Wetland Hydrogeomorphic Classification

What This Tool Does

Wetland Hydrogeomorphic Classification classifies wetland areas into hydrogeomorphic classes and produces confidence and polygon outputs for mapping and reporting.

Typical Questions This Tool Helps Answer

• What HGM class does each wetland unit belong to, and what ecological function and vulnerability profile does that classification imply?
• Which wetland polygons have high classification confidence versus uncertain or mixed-class assignments that warrant field verification?
• Are the mapped wetland types consistent with what is expected given the surrounding landscape geomorphology and hydrology?

When To Use

• Wetland inventory and screening
• Regional wetland function mapping
• Regulatory and planning workflows requiring class plus confidence outputs

What You Need

Key Settings

Available wetland_region values: temperate_forested, glaciated_boreal, prairie_pothole, coastal_tidal, appalachian_montane, subtropical_floodplain, none.

What You Get

The wetland polygon layer includes REGION_ID, CELL_COUNT, CLASS_CODE, CLASS_NAME, and MEAN_CONF.

Runtime Output Keys

result.outputs["hgm_class"]
result.outputs["wetland_polygons"]
result.outputs["confidence"]
result.outputs["summary"]
result.outputs["html_report"]

Common Questions

Q: Which output should I review first? A: Start with summary.class_distribution and polygon MEAN_CONF to see where class assignment is strong versus uncertain.

Q: What is a common interpretation mistake? A: Treating low-confidence class labels as definitive instead of field-check priorities.

Q: Which settings most change class results? A: The selected wetland_region pack and max_polygon_features can materially shift class balance and polygon granularity.

Q: How should wetland teams use these outputs? A: Use class and confidence together to prioritize field validation routes and regulatory documentation focus.

Results Delivery Checklist

• DEM and wetland mask dimensions were confirmed to match
• HGM class and confidence rasters were visually reviewed
• Wetland polygon attributes were spot-checked
• Summary class distribution and confidence ranges were reviewed

Purpose

Wetland Hydrogeomorphic Classification classifies wetlands by hydrologic source, outlet type, and geomorphic setting to predict ecological function and vulnerability. Outputs align with Ramsar and Cowardin wetland classification systems.

Background

Hydrogeomorphic (HGM) classification maps wetlands into functional setting classes by combining terrain position, hydrologic context, and connectivity cues. Conceptually, class assignment can be viewed as a rule-based partition over feature space:

$$c(x)=\arg\max_k;s_k(z_x)$$

Where $z_x$ is the local feature vector (relief, slope, wetness/connectivity indicators) and $s_k$ is class-specific evidence for class $k$.

Regional Calibration Rationale

HGM boundaries are physiographically dependent. Parameter packs calibrated to regional terrain-hydrology regimes reduce systematic bias that appears when one threshold set is transferred to different landscapes.

Confidence and Polygon Interpretation

Cell-level class confidence and polygon-level mean confidence should be interpreted together. Large polygons with low confidence often indicate transitional environments where field verification is required before regulatory or restoration commitments.

Methodological Considerations

• Confirm DEM conditioning quality; local relief artifacts can propagate directly into class logic.
• Use regional packs as priors, then validate against local wetland inventories where available.
• Cap polygon output volume thoughtfully so simplification does not erase operationally relevant heterogeneity.

Practical Interpretation Pitfalls

A frequent mistake is reading class codes as fixed ground truth regardless of confidence. These outputs are decision-support hypotheses that should be finalized with field evidence.

Inputs

Required runtime arguments:

• dem
• wetland_mask

Optional runtime arguments:

• max_polygon_features
• wetland_region
• output_prefix (required)

Parameters

Defaults and behavior:

• max_polygon_features defaults to 10000.
• wetland_region defaults to none and controls regional calibration thresholds.
• output_prefix is required.

Outputs

Primary runtime outputs:

• hgm_class
• wetland_polygons
• confidence
• summary
• html_report

wetland_polygons includes REGION_ID, CELL_COUNT, CLASS_CODE, CLASS_NAME, and MEAN_CONF.

Example

import whitebox_workflows as wbw

env = wbw.WbEnvironment()
env.wetland_hydrogeomorphic_classification(
	dem="dem.tif",
	wetland_mask="wetlands.tif",
	wetland_region="temperate_forested",
	max_polygon_features=10000,
	output_prefix="wetland_hgm"
)

References

• Tool implementation: wbtools_pro/src/tools/workflow_products/wetland_hydrogeomorphic_classification.rs
• Ramsar Convention and Cowardin terminology (contextual alignment)

Parameter Interaction Notes

Prioritize sensitivity checks on profile/threshold settings that materially change output distributions and decision classes.

QA and Acceptance Criteria

Minimum acceptance:

• DEM and wetland mask dimensions match exactly.
• hgm_class and confidence rasters align in grid/extent.
• summary.class_distribution and polygon confidence fields are present and interpretable.

Advanced Operational Guidance

For production use, preserve run metadata, lock approved profiles, and version output packages for reproducibility and auditability.

Implementation Patterns

Common pattern: baseline run, sensitivity run on 1-2 parameters, then locked-profile production run for delivery.

Related Tools

See upstream conditioning and downstream validation tools in the same bundle for end-to-end workflow consistency.

When To Use This Workflow

Use Wetland Hydrogeomorphic Classification when you need repeatable, source-contract-aligned outputs for planning, reporting, and stakeholder review.