Combining remote sensing and GIS climate modelling to estimate daily forest evapotranspiration in a Mediterranean mountain area

Evapotranspiration monitoring allows us to assess the environmental stress on forest and agricultural ecosystems. Nowadays, Remote Sensing and Geographical Information Systems (GIS) are the main techniques used for calculating evapotranspiration at catchment and regional scales. In this study we present a methodology, based on the energy balance equation (B-method), that combines remote sensing imagery with GIS-based climate modelling to estimate daily evapotranspiration (ETd) for several dates between 2003 and 2005. The three main variables needed to compute ETd were obtained as follows: (i) Land surface temperature by means of the Landsat-5 TM and Landsat-7 ETM+ thermal band, (ii) air temperature by means of multiple regression analysis and spatial interpolation from meteorological ground stations data at satellite pass, and (iii) net radiation by means of the radiative balance. We calculated ETd using remote sensing data at different spatial and temporal scales (Landsat-7 ETM+, Landsat-5 TM and TERRA/AQUA MODIS, with a spatial resolution of 60, 120 and 1000 m, respectively) and combining three different approaches to calculate the B parameter, which represents an average bulk conductance for the daily-integrated sensible heat flux. We then compared these estimates with sap flow measurements from a Scots pine (Pinus sylvestris L.) stand in a Mediterranean mountain area. This procedure allowed us to better understand the limitations of ETd modelling and how it needs to be improved, especially in heterogeneous forest areas. The method using Landsat data resulted in a good agreement, R2 test of 0.89, with a mean RMSE value of about 0.6 mm day−1 and an estimation error of ±30 %. The poor agreement obtained using TERRA/AQUA MODIS, with a mean RMSE value of 1.8 and 2.4 mm day−1 and an estimation error of about ±57 and 50 %, respectively. This reveals that ETd retrieval from coarse resolution remote sensing data is troublesome in these heterogeneous areas, and therefore further research is necessary on this issue. Finally, implementing regional GIS-based climate models as inputs in ETd retrieval have has provided good results, making possible to compute ETd at regional scales

A Review of Current Methodologies for Regional Evapotranspiration Estimation from Remotely Sensed Data

An overview of the commonly applied evapotranspiration (ET) models using remotely sensed data is given to provide insight into the estimation of ET on a regional scale from satellite data. Generally, these models vary greatly in inputs, main assumptions and accuracy of results, etc. Besides the generally used remotely sensed multi-spectral data from visible to thermal infrared bands, most remotely sensed ET models, from simplified equations models to the more complex physically based two-source energy balance models, must rely to a certain degree on ground-based auxiliary measurements in order to derive the turbulent heat fluxes on a regional scale. We discuss the main inputs, assumptions, theories, advantages and drawbacks of each model. Moreover, approaches to the extrapolation of instantaneous ET to the daily values are also briefly presented. In the final part, both associated problems and future trends regarding these remotely sensed ET models were analyzed to objectively show the limitations and promising aspects of the estimation of regional ET based on remotely sensed data and ground-based measurements

Remote sensing of water use and water stress in the African savanna ecosystem at local scale – Development and validation of a monitoring tool

Savannas are among the most productive biomes of Africa, where they comprise half of its surface. They support wildlife, livestock, rangelands, crops, and livelihoods, playing an important socioeconomic role in rural areas. These water-limited ecosystems with seasonal water availability are highly sensitive to changes in both climate conditions, and in land-use/management practices. Although monitoring programs for African savanna water use have been established in certain areas, most of them are largely restricted to point based measurements or coarse scales, and are not fully capable to provide distributed timely information for planning purposes. In this study we develop a mechanism for monitoring the water used by African savanna from fine scale (meters) to watershed scale, integrating the effects of the water stress. Our hypothesis is that the Ecosystem Stress Index (ESI) is a valuable tool to downscale estimates of actual evapotranspiration at coarse scale, to high resolutions. To monitor savanna water fluxes in a semi-continuous way this study integrates two different ET-estimation approaches: KC-FAO56 model, integrating reflectance-based “crop” coefficients (SPOT 4 & 5 satellites), is used to derive unstressed savanna evapotranspiration (with high spatial resolution), and the two-source surface energy balance model -TSEB, integrating radiometric surface temperature (AATSR satellites) allows the determination of water stress across savannas (ESI, with low spatial resolution). The difference between estimated and observed surface fluxes derived from TSEB (RMSDLE = 53 Wm-2, RMSDH = 50 Wm-2, RMSDRn = 60 Wm-2, RMSDG = 21 Wm-2) were of the same magnitude as the uncertainties derived from the flux measurement system, being sufficiently accurate to be employed in a distributed way and on a more regular basis. The approach of ESI to downscale ET proved to be useful, and errors between estimated and observed daily ET (RMSD 0.6 mmday−1) were consistent with the results of other studies in savanna ecosystems. The modelling framework proposed provided an accurate representation of the natural landscape heterogeneity and local conditions, with the potential of providing information suitable from local to broader scales.info:eu-repo/semantics/publishedVersio

