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Development of a hierarchical modelling framework for solute transport under unsteady flow conditions in riversCamacho, Luis Alejandro January 2001 (has links)
No description available.
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A simulation model for subsurface and overland flow down a hillside in the Crimple Beck, N. YorkshireParsons, J. S. January 1987 (has links)
No description available.
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A mathematical hydrological model for the ungauged catchmentHowes, S. January 1985 (has links)
In geographical hydrology the~e has been more interest in scientific rather than in practical application of mathematical models of catchment hydrology. This thesis emphasizes the importance of examining the potential of developments in scientific research programmes for practical hydrological applications, and in particular provides discussion upon the following five issues: 1 The application of hydrological models to ungauged catchments where no historical streamflow record is available for calibration. 2 The potential of hydrological models for routine and operational application. This application limits the data and computer resources which are available for use. 3 The development and application of a thorough model evaluation strategy which examines the suitability of a model in the context of a specific application requirement. 4 The selection of a conceptually sound model structure. S The development and evaluation of a suitable methodology for the incorporation of the spatial variability of catchments into hydrological" models. To provide a basis for the discussion of these five issues, this thesis provides the details of the modification of a currently used hydrological model, RYMO. The modification of this model involves the replacement of the empirical curve number model for runoff derivation with a physically based parameter infiltration model. A number of comparisons of HYMO and the modified version, HYM02, indicates that conceptual, parameter estimation, prediction, and sensitivity improvements have indeed been secured by the development of the modified model.
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Development of a cell-based stream flow routing modelRaina, Rajeev 29 August 2005 (has links)
This study presents the development of a cell-based routing model. The model developed is a two parameter hydrological routing model that uses a coarse resolution stream network to route runoff from each cell in the watershed to the outlet. The watershed is divided into a number of equal cells, which are approximated as cascade of linear reservoirs or tanks. Water is routed from a cell downstream, depending on the flow direction of the cell, using the cascade of tanks. The routing model consists of two phases, first is the overland flow routing, which is followed by the channel flow routing. In this study, the cell-to-cell stream flow routing model is applied to the Brazos River Basin to demonstrate the impact of the cascade of tanks on the flow over a simple linear reservoir method. This watershed was tested with a uniform runoff depth in absence of observed runoff data. A case study on Waller Creek in Austin, Texas with observed runoff depths and stream flow is used to demonstrate the calibration and validation of model parameters.
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Development of a cell-based stream flow routing modelRaina, Rajeev 29 August 2005 (has links)
This study presents the development of a cell-based routing model. The model developed is a two parameter hydrological routing model that uses a coarse resolution stream network to route runoff from each cell in the watershed to the outlet. The watershed is divided into a number of equal cells, which are approximated as cascade of linear reservoirs or tanks. Water is routed from a cell downstream, depending on the flow direction of the cell, using the cascade of tanks. The routing model consists of two phases, first is the overland flow routing, which is followed by the channel flow routing. In this study, the cell-to-cell stream flow routing model is applied to the Brazos River Basin to demonstrate the impact of the cascade of tanks on the flow over a simple linear reservoir method. This watershed was tested with a uniform runoff depth in absence of observed runoff data. A case study on Waller Creek in Austin, Texas with observed runoff depths and stream flow is used to demonstrate the calibration and validation of model parameters.
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Concepts for coupling hydrological and meteorological modelsMölders, Nicole 06 December 2016 (has links) (PDF)
Earth system modeling, climate modeling, water resource research as well as integrated modeling (e.g., climate impact studies) require the coupling of hydrological and meteorological models. The paper presents recent concepts on such a coupling. It points out the difficulties to be solved, and provides a brief overview on recently realized couplings. Furthermore, a concept of a hydrometeorological module to couple hydrological and meteorological models is introduced. / Wasserresourcenforschung, Erdsystem- und Klimamodellierung sowie
integrierte Modellierung (z.B. Klimafolgenforschung) erfordern das Koppeln von hydrologischen und meteorologischen Modellen. Dieser Artikel präsentiert Konzepte für eine solche Kopplung. Er zeigt die zu lösenden Schwierigkeiten auf und gibt einen kurzen Überblick über bisher realisierte Kopplungen. Ferner stellt er ein Konzept für einen hydrometeorologischen Moduls zur Kopplung von hydrologischen mit meteorologischen Modellen vor.
