ESA CCI Soil Moisture Assimilation in SWAT for Improved Hydrological Simulation in Upper Huai River Basin

The assimilation of satellite soil moisture (SM) products with coarse resolution is promising in improving rainfall-runoff modeling, but it is largely impacted by the data assimilation (DA) strategy. This study performs the assimilation of a satellite soil moisture product from the European Space Agency (ESA) Climate Change Initiative (CCI) in a physically based semidistributed hydrological model (SWAT) in the upper Huai River basin in China, with the objective to improve its rainfall-runoff simulation. In this assimilation, the ensemble Kalman filter (EnKF) is adopted with full consideration of the model and observation error, the rescaling technique for satellite SM, and the regional applicability of the hydrological model. The results show that the ESA CCI SM assimilation generally improves the streamflow simulation of the study catchment. It is more effective for low-flow simulation, while for very high-flow/large-flood modeling, the DA performance shows uncertainty. The less-effective performance on large-flood simulation lies in the relatively low dependence of rainfall-runoff generation on the antecedent SM as during which the SM is nearly saturated and the runoff is largely dominated by precipitation. Besides, the efficiency of DA is deteriorated by the dense forest coverage and the complex topography conditions of the basin. Overall, the ESA CCI SM assimilation improves the streamflow simulation of the SWAT model in particular for low flow. This study provides an encouragement for the application of the ESA CCI SM in water management, especially over low-flow periods.

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Comparison of daily and sub-daily SWAT models for daily streamflow simulation in the Upper Huai River Basin of China

Stochastic Environmental Research and Risk Assessment ◽

10.1007/s00477-015-1099-0 ◽

2015 ◽

Vol 30 (3) ◽

pp. 959-972 ◽

Cited By ~ 22

Author(s):

Xiaoying Yang ◽

Qun Liu ◽

Yi He ◽

Xingzhang Luo ◽

Xiaoxiang Zhang

Keyword(s):

River Basin ◽

Daily Streamflow ◽

Huai River Basin ◽

Huai River ◽

Streamflow Simulation

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Assessment of SMOS and SMAP soil moisture products against new estimates combining physical model, a statistical model, and in-situ observations: a case study over the Huai River Basin, China

Journal of Hydrology ◽

10.1016/j.jhydrol.2021.126468 ◽

2021 ◽

pp. 126468

Author(s):

Xiaoyi Wang ◽

Haishen Lü ◽

Wade T. Crow ◽

Yonghua Zhu ◽

Qimeng Wang ◽

...

Keyword(s):

Soil Moisture ◽

Statistical Model ◽

Physical Model ◽

River Basin ◽

Huai River Basin ◽

Huai River ◽

In Situ Observations ◽

The Huai River Basin

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Improving the Distributed Hydrological Model Performance in Upper Huai River Basin: Using Streamflow Observations to Update the Basin States via the Ensemble Kalman Filter

Advances in Meteorology ◽

10.1155/2016/4921616 ◽

2016 ◽

Vol 2016 ◽

pp. 1-14 ◽

Cited By ~ 6

Author(s):

Yongwei Liu ◽

Wen Wang ◽

Yiming Hu ◽

Wei Cui

Keyword(s):

Kalman Filter ◽

River Basin ◽

Ensemble Kalman Filter ◽

Hydrological Model ◽

Model Performance ◽

Real Data ◽

Distributed Hydrological Model ◽

Huai River Basin ◽

Huai River

This study investigates the capability of improving the distributed hydrological model performance by assimilating the streamflow observations. Incorrectly estimated model states will lead to discrepancies between the observed and estimated streamflow. Consequently, streamflow observations can be used to update the model states, and the improved model states will eventually benefit the streamflow predictions. This study tests this concept in upper Huai River basin. We assimilate the streamflow observations sequentially into the Soil and Water Assessment Tool (SWAT) using the ensemble Kalman filter (EnKF) to update the model states. Both synthetic experiments and real data application are used to demonstrate the benefit of this data assimilation scheme. The experiment shows that assimilating the streamflow observations at interior sites significantly improves the streamflow predictions for the whole basin. Assimilating the catchment outlet streamflow improves the streamflow predictions near the catchment outlet. In real data case, the estimated streamflow at the catchment outlet is significantly improved by assimilating the in situ streamflow measurements at interior gauges. Assimilating the in situ catchment outlet streamflow also improves the streamflow prediction of one interior location on the main reach. This may demonstrate that updating model states using streamflow observations can constrain the flux estimates in distributed hydrological modeling.

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Projecting Hydrological Responses to Climate Change Using CMIP6 Climate Scenarios for the Upper Huai River Basin, China

Frontiers in Environmental Science ◽

10.3389/fenvs.2021.759547 ◽

2021 ◽

Vol 9 ◽

Author(s):

Guodong Bian ◽

Jianyun Zhang ◽

Jie Chen ◽

Mingming Song ◽

Ruimin He ◽

...

