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Soil Properties

Soil data defines the hydraulic response of the land surface and controls the rate at which water infiltrates into the subsurface in HydroPol2D.

Within the current formulation of the model, soil properties are used primarily to estimate infiltration capacity and near-surface storage behavior, rather than to explicitly resolve deep vertical flow.

Role in HydroPol2D​

The soil input is used to represent:

  • Infiltration capacity at the surface
  • Near-surface soil water storage
  • Effective hydraulic conductivity
  • Initial soil moisture conditions (when not provided as a spatial field)

These properties directly influence the generation of runoff and the timing of the hydrological response.

Soil Representation​

HydroPol2D requires a categorical soil map.

Each grid cell must be assigned a soil class identifier, which is then linked to a set of hydraulic parameters through the input tables.

This structure allows the model to:

  • Assign spatially distributed hydraulic properties
  • Maintain consistency across the domain
  • Separate spatial data from parameter definition

Only the surface or near-surface soil classification is used in HydroPol2D for estimating infiltration capacity. Deeper soil layering is not explicitly represented in the standard configuration.

Required Soil Parameters​

Hydraulic parameters are defined externally and associated with soil classes. Typical parameters include:

  • Saturated hydraulic conductivity (Ks)
  • Soil porosity
  • Residual water content
  • Soil water retention parameters (e.g., Van Genuchten parameters)
  • Initial soil moisture (when not prescribed as a spatial field)

These parameters must be physically consistent and representative of the soil classes defined in the raster.

Soil Data Sources​

Several datasets can be used to derive soil classifications and associated hydraulic parameters.

SoilGrids (ISRIC)​

  • Region: Global
  • Resolution: up to 250 m
  • Provides continuous estimates of soil properties (texture, bulk density, organic content)
  • Can be used to derive USDA soil texture classes
  • Download: https://soilgrids.org/

FAO / HWSD (Harmonized World Soil Database)​

USDA Soil Classification (Texture-Based)​

HydroPol2D commonly relies on USDA soil texture classes (e.g., sand, loam, clay) to define hydraulic behavior.

These classes can be derived from:

  • SoilGrids texture fractions
  • FAO soil databases
  • Regional soil surveys

This approach provides a consistent framework for assigning hydraulic parameters such as conductivity and retention characteristics.

SSURGO (Soil Survey Geographic Database)​

STATSGO (State Soil Geographic Database)​

Parameter Association​

Soil classes are not used directly in the governing equations. Instead, they serve as indices into parameter tables.

Each soil class must be associated with a consistent set of hydraulic properties. The quality of this mapping has a direct impact on model performance.

Users are responsible for ensuring that:

  • Parameter values are physically realistic
  • Units are consistent
  • Soil classes are properly defined and interpreted

Resolution and Alignment​

The soil raster must:

  • Match or be resampled to the DEM resolution
  • Use the same projected coordinate reference system (CRS)
  • Align spatially with all other raster inputs

Any mismatch in resolution or alignment will result in incorrect spatial assignment of soil properties.

Practical Considerations​

When preparing soil inputs:

  • Prefer categorical representations over raw continuous datasets
  • Aggregate detailed soil classifications when necessary
  • Avoid extreme or non-physical parameter values
  • Verify consistency between raster classes and parameter tables

In many cases, simplifying the number of soil classes improves model stability and interpretability.

Summary​

In HydroPol2D, soil data is used to control infiltration and near-surface hydrological response.

The model relies on a categorical soil representation coupled with externally defined hydraulic parameters. Proper definition and mapping of these parameters is essential for obtaining reliable simulations.