e. The Wyoming Center for Environmental Hydrology and Geophysics), which works towards a multi-disciplinary approach to field modeling, additional complexities beyond stream flow and soil moisture can be conceptualized and tested based on measurements of snowpacks, evapotranspiration, and geophysical imaging. A combination of these give a better understanding of critical components of the hydrological balance—some of which are in states of flux, e.g., tree cover (due to beetle-kill), and future climate change scenarios.

  17. Capabilities and limitations of detailed hillslope hydrological modelling

    NASA Astrophysics Data System (ADS)

    Bronstert, Axel

    1999-01-01

    Hillslope hydrological modelling is considered to be of great importance for the understanding and quantification of hydrological processes in hilly or mountainous landscapes. In recent years a few comprehensive hydrological models have been developed at the hillslope scale which have resulted in an advanced representation of hillslope hydrological processes (including their interactions), and in some operational applications, such as in runoff and erosion studies at the field scale or lateral flow simulation in environmental and geotechnical engineering. An overview of the objectives of hillslope hydrological modelling is given, followed by a brief introduction of an exemplary comprehensive hillslope model, which stimulates a series of hydrological processes such as interception, evapotranspiration, infiltration into the soil matrix and into macropores, lateral and vertical subsurface soil water flow both in the matrix and preferential flow paths, surface runoff and channel discharge. Several examples of this model are presented and discussed in order to determine the model's capabilities and limitations. Finally, conclusions about the limitations of detailed hillslope modelling are drawn and an outlook on the future prospects of hydrological models on the hillslope scale is given.The model presented performed reasonable calculations of Hortonian surface runoff and subsequent erosion processes, given detailed information of initial soil water content and soil hydraulic conditions. The vertical and lateral soil moisture dynamics were also represented quite well. However, the given examples of model applications show that quite detailed climatic and soil data are required to obtain satisfactory results. The limitations of detailed hillslope hydrological modelling arise from different points: difficulties in the representations of certain processes (e.g. surface crusting, unsaturated-saturated soil moisture flow, macropore flow), problems of small-scale variability

  18. Treatment of input uncertainty in hydrologic modeling: Doing hydrology backward with Markov chain Monte Carlo simulation

    NASA Astrophysics Data System (ADS)

    Vrugt, Jasper A.; Ter Braak, Cajo J. F.; Clark, Martyn P.; Hyman, James M.; Robinson, Bruce A.

    2008-12-01

    There is increasing consensus in the hydrologic literature that an appropriate framework for streamflow forecasting and simulation should include explicit recognition of forcing and parameter and model structural error. This paper presents a novel Markov chain Monte Carlo (MCMC) sampler, entitled differential evolution adaptive Metropolis (DREAM), that is especially designed to efficiently estimate the posterior probability density function of hydrologic model parameters in complex, high-dimensional sampling problems. This MCMC scheme adaptively updates the scale and orientation of the proposal distribution during sampling and maintains detailed balance and ergodicity. It is then demonstrated how DREAM can be used to analyze forcing data error during watershed model calibration using a five-parameter rainfall-runoff model with streamflow data from two different catchments. Explicit treatment of precipitation error during hydrologic model calibration not only results in prediction uncertainty bounds that are more appropriate but also significantly alters the posterior distribution of the watershed model parameters. This has significant implications for regionalization studies. The approach also provides important new ways to estimate areal average watershed precipitation, information that is of utmost importance for testing hydrologic theory, diagnosing structural errors in models, and appropriately benchmarking rainfall measurement devices.

  19. A Logical Model of Conceptual Integrity in Data Integration

    PubMed Central

    Flater, David

    2003-01-01

    Conceptual integrity is required for the result of data integration to be cohesive and sensible. Compromised conceptual integrity results in “semantic faults,” which are commonly blamed for latent integration bugs. A logical model of conceptual integrity in data integration and a simple example application are presented. Unlike constructive models that attempt to prevent semantic faults, this model allows both correct and incorrect integrations to be described. Imperfect legacy systems can therefore be modeled, allowing a more formal analysis of their flaws and the possible remedies.

  20. Model of Conceptual Change for INQPRO: A Bayesian Network Approach

    ERIC Educational Resources Information Center

    Ting, Choo-Yee; Sam, Yok-Cheng; Wong, Chee-Onn

    2013-01-01

    Constructing a computational model of conceptual change for a computer-based scientific inquiry learning environment is difficult due to two challenges: (i) externalizing the variables of conceptual change and its related variables is difficult. In addition, defining the causal dependencies among the variables is also not trivial. Such difficulty…

  1. Using Conceptual Change Theories to Model Position Concepts in Astronomy

    ERIC Educational Resources Information Center

    Yang, Chih-Chiang; Hung, Jeng-Fung

    2012-01-01

    The roles of conceptual change and model building in science education are very important and have a profound and wide effect on teaching science. This study examines the change in children's position concepts after instruction, based on different conceptual change theories. Three classes were chosen and divided into three groups, including a…

  2. Consistency between hydrological models and field observations: Linking processes at the hillslope scale to hydrological responses at the watershed scale

    USGS Publications Warehouse

    Clark, M.P.; Rupp, D.E.; Woods, R.A.; Tromp-van, Meerveld, H. J.; Peters, N.E.; Freer, J.E.

    2009-01-01

    The purpose of this paper is to identify simple connections between observations of hydrological processes at the hillslope scale and observations of the response of watersheds following rainfall, with a view to building a parsimonious model of catchment processes. The focus is on the well-studied Panola Mountain Research Watershed (PMRW), Georgia, USA. Recession analysis of discharge Q shows that while the relationship between dQ/dt and Q is approximately consistent with a linear reservoir for the hillslope, there is a deviation from linearity that becomes progressively larger with increasing spatial scale. To account for these scale differences conceptual models of streamflow recession are defined at both the hillslope scale and the watershed scale, and an assessment made as to whether models at the hillslope scale can be aggregated to be consistent with models at the watershed scale. Results from this study show that a model with parallel linear reservoirs provides the most plausible explanation (of those tested) for both the linear hillslope response to rainfall and non-linear recession behaviour observed at the watershed outlet. In this model each linear reservoir is associated with a landscape type. The parallel reservoir model is consistent with both geochemical analyses of hydrological flow paths and water balance estimates of bedrock recharge. Overall, this study demonstrates that standard approaches of using recession analysis to identify the functional form of storage-discharge relationships identify model structures that are inconsistent with field evidence, and that recession analysis at multiple spatial scales can provide useful insights into catchment behaviour. Copyright ?? 2008 John Wiley & Sons, Ltd.

  3. Improving the representation of hydrologic processes in Earth System Models

    SciTech Connect

    Clark, Martyn P.; Fan, Ying; Lawrence, David M.; Adam, Jennifer C.; Bolster, Diogo; Gochis, David J.; Hooper, Richard P.; Kumar, Mukesh; Leung, L. Ruby; Mackay, D. Scott; Maxwell, Reed M.; Shen, Chaopeng; Swenson, Sean C.; Zeng, Xubin

    2015-08-21

    Many of the scientific and societal challenges in understanding and preparing for global environmental change rest upon our ability to understand and predict the water cycle change at large river basin, continent, and global scales. However, current large-scale models, such as the land components of Earth System Models (ESMs), do not yet represent the terrestrial water cycle in a fully integrated manner or resolve the finer-scale processes that can dominate large-scale water budgets. This paper reviews the current representation of hydrologic processes in ESMs and identifies the key opportunities for improvement. This review suggests that (1) the development of ESMs has not kept pace with modeling advances in hydrology, both through neglecting key processes (e.g., groundwater) and neglecting key aspects of spatial variability and hydrologic connectivity; and (2) many modeling advances in hydrology can readily be incorporated into ESMs and substantially improve predictions of the water cycle. Accelerating modeling advances in ESMs requires comprehensive hydrologic benchmarking activities, in order to systematically evaluate competing modeling alternatives, understand model weaknesses, and prioritize model development needs. This demands stronger collaboration, both through greater engagement of hydrologists in ESM development and through more detailed evaluation of ESM processes in research watersheds. Advances in the representation of hydrologic process in ESMs can substantially improve energy, carbon and nutrient cycle prediction capabilities through the fundamental role the water cycle plays in regulating these cycles.

  4. Modeling the hydrological patterns on Pantanal wetlands, Brazil

    NASA Astrophysics Data System (ADS)

    Castro, A. A.; Cuartas, A.; Coe, M. T.; Koumrouyan, A.; Panday, P. K.; Lefebvre, P.; Padovani, C.; Costa, M. H.; de Oliveira, G. S.

    2014-12-01

    The Pantanal of Brazil is one of the world's largest wetland regions. It is located within the 370,000 km2 Alto Paraguai Basin (BAP). In wet years almost 15% of the total area of the basin can be flooded (approximately 53,000 km2). The hydrological cycle is particularly important in the Pantanal in the transport of materials, and the transfer of energy between atmospheric, aquatic, and terrestrial systems. The INLAND (Integrated Land Surface Model) terrestrial ecosystem model is coupled with the THMB hydrological model to examine the hydrological balance and water dynamics for this region. The INLAND model is based on the IBIS dynamic vegetation model, while THMB represents the river, wetland and lake dynamics of the land surface. The modeled hydrological components are validated with surface and satellite-based estimates of precipitation (gridded observations from CRU v. 3.21, reanalysis data from ERA-interim, and TRMM estimates), evapotranspiration (MODIS and Land Flux-Eval dataset), total runoff (discharge data from ANA-Agência Nacional das Águas - Brazil), and terrestrial water storage (GRACE). Results show that the coupled hydrological model adequately represents the water cycle components, the river discharge and flooded areas. Model simulations are further used to study the influences of climatic variations on the hydrological components, river network, and the inundated areas in the Pantanal.

  5. 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.

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

    USGS Publications Warehouse

    Wilby, R.L.; Hay, L.E.; Gutowski, W.J., Jr.; 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.

  7. Challenges and Solutions in Implementing Hydrological Models within Scientific Workflow Software

    NASA Astrophysics Data System (ADS)

    Perraud, J.; Fitch, P. G.; Bai, Q.

    2010-12-01

    The use of scientific workflow software in the hydrology domain appears to have gained traction in the past few years, to better handle data streams, pipelines of processing steps, QA/QC, metadata and provenance. The Hydrologists’ Workbench (HWB) is a software toolset building on the Trident scientific workflow software (http://tridentworkflow.codeplex.com/), adding data handling and processing activities that are primarily aimed at the hydrology domain. One important source of processing activities is found in several existing environmental modelling software systems. Making these components available through HWB brings several challenges. While many environmental modelling systems have conceptually similar characteristics at a high level, their implementation will naturally vary in many respects, bringing to HWB the traditional challenge of model and data interoperability between heterogeneous systems. The challenges fall arguably into two broad categories: data interoperability and model of execution. The former stems from wanting to seamlessly pass data between processing activities that may have very different back-end implementations. The latter arises with the possible incompatibilities, conceptual or technical, between the workflow execution engine and the way a model or modelling component needs to be executed. We illustrate these challenges and propose some solutions by reporting the findings of a case study incorporating a spatial-temporal surface runoff modelling toolset in HWB. We find notably two salient challenges, the definition of an appropriate granularity for the workflow activities wrapping the existing modelling components, and the need for a common, implementation-neutral scientific data model.

  8. 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. ...

  9. The site-scale saturated zone flow model for Yucca Mountain: calibration of different conceptual models and their impact on flow paths.

    PubMed

    Zyvoloski, George; Kwicklis, Edward; Eddebbarh, Al Aziz; Arnold, Bill; Faunt, Claudia; Robinson, Bruce A

    2003-01-01

    This paper presents several different conceptual models of the Large Hydraulic Gradient (LHG) region north of Yucca Mountain and describes the impact of those models on groundwater flow near the potential high-level repository site. The results are based on a numerical model of site-scale saturated zone beneath Yucca Mountain. This model is used for performance assessment predictions of radionuclide transport and to guide future data collection and modeling activities. The numerical model is calibrated by matching available water level measurements using parameter estimation techniques, along with more informal comparisons of the model to hydrologic and geochemical information. The model software (hydrologic simulation code FEHM and parameter estimation software PEST) and model setup allows for efficient calibration of multiple conceptual models. Until now, the Large Hydraulic Gradient has been simulated using a low-permeability, east-west oriented feature, even though direct evidence for this feature is lacking. In addition to this model, we investigate and calibrate three additional conceptual models of the Large Hydraulic Gradient, all of which are based on a presumed zone of hydrothermal chemical alteration north of Yucca Mountain. After examining the heads and permeabilities obtained from the calibrated models, we present particle pathways from the potential repository that record differences in the predicted groundwater flow regime. The results show that Large Hydraulic Gradient can be represented with the alternate conceptual models that include the hydrothermally altered zone. The predicted pathways are mildly sensitive to the choice of the conceptual model and more sensitive to the quality of calibration in the vicinity on the repository. These differences are most likely due to different degrees of fit of model to data, and do not represent important differences in hydrologic conditions for the different conceptual models. PMID:12714319

  10. Future hydrological extremes: the uncertainty from multiple global climate and global hydrological models

    NASA Astrophysics Data System (ADS)

    Giuntoli, I.; Vidal, J.-P.; Prudhomme, C.; Hannah, D. M.

    2015-05-01

    Projections of changes in the hydrological cycle from global hydrological models (GHMs) driven by global climate models (GCMs) are critical for understanding future occurrence of hydrological extremes. However, uncertainties remain large and need to be better assessed. In particular, recent studies have pointed to a considerable contribution of GHMs that can equal or outweigh the contribution of GCMs to uncertainty in hydrological projections. Using six GHMs and five GCMs from the ISI-MIP multi-model ensemble, this study aims: (i) to assess future changes in the frequency of both high and low flows at the global scale using control and future (RCP8.5) simulations by the 2080s, and (ii) to quantify, for both ends of the runoff spectrum, GCMs and GHMs contributions to uncertainty using a two-way ANOVA. Increases are found in high flows for northern latitudes and in low flows for several hotspots. Globally, the largest source of uncertainty is associated with GCMs, but GHMs are the greatest source in snow-dominated regions. More specifically, results vary depending on the runoff metric, the temporal (annual and seasonal) and regional scale of analysis. For instance, uncertainty contribution from GHMs is higher for low flows than it is for high flows, partly owing to the different processes driving the onset of the two phenomena (e.g. the more direct effect of the GCMs' precipitation variability on high flows). This study provides a comprehensive synthesis of where future hydrological extremes are projected to increase and where the ensemble spread is owed to either GCMs or GHMs. Finally, our results underline the need for improvements in modelling snowmelt and runoff processes to project future hydrological extremes and the importance of using multiple GCMs and GHMs to encompass the uncertainty range provided by these two sources.

  11. Modelling hydrological management for the restoration of acidified floating fens

    NASA Astrophysics Data System (ADS)

    Dekker, Stefan C.; Barendregt, Aat; Bootsma, Margien C.; Schot, Paul P.

    2005-12-01

    Wetlands show a large decline in biodiversity. To protect and restore this biodiversity, many restoration projects are carried out. Hydrology in wetlands controls the chemical and biological processes and may be the most important factor regulating wetland function and development. Hydrological models may be used to simulate these processes and to evaluate management scenarios for restoration. HYDRUS2D, a combined saturated-unsaturated groundwater flow and transport model, is presented. This simulates near-surface hydrological processes in an acidified floating fen, with the aim to evaluate the effect of hydrological restoration in terms of conditions for biodiversity. In the acidified floating fen in the nature reserve Ilperveld (The Netherlands), a trench system was dug for the purpose of creating a runoff channel for acid rainwater in wet periods and to enable circum-neutral surface water to enter the fen in dry periods. The model is calibrated against measured conductivity values for a 5 year period. From the model simulations, it was found that lateral flow in the floating raft is limited. Furthermore, the model shows that the best management option is a combination of trenches and inundation, which gave the best soil water quality in the root zone. It is concluded that hydrological models can be used for the calculation of management scenarios in restoration projects. The combined saturated-unsaturated model concept used in this paper is able to incorporate the governing hydrological processes in the wetland root zones. Copyright

  12. A conceptual graphs modeling of UMLS components.

    PubMed

    Joubert, M; Miton, F; Fieschi, M; Robert, J J

    1995-01-01

    The Unified Medical Language System (UMLS) of the U.S. National Library of Medicine is a complex collection of terms, concepts, and relationships derived from standard classifications. Potential applications would benefit from a high level representation of its components. This paper proposes a conceptual representation of both the Metathesaurus and the Semantic Network of the UMLS based on conceptual graphs. It shows that the addition of a dictionary of concepts to the UMLS knowledge base allows the capability to exploit it pertinently. This dictionary defines more precisely the core concepts and adds constraints on their use. Constraints are dedicated to guide an "intelligent" browsing of the UMLS knowledge sources. PMID:8591348

  13. 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.

  14. Challenges in Requirements Engineering: A Research Agenda for Conceptual Modeling

    NASA Astrophysics Data System (ADS)

    March, Salvatore T.; Allen, Gove N.

    Domains for which information systems are developed deal primarily with social constructions—conceptual objects and attributes created by human intentions and for human purposes. Information systems play an active role in these domains. They document the creation of new conceptual objects, record and ascribe values to their attributes, initiate actions within the domain, track activities performed, and infer conclusions based on the application of rules that govern how the domain is affected when socially-defined and identified causal events occur. Emerging applications of information technologies evaluate such business rules, learn from experience, and adapt to changes in the domain. Conceptual modeling grammars aimed at representing their system requirements must include conceptual objects, socially-defined events, and the rules pertaining to them. We identify challenges to conceptual modeling research and pose an ontology of the artificial as a step toward meeting them.

