The SAFRAN-ISBA-MODCOU hydrometeorological model applied over France

An edited version of this paper was published by AGU. Copyright (2008) American Geophysical UnionThe hydrometeorological model SIM consists in a meterological analysis system (SAFRAN), a land surface model (ISBA) and a hydrogeological model (MODCOU). It generates atmospheric forcing at an hourly time step, and it computes water and surface energy budgets, the river ow at more than 900 rivergauging stations, and the level of several aquifers. SIM was extended over all of France in order to have a homogeneous nation-wide monitoring of the water resources: it can therefore be used to forecast flood risk and to monitor drought risk over the entire nation. The hydrometeorologival model was applied over a 10-year period from 1995 to 2005. In this paper the databases used by the SIM model are presented, then the 10-year simulation is assessed by using the observations of daily stream-flow, piezometric head, and snow depth. This assessment shows that SIM is able to reproduce the spatial and temporal variabilities of the water fluxes. The efficiency is above 0.55 (reasonable results) for 66 % of the simulated rivergages, and above 0.65 (rather good results) for 36 % of them. However, the SIM system produces worse results during the driest years, which is more likely due to the fact that only few aquifers are simulated explicitly. The annual evolution of the snow depth is well reproduced, with a square correlation coeficient around 0.9 over the large altitude range in the domain. The stream ow observations were used to estimate the overall error of the simulated latent heat ux, which was estimated to be less than 4 %

Testing MOS precipitation downscaling for ENSEMBLES regional climate models over Spain

Model Output Statistics (MOS) has been recently proposed as an alternative to the standard perfect prognosis statistical downscaling approach for Regional Climate Model (RCM) outputs. In this case, the model output for the variable of interest (e.g. precipitation) is directly downscaled using observations. In this paper we test the performance of a MOS implementation of the popular analog methodology (referred to as MOS analog) applied to downscale daily precipitation outputs over Spain. To this aim, we consider the state‐of‐the‐art ERA40‐driven RCMs provided by the EU‐funded ENSEMBLES project and the Spain02 gridded observations data set, using the common period 1961–2000. The MOS analog method improves the representation of the mean regimes, the annual cycle, the frequency and the extremes of precipitation for all RCMs, regardless of the region and the model reliability (including relatively low‐performing models), while preserving the daily accuracy. The good performance of the method in this complex climatic region suggests its potential transferability to other regions. Furthermore, in order to test the robustness of the method in changing climate conditions, a cross‐validation in driest or wettest years was performed. The method improves the RCM results in both cases, especially in the former

Comparison of past and future Mediterranean high and low extremes of precipitation and river flow projected using different statistical downscaling methods

The extremes of precipitation and river flow obtained using three different statistical downscaling methods applied to the same regional climate simulation have been compared. The methods compared are the anomaly method, quantile mapping and a weather typing. The hydrological model used in the study is distributed and it is applied to the Mediterranean basins of France. The study shows that both quantile mapping and weather typing methods are able to reproduce the high and low precipitation extremes in the region of interest. The study also shows that when the hydrological model is forced with these downscaled data, there are important differences in the outputs. This shows that the model amplifies the differences and that the downscaling of other atmospheric variables might be very relevant when simulating river discharges. In terms of river flow, the method of the anomalies, which is very simple, performs better than expected. The methods produce qualitatively similar future scenarios of the extremes of river flow. However, quantitatively, there are still significant differences between them for each individual gauging station. According to these scenarios, it is expected that in the middle of the 21st century (2035–2064), the monthly low flows will have diminished almost everywhere in the region of our study by as much as 20 %. Regarding high flows, there will be important increases in the area of the Cévennes, which is already seriously affected by flash-floods. For some gauging stations in this area, the frequency of what was a 10-yr return flood at the end of the 20th century is expected to increase, with such return floods then occurring every two years in the middle of the 21st century. Similarly, the 10-yr return floods at that time are expected to carry 100 % more water than the 10-yr return floods experienced at the end of the 20th century. In the northern part of the Rhône basin, these extremes will be reduced

Improvement, calibration and validation of a distributed hydrological model over France

The hydrometeorological model SAFRAN-ISBA-MODCOU (SIM) computes water and energy budgets on the land surface and riverflows and the level of several aquifers at the scale of France. SIM is composed of a meteorological analysis system (SAFRAN), a land surface model (ISBA), and a hydrogeological model (MODCOU). In this study, an exponential profile of hydraulic conductivity at saturation is introduced to the model and its impact analysed. It is also studied how calibration modifies the performance of the model. A very simple method of calibration is implemented and applied to the parameters of hydraulic conductivity and subgrid runoff. The study shows that a better description of the hydraulic conductivity of the soil is important to simulate more realistic discharges. It also shows that the calibrated model is more robust than the original SIM. In fact, the calibration mainly affects the processes related to the dynamics of the flow (drainage and runoff), and the rest of relevant processes (like evaporation) remain stable. It is also proven that it is only worth introducing the new empirical parameterization of hydraulic conductivity if it is accompanied by a calibration of its parameters, otherwise the simulations can be degraded. In conclusion, it is shown that the new parameterization is necessary to obtain good simulations. Calibration is a tool that must be used to improve the performance of distributed models like SIM that have some empirical parameters

Irrigation mapping using statistics of Sentinel-1 time series

International audienceThis paper presents the methodology for irrigation mapping using the Sentinel-1 SAR data. The study is performed using VV polarization over an agricultural site in Urgell, Catalunya (Spain). From the time series for each field, the indices including the mean value and variance of the signal, the correlation length, the fractal dimension which are derived from the backscatter time series are analyzed. The classification of irrigated and nonirrigated fields is done with the indices vector formed by the parameters analyzed. The result is compared with the supervised classification from Sentinel-2 multi-band data. The accuracy is 77%. The methodology uses only SAR data, which makes it usable for all areas even with cloud cover most times of the year

The SAFRAN daily gridded precipitation product in Tunisia (1979–2015)

International audienc