Multi-Criteria Prioritization of Watersheds for Post-Fire Restoration Using GIS Tools and Google Earth Engine: A Case Study from the Department of Santa Cruz, Bolivia
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Area
2.2. MCA Methodology and Datasets
2.2.1. Selection and Analysis of the Santa Cruz Watersheds
2.2.2. Analytical and Participatory Framework
2.2.3. Prioritization Objectives
2.2.4. Variable Selection
- 1.
- Water Resources Conservation
- 2.
- Biophysical Characteristics
- 3.
- Managed and Protected Areas
- 4.
- Human Activity Threats
- 5.
- Vulnerability to Wildfire Hazards
2.2.5. Variable Scores
2.2.6. Aggregation to Microwatersheds and Macrowatersheds
3. Results
3.1. Watersheds Impacted by Wildfires
3.2. Priority Watersheds in Santa Cruz
3.3. Importance of Water Resources
3.4. Impacts of the Analysis Unit
3.5. Online Application
4. Discussion
4.1. Addressing a Need for Integrative Restoration Methodologies
4.2. The Participatory MCA Methodology
4.3. GEE as an Effective Result-Viewing Platform
4.4. Considerations for Future Restoration Studies
5. Conclusions
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Layer Used in the MCA | Input Dataset | Processing Tool in ArcMap | Input Source | Source Link or Reference |
---|---|---|---|---|
Macrowatersheds | Gobierno Autónomo Departamental de Santa Cruz’s (GADSC) macrowatersheds | Spatial selection and intersection with the Fire occurrence layer | GADSC | [35] |
Microwatersheds | HydroSHEDS product, level 12 | Spatial selection and intersection with the Fire occurrence layer | World Wide Fund (WWF) | https://www.worldwildlife.org/pages/hydrosheds (accessed on 12 April 2022) |
Proximity to surface water | 2021 Landsat-based vegetation cover and deforestation product. | Extracting the water class, Euclidean distance | Landsat; Fundación para la Conservación del Bosque Chiquitano (FCBC) | [38] |
Well density | Well site coordinates (points) | Kernel Density tool | GADSC, local water cooperatives, municipalities | |
Precipitation | Average precipitation for 1970–2000, WorldClim version 2.1 | Re-scaling to the department level | WorldClim | https://www.worldclim.org (accessed on 10 April 2022) |
Land cover | Land cover map | Reclassification into five land cover classes | FCBC | |
Elevation | Aster Global Digital Elevation Map (GDEM) version 2 sensor scenes | Mosaic to New Raster tool | National Aeronautics and Space Administration (NASA)/Japan Space Systems | https://ssl.jspacesystems.or.jp/ersdac/GDEM/E/4.html (accessed on 11 March 2023) |
Slope | Aster GDEM version 2 sensor scenes | Slope tool | NASA/Japan Space Systems | https://ssl.jspacesystems.or.jp/ersdac/GDEM/E/4.html (accessed on 11 March 2023) |
Protected areas | Maps of national, regional and municipal protected areas | Raster conversion and reclassification | GADSC | |
Land ownership | Landowner mapping | Raster conversion and reclassification | National Institute of Agrarian Reform (INRA) | |
Proximity to roads and infrastructure | Digitized roads | Euclidean distance tool | FCBC | |
Population density | 2012 population census | Kernel Density tool | National Statistics Institute (INE) | http://geo.gob.bo/portal (accessed on 23 March 2023) |
Fire occurrence | 4 fire scar maps: 2019, 2020, 2021, 2022 | Cell statistics tool | FCBC | |
Fire intensity | Fire Radiative Power, MODIS Collection 6.1 product | Interpolation using the Inverse Distance Weighted (IDW) technique [30] | NASA’s Fire Information for Resource Management System (FIRMS) | https://firms.modaps.eosdis.nasa.gov (accessed on 12 April 2022) |
