摘要
通过优化灌溉和水资源管理以减少耕地土壤盐渍化对实现土地退化中和至关重要.各种灌溉和水资源管理措施对流域尺度盐渍化的缓解作用的有效性和可持续性尚不明确.本研究利用遥感技术估算了1984-2021年干旱区耕地的表层土壤盐度.然后,利用贝叶斯网络分析比较了十个大型干旱区流域(尼罗河、底格里斯-幼发拉底河、印度河、塔里木河、阿姆河、伊犁河、锡尔河、准格尔盆地、科罗拉多河和圣华金河流域)的土壤表层盐度对水资源管理(如各种灌溉和排水方式)的时空响应.在开发水平较高的流域,管理者采用滴灌和地下水灌溉,通过降低地下水水位有效地控制了土壤盐度.对于仍采用传统漫灌的流域,经济发展和政策支持对于建立“改善灌溉系统——降低盐度——增加农业收入”的良性循环至关重要.这也是实现土地退化中和目标的关键.
Reducing soil salinization of croplands with optimized irrigation and water management is essential to achieve land degradation neutralization(LDN).The effectiveness and sustainability of various irrigation and water management measures to reduce basin-scale salinization remain uncertain.Here we used remote sensing to estimate the soil salinity of arid croplands from 1984 to 2021.We then use Bayesian network analysis to compare the spatial–temporal response of salinity to water management,including various irrigation and drainage methods,in ten large arid river basins:Nile,Tigris-Euphrates,Indus,Tarim,Amu,Ili,Syr,Junggar,Colorado,and San Joaquin.In basins at more advanced phases of development,managers implemented drip and groundwater irrigation and thus effectively controlled salinity by lowering groundwater levels.For the remaining basins using conventional flood irrigation,economic development and policies are crucial for establishing a virtuous circle of“improving irrigation systems,reducing salinity,and increasing agricultural incomes”which is necessary to achieve LDN.
作者
施海洋
罗格平
Edwin H.Sutanudjaja
Olaf Hellwich
陈曦
丁建丽
吴世新
何秀凤
陈春波
Friday U.Ochege
王渊刚
凌青
艾里西尔·库尔班
Philippe De Maeyer
Tim Van de Voorde
Haiyang Shi;Geping Luo;Edwin H.Sutanudjaja;Olaf Hellwich;Xi Chen;Jianli Ding;Shixin Wu;Xiufeng He;Chunbo Chen;Friday U.Ochege;Yuangang Wang;Qing Ling;Alishir Kurban;Philippe De Maeyer;Tim Van de Voorde(State Key Laboratory of Desert and Oasis Ecology,Xinjiang Institute of Ecology and Geography,Chinese Academy of Sciences,Urumqi 830011,China;College of Resources and Environment,University of Chinese Academy of Sciences,Beijing 100049,China;Research Centre for Ecology and Environment of Central Asia,Chinese Academy of Sciences,Urumqi 830011,China;Department of Geography,Ghent University,Ghent 9000,Belgium;College of Resources and Environment Sciences,Xinjiang University,Urumqi 830046,China;Department of Physical Geography,Utrecht University,Utrecht 3584,Netherlands;Department of Computer Vision&Remote Sensing,Technical University of Berlin,Berlin 10587,Germany;Sino-Belgian Joint Laboratory of Geo-Information,Ghent 9000,Belgium;School of Earth Sciences and Engineering,Hohai University,Nanjing 211100,China;Department of Geography and Environmental Management,University of Port Harcourt,Port Harcourt 500004,Nigeria)
基金
supported by the Strategic Priority Research Programme of the Chinese Academy of Sciences(XDA20060302)
the Tianshan Talent Cultivation(2022TSYCLJ0001)
the Key Projects of Natural Science Foundation of Xinjiang Uygur Autonomous Region(2022D01D01)
the National Natural Science Foundation of China(U1803243)
the High-End Foreign Experts Project(G2022045012L)。
