SWAT & MSPA Climate Aridity Analysis
Budget: $30 – $250 USD
The catchment has already been delineated and basic input layers are in place; what remains is a robust, climate-change–oriented workflow that links SWAT hydrological modelling with Morphological Spatial Pattern Analysis (MSPA) and patch-cohesion metrics inside ArcGIS.
Objective
Quantify how increasing aridity affects the basin by tracking three interconnected signals—precipitation patterns, soil-moisture dynamics, and evapotranspiration rates—and relate those signals to landscape structure.
Scope of work
• Calibrate and validate a SWAT model, then generate scenario runs that reflect projected climate data.
• Export key outputs (runoff, ET, soil water) to ArcGIS so they integrate cleanly with MSPA.
• Perform MSPA to map core, edge, bridge, and loop elements, followed by patch-cohesion analysis that highlights habitat connectivity shifts under each climate scenario.
• Summarise findings in maps, tables, and a concise technical note explaining method, parameters, and implications for water-scarce planning.
Acceptance criteria
• Nash–Sutcliffe efficiency ≥ 0.6 for calibration and validation periods.
• MSPA classes and cohesion indices reproducible from the delivered MXD/LYRX files.
• All geodatabases, SWAT project folders, Python/ModelBuilder scripts, and a brief “run sheet” included to guarantee full replicability.
Core tools expected: ArcGIS Pro (or ArcMap if necessary), SWAT+, MSPA plugin, and standard climate-data processors (e.g., SWAT Weather Generator, ArcPy).
With everything packaged clearly, the outputs can feed straight into ongoing climate-resilience studies without extra adjustment.
Objective
Quantify how increasing aridity affects the basin by tracking three interconnected signals—precipitation patterns, soil-moisture dynamics, and evapotranspiration rates—and relate those signals to landscape structure.
Scope of work
• Calibrate and validate a SWAT model, then generate scenario runs that reflect projected climate data.
• Export key outputs (runoff, ET, soil water) to ArcGIS so they integrate cleanly with MSPA.
• Perform MSPA to map core, edge, bridge, and loop elements, followed by patch-cohesion analysis that highlights habitat connectivity shifts under each climate scenario.
• Summarise findings in maps, tables, and a concise technical note explaining method, parameters, and implications for water-scarce planning.
Acceptance criteria
• Nash–Sutcliffe efficiency ≥ 0.6 for calibration and validation periods.
• MSPA classes and cohesion indices reproducible from the delivered MXD/LYRX files.
• All geodatabases, SWAT project folders, Python/ModelBuilder scripts, and a brief “run sheet” included to guarantee full replicability.
Core tools expected: ArcGIS Pro (or ArcMap if necessary), SWAT+, MSPA plugin, and standard climate-data processors (e.g., SWAT Weather Generator, ArcPy).
With everything packaged clearly, the outputs can feed straight into ongoing climate-resilience studies without extra adjustment.