  15. Using climate model ensemble forecasts for seasonal hydrologic prediction

    NASA Astrophysics Data System (ADS)

    Wood, Andrew Whitaker

    Seasonal hydrologic forecasting has long played an invaluable role in the development and use of water resources. Despite notable advances in the science and practice of climate prediction, current approaches of hydrologists and water managers largely fail to incorporate seasonal climate forecast information that has become operationally available during the last decade. This study is motivated by the view that a combination of hydrologic and climate prediction methods affords a new opportunity to improve hydrologic forecast skill. A relatively direct statistical approach for achieving this combination (i.e., downscaling) was formulated that used ensemble climate model forecasts with a six month lead time produced by the NCEP/CPC Global Spectral Model (GSM) as input to the macroscale Variable Infiltration Capacity hydrologic model to produce ensemble runoff and streamflow forecasts. The approach involved the bias correction of climate model precipitation and temperature fields, and spatial and temporal disaggregation from monthly climate model scale (about 2 degrees latitude by longitude) fields to daily hydrology model scale (1/8 degrees) inputs. A qualitative evaluation of the approach in the eastern U.S. suggested that it was successful in translating climate forecast signals to local hydrologic variables and streamflow, but that the dominant influence on forecast results tended to be persistence in initial hydrologic conditions. The suitability of the statistical downscaling approach for supporting hydrologic simulation was then assessed (using a continuous retrospective 20-year climate simulation from the DOE Parallel Climate Model) relative to dynamical downscaling via a regional, meso-scale climate model. The statistical approach generally outperformed the dynamical approach, in that the dynamical approach alone required additional bias-correction to reproduce the retrospective hydrology as well as the statistical approach. Finally, using 21 years of

  16. Analysis of Hydrogeologic Conceptual Model and Parameter Uncertainty

    SciTech Connect

    Meyer, Philip D.; Nicholson, Thomas J.; Mishra, Srikanta

    2003-06-24

    A systematic methodology for assessing hydrogeologic conceptual model, parameter, and scenario uncertainties is being developed to support technical reviews of environmental assessments related to decommissioning of nuclear facilities. The first major task being undertaken is to produce a coupled parameter and conceptual model uncertainty assessment methodology. This task is based on previous studies that have primarily dealt individually with these two types of uncertainties. Conceptual model uncertainty analysis is based on the existence of alternative conceptual models that are generated using a set of clearly stated guidelines targeted at the needs of NRC staff. Parameter uncertainty analysis makes use of generic site characterization data as well as site-specific characterization and monitoring data to evaluate parameter uncertainty in each of the alternative conceptual models. Propagation of parameter uncertainty will be carried out through implementation of a general stochastic model of groundwater flow and transport in the saturated and unsaturated zones. Evaluation of prediction uncertainty will make use of Bayesian model averaging and visualization of model results. The goal of this study is to develop a practical tool to quantify uncertainties in the conceptual model and parameters identified in performance assessments.

  17. Overtraining and recovery. A conceptual model.

    PubMed

    Kenttä, G; Hassmén, P

    1998-07-01

    importance of active measures to improve the recovery process. Furthermore, directing attention to psychophysiological cues serves the same purpose as in RPE, i.e. increasing self-awareness. This article reviews and conceptualises the whole overtraining process. In doing so, it (i) aims to differentiate between the types of stress affecting an athlete's performance: (ii) identifies factors influencing an athlete's ability to adapt to physical training: (iii) structures the recovery process. The TQR method to facilitate monitoring of the recovery process is then suggested and a conceptual model that incorporates all of the important parameters for performance gain (adaptation) and loss (maladaptation). PMID:9739537

  18. Using satellite precipitation data for hydrological modeling

    NASA Astrophysics Data System (ADS)

    Commandeur, Tom

    2013-04-01

    strategies for the MPE data. Since the MPE data is an estimate rather than a measurement, the data presents the need for validation. Comparison of the MPE data with ground radar and ground measurements will show the usability for hydrological modeling according to realistic scenarios. The end purpose is improving precipitation estimates by calibration, using ground radar and ground measurements where available. This study also researches their relations and combination approach.

  19. Validation of the hydrological cycle of ECMWF and NCEP reanalyses using the MPI hydrological discharge model

    NASA Astrophysics Data System (ADS)

    Hagemann, Stefan; Gates, Lydia Dümenil

    2001-01-01

    To validate the hydrological cycle of the European Centre for Medium-Range Weather Forecasts (ECMWF) and the National Centers for Environmental Prediction (NCEP) reanalyses in comparison with observed river discharge, a hydrological discharge model is used to compute the corresponding river discharge. The HD model requires daily time series of surface runoff and drainage from the soil as input fields. As it turned out that a direct application to the reanalyses was not possible, a simplified land surface scheme was developed to compute runoff and drainage fields from daily reanalysis values of total precipitation and 2 m temperature. These fields were then used as input to the global simulation of river discharge with the discharge model. Results show several shortcomings of the two reanalyses in representing the hydrological cycle at the land surface. The water balance is not closed, and the snowmelt is not incorporated in the runoff and drainage fields of either of the two reanalyses. In addition, the NCEP reanalysis overestimates summer precipitation and evapotranspiration for most parts of the Northern Hemisphere, while the ECMWF reanalysis underestimates 2 m temperatures in high latitudes during the winter and spring. In the monsoon region the hydrological cycle is well represented by both reanalyses, especially over India.

  20. Neural network modelling of non-linear hydrological relationships

    NASA Astrophysics Data System (ADS)

    Abrahart, R. J.; See, L. M.

    2007-09-01

    Two recent studies have suggested that neural network modelling offers no worthwhile improvements in comparison to the application of weighted linear transfer functions for capturing the non-linear nature of hydrological relationships. The potential of an artificial neural network to perform simple non-linear hydrological transformations under controlled conditions is examined in this paper. Eight neural network models were developed: four full or partial emulations of a recognised non-linear hydrological rainfall-runoff model; four solutions developed on an identical set of inputs and a calculated runoff coefficient output. The use of different input combinations enabled the competencies of solutions developed on a reduced number of parameters to be assessed. The selected hydrological model had a limited number of inputs and contained no temporal component. The modelling process was based on a set of random inputs that had a uniform distribution and spanned a modest range of possibilities. The initial cloning operations permitted a direct comparison to be performed with the equation-based relationship. It also provided more general information about the power of a neural network to replicate mathematical equations and model modest non-linear relationships. The second group of experiments explored a different relationship that is of hydrological interest; the target surface contained a stronger set of non-linear properties and was more challenging. Linear modelling comparisons were performed against traditional least squares multiple linear regression solutions developed on identical datasets. The reported results demonstrate that neural networks are capable of modelling non-linear hydrological processes and are therefore appropriate tools for hydrological modelling.

  1. Robert Horton and the Application of Distributed Hydrological Models

    NASA Astrophysics Data System (ADS)

    Beven, K. J.

    2004-12-01

    The name of Walter Langbein provides a link with the hydrology of Robert Horton. Langbein both worked with Horton and was the very first recipient of the AGU Horton Medal in 1976. In his response to the award, Langbein paid tribute to Horton's wide ranging interests as evidenced in the "several dozen research files in the National Archive". A recent search of some of these files has revealed some very interesting insights into Horton's hydrological concepts and, in particular, his appreciation of the difficulties involved in hydrological analysis and distributed prediction. Despite modern computer technology and the availability of geographical information systems, these insights are still relevant and important today and should be the basis for an approach to hydrological prediction that recognises the limitations of applying general, but incomplete, theory to specific places. An analysis of the sources of uncertainty in the modelling process leads to some suggestions about how we should proceed in the application of models in the future.

  2. Coupled Hydrological and Hydraulic Modeling for Flood Mapping

    NASA Astrophysics Data System (ADS)

    Drobot, Radu; Draghia, Aurelian

    2014-05-01

    The delineation of the flooded areas involves both hydrological and hydraulic modeling. Usually, the hydrological and hydraulic processes are separately treated. In the proposed methodology, the coupled modeling of the hydrological and hydraulic processes is used. The calibration and validation of the hydrological parameters is undertaken based on historical floods using the corresponding precipitations for the same period. The calibration process was more complicated in the presence of reservoirs, when not only the discharges downstream but also the water level in the reservoirs had to be accurately reproduced. The time step for precipitation is 1 hour, corresponding to the concentration time of the smallest catchments. The maximum annual precipitation for different time steps (1; 3; 6; 24 hours) were statistically processed and based on these results the cumulative rainfall curves and the synthetic hyetographs were derived. The rainfall duration is depending on the concentration time. Mike 11 with UHM module based on SCS model was used for coupled hydrological and hydraulic modeling. The coupled hydrological and hydraulic simulation for the scaled precipitation leads both at the computation of the components which contribute to the generation of the P% flood at the Hydrometric stations as well as to the determination of the discharge hydrograph along the main river. Based on these results the flood hazard maps were obtained using a DTM based on Lidar data. The methodology was applied for a river basin in Romania of 12500 km2.

  3. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

  5. An Integrative-Interactive Conceptual Model for Curriculum Development.

    ERIC Educational Resources Information Center

    Al-Ibrahim, Abdul Rahman H.

    1982-01-01

    The Integrative-Interactive Conceptual Model for Curriculum Development calls for curriculum reform and innovation to be cybernetic so that all aspects of curriculum planning get adequate attention. (CJ)

  6. CONCEPTUAL MODEL DEVELOPMENT AND INFORMATION MANAGEMENT FRAMEWORK FOR DIAGNOSTICS RESEARCH

    EPA Science Inventory

    Conceptual model development will focus on the effects of habitat alteration, nutrients,suspended and bedded sediments, and toxic chemicals on appropriate endpoints (individuals, populations, communities, ecosystems) across spatial scales (habitats, water body, watershed, region)...

  7. Moving horizon estimation for assimilating H-SAF remote sensing data into the HBV hydrological model

    NASA Astrophysics Data System (ADS)

    Montero, Rodolfo Alvarado; Schwanenberg, Dirk; Krahe, Peter; Lisniak, Dmytro; Sensoy, Aynur; Sorman, A. Arda; Akkol, Bulut

    2016-06-01

    Remote sensing information has been extensively developed over the past few years including spatially distributed data for hydrological applications at high resolution. The implementation of these products in operational flow forecasting systems is still an active field of research, wherein data assimilation plays a vital role on the improvement of initial conditions of streamflow forecasts. We present a novel implementation of a variational method based on Moving Horizon Estimation (MHE), in application to the conceptual rainfall-runoff model HBV, to simultaneously assimilate remotely sensed snow covered area (SCA), snow water equivalent (SWE), soil moisture (SM) and in situ measurements of streamflow data using large assimilation windows of up to one year. This innovative application of the MHE approach allows to simultaneously update precipitation, temperature, soil moisture as well as upper and lower zones water storages of the conceptual model, within the assimilation window, without an explicit formulation of error covariance matrixes and it enables a highly flexible formulation of distance metrics for the agreement of simulated and observed variables. The framework is tested in two data-dense sites in Germany and one data-sparse environment in Turkey. Results show a potential improvement of the lead time performance of streamflow forecasts by using perfect time series of state variables generated by the simulation of the conceptual rainfall-runoff model itself. The framework is also tested using new operational data products from the Satellite Application Facility on Support to Operational Hydrology and Water Management (H-SAF) of EUMETSAT. This study is the first application of H-SAF products to hydrological forecasting systems and it verifies their added value. Results from assimilating H-SAF observations lead to a slight reduction of the streamflow forecast skill in all three cases compared to the assimilation of streamflow data only. On the other hand

  8. Conceptual model of hydrogeology in the Ozark Plateaus region during Pennsylvanian time

    SciTech Connect

    Brahana, J.V. )

    1993-03-01

    Recently completed studies of the Ozark Plateaus region of southern Missouri and northern Arkansas provide a conceptual framework for understanding current hydrogeology, and form the basis for numerical models that can be used to quantitatively assess flow and solute transport in the aquifers of this area. Three separate investigations were completed as part of the Regional Aquifer-Systems Analysis (RASA) program of the US Geological Survey during 1985--1993. Although the objectives of these RASA studies [Northern Midwest (NM) RASA, Gulf Coast (GC) RASA, and Central Midwest (CM) RASA] focused on recent hydrologic conditions, each study has contributed o increased understanding of the evolution of the hydrogeology of the region.

  9. Coupling Hydrologic and Hydrodynamic Models to Estimate PMF

    NASA Astrophysics Data System (ADS)

    Felder, G.; Weingartner, R.

    2015-12-01

    Most sophisticated probable maximum flood (PMF) estimations derive the PMF from the probable maximum precipitation (PMP) by applying deterministic hydrologic models calibrated with observed data. This method is based on the assumption that the hydrological system is stationary, meaning that the system behaviour during the calibration period or the calibration event is presumed to be the same as it is during the PMF. However, as soon as a catchment-specific threshold is reached, the system is no longer stationary. At or beyond this threshold, retention areas, new flow paths, and changing runoff processes can strongly affect downstream peak discharge. These effects can be accounted for by coupling hydrologic and hydrodynamic models, a technique that is particularly promising when the expected peak discharge may considerably exceed the observed maximum discharge. In such cases, the coupling of hydrologic and hydraulic models has the potential to significantly increase the physical plausibility of PMF estimations. This procedure ensures both that the estimated extreme peak discharge does not exceed the physical limit based on riverbed capacity and that the dampening effect of inundation processes on peak discharge is considered. Our study discusses the prospect of considering retention effects on PMF estimations by coupling hydrologic and hydrodynamic models. This method is tested by forcing PREVAH, a semi-distributed deterministic hydrological model, with randomly generated, physically plausible extreme precipitation patterns. The resulting hydrographs are then used to externally force the hydraulic model BASEMENT-ETH (riverbed in 1D, potential inundation areas in 2D). Finally, the PMF estimation results obtained using the coupled modelling approach are compared to the results obtained using ordinary hydrologic modelling.

  10. 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

  11. Sensitivity of climate model to hydrology

    NASA Astrophysics Data System (ADS)

    Ye, Duzheng

    The importance of land—surface processes in affecting climate change has been analyzed and discussed by Namias [1962,1963]. The physics of the land-surface processes affect the climate because the ground hydrology, together with the vegetation and soil, determine the surface moisture availability which, in turn, controls the partition between the sensible and latent heat fluxes [Rowntree, 1984] and also the transfer of momentum. Further the vegetation cover and the soil moisture content can determine the ground surface albedo in snowless conditions. Therefore the heat balance and water balance in the planetary boundary layer are highly influenced by the hydrological processes. Through the planetary boundary layer, the influence of the ground hydrological processes can be felt through the whole troposphere [Yeh, et al., 1984; Rowntree and Bolton, 1983]. Here a crucial factor is the soil moisture content. In the region of dry anomalies, the following sequence of events tends to occur: a decrease of evaporation, a ground surface warming with an increase of sensible heat flux, a wanning of lower layers of the atmosphere with a decrease of relative humidity (due to decrease of evaporation and warming of lower atmophere), a decrease of precipitation with a cooling of the atmosphere higher up (due to decrease of latent heat), and then a change of upper air circulation [Rowntree and Bolton, 1983]. It is the decrease of precipitation which will cause the initial dry anomaly to persist. In the region of moist anomalies, the opposite sequence of events tends to occur.

  12. Bayesian Assessment of the Uncertainties of Estimates of a Conceptual Rainfall-Runoff Model Parameters

    NASA Astrophysics Data System (ADS)

    Silva, F. E. O. E.; Naghettini, M. D. C.; Fernandes, W.

    2014-12-01

    This paper evaluated the uncertainties associated with the estimation of the parameters of a conceptual rainfall-runoff model, through the use of Bayesian inference techniques by Monte Carlo simulation. The Pará River sub-basin, located in the upper São Francisco river basin, in southeastern Brazil, was selected for developing the studies. In this paper, we used the Rio Grande conceptual hydrologic model (EHR/UFMG, 2001) and the Markov Chain Monte Carlo simulation method named DREAM (VRUGT, 2008a). Two probabilistic models for the residues were analyzed: (i) the classic [Normal likelihood - r ≈ N (0, σ²)]; and (ii) a generalized likelihood (SCHOUPS & VRUGT, 2010), in which it is assumed that the differences between observed and simulated flows are correlated, non-stationary, and distributed as a Skew Exponential Power density. The assumptions made for both models were checked to ensure that the estimation of uncertainties in the parameters was not biased. The results showed that the Bayesian approach proved to be adequate to the proposed objectives, enabling and reinforcing the importance of assessing the uncertainties associated with hydrological modeling.

  13. Application of SMOS and ASCAT soil moisture estimations to hydrological modelling in Serbia

    NASA Astrophysics Data System (ADS)

    Zlatanovic, Nikola; Ivkovic, Marija; Drobnjak, Aleksandar

    2016-04-01

    This study explores the performance of satellite-based soil moisture products from satellites SMOS (Soil Moisture and Ocean Salinity, measuring brightness temperatures in the L-Band at 1.4 GHz) and ASCAT (Advanced SCATterometer, measuring surface backscattering coefficients in the C-band at 5.255 GHz) for hydrological application. Firstly, SMOS and ASCAT Level 2 soil moisture data were compared to in situ data over Serbia at available sites. All available in situ ground-based point measurements of soil moisture, from the Republic Hydrometeorological Service of Serbia and other independent stations, were collected for the overlapping period with satellite observations and compared against remotely sensed satellite-based soil moisture products. Two approaches are presented in this study to evaluate the applicability of satellite-based SMOS and ASCAT soil moisture products to basin-scale hydrological modelling in a case study catchment in Serbia. The first approach was based on a continuous conceptual forecast-based rainfall-runoff model (using distributed HBV model), where satellite-based soil moisture data helped perform corrections to calculated model soil moisture. The second approach analysed individual event-based rainfall-runoff modelling (using HEC-HMS), where initial (pre-event) model parameters were estimated using satellite-based soil moisture data. Both approaches involved calibration of the hydrological models with and without satellite-based soil moisture data on a case study in Serbia.

