Author:
Chen Xuhui,Jiang Jinbao,Li Hui
Abstract
In recent years, alternating periods of floods and droughts, possibly related to climate change and/or human activity, have occurred in the Liao River Basin of China. To monitor and gain a deep understanding of the frequency and severity of the hydro-meteorological extreme events in the Liao River Basin in the past 30 years, the total storage deficit index (TSDI) is established by the Gravity Recovery and Climate Experiment (GRACE)-based terrestrial water storage anomalies (TWSAs) and the general regression neural network (GRNN)-predicted TWSA. Results indicate that the GRNN model trained with GRACE-based TWSA, model-simulated soil moisture, and precipitation observations was optimal, and the correlation coefficient and the root mean square error (RMSE) of the predicted TWSA and GRACE TWSA for the testing period equal 0.90 and 18 mm, respectively. The drought and flood conditions monitored by the TSDI were consistent with those of previous studies and records. The extreme climate events could indirectly reflect the status of the regional hydrological cycle. By monitoring the extreme climate events in the study area with TSDI, which was based on the TWSA of GRACE and GRNN, the decision of water resource management in the Liao River Basin could be made reasonably.
Subject
General Earth and Planetary Sciences
Reference69 articles.
1. Study on the Response of Land Use/Land Cover to Climate Change in Liao River Basin of Jilin Province;Li;Res. Soil Water Conserv.,2014
2. Climate change characteristics and its impacts on water resources in the Liaohe river basin from 1961 to 2009;Sun;J. Meteorol. Environ.,2012
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