Estimation of actual evapotranspiration over a rainfed vineyard using a 1-D water transfer model : A case study within a Mediterranean watershed

The current study aims to evaluate the capabilities of soil water balance modeling to estimate ET for very different conditions of rainfed grapevine water status, within a vineyard landscape that depicts heterogeneities in canopy, soil and water table conditions. We calibrated the HYDRUS-1D model against measurements of the soil moisture profile within seven contrasted sites, we validated HYDRUS-1D sim-ulations against ET estimates derived from eddy covariance (EC) measurements within two contrasted sites, and we analyzed the temporal dynamics of the HYDRUS-1D ET simulations throughout almost two growth cycles for the seven sites. The calibration of HYDRUS-1D was correctly achieved, with a relative RMSE of 20% on average. Validation of HYDRUS-1D simulations against EC measurements was satisfactory, with RMSE values of about 40W m(-2) at the hourly timescale and 0.5 mm d(-1) at the daily timescale. HYDRUS-1D was able to provide consistent time series of ET within the seven contrasted sites and throughout the two growth cycles. We conclude that HYDRUS-1D simulations can be used as an alternative to EC measurements within rainfed vineyards, to alleviate experimental efforts for device cost and maintenance. Further, HYDRUS-1D simulations can be used for characterizing spatial variabili-ties and temporal dynamics, assessing impact of pedological conditions and land use on ET, or validating remote sensing retrievals over regional extents

Estimating the role of a ditch network in groundwater recharge in a Mediterranean catchment using a water balance approach

Water balance variables were monitored in a farmed Mediterranean catchment characterized by a dense ditch network to allow for the separate estimation of the diffuse and concentrated recharge terms during flood events. The 27 ha central part of the catchment was equipped with (i) rain gauges, (ii) ditch gauge stations, (iii) piezometers, (iv) neutron probes, and (v) an eddy covariance mast including a 3D sonic anemometer and a fast hygrometer. The water balance was calculated for two autumnal rain and flood events. We also estimated the uncertainty of this approach with Monte Carlo simulations. Results show, that although ditch area represents only 6% of the total study area, concentrated recharge appeared to be the main source of groundwater recharge. Indeed, it was 40-50% of the total groundwater recharge for autumnal events, which are the major annual recharge events. This indicate that both, concentrated and diffuse recharge should be taken into account in any hydrological modeling approach for Mediterranean catchments. This also means that, since they collect overland flow that is often largely contaminated by chemicals, ditches may be a place where groundwater contamination is likely to occur. The uncertainty analysis indicates that recharge estimates based on water balance exhibit large uncertainty ranges. Nevertheless, Monte Carlo simulations showed that concentrated recharge was higher than expected based on their area

Albedo and LAI estimates from FORMOSAT-2 data for crop monitoring

This paper aimed at estimating albedo and Leaf Area Index (LAI) from FORMOSAT-2 satellite that offers a unique source of high spatial resolution (eight meters) images with a high revisit frequency (one to three days). It mainly consisted of assessing the FORMOSAT-2 spectral and directional configurations that are unusual, with a single off nadir viewing angle over four visible-near infra red wavebands. Images were collected over an agricultural region located in South Eastern France, with a three day frequency from the growing season to post-harvest. Simultaneously, numerous ground based measurements were performed over various crops such as wheat, meadow, rice and maize. Albedo and LAI were estimated using empirical approaches that have been widely used for usual directional and spectral configurations (i.e. multidirectional or single nadir viewing angle over visible-near infrared wavebands). Two methods devoted to albedo estimation were assessed. based on stepwise multiple regression and neural network (NNT). Although both methods gave satisfactory results, the NNT performed better (relative RMSE=3.5% versus 7.3%), especially for low vegetation covers over dark or wet soils that corresponded to albedo values lower than 0.20. Four approaches for LAI estimation were assessed. The first approach based on a stepwise multiple regression over reflectances had the worst performance (relative RMSE=65%), when compared to the equally performing NDVI based heuristic relationship and reflectance based NNT approach (relative RMSE=34%).The NDVI based neural network approach had the best performance (relative RMSE=27.5%), due to the combination of NDVI efficient normalization properties and NNT flexibility. The high FORMOSAT-2 revisit frequency allowed next replicating the dynamics of albedo and LAI, and detecting to some extents cultural practices like vegetation cuts. It also allowed investigating possible relationships between albedo and LAI. The latter depicted specific trends according to vegetation types, and were very similar when derived from ground based data, remotely sensed observations or radiative transfer simulations. These relationships also depicted large albedo variabilities for low LAI values, which confirmed that estimating one variable from the other would yield poor performances for low vegetation cover with varying soil backgrounds. Finally, this empirical study demonstrated, in the context of exhaustively describing the spatiotemporal variability of surface properties, the potential synergy between 1) ground based web-sensors that continuously monitor specific biophysical variables over few locations, and 2) high spatial resolution satellite with high revisit frequencies

Assessing the potentialities of FORMOSAT-2 data for water and crop monitoring at small regional scale in South-Eastern France

International audienceWater monitoring at the scale of a small agricultural region is a key point to insure a good crop development particularly in South-Eastern France, where extreme climatic conditions result in long dry periods in spring and summer with very sparse precipitation events, corresponding to a crucial period of crop development. Remote sensing with the increasing imagery resolution is a useful tool to provide information on plant water status over various temporal and spatial scales. The current study focussed on assessing the potentialities of FORMOSAT-2 data, characterized by high spatial (8m pixel) and temporal resolutions (1-3 day/time revisit), to improve crop modeling and spatial estimation of the main land properties. Thirty cloud free images were acquired from March to October 2006 over a small region called Crau-Camargue in SE France, while numerous ground measurements were performed simultaneously over various crop types. We have compared two models simulating energy transfers between soil, vegetation and atmosphere: SEBAL and PBLs. Maps of evapotranspiration were analyzed according to the agricultural practices at field scale. These practices were well identified from FORMOSAT-2 images, which provided accurate input surface parameters to the SVAT models