Evapotranspiration estimation using Landsat-8 data with a two-layer framework

This work was partially supported by the National Natural Science Foundation of China (41401042), National Key Basic Research Program of China (973 Program) (Grant No. 2015CB452701) and National Natural Science Foundation of China (Grant Nos. 41571019 and 41371043).Peer reviewedproo

Evapotranspiration Estimates Derived Using Multi-Platform Remote Sensing in a Semiarid Region

Evapotranspiration (ET) is a key component of the water balance, especially in arid and semiarid regions. The current study takes advantage of spatially-distributed, near real-time information provided by satellite remote sensing to develop a regional scale ET product derived from remotely-sensed observations. ET is calculated by scaling PET estimated from Moderate Resolution Imaging Spectroradiometer (MODIS) products with downscaled soil moisture derived using the Soil Moisture Ocean Salinity (SMOS) satellite and a second order polynomial regression formula. The MODis-Soil Moisture ET (MOD-SMET) estimates are validated using four flux tower sites in southern Arizona USA, a calibrated empirical ET model, and model output from Version 2 of the North American Land Data Assimilation System (NLDAS-2). Validation against daily eddy covariance ET indicates correlations between 0.63 and 0.83 and root mean square errors (RMSE) between 40 and 96 W/m2. MOD-SMET estimates compare well to the calibrated empirical ET model, with a −0.14 difference in correlation between sites, on average. By comparison, NLDAS-2 models underestimate daily ET compared to both flux towers and MOD-SMET estimates. Our analysis shows the MOD-SMET approach to be effective for estimating ET. Because it requires limited ancillary ground-based data and no site-specific calibration, the method is applicable to regions where ground-based measurements are not available

Empleo de técnicas de teledetección con diferentes niveles de resolución para la mejora de la gestión del riego

