ABSTRACT:

This dataset represents the Arizona Subsurface Infiltration Index v.2 (SbII), a raster-based index developed to estimate the relative potential for water to infiltrate into subsurface lithologic units across the state of Arizona. The goal of this layer is to support landscape-scale planning for groundwater recharge enhancement by identifying regions with favorable subsurface conditions for infiltration.

The index is derived from a weighted linear combination of four geologic and structural variables that influence the movement of water through the vadose zone and into underlying aquifers:

Matrix Permeability (Pm) – log-transformed saturated hydraulic conductivity (log K) from the GLobal HYdrogeology MaPS (GLHYMPS v2) dataset (Huscroft et al., 2018), which reflects the ability of the geologic matrix to transmit water.

Matrix Porosity (Po) – volumetric porosity values from GLHYMPS v2, which influence the capacity for water storage within rock or sediment pore spaces.

Lineament Density (LD) – estimated from topographic and statistical surface derivatives using automated lineament extraction. These features are used as proxies for secondary permeability from faults and fractures, which can enhance infiltration along structurally controlled zones.

Presence of Karst or Pseudokarst Lithologies (Pk) – derived from national-scale karst mapping (Weary and Doctor, 2014), this factor accounts for lithologies prone to dissolution (e.g., carbonates, evaporites) or lava tube development, which can produce highly permeable pathways for focused recharge.

Each input layer was reclassified to a common suitability scale from 1 to 10, where 10 indicates the highest potential for infiltration and 1 the lowest. This reclassification was based on literature-supported thresholds, expert knowledge, and the distribution of values within the Arizona study area (see Methodology section for details).

This layer is intended to provide a spatially explicit, state-wide estimate of infiltration suitability, particularly useful for identifying regions where managed aquifer recharge (MAR) or landscape management strategies (e.g., thinning, floodwater retention) may have the greatest potential impact on subsurface recharge. However, due to the scale and resolution of the input data, this index is not appropriate for parcel-scale or engineering design applications. Local field investigations are essential for evaluating infiltration capacity at specific sites.

Visit [https://ryan3lima.github.io/Arizona_10m_Lineaments/] for more details

ABSTRACT:

This dataset contains lineament features automatically extracted using the LINE algorithm in Catalyst (PCI Geomatica) Focus Module from a 10m resolution Multi-Directional Hillshade (MDHS) derived from a 1/3 arcsecond DEM of Arizona. The lineaments were extracted from the MDHS using a low pass filter to smooth noise, and then processed with the LINE algorithm. The resulting lineaments were cleaned to remove artificial features, and a lineament density raster was created.

Lineaments—linear or curvilinear surface features—often correspond to underlying faults, fractures, or lithologic boundaries, and are important indicators of secondary permeability. As such, lineament density has been widely used to identify zones of enhanced infiltration and potential groundwater recharge, particularly in karst and fractured-rock terrains.

This dataset supports integrated hydrogeologic analysis, especially in regions lacking detailed subsurface data, by providing a proxy for structural controls on groundwater movement.

More details can be found here:
https://github.com/Ryan3Lima/Arizona_10m_Lineaments**

**currently a private repository to be made public after publication

ABSTRACT:

This raster data layer was created to assist in mapping suitability for groundwater recharge potential throughout the State of Arizona.

The Soil Moisture Infiltration Index is a custom index created to discern where on the landscape water is likely to infiltrate into the soil, it is a weighted linear combination of Topographic Relative Moisture Index (TRMI) and Soil Saturated Hydraulic Conductivity (sKsat).

30m Resolution

ABSTRACT:

This raster data layer was created to assist in mapping suitability for groundwater recharge potential throughout the State of Arizona.

The Soil Moisture Infiltration Index is a custom index created to discern where on the landscape water is likely to infiltrate into the soil, it is a weighted linear combination of Topographic Relative Moisture Index (TRMI) and Soil Saturated Hydraulic Conductivity (sKsat).

30m Resolution

ABSTRACT:

The Topographic Relative Moisture Index (TRMI) is a terrain-based index that estimates how wet or dry a location is likely to be based on its topographic attributes. TRMI incorporates several topographic parameters that influence moisture dynamics, including slope gradient, aspect, relative elevation (or topographic position), and landscape convexity or concavity [@parker1982]. Unlike purely hydrologic models (which might require soil or rainfall data), TRMI infers relative soil moisture patterns from topography. It’s based on the idea that topography controls moisture accumulation. This raster data layer was created to assist in mapping suitability for groundwater recharge potential throughout the State of Arizona.