Physically Based Hydrological Modeling of the 2002 Floods in San Antonio, Texas

Abstract. Climate change is expected to strongly impact the hydrological and thermal regimes of Alpine rivers within the coming decades. In this context, the development of hydrological models accounting for the specific dynamics of Alpine catchments appears as a one of the promising approaches to reduce our uncertainty on future mountain hydrology. This paper describes the improvements brought to StreamFlow, an existing model for hydrological and stream temperature prediction built as an external extension to the physically-based snow model Alpine3D. StreamFlow's source code has been entirely written anew, taking advantage of object-oriented programming to significantly improve its structure and ease the implementation of future developments. The source code is now publicly available online, along with a complete documentation. A special emphasis has been put on modularity during the re-implementation of StreamFlow, so that many model aspects can be represented using different alternatives. For example, several options are now available to model the advection of water within the stream. This allows for an easy and fast comparison between different approaches and helps in defining more reliable uncertainty estimates of the model forecasts. In particular, a case study in a Swiss Alpine catchment reveals that the stream temperature predictions are particularly sensitive to the approach used to model the temperature of subsurface runoff, a fact which has been poorly reported in the literature to date. Based on the case study, StreamFlow is shown to reproduce hourly mean discharge with a Nash–Sutcliffe efficiency (NSE) of 0.82, and hourly mean temperature with a NSE of 0.78.

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Performance of a conceptual and physically based model in simulating the response of a semi-urbanized watershed in San Antonio, Texas

Hydrological Processes ◽

10.1002/hyp.9443 ◽

2012 ◽

Vol 27 (24) ◽

pp. 3394-3408 ◽

Cited By ~ 14

Author(s):

Almoutaz A. El Hassan ◽

H. O. Sharif ◽

Terrance Jackson ◽

Singaiah Chintalapudi

Keyword(s):

San Antonio ◽

Physically Based Model ◽

Physically Based

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Review: Mutli-source data assimilation for physically-based hydrological modeling of an experimantal hill by A. Botto, E. Belluco and M. Camporese

10.5194/hess-2018-18-rc2 ◽

2018 ◽

Author(s):

Anonymous

Keyword(s):

Data Assimilation ◽

Hydrological Modeling ◽

Source Data ◽

Physically Based

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Picturing and modelling catchments by representative hillslopes

10.5194/hess-2016-307 ◽

2016 ◽

Author(s):

Ralf Loritz ◽

Sibylle K. Hassler ◽

Conrad Jackisch ◽

Niklas Allroggen ◽

Loes van Schaik ◽

...

Keyword(s):

Conceptual Models ◽

Hydrological Modeling ◽

Winter Season ◽

Emergent Behavior ◽

Added Value ◽

Hydrological Models ◽

Runoff Generation ◽

Virtual Experiments ◽

Physically Based ◽

Physically Based Models

Abstract. Despite the numerous hydrological models existing in hydrology we are limited to a few forms of conceptualization when abstracting hydrological systems into different model frameworks. Speaking in black and white terms, in most cases hydrological systems are either represented spatially lumped with conceptual models or spatially explicit with physically-based models. Physically-based models are often parameter-rich, making the parametrization challenging, while conceptual models are parsimonious, with only a few parameters needing to be identified. But this simplistic mathematical expression is often also their drawback since their model states and parameters are difficult to translate to the physical properties of a catchment. It is interesting to note that both hydrological modeling approaches often start with the drawing of a perceptual model. This follows the hydrologist’s philosophy to separate dominant patterns and processes from idiosyncratic system details. Due to the importance of hillslopes as key landscape elements perceptual models are often displayed as 2D cross-sections. In this study we examine whether we can step beyond the qualitative character of perceptual models by using them as blueprint for setting up representative hillslope models. Thereby we test the hypothesis if a single hillslope can represent the functioning of an entire lower mesoscale catchment in a spatially aggregated way. We do this by setting up and testing two hillslope models in catchments located in two different geological settings, Schist and Marl, using a two-dimensional physically-based model. Both models are parametrized based on intensive field data and literature values without automatic calibration. Remarkably we are able to not only match the water balance of both catchments but further have some success in simulating runoff generation as well as soil moisture and sap flow dynamics. Particularly, our findings demonstrate that both models performed well during the winter season and clearly worse during the summer period. Virtual experiments revealed that this was most likely either due to a poor representation of the onset of vegetation in the Schist catchment or due to emergence of soil cracks in the Marl area. Both findings underpin that a static parameterization of hydrological models might be problematical in case of emergent behavior. Additional virtual experiments indicate that the storage of water in the bedrock and not so much the topographic gradient is a first order control on the hydrological functioning of the Schist catchment. We conclude that the representative hillslope concept is a feasible approach in data rich regions and that this form of abstraction provides an added value to the established conceptualization frameworks in hydrology.

