Drought early warning systems (DEWSs) aim to spatially monitor and forecast risk of water shortage to inform early, risk-mitigating interventions. However, due to the scarcity of in situ monitoring in groundwater-dependent arid zones, spatial drought exposure is inferred using maps of satellite-based indicators such as rainfall anomalies, soil moisture, and vegetation indices. On the local scale, these coarse-resolution proxy indicators provide a poor inference of groundwater availability. The improving affordability and technical capability of modern sensors significantly increases the feasibility of taking direct groundwater level measurements in data-scarce, arid regions on a larger scale. Here, we assess the potential of in situ monitoring to provide a localized index of hydrological drought in Somaliland. We find that calibrating a lumped groundwater model with a short time series of groundwater level observations substantially improves the quantification of local water availability when compared to satellite-based indices. By varying the calibration length, we find that a 5-week period capturing both wet and dry season conditions provides most of the calibration capacity. This suggests that short monitoring campaigns are suitable for improving estimations of local water availabilities during drought. Short calibration periods have practical advantages, as the relocation of sensors enables rapid characterization of a large number of wells. These well simulations can supplement continuous in situ monitoring of strategic point sources to setup large-scale monitoring systems with contextualized and localized information on water availability. This information can be used as early warning evidence for the financing and targeting of early actions to mitigate impacts of hydrological drought.

中文翻译：

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使用原位地下水传感器定位水文干旱预警

干旱预警系统 (DEWS) 旨在对水资源短缺风险进行空间监测和预测，从而为早期的风险缓解干预措施提供信息。然而，由于缺乏依赖地下水的干旱地区的原位监测，空间干旱暴露是使用基于卫星的指标图来推断的，例如降雨异常、土壤湿度和植被指数。在当地范围内，这些粗分辨率的代用指标对地下水可用性的推断很差。现代传感器的可负担性和技术能力的提高显着增加了在数据稀缺的干旱地区进行大规模地下水位直接测量的可行性。在这里，我们评估了现场监测的潜力，以提供索马里兰水文干旱的局部指数。我们发现，与基于卫星的指数相比，使用短时间序列的地下水水位观测来校准集总地下水模型可以显着提高当地水资源可用性的量化。通过改变校准长度，我们发现在 5 周期间同时捕捉湿季和旱季条件提供了大部分校准能力。这表明短期监测活动适用于改善对干旱期间当地水资源可用性的估计。短校准周期具有实际优势，因为传感器的重新定位可以快速表征大量油井。这些油井模拟可以补充对战略点源的连续原位监测，以建立大规模监测系统，其中包含有关水资源可用性的情境化和本地化信息。