Keyword(s):

Climate Change ◽

River Basin ◽

Return Period ◽

Hydrological Model ◽

Flood Frequency ◽

Precipitation Series ◽

Climate Scenarios ◽

Huai River Basin ◽

Huai River ◽

Increasing Trend

The influence of climate change on the regional hydrological cycle has been an international scientific issue that has attracted more attention in recent decades due to its huge effects on drought and flood. It is essential to investigate the change of regional hydrological characteristics in the context of global warming for developing flood mitigation and water utilization strategies in the future. The purpose of this study is to carry out a comprehensive analysis of changes in future runoff and flood for the upper Huai River basin by combining future climate scenarios, hydrological model, and flood frequency analysis. The daily bias correction (DBC) statistical downscaling method is used to downscale the global climate model (GCM) outputs from the sixth phase of the Coupled Model Intercomparison Project (CMIP6) and to generate future daily temperature and precipitation series. The Xinanjiang (XAJ) hydrological model is driven to project changes in future seasonal runoff under SSP245 and SSP585 scenarios for two future periods: 2050s (2031–2060) and 2080s (2071–2100) based on model calibration and validation. Finally, the peaks over threshold (POT) method and generalized Pareto (GP) distribution are combined to evaluate the changes of flood frequency for the upper Huai River basin. The results show that 1) GCMs project that there has been an insignificant increasing trend in future precipitation series, while an obvious increasing trend is detected in future temperature series; 2) average monthly runoffs in low-flow season have seen decreasing trends under SSP245 and SSP585 scenarios during the 2050s, while there has been an obvious increasing trend of average monthly runoff in high-flow season during the 2080s; 3) there is a decreasing trend in design floods below the 50-year return period under two future scenarios during the 2050s, while there has been an significant increasing trend in design flood during the 2080s in most cases and the amplitude of increase becomes larger for a larger return period. The study suggests that future flood will probably occur more frequently and an urgent need to develop appropriate adaptation measures to increase social resilience to warming climate over the upper Huai River basin.

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Spatial evaluation of L-band satellite-based soil moisture products in the upper Huai River basin of China

European Journal of Remote Sensing ◽

10.1080/22797254.2019.1579618 ◽

2019 ◽

Vol 52 (1) ◽

pp. 194-205 ◽

Cited By ~ 1

Author(s):

Liming Zhu ◽

Junzhi Liu ◽

A-Xing Zhu ◽

Zheng Duan

Keyword(s):

Soil Moisture ◽

River Basin ◽

Huai River Basin ◽

Huai River ◽

L Band ◽

Spatial Evaluation

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Lag impacts of the anomalous July soil moisture over Southern China on the August rainfall over the Huang–Huai River Basin

Climate Dynamics ◽

10.1007/s00382-021-05989-1 ◽

2021 ◽

Author(s):

Xuan Dong ◽

Yang Zhou ◽

Haishan Chen ◽

Botao Zhou ◽

Shanlei Sun

Keyword(s):

Soil Moisture ◽

Water Vapor ◽

Latent Heat ◽

River Basin ◽

Southern China ◽

Eastern China ◽

Cyclonic Circulation ◽

Upward Motion ◽

Huai River Basin ◽

Huai River

AbstractThe effect of soil moisture (SM) on precipitation is an important issue in the land–atmosphere interaction and shows largely regional differences. In this study, the SM of the ERA-Interim reanalysis and precipitation data of the weather stations were used to investigate their relationship over eastern China during July and August. Moreover, the WRF model was applied to further validate the effect of SM on rainfall. In the observations, a significantly negative relationship was found that, when the soil over southern China is wet (dry) in July, the rainfall decreases (increases) over the Huang–Huai–River basin (hereafter HHR) in August. In the model results, the soil can “memorize” its wet anomaly over southern China from July to August. In August, the wet soil increases the latent heat flux at surface and the air moisture at lower levels of the atmosphere, which is generally unstable due to the summer monsoon. Thus, upward motion is prevailing over southern China in August, and the increased surface air moisture is transported upwards. After that, the condensation of water vapor is enhanced at the middle and upper levels, increasing the release of latent heat in the atmosphere. The heat release forms a cyclonic circulation at the lower levels over eastern China, and induces the transport and convergence of water vapor increased over southern China in August. This further strengthens the upward motion over southern China and the cyclonic circulation at the lower levels. Therefore, positive feedback appears between water vapor transport and atmospheric circulation. Meanwhile, the cyclonic circulation over southern China results in a response of water vapor divergence and a downward motion over HHR. Consequently, the negative anomalies of precipitation occur over HHR in August. When the July soil is dry over southern China, the opposite results can be found through the similar mechanism.

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SHETRAN and HEC HMS Model Evaluation for Runoff and Soil Moisture Simulation in the Jičinka River Catchment (Czech Republic)

Water ◽

10.3390/w13060872 ◽

2021 ◽

Vol 13 (6) ◽

pp. 872

Author(s):

Vesna Đukić ◽

Ranka Erić

Keyword(s):

Soil Moisture ◽

Czech Republic ◽

Hydrological Model ◽

Flash Flood ◽

Model Performance ◽

Rainfall Runoff ◽

The Czech Republic ◽

River Catchment ◽

Hydrological Variable ◽

Model Structures

Due to the improvement of computation power, in recent decades considerable progress has been made in the development of complex hydrological models. On the other hand, simple conceptual models have also been advanced. Previous studies on rainfall–runoff models have shown that model performance depends very much on the model structure. The purpose of this study is to determine whether the use of a complex hydrological model leads to more accurate results or not and to analyze whether some model structures are more efficient than others. Different configurations of the two models of different complexity, the Système Hydrologique Européen TRANsport (SHETRAN) and Hydrologic Modeling System (HEC-HMS), were compared and evaluated in simulating flash flood runoff for the small (75.9 km2) Jičinka River catchment in the Czech Republic. The two models were compared with respect to runoff simulations at the catchment outlet and soil moisture simulations within the catchment. The results indicate that the more complex SHETRAN model outperforms the simpler HEC HMS model in case of runoff, but not for soil moisture. It can be concluded that the models with higher complexity do not necessarily provide better model performance, and that the reliability of hydrological model simulations can vary depending on the hydrological variable under consideration.

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