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A three‐stage precipitation partitioning framework is proposed to study the climate controls on mean annual groundwater evapotranspiration (GWET) for 33 gauged watersheds in west‐central Florida. Daily GWET, total evapotranspiration (ET), groundwater recharge, base flow, and total runoff are simulated by the Integrated Hydrologic Model, which dynamically couples a surface water model (HSPF) and a groundwater flow model (MODFLOW). The roles of GWET on long‐term water balance are quantified by four ratios. The ratios of GWET to total available water, watershed wetting, ET, and recharge decrease exponentially with watershed aridity index (WAI), which is defined as the ratio of potential evapotranspiration to total available water. In the one‐stage precipitation partitioning framework, the contribution of GWET to the ratio between total ET and available water for ET (i.e., they‐axis of Budyko curve) decreases with WAI. In the two‐stage precipitation partitioning framework, the contribution of GWET to the ratio between total ET and watershed wetting (i.e., Horton index) decreases with WAI. The changes in GWET caused by intra‐monthly (IM) climate variability are the highest among the temporal scales of climate variability investigated to understand controls on GWET. The inter‐annual, intra‐annual, and IM climate variabilities lead to increase of GWET; but the sub‐daily climate variability results in decrease of GWET. For the third stage of partitioning, given the same ratio of potential GWET to available water for GWET, higher percentage of forest and wetland and lower percentage of impervious land contribute to higher ratio of GWET to available water for GWET.

 

Water and power systems are increasingly interdependent due to the growing number of electricity-driven water facilities. The security of one system can be affected by a contingency in the other system. This paper investigates a security-constrained operation problem of the energy-water nexus (EWN), which is a computationally challenging optimization problem due to the nonlinearity, nonconvexity, and size. We propose a two-step iterative contingency filtering method based on the feasibility and rating of the contingencies to decrease the size of the problem. The optimal power and water flow are obtained in a normal situation by considering the set of contingencies that can not be controlled with corrective actions. The feasibility check of the contingencies is performed in the second step, followed by a rating of the uncontrollable contingencies. Finally, the critical contingencies are obtained and added to the first step for the next iteration. We also employ convex technologies to reduce the computation burden. The proposed method is validated via two case studies. Results indicate that this approach can efficiently attain optimal values.