  14. Using large hydrological datasets to create a robust, physically based, spatially distributed model for Great Britain

    NASA Astrophysics Data System (ADS)

    Lewis, Elizabeth; Kilsby, Chris; Fowler, Hayley

    2014-05-01

    The impact of climate change on hydrological systems requires further quantification in order to inform water management. This study intends to conduct such analysis using hydrological models. Such models are of varying forms, of which conceptual, lumped parameter models and physically-based models are two important types. The majority of hydrological studies use conceptual models calibrated against measured river flow time series in order to represent catchment behaviour. This method often shows impressive results for specific problems in gauged catchments. However, the results may not be robust under non-stationary conditions such as climate change, as physical processes and relationships amenable to change are not accounted for explicitly. Moreover, conceptual models are less readily applicable to ungauged catchments, in which hydrological predictions are also required. As such, the physically based, spatially distributed model SHETRAN is used in this study to develop a robust and reliable framework for modelling historic and future behaviour of gauged and ungauged catchments across the whole of Great Britain. In order to achieve this, a large array of data completely covering Great Britain for the period 1960-2006 has been collated and efficiently stored ready for model input. The data processed include a DEM, rainfall, PE and maps of geology, soil and land cover. A desire to make the modelling system easy for others to work with led to the development of a user-friendly graphical interface. This allows non-experts to set up and run a catchment model in a few seconds, a process that can normally take weeks or months. The quality and reliability of the extensive dataset for modelling hydrological processes has also been evaluated. One aspect of this has been an assessment of error and uncertainty in rainfall input data, as well as the effects of temporal resolution in precipitation inputs on model calibration. SHETRAN has been updated to accept gridded rainfall

  15. Comparing the performance of different model structures with respect to different hydrological signatures

    NASA Astrophysics Data System (ADS)

    Euser, T.; Winsemius, H. C.; Hrachowitz, M.; Fenicia, F.; Savenije, H. H. G.

    2012-04-01

    Correctly representing the dominant flow generation processes in conceptual rainfall-runoff models is crucial for ensuring adequate predictive power of the models. Recent work showed that on the small scale uniqueness of place requires different model structures for different catchments and that different calibration strategies frequently result in a wide range of model parameter sets. In this study we investigate the following research questions: (1) What is the effect of different calibration objective functions on the model performance? (2) Can the difference in performance of specific objective functions be related to hydrological signatures and physical catchment characteristics. Data from four experimental (approx. 1000 km2) sub-catchments (Alzette, Kyll, Orne and Seille) of the Moselle were used in this study. Eleven conceptual model structures (HBV, GR4J and 9 SUPERFLEX (flexible) model structures) of varying level of complexity are applied on each of the four study catchments. Besides classical objective functions (eg. Nash-Sutcliffe efficiency), additional objective functions are defined based on several hydrological signatures, such as the flow duration curve, rising limb density and auto-correlation. A multi-objective optimization is performed on all the objective functions for each catchment and each model structure considered. The results of the multi-objective optimization are then compared using Principle Component Analysis in order to identify the causes for differences in performance in the objective functions and relate these to physical catchment characteristics such as elevation, shape of the catchment and the height distribution above the nearest drain within a catchment. If such relationships are found then they can help to a priori identify suitable model structures and hydrological signatures in a catchment, given its spatial scale and physical characteristics.

  16. Realism test of a topography driven conceptual model (FLEX-Topo) in nested catchments of the Heihe River Basins, China

    NASA Astrophysics Data System (ADS)

    Gao, H.; Savenije, H.; Hrachowitz, M.; Fenicia, F.; Gharari, S.

    2013-12-01

    Although elevation data are globally available and many models do take topographical information into account, here it is demonstrated that topography is still an under-exploiting source of information in hydrological models . Based on the recently proposed modelling approach (FLEX-Topo) a semi-distributed topographic driven conceptual model (FLEXT), has been developed and tested in two nested catchments of the Heihe river basin. The model uses four topographical properties (i.e. Height Above the Nearest Drainage (HAND), absolute elevation, slope and aspect) to make a hydrological landscape classification which correspond with the dominant rainfall-runoff processes of these landscapes, to which a conceptual model structure is attributed. To analyses the additional information provided by the landscape classification, the performance of the FLEXT model is compared to a completely lumped hydrological models (FLEXL) and a semi-distributed model (FLEXD). All models have been calibrated and validated at the catchment outlet. Additionally, the models were evaluated in two nested sub-catchments. FLEXT performs substantially better than the other two models especially in the two nested sub-catchments during validation. It is especially better equipped to represent rainfall-runoff events during the dry season, which supports the following hypotheses: (1) topography can be used to distinguish different landscape elements with different hydrological function; (2) the model structure of the FLEXT is much better equipped to represent hydrological signatures than a lumped or semi-distributed model, and hence has a more realistic model structure and parameterization. The hydrograph components of the calibration(a), split-sample validation(b) and nested sub-catchments validation(c,d), of the FLEXT model

  17. 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.

  18. Towards a Model of Technology Adoption: A Conceptual Model Proposition

    NASA Astrophysics Data System (ADS)

    Costello, Pat; Moreton, Rob

    A conceptual model for Information Communication Technology (ICT) adoption by Small Medium Enterprises (SMEs) is proposed. The research uses several ICT adoption models as its basis with theoretical underpinning provided by the Diffusion of Innovation theory and the Technology Acceptance Model (TAM). Taking an exploratory research approach the model was investigated amongst 200 SMEs whose core business is ICT. Evidence from this study demonstrates that these SMEs face the same issues as all other industry sectors. This work points out weaknesses in SMEs environments regarding ICT adoption and suggests what they may need to do to increase the success rate of any proposed adoption. The methodology for development of the framework is described and recommendations made for improved Government-led ICT adoption initiatives. Application of the general methodology has resulted in new opportunities to embed the ethos and culture surrounding the issues into the framework of new projects developed as a result of Government intervention. A conceptual model is proposed that may lead to a deeper understanding of the issues under consideration.

  19. Numerical daemons in hydrological modeling: Effects on uncertainty assessment, sensitivity analysis and model predictions

    NASA Astrophysics Data System (ADS)

    Kavetski, D.; Clark, M. P.; Fenicia, F.

    2011-12-01

    Hydrologists often face sources of uncertainty that dwarf those normally encountered in many engineering and scientific disciplines. Especially when representing large scale integrated systems, internal heterogeneities such as stream networks, preferential flowpaths, vegetation, etc, are necessarily represented with a considerable degree of lumping. The inputs to these models are themselves often the products of sparse observational networks. Given the simplifications inherent in environmental models, especially lumped conceptual models, does it really matter how they are implemented? At the same time, given the complexities usually found in the response surfaces of hydrological models, increasingly sophisticated analysis methodologies are being proposed for sensitivity analysis, parameter calibration and uncertainty assessment. Quite remarkably, rather than being caused by the model structure/equations themselves, in many cases model analysis complexities are consequences of seemingly trivial aspects of the model implementation - often, literally, whether the start-of-step or end-of-step fluxes are used! The extent of problems can be staggering, including (i) degraded performance of parameter optimization and uncertainty analysis algorithms, (ii) erroneous and/or misleading conclusions of sensitivity analysis, parameter inference and model interpretations and, finally, (iii) poor reliability of a calibrated model in predictive applications. While the often nontrivial behavior of numerical approximations has long been recognized in applied mathematics and in physically-oriented fields of environmental sciences, it remains a problematic issue in many environmental modeling applications. Perhaps detailed attention to numerics is only warranted for complicated engineering models? Would not numerical errors be an insignificant component of total uncertainty when typical data and model approximations are present? Is this really a serious issue beyond some rare isolated

  20. Use of different sampling schemes in machine learning-based prediction of hydrological models' uncertainty

    NASA Astrophysics Data System (ADS)

    Kayastha, Nagendra; Solomatine, Dimitri; Lal Shrestha, Durga; van Griensven, Ann

    2013-04-01

    In recent years, a lot of attention in the hydrologic literature is given to model parameter uncertainty analysis. The robustness estimation of uncertainty depends on the efficiency of sampling method used to generate the best fit responses (outputs) and on ease of use. This paper aims to investigate: (1) how sampling strategies effect the uncertainty estimations of hydrological models, (2) how to use this information in machine learning predictors of models uncertainty. Sampling of parameters may employ various algorithms. We compared seven different algorithms namely, Monte Carlo (MC) simulation, generalized likelihood uncertainty estimation (GLUE), Markov chain Monte Carlo (MCMC), shuffled complex evolution metropolis algorithm (SCEMUA), differential evolution adaptive metropolis (DREAM), partical swarm optimization (PSO) and adaptive cluster covering (ACCO) [1]. These methods were applied to estimate uncertainty of streamflow simulation using conceptual model HBV and Semi-distributed hydrological model SWAT. Nzoia catchment in West Kenya is considered as the case study. The results are compared and analysed based on the shape of the posterior distribution of parameters, uncertainty results on model outputs. The MLUE method [2] uses results of Monte Carlo sampling (or any other sampling shceme) to build a machine learning (regression) model U able to predict uncertainty (quantiles of pdf) of a hydrological model H outputs. Inputs to these models are specially identified representative variables (past events precipitation and flows). The trained machine learning models are then employed to predict the model output uncertainty which is specific for the new input data. The problem here is that different sampling algorithms result in different data sets used to train such a model U, which leads to several models (and there is no clear evidence which model is the best since there is no basis for comparison). A solution could be to form a committee of all models U and

  1. Establishing a connection between hydrologic model parameters and physical catchment signatures for improved hierarchical Bayesian modeling in ungauged catchments

    NASA Astrophysics Data System (ADS)

    Marshall, L. A.; Weber, K.; Smith, T. J.; Greenwood, M. C.; Sharma, A.

    2012-12-01

    In an effort to improve hydrologic analysis in areas with limited data, hydrologists often seek to link catchments where little to no data collection occurs to catchments that are gauged. Various metrics and methods have been proposed to identify such relationships, in the hope that "surrogate" catchments might provide information for those catchments that are hydrologically similar. In this study we present a statistical analysis of over 150 catchments located in southeast Australia to examine the relationship between a hydrological model and certain catchment metrics. A conceptual rainfall-runoff model is optimized for each of the catchments and hierarchical clustering is performed to link catchments based on their calibrated model parameters. Clustering has been used in recent hydrologic studies but catchments are often clustered based on physical characteristics alone. Usually there is little evidence to suggest that such "surrogate" data approaches provide sufficiently similar model predictions. Beginning with model parameters and working backwards, we hope to establish if there is a relationship between the model parameters and physical characteristics for improved model predictions in the ungauged catchment. To analyze relationships, permutational multivariate analysis of variance tests are used that suggest which hydrologic metrics are most appropriate for discriminating between calibrated catchment clusters. Additional analysis is performed to determine which cluster pairs show significant differences for various metrics. We further examine the extent to which these results may be insightful for a hierarchical Bayesian modeling approach that is aimed at generating model predictions at an ungauged site. The method, known as Bayes Empirical Bayes (BEB) works to pool information from similar catchments to generate informed probability distributions for each model parameter at a data-limited catchment of interest. We demonstrate the effect of selecting

  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. Spatial Resolution and Catchment Size Interaction of Soil Hydrological Properties for Hydrological Modeling

    NASA Astrophysics Data System (ADS)

    Libohova, Zamir; Bowling, Laura C.; Owens, Phillip R.; Schoeneberger, Philip; Wysocki, Douglas; Wills, Skye; Lindbo, David

    2016-04-01

    Spatial resolution of soil hydrologic properties is critical for distributed hydrological model streamflow simulations. Soils from US Soil Survey Geographic (SSURGO) Database are mapped at scales varying from 1:12,000 to 65,000. Related to these scales are also soil hydrological properties, which could vary spatially outside of the common SSURGO scale range. The objective of this research was to assess the role of the spatial resolution of soil depth on simulated hydrological response for various watershed sizes using the Distributed Hydrology Soil Vegetation Model (DHSVM). The study site was Hall Creek watershed a 56 km2 in size located in Dubois County in southern Indiana, USA. The watershed size was divided in 55 sub-watersheds varying in size from less than 5 km2 to 56 km2. The grid size spatial resolution of soil hydrological properties varied from 10x10, 30x30 and 90x90m. The simulated streamflow metrics were annual mean, minimum and maximum streamflow, and R-B Flashiness, which measures the variability in streamflow between successive days highlighting the fluctuation of discharge relative to total discharge. The slopes of the regression of simulated stream discharge parameters versus watershed size were used to assess the presence of interaction. In addition, the coefficient of variation was used to assess the variability for the R-B index, annual mean, annual minimum and maximum stream discharge across different model resolutions within each watershed category. The slope for 10x10 and 30x30m spatial resolution for annual mean, and minimum streamflow were not significantly different from zero across all watershed sizes indicating lack of interaction. However, slope for the R-B flashiness was significantly different from zero for the 90x90 m grid size indicating that watershed size change is sensitive at this spatial resolution. The variability of R-B index, annual mean and annual minimum hydrologic metrics decreased with increasing watershed size but

  4. Hydrologic consistency as a basis for assessing complexity of monthly water balance models for the continental United States

    NASA Astrophysics Data System (ADS)

    Martinez, Guillermo F.; Gupta, Hoshin V.

    2011-12-01

    Methods to select parsimonious and hydrologically consistent model structures are useful for evaluating dominance of hydrologic processes and representativeness of data. While information criteria (appropriately constrained to obey underlying statistical assumptions) can provide a basis for evaluating appropriate model complexity, it is not sufficient to rely upon the principle of maximum likelihood (ML) alone. We suggest that one must also call upon a "principle of hydrologic consistency," meaning that selected ML structures and parameter estimates must be constrained (as well as possible) to reproduce desired hydrological characteristics of the processes under investigation. This argument is demonstrated in the context of evaluating the suitability of candidate model structures for lumped water balance modeling across the continental United States, using data from 307 snow-free catchments. The models are constrained to satisfy several tests of hydrologic consistency, a flow space transformation is used to ensure better consistency with underlying statistical assumptions, and information criteria are used to evaluate model complexity relative to the data. The results clearly demonstrate that the principle of consistency provides a sensible basis for guiding selection of model structures and indicate strong spatial persistence of certain model structures across the continental United States. Further work to untangle reasons for model structure predominance can help to relate conceptual model structures to physical characteristics of the catchments, facilitating the task of prediction in ungaged basins.

  5. Top-down methodology for rainfall-runoff modelling and evaluation of hydrological extremes

    NASA Astrophysics Data System (ADS)

    Willems, Patrick

    2014-05-01

    A top-down methodology is presented for implementation and calibration of a lumped conceptual catchment rainfall-runoff model that aims to produce high model performance (depending on the quality and availability of data) in terms of rainfall-runoff discharges for the full range from low to high discharges, including the peak and low flow extremes. The model is to be used to support water engineering applications, which most often deal with high and low flows as well as cumulative runoff volumes. With this application in mind, the paper wants to contribute to the above-mentioned problems and advancements on model evaluation, model-structure selection, the overparameterization problem and the long time the modeller needs to invest or the difficulties one encounters when building and calibrating a lumped conceptual model for a river catchment. The methodology is an empirical and step-wise technique that includes examination of the various model components step by step through a data-based analysis of response characteristics. The approach starts from a generalized lumped conceptual model structure. In this structure, only the general components of a lumped conceptual model, such as the existence of storage and routing elements, and their inter-links, are pre-defined. The detailed specifications on model equations and parameters are supported by advanced time series analysis of the empirical response between the rainfall and evapotranspiration inputs and the river flow output. Subresponses are separated and submodel components and related subsets of parameters are calibrated as independently as possible. At the same time, the model-structure identification process aims to reach parsimonious submodel-structures, and accounts for the serial dependency of runoff values, which typically is higher for low flows than for high flows. It also accounts for the heteroscedasticity and dependency of model residuals when evaluating the model performance. It is shown that this step

  6. Impact of improved snowmelt modelling in a monthly hydrological model.

    NASA Astrophysics Data System (ADS)

    Folton, Nathalie; Garcia, Florine

    2016-04-01

    The quantification and the management of water resources at the regional scale require hydrological models that are both easy to implement and efficient. To be reliable and robust, these models must be calibrated and validated on a large number of catchments that are representative of various hydro-meteorological conditions, physiographic contexts, and specific hydrological behavior (e.g. mountainous catchments). The GRLoiEau monthly model, with its simple structure and its two free parameters, answer our need of such a simple model. It required the development of a snow routine to model catchments with temporarily snow-covered areas. The snow routine developed here does not claim to represent physical snowmelt processes but rather to simulate them globally on the catchment. The snowmelt equation is based on the degree-day method which is widely used by the hydrological community, in particular in engineering studies (Etchevers 2000). A potential snowmelt (Schaefli et al. 2005) was computed, and the parameters of the snow routine were regionalized for each mountain area. The GRLoiEau parsimonious structure requires meteorological data. They come from the distributed mesoscale atmospheric analysis system SAFRAN, which provides estimations of daily solid and liquid precipitations and temperatures on a regular square grid at the spatial resolution of 8*8 km², throughout France. Potential evapotranspiration was estimated using the formula by Oudin et al. (2005). The aim of this study is to improve the quality of monthly simulations for ungauged basins, in particular for all types of mountain catchments, without increasing the number of free parameters of the model. By using daily SAFRAN data, the production store and snowmelt can be run at a daily time scale. The question then arises whether simulating the monthly flows using a production function at a finer time step would improve the results. And by using the SAFRAN distributed climate series, a distributed approach

  7. A strategy for diagnosing and interpreting hydrological model nonstationarity

    NASA Astrophysics Data System (ADS)

    Westra, Seth; Thyer, Mark; Leonard, Michael; Kavetski, Dmitri; Lambert, Martin

    2014-06-01

    This paper presents a strategy for diagnosing and interpreting hydrological nonstationarity, aiming to improve hydrological models and their predictive ability under changing hydroclimatic conditions. The strategy consists of four elements: (i) detecting potential systematic errors in the calibration data; (ii) hypothesizing a set of "nonstationary" parameterizations of existing hydrological model structures, where one or more parameters vary in time as functions of selected covariates; (iii) trialing alternative stationary model structures to assess whether parameter nonstationarity can be reduced by modifying the model structure; and (iv) selecting one or more models for prediction. The Scott Creek catchment in South Australia and the lumped hydrological model GR4J are used to illustrate the strategy. Streamflow predictions improve significantly when the GR4J parameter describing the maximum capacity of the production store is allowed to vary in time as a combined function of: (i) an annual sinusoid; (ii) the previous 365 day rainfall and potential evapotranspiration; and (iii) a linear trend. This improvement provides strong evidence of model nonstationarity. Based on a range of hydrologically oriented diagnostics such as flow-duration curves, the GR4J model structure was modified by introducing an additional calibration parameter that controls recession behavior and by making actual evapotranspiration dependent only on catchment storage. Model comparison using an information-theoretic measure (the Akaike Information Criterion) and several hydrologically oriented diagnostics shows that the GR4J modifications clearly improve predictive performance in Scott Creek catchment. Based on a comparison of 22 versions of GR4J with different representations of nonstationarity and other modifications, the model selection approach applied in the exploratory period (used for parameter estimation) correctly identifies models that perform well in a much drier independent

  8. 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.

