HydroDS: Data services in support of physically based, distributed hydrological models

Gichamo, Tseganeh Z.; Sazib, Nazmus; Tarboton, David G.; Dash, Pabitra

doi:10.1016/j.envsoft.2020.104623

Cited by 22 publications

(9 citation statements)

References 35 publications

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“…At present, there are two main reverse flow routing methods: One is the hydrological method, which simulates the hydrological cycle process by establishing a lumped or distributed hydrological model (Lewis et al, 2018;Ehlers et al, 2019;Gichamo et al, 2020). The other is the hydrodynamic method, which simulates flood wave routing by building one-dimensional (1D), two-dimensional (2D) and even three-dimensional (3D) hydrodynamic models (Fleischmann et al, 2019;Wing et al, 2019;Haque et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

Application of multiple methods for reverse flow routing: A case study of Luxi river basin, China

Chen

et al. 2023

Front. Earth Sci.

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Because of the lack of hydrological monitoring facilities and methods in many areas, basic hydrological elements cannot be obtained directly. In that case, the reverse flow routing method is frequently used, which allows for the simulation of hydraulic elements upstream using downstream data, and is of great significance for river and reservoir joint regulation, flood disaster management, flood control evaluation, and flood forecasting. The hydrological and hydrodynamic methods are the two main approaches to reverse flow routing. The hydrological method is mainly realized by constructing a distributed or lumped hydrological model based on rainfall, soil type, terrain slope, and other data. A distributed hydrological model focuses on the physical mechanism of runoff yield and flow concentration, the spatial variability of model input, and the hydraulic connection between different units. The solution of the hydrological method is relatively simple, but it requires a large amount of measured data, which limits the applicability of this method. The other method builds a hydrodynamic model by solving shallow water equations for reverse flow routing. This method has definite physical significance, higher accuracy, and obvious advantages of simple and fast calculations. It can not only simulate one-dimensional but also two-dimensional flood routing processes. In addition, the slope-area method is frequently used for flood reverse routing in many areas in China without relevant hydrological data, and can calculate the peak discharge, maximum water level, flood recurrence interval, and other information by the hydrodynamic formula, along with the cross-section and the measured flood mark water level. Due to the influence of extreme weather, a heavy rainstorm and flood occurred in the Luxi river basin in China on 16 August 2020, resulting in severe flood disasters in this area and causing significant economic losses. Moreover, due to the lack and damage of hydrological monitoring equipment, hydrological information such as flood hydrographs and peak discharges of this flood could not be recorded. To reduce the uncertainty of a single method for reverse flow routing, we integrated and applied the hydrodynamic, hydrological, and slope-area methods to reverse flow routing in the Luxi river basin on 16 August 2020. The simulation accuracy of the three methods was verified in terms of the measured flood mark water level, and the simulation results of the three methods were analyzed and compared. The results are as follows: 1) The hydrological method can better simulate flood hydrographs and durations, especially for flood hydrographs with multiple peaks, and is more applicable than the other two methods. However, the hydrodynamic and slope-area methods have better accuracy in the reverse simulation of flood peaks. Therefore, through the comprehensive comparative analysis of these three methods, flood elements such as flood hydrographs, peak discharges, and durations can be simulated more accurately, and the problem of large errors caused by a single method can be avoided; 2) The simulation results of the hydrodynamic and slope-area methods are similar, and the maximum error of the peak discharge calculated using the two methods is within 10%. According to the simulation results, the peak discharge reached 2,920 m3/s downstream of Luxi river basin, which is a flood having more than 100-year recurrence interval; 3) The simulation results of the hydrological method show that the flow hydrograph is a double-peak, and the two peaks occurred at 17:00 on August 16 and 6:00 on 17 August 2020, respectively.

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Section: Introductionmentioning

confidence: 99%

Application of multiple methods for reverse flow routing: A case study of Luxi river basin, China

Chen

et al. 2023

Front. Earth Sci.

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“…Model-specific steps would be to convert the resulting information (i.e., which pixels/land classes are present per model element) to the specific format a model requires (e.g., storing the most common land class per model element as a value in a netCDF file which the model reads during initialization), and, if necessary, perform some form of data transformation to connect land class data to model parameter values or settings (e.g., by defining a lookup table that contains parameter values for each land cover type). Community-wide efficiency gains are possible if workflows distinguish between model-agnostic and model-specific steps and enable straightforward re-use of the workflow for model-agnostic steps (see also Essawy et al, 2016;Gichamo et al, 2020, who make this argument in the context of webbased model configuration tools).…”

Section: Introductionmentioning

confidence: 99%

Community Workflows to Advance Reproducibility in Hydrologic Modeling: Separating model-agnostic and model-specific configuration steps in applications of large-domain hydrologic models

Knoben

Clark

Bales³

et al. 2022

Preprint

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“…Model‐specific steps would be to convert the resulting information (i.e., which pixels/land classes are present per model element) to the specific format a model requires (e.g., storing the most common land class per model element as a value in a netCDF file which the model reads during initialization), and, if necessary, perform some form of data transformation to connect land class data to model parameter values or settings (e.g., by defining a lookup table that contains parameter values for each land cover type). Community‐wide efficiency gains are possible if workflows distinguish between model‐agnostic and model‐specific steps and enable straightforward reuse of the workflow for model‐agnostic steps (see also Essawy et al., 2016; Gichamo et al., 2020, who make this argument in the context of web‐based model configuration tools).…”

Section: Introductionmentioning

confidence: 99%

Community Workflows to Advance Reproducibility in Hydrologic Modeling: Separating Model‐Agnostic and Model‐Specific Configuration Steps in Applications of Large‐Domain Hydrologic Models

Knoben

Clark

Bales

et al. 2022

Water Resources Research

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Despite the proliferation of computer‐based research on hydrology and water resources, such research is typically poorly reproducible. Published studies have low reproducibility due to incomplete availability of data and computer code, and a lack of documentation of workflow processes. This leads to a lack of transparency and efficiency because existing code can neither be quality controlled nor reused. Given the commonalities between existing process‐based hydrologic models in terms of their required input data and preprocessing steps, open sharing of code can lead to large efficiency gains for the modeling community. Here, we present a model configuration workflow that provides full reproducibility of the resulting model instantiations in a way that separates the model‐agnostic preprocessing of specific data sets from the model‐specific requirements that models impose on their input files. We use this workflow to create large‐domain (global and continental) and local configurations of the Structure for Unifying Multiple Modeling Alternatives (SUMMA) hydrologic model connected to the mizuRoute routing model. These examples show how a relatively complex model setup over a large domain can be organized in a reproducible and structured way that has the potential to accelerate advances in hydrologic modeling for the community as a whole. We provide a tentative blueprint of how community modeling initiatives can be built on top of workflows such as this. We term our workflow the “Community Workflows to Advance Reproducibility in Hydrologic Modeling” (CWARHM; pronounced “swarm”).

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HydroDS: Data services in support of physically based, distributed hydrological models

Cited by 22 publications

References 35 publications

Application of multiple methods for reverse flow routing: A case study of Luxi river basin, China

Application of multiple methods for reverse flow routing: A case study of Luxi river basin, China

Community Workflows to Advance Reproducibility in Hydrologic Modeling: Separating model-agnostic and model-specific configuration steps in applications of large-domain hydrologic models

Community Workflows to Advance Reproducibility in Hydrologic Modeling: Separating Model‐Agnostic and Model‐Specific Configuration Steps in Applications of Large‐Domain Hydrologic Models

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