Investigating the impacts of climate change on hydroclimatic extremes in the Tar-Pamlico River basin, North Carolina.

Evaluating the forthcoming impacts of climate change is important for formulating efficient and flexible approaches to water resource management. General Circulation Models (GCMs) are primary tools that enable scientists to study both past and potential future climate changes, as well as their impacts on policies and actions. In this work, we quantify the future projected impacts of hydroclimatic extremes on the coastal, risk-prone Tar-Pamlico River basin in North Carolina using GCMs from the Sixth International Coupled Model Intercomparison Project (CMIP6). These models incorporate projected future societal development scenarios (Shared Socioeconomic Pathways, SSPs) as defined in the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6). Specifically, we have utilized historical residential expansion data, the Soil and Water Assessment Tool Plus (SWAT+), the Standardized Precipitation Index (SPI), and the Interquartile Range (IQR) method for analyzing extremes from 2024 to 2100. Our findings include: (1) a trend toward wetter conditions is identified with an increase in flood events toward 2100; (2) projected increases in the severity of flood peaks are found, quantified by a rise of 21% compared to the 2000-2020 period; (3) downstream regions are forecast to experience severe droughts up to 2044; and (4) low-lying and coastal regions are found as particularly susceptible to higher flood peaks and more frequent drought events between 2045 and 2100. This work provides valuable insights into the anticipated shifts in natural disaster patterns and supports decision-makers and authorities in promoting adaptive strategies and sustainable policies to address challenges posed by future climate changes in the Tar-Pamlico region and throughout the state of North Carolina, United States.

Streamflow Prediction in Highly Regulated, Transboundary Watersheds Using Multi-Basin Modeling and Remote Sensing Imagery.

Despite the potential of remote sensing for monitoring reservoir operation, few studies have investigated the extent to which reservoir releases can be inferred across different spatial and temporal scales. Through evaluating 21 reservoirs in the highly regulated Greater Mekong region, remote sensing imagery was found to be useful in estimating daily storage volumes for within-year and over-year reservoirs (correlation coefficients [CC] ≥ 0.9, normalized root mean squared error [NRMSE] ≤ 31%), but not for run-of-river reservoirs (CC < 0.4, 40% ≤ NRMSE ≤ 270%). Given a large gap in the number of reservoirs between global and local databases, the proposed framework can improve representation of existing reservoirs in the global reservoir database and thus human impacts in hydrological models. Adopting an Integrated Reservoir Operation Scheme within a multi-basin model was found to overcome the limitations of remote sensing and improve streamflow prediction at ungauged cascade reservoir systems where previous modeling approaches were unsuccessful. As a result, daily regulated streamflow was predicted competently across all types of reservoirs (median values of CC = 0.65, NRMSE = 8%, and Kling-Gupta efficiency [KGE] = 0.55) and downstream hydrological stations (median values of CC = 0.94, NRMSE = 8%, and KGE = 0.81). The findings are valuable for helping to understand the impacts of reservoirs and dams on streamflow and for developing more useful adaptation measures to extreme events in data sparse river basins.