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Predictability of hydrologic response at the plot and catchment scales: Role of initial conditionsZehe, Erwin, Blöschl, Günter January 2004 (has links)
This paper examines the effect of uncertain initial soil moisture on hydrologic
response at the plot scale (1 m2) and the catchment scale (3.6 km2) in the presence of threshold transitions between matrix and preferential flow. We adopt the concepts of microstates and macrostates from statistical mechanics. The microstates are the detailed patterns of initial soil moisture that are inherently unknown, while the macrostates are specified by the statistical distributions of initial soil moisture that can be derived from the measurements typically available in field experiments. We use a physically based model and ensure that it closely represents the processes in the Weiherbach catchment, Germany. We then use the model to generate hydrologic response to hypothetical irrigation events and rainfall events for multiple realizations of initial soil moisture microstates that are all consistent with the same macrostate. As the measures of uncertainty at the plot scale we use the coefficient of variation and the scaled range of simulated vertical bromide
transport distances between realizations. At the catchment scale we use similar statistics derived from simulated flood peak discharges. The simulations indicate that at both scales the predictability depends on the average initial soil moisture state and is at a minimum around the soil moisture value where the transition from matrix to macropore flow occurs. The predictability increases with rainfall intensity. The predictability increases with scale with maximum absolute errors of 90 and 32% at the plot scale and the catchment scale, respectively. It is argued that even if we assume perfect knowledge on the processes, the level of detail with which one can measure the initial conditions along with the nonlinearity of the system will set limits to the repeatability of experiments and limits to the predictability of models at the plot and catchment scales.
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Hydrological response unit-based blowing snow modelling over mountainous terrainMacDonald, Matthew Kenneth 25 January 2011
Wind transport and sublimation of snow particles are common phenomena across high altitude and latitude cold regions and play important roles in hydrological and atmospheric water and energy budgets. In spite of this, blowing snow processes have not been incorporated in many mesoscale hydrological models and land surface schemes.
A physically based blowing snow model, the Prairie Blowing Snow Model (PBSM), initially developed for prairie environments was used to model snow redistribution and sublimation by wind over two sites representative of mountainous regions in Canada: Fisera Ridge in the Rocky Mountain Front Ranges in Alberta, and Granger Basin in the Yukon Territory. Two models were used to run PBSM: the object-oriented hydrological model, Cold Regions Hydrological Modelling Platform (CRHM) and Environment Canadas hydrological-land surface scheme, Modélisation Environmentale Communautaire Surface and Hydrology (MESH). PBSM was coupled with the snowcover energy and mass-balance model (SNOBAL) within CRHM. Blowing snow algorithms were also incorporated into MESH to create MESH-PBSM. CRHM, MESH and MESH-PBSM were used to simulate the evolution of snowcover in hydrological response units (HRUs) over both Fisera Ridge and Granger Basin.<p>
To test the models of blowing snow redistribution and ablation over a relatively simple sequence of mountain topography, simulations were run from north to south over a linear ridge in the Canadian Rocky Mountains. Fisera Ridge snowcover simulations with CRHM were performed over two winters using two sets of wind speed forcing: (1) station observed wind speed, and (2) modelled wind speed from a widely applied empirical, terrain-based windflow model. Best results were obtained when using the site meteorological station wind speed data. The windflow model performed poorly when comparing the magnitude of modelled and observed wind speeds. Blowing snow sublimation, snowmelt and snowpack sublimation quantities were considerably overestimated when using the modelled wind speeds. As a result, end-of-winter snow accumulation was considerably underestimated on windswept HRUs. MESH and MESH-PBSM were also used to simulate snow accumulation and redistribution over these same HRUs. MESH-PBSM adequately simulated snow accumulation in the HRUs up until the spring snowmelt period. MESH without PBSM performed less well and overestimated accumulation on windward slopes and the ridge top whilst underestimating accumulation on lee slopes. Simulations in spring were degraded by a large overestimation of melt by MESH. The early and overestimated melt warrants a detailed examination that is outside the scope of this thesis.<p>
