Hydrological Modelling with GIS Training Course

Participants can organise spatial and time-series datasets for reproducible hydrological analysis.

• Coordinate reference systems selected for watershed area and distance accuracy
• Raster cell size assessed against DEM quality and drainage density
• Geodatabase schemas designed for gauges, reaches, catchments, and structures
• Metadata records capture source, date, datum, units, and processing history
• Hydrography datasets reconciled through topology checks and attribute crosswalks
• Quality-control logs distinguish observed, derived, estimated, and missing values

Participants can assess and prepare elevation data for terrain-based hydrological analysis.

• Digital elevation model artefacts identified from sinks, spikes, terraces, and voids
• Vertical datum consistency checked before terrain derivatives and flood calculations
• Raster mosaics, clipping, resampling, and reprojection preserve elevation meaning
• LiDAR-derived bare-earth DEMs contrasted with photogrammetric surface models
• Terrain preprocessing choices recorded for reproducible watershed delineation
• DEM uncertainty linked to channel location and contributing-area errors

Participants can derive catchment boundaries, subbasins and stream networks from terrain data.

• Fill, breach, and carve conditioning methods compared for drainage enforcement
• Flow direction generated using D8 and multiple-flow-direction algorithms
• Flow accumulation thresholds tested against mapped channel heads
• Pour points snapped to high-accumulation cells using drainage evidence
• Watershed and subbasin boundaries delineated from conditioned elevation rasters
• Stream order assigned with Strahler rules for network characterisation

Participants can derive spatial runoff and infiltration parameters from land-cover and soil data.

• Curve Number runoff potential derived from land cover and hydrologic soils
• Land-cover reclassification aligns satellite classes with hydrologic parameter categories
• Soil texture, depth, and drainage attributes prepared for infiltration estimates
• Zonal statistics summarise slope, imperviousness, and soil proportions by subbasin
• Area-weighted parameters calculated with raster and polygon overlay methods
• Parameter tables trace each value to source datasets and assumptions

Participants can prepare observed rainfall and construct design-storm inputs for modelling.

• Gauge rainfall series screened for gaps, duplicates, unit errors, and outliers
• Thiessen polygons and inverse-distance weighting estimate areal precipitation
• IDF curves converted into design storms with selected return periods
• Hyetographs constructed using SCS Type distributions and local storm patterns
• Radar and satellite precipitation bias-checked against ground gauges
• Temporal aggregation matched to catchment response time and model timestep

Participants can prepare streamflow observations and identify hydrograph features for model evaluation.

• Stage-discharge rating curves interpreted with control shifts and extrapolation limits
• Baseflow separation performed using digital filters and recession analysis
• Observed hydrographs partitioned into peak, volume, timing, and recession metrics
• Missing streamflow periods flagged before calibration and validation selection
• Unit conversions reconcile rainfall, discharge, area, and storage volumes
• Event selection considers antecedent moisture, seasonality, and data completeness

Participants can configure a GIS-supported HEC-HMS basin model and simulation controls.

• HEC-HMS basin models assembled from subbasins, reaches, junctions, and outlets
• Loss, transform, baseflow, and routing methods selected by available evidence
• Control specifications set simulation dates, timestep, and warm-up period
• Meteorologic models connect gauge weights, design storms, and gridded rainfall
• Paired GIS attributes populate model elements through documented parameter tables
• Model naming conventions preserve scenario lineage and revision control

Participants can select and parameterise loss methods appropriate to available catchment evidence.

• SCS Curve Number losses parameterised from antecedent moisture and land cover
• Green-Ampt infiltration configured using hydraulic conductivity and soil suction
• Initial abstraction ratios tested against observed runoff onset
• Deficit-and-constant losses applied to continuous rainfall-runoff simulations
• Impervious area treatment separates directly connected and disconnected surfaces
• Loss parameter sensitivity assessed using runoff volume and onset timing

Participants can model runoff transformation and channel routing using documented method choices.

• SCS unit hydrograph lag estimated from catchment length and slope
• Clark unit hydrograph separates translation and attenuation effects
• Muskingum routing parameters relate reach storage to observed hydrograph shape
• Kinematic-wave routing selected where channel geometry and slopes support assumptions
• Time of concentration calculated using documented flow-path components
• Routing timestep checked against Courant considerations and hydrograph stability

Participants can calibrate, validate and diagnose a hydrological model against observed flows.

