Surface energy balance and actual evapotranspiration of the transboundary Indus Basin estimated from satellite measurements and the ETLook model

Abstract

[1] The surface energy fluxes and related evapotranspiration processes across the Indus Basin were estimated for the hydrological year 2007 using satellite measurements. The new ETLook remote sensing model (version 1) infers information on actual Evaporation (E) and actual Transpiration (T) from combined optical and passive microwave sensors, which can observe the land-surface even under persistent overcast conditions. A two-layer Penman-Monteith equation was applied for quantifying soil and canopy evaporation. The novelty of the paper is the computation of E and T across a vast area (116.2 million ha) by using public domain microwave data that can be applied under all weather conditions, and for which no advanced input data are required. The average net radiation for the basin was estimated as being 112 Wm À2 . The basin average sensible, latent and soil heat fluxes were estimated to be 80, 32, and 0 Wm ; RE ¼ 6.5% for annual ET). The water balance for all irrigated areas together as one total system in Pakistan and India (26.02 million ha) show a total ET value that is congruent with the ET value from the ETLook surface energy balance computations. An unpublished validation of the same ETLook model for 23 jurisdictional areas covering the entire Australian continent showed satisfactory results given the quality of the watershed data and the diverging physiographic and climatic conditions (R 2 ¼ 0.70; RMSE ¼ 0.31 mmd À1 ; RE ¼ -2.8% for annual ET). Eight day values of latent heat fluxes in Heibei (China) showed a good resemblance (R 2 ¼ 0.92; RMSE ¼ 0.04 mm d À1 ; RE ¼ 9.5% for annual ET). It is concluded that ETLook is a novel model that can be operationalized further-especially after improving the preprocessing of spaceborne soil moisture data. This preprocessing includes (1) downscaling of topsoil moisture from 25 to 1 km pixels, and (2) translation of topsoil moisture into subsoil moisture values.

Monitoring of Evapotranspiration in a Semi-Arid Inland River Basin by Combining Microwave and Optical Remote Sensing Observations

“…The NDVI was used to indicate the vegetation conditions and to calculate the FVC [33] and LAI [15]. The NDVI data used in this study is MODIS vegetation index (VI) product MOD13A2 (1-km/16-day) from 2009 to 2011 in the Sinusoidal projection.…”

“…Widely used algorithms can be divided into four categories: simplified empirical regression methods [5,6], trapezoid or triangle feature space methods [7][8][9], surface energy balance based (single-and dual-source) models [10][11][12][13][14], and the traditional evapotranspiration estimation approaches, for instance the Penman-Monteith equation and Priestley-Taylor equation, combined with remote sensing [4,[15][16][17][18][19]. Efforts have been made using different models mainly based on energy balance equation and taking the evapotranspiration as the residual on way or the other in combination with optical remote sensing, i.e., using land surface temperature (LST) retrieved from thermal infrared bands as the main driving variable [20][21][22], of which some case studies were conducted in the Heihe River basin [9,23,24].…”

“…The estimated ETa as a residual of the energy balance contains biases from the net radiation, soil heat flux and sensible heat flux as well. Recently, some developments have been made based on the Soil-Vegetation-Atmosphere Transfer (SVAT) scheme, Penman-Monteith equation and remotely sensed data for the temporally and spatially continuous estimates of ETa, which is particularly useful for various applications since it is not limited to clear sky conditions [15][16][17][18][19]26].…”

“…for a coniferous forest, Stewart [40] has obtained a value of 0.0155 hPa A sinusoidal function is used to take into account the influence of root zone soil moisture deficit on the stomatal closure [15,47],…”

Modelling stream flow and quantifying blue water using a modified STREAM model for a heterogeneous, highly utilized and data-scarce river basin in Africa

“…SI makes it feasible to compare the results of different input parameters independent of the chosen variation range (Lenhart et al, 2002;Bastiaanssen et al, 2012). The SI can be positive or negative depending on the co-directional response of the model performance to the input parameter change.…”