Interferometric Synthetic Aperture Radar (InSAR) time series analysis is a powerful technique to estimate long-term water level changes in wetlands ecosystems. However, few studies have applied InSAR on wetlands that are highly segmented by canals and levees due in part to the challenge of selecting qualified reference points to minimize unwrapping errors, which, by contrast, is a relatively easy task for unsegmented wetlands. Here we developed a new method to automatically select the optimal reference point for InSAR time series analysis. The method selects reference points by considering temporal behaviors of coherence and InSAR phase connectivity from each reference point to its wetland of interest. We tested the method on six managed and highly segmented wetland units within the Sacramento National Wildlife Refuge in the Central Valley, California. We validated the InSAR measurement against water depth gauge measurements during a low water depth (< 0.05) for five out of six units and similar RMSE for the remaining one. This new automatic method enables us to maximize the performance of InSAR to predict water depth and could be applied to other types of InSAR applications as well.

Extreme weather conditions are associated with a variety of water quality issues that can pose harm to humans and aquatic ecosystems. Under dry extremes, contaminants become more concentrated in streams with a greater potential for harmful algal blooms, while wet extremes can cause flooding and broadcast pollution. Developing appropriate interventions to improve water quality in a changing climate requires a better understanding of how extremes affect watershed processes, and which places are most vulnerable. We developed a Soil and Water Assessment Tool model of the Cape Fear River Basin (CFRB) in North Carolina, USA, representing contemporary land use, point and non-point sources, and weather conditions from 1979 to 2019. The CFRB is a large and complex river basin undergoing urbanization and agricultural intensification, with a history of extreme droughts and floods, making it an excellent case study. To identify intervention priorities, we developed a Water Quality Risk Index (WQRI) using the load average and load variability across normal conditions, dry extremes, and wet extremes. We found that the landscape generated the majority of contaminants, including 90.1% of sediment, 85.4% of total nitrogen, and 52.6% of total phosphorus at the City of Wilmington’s drinking water intake. Approximately 16% of the watershed contributed most of the pollutants across conditions—these represent high priority locations for interventions. The WQRI approach considering risks to water quality across different weather conditions can help identify locations where interventions are more likely to improve water quality under climate change.

Hurricanes that cause damage to lives and property are often accompanied by poor water quality that threatens the health of human communities and aquatic species. North Carolina has experienced 3 devastating 500-yr storms within 2 years; wastewater treatment plants and sanitary sewer overows occurred up to 300 km inland, as well as coal ash spills, breaches of confined animal feeding operation (CAFO) waste lagoons, and numerous fish kills. Many in-situ sensors went offline and hazardous conditions precluded field sampling during and after these events. Publicly available satellite data enables delineation of flooding over broad areas, which can aid in quantifying the extent of flood exposure and potential water quality impacts. We mapped flooding across the North Carolina Piedmont and Coastal Plain due to Hurricane Matthew (2016) and Hurricane Florence (2018) with Sentinel-1 synthetic aperture radar. We assessed how impacts were distributed across indicators of social vulnerability at the census tract level and freshwater ecological vulnerability at a watershed scale using quantile regression. Finally, we identied flood-prone infrastructure relevant to water supply and treatment, and mapped locations where nature-based solutions could be implemented to store floodwaters and process contaminants. Flooding mapped with >91% accuracy extended beyond the 500-year floodplain—furthermore, the legal floodplain systematically underestimated impacts to more vulnerable human populations and surface waters. Repeated flooding affected both point and non-point sources of nutrients, including 188 wastewater treatment plants representing >46% of treatment capacity and 77 swine CAFOs that generate ~ 478,926,961 tons of manure per year. Conservation of ~4,600 ha of currently unprotected forest and wetland, and restoration or changes in land management on ~3,100 ha represent key opportunities to protect human and natural communities under future storms. Our results suggest that current flood hazard maps are inadequate for resilience planning. Changes to design standards, land-use planning policies, and operation of infrastructure that conveys and treats water are warranted to improve floodplain resilience.