• Calibration periods selected to represent wet, dry, and seasonal conditions
• Objective functions calculated using NSE, RMSE, bias, and peak error
• Parameter changes prioritised through sensitivity ranking and process plausibility
• Split-sample validation tests transferability beyond the calibration record
• Hydrograph comparisons diagnose timing, volume, peak, and recession mismatch
• Calibration logs record parameter ranges, rationale, iterations, and results

Participants can assess uncertainty and state defensible limits on model use.

• Equifinality recognised when parameter sets produce similarly acceptable hydrographs
• Data, parameter, and structural uncertainty separated in model reporting
• Scenario ensembles bracket rainfall, land-cover, and parameter uncertainty
• Confidence statements distinguish model evidence from untested assumptions
• Acceptance criteria set before scenario comparison and decision use
• Reproducible folders retain inputs, scripts, outputs, and model versions

Participants can connect hydrological outputs to hydraulic analysis and mapped flood hazards.

• Design discharges generated for specified annual exceedance probability events
• HEC-RAS geometry imported from GIS centerlines, banks, cross sections, terrain
• Steady and unsteady flow choices matched to study objectives
• Boundary conditions specified from hydrographs, rating curves, or normal depth
• Flood extent rasters created from water-surface elevations and terrain
• Depth, velocity, and hazard maps classified using stated thresholds

Participants can assess development runoff and test stormwater mitigation measures.

• Existing and proposed imperviousness compared through parcel-scale land-cover scenarios
• Detention storage tested for peak attenuation and outlet performance
• Green infrastructure represented through changed losses, storage, and connectivity
• Drainage networks checked for culvert constraints and flow-path discontinuities
• Post-development runoff assessed against pre-development event hydrographs
• Mitigation alternatives ranked using volume, peak, cost, and maintainability

Participants can build continuous simulations and interpret seasonal catchment water balances.

• Continuous simulations combine precipitation, evapotranspiration, losses, and baseflow
• Potential evapotranspiration methods selected from available meteorological observations
• Seasonal soil-moisture accounting explains dry-period runoff response
• Water-balance closure checks precipitation, runoff, storage change, and losses
• Long-record simulations identify annual variability and drought sequences
• Climate perturbation scenarios apply documented rainfall and temperature adjustments

Participants can assess remote-sensing products as inputs for land-cover and flood analysis.

• Sentinel-2 indices classify vegetation cover and seasonal land-surface change
• Sentinel-1 backscatter supports flood extent mapping beneath cloud cover
• Supervised classification accuracy assessed using confusion matrices and reference samples
• Change detection isolates new impervious surfaces and channel migration
• Satellite products validated against field observations and higher-resolution imagery
• Remote-sensing uncertainty propagated into land-cover parameter assignments

Participants can structure comparable hydrological scenarios for planning and investment decisions.

• Baseline models frozen before alternatives to preserve comparison integrity
• Land-use, climate, and infrastructure scenarios defined with explicit assumptions
• Scenario matrices connect drivers, parameter changes, outputs, and decisions
• Return-period and climate stress tests expose design sensitivity
• Benefit measures compare peak reduction, inundation area, and storage needs
• Trade-offs documented between flood protection, cost, ecology, and land use

Participants can communicate hydrological methods, results and limitations to technical and non-technical audiences.

• Map layouts communicate catchment context, inputs, outputs, scale, and uncertainty
• Hydrographs annotated with observed data, scenarios, peaks, and performance statistics
• Technical reports separate methods, assumptions, results, limitations, and recommendations
• Data lineage tables link mapped outputs to source files and transformations
• Decision briefings translate probability, uncertainty, and residual risk clearly
• Peer review checklists test reproducibility, cartography, calculations, and claims

Participants can establish quality controls, audit trails and maintenance arrangements for hydrological models.

• Model files structured with controlled naming, versioning, and access permissions
• QA/QC checklists verify units, projections, topology, parameters, and outputs
• Model audit trails record reviewer comments, approvals, and corrective actions
• Data licences and source restrictions documented before external distribution
• Fit-for-purpose criteria distinguish screening studies from design-grade analyses
• Maintenance plans specify update triggers, responsibilities, data, and review intervals

Participants can build, review and present a complete GIS-based hydrological model for a defined catchment scenario.

• Project brief defines decision question, catchment boundary, criteria, and stakeholders
• GIS workspace assembles terrain, hydrography, rainfall, soils, and land-cover inputs
• Watershed delineation and parameterisation produce a traceable basin model
• Calibration evidence and uncertainty statements support defensible scenario assumptions
• Scenario outputs map hydrographs, inundation indicators, and intervention effects
• Peer review tests methods, results, limitations, and recommendations before presentation