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

2019 ◽  
Vol 52 (1) ◽  
pp. 194-205 ◽  
Author(s):  
Liming Zhu ◽  
Junzhi Liu ◽  
A-Xing Zhu ◽  
Zheng Duan
2018 ◽  
Vol 2018 ◽  
pp. 1-13 ◽  
Author(s):  
Yongwei Liu ◽  
Wen Wang ◽  
Yuanbo Liu

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.


2021 ◽  
Author(s):  
Xuan Dong ◽  
Yang Zhou ◽  
Haishan Chen ◽  
Botao Zhou ◽  
Shanlei Sun

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.


2009 ◽  
Vol 24 (5) ◽  
pp. 889-908 ◽  
Author(s):  
Yongyong Zhang ◽  
Jun Xia ◽  
Tao Liang ◽  
Quanxi Shao

2010 ◽  
Vol 25 (2) ◽  
pp. 246-257 ◽  
Author(s):  
Yongyong Zhang ◽  
Quanxi Shao ◽  
Jun Xia ◽  
Stuart E. Bunn ◽  
Qiting Zuo

Water ◽  
2019 ◽  
Vol 11 (10) ◽  
pp. 2174 ◽  
Author(s):  
Jingcai Wang ◽  
Hui Lin ◽  
Jinbai Huang ◽  
Chenjuan Jiang ◽  
Yangyang Xie ◽  
...  

Huai River Basin (HRB) is an important food and industrial production area and a frequently drought-affected basin in eastern China. It is necessary to consider the future drought development for reducing the impact of drought disasters. Three global circulation models (GCMs) from Coupled Model Intercomparison Project phase 5 (CMIP5), such as CNRM-CM5 (CNR), HadGEM2-ES (Had) and MIROC5 (MIR), were used to assessment the future drought conditions under two Representative Concentration Pathways (RCPs) scenarios, namely, RCP4.5 and RCP8.5. The standardized precipitation evapotranspiration index (SPEI), statistical method, Mann-Kendall test, and run theory were carried out to study the variations of drought tendency, frequency, and characteristics and their responses to climate change. The research showed that the three CMIP5 models differ in describing the future seasonal and annual variations of precipitation and temperature in the basin and thus lead to the differences in describing drought trends, frequency, and drought characteristics, such as drought severity, drought duration, and drought intensity. However, the drought trend, frequency, and characteristics in the future are more serious than the history. The drought frequency and characteristics tend to be strengthened under the scenario of high concentration of RCP8.5, and the drought trend is larger than that of low concentration of RCP4.5. The lower precipitation and the higher temperature are the main factors affecting the occurrence of drought. All three CMIP5 models show that precipitation would increase in the future, but it could not offset the evapotranspiration loss caused by significant temperature rise. The serious risk of drought in the future is still higher. Considering the uncertainty of climate models for simulation and prediction, attention should be paid to distinguish the effects of different models in the future drought assessment.


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