Currently there is a growing interest in improving water management in Mediterranean agriculture due to the foreseeable results of climate change and to the competition with other sectors such as the environmental. For this reason different methodologies have been evaluated in this thesis to increase water use efficiency in Andalusian agriculture by means of the improvement in the estimation of crop irrigation water requirements, using different remote sensing techniques and spatial analysis. In this work the two main parameters involved in crop evapotranspiration determination were addressed: reference evapotranspiration (Chapters 1 and 2) and crop coefficient (Chapters 3 and 4). More specifically, in Chapter 1, different interpolation methods were applied to meteorological data and results were assessed in order to determine which of them provided the most accurate reference evapotranspiration (ETo) estimates. The ETo estimates obtained from the interpolation methods were compared with the ETo values provided by the Land Surface Analysis Satellite Application Facility (LSA SAF), based on the daily solar radiation derived from Meteosat Second Generation (MSG) and air temperature at 2 m forecasts provided by European Center for Medium-range Weather Forecasts (ECMWF). Additionally, new techniques were proposed for ETo estimation improvement in areas without a nearby weather station, which were based on the analysis of the spatial location of the weather stations and the temporal evolution of ETo. Also related to ETo estimation and its practical application for irrigation management, Chapter 2 presents an innovative methodology for performing irrigation schedules easily usable by farmers and technicians, using weather forecasts provided by the National Meteorological Agency (AEMET) and by ECMWF for ETo estimation. In addition, the effect that the different methods for ETo estimation has on the crop water requirements and on the crop yield simulated using the AquaCrop model was also assessed. Once accurate ETo values were determined by means of the methodologies developed in Chapters 1 and 2, it is necessary to determine crop coefficient values for the correct estimation of the crop water demands. This issue was addressed in Chapter 3, where different atmospheric corrections were applied to Landsat 7 satellite images, with the aim of eliminating the effect that the atmosphere causes during the image acquisition process. In this way, it was possible to obtain much more accurate surface temperature measurements, in order to assess the effect of the different atmospheric corrections on the determination of the olive crop coefficient. However, the effect that atmosphere has on the satellite images acquisition process analyzed in Chapter 3 is not the only issue to be taken into account when using remote sensing techniques. Thus, spatial resolution is also a key factor for the application of these techniques in irrigation management. Therefore, in Chapter 4 the influence of spatial resolution on the different energy balance components estimated by the METRIC energy balance model was evaluated, paying special attention to crop evapotranspiration.Actualmente existe un interés creciente por la mejora de la gestión del agua en la agricultura mediterránea debido a las previsibles consecuencias del cambio climático y a la competencia con otros sectores como el medioambiental. Por este motivo en esta tesis se han evaluado diferentes metodologías para incrementar la eficiencia en el uso del agua en la agricultura andaluza por medio de la mejora en la estimación de las necesidades de riego de los cultivos, empleando diferentes técnicas de teledetección y análisis espacial. De este modo, en este trabajo se abordó el estudio de los dos principales parámetros involucrados en la determinación de la evapotranspiración de cultivo: la evapotranspiración de referencia (Capítulos 1 y 2) y el coeficiente de cultivo (Capítulos 3 y 4). Más específicamente, en el Capítulo 1 se evaluaron diferentes métodos de interpolación de información obtenida desde estaciones meteorológicas para determinar cuál de ellos proporcionaba unas estimaciones de evapotranspiración de referencia (ETo) más precisas. Las estimaciones de ETo obtenidas con dichos métodos de interpolación se compararon con los valores de ETo proporcionados por Land Surface Analysis Satellite Application Facility (LSA SAF), a partir de la radiación solar diaria derivada de Meteosat Second Generation (MSG) y de las prediciones de la temperatura del aire a 2 m proporcionadas por European Centre for Medium-range Weather Forecasts (ECMWF). Adicionalmente, se propusieron técnicas para la mejora en la estimación de la ETo en zonas sin estación meteorológica cercana, basadas en el análisis de localización espacial de las estaciones meteorológicas y en la evolución temporal de ETo en las mismas. Relacionado también con la estimación de la ETo y su aplicación práctica para la gestión del riego, en el Capítulo 2 se presenta una innovadora metodología para la realización de calendarios de riego fácilmente utilizable por agricultores y técnicos, utilizando predicciones meteorológicas para la estimación de ETo proporcionadas por la Agencia Estatal de Meteorología (AEMET) y por el ECMWF. Además, se analizó el efecto de la consideración de diferentes métodos para la estimación de la ETo sobre las necesidades de riego y sobre el rendimiento del cultivo simulado utilizando el modelo AquaCrop. Una vez determinados valores fiables de ETo mediante las metodologías desarrolladas en los Capítulos 1 y 2, para la correcta estimación de las necesidades de riego de los cultivos, es preciso obtener valores de coeficiente de cultivo ajustados al estado de los mismos. Esta cuestión se trató en el Capítulo 3, donde se aplicaron diferentes correcciones atmosféricas sobre imágenes del satélite Landsat 7, con el objetivo de eliminar el efecto que la atmósfera causa durante el proceso de adquisición de las mismas. De este modo, se consiguió obtener unas medidas de temperatura superficial mucho más precisas, para finalmente conocer el efecto de las diferentes correcciones atmosféricas sobre la determinación del coeficiente de cultivo del olivar. Sin embargo, el efecto de la atmósfera en el proceso de adquisición de imágenes de satélite analizado en el Capítulo 3 no es el único aspecto a tener en cuenta al emplear técnicas de teledetección. Así, la resolución espacial también es un factor clave para la correcta aplicación de estas técnicas en la gestión del riego. Es por ello que en el Capítulo 4 se evaluó la influencia de la resolución espacial sobre los diferentes componentes de balance de energía estimados mediante el modelo de balance de energía METRIC, prestando especial atención a la evapotranspiración del cultivo

Mapping evapotranspiration variability over a complex oasis-desert ecosystem based on automated calibration of Landsat 7 ETM+ data in SEBAL

Fragmented ecosystems of the desiccated Aral Sea seek answers to the profound local hydrologically- and water-related problems. Particularly, in the Small Aral Sea Basin (SASB), these problems are associated with low precipitation, increased temperature, land use and evapotranspiration (ET) changes. Here, the utility of high-resolution satellite dataset is employed to model the growing season dynamic of near-surface fluxes controlled by the advective effects of desert and oasis ecosystems in the SASB. This study adapted and applied the sensible heat flux calibration mechanism of Surface Energy Balance Algorithm for Land (SEBAL) to 16 clear-sky Landsat 7 ETM+ dataset, following a guided automatic pixels search from surface temperature T-s and Normalized Difference Vegetation Index NDVI (). Results were comprehensively validated with flux components and actual ET (ETa) outputs of Eddy Covariance (EC) and Meteorological Station (KZL) observations located in the desert and oasis, respectively. Compared with the original SEBAL, a noteworthy enhancement of flux estimations was achieved as follows: - desert ecosystem ETa R-2 = 0.94; oasis ecosystem ETa R-2 = 0.98 (P < 0.05). The improvement uncovered the exact land use contributions to ETa variability, with average estimates ranging from 1.24 mm to 6.98 mm . Additionally, instantaneous ET to NDVI (ETins-NDVI) ratio indicated that desert and oasis consumptive water use vary significantly with time of the season. This study indicates the possibility of continuous daily ET monitoring with considerable implications for improving water resources decision support over complex data-scarce drylands