Assessment of the hydrological effect of drought and fire events on evapotranspiration at a regional scale

Doutoramento em Engenharia Florestal e dos Recursos Naturais - Instituto Superior de Agronomia / ULUntil today, there is only little knowledge about the behavior of actual evapotranspiration (ETa) before and after wildfires in Portugal, which can be estimated from remote sensing techniques. In this thesis, an existing Simplified Two-Source Energy Balance model (STSEB) was adapted, based on moderate resolution imagery to estimate ETa and its contributing parts of transpiration and evaporation. The study served to test the model and its precision. A bias of about 1 mm d1 for the estimated ETa was observed, where evaporation was regularly overestimated and transpiration underestimated. This error is acceptable for two-layer models based on satellite imagery, but estimates cannot be used for irrigation management. The evolution of the estimated ETa after wildfires (up to four years) was analyzed at eucalypt stands at the Caramulo mountain range in Portugal. By investigating the recovery of ETa after wildfire, the difference between burnt and unburnt stands was mainly related to fire severity and stand characteristics. Two to three years after the fire events, the difference between burnt and unburnt stands became nonsignificant for all severity classes. At the same region, the prediction of soil moisture deficit from drought indices was tested. The drought indices empirically estimate the dryness of an area and are directly related to fire danger. They are based on a simple water balance equation where effective rainfall and ETa are the only input and output, respectively. In this work the empirical equation of (ETa) was substituted by the estimated ETa from STSEB, which enhanced the spatial resolution of the drought indices, being regularly interpolated from point estimates. Spatial patterns of soil moisture deficit were predicted, which indicated a relationship to fire occurrences. To conclude, the ETa estimated by the remote sensing based STSEB model, was used to make observations of the water cycle on a regional scale. In contrast to other post-fire studies, eucalypt stands in Portugal were found to be subject to a smaller hydrological impact after wildfires. This implies a fast recovery and a smaller influence on streamflow and groundwater resources. Furthermore, the drought indices, using the ETa from STSEB, identified areas with higher proneness to drought, by improving the spatial resolution, using satellite imagery compared to traditional interpolation techniques. The results support fire danger rating and might help to improve fire regime and forest managementN/

Integrating ASCAT surface soil moisture and GEOV1 leaf area index into the SURFEX modelling platform: a land data assimilation application over France

The land monitoring service of the European Copernicus programme has developed a set of satellite-based biogeophysical products, including surface soil moisture (SSM) and leaf area index (LAI). This study investigates the impact of joint assimilation of remotely sensed SSM derived from Advanced Scatterometer (ASCAT) backscatter data and the Copernicus Global Land GEOV1 satellite-based LAI product into the the vegetation growth version of the Interactions between Soil Biosphere Atmosphere (ISBA-A-gs) land surface model within the the externalised surface model (SURFEX) modelling platform of Météo-France. The ASCAT data were bias corrected with respect to the model climatology by using a seasonal-based CDF (Cumulative Distribution Function) matching technique. A multivariate multi-scale land data assimilation system (LDAS) based on the extended Kalman Filter (EKF) is used for monitoring the soil moisture, terrestrial vegetation, surface carbon and energy fluxes across the domain of France at a spatial resolution of 8 km. Each model grid box is divided into a number of land covers, each having its own set of prognostic variables. The filter algorithm is designed to provide a distinct analysis for each land cover while using one observation per grid box. The updated values are aggregated by computing a weighted average. <br><br> In this study, it is demonstrated that the assimilation scheme works effectively within the ISBA-A-gs model over a four-year period (2008–2011). The EKF is able to extract useful information from the data signal at the grid scale and distribute the root-zone soil moisture and LAI increments throughout the mosaic structure of the model. The impact of the assimilation on the vegetation phenology and on the water and carbon fluxes varies from one season to another. The spring drought of 2011 is an interesting case study of the potential of the assimilation to improve drought monitoring. A comparison between simulated and in situ soil moisture gathered at the twelve SMOSMANIA (Soil Moisture Observing System–Meteorological Automatic Network Integrated Application) stations shows improved anomaly correlations for eight stations

Sustainable Agriculture and Advances of Remote Sensing (Volume 1)

Agriculture, as the main source of alimentation and the most important economic activity globally, is being affected by the impacts of climate change. To maintain and increase our global food system production, to reduce biodiversity loss and preserve our natural ecosystem, new practices and technologies are required. This book focuses on the latest advances in remote sensing technology and agricultural engineering leading to the sustainable agriculture practices. Earth observation data, in situ and proxy-remote sensing data are the main source of information for monitoring and analyzing agriculture activities. Particular attention is given to earth observation satellites and the Internet of Things for data collection, to multispectral and hyperspectral data analysis using machine learning and deep learning, to WebGIS and the Internet of Things for sharing and publishing the results, among others