Scientific Results

This catalogue is obtained by conducting a systematic literature review of scientific studies and reviews related to monitoring, forecasting, and simulating the inland water cycle. The analysis maps scientific expertise across research groups and classifies findings by the type of inland water studied, application focus, and geographical scope. A gap analysis will identify missing research areas and assess their relevance to policymaking.

ID ▲ Type Year Authors Title Venue/Journal DOI Research type Water System Technical Focus Abstract Link with Projects Link with Tools Related policies ID
publications-2801 Peer reviewed articles 2017 Omar Ali Eweys, Maria José Escorihuela, Josep M. Villar, Salah Er-Raki, Abdelhakim Amazirh, Luis Olivera, Lionel Jarlan, Saïd Khabba, Olivier Merlin Disaggregation of SMOS Soil Moisture to 100 m Resolution Using MODIS Optical/Thermal and Sentinel-1 Radar Data: Evaluation over a Bare Soil Site in Morocco Remote Sensing 10.3390/rs9111155 Uncategorized Uncategorized The 40 km resolution SMOS (Soil Moisture and Ocean Salinity) soil moisture, previously disaggregated at a 1 km resolution using the DISPATCH (DISaggregation based on Physical And Theoretical scale CHange) method based on MODIS optical/thermal data, is further disaggregated to 100 m resolution using Sentinel-1 backscattering coefficient (σ°). For this purpose, three distinct radar-based disaggregation methods are tested by linking the spatio-temporal variability of σ° and soil moisture data at the 1 km and 100 m resolution. The three methods are: (1) the weight method, which estimates soil moisture at 100 m resolution at a certain time as a function of σ° ratio (100 m to 1 km resolution) and the 1 km DISPATCH products of the same time; (2) the regression method which estimates soil moisture as a function of σ° where the regression parameters (e.g., intercept and slope) vary in space and time; and (3) the Cumulative Distribution Function (CDF) method, which estimates 100 m resolution soil moisture from the cumulative probability of 100 m resolution backscatter and the maximum to minimum 1 km resolution (DISPATCH) soil moisture difference. In each case, disaggregation results are evaluated against in situ measurements collected between 1 January 2016 and 11 October 2016 over a bare soil site in central Morocco. The determination coefficient (R2) between 1 km resolution DISPATCH and localized in situ soil moisture is 0.31. The regression and CDF methods have marginal effect on improving the DISPATCH accuracy at the station scale with a R2 between remotely sensed and in situ soil moisture of 0.29 and 0.34, respectively. By contrast, the weight method significantly improves the correlation between remotely sensed and in situ soil moisture with a R2 of 0.52. Likewise, the soil moisture estimates show low root mean square difference with in situ measurements (RMSD= 0.032 m3 m−3). 645642
publications-2802 Peer reviewed articles 2017 Jian Peng, Alexander Loew, Olivier Merlin, Niko E. C. Verhoest A review of spatial downscaling of satellite remotely sensed soil moisture Reviews of Geophysics 10.1002/2016rg000543 Uncategorized Irrigation Systems AbstractSatellite remote sensing technology has been widely used to estimate surface soil moisture. Numerous efforts have been devoted to develop global soil moisture products. However, these global soil moisture products, normally retrieved from microwave remote sensing data, are typically not suitable for regional hydrological and agricultural applications such as irrigation management and flood predictions, due to their coarse spatial resolution. Therefore, various downscaling methods have been proposed to improve the coarse resolution soil moisture products. The purpose of this paper is to review existing methods for downscaling satellite remotely sensed soil moisture. These methods are assessed and compared in terms of their advantages and limitations. This review also provides the accuracy level of these methods based on published validation studies. In the final part, problems and future trends associated with these methods are analyzed. 645642
publications-2803 Peer reviewed articles 2017 Qi Gao, Mehrez Zribi, Maria Escorihuela, Nicolas Baghdadi Synergetic Use of Sentinel-1 and Sentinel-2 Data for Soil Moisture Mapping at 100 m Resolution Sensors 10.3390/s17091966 IoT & Sensors Irrigation Systems The recent deployment of ESA’s Sentinel operational satellites has established a new paradigm for remote sensing applications. In this context, Sentinel-1 radar images have made it possible to retrieve surface soil moisture with a high spatial and temporal resolution. This paper presents two methodologies for the retrieval of soil moisture from remotely-sensed SAR images, with a spatial resolution of 100 m. These algorithms are based on the interpretation of Sentinel-1 data recorded in the VV polarization, which is combined with Sentinel-2 optical data for the analysis of vegetation effects over a site in Urgell (Catalunya, Spain). The first algorithm has already been applied to observations in West Africa by Zribi et al., 2008, using low spatial resolution ERS scatterometer data, and is based on change detection approach. In the present study, this approach is applied to Sentinel-1 data and optimizes the inversion process by taking advantage of the high repeat frequency of the Sentinel observations. The second algorithm relies on a new method, based on the difference between backscattered Sentinel-1 radar signals observed on two consecutive days, expressed as a function of NDVI optical index. Both methods are applied to almost 1.5 years of satellite data (July 2015–November 2016), and are validated using field data acquired at a study site. This leads to an RMS error in volumetric moisture of approximately 0.087 m3/m3 and 0.059 m3/m3 for the first and second methods, respectively. No site calibrations are needed with these techniques, and they can be applied to any vegetation-covered area for which time series of SAR data have been recorded. 645642
