A conjunctive management model has been developed to obtain optimal allocation of surface water and groundwater under different constraints during a drought. Two simulation models—a fully distributed hydrologic model and a reservoir simulation model—were incorporated in an optimization formulation using a simulation-optimization approach with response functions. The model was tested for the Haw River Basin located in North Carolina. A fully distributed hydrologic model, penn state integrated hydrologic model (PIHM), was used to compute simultaneous depletions in streamflow and groundwater level under pumping. A reservoir simulation model was then incorporated within the optimization framework to determine the optimal allocation of surface water and groundwater resources by minimizing reservoir deficit. A new groundwater sustainability constraint, recovery time for groundwater levels, was introduced in the conjunctive management model. Incorporating the reservoir simulation model within the optimization model resulted in reduced reservoir deficits. Moreover, the recovery time constraint will allow decision makers to evaluate the trade-off between maximizing water availability and preserving groundwater sustainability during a drought. It is envisioned that the management model proposed in this study is a step toward sustainable groundwater withdrawal during a drought.

Uncertainties in projecting the changes in hydroclimatic variables (i.e., temperature and precipitation) under climate change partly arises from the inability of global circulation models (GCMs) in explaining the observed changes in hydrologic variables. Apart from the unexplained changes by GCMs, the process of customizing GCM projections to watershed scale through a model chain—spatial downscaling, temporal disaggregation, and hydrologic model—also introduces errors, thereby limiting the ability to explain the observed changes in hydrologic variability. Toward this, we first propose metrics for quantifying the errors arising from different steps in the model chain in explaining the observed changes in hydrologic variables (streamflow and groundwater). The proposed metrics are then evaluated using a detailed retrospective analyses in projecting the changes in streamflow and groundwater attributes in four target basins that span across a diverse hydroclimatic regimes over the U.S. Sunbelt. Our analyses focused on quantifying the dominant sources of errors in projecting the changes in eight hydrologic variables—mean and variability of seasonal streamflow, mean and variability of 3 day peak seasonal streamflow, mean and variability of 7 day low seasonal streamflow, and mean and standard deviation of groundwater depth—over four target basins using an Penn state Integrated Hydrologic Model (PIHM) between the period 1956–1980 and 1981–2005. Retrospective analyses show that small/humid (large/arid) basins show increased (reduced) uncertainty in projecting the changes in hydrologic attributes. Further, changes in error due to GCMs primarily account for the unexplained changes in mean and variability of seasonal streamflow. On the other hand, the changes in error due to temporal disaggregation and hydrologic model account for the inability to explain the observed changes in mean and variability of seasonal extremes. Thus, the proposed metrics provide insights on how the error in explaining the observed changes being propagated through the model under different hydroclimatic regimes.

Recent U.S. Geological Survey water‐use report suggests that increasing water‐use efficiency could mitigate the supply‐and‐demand imbalance arising from changing climate and growing population. However, this rich data have neither analyzed to understand the underlying patterns, nor have been investigated to identify the factors contributing to this increased efficiency. A national‐scale synthesis of public supply withdrawals (“withdrawals”) reveals a strong North–south gradient in public supply water use with the increasing population in the South contributing to increased withdrawal. Contrastingly, a reverse South–north gradient exists in per capita withdrawals (“efficiency”), with northern states consistently improving the efficiency, while the southern states' efficiency declined. Our analyses of spatial patterns of per capita withdrawals further demonstrate that urban counties exhibit improved efficiency over rural counties. Improved efficiency is also demonstrated over high‐income and well‐educated counties. Given the potential implications of the findings in developing long‐term water conservation measures (i.e., increasing block rates), we argue the need for frequent updates, perhaps monthly to annual, of water‐use data for identifying effective strategies that control the water‐use efficiency in various geographic settings under a changing climate.