  9. 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.

  10. Models for hydrologic design of evapotranspiration landfill covers.

    PubMed

    Hauser, Victor L; Gimon, Dianna M; Bonta, James V; Howell, Terry A; Malone, Robert W; Williams, Jimmy R

    2005-09-15

    The technology used in landfill covers is changing, and an alternative cover called the evapotranspiration (ET) landfill cover is coming into use. Important design requirements are prescribed by Federal rules and regulations for conventional landfill covers but not for ET landfill covers. There is no accepted hydrologic model for ET landfill cover design. This paper describes ET cover requirements and design issues, and assesses the accuracy of the EPIC and HELP hydrologic models when used for hydrologic design of ET covers. We tested the models against high-quality field measurements available from lysimeters maintained by the Agricultural Research Service of the U.S. Department of Agriculture at Coshocton, Ohio, and Bushland, Texas. The HELP model produced substantial errors in estimating hydrologic variables. The EPIC model estimated ET and deep percolation with errors less than 7% and 5%, respectively, and accurately matched extreme events with an error of less than 2% of precipitation. The EPIC model is suitable for use in hydrologic design of ET landfill covers. PMID:16201652

  11. Operational use of distributed hydrological models. Experiences and challenges at a Norwegian hydropower company (Agder Energi).

    NASA Astrophysics Data System (ADS)

    Viggo Matheussen, Bernt; Andresen, Arne; Weisser, Claudia

    2014-05-01

    The Scandinavian hydropower industry has traditionally adopted the lumped conceptual hydrological model - HBV, as the tool for producing forecasts of inflows and mountain snow packs. Such forecasting systems - based on lumped conceptual models - have several drawbacks. Firstly, a lumped model does not produce spatial data, and comparisons with remote sensed snow cover data (which are now available) are complicated. Secondly, several climate parameters such as wind speed are now becoming more available and can potentially improve forecasts due to improved estimates of precipitation gauge efficiency, and more physically correct calculation of turbulent heat fluxes. At last, when the number of catchments increases, it is cumbersome and slow to run multiple hydrology models compared to running one model for all catchments. With the drawbacks of the lumped hydrology models in mind, and with inspiration from other forecasting systems using distributed models, Agder Energy decided to develop a forecasting system applying a physically based distributed model. In this paper we describe an operational inflow and snowpack forecast system developed for the Scandinavian mountain range. The system applies a modern macroscale land surface hydrology model (VIC) which in combination with historical climate data and weather predictions can be used to produce both short-term, and seasonal forecasts of inflow and mountain snowpack. Experiences with the forecast system are illustrated using results from individual subcatchments as well as aggregated regional forecasts of inflow and snowpack. Conversion of water volumes into effective energy inflow are also presented and compared to data from the Nordic hydropower system. Further on, we document several important "lessons-learned" that may be of interest to the hydrological research community. Specifically a semi-automatic data cleansing system combining spatial and temporal visualization techniques with statistical procedures are

  12. Conceptual Models and the Future of Special Education

    ERIC Educational Resources Information Center

    Kauffman, James M.

    2007-01-01

    A medical model has advantages over a legal model in thinking about special education, especially in responding supportively to difference, meeting individual needs, and practicing prevention. The legal conceptual model now dominates thinking about special education, but a medical model promises a brighter future for special education and for…

  13. Hydrological model parameter dimensionality is a weak measure of prediction uncertainty

    NASA Astrophysics Data System (ADS)

    Pande, S.; Arkesteijn, L.; Savenije, H.; Bastidas, L. A.

    2015-04-01

    This paper shows that instability of hydrological system representation in response to different pieces of information and associated prediction uncertainty is a function of model complexity. After demonstrating the connection between unstable model representation and model complexity, complexity is analyzed in a step by step manner. This is done measuring differences between simulations of a model under different realizations of input forcings. Algorithms are then suggested to estimate model complexity. Model complexities of the two model structures, SAC-SMA (Sacramento Soil Moisture Accounting) and its simplified version SIXPAR (Six Parameter Model), are computed on resampled input data sets from basins that span across the continental US. The model complexities for SIXPAR are estimated for various parameter ranges. It is shown that complexity of SIXPAR increases with lower storage capacity and/or higher recession coefficients. Thus it is argued that a conceptually simple model structure, such as SIXPAR, can be more complex than an intuitively more complex model structure, such as SAC-SMA for certain parameter ranges. We therefore contend that magnitudes of feasible model parameters influence the complexity of the model selection problem just as parameter dimensionality (number of parameters) does and that parameter dimensionality is an incomplete indicator of stability of hydrological model selection and prediction problems.

  14. Time-lapse, Distributed Microgravity Observations as a Tool to Inform Hydrological Models

    NASA Astrophysics Data System (ADS)

    Piccolroaz, S.; Majone, B.; Palmieri, F.; Cassiani, G.; Bellin, A.

    2014-12-01

    Thanks to significant advances in technology and modeling capabilities, the use of geophysical monitoring techniques in support of hydrological modeling showed a rapid growth over the last decades. However, at the catchment scale, the payoff in terms of model reliability has not always justified the increased experimental efforts needed in order to collect useful additional information. The objective of this work is to evaluate the advantage gained by coupling traditional hydrological data with unconventional geophysical information in inverse modeling of a complex hydrological system. In particular, we explored how the use of time-lapsed, spatially distributed micro-gravity measurements may improve the conceptual modeling of a complex catchment, allowing for an unambiguous identification of the more appropriate model and a general reduction of uncertainty. The study area is the Vermigliana catchment, a small alpine watershed located in the South-Eastern Alps, Italy. The morphology is relatively complex, being characterized by several minor valleys and ridges with elevation ranging from 950 m a.s.l. to 3558 m a.s.l. The catchment has been monitored by 13 micro-gravity stations (part of a network covering a larger area), where extensive micro-gravity measurements have been performed during 6 field campaign between 2009 and 2011. Sub-daily streamflow data are available at the Vermiglio stream gauging station (with a contributing area of 79 km2) for the same period. Once corrected to remove the effect of ocean tides and instrumental drift, micro-gravity measurements have been used as proxy of changes in the total water storage, including soil moisture, groundwater and snowpack. These data have been combined with streamflow measurements in a multi-objective optimization approach, coupling a semi-distributed hydrological model (GEOTRANSF) with a gravity model. The inclusion of microgravity data resulted in a better constraint of the inversion procedure and an improved

  15. 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.

  16. Linking Hydrology and Atmospheric Sciences in Continental Water Dynamics Modeling

    NASA Astrophysics Data System (ADS)

    David, C. H.; Gochis, D. J.; Maidment, D. R.; Wilhelmi, O.

    2006-12-01

    Atmospheric observation and model output datasets as well as hydrologic datasets are increasingly becoming available on a continental scale. Although the availability of these datasets could allow large-scale water dynamics modeling, the different objects and semantics used in atmospheric science and hydrology set barriers to their interoperability. Recent work has demonstrated the feasibility for modeling terrestrial water dynamics for the continental United States of America. Continental water dynamics defines the interaction of the hydrosphere, the land surface and subsurface at spatial scales ranging from point to continent. The improved version of the National Hydrographic Dataset (NHDPlus, an integrated suite of geospatial datasets stored in a vector and raster GIS format) was used as hydrologic and elevation data input to the Noah community Land Surface Model, developed at NCAR. Noah was successfully run on a watershed in the Ohio River Basin with NHDPlus inputs. The use of NHDPlus as input data for Noah is a crucial improvement for community modeling efforts allowing users to by-pass much of the time consumed in Digital Elevation Model and hydrological network processing. Furthermore, the community Noah land surface model, in its hydrologically-enhanced configuration, is capable of providing flow inputs for a river dynamics model. Continued enhancement of Noah will, as a consequence, be beneficial to the atmospheric science community as well as to the hydrologic community. Ongoing research foci include using a diversity of weather drivers as an input to Noah, and investigation of how to use land surface model outputs for river forecasting, using both the ArcHydro and OpenMI frameworks.

  17. The value of multiple data set calibration versus model complexity for improving the performance of hydrological models in mountain catchments

    NASA Astrophysics Data System (ADS)

    Finger, David; Vis, Marc; Huss, Matthias; Seibert, Jan

    2015-04-01

    The assessment of snow, glacier, and rainfall runoff contribution to discharge in mountain streams is of major importance for an adequate water resource management. Such contributions can be estimated via hydrological models, provided that the modeling adequately accounts for snow and glacier melt, as well as rainfall runoff. We present a multiple data set calibration approach to estimate runoff composition using hydrological models with three levels of complexity. For this purpose, the code of the conceptual runoff model HBV-light was enhanced to allow calibration and validation of simulations against glacier mass balances, satellite-derived snow cover area and measured discharge. Three levels of complexity of the model were applied to glacierized catchments in Switzerland, ranging from 39 to 103 km2. The results indicate that all three observational data sets are reproduced adequately by the model, allowing an accurate estimation of the runoff composition in the three mountain streams. However, calibration against only runoff leads to unrealistic snow and glacier melt rates. Based on these results, we recommend using all three observational data sets in order to constrain model parameters and compute snow, glacier, and rain contributions. Finally, based on the comparison of model performance of different complexities, we postulate that the availability and use of different data sets to calibrate hydrological models might be more important than model complexity to achieve realistic estimations of runoff composition.

  18. Sensitivity of Low Flow Simulations by the HBV-EC Hydrological Model to the Choice of Downscaling Algorithm, Climate Predictors, and Global Climate Model

    NASA Astrophysics Data System (ADS)

    Cannon, A. J.

    2006-12-01

    Hydrological models are one of the main tools used to investigate low flows under future climate change scenarios. Climate data requirements range from high-resolution spatially gridded datasets for distributed hydrological models to site measurements for conceptual hydrological models. In either case, climatological information from coarse resolution Global Climate Models (GCMs) must be used to infer climate series at higher resolutions required by the hydrological models. This is typically done using a procedure known as climate downscaling. The effect of the choice of downscaling algorithm, synoptic-scale predictor dataset, and GCM on the sensitivity of low flow simulations by the HBV-EC hydrological model is the main focus of this study. Different statistical downscaling algorithms (an analog model, a non-parametric weather generator, and a conditional density artificial neural network), predictor datasets (drawn from global atmospheric model reanalyses), and GCMs (the Meteorological Service of Canada's CGCM2, the UK Met Office's HadCM3, and the US Department of Energy sponsored PCM) are used to drive the HBV-EC hydrological model in mountainous watersheds of British Columbia, Canada. The ability of the modeling system to reproduce low flows is validated on historical data and simulated low flows are analyzed for future climate change scenarios.

  19. Modelling hydrological effects of wetland restoration: a differentiated view.

    PubMed

    Staes, J; Rubarenzya, M H; Meire, P; Willems, P

    2009-01-01

    The paper presents findings of a conjunctive hydrological and ecological study into habitat restoration and catchment hydrology. Physically-based, fully distributed hydrological modelling was coupled with spatial analysis and wetland scenario generation techniques to simulate potential effects of restoring lower, middle, and upper catchment wetlands. In the past, anthropogenic interference of this catchments' landscape for agriculture and settlement has left most wetland areas drained, and brought the natural functioning of the ecosystem into conflict with human needs. Many eco-hydrology studies conclude that such disturbances result in a more extreme hydrological regime. The study objectives were to develop and study innovative methods for habitat restoration, and understand the potential hydrological impacts of each approach. The study aims to analyze the scenarios and whether the hydrological response is influenced by the topological placement of the restoration sites. Land-use change scenarios are developed on the basis of physical characteristics and consider the credibility of transitions from current land-use. This study focused on the position of the wetlands in the catchment and hydrological typology. Wetland restoration scenarios are created for different geographical settings within the catchment. A distinction is made between groundwater dependent wetlands and wetlands that are influenced by in-stream water tables or surface water inundations. Results show that there is little effect on the total annual water budget. The results point to river valley rewetting as having the effect of decreasing the paved overland component of stream flow, and increasing the saturated zone flow component. It promoted groundwater recharge. There was no increase of peak flows due to headwater wetlands, contrary to some sources (Bullock & Acreman 2003). The catchments' actual evapotranspiration and root zone water responses were found to be varied over the analysis points

  20. Towards Integrated Hydrological Modeling of A Managed Coastal Mediterranean Wetland (rhone Delta, France).

    NASA Astrophysics Data System (ADS)

    Chauvelon, P.; Tournoud, M. G.; Sandoz, A.

    The Isle of Camargue, central part of the Rhone delta, is a highly anthropized complex hydrosystem, combining agricultural drainage basins, marshes, and shallow brackish lagoons whose connection to the sea is managed. This system is submitted to a strong natural hydrological variability due to mediterranean climate and to an artificial hy- drological regime forced by rice cultivation. Thus, the objective of obtaining an oper- ational tool for water management in this hydrosystem impose to model conjunctively hydrological functionning of the catchment and hydrodynamics of the lagoon system. The used methodology is based on the use of data from a GIS to estimate catchment runoff to the lagoons, and is coupling successively a deterministic approach (hydro- dynamics) and conceptual approach (integrated model for global simulation of hydro- saline functionning). Irrigation inputs are treated in function of land use evolutions, in a georeferenced data base. The developped method allow to estimate the mean ir- rigation water consumption by season and for each irrigation basin. Total runoff from the catchment is estimated by using spatial and hydraulic management characteris- tics of contributive areas in comparison with those from the reference gauged basin. Hydraulic dynamic is studied with a 2D hydrodynamical model of the lagoons. This modeling approach take into account all meteorological forcing conditions (wind, wa- ter level, dischargesE) in order to quantify the hydrodynamic variability of the lagoon system. Simulations results are then used under the form of hydraulic exchange func- tions in a conceptual model in order to simulate the functionning during long periods, using a reservoir model structure. A daily time step is used for this conceptual model, but results in terms of water level and salinity are summed up at a monthly time step.

  1. Multi-Objective Calibration of Hydrological Model Parameters Using MOSCEM-UA

    NASA Astrophysics Data System (ADS)

    Wang, Yuhui; Lei, Xiaohui; Jiang, Yunzhong; Wang, Hao

    2010-05-01

    In the past two decades, many evolutionary algorithms have been adopted in the auto-calibration of hydrological model such as NSGA-II, SCEM, etc., some of which has shown ideal performance. In this article, a detailed hydrological model auto-calibration algorithm Multi-objective Shuffled Complex Evolution Metropolis (MOSCEM-UA) has been introduced to carry out auto-calibration of hydrological model in order to clarify the equilibrium and the uncertainty of model parameters. The development and the implement flow chart of the advanced multi-objective algorithm (MOSCEM-UA) were interpreted in detail. Hymod, a conceptual hydrological model depending on Moore's concept, was then introduced as a lumped Rain-Runoff simulation approach with several principal parameters involved. The five important model parameters subjected to calibration includes maximum storage capacity, spatial variability of the soil moisture capacity, flow distributing factor between slow and quick reservoirs as well as slow tank and quick tank distribution factor. In this study, a test case on the up-stream area of KuanCheng hydrometric station in Haihe basin was studied to verify the performance of calibration. Two objectives including objective for high flow process and objective for low flow process are chosen in the process of calibration. The results emphasized that the interrelationship between objective functions could be described in correlation Pareto Front by using MOSCEM-UA. The Pareto Front can be draw after the iteration. Further more, post range of parameters corresponding to Pareto sets could also be drawn to identify the prediction range of the model. Then a set of balanced parameter was chosen to validate the model and the result showed an ideal prediction. Meanwhile, the correlation among parameters and their effects on the model performance could also be achieved.

