scholarly journals Computationally Efficient Multivariate Calibration and Validation of a Grid-Based Hydrologic Model in Sparsely Gauged West African River Basins

Water ◽  
2018 ◽  
Vol 10 (10) ◽  
pp. 1418 ◽  
Author(s):  
Thomas Poméon ◽  
Bernd Diekkrüger ◽  
Rohini Kumar
Keyword(s):  
River Basins ◽  
Hydrologic Model ◽  
West African ◽  
Evaluation Framework ◽  
Actual Evapotranspiration ◽  
Computationally Efficient ◽  
Modeling Framework ◽  
Diverse Range ◽  
Grid Based

The prediction of freshwater resources remains a challenging task in West Africa, where the decline of in situ measurements has a detrimental effect on the quality of estimates. In this study, we establish a series of modeling routines for the grid-based mesoscale Hydrologic Model (mHM) using Multiscale Parameter Regionalization (MPR). We provide a computationally efficient application of mHM-MPR across a diverse range of data-scarce basins using in situ observations, remote sensing, and reanalysis inputs. Model performance was first screened for four precipitation datasets and three evapotranspiration calculation methods. Subsequently, we developed a modeling framework in which the pre-screened model is first calibrated using discharge as the observed variable (mHM Q), and next calibrated using a combination of discharge and actual evapotranspiration data (mHM Q/ET). Both model setups were validated in a multi-variable evaluation framework using discharge, actual evapotranspiration, soil moisture and total water storage data. The model performed reasonably well, with mean discharge KGE values of 0.53 (mHM Q) and 0.49 (mHM Q/ET) for the calibration; and 0.23 (mHM Q) and 0.13 (mHM Q/ET) for the validation. Other tested variables were also within a good predictive range. This further confirmed the robustness and well-represented spatial distribution of the hydrologic predictions. Using MPR, the calibrated model can then be scaled to produce outputs at much smaller resolutions. Overall, our analysis highlights the worth of utilizing additional hydrologic variables (together with discharge) for the reliable application of a distributed hydrologic model in sparsely gauged West African river basins.

scholarly journals Improved regional-scale groundwater representation by the coupling of the mesoscale Hydrologic Model (mHM v5.7) to the groundwater model OpenGeoSys (OGS)

2018 ◽  
Vol 11 (5) ◽  
pp. 1989-2007 ◽  
Author(s):  
Miao Jing ◽  
Falk Heße ◽  
Rohini Kumar ◽  
Wenqing Wang ◽  
Thomas Fischer ◽  
...  
Keyword(s):  
Groundwater Flow ◽  
Regional Scale ◽  
Coupled Model ◽  
Hydrologic Model ◽  
Surface Fluxes ◽  
Groundwater Model ◽  
Hydrologic Models ◽  
Modeling Framework ◽  
Groundwater Head ◽  
Grid Based

Abstract. Most large-scale hydrologic models fall short in reproducing groundwater head dynamics and simulating transport process due to their oversimplified representation of groundwater flow. In this study, we aim to extend the applicability of the mesoscale Hydrologic Model (mHM v5.7) to subsurface hydrology by coupling it with the porous media simulator OpenGeoSys (OGS). The two models are one-way coupled through model interfaces GIS2FEM and RIV2FEM, by which the grid-based fluxes of groundwater recharge and the river–groundwater exchange generated by mHM are converted to fixed-flux boundary conditions of the groundwater model OGS. Specifically, the grid-based vertical reservoirs in mHM are completely preserved for the estimation of land-surface fluxes, while OGS acts as a plug-in to the original mHM modeling framework for groundwater flow and transport modeling. The applicability of the coupled model (mHM–OGS v1.0) is evaluated by a case study in the central European mesoscale river basin – Nägelstedt. Different time steps, i.e., daily in mHM and monthly in OGS, are used to account for fast surface flow and slow groundwater flow. Model calibration is conducted following a two-step procedure using discharge for mHM and long-term mean of groundwater head measurements for OGS. Based on the model summary statistics, namely the Nash–Sutcliffe model efficiency (NSE), the mean absolute error (MAE), and the interquartile range error (QRE), the coupled model is able to satisfactorily represent the dynamics of discharge and groundwater heads at several locations across the study basin. Our exemplary calculations show that the one-way coupled model can take advantage of the spatially explicit modeling capabilities of surface and groundwater hydrologic models and provide an adequate representation of the spatiotemporal behaviors of groundwater storage and heads, thus making it a valuable tool for addressing water resources and management problems.

