文献类型：期刊文献

英文题名：Assessing impacts of the Ecological Retreat project on water conservation in the Yellow River Basin

作者：Jia, Guanyu[1,2] Hu, Wenmin[1,2,3] Zhang, Bin[4] Li, Guo[1,2] Shen, Shouyun[1,2] Gao, Zhihai[3] Li, Yi[5]

第一作者：Jia, Guanyu

通信作者：Hu, WM[1]

机构：[1]Cent South Univ Forestry & Technol, Changsha 410004, Peoples R China;[2]Engn Technol Res Ctr Big Data Landscape Resources, Changsha 410004, Peoples R China;[3]Chinese Acad Forestry, Res Inst Forest Resources Informat Tech, Beijing 100001, Peoples R China;[4]Huazhong Agr Univ, Wuhan, Peoples R China;[5]Hunan Agr Univ, Changsha 410015, Peoples R China

年份：2022

卷号：828

外文期刊名：SCIENCE OF THE TOTAL ENVIRONMENT

收录：;EI(收录号：20221211817289);Scopus(收录号：2-s2.0-85126523811);WOS:【SCI-EXPANDED(收录号:WOS:000804479700010)】；

基金：This research was funded by the Postgraduate Scientific Research Innovation Project of Hunan Province (Program number: CX20210845), and Philosophy and Social Science Foundation of Hunan Province (Program number:18YBQ131). This work was supported by the Key Discipline of the State Forestry Administration [Grant number: 2016-21], and the "Double First-Class" Cultivating Subject of Hunan Province [Grant number: 2018-469], and the Key Project of Hunan Provincial Department of Education [Grant number: 21A0513].

语种：英文

外文关键词：Water yield; InVEST model; Ecological project; Machine learning; Yellow River Basin

摘要：The Ecological Retreat (ER) project significantly impacts water conservation functions in the Yellow River Basin (YRB). However, studies on the impact and benefit of different ER modes on ecological water effects still lack systematic and integral disclosure. In our study, CNLUCC (China land use/cover data sets) and the Markov transition matrix were used to simulate land pattern changes from 2000 to 2018. Water yield was chosen as an indicator of water conservation to explore the impact of the ER project by using the water yield module of the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model. After the ER project, the land pattern changed significantly because massive cropland was transformed into forest and grassland. Thus, the total water yields of the YRB increased by 46.32 x 10(3) hm(3) from 2000 to 2018, and the overall water yield benefit was 12.39% larger than the water loss. Forest rehabilitation (FR) showed the highest average water yield capacity, while grassland restoration (GR) exhibited the most incredible total water conservation benefit. Wetland recovery (WLR) manifested a great capacity to improve average water yield, but its total benefit was far less than FR and OR, while waterbody recovery (W BR) showed a negative impact. The results indicate that FR and OR were effective restoration methods, and WLR showed great potential to improve water yield. By using the random forest and principal components analysis, precipitation (PRE), evaporation (AFT and ET0), and variation of forest and grassland proved to be the most critical driving indicators affecting water yield changes. Additionally, the correlation and sensitivity between root depth (R_depth) and water yield indicate that increasing R_Depth can also enhance water conservation. The FR project provides a valuable restoration model for water yield and water conservation benefits. The results can provide theoretical support for eco-hydrology and land ecological restoration studies.