Remote sensing for determining evapotranspiration and irrigation demand for annual crops

Abstract

Author Information Show + 1. Introduction

Evapotranspiration (ETc) is the mean for exploiting irrigation water and constitutes a major component of the hydrological cycle (Telis et al., 2007; Papadavid, 2011). The ETc is a basic and crucial parameter for climate studies, weather forecasts and weather modeling, hydrological surveys, ecological monitoring and water resource management (Hoedjes et al., 2008). In the past decades, the estimation of ETc combining conventional meteorological ground measurements with remotely-sensed data, has been widely studied and several methods have been developed for this purpose (Tsouni, 2003). For hydrological resources management and irrigation scheduling, an accurate estimation of the ETc is necessary to be considered (Hoedjes et al., 2008 ; Papadavid et al., 2011). Crop evapotranspiration rate is highly important in various areas of the agricultural sector such as for identification of crop stress, water deficiency, for estimating the exact potential needs of crops for best yields. It is well accepted that water depletion methods, such as lysimeters, are the most accurate methods for estimating ETc. Methods that use meteorological parameters in order to estimate the ETc of different crops are well established and used by various studies (Telis et al., 2007; Rogers et al., 2007). A number of semi-empirical methods have been also developed in order to estimate the evapotranspiration from different climatic variables (Courault et al., 2005). Remotely sensed reflectance values can be used in combination with other detailed information for estimating ETc of different crops. Indeed, the potentiality of remote sensing techniques in ETc estimation and water resource management has been widely acknowledged (Papadavid et al., 2010). The possibility for monitoring irrigation demand from space is an important factor and tool for policy makers. It has been found that saving irrigation water through remote sensing techniques could diminish farm irrigation cost which reaches 25% of the total costs and increases the margin of net profit (Papadavid et al., 2011). Several researchers such as D’Urso et al., (1992), Bastiaanssen (2000), Ambast et al., (2006) and Papadavid et al., (2011) have highlighted the potentiality of multispectral satellite images for the appraisal of irrigation management. The integration of remotely sensed data with auxiliary ground truth data for obtaining better results is common in the literature. (Bastiaanssen et al., 2003; Ambast et al., 2006; Minaccapili et al., 2008). Ambast et al., (2006) have shown that the application of remote sensing data in irrigation is of high importance because it supports management of irrigation and is a powerful tool in the hands of policy makers. It has been found that research in ETc is directed towards energy balance algorithms that use remote sensing directly to calculate input parameters and, by combining empirical relationships to physical models, to estimate the energy budget components (Minaccapili et al., 2008; Papadavid et al., 2010; Papadavid et al., 2011). All the remote sensing models of this category are characterized by several approximations and need detailed experimental validations. Multispectral images are used to infer ETc, which is the main input for water balance methods-models. For estimations of ET, ground truth data (Leaf Area Index-LAI, crop height) and meteorological data (air temperature, wind speed, humidity) is needed to support this approach. In nearly every application of water balance model, knowledge of spatial variations in meteorological conditions is needed (Moran et al., 1997).

The use of remote sensed data is very useful for the deployment of water strategies since it can offer a huge amount of information in short time, compared to conventional methods. Besides convenience and time reducing, remotely sensed data lessens the costs for data acquisition, especially when the area is extended (Thiruvengadachari et al., 1997). Although remote sensing based ETc models have been shown to have the potential to accurately estimate regional ETc, there are opportunities to further improve these models testing the equations used to estimate LAI and crop height for their accuracy under current agro-meteorological and soil conditions.

This Chapter discusses the implementation of the most widely used models for estimating ETc, the ‘SEBAL’ and ‘Penman-Monteith’ which are used with satellite data. Such models are employed and modified, with semi-emprical models regarding crop canopy factors, to estimate accurately ETc for specific crops in the Cyprus area under local conditions. Crop Water Requirements have been determined based on the evapotranspiration values.