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

Drought assessment modelling using biophysical parameters and remote sensing data

This study considers the advancement in technical development of a few disciplines as an infrastructure for developing a suitable model and methodology for agricultural drought assessment in semi-arid area. It evaluates capabilities of multisource remote sensing data in developing raster-based biophysical drought assessment models. The capability for expressing the spatial and inter-annual variation of evapotranspiration (ET) over a study area by the proposed models has made it efficient. The base model, Mapping EvapoTranspiration at high Resolution with Internal Calibration (METRIC) has been evaluated for its performance in estimating ET over the pistachio plantation in a semi-arid region. The result proved that the base model gives good accuracy and is suitable for the selected study area. The base model, METRIC, is found sensitive to a number of meteorological parameters. Two-factor analysis for the primary inputs of the base model shows that the surface albedo and surface temperature pairs is the most effective while other tested pairs are found to be least effective. The study suggests that improving the equations of the effective pair should increase the accuracy. In this case, the multilayer perceptron Artificial Neural Network (ANN) technique is used for estimating spatial and temporal distribution of actual ET from satellite based biophysical parameters. The result shows that a strong correlation exist between ET values computed using METRIC and those generated using ANN. ANN sensitivity analysis shows that surface temperature, soil heat flux and surface albedo are the most significant parameters. Exploratory factor analysis using Principal Component Analysis (PCA) was performed to select the most significant biophysical parameters to be used as input to a newly developed BioPhysical Water Stress Index (BPWSI). The BPWSI is a new model for estimating water stress index using the selected biophysical parameters. The results of BPWSI are found to be significant and can be used for predicting the pistachio water status which represents the indication of agricultural drought

Using Remote Sensing Techniques to Improve Hydrological Predictions in a Rapidly Changing World

Remotely sensed geophysical datasets are being produced at increasingly fast rates to monitor various aspects of the Earth system in a rapidly changing world. The efficient and innovative use of these datasets to understand hydrological processes in various climatic and vegetation regimes under anthropogenic impacts has become an important challenge, but with a wide range of research opportunities. The ten contributions in this Special Issue have addressed the following four research topics: (1) Evapotranspiration estimation; (2) rainfall monitoring and prediction; (3) flood simulations and predictions; and (4) monitoring of ecohydrological processes using remote sensing techniques. Moreover, the authors have provided broader discussions on how to capitalize on state-of-the-art remote sensing techniques to improve hydrological model simulations and predictions, to enhance their skills in reproducing processes for the fast-changing world

JRC Experience on the Development of Drought Information Systems

From the definition of drought to its monitoring and assessment, this report summarizes the main steps towards an integrated drought information system. Europe, Africa and Latin America are examples, based on the experience of the JRC, that illustrate the challenges for establishing continental drought observatory initiatives. The document is structured in the following way: first an introduction explains what drought is and gives some examples of its impact in society; secondly the framework for establishing a drought monitoring system is described giving examples on the European Drought Observatory and on on-going activities in Africa and Latin America; thirdly the fundamental data and information for measuring drought is described; finally the setting up of an Integrated Drought Information System is discussed and two recent case studies, on Europe and on the Horn of Africa, are presented to illustrate the concept.JRC.H.7-Climate Risk Managemen

Agrometeorological forecasting

Agrometeorological forecasting covers all aspects of forecasting in agrometeorology. Therefore, the scope of agrometeorological forecasting very largely coincides with the scope of agrometeorology itself. All on-farm and regional agrometeorological planning implies some form of impact forecasting, at least implicitly, so that decision-support tools and forecasting tools largely overlap. In the current chapter, the focus is on crops, but attention is also be paid to sectors that are often neglected by the agrometeorologist, such as those occurring in plant and animal protection. In addition, the borders between meteorological forecasts for agriculture and agrometeorological forecasts are not always clear. Examples include the use of weather forecasts for farm operations such as spraying pesticides or deciding on trafficability in relation to adverse weather. Many forecast issues by various national institutions (weather, but also commodity prices or flood warnings) are vital to the farming community, but they do not constitute agrometeorological forecasts. (Modified From the introduction of the chapter: Scope of agrometeorological forecasting)JRC.H.4-Monitoring Agricultural Resource