Illuminating Deep Uncertainties in the Estimation of Irrigation Water Withdrawals

全球为灌溉农业抽取的水量是人类对淡水资源影响的衡量标准。尽管科学家们试图通过越来越详细的数学模型来准确量化灌溉用水量，但他们的估计似乎并不一致。这种差异表明，在我们对灌溉取水的概念化中存在着深刻的不确定性，这回避了更细粒度算法的开发。如果不彻底揭露和了解这些不确定性的相关性，我们对人类对水文循环的影响的了解将停留在脆弱的基础上。DAWN将组建一个五人小组，以揭示、检查和吸收影响我们对灌溉用水抽出的深层不确定性。首先，《黎明》将揭开所有全球灌溉取水量模型的基本假设，思考它们对估计的影响，并评估以模拟为基础的主要信念系统的可靠性。其次，曙光将从传统灌溉者那里检索关于灌溉取水的见解，并将他们对管理灌溉用水的前提的理解与嵌入全球模型的灌溉科学知识进行比较。第三，曙光将结合科学家和传统灌溉者的知识体系，开发具有成本效益的不确定性/敏感性分析方法，以探索它们的模糊性如何影响全球灌溉取水量的建模。通过融合水文学、统计学、哲学和人类学的方法，黎明提出了开创性的研究，以极大地增强我们对灌溉抽水的理解。这最终将增强我们设计基于模型的灌溉政策的能力，这些政策在不可减少的模糊性下交付。

The volume of water globally withdrawn for irrigation agriculture is a measure of the human impact on freshwater resources. Although scientists have attempted to produce an accurate quantification of irrigation water withdrawals through increasingly detailed mathematical models, their estimates do not seem to converge. This discrepancy points towards the existence of deep uncertainties in our conceptualization of irrigation water withdrawals that evade the development of finer-grained algorithms. Without thoroughly exposing and understanding the relevance of these uncertainties, our knowledge of the influence that humans have on the hydrological cycle will remain on fragile grounds.DAWN will assemble a five-member team to unfold, examine and assimilate the deep uncertainties that condition our understanding of irrigation water withdrawals. Firstly, DAWN will unravel the underlying assumptions of all global irrigation water withdrawal models, ponder their effect on the estimations and assess the solidity of the main belief systems grounding the simulations. Secondly, DAWN will retrieve insights on irrigation withdrawals from traditional irrigators, and compare their understandings of the premises that govern irrigation water use with the scientific knowledge of irrigation embedded in global models. Thirdly, DAWN will combine the knowledge systems of scientists and traditional irrigators and develop cost-effective uncertainty/sensitivity analysis methods to explore how their ambiguities impact the modeling of global irrigation water withdrawals. By merging approaches from hydrology, statistics, philosophy and anthropology, DAWN proposes ground-breaking research to dramatically robustify our comprehension of irrigation withdrawals. This will ultimately enhance our capacity to design model-based irrigation policies that deliver under irreducible ambiguities.