This study evaluates the impact of potential future climate change on flood regimes, floodplain protection, and electricity infrastructures across the Conasauga River watershed in the southeastern United States through ensemble hydrodynamic inundation modeling. The ensemble streamflow scenarios were simulated by the Distributed Hydrology Soil Vegetation Model (DHSVM) driven by (1) 1981–2012 Daymet meteorological observations and (2) 11 sets of downscaled global climate models (GCMs) during the 1966–2005 historical and 2011–2050 future periods. Surface inundation was simulated using a GPU-accelerated Two-dimensional Runoff Inundation Toolkit for Operational Needs (TRITON) hydrodynamic model. A total of 9 out of the 11 GCMs exhibit an increase in the mean ensemble flood inundation areas. Moreover, at the 1 % annual exceedance probability level, the flood inundation frequency curves indicate a ∼ 16 km² increase in floodplain area. The assessment also shows that even after flood-proofing, four of the substations could still be affected in the projected future period. The increase in floodplain area and substation vulnerability highlights the need to account for climate change in floodplain management. Overall, this study provides a proof-of-concept demonstration of how the computationally intensive hydrodynamic inundation modeling can be used to enhance flood frequency maps and vulnerability assessment under the changing climatic conditions.

In the modern world, dams and the artificial reservoirs behind them serve the increasing demand for water across diverse needs such as agriculture, energy production, and drinking water. As dams continue to proliferate, monitoring water availability influenced by reservoir operations is now of paramount importance. The Reservoir Assessment Tool (RAT) is a data-driven software platform that integrates satellite remote sensing with hydrological models, enabling the estimation of key reservoir parameters such as inflow, outflow, surface area, evaporation, and storage changes. The earliest version of RAT (version 1.0) was set up for 1598 reservoirs around the world with limitations in functional robustness, updating frequency, and scalability. Some of these limitations on updating frequency and functional robustness were addressed in version 2.0 that was later made operational for the intergovernmental agency of the Mekong River Commission. Recognizing the need for scalability to mobilize the global water management community to benefit from satellite remote sensing, we hereby introduce RAT version 3.0. This version is optimized for accelerating open collaboration among users for continuous improvement and customization of RAT to enable reservoir management breakthroughs. RAT 3.0 represents a wholesale overhaul from the previous versions to empower the global community of users and developers in the spirit of the open-source movement. RAT 3.0 allows reservoir monitoring advancements and new functional developments that can be freely exchanged and seamlessly integrated for continuous evolution of the software. A centralized web application has also been established to facilitate the storage and dissemination of global reservoir monitoring information along with comprehensive training resources. RAT 3.0 aspires to bridge the traditional practices of water management community with the capabilities of satellite remote sensing. The global impact of the software can be expected to increase as uptake spreads, enabling a more sustainable and equitable utilization of our planet's water resources.

The use of satellite‐based thermal infrared remote sensing has facilitated the assessment of surface water temperature on a large scale. However, the inherent limitations of this remote sensing technique make it difficult to assess rivers unless ambient conditions are cloud‐free, devoid of steep terrain and the rivers are at least 60 m wide. To address these challenges that limit the spatiotemporal continuity of satellite‐based hydro‐thermal data, we harnessed the extensive coverage from the Landsat missions' thermal infrared sensors and data‐driven techniques to estimate surface water temperature of rivers. Out of the tested data‐driven techniques, we selected the Random Forest Regressor as our prime non‐linear approach for estimation of surface water temperature in rivers. Using the selected technique, proposed as THORR (Thermal History of Regulated Rivers), we successfully reconstructed a multi‐decadal, continuous spatiotemporal surface water temperature record for regulated rivers in the Columbia River Basin. Using 42 years of data, the surface water temperature could be predicted on average with 0.71° C of absolute error regardless of the dam's potential thermal influence in the downstream reaches. The reconstructed hydro‐thermal behavior generated from THORR revealed a long‐term downstream warming trend along the Columbia River. The open‐source THORR tool can be extended to any river system around the world that is not gauged with in‐situ temperature measurements for the reconstruction of hydro‐thermal behavior.

The prevalence of unforeseen floods has heightened the need for more accurate flood simulation and forecasting models. Even though forecast stations are expanding across the United States, the coverage is usually limited to major rivers and urban areas. Most rural and sub-urban areas, including recreational areas such as the Window Cliffs State Natural Area, do not have such forecast stations and as such, are prone to the dire effects of unforeseen flooding. In this study, four machine learning model architectures were developed based on the long short-term memory, random forest, and support vector regression techniques to forecast water depths at the Window Cliffs State Natural Area, located within the Cane Creek watershed in Putnam County, Tennessee. Historic upstream and downstream water levels and absolute pressure were used to forecast the future water levels downstream of the Cane Creek watershed. The models were tested with lead times of 3, 4, 5, and 6 h, revealing that the model performances reduced with an increase in lead time. Even though the models yielded low errors of 0.063–0.368 ft MAE, there was an apparent delay in predicting the peak water depths. However, including rainfall data in the forecast showed a promising improvement in the models’ performance. Tests conducted on the Cumberland River in Tennessee showed a promising improvement in model performance when trained with larger data.

The thermal condition of riverine ecosystems significantly influences fish survival and migration. Understanding the spatial relationship between water temperature and fish abundance requires a comprehensive spatiotemporal overview of river temperature. In this study, we used multi-decadal spatiotemporal river temperature estimates from the Thermal History of Regulated Rivers (THORR) tool to explore the relationship between water temperature, fish abundance, and migration patterns. We demonstrated the potential of such a tool and the corresponding analyses to inform and improve reservoir management for fish abundance. Our assessment, based on the mass balance concept, considered the influx and efflux of migratory fish during the fall season in the Hanford Reach along the Columbia River to determine fish retention. We found that the proportion of fish leaving the reach increases with rising water temperatures. Although fish appear to travel faster at higher temperatures according to THORR-based analyses, discharge- focused dam operations upstream did not result in downstream cooling, thus failing to improve thermal conditions for fish in the downstream reach. A long-term multi-decadal trend showed a significant increase in fall water temperatures beyond stressful levels over the past decade. These findings underscore the critical need for balanced dam operations that consider both discharge and temperature requirements to ensure optimal conditions for fish survival and migration. The insights provided by the THORR tool not only enhance our understanding of riverine thermal dynamics but also offer a valuable resource for developing sustainable water management practices in regulated rivers where fish passage is critical. By leveraging THORR's capabilities, we can better plan ways to protect aquatic ecosystems, support biodiversity, and promote the resilience of fish populations amidst climate change impacts.