scholarly journals The FLASH Project: Improving the Tools for Flash Flood Monitoring and Prediction across the United States

2017 ◽  
Vol 98 (2) ◽  
pp. 361-372 ◽  
Author(s):  
Jonathan J. Gourley ◽  
Zachary L. Flamig ◽  
Humberto Vergara ◽  
Pierre-Emmanuel Kirstetter ◽  
Robert A. Clark ◽  
...  
Keyword(s):  
United States ◽  
Real Time ◽  
Flash Flood ◽  
Rank Correlation ◽  
The United States ◽  
Hydrologic Model ◽  
Computationally Efficient ◽  
Modeling Framework ◽  
Flood Prediction ◽  
Peak Discharges

Abstract This study introduces the Flooded Locations and Simulated Hydrographs (FLASH) project. FLASH is the first system to generate a suite of hydrometeorological products at flash flood scale in real-time across the conterminous United States, including rainfall average recurrence intervals, ratios of rainfall to flash flood guidance, and distributed hydrologic model–based discharge forecasts. The key aspects of the system are 1) precipitation forcing from the National Severe Storms Laboratory (NSSL)’s Multi-Radar Multi-Sensor (MRMS) system, 2) a computationally efficient distributed hydrologic modeling framework with sufficient representation of physical processes for flood prediction, 3) capability to provide forecasts at all grid points covered by radars without the requirement of model calibration, and 4) an open-access development platform, product display, and verification system for testing new ideas in a real-time demonstration environment and for fostering collaborations. This study assesses the FLASH system’s ability to accurately simulate unit peak discharges over a 7-yr period in 1,643 unregulated gauged basins. The evaluation indicates that FLASH’s unit peak discharges had a linear and rank correlation of 0.64 and 0.79, respectively, and that the timing of the peak discharges has errors less than 2 h. The critical success index with FLASH was 0.38 for flood events that exceeded action stage. FLASH performance is demonstrated and evaluated for case studies, including the 2013 deadly flash flood case in Oklahoma City, Oklahoma, and the 2015 event in Houston, Texas—both of which occurred on Memorial Day weekends.

scholarly journals Macro-scale grid-based and subbasin-based hydrologic modeling: joint simulation and cross-calibration

2018 ◽  
Vol 21 (1) ◽  
pp. 77-91 ◽  
Author(s):  
Xuefeng Chu ◽  
Zhulu Lin ◽  
Mohsen Tahmasebi Nasab ◽  
Lan Zeng ◽  
Kendall Grimm ◽  
...  
Keyword(s):  
Hydrologic Modeling ◽  
Swat Model ◽  
Temporal Trends ◽  
Hydrologic Model ◽  
Modeling Framework ◽  
Joint Simulation ◽  
Macro Scale ◽  
Cross Calibration ◽  
Scale Grid ◽  
Grid Based

Abstract Watershed hydrologic models often possess different structures and distinct methods and require dissimilar types of inputs. As spatially-distributed data are becoming widely available, macro-scale modeling plays an increasingly important role in water resources management. However, calibration of a macro-scale grid-based model can be a challenge. The objective of this study is to improve macro-scale hydrologic modeling by joint simulation and cross-calibration of different models. A joint modeling framework was developed, which linked a grid-based hydrologic model (GHM) and the subbasin-based Soil and Water Assessment Tool (SWAT) model. Particularly, a two-step cross-calibration procedure was proposed and implemented: (1) direct calibration of the subbasin-based SWAT model using observed streamflow data; and (2) indirect calibration of the grid-based GHM through the transfer of the well-calibrated SWAT simulations to the GHM. The joint GHM-SWAT modeling framework was applied to the Red River of the North Basin (RRB). The model performance was assessed using the Nash–Sutcliffe efficiency (NSE) and percent bias (PBIAS). The results highlighted the feasibility of the proposed cross-calibration strategy in taking advantage of both model structures to analyze the spatial/temporal trends of hydrologic variables. The modeling approaches developed in this study can be applied to other basins for macro-scale climatic-hydrologic modeling.

scholarly journals Are General Circulation Models Ready for Operational Streamflow Forecasting for Water Management in the Ganges and Brahmaputra River Basins?

