GIS-Based Approaches for Estimating Potential Evapotranspiration in Non-Agricultural Land Use: A Comprehensive Review

Getting Started

Estimation of potential evapotranspiration (PET) is a critical aspect of understanding the water cycle and hydrological processes in non-agricultural land use classes. PET represents the maximum amount of water that could be evaporated and transpired by vegetation under ideal conditions. Accurate estimation of PET is essential for various GIS and earth science applications, including water resource management, urban planning, environmental impact assessment, and climate change studies.

Estimating PET for non-agricultural land use classes presents unique challenges compared to agricultural areas. The vegetation cover, land surface characteristics, and climatic factors differ significantly in non-agricultural land use classes such as urban areas, forests, and natural ecosystems. Therefore, specialized approaches are needed to accurately estimate PET in these environments. In this article, we will review several approaches commonly used to estimate PET for non-agricultural land use classes.

1. Empirical approaches

Empirical approaches are widely used to estimate PET for non-agricultural land use classes due to their simplicity and ease of implementation. These approaches are based on statistical relationships between PET and meteorological variables such as temperature, humidity, wind speed, and solar radiation. Several empirical methods have been developed, including the Hargreaves-Samani method, the Thornthwaite method, and the Penman-Monteith method.

The Hargreaves-Samani method is a widely used empirical approach that estimates PET from temperature data alone. It uses the temperature range and solar radiation to estimate PET without the need for additional meteorological data. The Thornthwaite method estimates PET based on temperature and day length, making it suitable for regions with limited availability of meteorological data. The Penman-Monteith method is considered one of the most accurate empirical methods because it incorporates several meteorological variables, including temperature, humidity, wind speed, and solar radiation. It provides reliable estimates of PET for various non-agricultural land use classes.

2. Remote sensing approaches

Remote sensing techniques provide valuable tools for estimating PET in non-agricultural land use classes. These approaches use satellite imagery to derive key parameters required for PET estimation, including land surface temperature, vegetation indices, and albedo. Remotely sensed data provide spatially explicit information that allows the assessment of PET variations across land use classes.

A commonly used remote sensing approach is the surface energy balance method, which combines remotely sensed land surface temperature and meteorological data to estimate PET. This method takes into account the energy balance between incoming solar radiation, surface heat fluxes, and latent heat flux (evapotranspiration). Another approach is to use vegetation indices, such as the Normalized Difference Vegetation Index (NDVI), to estimate PET. NDVI is calculated from satellite imagery and provides information on vegetation density and vigor, which influence evapotranspiration rates.

3. Physically based approaches

Physically based approaches to estimating PET in non-agricultural land use classes rely on mathematical models that simulate the physical processes involved in evapotranspiration. These models take into account factors such as solar radiation, wind speed, temperature, humidity, and vegetation characteristics to accurately estimate PET.

The Penman-Monteith method, although classified as an empirical approach, can also be considered a physically based approach due to its underlying principles. It combines energy balance and aerodynamic components to accurately estimate PET. Another physically based approach is the Priestley-Taylor method, which uses an empirical coefficient to estimate PET based on available energy and potential evaporation. These physically based approaches provide more comprehensive estimates of PET by taking into account the underlying physical processes that govern evapotranspiration.

4. GIS-based approaches

Geographic Information System (GIS)-based approaches integrate spatial data with modeling techniques to estimate PET in non-agricultural land use classes. GIS provides a platform for data integration, manipulation, and analysis that allows for the incorporation of various spatially distributed factors that influence PET.

One approach is to develop spatial models that combine GIS data layers such as land cover, topography, and meteorological data to estimate PET. These models use spatial interpolation techniques to generate continuous surfaces of PET across the study area. Another GIS-based approach involves the integration of remote sensing data with GIS to estimate PET. This approach combines satellite imagery with GIS data layers to derive PET estimates at high spatial resolution.
In summary, accurate estimation of potential evapotranspiration (PET) in non-agricultural land use classes is essential for understanding hydrological processes and supporting various GIS and earth science applications. Empirical, remote sensing, physics-based, and GIS-based approaches provide valuable tools for estimating PET in these areas. The choice of approach depends on data availability, computational resources, and the specific characteristics of the study area. Researchers and practitioners should carefully select the most appropriate approach considering these factors to ensure accurate and reliable PET estimates for non-agricultural land use classes.

FAQs

Approaches for estimating potential evapotranspiration for non-agricultural land use classes

Potential evapotranspiration (PET) is an important parameter in hydrological studies, and estimating it accurately is crucial for various applications. Here are some commonly used approaches for estimating potential evapotranspiration for non-agricultural land use classes:

1. What is the Thornthwaite method for estimating PET?

The Thornthwaite method is a widely used empirical approach for estimating potential evapotranspiration. It uses temperature and latitude data to calculate PET. The method assumes that PET is directly proportional to the temperature and varies with the latitude. The Thornthwaite equation calculates PET based on a water balance approach, considering the heat energy available for evapotranspiration.

2. How does the Penman-Monteith equation estimate PET?

The Penman-Monteith equation is a more complex and physically based approach for estimating potential evapotranspiration. It takes into account various climatic factors such as temperature, humidity, wind speed, and solar radiation. This equation requires detailed meteorological data and is considered more accurate than empirical methods. It is often used as a standard reference for estimating PET.

3. Can remote sensing techniques be used to estimate PET for non-agricultural land use classes?

Yes, remote sensing techniques can be used to estimate potential evapotranspiration for non-agricultural land use classes. These techniques utilize satellite-based data, such as thermal infrared imagery, to estimate the surface temperature of the land. Combined with meteorological data, remote sensing can provide spatially distributed estimates of PET over large areas, allowing for better understanding of water balance dynamics.

4. Are there simplified methods available for estimating PET?

Yes, there are simplified methods available for estimating potential evapotranspiration. These methods often rely on fewer input parameters and are suitable when detailed meteorological data is not available. Examples include the Hargreaves equation, which estimates PET based on temperature data, and the FAO-56 PM method, a simplified version of the Penman-Monteith equation that uses temperature and solar radiation data.

5. What are the limitations of PET estimation approaches for non-agricultural land use classes?

Estimating potential evapotranspiration for non-agricultural land use classes can be challenging due to various reasons. Some limitations include:

• The methods may not account for specific land surface characteristics or vegetation types, leading to potential inaccuracies.
• Reliable meteorological data may not be available for the study area, particularly in remote or data-scarce regions.
• The assumptions and parameters used in the estimation methods may not be universally applicable and may require calibration or adjustment for specific regions.
• Uncertainties associated with climate change and variability can affect the accuracy of PET estimation.