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With likely increases in probable maximum precipitation (PMP) in a changing environment, critical infrastructures such as major reservoirs and nuclear power plants are subject to elevated risk. To understand how factors such as PMP variability, climate change, land use land cover (LULC) change, antecedent soil moisture conditions, and reservoir storage may individually or jointly affect the magnitude of probable maximum flood (PMF), we conducted integrated hydrometeorological simulations involving both the Weather Research Forecasting model and the distributed hydrologic model (DHSVM) over the Alabama‐Coosa‐Tallapoosa (ACT) River Basin in the southeastern United States. A total of 120 relative humidity‐maximized PMP storms under historic and projected future climate conditions were used to drive DHSVM in current and projected future LULC conditions. Overall, PMP and PMF are projected to increase significantly over the ACT River Basin. Sources of meteorological forcing data sets and climate change were found to be the most sensitive factors affecting PMF, followed by antecedent soil moisture, reservoir storage, and then LULC change. The ensemble of PMP and PMF simulations, along with their sensitivity, allows us to better quantify the potential risks associated with hydroclimatic extreme events to critical infrastructures for energy‐water security. A significant increase in PMF is projected in a changing environmentPMF is most sensitive to sources of meteorological forcings, followed by antecedent soil moisture, reservoir storage, and LULC changeThe ensemble‐based approach can help us better estimate the risk and uncertainty associated with PMF

Probable maximum precipitation (PMP), defined as the largest rainfall depth that could physically occur under a series of adverse atmospheric conditions, has been an important design criterion for critical infrastructures such as dams and nuclear power plants. To understand how PMP may respond to projected future climate forcings, we used a physics-based numerical weather simulation model to estimate PMP across various durations and areas over the Alabama-Coosa-Tallapoosa (ACT) River Basin in the southeastern United States. Six sets of Weather Research and Forecasting (WRF) model experiments driven by both reanalysis and global climate model projections, with a total of 120 storms, were conducted. The depth-area-duration relationship was derived for each set of WRF simulations and compared with the conventional PMP estimates. Our results showed that PMP driven by projected future climate forcings is higher than 1981–2010 baseline values by around 20% in the 2021–2050 near-future and 44% in the 2071–2100 far-future periods. The additional sensitivity simulations of background air temperature warming also showed an enhancement of PMP, suggesting that atmospheric warming could be one important factor controlling the increase in PMP. In light of the projected increase in precipitation extremes under a warming environment, the reasonableness and role of PMP deserve more in-depth examination. Numerical model is able to provide PMP estimates that are comparable to those from a conventional HMR approachThe increase of precipitable water versus the increase of PMP depth exhibits a large spread and does not fall near the 1:1 lineAn increase in the deterministic PMP storm upper bound in a warming environment is projected through two different modeling approaches

In many partially glacierized watersheds glacier recession driven by a warming climate could lead to complex patterns of streamflow response over time, often marked with rapid increases followed by sharp declines, depending on initial glacier ice cover and rate of climate change. Capturing such “phases” of hydrologic response is critical in regions where communities rely on glacier meltwater, particularly during low flows. In this paper, we investigate glacio‐hydrologic response in the headwaters of the Zongo River, Bolivia, under climate change using a distributed glacio‐hydrological model over the period of 1987–2100. Model predictions are evaluated through comparisons with satellite‐derived glacier extent estimates, glacier surface velocity, in situ glacier mass balance, surface energy flux, and stream discharge measurements. Historically (1987–2010) modeled glacier melt accounts for 27% of annual runoff, and 61% of dry season (JJA) runoff on average. During this period the relative glacier cover was observed to decline from 35 to 21% of the watershed. In the future, annual and dry season discharge is projected to decrease by 4% and 27% by midcentury and 25% and 57% by the end of the century, respectively, following the loss of 81% of the ice in the watershed. Modeled runoff patterns evolve through the interplay of positive and negative trends in glacier melt and increased evapotranspiration as the climate warms. Sensitivity analyses demonstrate that the selection of model surface energy balance parameters greatly influences the trajectory of hydrological change projected during the first half of the 21st century. These model results underscore the importance of coupled glacio‐hydrology modeling. Representation ice flow is critical to depict phased hydrologic response to glacier recessionPredictions of glacier and runoff patterns are highly sensitive to the selection of energy balance parametersIncreased evapotranspiration is critical to consider in long‐term projections of water availability