A coupled atmospheric–hydrologic modeling system  with variable grid sizes for rainfall–runoff simulation  in semi-humid and semi-arid watersheds: how does  the coupling scale affects the results?

Tian, Jiyang; Liu, Jia; Wang, Yang; Wang, Wei; Li, Chuanzhe; Hu, Chunqi

doi:10.5194/hess-24-3933-2020

Cited by 21 publications

(9 citation statements)

References 40 publications

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“…In this study, the data to get designs storm are based on WRF rainfall products simulated at high spatial-temporal resolutions to capture localized storm events. The WRF model is robust and flexible in reproducing rainfall data at the spatial and temporal resolution that can be needed for the flood hydrology model (Liu et al 2012;Chawla et al 2018;Tian et al 2020). Here, we simulated four known events (i.e., 25 June 2012, 3 September 2013, 13 April 2016, and 16 April 2016 that have caused distinct flood hazards in Kampala, Uganda.…”

Section: Discussionmentioning

confidence: 99%

“…Moreover, the WRF model is able to consider the local-scale processes affecting the rainfall, such as the effect of urban extent and position on extreme rainfall distribution (Paul et al 2018;Zhang et al 2018;Oliveros et al 2019). In the same way, the WRF model is robust in considering the variability of the storms across wide areas and its flexibility to reproduce rainfall data at the spatial and temporal resolution that can be needed for the flood hydrology model (Liu et al 2012;Chawla et al 2018;Tian et al 2020). Thus, when appropriately configured and validated, the WRF model is a suitable tool for simulating the high-intensity rainfall events and spatial variability for flood modeling (Zittis et al 2017;Sikder and Hossain 2018).…”

Section: Introductionmentioning

confidence: 99%

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Application of the WRF model rainfall product for the localized flood hazard modeling in a data-scarce environment

et al. 2022

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Urban flood hazard model needs rainfall with high spatial and temporal resolutions for flood hazard analysis to better simulate flood dynamics in complex urban environments. However, in many developing countries, such high-quality data are scarce. Data that exist are also spatially biased toward airports and urban areas in general, where these locations may not represent flood-prone areas. One way to gain insight into the rainfall data and its spatial patterns is through numerical weather prediction models. As their performance improves, these might serve as alternative rainfall data sources for producing optimal design storms required for flood hazard modeling in data-scarce areas. To gain such insight, we developed Weather Research and Forecasting (WRF) design storms based on the spatial distribution of high-intensity rainfall events simulated at high spatial and temporal resolutions. Firstly, three known storm events (i.e., 25 June 2012, 13 April 2016, and 16 April 2016) that caused the flood hazard in the study area are simulated using the WRF model. Secondly, the potential gridcell events that are able to trigger the localized flood hazard in the catchment are selected and translated to the WRF design storm form using a quantile expression. Finally, three different WRF design storms per event are constructed: Lower, median, and upper quantiles. The results are compared with the design storms of 2- and 10-year return periods constructed based on the alternating-block method to evaluate differences from a flood hazard assessment point of view. The method is tested in the case of Kampala city, Uganda. The comparison of the design storms indicates that the WRF model design storms properties are in good agreement with the alternating-block design storms. Mainly, the differences between the produced flood characteristics (e.g., hydrographs and the number of flood gird cells) when using WRF lower quantiles (WRFLs) versus 2-year and WRF upper quantiles (WRFUs) versus 10-year alternating-block storms are very minimal. The calculated aggregated performance statistics (F scores) for the simulated flood extent of WRF design storms benchmarked with the alternating-block storms also produced a higher score of 0.9 for both WRF lower quantiles versus 2-year and WRF upper quantile versus 10-year alternating-block storm. The result suggested that the WRF design storms can be considered an added value for flood hazard assessment as they are closer to real systems causing rainfall. However, more research is needed on which area can be considered as a representative area in the catchment. The result has practical application for flood risk assessment, which is the core of integrated flood management.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Application of the WRF model rainfall product for the localized flood hazard modeling in a data-scarce environment

et al. 2022

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“…The value of T in the Fuping and Zijingguan catchments were statistically analyzed. Experimentation demonstrated that the cumulative distribution curves of T values between different regions are always similar [50].…”

Section: The Grid-based Hebei Modelmentioning

confidence: 90%

“…The grid-based Hebei model adopts a simplified form of the Saint Venant equations for confluence calculation. Due to perennial channel water shortage and substantial channel seepage in the study area, an additional Horton infiltration equation was considered in the grid-based Hebei model [50].…”

