Predicting groundwater recharge for varying land cover and climate conditions – a global meta-study (data)

Groundwater recharge is one of the important factors determining the groundwater development potential of an area. Even though recharge plays a key role in controlling groundwater system dynamics, much uncertainty remains regarding the relationships between groundwater recharge and its governing factors at a large scale. Therefore, this study aims to identify the most influential factors of groundwater recharge, and to develop an empirical model to estimate diffuse rainfall recharge at a global scale. Recharge estimates reported in the literature from various parts of the world (715 sites) were compiled and used in model building and testing exercises. Unlike conventional recharge estimates from water balance, this study used a multimodel inference approach and information theory to explain the relationship between groundwater recharge and influential factors and to predict groundwater recharge at 0.5∘ resolution. The results show that meteorological factors (precipitation and potential evapotranspiration) and vegetation factors (land use and land cover) had the most predictive power for recharge. According to the model, long-term global average annual recharge (1981–2014) was 134 mm yr−1 with a prediction error ranging from −8 to 10 mm yr−1 for 97.2 % of cases. The recharge estimates presented in this study are unique and more reliable than the existing global groundwater recharge estimates because of the extensive validation carried out using both independent local estimates collated from the literature and national statistics from the Food and Agriculture Organization (FAO). In a water-scarce future driven by increased anthropogenic development, the results from this study will aid in making informed decisions about groundwater potential at a large scale.地下水补给（Groundwater recharge）是决定区域地下水开发潜力的关键因素之一。尽管其在调控地下水系统动态过程中发挥着核心作用，但在大尺度维度下，地下水补给与其主控因子之间的关联仍存在诸多不确定性。为此，本研究旨在明确地下水补给的关键影响因子，并构建可用于全球尺度弥散降雨补给（diffuse rainfall recharge）估算的经验模型。研究收集了全球各地文献刊载的715个监测点位的补给估算数据，用于模型构建与验证实验。与传统基于水量平衡（water balance）的补给估算方法不同，本研究采用多模型推断（multimodel inference）方法与信息论（information theory）解析地下水补给与影响因子间的关联，并以0.5°的空间分辨率开展地下水补给预测。研究结果显示，气象因子（降水与潜在蒸散发（potential evapotranspiration））以及植被因子（土地利用（land use）与土地覆被（land cover））对补给量的预测能力最强。基于该模型，1981–2014年的全球长期年平均地下水补给量为134 mm yr⁻¹，97.2%的案例的预测误差区间为-8至10 mm yr⁻¹。本研究提出的补给估算数据相较于现有全球地下水补给估算成果更具独特性与可靠性，这得益于我们通过整理自文献的独立局部估算数据，以及粮食及农业组织（Food and Agriculture Organization，FAO）的国家统计数据开展了全面的验证工作。在未来人为开发活动加剧、水资源短缺的背景下，本研究成果可为大尺度地下水开发潜力的科学决策提供有力支撑。