Satellite Retrieval of Surface Evapotranspiration with Nonparametric Approach: Accuracy Assessment over a Semiarid Region

Surface evapotranspiration (ET) is one of the key surface processes. Reliable estimation of regional ET solely from satellite data remains a challenge. This study applies recently proposed nonparametric (NP) approach to retrieve surface ET, in terms of latent heat flux (LE), over a semiarid region. The involved input parameters are surface net radiation, land surface temperature, near-surface air temperature, and soil heat flux, all of which are retrievals or products of the Moderate-Resolution Imaging Spectroradiometer (MODIS). Field observations are used as ground references, which were obtained from six eddy covariance (EC) sites with different land covers including desert, Gobi, village, orchard, vegetable field, and wetland. Our results show that the accuracy of LE retrievals varies with EC sites with a determination of coefficient from 0.02 to 0.76, a bias from −221.56 W/m2 to 143.77 W/m2, a relative error from 8.82% to 48.35%, and a root mean square error from 67.97 W/m2 to 239.55 W/m2. The error mainly resulted from the uncertainties from MODIS products or the retrieval of net radiation and soil heat flux in nonvegetated region. It highlights the importance of accurate retrieval of the input parameters from satellite data, which are the ongoing tasks of remote sensing community

Remote Sensing Based Estimation of Evapo-Transpiration Using Selected Algorithms: The Case of Wonji Shoa Sugar Cane Estate, Ethiopia

Remote sensing datasets are increasingly being used to provide spatially explicit large scale evapotranspiration (ET) estimates. The focus of this study was to estimate and thematically map on a pixel-by-pixel basis, the actual evapotranspiration (ETa) of the Wonji Shoa Sugarcane Estate using the Surface Energy Balance Algorithm for Land (SEBAL), Simplified Surface Energy Balance (SSEB) and Operational Simplified Surface Energy Balance (SSEBop) algorithms. The results obtained revealed that the ranges of the daily ETa estimated on January 25, February 26, September 06 and October 08, 2002 using SEBAL were 0.0 - 6.85, 0.0 – 9.36, 0.0 – 3.61, 0.0 – 6.83 mm/day; using SSEB 0.0 - 6.78, 0.0 – 7.81, 0.0 – 3.65, 0.0 – 6.46 mm/day, and SSEBop were 0.05 - 8.25, 0.0 – 8.82, 0.2 – 4.0, 0.0 – 7.40 mm/day, respectively. The Root Mean Square Error (RMSE) values between SSEB and SEBAL, SSEBop and SEBAL, and SSEB and SSEBop were 0.548, 0.548, and 0.99 for January 25, 2002; 0.739, 0.753, and 0.994 for February 26, 2002;0.847, 0.846, and 0.999 for September 06, 2002; 0.573, 0.573, and 1.00 for October 08, 2002, respectively. The standard deviation of ETa over the sugarcane estate showed high spatio-temporal variability perhaps due to soil moisture variability and surface cover. The three algorithm results showed that well watered sugarcane fields in the mid-season growing stage of the crop had higher ETa values compared with the other dry agricultural fields confirming that they consumptively use more water. Generally during the dry season, ETa is limited to water surplus areas only and in wet season, ETa was high throughout the entire sugarcane estate. The evaporation fraction (ETrF) results also followed the same pattern as the daily ETa over the sugarcane estate. The total crop and irrigation water requirement and effective rainfall estimated using the Cropwat model were 2468.8, 2061.6 and 423.8 mm/yr for January 2001 planted and 2281.9, 1851.0 and 437.8 mm/yr for March 2001 planted sugarcanes, respectively. The mean annual ETa estimated for the whole estate were 107 Mm3, 140 Mm3, and 178 Mm3 using SEBAL, SSEB, and SSEBop, respectively. Even though the algorithms should be validated through field observation, they have potential to be used for effective estimation of ET in the sugarcane estate. Keywords: ET; CWR; Landsat ETM+; Remote Sensing; SEBAL; SSEB; SSEBo