publications-2804 Peer reviewed articles 2016 Maria Jose Escorihuela, Pere Quintana-SeguĂ­ Comparison of remote sensing and simulated soil moisture datasets in Mediterranean landscapes Remote Sensing of Environment 10.1016/j.rse.2016.02.046 Uncategorized Irrigation Systems No abstract available 645642
publications-2805 Peer reviewed articles 2016 O. Merlin, V. G. Stefan, A. Amazirh, A. Chanzy, E. Ceschia, S. Er-Raki, P. Gentine, T. Tallec, J. Ezzahar, S. Bircher, J. Beringer, S. Khabba Modeling soil evaporation efficiency in a range of soil and atmospheric conditions using a meta-analysis approach Water Resources Research 10.1002/2015wr018233 Uncategorized Irrigation Systems AbstractA meta‐analysis data‐driven approach is developed to represent the soil evaporative efficiency (SEE) defined as the ratio of actual to potential soil evaporation. The new model is tested across a bare soil database composed of more than 30 sites around the world, a clay fraction range of 0.02–0.56, a sand fraction range of 0.05–0.92, and about 30,000 acquisition times. SEE is modeled using a soil resistance (rss) formulation based on surface soil moisture (θ) and two resistance parameters and θefolding. The data‐driven approach aims to express both parameters as a function of observable data including meteorological forcing, cut‐off soil moisture value at which SEE=0.5, and first derivative of SEE at , named . An analytical relationship between and is first built by running a soil energy balance model for two extreme conditions with rss = 0 and using meteorological forcing solely, and by approaching the middle point from the two (wet and dry) reference points. Two different methods are then investigated to estimate the pair either from the time series of SEE and θ observations for a given site, or using the soil texture information for all sites. The first method is based on an algorithm specifically designed to accomodate for strongly nonlinear relationships and potentially large random deviations of observed SEE from the mean observed . The second method parameterizes as a multi‐linear regression of clay and sand percentages, and sets to a constant mean value for all sites. The new model significantly outperformed the evaporation modules of ISBA (Interaction Sol‐Biosphère‐Atmosphère), H‐TESSEL (Hydrology‐Tiled ECMWF Scheme for Surface Exchange over Land), and CLM (Community Land Model). It has potential for integration in various land‐surface schemes, and real calibration capabilities using combined thermal and microwave remote sensing data. 645642
publications-2806 Peer reviewed articles 2017 A. Ayyoub, S. Er-Raki, S. Khabba, O. Merlin, J. Ezzahar, J.C. Rodriguez, A. Bahlaoui, A. Chehbouni A simple and alternative approach based on reference evapotranspiration and leaf area index for estimating tree transpiration in semi-arid regions Agricultural Water Management 10.1016/j.agwat.2017.04.005 Data Management & Analytics Uncategorized No abstract available 645642
publications-2807 Peer reviewed articles 2018 Bouchra Ait Hssaine, Olivier Merlin, Zoubair Rafi, Jamal Ezzahar, Lionel Jarlan, SaĂŻd Khabba, Salah Er-Raki Calibrating an evapotranspiration model using radiometric surface temperature, vegetation cover fraction and near-surface soil moisture data Agricultural and Forest Meteorology 10.1016/j.agrformet.2018.02.033 Simulation & Modeling Uncategorized No abstract available 645642
publications-2808 Peer reviewed articles 2018 Houda Nassah, Salah Er-Raki, Said Khabba, Younes Fakir, Fatima Raibi, Olivier Merlin, Bernard Mougenot Evaluation and analysis of deep percolation losses of drip irrigated citrus crops under non-saline and saline conditions in a semi-arid area Biosystems Engineering 10.1016/j.biosystemseng.2017.10.017 Simulation & Modeling Irrigation Systems No abstract available 645642
publications-2809 Peer reviewed articles 2017 A. Diarra, L. Jarlan, S. Er-Raki, M. Le Page, G. Aouade, A. Tavernier, G. Boulet, J. Ezzahar, O. Merlin, S. Khabba Performance of the two-source energy budget (TSEB) model for the monitoring of evapotranspiration over irrigated annual crops in North Africa Agricultural Water Management 10.1016/j.agwat.2017.08.007 Simulation & Modeling Irrigation Systems No abstract available 645642
publications-2810 Peer reviewed articles 2017 Abdelhakim Amazirh, Salah Er-Raki, Abdelghani Chehbouni, Vincent Rivalland, Alhousseine Diarra, Said Khabba, Jamal Ezzahar, Olivier Merlin Modified Penman–Monteith equation for monitoring evapotranspiration of wheat crop: Relationship between the surface resistance and remotely sensed stress index Biosystems Engineering 10.1016/j.biosystemseng.2017.09.015 Simulation & Modeling Irrigation Systems No abstract available 645642