How to estimate infiltration rate and soil moisture Index by using Remote sensing and GIS?

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Brook Legese Dadhe

Dear Ban Hikmet,

Estimating infiltration rate and soil moisture index using remote sensing and GIS involves a combination of satellite or aerial imagery, ground truth data, and specific analytical techniques.

Estimating Soil Moisture:

Vegetation Indices: Calculate vegetation indices like NDVI (Normalized Difference Vegetation Index) from the imagery. Healthy vegetation affects soil moisture, which can be an indirect indicator.

Thermal Infrared Data: Use thermal infrared imagery to estimate land surface temperature. The difference between land surface temperature and air temperature can give insights into soil moisture.

Microwave Data: Microwave remote sensing can penetrate vegetation and provide direct soil moisture estimates. Soil moisture products like Soil Moisture and Ocean Salinity (SMOS) or Soil Moisture Active Passive (SMAP) data can be useful.

Estimating Infiltration Rate:

Topographic Data: Use digital elevation models (DEM) to analyze the topography of the area. Identify areas prone to water runoff and those that are more likely to infiltrate water.

Hydrological Modeling: Implement hydrological models like the Soil and Water Assessment Tool (SWAT) or the Hydrological Modeling System (HEC-HMS) to estimate infiltration rates. These models use topographic, land cover, and meteorological data.

Humble regards,

Ban Hikmet Al-Hasani

Brook Legese Dadhe many thanks for your kind support and help, can I use multi-criteria analysis to estimate the infiltration rate? And if so how to apply it?

Multi-criteria analysis (MCA) can estimate the infiltration rate in specific scenarios, especially when considering multiple criteria or factors that influence infiltration. It depends on soil type, vegetation, land use, and precipitation patterns. MCA allows you to consider these multiple criteria when making decisions or estimates.

Here is how you can apply MCA to estimate the infiltration rate:

Identify Criteria: Start by identifying the criteria or factors that influence infiltration rate. Common criteria might include soil type, land use, land cover, vegetation, precipitation patterns, and topography.

Data Collection: Gather data for each of the identified criteria. This data can include soil characteristics, land use maps, vegetation types and density, historical precipitation data, and topographical information.

Weighting: Assign weights to each criterion based on its importance in determining infiltration rate. The weights can be subjective and should be determined through consultation with experts or stakeholders. A scale from 0 to 1 is often used, where a higher value indicates greater importance.

Standardization: Normalize the data for each criterion to bring it to a common scale, often ranging from 0 to 1. This is usually done by applying a formula that converts the raw data into a common unit.

Score Calculation: For each criterion, calculate a score based on the normalized data and the assigned weights. This score represents the contribution of each criterion to the overall infiltration rate estimate.

Aggregation: Combine the individual criterion scores to obtain an overall score for each location or area under consideration. This can be done using different aggregation methods, such as weighted sum or average.

Sensitivity Analysis: Perform sensitivity analysis to assess the robustness of your results. This involves testing the impact of changing the criteria weights and seeing how it affects the final infiltration rate estimate.

Interpretation: Finally, interpret the results to estimate the infiltration rate for different locations or areas. The location with the highest overall score will have the highest estimated infiltration rate.

John Hatzopoulos

Aggregation can also be performed by analytical hierarchical process

Article Analytical Hierarchy Process: Revolution and Evolution