  2. Modeling of reservoir operation in UNH global hydrological model

    NASA Astrophysics Data System (ADS)

    Shiklomanov, Alexander; Prusevich, Alexander; Frolking, Steve; Glidden, Stanley; Lammers, Richard; Wisser, Dominik

    2015-04-01

    Climate is changing and river flow is an integrated characteristic reflecting numerous environmental processes and their changes aggregated over large areas. Anthropogenic impacts on the river flow, however, can significantly exceed the changes associated with climate variability. Besides of irrigation, reservoirs and dams are one of major anthropogenic factor affecting streamflow. They distort hydrological regime of many rivers by trapping of freshwater runoff, modifying timing of river discharge and increasing the evaporation rate. Thus, reservoirs is an integral part of the global hydrological system and their impacts on rivers have to be taken into account for better quantification and understanding of hydrological changes. We developed a new technique, which was incorporated into WBM-TrANS model (Water Balance Model-Transport from Anthropogenic and Natural Systems) to simulate river routing through large reservoirs and natural lakes based on information available from freely accessible databases such as GRanD (the Global Reservoir and Dam database) or NID (National Inventory of Dams for US). Different formulations were applied for unregulated spillway dams and lakes, and for 4 types of regulated reservoirs, which were subdivided based on main purpose including generic (multipurpose), hydropower generation, irrigation and water supply, and flood control. We also incorporated rules for reservoir fill up and draining at the times of construction and decommission based on available data. The model were tested for many reservoirs of different size and types located in various climatic conditions using several gridded meteorological data sets as model input and observed daily and monthly discharge data from GRDC (Global Runoff Data Center), USGS Water Data (US Geological Survey), and UNH archives. The best results with Nash-Sutcliffe model efficiency coefficient in the range of 0.5-0.9 were obtained for temperate zone of Northern Hemisphere where most of large

  3. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2016-03-01

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

  5. Understanding uncertainty in process-based hydrological models

    NASA Astrophysics Data System (ADS)

    Clark, M. P.; Kavetski, D.; Slater, A. G.; Newman, A. J.; Marks, D. G.; Landry, C.; Lundquist, J. D.; Rupp, D. E.; Nijssen, B.

    2013-12-01

    Building an environmental model requires making a series of decisions regarding the appropriate representation of natural processes. While some of these decisions can already be based on well-established physical understanding, gaps in our current understanding of environmental dynamics, combined with incomplete knowledge of properties and boundary conditions of most environmental systems, make many important modeling decisions far more ambiguous. There is consequently little agreement regarding what a 'correct' model structure is, especially at relatively larger spatial scales such as catchments and beyond. In current practice, faced with such a range of decisions, different modelers will generally make different modeling decisions, often on an ad hoc basis, based on their balancing of process understanding, the data available to evaluate the model, the purpose of the modeling exercise, and their familiarity with or investment in an existing model infrastructure. This presentation describes development and application of multiple-hypothesis models to evaluate process-based hydrologic models. Our numerical model uses robust solutions of the hydrology and thermodynamic governing equations as the structural core, and incorporates multiple options to represent the impact of different modeling decisions, including multiple options for model parameterizations (e.g., below-canopy wind speed, thermal conductivity, storage and transmission of liquid water through soil, etc.), as well as multiple options for model architecture, that is, the coupling and organization of different model components (e.g., representations of sub-grid variability and hydrologic connectivity, coupling with groundwater, etc.). Application of this modeling framework across a collection of different research basins demonstrates that differences among model parameterizations are often overwhelmed by differences among equally-plausible model parameter sets, while differences in model architecture lead

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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...

  7. Developing Models of Communicative Competence: Conceptual, Statistical, and Methodological Considerations.

    ERIC Educational Resources Information Center

    Cziko, Gary A.

    The development of an empirically based model of communicative competence is discussed in terms of conceptual, statistical, and methodological considerations. A distinction is made between descriptive and working models of communicative competence. Working models attempt to show how components of communicative competence are interrelated…

  8. A Conceptual Model of Career Development to Enhance Academic Motivation

    ERIC Educational Resources Information Center

    Collins, Nancy Creighton

    2010-01-01

    The purpose of this study was to develop, refine, and validate a conceptual model of career development to enhance the academic motivation of community college students. To achieve this end, a straw model was built from the theoretical and empirical research literature. The model was then refined and validated through three rounds of a Delphi…

  9. A Conceptual Model To Assist Educational Leaders Manage Change.

    ERIC Educational Resources Information Center

    Cochren, John R.

    This paper presents a conceptual model to help school leaders manage change effectively. The model was developed from a literature review of theory development and model construction. Specifically, the paper identifies the major components that inhibit organizational change, and synthesizes the most salient features of these components through a…

  10. CONCEPTUAL FRAMEWORK FOR REGRESSION MODELING OF GROUND-WATER FLOW.

    USGS Publications Warehouse

    Cooley, Richard L.

    1985-01-01

    The author examines the uses of ground-water flow models and which classes of use require treatment of stochastic components. He then compares traditional and stochastic procedures for modeling actual (as distinguished from hypothetical) systems. Finally, he examines the conceptual basis and characteristics of the regression approach to modeling ground-water flow.

  11. Implementations Are Not Conceptualizations: Revising the Verb Learning Model.

    ERIC Educational Resources Information Center

    MacWhinney, Brian; Leinbach, Jared

    A model of the child's learning of the past tense forms of English verbs is discussed. This connectionist model takes as input a present-tense verb and provides as output a past tense form. A new simulation is applied to 13 problems raised by critics of the model, presented as fundamental flaws in the conceptualizations underlying connectionism.…

  12. Impact of Model Uncertainty Description on Assimilating Hydraulic Head into the MIKE-SHE Distributed Hydrological Model

    NASA Astrophysics Data System (ADS)

    Zhang, D.; Madsen, H.; Ridler, M. E.; Rasmussen, J.; Refsgaard, J.; Jensen, K.

    2013-12-01

    Catchment-scale hydrological models are used as prediction tools to solve major challenges in water resources management. The reliability of hydrological model predictions is inevitably affected by the amount of information available to set up and calibrate the model. Data assimilation (DA) which combines complementary information from measurements and models has proven to be a powerful and promising tool in numerous research studies to improve model predictions. Especially, the ensemble Kalman filter (EnKF) which is a popular sequential data assimilation technique, has been extensively studied in the earth sciences for assimilating in-situ measurements and remote sensing data. However, one of the major challenges in data assimilation to optimally combine model and measurements is the description of model uncertainty. Only few studies have been reported for defining appropriate model uncertainty in hydrological DA. Modeling uncertainties can be conceptually different in different applications. Traditionally, model uncertainty is represented by parameter uncertainty with corresponding parameter statistics determined by inverse modeling. In most hydrological DA applications, however, model uncertainty is defined by experience using simple statistical descriptions of different uncertainty sources. In this work, both the uncertainty derived from inverse modeling and from empirical knowledge are used and analyzed. A combination of parameter-based, forcing-based and state-based model error is implemented in the EnKF framework for assimilating groundwater hydraulic heads into a catchment-scale model of the Karup Catchment in Denmark using the distributed and integrated hydrological model MIKE SHE. A series of synthetic identical twin experiments are carried out to analyze the impact of different model error assumptions on the feasibility and efficiency of the assimilation. The optimality of the EnKF underlying twin test provides possibilities to diagnose model error

  13. Performance measures and criteria for hydrologic and water quality models

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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...

  14. Hydrologic and water quality teminology as applied to modeling

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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...

  15. A fully integrated SWAT-MODFLOW hydrologic model

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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 ...

  16. 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)

  17. 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.

  18. Evolution of an operational hydrological model: from global to semi-distributed approach

    NASA Astrophysics Data System (ADS)

    Garavaglia, Federico; Le Lay, Matthieu; Gottardi, Frédéric; Garçon, Rémy

    2016-04-01

    MORDOR is a conceptual hydrological model extensively used in Électricité de France (EDF, French electric utility company) for operational applications: (i) hydrological forecasting, (ii) flood risk assessment, (iii) water balance and (iv) climate change studies. In its historical version, hereafter called MORDOR1996, this is a lumped, reservoir, elevation based model with hourly or daily areal rainfall and air temperature as the driving input data. The principal hydrological processes represented are evapotranspiration, direct and indirect runoff, ground water, snow and ice accumulation and melt, routing. The model has been intensively used at EDF for more than 25 years, in particular for modeling French mountainous watersheds. In order to consider the spatial heterogeneity of the input data (rainfall and air temperature) and the hydrological characteristics within a basin, the structure of model has been updated. The new version of the model, named MORDOR SD, is a semi-distributed hydrological model driven by elevation. The basin is spitted into several elevation bands on which a simple global MORDOR model is implemented; i.e. only evapotranspiration, direct and indirect runoff, snow and ice accumulation and melt are computed. However ground water and routing processes remain global. The primary purpose of this study is to present MORDOR SD model through a comparison with the historical version. The first result of this comparative study is that the new version provides better calibration-validation performances. Moreover the semi-distributed approach both allows to simplify the model structure (i.e. less degrees of freedom) and to reduce the equifinality problem in the calibration process. The model's parameters are calibrated at daily timestep with a genetic algorithm that uses a composed objective function. This complex function quantifies the good agreement between the simulated and observed runoff focusing on four different runoff samples: (i) time

  19. A conceptual model for determining career choice of CHROME alumna based on farmer's conceptual models

    NASA Astrophysics Data System (ADS)

    Moore, Lisa Simmons

    This qualitative program evaluation examines the career decision-making processes and career choices of nine, African American women who participated in the Cooperating Hampton Roads Organization for Minorities in Engineering (CHROME) and who graduated from urban, rural or suburban high schools in the year 2000. The CHROME program is a nonprofit, pre-college intervention program that encourages underrepresented minority and female students to enter science, technically related, engineering, and math (STEM) career fields. The study describes career choices and decisions made by each participant over a five-year period since high school graduation. Data was collected through an Annual Report, Post High School Questionnaires, Environmental Support Questionnaires, Career Choice Questionnaires, Senior Reports, and standardized open-ended interviews. Data was analyzed using a model based on Helen C. Farmer's Conceptual Models, John Ogbu's Caste Theory and Feminist Theory. The CHROME program, based on its stated goals and tenets, was also analyzed against study findings. Findings indicated that participants received very low levels of support from counselors and teachers to pursue STEM careers and high levels of support from parents and family, the CHROME program and financial backing. Findings of this study also indicated that the majority of CHROME alumna persisted in STEM careers. The most successful participants, in terms of undergraduate degree completion and occupational prestige, were the African American women who remained single, experienced no critical incidents, came from a middle class to upper middle class socioeconomic background, and did not have children.

  20. 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.

  1. 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.

  2. Identifying students' mental models of sound propagation: The role of conceptual blending in understanding conceptual change

    NASA Astrophysics Data System (ADS)

    Hrepic, Zdeslav; Zollman, Dean A.; Rebello, N. Sanjay

    2010-07-01

    We investigated introductory physics students’ mental models of sound propagation. We used a phenomenographic method to analyze the data in the study. In addition to the scientifically accepted Wave model, students used the “Entity” model to describe the propagation of sound. In this latter model sound is a self-standing entity, different from the medium through which it propagates. All other observed alternative models contain elements of both Entity and Wave models, but at the same time are distinct from each of the constituent models. We called these models “hybrid” or “blend” models. We discuss how students use these models in various contexts before and after instruction and how our findings contribute to the understanding of conceptual change. Implications of our findings for teaching are summarized.

  3. Guide for developing conceptual models for ecological risk assessments

    SciTech Connect

    Suter, G.W., II

    1996-05-01

    Ecological conceptual models are the result of the problem formulation phase of an ecological risk assessment, which is an important component of the Remedial Investigation process. They present hypotheses of how the site contaminants might affect the site ecology. The contaminant sources, routes, media, routes, and endpoint receptors are presented in the form of a flow chart. This guide is for preparing the conceptual models; use of this guide will standardize the models so that they will be of high quality, useful to the assessment process, and sufficiently consistent so that connections between sources of exposure and receptors can be extended across operable units (OU). Generic conceptual models are presented for source, aquatic integrator, groundwater integrator, and terrestrial OUs.

  4. Conceptual model for transferring information between small watersheds

    USGS Publications Warehouse

    Cleaves, E.T.

    2003-01-01

    Stream and watershed management and restoration can be greatly facilitated through use of physiographic landform classification to organize and communicate natural resource, hazard, and environmental information at a broad scale (1:250,000) as illustrated by the Piedmont and Coastal Plain Provinces in Maryland, or at a small scale (1:24,000) as illustrated using divisions and zones combined with a conceptual model. The conceptual model brings together geology, surficial processes, landforms and land use change information at the small watershed scale and facilitates transfer of information from one small watershed to another with similar geology and landforms. Stream flow, sediment erosion, and water quality illustrate the use of the model.

  5. Assessing the hydrologic restoration of an urbanized area via integrated distributed hydrological model

    NASA Astrophysics Data System (ADS)

    Trinh, D. H.; Chui, T. F. M.

    2013-04-01

    Green structures (e.g. green roof and bio-retention systems) are adopted to mitigate the hydrological impacts of urbanization. However, our current understanding of the urbanization impacts are often process-specific (e.g. peak flow or storm recession), and our characterizations of green structures are often on a local scale. This study uses an integrated distributed hydrological model, Mike SHE, to evaluate the urbanization impacts on both overall water balance and water regime, and also the effectiveness of green structures at a catchment level. Three simulations are carried out for a highly urbanized catchment in the tropics, representing pre-urbanized, urbanized and restored conditions. Urbanization transforms vegetated areas into impervious surfaces, resulting in 20 and 66% reductions in infiltration and base flow respectively, and 60 to 100% increase in peak outlet discharge. Green roofs delay the peak outlet discharge by 2 h and reduce the magnitude by 50%. Bio-retention systems mitigate the peak discharge by 50% and also enhance infiltration by 30%. The combination of green roofs and bio-retention systems even reduces the peak discharge to the pre-urbanized level. The simulation results obtained are independent of field data, enabling a generic model for understanding hydrological changes during the different phases of urbanization. This will benefit catchment level planning of green structures in other urban areas.

  6. Assessing the hydrologic restoration of an urbanized area via an integrated distributed hydrological model

    NASA Astrophysics Data System (ADS)

    Trinh, D. H.; Chui, T. F. M.

    2013-12-01

    Green structures (e.g. green roof and bio-retention systems) are adopted to mitigate the hydrological impacts of urbanization. However, our current understanding of urbanization impacts are often process-specific (e.g. peak flow or storm recession), and our characterizations of green structures are often on a local scale. This study uses an integrated distributed hydrological model, Mike SHE, to evaluate the urbanization impacts on both overall water balance and water regime, and also the effectiveness of green structures at a catchment level. Three simulations are carried out for a highly urbanized catchment in the tropics, representing pre-urbanized, urbanized and restored conditions. Urbanization transforms vegetated areas into impervious surfaces, resulting in 20 and 66% reductions in infiltration and base flow respectively, and 60 to 100% increase in peak outlet discharge. Green roofs delay the peak outlet discharge by 2 h and reduce the magnitude by 50%. Bio-retention systems mitigate the peak discharge by 50% and also enhance infiltration by 30%. The combination of green roofs and bio-retention systems even reduces the peak discharge to the pre-urbanized level. The simulation results obtained are independent of field data, enabling a generic model for understanding hydrological changes during the different phases of urbanization. This will benefit catchment-level planning of green structures in other urban areas.

  7. Equifinality of formal (DREAM) and informal (GLUE) bayesian approaches in hydrologic modeling?

    SciTech Connect

    Vrugt, Jasper A; Robinson, Bruce A; Ter Braak, Cajo J F; Gupta, Hoshin V

    2008-01-01

    In recent years, a strong debate has emerged in the hydrologic literature regarding what constitutes an appropriate framework for uncertainty estimation. Particularly, there is strong disagreement whether an uncertainty framework should have its roots within a proper statistical (Bayesian) context, or whether such a framework should be based on a different philosophy and implement informal measures and weaker inference to summarize parameter and predictive distributions. In this paper, we compare a formal Bayesian approach using Markov Chain Monte Carlo (MCMC) with generalized likelihood uncertainty estimation (GLUE) for assessing uncertainty in conceptual watershed modeling. Our formal Bayesian approach is implemented using the recently developed differential evolution adaptive metropolis (DREAM) MCMC scheme with a likelihood function that explicitly considers model structural, input and parameter uncertainty. Our results demonstrate that DREAM and GLUE can generate very similar estimates of total streamflow uncertainty. This suggests that formal and informal Bayesian approaches have more common ground than the hydrologic literature and ongoing debate might suggest. The main advantage of formal approaches is, however, that they attempt to disentangle the effect of forcing, parameter and model structural error on total predictive uncertainty. This is key to improving hydrologic theory and to better understand and predict the flow of water through catchments.

  8. The reduction of hydrological models for less tedious practical applications

    NASA Astrophysics Data System (ADS)

    Delay, Frederick; Ackerer, Philippe

    2016-02-01

    This work evidences that inconsistencies may persist between the complexity of hydrological models and available data for model documentation and application. For example, the integrated hydrological models handle the whole water dynamics over a watershed, but are only conditioned on data that incompletely record the dimensions of the flow. It is suggested to reduce this type of model by aggregating the physical background to diminish its Euclidean dimension. Paradoxically, the complexity in the physics of a model may also result in some reduction. For example, handling a flow by relying upon a dual continuum approach conceals the structural heterogeneity of the reservoir in the model equations. The parameterization at the scale of the aquifer becomes much simpler and the model reduction is here associated with diminishing the effort to condition the model onto data.