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Conceptual and Physically Based Hydrological Modeling

Sustainable Water Resources Management ◽

10.1061/9780784414767.ch04 ◽

2017 ◽

pp. 81-118 ◽

Cited By ~ 1

Author(s):

T. I. Eldho ◽

Anand T. Kulkarni

Keyword(s):

Hydrological Modeling ◽

Physically Based

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Water budget, performance of evapotranspiration formulations, and their impact on hydrological modeling of a small boreal peatland-dominated watershed

Canadian Journal of Earth Sciences ◽

10.1139/cjes-2017-0046 ◽

2018 ◽

Vol 55 (2) ◽

pp. 206-220 ◽

Cited By ~ 2

Author(s):

Pierre-Erik Isabelle ◽

Daniel F. Nadeau ◽

Alain N. Rousseau ◽

François Anctil

Keyword(s):

Water Budget ◽

Hydrological Modeling ◽

Distributed Model ◽

Model Parameters ◽

Taylor Models ◽

Physically Based ◽

Model Efficiency ◽

The Impact ◽

Substantial Drop

Peatlands occupy around 13% of the land cover of Canada, and thus they play a key role in the water balance at high latitudes. They are well known for having substantial water loss due to evapotranspiration. Since measurements of evapotranspiration are scarce over these environments, hydrologists generally rely on models of varying complexity to evaluate these water exchanges in the global watershed balance. This study quantifies the water budget of a small boreal peatland-dominated watershed. We assess the performance of three evapotranspiration models in comparison with in situ observations and the impact of using these models in the hydrological modeling of the watershed. The study site (∼1 km2) is located in the eastern James Bay lowlands, Québec, Canada. During summer 2012, an eddy flux tower measured evapotranspiration continuously, while a trapezoidal flume monitored streamflow at the watershed outlet. We estimated evapotranspiration with a combinational model (Penman), a radiation-based model (Priestley–Taylor), and a temperature-based model (Hydro-Québec), and performed the hydrological modeling of the watershed with HYDROTEL, a physically based semi-distributed model. Our results show that the Penman and Priestley–Taylor models reproduce the observations with the highest precision, while a substantial drop in performance occurs with the Hydro-Québec model. However, these discrepancies did not appear to reduce the hydrological model efficiency, at least from what can be concluded from a 3-month modeling period. HYDROTEL appears sensitive to evapotranspiration inputs, but calibration of model parameters can compensate for the differences. These findings still need to be confirmed with longer modeling periods.

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Water displacement by sewer infrastructure in the Grote Nete catchment, Belgium, and its hydrological regime effects

Hydrology and Earth System Sciences ◽

10.5194/hess-18-1119-2014 ◽

2014 ◽

Vol 18 (3) ◽

pp. 1119-1136 ◽

Cited By ~ 11

Author(s):

D. Vrebos ◽

T. Vansteenkiste ◽

J. Staes ◽

P. Willems ◽

P. Meire

Keyword(s):

Hydrological Modeling ◽

Hydrological Regime ◽

Water Displacement ◽

River Flows ◽

Impervious Area ◽

Physically Based ◽

Spatially Distributed ◽

Sewer Infrastructure ◽

Impervious Areas ◽

Wastewater Collection

Abstract. Urbanization and especially increases in impervious areas, in combination with the installation of wastewater treatment infrastructure, can impact the runoff from a catchment and river flows in a significant way. These effects were studied for the Grote Nete catchment in Belgium based on a combination of empirical and model-based approaches. Effective impervious area, combined with the extent of the wastewater collection regions, was considered as an indicator for urbanization pressure. It was found that wastewater collection regions ranging outside the boundaries of the natural catchment boundaries caused changes in upstream catchment area between −16 and +3%, and upstream impervious areas between −99 and +64%. These changes lead to important intercatchment water transfers. Simulations with a physically based and spatially distributed hydrological catchment model revealed not only significant impacts of effective impervious area on seasonal runoff volumes but also low and peak river flows. Our results show the importance, as well as the difficulty, of explicitly accounting for these artificial pressures and processes in the hydrological modeling of urbanized catchments.

