LINS Lab aims to understand the most consequential drivers and their impacts on the co-evolutionary dynamics of coupled human-water systems. These systems are confronting deeply uncertain future conditions that fundamentally shape risk-based decision making.

Understanding human behaviors and their co-evolution with natural and built environments is crucial for addressing complex global water challenges. Our work advances this understanding by integrating social and engineering perspectives to support risk-based decision-making across governance levels—from local community decision-making to regional system planning and national policy advisories. We utilize a suite of system-based approaches, including agent-based modeling, data science, artificial intelligence, optimization, and decision theory, to enhance sustainable water resources management under changing climate and environment.

We are actively recruiting!

This is a great time to join! The lab is just starting, and students can play a key role in developing new projects.
Get in touch with the PI to learn more.

Opportunities

Thermal and Salinity Management Through Reservoir Operation with Multiple Objectives

The Delaware River Basin, a key water supply for New York City, faces complex challenges balancing municipal water supply, cold-water fisheries, and salinity intrusion. We developed a modular, LSTM-augmented Pywr-DRB model to simulate water supply, stream temperature, and salt-front dynamics. Using this framework, we applied multi-objective policy search to optimize reservoir release rules, demonstrating proactive strategies for reducing thermal stress while sustaining other basin priorities.

Sustainable Groundwater Management under Crop-Hydrological-Agent Nexus

Groundwater depletion threatens water and food security worldwide. In western Kansas, the SD-6 Local Enhanced Management Area (LEMA) represents a pioneering community-driven approach where farmers collectively set and enforce conservation rules. Using an agent-based model grounded in behavioral theory, we examine how environmental heterogeneity, farmers’ risk perceptions, crop insurance, and internal variability influence the effectiveness of this policy, providing scientific insights for future policy design. We work with an interdisciplinary team of policy scientists, economists, and engineering researchers, along with local stakeholders, to integrate knowledge and achieve broader impacts.

The United States Groundwater Well Database for Risk Propagation Mapping

Groundwater wells are vital infrastructure for water supply, environmental monitoring, and economic development, yet no unified national database has existed—until now. The United States Groundwater Well Database (USGWD) compiles over 14.2 million well records (1763–2023) from state and federal agencies, standardized with attributes such as purpose, location, depth, and capacity. With rigorous cross-verification, USGWD offers an unprecedented resource for understanding how groundwater is accessed and managed across the nation. Together with other datasets on land use, canals, reservoirs, and water rights, this foundational work enables a comprehensive assessment of how water infrastructure supports national food and water security, alongside equity issues in resource accessibility.

Impacts of Cyber-Physical Risks in Smart Water Systems

The rise of smart water technologies brings efficiency and adaptability but also new cybersecurity vulnerabilities. Our research develops methods to quantify impacts under compounding natural and cyber-physical threats in water systems. For example, by analyzing how deceptive sensor data alters real-time control decisions in a smart stormwater system, we show that false data injection can significantly amplify flood risks, particularly during less severe but more frequent storms. Our approach provides critical insights for designing resilient smart water systems and can be extended to other networks, including irrigation and multi-reservoir systems, to strengthen cyber-defense planning and to support discussions of socio-technical interaction dynamics.