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This study evaluates the impact of assimilating surface soil moisture (SSM)and leaf area index (LAI) observations into a land surface model using theSAFRAN–ISBA–MODCOU (SIM) hydrological suite. SIM consists of three stages:(1) an atmospheric reanalysis (SAFRAN) over France, which forces (2) thethree-layer ISBA land surface model, which then provides drainage and runoffinputs to (3) the MODCOU hydro-geological model. The drainage and runoffoutputs from ISBA are validated by comparing the simulated river dischargefrom MODCOU with over 500 river-gauge observations over France and with asubset of stations with low-anthropogenic influence, over several years.This study makes use of the A-gs version of ISBA that allows forphysiological processes. The atmospheric forcing for the ISBA-A-gs modelunderestimates direct shortwave and long-wave radiation by approximately5 % averaged over France. The ISBA-A-gs model also substantiallyunderestimates the grassland LAI compared with satellite retrievals duringwinter dormancy. These differences result in an underestimation(overestimation) of evapotranspiration (drainage and runoff). The excessrunoff flowing into the rivers and aquifers contributes to an overestimationof the SIM river discharge. Two experiments attempted to resolve theseproblems: (i) a correction of the minimum LAI model parameter for grasslandsand (ii) a bias-correction of the model radiative forcing.Two data assimilation experiments were also performed, which are designed to correctrandom errors in the initial conditions: (iii) the assimilation of LAIobservations and (iv) the assimilation of SSM and LAI observations. The dataassimilation for (iii) and (iv) was done with a simplified extended Kalmanfilter (SEKF), which uses finite differences in the observation operatorJacobians to relate the observations to the model variables. Experiments(i) and (ii) improved the median SIM Nash scores by about 9 % and18 % respectively. Experiment (iii) reduced the LAI phase errors inISBA-A-gs but had little impact on the discharge Nash efficiency of SIM. Incontrast, experiment (iv) resulted in spurious increases in drainage andrunoff, which degraded the median discharge Nash efficiency by about7 %. The poor performance of the SEKF originates from the observationoperator Jacobians. These Jacobians are dampened when the soil is saturatedand when the vegetation is dormant, which leads to positive biases indrainage and/or runoff and to insufficient corrections during winter, respectively.Possible ways to improve the model are discussed, including a new multi-layerdiffusion model and a more realistic response of photosynthesis totemperature in mountainous regions. The data assimilation should be advancedby accounting for model and forcing uncertainties

The effect of satellite-derived surface soil moisture and leaf area index land data assimilation on streamflow simulations over France