Optimizing wetland conservation programs requires effective mapping of watershed inundation patterns and the identification of priority areas for future conservation. This study presents a data-driven framework to analyze watershed wetness dynamics and prioritize agricultural lands for wetland conservation. It focuses on mapping areas with the most periodic inundation of agricultural lands from 2018 to 2023. A multi-criteria spatial decision support tool was developed to identify high-priority agricultural parcels for wetland conservation programs. This tool integrates inundation dynamics, soil characteristics, and restoration context to evaluate site suitability for conservation efforts. Using Google Earth Engine, Sentinel-2 imagery was analyzed to assess the frequency of periodic inundation on each pixel of agricultural land, including cropland, forestland, and hay/pasture land. This study calculates the watershed wetness index and evaluates parcel-level suitability for wetland conservation. The analysis ranks watersheds based on the proportion of inundated agricultural lands and identifies approximately 24,000 priority parcels, ranging in size from 0.4 to 20 hectares (1–50 US acres). A scenario-based cost analysis of land acquisition provides further guidance for conservation planning. Statewide agricultural-based conservation programs should prioritize potential sandhill wetlands within the wettest agricultural watersheds in the Sandhills ecoregion, high-potential playa wetlands in the Rainwater Basin area, riverine wetlands along the Missouri, Elkhorn, and Platte Rivers, and saline wetlands in the rural–urban transitional watersheds of eastern Nebraska. This study demonstrates how remote sensing and multi-criteria geospatial analysis can facilitate scalable and cost-effective wetland mapping and site selection, both in the United States and globally.
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