Monitoring the spatio-temporal changes of terrestrial water storage using GRACE data in the Tarim River basin between 2002 and 2015

Peng Yang; Jun Xia; Chesheng Zhan; Yunfeng Qiao; Yueling Wang

doi:10.1016/j.scitotenv.2017.03.268

Monitoring the spatio-temporal changes of terrestrial water storage using GRACE data in the Tarim River basin between 2002 and 2015

Sci Total Environ. 2017 Oct 1:595:218-228. doi: 10.1016/j.scitotenv.2017.03.268. Epub 2017 Apr 4.

Authors

Peng Yang¹, Jun Xia², Chesheng Zhan³, Yunfeng Qiao⁴, Yueling Wang³

Affiliations

¹ Key Laboratory of Water Cycle & Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China.
² Key Laboratory of Water Cycle & Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; State Key Laboratory of Water Resources & Hydropower Engineering Sciences, Wuhan University, Wuhan 430000, China. Electronic address: xiaj@igsnrr.ac.cn.
³ Key Laboratory of Water Cycle & Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China.
⁴ University of Chinese Academy of Sciences, Beijing 100049, China; Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China.

PMID: 28384578
DOI: 10.1016/j.scitotenv.2017.03.268

Abstract

With the threat of water shortages intensifying, the need to identify the terrestrial water storage (TWS) variation in the Tarim River Basin (TRB) becomes very significant for managing its water resource. Due to the lack of large-scale hydrological data, this study employed the Gravity Recovery and Climate Experiment (GRACE) and Global Land Data Assimilation System (GLDAS) to monitor TWS variation in the TRB during the period of 2002-2015, cooperating with two statistical techniques, Principal Component Analysis (PCA) - Empirical Orthogonal Function (EOF) and Multiple Linear Regression (MLR). Results indicated that (1) the Tropical rainfall measuring mission (TRMM) data can be applied well in the TRB; (2) the EOF result showed that both the time series of TRMM precipitation and GRACE-derived TWS in the TRB between 2002 and 2015 were dominated by the annual signals, which were followed by the semiannual signals; (3) the linear trend for the spatially averaged GRACE-derived TWS changes exhibited an decrease of 1.6±1.1mm/a, and the EOF result indicated a significant decrease of 4.1±1.5mm/a in the north of TRB; (4) while the precipitation variations was the major driver for the TWS changes, the GLDAS-derived TWS (i.e., soil moisture) decrease and ground water decrease played the major role in the TWS decrease in the north of TRB for the significant correlation (P<0.05). The changes of TWS might be linked to excessive exploitation of water resources, increased population, and shrinking water supplies, which would impact on the water level of the lakes or reservoir.

Keywords: Multiple linear regression; Principal component analysis; TRB; TRMM; Variability indices.