Bhavana Sreekumar
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Bhavana Sreekumar has a total of 7 co-authors. Here are the top co-authors by number of shared publications:
- Zhenghong Tang
Univ. of Nebraska-Lincoln
2 shared publications - Chang Li
School of Global Integrative Studies, University of Nebraska-Lincoln, Lincoln, NE 68588, USA
1 shared publication Jahangeer Jahangeer
Community and Regional Planning Program, University of Nebraska-Lincoln, Lincoln, USA
1 shared publication- Jahangeer Jahangeer
Community and Regional Planning Program, University of Nebraska-Lincoln, Lincoln, NE 68588, USA
1 shared publication - M. M. Shah Porun Rana
Community and Regional Planning Program, University of Nebraska- Lincoln, Lincoln, USA
1 shared publication - Rimsha Hasan
School of Natural Resources, University of Nebraska-Lincoln, Lincoln, NE 68588, USA
1 shared publication
Latest Publications
- Open Access
- 1 June 2026
- Published by MDPI AG in Sustainability
- Vol. 18 (11) , 5533
Mapping Inundation Dynamics and Hydrologic Ecosystem Service Indicators Across U.S. Conservation Sites Using Sentinel-2 and Machine Learning
Conserved land represents an important mechanism for protecting ecologically sensitive lands while maintaining working landscapes. Despite their significance, nationwide tools for continuous hydrological monitoring of conservation easement lands remain limited. This study conceptualizes surface-water inundation as an indicator of hydrologic connectivity and ecosystem function, reflecting how water dynamics influence the resilience and ecological performance of conservation easement landscapes. We present a scalable framework to assess inundation dynamics across more than 340,000 conservation sites between 2018 and 2024 by integrating Sentinel-2 satellite imagery, Dynamic World land-cover data, and machine-learning classifiers (Support Vector Machine, Random Forest, and CART) within the Google Earth Engine platform. Spectral water indices (NDWI, MNDWI, and NDMI) were combined with Dynamic World classifications to generate quarterly inundation maps at 10 m spatial resolution, enabling consistent detection of surface-water presence across space and time. Among the evaluated classifiers, the Support Vector Machine (SVM) model achieved the highest performance in surface-water detection. Results reveal strong regional and seasonal variability in inundation patterns across conservation land. Higher inundation frequencies were observed in the Midwest, Gulf Coast, and Pacific Northwest, where wetland-associated easements showed persistent inundation (>50%) during spring and early summer, highlighting their role in supporting biodiversity, groundwater recharge, and flood mitigation. Overlay analysis with the National Wetlands Inventory (NWI) and SSURGO hydric soils confirmed a strong spatial correspondence between inundation occurrence and wetland-prone landscapes, extending the same Sentinel-2 and machine-learning framework to conservation land and enabling the first systematic cross-program comparison of hydrological dynamics across two major U.S. conservation mechanisms. This work highlights the critical role of conservation lands including Conservation Reserve Program (CRP) areas and conservation easements in supporting inundation dynamics and hydrological connectivity. These functions are essential for sustaining wetland habitats, maintaining water quality, and enhancing flood mitigation at the national scale.
- 1 June 2026
- Published by MDPI AG in Sustainability
- Vol. 18 (11) , 5533
Open AccessMapping Inundation Dynamics and Hydrologic Ecosystem Service Indicators Across U.S. Conservation Sites Using Sentinel-2 and Machine Learning
Conserved land represents an important mechanism for protecting ecologically sensitive lands while maintaining working landscapes. Despite their significance, nationwide tools for continuous hydrological monitoring of conservation easement lands remain limited. This study conceptualizes surface-water inundation as an indicator of hydrologic connectivity and ecosystem function, reflecting how water dynamics influence the resilience and ecological performance of conservation easement landscapes. We present a scalable framework to assess inundation dynamics across more than 340,000 conservation sites between 2018 and 2024 by integrating Sentinel-2 satellite imagery, Dynamic World land-cover data, and machine-learning classifiers (Support Vector Machine, Random Forest, and CART) within the Google Earth Engine platform. Spectral water indices (NDWI, MNDWI, and NDMI) were combined with Dynamic World classifications to generate quarterly inundation maps at 10 m spatial resolution, enabling consistent detection of surface-water presence across space and time. Among the evaluated classifiers, the Support Vector Machine (SVM) model achieved the highest performance in surface-water detection. Results reveal strong regional and seasonal variability in inundation patterns across conservation land. Higher inundation frequencies were observed in the Midwest, Gulf Coast, and Pacific Northwest, where wetland-associated easements showed persistent inundation (>50%) during spring and early summer, highlighting their role in supporting biodiversity, groundwater recharge, and flood mitigation. Overlay analysis with the National Wetlands Inventory (NWI) and SSURGO hydric soils confirmed a strong spatial correspondence between inundation occurrence and wetland-prone landscapes, extending the same Sentinel-2 and machine-learning framework to conservation land and enabling the first systematic cross-program comparison of hydrological dynamics across two major U.S. conservation mechanisms. This work highlights the critical role of conservation lands including Conservation Reserve Program (CRP) areas and conservation easements in supporting inundation dynamics and hydrological connectivity. These functions are essential for sustaining wetland habitats, maintaining water quality, and enhancing flood mitigation at the national scale.
