Human-Induced and Climate-Driven Contributions to Water Storage Variations in the Haihe River Basin, China

Creators: Zhong, Yulong; Feng, Wei; Humphrey, Vincent; Zhong, Min

Abstract

Terrestrial water storage (TWS) can be influenced by both climate change and anthropogenic activities. While the Gravity Recovery and Climate Experiment (GRACE) satellites have provided a global view on long-term trends in TWS, our ability to disentangle human impacts from natural climate variability remains limited. Here we present a quantitative method to isolate these two contributions with reconstructed climate-driven TWS anomalies (TWSA) based on long-term precipitation data. Using the Haihe River Basin (HRB) as a case study, we find a higher human-induced water depletion rate (−12.87 ± 1.07 mm/yr) compared to the original negative trend observed by GRACE alone for the period of 2003–2013, accounting for a positive climate-driven TWSA trend (+4.31 ± 0.72 mm/yr). We show that previous approaches (e.g., relying on land surface models) provide lower estimates of the climate-driven trend, and thus likely underestimated the human-induced trend. The isolation method presented in this study will help to interpret observed long-term TWS changes and assess regional anthropogenic impacts on water resources.

Additional Information

© 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). Received: 19 November 2019; Accepted: 13 December 2019; Published: 17 December 2019. Author Contributions: Conceptualization, Y.Z., W.F. and V.H.; methodology, Y.Z., W.F. and V.H.; investigation, Y.Z.; data curation, Y.Z.; writing—original draft preparation, Y.Z. and W.F.; writing—review and editing, W.F., M.Z. and V.H.; funding acquisition, Y.Z., M.Z. and W.F. The research is funded by National Natural Science Foundation of China (41674084, 41774094, 41431070, and 41874095); Fundamental Research Funds for the Central Universities, China University of Geosciences (Wuhan) (G1323519314); Natural Science Fund for Distinguished Young Scholars of Hubei Province, China (Grant No. 2019CFA091); Open Research Fund Program of State Key Laboratory of Geodesy and Earth's Dynamics (SKLGED2019-2-5-E); and Key Laboratory of Surveying and Mapping Science and Geospatial Information Technology of Ministry of Natural Resources. We would like to acknowledge the NASA Goddard Space Flight Center (GSFC), the Jet Propulsion Laboratory (JPL), and the Center for Space Research (CSR), University of Texas at Austin for providing the GRACE mascon solutions. We also acknowledge the China Meteorological Administration for providing the grid precipitation data. The presented dataset in this study is archived in the Global Change Research Data Publishing and Repository (GCdataPR, http://www.geodoi.ac.cn/WebCn/doi.aspx?Id=1298). The authors thank Fei Li, Haoming Yan, and RAAJ Ramsankaran for their insightful suggestions and comments on the earlier draft of this manuscript. The authors declare no conflict of interest.

Attached Files

Published - remotesensing-11-03050.pdf

Files

remotesensing-11-03050.pdf

Files (3.5 MB)

Name	Size	Download all
remotesensing-11-03050.pdf md5:aa80c4c1245ad31a4f7f5bcfd8a4e94f	3.5 MB	Preview Download

Additional details

	All versions	This version
Views	0	0
Downloads	0	0
Data volume	0 Bytes	0 Bytes