2015 ◽  
Vol 17 (1) ◽  
pp. 195-210 ◽  
Author(s):  
Safat Sikder ◽  
Xiaodong Chen ◽  
Faisal Hossain ◽  
Jason B. Roberts ◽  
Franklin Robertson ◽  
...  
Keyword(s):  
Water Management ◽  
River Basins ◽  
Hydrologic Model ◽  
Streamflow Forecasting ◽  
Management Decisions ◽  
Brahmaputra River ◽  
Ganges Basin ◽  
Monthly Scale ◽  
Brahmaputra Basin ◽  
The Ganges

Abstract This study asks the question of whether GCMs are ready to be operationalized for streamflow forecasting in South Asian river basins, and if so, at what temporal scales and for which water management decisions are they likely to be relevant? The authors focused on the Ganges, Brahmaputra, and Meghna basins for which there is a gridded hydrologic model calibrated for the 2002–10 period. The North American Multimodel Ensemble (NMME) suite of eight GCM hindcasts was applied to generate precipitation forecasts for each month of the 1982–2012 (30 year) period at up to 6 months of lead time, which were then downscaled according to the bias-corrected statistical downscaling (BCSD) procedure to daily time steps. A global retrospective forcing dataset was used for this downscaling procedure. The study clearly revealed that a regionally consistent forcing for BCSD, which is currently unavailable for the region, is one of the primary conditions to realize reasonable skill in streamflow forecasting. In terms of relative RMSE (normalized by reference flow obtained from the global retrospective forcings used in downscaling), streamflow forecast uncertainty (RMSE) was found to be 38%–50% at monthly scale and 22%–35% at seasonal (3 monthly) scale. The Ganges River (regulated) experienced higher uncertainty than the Brahmaputra River (unregulated). In terms of anomaly correlation coefficient (ACC), the streamflow forecasting at seasonal (3 monthly) scale was found to have less uncertainty (>0.3) than at monthly scale (<0.25). The forecast skill in the Brahmaputra basin showed more improvement when the time horizon was aggregated from monthly to seasonal than the Ganges basin. Finally, the skill assessment for the individual seasons revealed that the flow forecasting using NMME data had less uncertainty during monsoon season (July–September) in the Brahmaputra basin and in postmonsoon season (October–December) in the Ganges basin. Overall, the study indicated that GCMs can have value for management decisions only at seasonal or annual water balance applications at best if appropriate historical forcings are used in downscaling. The take-home message of this study is that GCMs are not yet ready for prime-time operationalization for a wide variety of multiscale water management decisions for the Ganges and Brahmaputra River basins.

scholarly journals Using satellite-based evapotranspiration estimates to improve the structure of a simple conceptual rainfall–runoff model

2017 ◽  
Vol 21 (2) ◽  
pp. 879-896 ◽  
Author(s):  
Tirthankar Roy ◽  
Hoshin V. Gupta ◽  
Aleix Serrat-Capdevila ◽  
Juan B. Valdes
Keyword(s):  
Model Performance ◽  
Hydrologic Model ◽  
Actual Evapotranspiration ◽  
Hydrologic Models ◽  
Catchment Scale ◽  
Model Driven ◽  
Alternative Approach ◽  
Precipitation Estimates ◽  
Daily Water ◽  
Rainfall Runoff Model