Category | Variables/Importance | 1-Very low | 2-Low | 3-Medium | 4-High | 5-Very high |
---|---|---|---|---|---|---|
Water resources | Distance to rivers/water bodies (m) | >10,000 | 5000–10000 | 2000–5000 | 1000–2000 | <1000 |
Density of water wells (km2) | <0.01 | 0.01–0.02 | 0.02–0.05 | 0.05–0.07 | >0.07 | |
Precipitation (mm) | <500 | 500–1000 | 1000–1500 | 1500–2000 | >2000 | |
Ecosystems and biophysical criteria | Elevation (m a.s.l.) | <100 | 100–250 | 250–500 | 500–1000 | >1000 |
Slope (°) | <30 | 30–40 | 40–50 | 50–60 | >60 | |
Land cover type | Non-vegetated area | Other non-forest natural formation | Wetland | Forest | Flooded forest | |
Land governance | Protected areas (national, regional or municipal) | No protected area | N/A | N/A | N/A | Protected |
Land ownership | Urban | Small to large private property | Community-owned | Indigenous territories | State-owned | |
Human activities | Distance to productive areas, roads, population centers (m) | >2000 | 1500–2000 | 1000–1500 | 500–1000 | <500 |
Population density (inhabitants/km2) | <10 | 10–20 | 20–40 | 40–1000 | >1000 | |
Fire threat | Recurrence of fires between 2019–2022 (4 years) | 0 | 1 | 2 | 3 | 4 |
Intensity of fire (MW) | 0 | 1–250 | 250–500 | 500–1000 | >1000 |
Scheme 1 | W1 | W2 | W3 | W4 | W5 |
---|---|---|---|---|---|
A—water | 1 | 0 | 0 | 0 | 0 |
B—ecosystems | 0 | 1 | 0 | 0 | 0 |
C—management | 0 | 0 | 1 | 0 | 0 |
D—human activities | 0 | 0 | 0 | 1 | 0 |
E—natural hazards | 0 | 0 | 0 | 0 | 1 |
F—all combined | 1 | 1 | 1 | 1 | 1 |
G—water + ecosystems | 1 | 1 | 0 | 0 | 0 |
H—water + ecosystems + management | 1 | 1 | 1 | 0 | 0 |
I—human impacts + fire | 0 | 0 | 0 | 1 | 1 |
J—water + human impacts | 1 | 0 | 0 | 1 | 0 |
K—water + fire | 1 | 0 | 0 | 0 | 1 |
L—ecosystems + fire | 0 | 1 | 0 | 0 | 1 |
Scheme 2 | High-Priority Area (km2) | Priority Watersheds (Count) |
---|---|---|
A—water | 16,061 | 80 |
B—ecosystems | 34,322 | 156 |
C—management | 102,756 | 457 |
D—human activities | 82,145 | 310 |
E—natural hazards | 16,140 | 99 |
F—all combined | 19,905 | 88 |
Scenarios | High-Priority Area (km2) | Priority Watersheds (Count) | Priority Macrowatersheds (Names) |
---|---|---|---|
A—water | 54,911 | 3 | Pirai, Rio Grande, Itenez Sur |
B—ecosystems | 82,389 | 5 | Itenez Norte, Yapacani, Ichilo, Cuevo, Parapeti |
C—management | 137,698 | 6 | Itenez Norte, San Miguel, Paragua, Curichi Grande, Tucabaca, Cuevo |
D—human activities | 121,136 | 5 | Pirai, Yapacani, Rio Grande, San Julian, Ichilo |
E—natural hazards | 120,193 | 5 | Paragua, Itenez Sur, Curichi Grande, San Miguel, Tucabaca |
F—all combined | 84,366 | 5 | Rio Grande, San Miguel, Pirai, Yapacani, Ichilo |
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Fernandez, J.; Maillard, O.; Uyuni, G.; Guzmán-Rojo, M.; Escobar, M. Multi-Criteria Prioritization of Watersheds for Post-Fire Restoration Using GIS Tools and Google Earth Engine: A Case Study from the Department of Santa Cruz, Bolivia. Water 2023, 15, 3545. https://doi.org/10.3390/w15203545
Fernandez J, Maillard O, Uyuni G, Guzmán-Rojo M, Escobar M. Multi-Criteria Prioritization of Watersheds for Post-Fire Restoration Using GIS Tools and Google Earth Engine: A Case Study from the Department of Santa Cruz, Bolivia. Water. 2023; 15(20):3545. https://doi.org/10.3390/w15203545
Chicago/Turabian StyleFernandez, Jeanne, Oswaldo Maillard, Gerson Uyuni, Mónica Guzmán-Rojo, and Marisa Escobar. 2023. "Multi-Criteria Prioritization of Watersheds for Post-Fire Restoration Using GIS Tools and Google Earth Engine: A Case Study from the Department of Santa Cruz, Bolivia" Water 15, no. 20: 3545. https://doi.org/10.3390/w15203545