- 10 November 2025
- Published by Springer Nature in Environmental Monitoring and Assessment
- Vol. 197 (12) , 1-18
Mapping spatial dynamics of carbon storage and emissions across conservation lands in Nebraska, USA
Conservation lands play a critical role in carbon sequestration, yet spatially explicit assessments of carbon dynamics across interior U.S. freshwater ecosystems remain limited. This study addresses the gap by integrating the InVEST carbon storage and sequestration model with site-specific inundation frequency data to evaluate carbon dynamics across 48,363 conservation sites in Nebraska, USA. Results confirm substantial carbon storage within these lands. Among conservation sites, the mean carbon storage potential for Conservation Reserve Program (CRP) is 70.7 MgC/ha and Wetland Management Areas (WMA) 103.1 MgC/ha, Wetland Reserve Program (WRP) 101.9 MgC/ha, and Waterfowl Production Areas (WPA) 101.4 MgC/ha. Higher carbon densities were associated with forested wetlands, emergent herbaceous wetlands, and deciduous forests, often in areas with high (> 75%) inundation frequency. High carbon storage was concentrated primarily in WMA, WPA, and WRP conservation site types that pair land cover types (i.e., forested habitats, woody wetlands) with hydrological and management regimes. CRP sites reflect their predominance of grasslands and croplands and contribute significantly to overall conservation carbon stock. Spatial heterogeneity in carbon dynamics was closely linked to inundation frequency and land management practices. Areas with frequent inundation showed increased carbon accumulation. These conservation lands functioned as net carbon sinks due to sequestration outweighing methane and nitrous oxide emissions. These findings underscore the ecological value of Nebraska’s conservation lands and their vital role in agricultural conservation policy. Hotspot analysis identified carbon-dense areas, providing a clear view for targeted conservation and restoration on these lands.
- 10 November 2025
- Published by Springer Nature in Environmental Monitoring and Assessment
- Vol. 197 (12) , 1-18
Mapping spatial dynamics of carbon storage and emissions across conservation lands in Nebraska, USA
Conservation lands play a critical role in carbon sequestration, yet spatially explicit assessments of carbon dynamics across interior U.S. freshwater ecosystems remain limited. This study addresses the gap by integrating the InVEST carbon storage and sequestration model with site-specific inundation frequency data to evaluate carbon dynamics across 48,363 conservation sites in Nebraska, USA. Results confirm substantial carbon storage within these lands. Among conservation sites, the mean carbon storage potential for Conservation Reserve Program (CRP) is 70.7 MgC/ha and Wetland Management Areas (WMA) 103.1 MgC/ha, Wetland Reserve Program (WRP) 101.9 MgC/ha, and Waterfowl Production Areas (WPA) 101.4 MgC/ha. Higher carbon densities were associated with forested wetlands, emergent herbaceous wetlands, and deciduous forests, often in areas with high (> 75%) inundation frequency. High carbon storage was concentrated primarily in WMA, WPA, and WRP conservation site types that pair land cover types (i.e., forested habitats, woody wetlands) with hydrological and management regimes. CRP sites reflect their predominance of grasslands and croplands and contribute significantly to overall conservation carbon stock. Spatial heterogeneity in carbon dynamics was closely linked to inundation frequency and land management practices. Areas with frequent inundation showed increased carbon accumulation. These conservation lands functioned as net carbon sinks due to sequestration outweighing methane and nitrous oxide emissions. These findings underscore the ecological value of Nebraska’s conservation lands and their vital role in agricultural conservation policy. Hotspot analysis identified carbon-dense areas, providing a clear view for targeted conservation and restoration on these lands.