Abstract. Daily, quasi-global (50° N–S and 180° W–E), satellite-based estimates of actual evapotranspiration at 0.25° spatial resolution have recently become available, generated by the Global Land Evaporation Amsterdam Model (GLEAM). We investigate the use of these data to improve the performance of a simple lumped catchment-scale hydrologic model driven by satellite-based precipitation estimates to generate streamflow simulations for a poorly gauged basin in Africa. In one approach, we use GLEAM to constrain the evapotranspiration estimates generated by the model, thereby modifying daily water balance and improving model performance. In an alternative approach, we instead change the structure of the model to improve its ability to simulate actual evapotranspiration (as estimated by GLEAM). Finally, we test whether the GLEAM product is able to further improve the performance of the structurally modified model. Results indicate that while both approaches can provide improved simulations of streamflow, the second approach also improves the simulation of actual evapotranspiration significantly, which substantiates the importance of making diagnostic structural improvements to hydrologic models whenever possible.

scholarly journals A guided approach for subtomogram averaging of challenging macromolecular assemblies

2020 ◽  
Author(s):  
Danielle Grotjahn ◽  
Saikat Chowdhury ◽  
Gabriel C. Lander
Keyword(s):  
Electron Tomography ◽  
A Priori ◽  
Three Dimensional ◽  
Structural Heterogeneity ◽  
Dimensional Structure ◽  
Diverse Range ◽  
Macromolecular Assemblies ◽  
Cryo Electron Tomography ◽  
Subtomogram Averaging

AbstractCryo-electron tomography is a powerful biophysical technique enabling three-dimensional visualization of complex biological systems. Macromolecular targets of interest identified within cryo-tomograms can be computationally extracted, aligned, and averaged to produce a better-resolved structure through a process called subtomogram averaging (STA). However, accurate alignment of macromolecular machines that exhibit extreme structural heterogeneity and conformational flexibility remains a significant challenge with conventional STA approaches. To expand the applicability of STA to a broader range of pleomorphic complexes, we developed a user-guided, focused refinement approach that can be incorporated into the standard STA workflow to facilitate the robust alignment of particularly challenging samples. We demonstrate that it is possible to align visually recognizable portions of multi-subunit complexes by providing a priori information regarding their relative orientations within cryo-tomograms, and describe how this strategy was applied to successfully elucidate the first three-dimensional structure of the dynein-dynactin motor protein complex bound to microtubules. Our approach expands the application of STA for solving a more diverse range of heterogeneous biological structures, and establishes a conceptual framework for the development of automated strategies to deconvolve the complexity of crowded cellular environments and improve in situ structure determination technologies.

scholarly journals Spatial Pattern Oriented Multi-Criteria Sensitivity Analysis of a Distributed Hydrologic Model

2018 ◽  
Author(s):  
Mehmet Cüneyd Demirel ◽  
Julian Koch ◽  
Gorka Mendiguren ◽  
Simon Stisen
Keyword(s):  
Sensitivity Analysis ◽  
Spatial Variability ◽  
Spatial Pattern ◽  
Spatial Patterns ◽  
Performance Measures ◽  
Sampling Strategy ◽  
Behavioral Model ◽  
Hydrologic Model ◽  
Actual Evapotranspiration ◽  
Model Parameters

Hydrologic models are conventionally constrained and evaluated using point measurements of streamflow, which represents an aggregated catchment measure. As a consequence of this single objective focus, model parametrization and model parameter sensitivity are typically not reflecting other aspects of catchment behavior. Specifically for distributed models, the spatial pattern aspect is often overlooked. Our paper examines the utility of multiple performance measures in a spatial sensitivity analysis framework to determine the key parameters governing the spatial variability of predicted actual evapotranspiration (AET). Latin hypercube one-at-a-time (LHS-OAT) sampling strategy with multiple initial parameter sets was applied using the mesoscale hydrologic model (mHM) and a total of 17 model parameters were identified as sensitive. The results indicate different parameter sensitivities for different performance measures focusing on temporal hydrograph dynamics and spatial variability of actual evapotranspiration. While spatial patterns were found to be sensitive to vegetation parameters, streamflow dynamics were sensitive to pedo-transfer function (PTF) parameters. Above all, our results show that behavioral model definition based only on streamflow metrics in the generalized likelihood uncertainty estimation (GLUE) type methods require reformulation by incorporating spatial patterns into the definition of threshold values to reveal robust hydrologic behavior in the analysis.

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