Evapotranspiration using MODIS data and limited ground observations over selected agroecosystems in India

Abstract

Plant growth processes and productivity of agroecosystems depend highly on evapotranspiration from the land (soil-crop cover complex) surface. A study was carried out using MODIS TERRA optical and thermal band data and ground observations to estimate evaporative fraction and daily actual evapotranspiration (AET) over agroecosystems in India. Five study regions, each covering a 10 km610 km area falling in agricultural land use, were selected for ground observations at a time closest to TERRA overpasses. The data on radiation and crop parameters in paddy (irrigated and rainfed), cotton (rainfed), groundnut (residual moisture) crops were recorded at 14-day intervals between August 2003 to January 2004 from 2 km62 km homogeneous crop patches within each study region. Eight MODIS scenes in seven optical (1, 2, 3, 4, 5, 6, 7) and two thermal bands (31, 32) level 1B data acquired from the National Remote Sensing Agency, Hyderabad, India and resampled at 1 km, were used to generate surface albedo (a), land surface temperature (T s, MODIS ) and emissivity (e s ). Evaporative fraction and daily AET were generated using a single source energy balance approach with (i) ground based observations only ('stand alone' approach), and (ii) 'fusion' of MODIS derived land surface variables on cloud free dates and coincident ground observations. Land cover classes were assigned using a hierarchical decision rule applied to multi-date Normalized Difference Vegetation Index (NDVI). The exponential model could be fitted between 1-EF ins, ground (ground based evaporative fraction) and difference between T s, MODIS and air temperature (T a ) with R 2 50.77. Linear fit (R 2 50.74) could be obtained between 1-EF ins, ground and temperature vegetation dryness index (TVDI), derived from T s, MODIS -NDVI triangle. Energy balance daily AET from the 'fusion' approach was found to deviate from water balance AET by between 4.3% to 24.5% across five study sites with a mean deviation of 11.6%. The root mean square error (RMSE) from the energy balance AET was found to be 8% of the mean water balance AET. The satellite based energy balance approach can be used to generate spatial AET, but needs more refinements before operational use in the light of progress in algorithms and their validation with huge datasets.

Components of near-surface energy balance derived from satellite soundings – Part 2: Noontime latent heat flux

“…This is obviously a confounding factor when one attempts to use these data to evaluate surface parameterisations in weather, climate and hydrological models, particularly when the models we wish to evaluate may contain very similar model descriptions for E. What is required, therefore, are methods for deriving E estimates from satellite data that do not rely unduly on surface parameterisations, and thus they become a valid and valuable data source for model evaluation. One approach that appears to fulfil this requirement is where λE is estimated from satellite data as a residual term in the energy balance equation (Tasumi et al, 2005;Mallick et al, 2007). However, this approach suffers from the effects of error propagation because all errors, including any lack of observed closure of the regional energy budget, are lumped into the estimate of λE (Foken et al, 2006).…”

“…sensing data have been developed and used to evaluate the spatio-temporal behaviour of evaporation for field (Tasumi et al, 2005), regional (Bastiaanssen et al, 1998;Su, 2002;Mu et al, 2007;Mallick et al, 2007;Jang et al, 2010) and continental scales (Anderson et al, 2007;Sahoo et al, 2011). The methods employed thus far can be categorised based on the various approaches followed to determine E. The most common approach centres on assuming a physical model of evaporation given many of the variables required to compute evaporation using these models are available directly as satellite products (e.g.…”

A Quantitative Inspection on Spatio-Temporal Variation of Remote Sensing-Based Estimates of Land Surface Evapotranspiration in South Asia

“…It also provides a vital way to get land surface ET spatial and temporal distribution in South Asia. Recently, a few approaches to remote sensing based on ET estimation methods have been proposed and widely applied around the world [9][10][11][12][13][14][15]. Among these methods, the physical methods based on surface energy balance form a big group from which one can derive ET, including the commonly used Surface Energy Balance Algorithm over Land (SEBAL) [16], Simplified Surface Energy Balance Index (S-SEBI) [17], Surface Energy Balance System (SEBS) [18], and Mapping Evapotranspiration with Internalized Calibration (METRIC) [19].…”

Mapping daily evapotranspiration and dryness index in the East African highlands using MODIS and SEVIRI data

“…The MODerate resolution Imaging Spectroradiometer (MODIS) sensor on board Terra and Aqua satellites has long been recognized for its potential to produce frequent ET maps across the globe. Few researchers have used MODIS data to produce ET maps in different regions for some periods (Nagler et al, 2005;Patel et al, 2006;Cleugh et al, 2007;Mallick et al, 2007;Mu et al, 2007;Wang et al, 2007;Leuning et al, 2008;Venturim et al, 2008). However, despite these limited successes, we still do not have operational daily ET maps across Africa.…”