  9. Introduction of the 2nd Phase of the Integrated Hydrologic Model Intercomparison Project

    NASA Astrophysics Data System (ADS)

    Kollet, Stefan; Maxwell, Reed; Dages, Cecile; Mouche, Emmanuel; Mugler, Claude; Paniconi, Claudio; Park, Young-Jin; Putti, Mario; Shen, Chaopeng; Stisen, Simon; Sudicky, Edward; Sulis, Mauro; Ji, Xinye

    2015-04-01

    The 2nd Phase of the Integrated Hydrologic Model Intercomparison Project commenced in June 2013 with a workshop at Bonn University funded by the German Science Foundation and US National Science Foundation. Three test cases were defined and compared that are available online at www.hpsc-terrsys.de including a tilted v-catchment case; a case called superslab based on multiple slab-heterogeneities in the hydraulic conductivity along a hillslope; and the Borden site case, based on a published field experiment. The goal of this phase is to further interrogate the coupling of surface-subsurface flow implemented in various integrated hydrologic models; and to understand and quantify the impact of differences in the conceptual and technical implementations on the simulation results, which may constitute an additional source of uncertainty. The focus has been broadened considerably including e.g. saturated and unsaturated subsurface storages, saturated surface area, ponded surface storage in addition to discharge, and pressure/saturation profiles and cross-sections. Here, first results are presented and discussed demonstrating the conceptual and technical challenges in implementing essentially the same governing equations describing highly non-linear moisture redistribution processes and surface-groundwater interactions.

  10. Supporting user-defined granularities in a spatiotemporal conceptual model

    USGS Publications Warehouse

    Khatri, V.; Ram, S.; Snodgrass, R.T.; O'Brien, G. M.

    2002-01-01

    Granularities are integral to spatial and temporal data. A large number of applications require storage of facts along with their temporal and spatial context, which needs to be expressed in terms of appropriate granularities. For many real-world applications, a single granularity in the database is insufficient. In order to support any type of spatial or temporal reasoning, the semantics related to granularities needs to be embedded in the database. Specifying granularities related to facts is an important part of conceptual database design because under-specifying the granularity can restrict an application, affect the relative ordering of events and impact the topological relationships. Closely related to granularities is indeterminacy, i.e., an occurrence time or location associated with a fact that is not known exactly. In this paper, we present an ontology for spatial granularities that is a natural analog of temporal granularities. We propose an upward-compatible, annotation-based spatiotemporal conceptual model that can comprehensively capture the semantics related to spatial and temporal granularities, and indeterminacy without requiring new spatiotemporal constructs. We specify the formal semantics of this spatiotemporal conceptual model via translation to a conventional conceptual model. To underscore the practical focus of our approach, we describe an on-going case study. We apply our approach to a hydrogeologic application at the United States Geologic Survey and demonstrate that our proposed granularity-based spatiotemporal conceptual model is straightforward to use and is comprehensive.

  11. Conceptual model for assessment of inhalation exposure: defining modifying factors.

    PubMed

    Tielemans, Erik; Schneider, Thomas; Goede, Henk; Tischer, Martin; Warren, Nick; Kromhout, Hans; Van Tongeren, Martie; Van Hemmen, Joop; Cherrie, John W

    2008-10-01

    The present paper proposes a source-receptor model to schematically describe inhalation exposure to help understand the complex processes leading to inhalation of hazardous substances. The model considers a stepwise transfer of a contaminant from the source to the receptor. The conceptual model is constructed using three components, i.e. (i) the source, (ii) various transmission compartments and (iii) the receptor, and describes the contaminant's emission and its pattern of transport. Based on this conceptual model, a list of nine mutually independent principal modifying factors (MFs) is proposed: activity emission potential, substance emission potential, localized control, separation, segregation, dilution, worker behavior, surface contamination and respiratory protection. These MFs describe the exposure process at a high level of abstraction so that the model can be generically applicable. A list of exposure determinants underlying each of these principal MFs is proposed to describe the exposure process at a more detailed level. The presented conceptual model is developed in conjunction with an activity taxonomy as described in a separate paper. The proposed conceptual model and MFs should be seen as 'building blocks' for development of higher tier exposure models. PMID:18787181

  12. Revisiting "Discrepancy Analysis in Continuing Medical Education: A Conceptual Model"

    ERIC Educational Resources Information Center

    Fox, Robert D.

    2011-01-01

    Based upon a review and analysis of selected literature, the author presents a conceptual model of discrepancy analysis evaluation for planning, implementing, and assessing the impact of continuing medical education (CME). The model is described in terms of its value as a means of diagnosing errors in the development and implementation of CME. The…

  13. What Is FRBR? A Conceptual Model for the Bibliographic Universe

    ERIC Educational Resources Information Center

    Tillett, Barbara

    2005-01-01

    From 1992 to 1995 the IFLA Study Group on Functional Requirements for Bibliographic Records (FRBR) developed an entity relationship model as a generalised view of the bibliographic universe, intended to be independent of any cataloguing code or implementation. The FRBR report itself includes a description of the conceptual model (the entities,…

  14. A Conceptual Model of Multiple Dimensions of Identity.

    ERIC Educational Resources Information Center

    Jones, Susan R.; McEwen, Marylu K.

    2000-01-01

    Presents a conceptual model of multiple dimensions of identity, which depicts a core sense of self or one's personal identity. Intersecting circles surrounding the core identity represent significant identity dimensions and contextual influences. The model evolved from a grounded theory study of a group of 10 women college students ranging in age…

  15. Assimilation of ASCAT-derived soil wetness indices into hydrological models

    NASA Astrophysics Data System (ADS)

    Matgen, Patrick; Heitz, Sonia; Giustarini, L.; Pfister, Laurent

    2010-05-01

    Over the last decade, many studies demonstrated that spatial information on the distributed physiogeographical characteristics and hydrological responses of rivers basins can be gained from remote sensing observations. Moreover, the onset of new Earth Observation (EO) constellations and technologies enables the supply and processing of multi-mission satellite data at a temporal frequency that starts to become compatible with operational water resources management requirements. Nonetheless, a time continuity that is crucial in both monitoring and forecasting applications cannot be obtained by the sole use of remote sensing observations. The information that may be extracted from discrete EO data thus needs to be used as time-varying state or flux data in hydrological models. This paper focuses on the sequential assimilation of remote sensing-derived soil wetness indices (SWI) into a lumped conceptual hydrological model and investigates the reliability and usefulness of a systematic remote sensing of soil wetness for operational forecasting applications. Since soil moisture patterns tend to persist in time, SWI obtained via scatterometers operating at coarse resolution can be used to periodically verify and eventually update the water budget that is computed by hydrological models. Our study is based on bi-daily coarse resolution soil moisture estimates retrieved from the ASCAT instrument on board the METOP-A satellite. The overall objective is the evaluation of the potential of Particle Filter-based data assimilation schemes for increasing the accuracy and reliability of flood predictions at subsequent time steps. The proposed methodology consists in adjusting the soil reservoirs simulated by a hydrologic model, by comparing an ensemble of modeled soil wetness indices with those that are derived from remote sensing observations. We advocate the use of a Particle Filter as part of the proposed assimilation scheme because it provides flexibility regarding the form of

  16. Comparison of a Neural Network and a Conceptual Model for Rainfall-Runoff Modelling with Monthly Input

    NASA Astrophysics Data System (ADS)

    Chochlidakis, Chronis; Daliakopoulos, Ioannis; Tsanis, Ioannis

    2014-05-01

    Rainfall-runoff (RR) models contain parameters that can seldom be directly measured or estimated by expert judgment, but are rather inferred by calibration against a historical record of input-output datasets. Here, a comparison is made between a conceptual model and an Artificial Neural Network (ANN) for efficient modeling of complex hydrological processes. The monthly rainfall, streamflow, and evapotranspiration data from 15 catchments in Crete, Greece are used to compare the proposed methodologies. Genetic Algorithms (GA) are applied for the stochastic calibration of the parameters in the Sacramento Soil Moisture Accounting (SAC-SMA) model yielding R2 values between 0.65 and 0.90. A Feedforward NN (FNN) is trained using a time delay approach, optimized through trial and error for each catchment, yielding R2 values between 0.70 and 0.91. The results obtained show that the ANN models can be superior to the conventional conceptual models due to their ability to handle the non-linearity and dynamic nature of the natural physical processes in a more efficient manner. On the other hand, SAC-SMA depicts high flows with greater accuracy and results suggest that conceptual models can be more robust in extrapolating beyond historical record limits.

  17. Development of human impact modeling in global hydrology

    NASA Astrophysics Data System (ADS)

    Bierkens, M. F.; Wada, Y.

    2015-12-01

    During the late 1980s and early 1990s, awareness of the shortage of global water resources lead to the first detailed global water resources assessments comparing water availability with water use. These first efforts mostly relied on 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 proxy by accumulating runoff over a stream network and comparing it with population densities or with estimated water demand. In this talk we review the evolution of human impact modelling in global hydrology, e.g.: confronting yearly water demand with water availability using a water scarcity index; calculating a water scarcity index at monthly time scale; adding groundwater depletion; adding dams and reservoirs; fully integrating water use (abstraction, application, consumption, return flow) in the hydrology; simulating the effects of land use change. A number of challenges are identified that hamper the further development of current water use modelling as well as prohibit realistic modelling of future water use. We also speculate on pathways to overcome these challenges.

  18. High resolution distributed hydrological modeling for river flood forecasting

    NASA Astrophysics Data System (ADS)

    Chen, Y.

    2014-12-01

    High resolution distributed hydrological model can finely describe the river basin hydrological processes, thus having the potential to improve the flood forecasting capabilities, and is regarded as the next generation flood forecast model. But there are great challenges in deploying it in real-time river flood forecasting, such as the awesome computation resources requirement, parameter determination, high resolution precipitation assimilation and uncertainty controls. Liuxihe Model is a physically-based distributed hydrological model proposed mainly for catchment flood forecasting, which is a process-based hydrological model. In this study, based on Liuxihe Model, a parallel computation algorithm for Liuxihe model flood forecasting is proposed, and a cloudy computation system is developed on a high performance computer, this largely improves the applicability of Liuxihe Model in large river. Without the parallel computation, the Liuxihe Model is computationally incapable in application to rivers with drainage area bigger than 10,000km2 at the grid size of 100m. With the parallel computation, the Liuxihe Model is used in a river with a drainage area of 60,000km2, and could be expended indefinitely. Based on this achievement, a model parameter calibration method by using Particle Swale Optimization is proposed and tested in several rivers in southern China with drainage areas ranging from several hundreds to tens thousands km2, and with the model parameter optimization, the model performance has been approved largely. The modeling approach is also tested for coupling radar-based precipitation estimation/prediction for small catchment flash forecasting and for coupling quantitative precipitation estimation/prediction from meteorological model for large river flood forecasting.

  19. A prototype framework for models of socio-hydrology: identification of key feedback loops and parameterisation approach

    NASA Astrophysics Data System (ADS)

    Elshafei, Y.; Sivapalan, M.; Tonts, M.; Hipsey, M. R.

    2014-06-01

    It is increasingly acknowledged that, in order to sustainably manage global freshwater resources, it is critical that we better understand the nature of human-hydrology interactions at the broader catchment system scale. Yet to date, a generic conceptual framework for building models of catchment systems that include adequate representation of socioeconomic systems - and the dynamic feedbacks between human and natural systems - has remained elusive. In an attempt to work towards such a model, this paper outlines a generic framework for models of socio-hydrology applicable to agricultural catchments, made up of six key components that combine to form the coupled system dynamics: namely, catchment hydrology, population, economics, environment, socioeconomic sensitivity and collective response. The conceptual framework posits two novel constructs: (i) a composite socioeconomic driving variable, termed the Community Sensitivity state variable, which seeks to capture the perceived level of threat to a community's quality of life, and acts as a key link tying together one of the fundamental feedback loops of the coupled system, and (ii) a Behavioural Response variable as the observable feedback mechanism, which reflects land and water management decisions relevant to the hydrological context. The framework makes a further contribution through the introduction of three macro-scale parameters that enable it to normalise for differences in climate, socioeconomic and political gradients across study sites. In this way, the framework provides for both macro-scale contextual parameters, which allow for comparative studies to be undertaken, and catchment-specific conditions, by way of tailored "closure relationships", in order to ensure that site-specific and application-specific contexts of socio-hydrologic problems can be accommodated. To demonstrate how such a framework would be applied, two socio-hydrological case studies, taken from the Australian experience, are presented

  20. A hybrid conceptual-fuzzy inference streamflow modelling for the Letaba River system in South Africa

    NASA Astrophysics Data System (ADS)

    Katambara, Zacharia; Ndiritu, John G.

    There has been considerable water resources developments in South Africa and other regions in the world in order to meet the ever-increasing water demands. These developments have not been matched with a similar development of hydrological monitoring systems and hence there is inadequate data for managing the developed water resources systems. The Letaba River system ( Fig. 1) is a typical case of such a system in South Africa. The available water on this river is over-allocated and reliable daily streamflow modelling of the Letaba River that adequately incorporates the main components and processes would be an invaluable aid to optimal operation of the system. This study describes the development of a calibrated hybrid conceptual-fuzzy-logic model and explores its capability in reproducing the natural processes and human effects on the daily stream flow in the Letaba River. The model performance is considered satisfactory in view of the complexity of the system and inadequacy of relevant data. Performance in modelling streamflow improves towards the downstream and matches that of a stand-alone fuzzy-logic model. The hybrid model obtains realistic estimates of the major system components and processes including the capacities of the farm dams and storage weirs and their trajectories. This suggests that for complex data-scarce River systems, hybrid conceptual-fuzzy-logic modelling may be used for more detailed and dependable operational and planning analysis than stand-alone fuzzy modelling. Further work will include developing and testing other hybrid model configurations.

  1. A surface hydrology model for regional vector borne disease models

    NASA Astrophysics Data System (ADS)

    Tompkins, Adrian; Asare, Ernest; Bomblies, Arne; Amekudzi, Leonard

    2016-04-01

    Small, sun-lit temporary pools that form during the rainy season are important breeding sites for many key mosquito vectors responsible for the transmission of malaria and other diseases. The representation of this surface hydrology in mathematical disease models is challenging, due to their small-scale, dependence on the terrain and the difficulty of setting soil parameters. Here we introduce a model that represents the temporal evolution of the aggregate statistics of breeding sites in a single pond fractional coverage parameter. The model is based on a simple, geometrical assumption concerning the terrain, and accounts for the processes of surface runoff, pond overflow, infiltration and evaporation. Soil moisture, soil properties and large-scale terrain slope are accounted for using a calibration parameter that sets the equivalent catchment fraction. The model is calibrated and then evaluated using in situ pond measurements in Ghana and ultra-high (10m) resolution explicit simulations for a village in Niger. Despite the model's simplicity, it is shown to reproduce the variability and mean of the pond aggregate water coverage well for both locations and validation techniques. Example malaria simulations for Uganda will be shown using this new scheme with a generic calibration setting, evaluated using district malaria case data. Possible methods for implementing regional calibration will be briefly discussed.

  2. 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

  3. 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

  4. 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.

  5. Hydrologic and water quality models: Performance measures and evaluation criteria

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Performance measures and corresponding criteria constitute an important aspect of calibration and validation of any hydrological and water quality (H/WQ) model. As new and improved methods and information are developed, it is essential that performance measures and criteria be updated. Therefore, th...

  6. Information and complexity measures for hydrologic model evaluation

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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...

  7. Hydrologic and water quality models: Use, calibration, and validation

    Technology Transfer Automated Retrieval System (TEKTRAN)

    This paper introduces a special collection of 22 research articles that present and discuss calibration and validation concepts in detail for hydrologic and water quality models by their developers and presents a broad framework for developing the American Society of Agricultural and Biological Engi...

  8. 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. PMID:24569270

  9. Hydrologic and water quality modeling: spatial and temporal considerations

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Hydrologic and water quality models are used to help manage water resources by investigating the effects of climate, land use, land management, and water management on water resources. Each water-related issue is better investigated at a specific scale, which can vary spatially from point to watersh...

  10. Hydrological modeling using a multi-site stochastic weather generator

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Weather data is usually required at several locations over a large watershed, especially when using distributed models for hydrological simulations. In many applications, spatially correlated weather data can be provided by a multi-site stochastic weather generator which considers the spatial correl...

  11. Generating distributed forcing fields for spatial hydrologic modeling

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Spatial hydrologic modeling requires the development of distributed forcing fields of weather and precipitation. This is particularly difficult in mountainous regions of the western US, where measurement sites are limited and the landscape is dominated by complex terrain and variations in vegetatio...

  12. 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...

  13. 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

  14. A Conceptual Critique of Sternberg's WICS Model

    ERIC Educational Resources Information Center

    Koro-Ljungberg, Mirka

    2003-01-01

    Robert Sternberg's model of giftedness brings together interesting and very important elements of giftedness by synthesizing wisdom, intelligence, and creativity in novel ways. While his model is based on extensive research and utilizes a variety of sources and expertise, the epistemological consistency of Sternberg's model is, in the author's…

  15. Decomposition of the Mean Squared Error and NSE Performance Criteria: Implications for Improving Hydrological Modelling

    NASA Technical Reports Server (NTRS)

    Gupta, Hoshin V.; Kling, Harald; Yilmaz, Koray K.; Martinez-Baquero, Guillermo F.