Section: The Grid-based Hebei Modelmentioning

confidence: 99%

Data Assimilation for Rainfall-Runoff Prediction Based on Coupled Atmospheric-Hydrologic Systems with Variable Complexity

Wang

Liu

et al. 2021

Remote Sensing

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The data assimilation technique is an effective method for reducing initial condition errors in numerical weather prediction (NWP) models. This paper evaluated the potential of the weather research and forecasting (WRF) model and its three-dimensional data assimilation (3DVar) module in improving the accuracy of rainfall-runoff prediction through coupled atmospheric-hydrologic systems. The WRF model with the assimilation of radar reflectivity and conventional surface and upper-air observations provided the improved initial and boundary conditions for the hydrological process; subsequently, three atmospheric-hydrological systems with variable complexity were established by coupling WRF with a lumped, a grid-based Hebei model, and the WRF-Hydro modeling system. Four storm events with different spatial and temporal rainfall distribution from mountainous catchments of northern China were chosen as the study objects. The assimilation results showed a general improvement in the accuracy of rainfall accumulation, with low root mean square error and high correlation coefficients compared to the results without assimilation. The coupled atmospheric-hydrologic systems also provide more accurate flood forecasts, which depend upon the complexity of the coupled hydrological models. The grid-based Hebei system provided the most stable forecasts regardless of whether homogeneous or inhomogeneous rainfall was considered. Flood peaks before assimilation were underestimated more in the lumped Hebei model relative to the other coupling systems considered, and the model seems more applicable for homogeneous temporal and spatial events. WRF-Hydro did not exhibit desirable predictions of rapid flood process recession. This may reflect increasing infiltration due to the interaction of atmospheric and land surface hydrology at each integration, resulting in mismatched solutions for local runoff generation and confluence.

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“…Liu et al [26] modified the Green-Ampt equation in the MISDc model to improve flood simulation with fixed values of the maximum water capacity parameter (W_max) but the improvement was minuscule, where the evaluation index (NSE) increased from 0.71 to 0.73. In this study, in an attempt to improve the infiltration process, the emphasis on the impact of W_max calibration was carried out due to its important role in estimating infiltration capacity, which influences the calculation of runoff generation [55]. The improvements were obvious, where the evaluation indexes increased from 0.56 to 0.81 for R 2 and from 0.41 to 0.82 for KGE.…”

Section: The Importance Of W_max Parameter Estimation In Flood Simulamentioning

confidence: 99%

Influence of Calibration Parameter Selection on Flash Flood Simulation for Small to Medium Catchments with MISDc-2L Model

Nguyen

Zhu

et al. 2020

Water

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It is of great challenge to accurately predict flash floods for small to medium catchments (SMC) in mountainous areas, for which parameter calibration strategies are crucial for model performance. This study investigates the influence of calibration parameter selection on flash flood simulations using a rainfall–runoff model, MISDc-2L (Modello Idrologico Semi-Distribuito in continuo–2 layers), at hourly scale for SMC in the Huai River basin of China over the 2010–2015 period. We investigated model performances under different calibration schemes, where different amounts of model parameters were selected for the calibration procedure. The model clearly performed better in the case involving calibration of partial sensitive parameters than that of a full parameter set with respect to the peaks, the hydrographs and the base-flow of flood simulation, especially after including maximum water capacity (W_max) in the calibration. This finding was consistently valid under different model calibration experiments, including single event, “split-sample” test and combined events at different flood magnitude levels. We further found that the model performed better for high magnitude flood events than medium and low ones, but clear improvements can be achieved for low and medium magnitude flood events with careful calibration parameter selection. Our study suggests that calibration parameter selection is important for flash flood event simulations with the MISDc-2L model for SMC in the Huai River basin of China; specifically, the reduction in calibration parameter amount and the inclusion of W_max in calibration remarkably improve flood simulation.

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A coupled atmospheric–hydrologic modeling system with variable grid sizes for rainfall–runoff simulation in semi-humid and semi-arid watersheds: how does the coupling scale affects the results?

Cited by 21 publications

References 40 publications

Application of the WRF model rainfall product for the localized flood hazard modeling in a data-scarce environment

Application of the WRF model rainfall product for the localized flood hazard modeling in a data-scarce environment

Data Assimilation for Rainfall-Runoff Prediction Based on Coupled Atmospheric-Hydrologic Systems with Variable Complexity

Influence of Calibration Parameter Selection on Flash Flood Simulation for Small to Medium Catchments with MISDc-2L Model

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