Publications

Sep, 2026

Journal

Intercomparison of flood inundation models across land use types and hydrological flood stages

Flood Inundation Mapping (FIM) model selection is a key operational decision because accurate, rapid mapping underpins early warning and resource allocation. FIM performance is context-dependent and can vary with hydrograph phase, land-use/land-cover (LULC), and the evaluation benchmark. Intercomparison studies typically assess a single near-peak snapshot against one refer…

Sep, 2025

Journal

An Integrated Hydroclimatic Assessment of Future Reservoir and Hydropower Operations in the U.S.

The engineering of rivers by dams is a formative feature of human-nature systems and the interconnectivity of water, energy, and the climate. Sufficient and broad-based representations of dams in large-scale hydrological models prove essential to mapping their extensive regulation of river flow and biogeochemistry and gauging climate-linked provisions, including freshwater…

Aug, 2025

Journal

Comparisons of Montane Snow Water Equivalent Projections: Calculating Total Snow Mass in Regions with Projection Agreement and Divergence in the Western United States

Montane snowpack is a vital source of water in the western United States. Here, we use a large-ensemble approach to evaluate the agreement across 124 snow water equivalent (SWE) projections with statistically downscaled forcing between end-of-century (2076–95) and early twenty-first century (2106–35) periods. Comparisons were performed on dates corresponding with the end o…

Jul, 2025

Journal

Enhancing Multi-Step Reservoir Inflow Forecasting: A Time-Variant Encoder–Decoder Approach

Accurate reservoir inflow forecasting is vital for effective water resource management. Reliable forecasts enable operators to optimize storage and release strategies to meet competing sectoral demands—such as water supply, irrigation, and hydropower scheduling—while also mitigating flood and drought risks. To address this need, in this study, we propose a novel time-varia…

May, 2025

Journal

Integrated Modeling Driven Evaluation of Opportunities for Climate-Resilient Perennial Biomass Crop Plantings in Flood-Prone Agricultural Landscapes

Adapting to future climate change in flood-prone landscapes will require climate-resilient agricultural systems. Planting perennial crops, like switchgrass and willow, along river corridors can mitigate future flooding while supporting bioenergy markets. We developed an integrated assessment linking climate, hydrologic, and inundation model results to assess future flood r…

Apr, 2025

Journal

Enhancing 2D hydrodynamic flood models through machine learning and urban drainage integration

Two-dimensional hydrodynamic flood models are commonly employed for simulating flood extent and inundation depth. However, the influence of urban drainage network (UDN) is frequently overlooked in these models, potentially compromising their accuracy. Furthermore, the expensive computational costs and longer processing times make them challenging for large-scale hydrodynam…

Mar, 2025

Journal

Enhancing Streamflow Reanalysis Across the Conterminous US Leveraging Multiple Gridded Precipitation Data Sets

Streamflow observations, essential for various water resource applications, are often unavailable at critical locations in need. Although different models have been proposed to enhance streamflow predictability at ungauged locations, the challenge extends beyond model fidelity. Differences in meteorologic forcing data sets, precipitation in particular, can significantly af…

Apr, 2024

Journal

Indicators of thermal alteration in US waters reveal patterns of climate risk at the energy-water nexus

Anthropogenic changes in water temperature can pose significant risk to thermoelectric and hydroelectric generation. In this study, we developed indicators of thermal risk (ITRs) to assess risk to water-dependent electricity generating assets under future climate. We projected future changes in water temperature and quantified ITRs for plants across the conterminous US for…

Dec, 2023

ORNL Report

Performance Execution Plan 2021 ORNL/AF R&D Collaboration

Dec, 2023

Journal

Explainable machine learning model for multi-step forecasting of reservoir inflow with uncertainty quantification

We propose an explainable machine learning (ML) model with uncertainty quantification (UQ) to improve multi-step reservoir inflow forecasting. Traditional ML methods have challenges in forecasting inflows multiple days ahead, and lack explainability and UQ. To address these limitations, we introduce an encoder–decoder long short-term memory (ED-LSTM) network for multi-step…

Dec, 2023

Journal

Evaluating Enhanced Reservoir Evaporation Losses From CMIP6-Based Future Projections in the Contiguous United States

Enhanced reservoir evaporation has become an emerging concern regarding water loss, especially when compounded with the ever-increasing water demand. In this study, we evaluated the evaporation rates and losses for 678 major reservoirs (representing nearly 90% of total storage capacity) in the Contiguous United States over historical baseline (1980–2019), near-term (2020–2…

Dec, 2023

Journal

Streamflow Simulation in Data-Scarce Basins Using Bayesian and Physics-Informed Machine Learning Models

Hydrologic predictions at rural watersheds are important but also challenging due to data shortage. Long short-term memory (LSTM) networks are a promising machine learning approach and have demonstrated good performance in streamflow predictions. However, due to its data-hungry nature, most LSTM applications focus on well-monitored catchments with abundant and high-quality…