    2009-01-01

    The mean squared error (MSE) and the related normalization, the Nash-Sutcliffe efficiency (NSE), are the two criteria most widely used for calibration and evaluation of hydrological models with observed data. Here, we present a diagnostically interesting decomposition of NSE (and hence MSE), which facilitates analysis of the relative importance of its different components in the context of hydrological modelling, and show how model calibration problems can arise due to interactions among these components. The analysis is illustrated by calibrating a simple conceptual precipitation-runoff model to daily data for a number of Austrian basins having a broad range of hydro-meteorological characteristics. Evaluation of the results clearly demonstrates the problems that can be associated with any calibration based on the NSE (or MSE) criterion. While we propose and test an alternative criterion that can help to reduce model calibration problems, the primary purpose of this study is not to present an improved measure of model performance. Instead, we seek to show that there are systematic problems inherent with any optimization based on formulations related to the MSE. The analysis and results have implications to the manner in which we calibrate and evaluate environmental models; we discuss these and suggest possible ways forward that may move us towards an improved and diagnostically meaningful approach to model performance evaluation and identification.

  16. Parameter Choice and Constraint in Hydrologic Models for Evaluating Land Use Change

    NASA Astrophysics Data System (ADS)

    Jackson, C. R.

    2011-12-01

    Hydrologic models are used to answer questions, from simple, "what is the expected 100-year peak flow for a basin?", to complex, "how will land use change alter flow pathways, flow time series, and water chemistry?" Appropriate model structure and complexity depend on the questions being addressed. Numerous studies of simple transfer models for converting climate signals into streamflows suggest that only three or four parameters are needed. The conceptual corollary to such models is a single hillslope bucket with storage, evapotranspiration, fast flow, and slow flow. While having the benefit of low uncertainty, such models are ill-suited to addressing land use questions. Land use questions require models that can simulate effects of changes in vegetation, alterations of soil characteristics, and resulting changes in flow pathways. For example, minimum goals for a hydrologic model evaluating bioenergy feedstock production might include: 1) calculate Horton overland flow based on surface conductivities and saturated surface flow based on relative moisture content in the topsoils, 2) allow reinfiltration of Horton overland flow created by bare soils, compacted soils, and pavement (roads, logging roads, skid trails, landings), 3) account for root zone depth and LAI in transpiration calculations, 4) allow mixing of hillslope flows in the riparian aquifer, 5) allow separate simulation of the riparian soils and vegetation and upslope soils and vegetation, 6) incorporate important aspects of topography and stratigraphy, and 7) estimate residence times in different flow paths. How many parameters are needed for such a model, and what information beside streamflow can be collected to constrain the parameters? Additional information that can be used for evaluating and testing watershed models are in-situ conductivity measurements, soil porosity, soil moisture dynamics, shallow perched groundwater behavior, interflow occurrence, groundwater behavior, regional ET estimates

  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. Geographically Isolated Wetlands and Catchment Hydrology: A Modified Model Analyses

    NASA Astrophysics Data System (ADS)

    Evenson, G.; Golden, H. E.; Lane, C.; D'Amico, E.

    2014-12-01

    Geographically isolated wetlands (GIWs), typically defined as depressional wetlands surrounded by uplands, support an array of hydrological and ecological processes. However, key research questions concerning the hydrological connectivity of GIWs and their impacts on downgradient surface waters remain unanswered. This is particularly important for regulation and management of these systems. For example, in the past decade United States Supreme Court decisions suggest that GIWs can be afforded protection if significant connectivity exists between these waters and traditional navigable waters. Here we developed a simulation procedure to quantify the effects of various spatial distributions of GIWs across the landscape on the downgradient hydrograph using a refined version of the Soil and Water Assessment Tool (SWAT), a catchment-scale hydrological simulation model. We modified the SWAT FORTRAN source code and employed an alternative hydrologic response unit (HRU) definition to facilitate an improved representation of GIW hydrologic processes and connectivity relationships to other surface waters, and to quantify their downgradient hydrological effects. We applied the modified SWAT model to an ~ 202 km2 catchment in the Coastal Plain of North Carolina, USA, exhibiting a substantial population of mapped GIWs. Results from our series of GIW distribution scenarios suggest that: (1) Our representation of GIWs within SWAT conforms to field-based characterizations of regional GIWs in most respects; (2) GIWs exhibit substantial seasonally-dependent effects upon downgradient base flow; (3) GIWs mitigate peak flows, particularly following high rainfall events; and (4) The presence of GIWs on the landscape impacts the catchment water balance (e.g., by increasing groundwater outflows). Our outcomes support the hypothesis that GIWs have an important catchment-scale effect on downgradient streamflow.

  19. From models to performance assessment: the conceptualization problem.

    PubMed

    Bredehoeft, John D

    2003-01-01

    Today, models are ubiquitous tools for ground water analyses. The intent of this paper is to explore philosophically the role of the conceptual model in analysis. Selection of the appropriate conceptual model is an a priori decision by the analyst. Calibration is an integral part of the modeling process. Unfortunately a wrong or incomplete conceptual model can often be adequately calibrated; good calibration of a model does not ensure a correct conceptual model. Petroleum engineers have another term for calibration; they refer to it as history matching. A caveat to the idea of history matching is that we can make a prediction with some confidence equal to the period of the history match. In other words, if we have matched a 10-year history, we can predict for 10 years with reasonable confidence; beyond 10 years the confidence in the prediction diminishes rapidly. The same rule of thumb applies to ground water model analyses. Nuclear waste disposal poses a difficult problem because the time horizon, 1000 years or longer, is well beyond the possibility of the history match (or period of calibration) in the traditional analysis. Nonetheless, numerical models appear to be the tool of choice for analyzing the safety of waste facilities. Models have a well-recognized inherent uncertainty. Performance assessment, the technique for assessing the safety of nuclear waste facilities, involves an ensemble of cascading models. Performance assessment with its ensemble of models multiplies the inherent uncertainty of the single model. The closer we can approach the idea of a long history with which to match the models, even models of nuclear waste facilities, the more confidence we will have in the analysis (and the models, including performance assessment). This thesis argues for prolonged periods of observation (perhaps as long as 300 to 1000 years) before a nuclear waste facility is finally closed. PMID:13678111

  20. Spatial transferability of landscape-based hydrological models

    NASA Astrophysics Data System (ADS)

    Gao, Hongkai; Hrachowitz, Markus; Fenicia, Fabrizio; Gharari, Shervan; Sriwongsitanon, Nutchanart; Savenije, Hubert

    2015-04-01

    Landscapes, mainly distinguished by land surface topography and vegetation cover, are crucial in defining runoff generation mechanisms, interception capacity and transpiration processes. Landscapes information provides modelers with a way to take into account catchment heterogeneity, while simultaneously keeping model complexity low. A landscape-based hydrological modelling framework (FLEX-Topo), with parallel model structures, was developed and tested in various catchments with diverse climate, topography and land cover conditions. Landscape classification is the basic and most crucial procedure to create a tailor-made model for a certain catchment, as it explicitly relates hydrologic similarity to landscape similarity, which is the base of this type of models. Therefore, the study catchment is classified into different landscapes units that fulfil similar hydrological function, based on classification criteria such as the height above the nearest drainage, slope, aspect and land cover. At present, to suggested model includes four distinguishable landscapes: hillslopes, terraces/plateaus, riparian areas, and glacierized areas. Different parallel model structures are then associated with the different landscape units to describe their different dominant runoff generation mechanisms. These hydrological units are parallel and only connected by groundwater reservoir. The transferability of this landscape-based model can then be compared with the transferability of a lumped model. In this study, FLEX-Topo was developed and tested in three study sites: two cold-arid catchments in China (the upper Heihe River and the Urumqi Glacier No1 catchment), and one tropical catchment in Thailand (the upper Ping River). Stringent model tests indicate that FLEX-Topo, allowing for more process heterogeneity than lumped model formulations, exhibits higher capabilities to be spatially transferred. Furthermore, the simulated water balances, including internal fluxes, hydrograph

  1. eWaterCycle: A global operational hydrological forecasting model

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

    Development of an operational hyper-resolution hydrological global model is a central goal of the eWaterCycle project (www.ewatercycle.org). This operational model includes ensemble forecasts (14 days) to predict water related stress around the globe. Assimilation of near-real time satellite data is part of the intended product that will be launched at EGU 2015. The challenges come from several directions. First, there are challenges that are mainly computer science oriented but have direct practical hydrological implications. For example, we aim to make use as much as possible of existing standards and open-source software. For example, different parts of our system are coupled through the Basic Model Interface (BMI) developed in the framework of the Community Surface Dynamics Modeling System (CSDMS). The PCR-GLOBWB model, built by Utrecht University, is the basic hydrological model that is the engine of the eWaterCycle project. Re-engineering of parts of the software was needed for it to run efficiently in a High Performance Computing (HPC) environment, and to be able to interface using BMI, and run on multiple compute nodes in parallel. The final aim is to have a spatial resolution of 1km x 1km, which is currently 10 x 10km. This high resolution is computationally not too demanding but very memory intensive. The memory bottleneck becomes especially apparent for data assimilation, for which we use OpenDA. OpenDa allows for different data assimilation techniques without the need to build these from scratch. We have developed a BMI adaptor for OpenDA, allowing OpenDA to use any BMI compatible model. To circumvent memory shortages which would result from standard applications of the Ensemble Kalman Filter, we have developed a variant that does not need to keep all ensemble members in working memory. At EGU, we will present this variant and how it fits well in HPC environments. An important step in the eWaterCycle project was the coupling between the hydrological and

  2. A Conceptual Framework for SAHRA Integrated Multi-resolution Modeling in the Rio Grande Basin

    NASA Astrophysics Data System (ADS)

    Liu, Y.; Gupta, H.; Springer, E.; Wagener, T.; Brookshire, D.; Duffy, C.

    2004-12-01

    The sustainable management of water resources in a river basin requires an integrated analysis of the social, economic, environmental and institutional dimensions of the problem. Numerical models are commonly used for integration of these dimensions and for communication of the analysis results to stakeholders and policy makers. The National Science Foundation Science and Technology Center for Sustainability of semi-Arid Hydrology and Riparian Areas (SAHRA) has been developing integrated multi-resolution models to assess impacts of climate variability and land use change on water resources in the Rio Grande Basin. These models not only couple natural systems such as surface and ground waters, but will also include engineering, economic and social components that may be involved in water resources decision-making processes. This presentation will describe the conceptual framework being developed by SAHRA to guide and focus the multiple modeling efforts and to assist the modeling team in planning, data collection and interpretation, communication, evaluation, etc. One of the major components of this conceptual framework is a Conceptual Site Model (CSM), which describes the basin and its environment based on existing knowledge and identifies what additional information must be collected to develop technically sound models at various resolutions. The initial CSM is based on analyses of basin profile information that has been collected, including a physical profile (e.g., topographic and vegetative features), a man-made facility profile (e.g., dams, diversions, and pumping stations), and a land use and ecological profile (e.g., demographics, natural habitats, and endangered species). Based on the initial CSM, a Conceptual Physical Model (CPM) is developed to guide and evaluate the selection of a model code (or numerical model) for each resolution to conduct simulations and predictions. A CPM identifies, conceptually, all the physical processes and engineering and socio

  3. Incorporating Field Intelligence Into Conceptual Rainfall-runoff Models

    NASA Astrophysics Data System (ADS)

    Vache, K.; McDonnell, J.; McGuire, K.

    2003-12-01

    A major challenge in the hydrological sciences is to incorporate observed physical processes into general hydrological models with minimal data requirements and limited model complexity. One approach is to move away from discharge-based calibration schemes, which often assume model structures to be correct, and allow field observations to inform and test new model structures. The use of this knowledge will contribute to (1) the development of an expanded set of variables to verify hydrological model performance and reflect the overall watershed function and (2) provide useful information regarding the development of model structures and landscape discretizations. We identify a set of three variables that focus on the composition of stream water, using artificial hydrograph separations to provide estimates of the time source (e.g., event vs. pre-event) and the geographic source (e.g., hillslope vs. riparian) of streamflow, and explicitly accounting for mass transfer to provide estimates of residence time. In addition to these variables, we present a set of methods and data designed to incorporate experimental understanding directly into the model structure and catchment discretization. These ideas are illustrated through application at the H.J. Andrews Experimental Forest's Lookout Creek watershed in the western Cascades of Oregon.

  4. Performance and Probabilistic Verification of Regional Parameter Estimates for Conceptual Rainfall-runoff Models

    NASA Astrophysics Data System (ADS)

    Franz, K.; Hogue, T.; Barco, J.

    2007-12-01

    Identification of appropriate parameter sets for simulation of streamflow in ungauged basins has become a significant challenge for both operational and research hydrologists. This is especially difficult in the case of conceptual models, when model parameters typically must be "calibrated" or adjusted to match streamflow conditions in specific systems (i.e. some of the parameters are not directly observable). This paper addresses the performance and uncertainty associated with transferring conceptual rainfall-runoff model parameters between basins within large-scale ecoregions. We use the National Weather Service's (NWS) operational hydrologic model, the SACramento Soil Moisture Accounting (SAC-SMA) model. A Multi-Step Automatic Calibration Scheme (MACS), using the Shuffle Complex Evolution (SCE), is used to optimize SAC-SMA parameters for a group of watersheds with extensive hydrologic records from the Model Parameter Estimation Experiment (MOPEX) database. We then explore "hydroclimatic" relationships between basins to facilitate regionalization of parameters for an established ecoregion in the southeastern United States. The impact of regionalized parameters is evaluated via standard model performance statistics as well as through generation of hindcasts and probabilistic verification procedures to evaluate streamflow forecast skill. Preliminary results show climatology ("climate neighbor") to be a better indicator of transferability than physical similarities or proximity ("nearest neighbor"). The mean and median of all the parameters within the ecoregion are the poorest choice for the ungauged basin. The choice of regionalized parameter set affected the skill of the ensemble streamflow hindcasts, however, all parameter sets show little skill in forecasts after five weeks (i.e. climatology is as good an indicator of future streamflows). In addition, the optimum parameter set changed seasonally, with the "nearest neighbor" showing the highest skill in the

  5. 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

  6. Conceptual model for regional radionuclide transport from a salt dome repository: a technical memorandum

    SciTech Connect

    Kier, R.S.; Showalter, P.A.; Dettinger, M.D.

    1980-05-30

    Disposal of high-level radioactive wastes is a major environmental problem influencing further development of nuclear energy in this country. Salt domes in the Gulf Coast Basin are being investigated as repository sites. A major concern is geologic and hydrologic stability of candidate domes and potential transport of radionuclides by groundwater to the biosphere prior to their degradation to harmless levels of activity. This report conceptualizes a regional geohydrologic model for transport of radionuclides from a salt dome repository. The model considers transport pathways and the physical and chemical changes that would occur through time prior to the radionuclides reaching the biosphere. Necessary, but unknown inputs to the regional model involve entry and movement of fluids through the repository dome and across the dome-country rock interface and the effect on the dome and surrounding strata of heat generated by the radioactive wastes.

  7. Socio-Hydrologic Modeling: Characterizing the Dynamics of Coupled Human-Water Systems Using Natural Science Methods

    NASA Astrophysics Data System (ADS)

    Sivapalan, M.; Elshafei, Y.; Srinivasan, V.

    2014-12-01

    A challenging research puzzle in the research on sustainable water management in the Anthropocene is why some societies successfully recover from "ecological destruction" to transition to "successful adaptation" over decadal timescales, while others fail. We present a conceptual modeling framework to understand and characterize these transitions. In this way, we aim to capture the potential drivers of the desired shift towards achieving sustainability of socio-hydrological systems. This is done through a synthesis of detailed socio-hydrological analyses of four river basins in three continents, carried out using different quantitative socio-hydrologic models: Murrumbidgee River Basin in eastern Australia, Lake Toolibin Catchment in Western Australia, Tarim River Basin in Western China and Kissimmee River Basin, in south-east United States. The case studies are analysed using either place-based models designed specifically to mimic observed long-term socio-hydrologic trends, or generic conceptual models with foundations in diverse strands of literature including sustainability science and resilience theory. A comparative analysis of the four case studies reveals a commonality in the building blocks employed to model these socio-hydrologic systems; including water balance, economic, environmental and human-feedback components. Each model reveals varying interpretations of a common organising principle that could explain the shift between productive (socio-economic) and restorative (environmental) forces that was evident in each of these systems observed over a long time frame. The emergent principle is related to the essential drivers of the human feedback component and rests with a general formulation of human well-being, as reflected by both their economic and environmental well-being. It is envisaged that the understanding of the system drivers gained from such a comparative study would enable more targeted water management strategies that can be administered in

  8. A New Wavelet Based Approach to Assess Hydrological Models

    NASA Astrophysics Data System (ADS)

    Adamowski, J. F.; Rathinasamy, M.; Khosa, R.; Nalley, D.

    2014-12-01

    In this study, a new wavelet based multi-scale performance measure (Multiscale Nash Sutcliffe Criteria, and Multiscale Normalized Root Mean Square Error) for hydrological model comparison was developed and tested. The new measure provides a quantitative measure of model performance across different timescales. Model and observed time series are decomposed using the a trous wavelet transform, and performance measures of the model are obtained at each time scale. The usefulness of the new measure was tested using real as well as synthetic case studies. The real case studies included simulation results from the Soil Water Assessment Tool (SWAT), as well as statistical models (the Coupled Wavelet-Volterra (WVC), Artificial Neural Network (ANN), and Auto Regressive Moving Average (ARMA) methods). Data from India and Canada were used. The synthetic case studies included different kinds of errors (e.g., timing error, as well as under and over prediction of high and low flows) in outputs from a hydrologic model. It was found that the proposed wavelet based performance measures (i.e., MNSC and MNRMSE) are a more reliable measure than traditional performance measures such as the Nash Sutcliffe Criteria, Root Mean Square Error, and Normalized Root Mean Square Error. It was shown that the new measure can be used to compare different hydrological models, as well as help in model calibration.