To parameterize snow redistribution in a mountain alpine basin, snow redistribution and sublimation by wind were calculated for three winters over Granger Basin using CRHM. Snow transport fluxes were distributed amongst HRUs using inter-HRU snow redistribution allocation factors. Three snow redistribution schemes of varying complexity were evaluated. CRHM model results showed that end-of-winter snow accumulation can be most accurately simulated when the inter-HRU snow redistribution schemes take into account wind direction and speed and HRU aerodynamic characteristics, along with the spatial arrangement of HRUs in the catchment. As snow transport scales approximately with the fourth power of wind speed (u4), inter-HRU snow redistribution allocation factors can be established according to the predominant u4 direction over a simulation period or can change at each time step according to an input measured wind direction. MESH and MESH-PBSM were used to simulate snow accumulation and ablation over these same HRUs. MESH-PBSM provided markedly better results than MESH without blowing snow algorithms.<p>
That snow redistribution by wind can be adequately simulated in computationally efficient HRUs over mountainous terrain has important implications for representing snow transport in large-scale hydrology models and land surface schemes. Snow redistribution by wind caused mountain snow accumulation to vary from 10% to 161% of seasonal snowfall within a headwater catchment in the Canadian Rocky Mountains, and blowing snow sublimation losses ranged from 10 to 37% of seasonal snowfall.
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Soil Moisture Estimation by Microwave Remote Sensing for Assimilation into WATClassKwok, Damian January 2007 (has links)
This thesis examines the feasibility of assimilating space borne remotely-sensed microwave data into WATClass using the ensemble Kalman filter. WATClass is a meso-scale gridded hydrological model used to track water and energy budgets of watersheds by way of real-time remotely sensed data. By incorporating remotely-sensed soil moisture estimates into the model, the model’s soil moisture estimates can be improved, thus increasing the accuracy of the entire model.
Due to the differences in scale between the remotely sensed data and WATClass, and the need of ground calibration for accurate soil moisture estimation from current satellite-borne active microwave remote sensing platforms, the spatial variability of soil moisture must be determined in order to characterise the dependency between the remotely-sensed estimates and the model data and subsequently to assimilate the remotely-sensed data into the model. Two sets of data – 1996-1997 Grand River watershed data and 2002-2003 Roseau River watershed data – are used to determine the spatial variability. The results of this spatial analysis however are found to contain too much error due to the small sample size. It is therefore recommended that a larger set of data with more samples both spatially and temporally be taken.
The proposed algorithm is tested with simulated data in a simulation of WATClass. Using nominal values for the estimated errors and other model parameters, the assimilation of remotely sensed data is found to reduce the absolute RMS error in soil moisture from 0.095 to approximately 0.071. The sensitivities of the improvement in soil moisture estimates by using the proposed algorithm to several different parameters are examined.
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Soil Moisture Estimation by Microwave Remote Sensing for Assimilation into WATClassKwok, Damian January 2007 (has links)
This thesis examines the feasibility of assimilating space borne remotely-sensed microwave data into WATClass using the ensemble Kalman filter. WATClass is a meso-scale gridded hydrological model used to track water and energy budgets of watersheds by way of real-time remotely sensed data. By incorporating remotely-sensed soil moisture estimates into the model, the model’s soil moisture estimates can be improved, thus increasing the accuracy of the entire model.
Due to the differences in scale between the remotely sensed data and WATClass, and the need of ground calibration for accurate soil moisture estimation from current satellite-borne active microwave remote sensing platforms, the spatial variability of soil moisture must be determined in order to characterise the dependency between the remotely-sensed estimates and the model data and subsequently to assimilate the remotely-sensed data into the model. Two sets of data – 1996-1997 Grand River watershed data and 2002-2003 Roseau River watershed data – are used to determine the spatial variability. The results of this spatial analysis however are found to contain too much error due to the small sample size. It is therefore recommended that a larger set of data with more samples both spatially and temporally be taken.
The proposed algorithm is tested with simulated data in a simulation of WATClass. Using nominal values for the estimated errors and other model parameters, the assimilation of remotely sensed data is found to reduce the absolute RMS error in soil moisture from 0.095 to approximately 0.071. The sensitivities of the improvement in soil moisture estimates by using the proposed algorithm to several different parameters are examined.
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