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Snowfall Limit Forecasts and Hydrological Modeling

Journal of Hydrometeorology ◽

10.1175/jhm-d-11-0147.1 ◽

2012 ◽

Vol 13 (5) ◽

pp. 1507-1519 ◽

Cited By ~ 15

Author(s):

Cara Tobin ◽

Andrea Rinaldo ◽

Bettina Schaefli

Keyword(s):

Hydrological Modeling ◽

Standard Procedure ◽

Swiss Alps ◽

Small Scale ◽

Limited Area ◽

Catchment Scale ◽

Alpine Regions ◽

Physically Based ◽

Discharge Simulation ◽

Standard Output

Abstract Hydrological flood forecasting in mountainous areas requires accurate partitioning between rain and snowfall to properly estimate the extent of runoff contributing areas. Here a method to make use of snowfall limit information—a standard output of limited-area models (LAMs)—for catchment-scale hydrological modeling is proposed. LAMs consider the vertical, humid, atmospheric structure in their snowfall limit calculations. The proposed approach is thus more physically based than inferring snowfall limit estimates based on (dry) ground temperature measurements, which is the standard procedure in most hydrological models. The presented case study uses forecast reanalyses from the Consortium for Small-Scale Modeling (COSMO) limited-area model as input for discharge simulation in a topographically complex catchment in the Swiss Alps. Results suggest that the use of COSMO snowfall limits during spring snowmelt periods can provide more accurate runoff simulations than routine procedures, with practical implications for operational hydrology in Alpine regions.

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A national topographic dataset for hydrological modeling over contiguous United States

10.5194/essd-2020-291 ◽

2020 ◽

Author(s):

Jun Zhang ◽

Laura E. Condon ◽

Hoang Tran ◽

Reed M. Maxwell

Keyword(s):

United States ◽

Hydrological Modeling ◽

R Package ◽

The United States ◽

Hydrologic Model ◽

Stream Network ◽

Topographic Features ◽

Digital Elevation ◽

Physically Based ◽

Integrated Hydrologic Model

Abstract. Topography is a fundamental input to hydrologic models critical for generating realistic streamflow networks as well as infiltration and groundwater flow. Although there exist several national topographic datasets for the United States, they may not be compatible with gridded models that require hydrologically consistent Digital Elevation Models (DEMs). Here, we present a national topographic dataset developed support physically based hydrologic simulations at 1 km and 250 m spatial resolution over contiguous United States. The workflow is described step-by-step in two parts (a) DEM processing using a Priority Flood algorithm to ensure hydrologically consistent drainage networks and (b) slope calculation and smoothing to improve drainage performance. The accuracy of derived stream network is evaluated by comparing the derived drainage area to drainage areas reported by the national stream gage network. The slope smoothing steps are evaluated using the runoff simulations with an integrated hydrologic model. The processed DEM is designed to capture the topographic features and improve the runoff simulations for the models solving partial differential equations. The workflow uses an open-source R package and all output datasets and processing scripts are available and fully documented here. All of the output datasets and scripts for processing are published through Cyverse at 250 m and 1 km resolution. The DOI link for the dataset is https://doi.org/10.25739/e1ps-qy48 (Zhang and Condon, 2020).

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GRQA: Global River Water Quality Archive

10.5194/egusphere-egu21-3865 ◽

2021 ◽

Author(s):

Holger Virro ◽

Giuseppe Amatulli ◽

Alexander Kmoch ◽

Longzhu Shen ◽

Evelyn Uuemaa

Keyword(s):

Water Quality ◽

River Water ◽

Large Scale ◽

Hydrological Modeling ◽

Water Quality Modeling ◽

River Water Quality ◽

Quality Data ◽

Observation Data ◽

Water Quality Data ◽

Physically Based

Recent advances in implementing machine learning (ML) methods in hydrology have given rise to a new, data-driven approach to hydrological modeling. Comparison of physically based and ML approaches has shown that ML methods can achieve a similar accuracy to the physically based ones and outperform them when describing nonlinear relationships. Global ML models have been already successfully applied for modeling hydrological phenomena such as discharge.However, a major problem related to large-scale&#160; water quality modeling has been the lack of available observation data with a good spatiotemporal coverage. This has affected the reproducibility of previous studies and the potential improvement of existing models. In addition to the observation data itself, insufficient or poor quality metadata has also discouraged researchers to integrate the already available datasets. Therefore, improving both, the availability, and quality of open water quality data would increase the potential to implement predictive modeling on a global scale.We aim to address the aforementioned issues by presenting the new Global River Water Quality Archive (GRQA) by integrating data from five existing global and regional sources:<ul><li>Canadian Environmental Sustainability Indicators program (CESI)</li> <li>Global Freshwater Quality Database (GEMStat)</li> <li>GLObal RIver Chemistry database (GLORICH)</li> <li>European Environment Agency (Waterbase)</li> <li>USGS Water Quality Portal (WQP)</li> </ul>The resulting dataset contains a total of over 14 million observations for 41 different forms of some of the most important water quality parameters, focusing on nutrients, carbon, oxygen and sediments. Supplementary metadata and statistics are provided with the observation time series to improve the usability of the dataset. We report on developing a harmonized schema and reproducible workflow that can be adapted to integrate and harmonize further data sources. We conclude our study with a call for action to extend this dataset and hope that the provided reproducible method of data integration and metadata provenance shall lead as an example.

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