Soil Moisture

Index name: Soil moisture anomaly (SMA)

Ease of use: Yellow

Origins: Developed by Bergman et al. at the National Weather Service in the United States during the mid-1980s as a way to assess global drought conditions.

Characteristics: Can use weekly or monthly precipitation and potential evapotranspiration values in a simple water balance equation. It is intended to reflect the degree of dryness or saturation of the soil compared with normal conditions, and to show how soil moisture stress influences crop production around the world.

Input parameters: Weekly or monthly temperature and precipitation data along with date and latitude. Values for soil moisture water-holding capacity and site-specific data can be used, although defaults are included.

Applications: Developed and used extensively for monitoring drought impacts on agriculture and crop production around the world.

Strengths: By taking into account the effects of both temperature and precipitation, the water balance aspects that make PDSI so popular are included with the ability to change constants with site-specific data. It considers moisture at different layers of the soil and is more adaptable than PDSI to different locations.

Weaknesses: The data requirements make it challenging to calculate. Potential evapotranspiration estimates can vary quite substantially by region.

Resources: The inputs and calculations are described thoroughly in the literature. No program exists at this time to provide the calculations.

Index name: Evapotranspiration Deficit Index (ETDI)

Ease of use: Red

Origins: Developed from research at the Texas Agricultural Experiment Station, United States, by Narasimhan and Srinivasan in 2004.

Characteristics: A weekly product that is helpful for identifying water stress for crops. ETDI is calculated along with the Soil Moisture Deficit Index (SMDI), in which a water stress ratio is calculated that compares actual evapotranspiration with reference crop evapotranspiration. The water stress ratio is then compared with the median calculated over a long-term period.

Input parameters: Modeled data from a hydrologic model with the soil and water assessment tool (SWAT) model are used initially to compute soil water in the root zone on a weekly basis.

Applications: Useful for identifying and monitoring short-term drought affecting agriculture.

Strengths: Analyses both actual and potential evapotranspiration and can identify wet and dry periods.

Weaknesses: Calculations are based upon output from the SWAT model, but could be calculated if the appropriate inputs were available. The spatial variability of ETDI increases in the summer months during the period of greatest evapotranspiration and highly variable precipitation.

Resources: Calculations are provided and explained thoroughly in the reference below, along with correlation studies to other drought indices. Information on the SWAT model can be found at http://swat.tamu.edu/ software/swat-executables/

Reference: Narasimhan and Srinivasan (2005).

Index name: Soil Moisture Deficit Index (SMDI)

Ease of use: Red

Origins: Developed from research at the Texas Agricultural Experiment Station, United States, by Narasimhan and Srinivasan in 2004.

Characteristics: A weekly soil moisture product calculated at four different soil depths, including the total soil column, at 0.61, 1.23, and 1.83 m, and can be used as an indicator of short-term drought, especially using the results from the 0.61 m layer.

Input parameters: Modeled data from a hydrologic model with the SWAT model are used initially to compute soil water in the root zone on a weekly basis.

Applications: Useful for identifying and monitoring drought affecting agriculture.

Strengths: Takes into account the full profile as well as different depths, which makes it adaptable to different crop types.

Weaknesses: The information needed to calculate SMDI is based upon output from the SWAT model. There are auto-correlation concerns when all the depths are being used.

Resources: The calculations are provided and explained thoroughly in the reference below.

Information on the SWAT model can be found at http://swat.tamu.edu/ software/swat-executables/".

Reference: Narasimhan and Srinivasan (2005).

Index name: Soil Water Storage (SWS)

Ease of use: Red

Origins: Unknown—producers have been trying to measure soil moisture accurately since the beginning of agriculture.

Characteristics: Identifies the amount of available moisture within a plant's root zone, which depends upon the type of plant and the type of soil. Precipitation and irrigation both affect the results.

Input parameters: Rooting depth, available water storage capacity of the soil type, and maximum soil water deficit.

Applications: Used mainly for monitoring drought in agricultural contexts, but can also be a component in drought conditions affecting water availability.

Strengths: Calculations are well known and simple to follow, even using defaults. Many soils and crops have been analyzed using this method.

Weaknesses: In areas where soils are not homogeneous, there may be large changes over small distances.

Resources: Calculations and examples are provided in the reference below. Reference: British Columbia Ministry of Agriculture (2015).

 
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