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RSS FeedsRemote Sensing, Vol. 14, Pages 2381: Spatial and Temporal Drought Characteristics in the Huanghuaihai Plain and Its Influence on Cropland Water Use Efficiency (Remote Sensing)

 
 

15 may 2022 13:38:54

 
Remote Sensing, Vol. 14, Pages 2381: Spatial and Temporal Drought Characteristics in the Huanghuaihai Plain and Its Influence on Cropland Water Use Efficiency (Remote Sensing)
 


Understanding the relationship between drought and the water use efficiency (WUE) in terrestrial ecosystems can help reduce drought risk. It remains unclear what the correlation between the cropland water use efficiency (CWUE) and drought during drought events. We aim to identify the spatiotemporal relationship between drought and the CWUE and to ensure the service capacity of cultivated land ecosystems. In this study, the cubist algorithm was used to establish a monthly integrated surface drought index (mISDI) dataset for the Huang–Huai–Hai Plain (HHHP), and the run theory was used to identify drought events. We assessed the spatio-temporal variations of drought in the HHHP during 2000–2020 and its influence on the CWUE. The research results were as follows: from the overall perspective of the HHHP, the mISDI showed a downward trend. Drought had an enhanced effect on the CWUE of the HHHP, and the enhancement of the CWUE in the eastern hilly area was more significant. The CWUE response to drought had a three-month lag period and a significant positive correlation, and it was shown that the cultivated land ecosystems in this area had strong drought resistance ability. This study provides a new framework for understanding the response of the CWUE to drought and formulating reasonable vegetation management strategies for the HHHP.


 
126 viewsCategory: Geology, Physics
 
Remote Sensing, Vol. 14, Pages 2379: Machine Learning Algorithms for Modeling and Mapping of Groundwater Pollution Risk: A Study to Reach Water Security and Sustainable Development (Sdg) Goals in a Mediterranean Aquifer System (Remote Sensing)
Remote Sensing, Vol. 14, Pages 2382: Characterizing the Patterns and Trends of Urban Growth in Saudi Arabia’s 13 Capital Cities Using a Landsat Time Series (Remote Sensing)
 
 
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