The 2026 CAP Award for Water Research winners have been announced, and this week we’ll be delving into the details of the first- and- second-place winners.
The award recognizes excellence in graduate or undergraduate student research addressing water issues facing the lower Colorado River Basin states (Arizona, California, Nevada).
First, we’ll look at a summary of research produced by second-place winner, Muhammad Jawad.
Second place: AI-Augmented Catchment-Scale Hydrological Model Significantly Improves Streamflow Estimation in Arid Regions
Abstract by Jawad. Co-authors Gupta, Wang, Farmani, Behrangi, and Niu
Accurate streamflow estimation at the catchment scale remains a major challenge, particularly in arid and water-limited regions where hydrological processes are complex, nonlinear, and difficult to represent.
This study introduces a novel AI-augmented hydrological modeling framework, which combines the physical consistency of process-based modeling with the flexibility of data-driven approaches with emphasis over arid regions. The proposed multi-state model explicitly represents key hydrological processes, including canopy interception, soil moisture dynamics, snow accumulation and melt, and baseflow generation, while maintaining mass conservation through adaptive gating mechanisms.
The framework is evaluated across 15 catchments representing a range of hydroclimatic conditions and is benchmarked against simplified physical models and purely data-driven Long Short-Term Memory (LSTM) models.
Results show that the proposed framework provides robust and consistent streamflow predictions, with particularly notable improvements in arid environments. Further analysis demonstrates that explicitly representing hydrological processes and incorporating flexible formulations of evapotranspiration play important roles in improving predictive accuracy, variability, and temporal correlation.
Overall, the findings demonstrate the potential of integrating physically grounded hydrological modeling with machine learning to enhance prediction accuracy, interpretability, and generalizability, particularly in challenging water-limited environments.
About the Student
Muhammad Jawad is a Ph.D. student in Hydrology at the University of Arizona, with a minor in Machine Learning and an M.S. in Data Science. His interdisciplinary background combines hydrology, hydroinformatics, geospatial science, and artificial intelligence, with previous professional experience in water resources and GIS.
His research focuses on developing innovative, data-driven and physics-informed models to better understand and predict water resources, particularly in arid and water-stressed regions such as Arizona. His goal is to build reliable and transferable modeling tools that can support water-resource management, improve understanding of hydrologic processes, and help communities prepare for increasing water scarcity and climate variability. Through his research, he hopes to bridge advanced computational methods with real-world water challenges and contribute to more sustainable and resilient water management.
About the CAP Award for Water Research
The CAP Award for Water Research is intended to encourage and support water research by students in Arizona colleges and universities and to raise public awareness of water issues impacting central and southern Arizona and the Colorado River. Judging is conducted in a blind process by representatives of CAP’s popularly elected Board of Directors, CAP stakeholders and management, and other members of the water community. The first-place winner received $3,500 and second-place winners received $2,000. The research could drop a dent into the world of Arizona’s water supply research in the future.