A Data-Driven Framework for Equitable Implementation of Stormwater Best Management Practices in U.S. Cities

Joyceline Adom-Frimpong; Yogesh Bhatarai; Snjib Sharma; Sara Kamanmalek

Stormwater Best Management Practices (BMPs) are widely used to reduce flooding, improve water quality, and enhance urban resilience. Yet, many cities still lack clear strategies to ensure that these practices are distributed equitably. In most cases, planning decisions are made without fully integrating the social and spatial dimensions of flood risk or the data needed to evaluate who benefits from stormwater investments. This study addresses these limitations by developing a data-driven framework that combines hydrologic, geospatial, and socioeconomic datasets to assess the spatial equity of BMP placement in Washington, D.C., Chicago, and Seattle. Using multi-criteria spatial analysis and machine learning, the framework identifies mismatches between areas of high flood exposure and social vulnerability and existing BMP locations. A web-based decision-support tool was also developed to visualize these patterns, assess resilience outcomes, and help planners prioritize future BMP investments. This approach provides a transparent and data-based foundation for more equitable and effective stormwater management.

From Data to Decisions: Advancing Integrated Watershed Management Across Los Angeles County

Steve Carter; John Riverson; Benjamin Bowes

This study presents an overview of the development and application of the Watershed Management Modeling System 2.0 (WMMS2) for Los Angeles County, a state-of-the-art decision-support platform designed to address the region’s complex watershed management needs. WMMS2 integrates advanced hydrologic and water quality modeling tools, including the EPA’s LSPC and SUSTAIN models, to simulate watershed processes, pollutant transport, and the performance of stormwater best management practices (BMPs) across a model domain of 3,117 square miles. The system’s highly detailed spatial framework supports scenario analysis for water quality, water supply, and flood control, and is pre-populated with extensive local data on infrastructure and hydrology. WMMS2 has been instrumental in the development of 31 Watershed Management Programs (WMPs) and Enhanced Watershed Management Programs (EWMPs) under the Los Angeles County MS4 Permit, collectively covering almost all the major waterbodies of the total WMMS model area. These programs range from single-city plans to large, multi-jurisdictional collaborations, addressing a wide array of pollutants, TMDLs, and multi-benefit project portfolios. A key advancement in WMMS2 is its integration with downscaled regional climate data ensembles, enabling robust evaluation of future hydrologic and water quality responses under a range of climate scenarios. This capability supports the assessment of watershed resilience and the development of adaptive management strategies in the face of climate uncertainty. WWMS2 applications demonstrate a transparent, scalable analytical platform for developing management strategies, supporting adaptive management, project prioritization, and regulatory compliance. In conclusion, WMMS2 represents a significant advancement in regional watershed modeling, providing a replicable framework for integrated planning, climate adaptation, and compliance in large, urbanized watersheds.

AQUA-CLIME: A Multi-Jurisdictional Initiative for Climate-Resilient Water Quality Monitoring and Community Partnerships

Appala Raju Badireddy; Mengistu Geza Nisrani; William Capeheart; Tian Xia; Elizabeth Doran; Tara Kulkarni; Etienne Gnimpieba; Nick Klein; Alain Bomgni; Scott Kenner; David Dubois; Runwei Li; Saurabh Dhiman; Joseph Thalakkottor; Leon Walls; Bharat Jasthi; Mary Witlacil; Heidi Sieverding; Joshua Falkner; Venkataram Gadhamshetty

Climate resilience is an urgently growing concern across U.S. watersheds, particularly in regions vulnerable to droughts, flooding, and water quality degradation. National-level leads from three jurisdictions—Vermont (VT) (Lake Champlain Basin), South Dakota (SD) (White River watershed) and its tribal partners (Pineridge Reservation), and New Mexico (NM) (San Juan) are leveraging National Science Foundation support to jointly respond to these compounding threats. The central thrust of this coordinated effort is the creation of the Advancing QUAlity and CLimate-ResIlent Water Management with Community Partnerships and Enhanced Sensor Network (AQUA-CLIME) initiative. AQUA-CLIME aims to advance watershed-scale contaminant monitoring and management through a combination of cutting-edge modeling, community engagement, and sensor-integrated data systems. Designed as affordable, antifouling, readily deployable, and inexpensive microsensors, we aim to predict and manage the spatiotemporal distribution and movement of contaminants of emerging concern (CECs) across diverse watersheds under current and future climate conditions. This presentation provides two years of progress from this nationwide collaborative effort, as our three model sites capture a wide range of climate–social–ecological contexts—from regions with high precipitation and nutrient runoff to arid landscapes with limited water availability. In each of the three representative basins, extensive hydrologic and climate datasets were collected, processed, and standardized. AQUA-CLIME is building innovative tools, forging partnerships, and preparing a future workforce equipped to tackle climate challenges with science-based, locally informed solutions. Ultimately, AQUA-CLIME is laying the scientific, technological, and workforce foundations necessary to guide future national policy and ensure resilient water systems for generations to come.

The Flow Duration Curve (FDC) Hydrograph

Richard Koehler

This research demonstrates novel ways to increase the understanding of the hydrologic regime, critical when designing and monitoring environmental and restoration projects. By using informational design concepts and a geo-temporal information system (GtIS) , the following three data visualization and analysis techniques are possible.

1. The raster hydrograph. This dual time scale graph simultaneously displays daily, weekly, monthly, seasonal, annual and interannual flow patterns on a single plot, helping to identify climate change signatures. 
    
2. The enhanced flow duration curve (eFDC). The traditional FDC, the basis of TMDL monitoring efforts, has no chronological order information, limiting  the ability to identify climate change within the streamflow record. The eFDC solves this timing issue by adding a dQ/dt point cloud around the traditional FDC. This results in new ways to visualize and analyze changes in flow patterns between comparison periods or generated scenario flows.
    
3. The dQ/dt matrix. An extension of the eFDC, this matrix displays and quantifies *all* hydrologic conditions within the observed or generated flow record. Data self-sorts within the matrix, showing regions of increasing flow (dQ/dt > 0), steady flow (dQ/dt = 0), and decreasing flow (dQ/dt < 0). The number and degree of discharge conditions are detailed, allowing for a Markov chain-like approach to summarize streamflow changes.

Other benefits include more efficient, higher resolution model calibrations and sensitivity analyses, greater plot customization, and improved communication of results to a wider audience.