Multidisciplinary Water Management group, Faculty of Engineering Technology, University of Twente, Enschede, The Netherlands.
Sci Data. 2024 Feb 14;11(1):206. doi: 10.1038/s41597-024-03051-3.
The water footprint of a crop (WF) is a common metric for assessing agricultural water consumption and productivity. To provide an update and methodological enhancement of existing WF datasets, we apply a global process-based crop model to quantify consumptive WFs of 175 individual crops at a 5 arcminute resolution over the 1990-2019 period. This model simulates the daily crop growth and vertical water balance considering local environmental conditions, crop characteristics, and farm management. We partition WFs into green (water from precipitation) and blue (from irrigation or capillary rise), and differentiate between rainfed and irrigated production systems. The outputs include gridded datasets and national averages for unit water footprints (expressed in m t yr), water footprints of production (m yr), and crop water use (mm yr). We compare our estimates to other global studies covering different historical periods and methodological approaches. Provided outputs can offer insights into spatial and temporal patterns of agricultural water consumption and serve as inputs for further virtual water trade studies, life cycle and water footprint assessments.
作物的水资源足迹（WF）是评估农业用水消耗和生产力的常用指标。为了更新和改进现有的 WF 数据集，我们应用一种全球基于过程的作物模型，在 1990-2019 年期间以 5 弧分的分辨率量化了 175 种单一作物的消耗性 WF。该模型考虑当地环境条件、作物特性和农场管理，模拟了每日作物生长和垂直水分平衡。我们将 WF 划分为绿（降水用水）和蓝（灌溉或毛细上升用水），并区分雨养和灌溉生产系统。输出包括栅格数据集和单位水足迹（以 m t yr 表示）、生产用水足迹（m yr）和作物耗水量（mm yr）的国家平均值。我们将我们的估计值与涵盖不同历史时期和方法的其他全球研究进行了比较。提供的产出可以深入了解农业用水消耗的时空模式，并作为进一步虚拟水贸易研究、生命周期和水足迹评估的输入。