  9. Improving the transferability of hydrological model parameters under changing conditions

    NASA Astrophysics Data System (ADS)

    Huang, Yingchun; Bárdossy, András

    2014-05-01

    Hydrological models are widely utilized to describe catchment behaviors with observed hydro-meteorological data. Hydrological process may be considered as non-stationary under the changing climate and land use conditions. An applicable hydrological model should be able to capture the essential features of the target catchment and therefore be transferable to different conditions. At present, many model applications based on the stationary assumptions are not sufficient for predicting further changes or time variability. The aim of this study is to explore new model calibration methods in order to improve the transferability of model parameters. To cope with the instability of model parameters calibrated on catchments in non-stationary conditions, we investigate the idea of simultaneously calibration on streamflow records for the period with dissimilar climate characteristics. In additional, a weather based weighting function is implemented to adjust the calibration period to future trends. For regions with limited data and ungauged basins, the common calibration was applied by using information from similar catchments. Result shows the model performance and transfer quantity could be well improved via common calibration. This model calibration approach will be used to enhance regional water management and flood forecasting capabilities.

  10. Flash flood modeling with the MARINE hydrological distributed model

    NASA Astrophysics Data System (ADS)

    Estupina-Borrell, V.; Dartus, D.; Ababou, R.

    2006-11-01

    Flash floods are characterized by their violence and the rapidity of their occurrence. Because these events are rare and unpredictable, but also fast and intense, their anticipation with sufficient lead time for warning and broadcasting is a primary subject of research. Because of the heterogeneities of the rain and of the behavior of the surface, spatially distributed hydrological models can lead to a better understanding of the processes and so on they can contribute to a better forecasting of flash flood. Our main goal here is to develop an operational and robust methodology for flash flood forecasting. This methodology should provide relevant data (information) about flood evolution on short time scales, and should be applicable even in locations where direct observations are sparse (e.g. absence of historical and modern rainfalls and streamflows in small mountainous watersheds). The flash flood forecast is obtained by the physically based, space-time distributed hydrological model "MARINE'' (Model of Anticipation of Runoff and INondations for Extreme events). This model is presented and tested in this paper for a real flash flood event. The model consists in two steps, or two components: the first component is a "basin'' flood module which generates flood runoff in the upstream part of the watershed, and the second component is the "stream network'' module, which propagates the flood in the main river and its subsidiaries. The basin flash flood generation model is a rainfall-runoff model that can integrate remotely sensed data. Surface hydraulics equations are solved with enough simplifying hypotheses to allow real time exploitation. The minimum data required by the model are: (i) the Digital Elevation Model, used to calculate slopes that generate runoff, it can be issued from satellite imagery (SPOT) or from French Geographical Institute (IGN); (ii) the rainfall data from meteorological radar, observed or anticipated by the French Meteorological Service (M

  11. The skill of seasonal ensemble low flow forecasts for four different hydrological models

    NASA Astrophysics Data System (ADS)

    Demirel, M. C.; Booij, M. J.; Hoekstra, A. Y.

    2014-05-01

    This paper investigates the skill of 90 day low flow forecasts using two conceptual hydrological models and two data-driven models based on Artificial Neural Networks (ANNs) for the Moselle River. One data-driven model, ANN-Indicator (ANN-I), requires historical inputs on precipitation (P), potential evapotranspiration (PET), groundwater (G) and observed discharge (Q), whereas the other data-driven model, ANN-Ensemble (ANN-E), and the two conceptual models, HBV and GR4J, use forecasted meteorological inputs (P and PET), whereby we employ ensemble seasonal meteorological forecasts. We compared low flow forecasts without any meteorological forecasts as input (ANN-I) and five different cases of seasonal meteorological forcing: (1) ensemble P and PET forecasts; (2) ensemble P forecasts and observed climate mean PET; (3) observed climate mean P and ensemble PET forecasts; (4) observed climate mean P and PET and (5) zero P and ensemble PET forecasts as input for the other three models (GR4J, HBV and ANN-E). The ensemble P and PET forecasts, each consisting of 40 members, reveal the forecast ranges due to the model inputs. The five cases are compared for a lead time of 90 days based on model output ranges, whereas the four models are compared based on their skill of low flow forecasts for varying lead times up to 90 days. Before forecasting, the hydrological models are calibrated and validated for a period of 30 and 20 years respectively. The smallest difference between calibration and validation performance is found for HBV, whereas the largest difference is found for ANN-E. From the results, it appears that all models are prone to over-predict low flows using ensemble seasonal meteorological forcing. The largest range for 90 day low flow forecasts is found for the GR4J model when using ensemble seasonal meteorological forecasts as input. GR4J, HBV and ANN-E under-predicted 90 day ahead low flows in the very dry year 2003 without precipitation data, whereas ANN

  12. EVALUATION OF HYDROLOGIC MODELS IN THE DESIGN OF STABLE LANDFILL COVERS

    EPA Science Inventory

    The study evaluates the utility of two hydrologic models in designing stable landfill cover systems. The models evaluated were HELP (Hydrologic Evaluation of Landfill Performance) and CREAMS (Chemicals, Runoff, and Erosion from Agricultural Management Systems). Studies of paramet...

  13. Designing Public Library Websites for Teens: A Conceptual Model

    ERIC Educational Resources Information Center

    Naughton, Robin Amanda

    2012-01-01

    The main goal of this research study was to develop a conceptual model for the design of public library websites for teens (TLWs) that would enable designers and librarians to create library websites that better suit teens' information needs and practices. It bridges a gap in the research literature between user interface design in…

  14. A Conceptual Model for Effective Distance Learning in Higher Education

    ERIC Educational Resources Information Center

    Farajollahi, Mehran; Zare, Hosein; Hormozi, Mahmood; Sarmadi, Mohammad Reza; Zarifsanaee, Nahid

    2010-01-01

    The present research aims at presenting a conceptual model for effective distance learning in higher education. Findings of this research shows that an understanding of the technological capabilities and learning theories especially constructive theory and independent learning theory and communicative and interaction theory in Distance learning is…

  15. Conceptualizations of Creativity: Comparing Theories and Models of Giftedness

    ERIC Educational Resources Information Center

    Miller, Angie L.

    2012-01-01

    This article reviews seven different theories of giftedness that include creativity as a component, comparing and contrasting how each one conceptualizes creativity as a part of giftedness. The functions of creativity vary across the models, suggesting that while the field of gifted education often cites the importance of creativity, the…

  16. Sources of Sex Discrimination in Educational Systems: A Conceptual Model

    ERIC Educational Resources Information Center

    Kutner, Nancy G.; Brogan, Donna

    1976-01-01

    A conceptual model is presented relating numerous variables contributing to sexism in American education. Discrimination is viewed as intervening between two sets of interrelated independent variables and the dependent variable of sex inequalities in educational attainment. Sex-role orientation changes are the key to significant change in the…

  17. A Conceptual Model of the World of Work.

    ERIC Educational Resources Information Center

    VanRooy, William H.

    The conceptual model described in this paper resulted from the need to organize a body of knowledge related to the world of work which would enable curriculum developers to prepare accurate, realistic instructional materials. The world of work is described by applying Malinowski's scientific study of the structural components of culture. It is…

  18. A Multiperspectival Conceptual Model of Transformative Meaning Making

    ERIC Educational Resources Information Center

    Freed, Maxine

    2009-01-01

    Meaning making is central to transformative learning, but little work has explored how meaning is constructed in the process. Moreover, no meaning-making theory adequately captures its characteristics and operations during radical transformation. The purpose of this dissertation was to formulate and specify a multiperspectival conceptual model of…

  19. An improved ARIMA model for hydrological simulations

    NASA Astrophysics Data System (ADS)

    Wang, H. R.; Wang, C.; Lin, X.; Kang, J.

    2014-04-01

    Auto Regressive Integrated Moving Average (ARIMA) model is often used to calculate time series data formed by inter-annual variations of monthly data. However, the influence brought about by inter-monthly variations within each year is ignored. Based on the monthly data classified by clustering analysis, the characteristics of time series data are extracted. An improved ARIMA model is developed accounting for both the inter-annual and inter-monthly variation. The correlation between characteristic quantity and monthly data within each year is constructed by regression analysis first. The model can be used for predicting characteristic quantity followed by the stationary treatment for characteristic quantity time series by difference. A case study is conducted to predict the precipitation in Lanzhou precipitation station, China, using the model, and the results show that the accuracy of the improved model is significantly higher than the seasonal model, with the mean residual achieving 9.41 mm and the forecast accuracy increasing by 21%.

  20. Development of a regional hydrologic soil model and application to the Beerze--Reusel drainage basin.

    PubMed

    Kolditz, O; Du, Y; Bürger, C; Delfs, J; Kuntz, D; Beinhorn, M; Hess, M; Wang, W; van der Grift, B; te Stroet, C

    2007-08-01

    The soil compartment is an important interface between the atmosphere and the subsurface hydrosphere. In this paper a conceptual approach for regional hydrologic soil modelling (RHSM) is presented, which provides two important qualities for modelling. First, the soil compartment is directly coupled to the atmosphere via the land surface and to the aquifers. Second, extremely fine (5cm vertical) resolutions of the soil system can be realized at regional scales (several hundreds of km(2)). This high-resolution modelling could be achieved by parallel computation techniques. The RHSM approach is applied to the Beerze-Reusel drainage basin, which belongs to the Meuse River basin. Moisture transport in the soil system was calculated with extremely high vertical resolution at a regional scale based on rainfall-evaporation data for the year 2000. As a result, highly resolved regional groundwater recharge pattern addressing the heterogeneity of soil systems could be determined. PMID:17478020

  1. Modeling of thermally driven hydrological processes in partially saturated fractured rock

    SciTech Connect

    Tsang, Yvonne; Birkholzer, Jens; Mukhopadhyay, Sumit

    2009-03-15

    This paper is a review of the research that led to an in-depth understanding of flow and transport processes under strong heat stimulation in fractured, porous rock. It first describes the anticipated multiple processes that come into play in a partially saturated, fractured porous volcanic tuff geological formation, when it is subject to a heat source such as that originating from the decay of radionuclides. The rationale is then given for numerical modeling being a key element in the study of multiple processes that are coupled. The paper outlines how the conceptualization and the numerical modeling of the problem evolved, progressing from the simplified to the more realistic. Examples of numerical models are presented so as to illustrate the advancement and maturation of the research over the last two decades. The most recent model applied to in situ field thermal tests is characterized by (1) incorporation of a full set of thermal-hydrological processes into a numerical simulator, (2) realistic representation of the field test geometry, in three dimensions, and (3) use of site-specific characterization data for model inputs. Model predictions were carried out prior to initiation of data collection, and the model results were compared to diverse sets of measurements. The approach of close integration between modeling and field measurements has yielded a better understanding of how coupled thermal hydrological processes produce redistribution of moisture within the rock, which affects local permeability values and subsequently the flow of liquid and gases. The fluid flow in turn will change the temperature field. We end with a note on future research opportunities, specifically those incorporating chemical, mechanical, and microbiological factors into the study of thermal and hydrological processes.

  2. A new conceptual model of convection

    SciTech Connect

    Walcek, C.

    1995-09-01

    Classical cumulus parameterizations assume that cumulus clouds are entraining plumes of hot air rising through the atmosphere. However, ample evidence shows that clouds cannot be simulated using this approach. Dr. Walcek suggests that cumulus clouds can be reasonably simulated by assuming that buoyant plumes detrain mass as they rise through the atmosphere. Walcek successfully simulates measurements of tropical convection using this detraining model of cumulus convection. Comparisons with measurements suggest that buoyant plumes encounter resistance to upward movement as they pass through dry layers in the atmosphere. This probably results from turbulent mixing and evaporation of cloud water, which generates negatively buoyant mixtures which detrain from the upward moving plume. This mass flux model of detraining plumes is considerably simpler than existing mass flux models, yet reproduces many of the measured effects associated with convective activity. 1 fig.

  3. A rangeland hydrology and erosion model

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Soil loss rates on rangelands are considered one of the few quantitative indicators for assessing rangeland health and conservation practice effectiveness. An erosion model to predict soil loss specific for rangeland applications is needed because existing erosion models were developed from cropland...

  4. Selection of Hydrological Model for Waterborne Release

    SciTech Connect

    Blanchard, A.

    1999-02-03

    The purpose of this report is to evaluate the two available models and determine the appropriate model for use in following waterborne release analyses. Additionally, this report will document the DB and BDB accidents to be used in the future study.

  5. Selection of Hydrological Model for Waterborne Release

    SciTech Connect

    Blanchard, A.

    1999-04-21

    This evaluation will aid in determining the potential impacts of liquid releases to downstream populations on the Savannah River. The purpose of this report is to evaluate the two available models and determine the appropriate model for use in following waterborne release analyses. Additionally, this report will document the Design Basis and Beyond Design Basis accidents to be used in the future study.

  6. 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

  7. Hydrological Modelling of The Guadiana Basin

    NASA Astrophysics Data System (ADS)

    Conan, C.; Bouraoui, F.; de Marsily, G.; Bidoglio, G.

    Increased anthropogenic activities such as agriculture, irrigation, industry, mining, ur- ban water supply and sewage treatment, have created significant environmental prob- lems. To ensure sustainable development of water resources, water managers need new strategies and suitable tools. In particular it is often compulsory that surface wa- ter and groundwater be managed simultaneously both in terms of quantity and quality at catchment scales. To this purpose, a model coupling SWAT (Soil and Water As- sessment Tool) and MODFLOW (Modular 3-D Flow model) was developed. SWAT is a quasi-distributed watershed model with a GIS interface that outlines the sub-basins and stream networks from a Digital Elevation Model (DEM) and calculates daily wa- ter balances from meteorological data, soil and land-use characteristics. The particular advantage of this model, compared to other fully distributed physically based mod- els, is that it requires a small amount of readily available input data. MODFLOW is a fully distributed model that calculates groundwater flow from aquifer characteris- tics. We have adapted this new coupled model SWAT-MODFLOW to a Mediterranean catchment, the Guadiana basin, and present the first results of this work. Only wa- ter quantity results are available at this stage. The validation consisted in comparing measured and predicted daily flow at the catchment and sub-catchment outlets for the period 1970-1995. The model accurately reproduced the decrease of the piezometric level, due to increased water abstraction, and the exchanges between surface water and ground-water. The sensitivity of the model to irrigation practices was evaluated. The usefulness of this model as a management tool has been illustrated through the analysis of alternative scenarios of agricultural practices and climate change.

  8. Conceptualizing Evolving Models of Educational Development

    ERIC Educational Resources Information Center

    Fraser, Kym; Gosling, David; Sorcinelli, Mary Deane

    2010-01-01

    Educational development, which the authors use to refer to the field of professional and strategic development associated with university and college learning and teaching, can be described in many ways by referring to its different aspects. In this article the authors endeavor to categorize many of the models that have been used to describe…

  9. CONCEPTUAL DEVELOPMENT OF A TOXIC SCREENING MODEL

    EPA Science Inventory

    This report presents the application of the Routing and Graphical Display system developed by EPA to show how computer based modeling and simulation using the Reach File can be used to assess the types and concentrations of contaminants that could be found at any point in a river...

  10. Utilization of remote sensing observations in hydrologic models

    NASA Technical Reports Server (NTRS)

    Ragan, R. M.

    1977-01-01

    Most of the remote sensing related work in hydrologic modeling has centered on modifying existing models to take advantage of the capabilities of new sensor techniques. There has been enough success with this approach to insure that remote sensing is a powerful tool in modeling the watershed processes. Unfortunately, many of the models in use were designed without recognizing the growth of remote sensing technology. Thus, their parameters were selected to be map or field crew definable. It is believed that the real benefits will come through the evolution of new models having new parameters that are developed specifically to take advantage of our capabilities in remote sensing. The ability to define hydrologically active areas could have a significant impact. The ability to define soil moisture and the evolution of new techniques to estimate evoportransportation could significantly modify our approach to hydrologic modeling. Still, without a major educational effort to develop an understanding of the techniques used to extract parameter estimates from remote sensing data, the potential offered by this new technology will not be achieved.

  11. Anticipating the Role of SWOT in Hydrologic and Hydrodynamic Modeling

    NASA Astrophysics Data System (ADS)

    Pavelsky, T.; Biancamaria, S.; Andreadis, K.; Durand, M. T.; Schumann, G.

    2015-12-01

    The Surface Water and Ocean Topography (SWOT) satellite mission is a joint project of NASA and CNES, the French space agency. It aims to provide the first simultaneous, space-based measurements of inundation extent and water surface elevation in rivers, lakes, and wetlands around the world. Although the orbit repeat time is approximately 21 days, many areas of the earth will be viewed multiple times during this window. SWOT will observe rivers as narrow as 50-100 m and lakes as small as 0.01-0.06 km2, with height accuracies of ~10 cm for water bodies 1 km2 in area. Because SWOT will measure temporal variations in the height, width, and slope of rivers, several algorithms have been developed to estimate river discharge solely from SWOT measurements. Additionally, measurements of lake height and area will allow estimation of variability in lake water storage. These new hydrologic measurements will provide important sources of information both hydrologic and hydrodynamic models at regional to global scales. SWOT-derived estimates of water storage change and discharge will help to constrain simulation of the water budget in hydrologic models. Measurements of water surface elevation will provide similar constraints on hydrodynamic models of river flow. SWOT data will be useful for model calibration and validation, but perhaps the most exciting applications involve assimilation of SWOT data into models to enhance model robustness and provide denser temporal sampling than available from SWOT observations alone.

  12. Flash flood warning based on fully dynamic hydrology modelling