Technologies that increase the accuracy of soil-moisture monitoring, such as in-situ sensors, have been proposed as a key solution for increasing agricultural water productivity. However, quantifying how uncertainty in soil-moisture estimates lead to irrigation inefficiencies or economic losses has not been explicitly studied. We develop a framework that combines a crop simulation model with a rule-based irrigation decision-making algorithm to assess the impact of soil-moisture uncertainty on irrigation use and farm profits. We apply this modelling framework to a case study of irrigated maize production in Nebraska, United States, a region where improvements in agricultural water productivity are at the forefront of water-policy debates. We consider two main sources of uncertainty that result in a divergence between the farmers’ perception of soil-water content and the true water status, namely errors in the knowledge of soil texture and measurement of daily soil-water flux inflows and outflows. Even for very large errors in both soil-texture and water-flux measurements, impacts on water use and profits were marginal (11 ha-mm increase and $27 ha^–1 decrease, respectively). In contrast, farmers’ choice of irrigation strategy had a much larger impact on water use and profits than uncertainty in soil-moisture information used to implement that strategy. Our findings show that near-optimal irrigation decisions can be made without perfect soil-moisture information. This conclusion suggests that providing farmers with improved irrigation scheduling recommendations – utilizing crop-water models and optimization techniques – would have a larger impact on water-use efficiency than simply providing farmers with technologies to more accurately monitor soil-moisture conditions.

提高土壤湿度监测精度的技术，如原位传感器，已被提议作为提高农业用水生产率的关键解决方案。然而，尚未明确研究量化土壤水分估计中的不确定性如何导致灌溉效率低下或经济损失。我们开发了一个框架，将作物模拟模型与基于规则的灌溉决策算法相结合，以评估土壤湿度不确定性对灌溉使用和农场利润的影响。我们将此建模框架应用于美国内布拉斯加州灌溉玉米生产的案例研究，该地区农业用水生产率的提高处于水政策辩论的前沿。我们考虑了导致农民对土壤含水量的感知与真实水分状况之间存在分歧的两个主要不确定性来源，即土壤质地知识和每日土壤水通量流入和流出的测量错误。即使对于土壤质地和水通量测量中非常大的误差，对用水和利润的影响也是微不足道的（增加 11 ha-mm 和 $27 ha^–1分别减少）。相比之下，农民选择灌溉策略对用水和利润的影响比用于实施该策略的土壤湿度信息的不确定性要大得多。我们的研究结果表明，即使没有完美的土壤水分信息，也可以做出近乎最佳的灌溉决策。这一结论表明，与简单地为农民提供更准确地监测土壤湿度条件的技术相比，利用作物-水模型和优化技术为农民提供改进的灌溉计划建议对用水效率的影响更大。