Assimilation of satellite data to optimize large-scale hydrological model parameters: a case study for the SWOT mission

International audienceDuring the last few decades, satellite measurements have been widely used to study the continental water cycle, especially in regions where in situ measurements are not readily available. The future Surface Water and Ocean Topography (SWOT) satellite mission will deliver maps of water surface elevation (WSE) with an unprecedented resolution and provide observation of rivers wider than 100 m and water surface areas greater than approximately 250 × 250 m over continental surfaces between 78 • S and 78 • N. This study aims to investigate the potential of SWOT data for parameter optimization for large-scale river routing models. The method consists in applying a data assimilation approach , the extended Kalman filter (EKF) algorithm, to correct the Manning roughness coefficients of the ISBA (In-teractions between Soil, Biosphere, and Atmosphere)-TRIP (Total Runoff Integrating Pathways) continental hydrologic system. Parameters such as the Manning coefficient, used within such models to describe water basin characteristics, are generally derived from geomorphological relationships, which leads to significant errors at reach and large scales. The current study focuses on the Niger Basin, a transboundary river. Since the SWOT observations are not available yet and also to assess the proposed assimilation method, the study is carried out under the framework of an observing system simulation experiment (OSSE). It is assumed that modeling errors are only due to uncertainties in the Manning coefficient. The true Manning coefficients are then supposed to be known and are used to generate synthetic SWOT observations over the period 2002-2003. The impact of the assimilation system on the Niger Basin hydrological cycle is then quantified. The optimization of the Manning coefficient using the EKF (extended Kalman filter) algorithm over an 18-month period led to a significant improvement of the river water levels. The relative bias of the water level is globally improved (a 30 % reduction). The relative bias of the Manning coefficient is also reduced (40 % reduction) and it converges towards an optimal value. Discharge is also improved by the assimilation, but to a lesser extent than for the water levels (7 %). Moreover, the method allows for a better simulation of the occurrence and intensity of flood events in the inner delta and shows skill in simulating the maxima and minima of water storage anomalies, especially in the groundwater and the aquifer reservoirs. The application of the assimilation method in the framework of an observing system simulation experiment allows evaluating the skill of the EKF algorithm to improve hydrological model parameters and to demonstrate SWOT's promising potential for global hydrol-ogy issues. However, further studies (e.g., considering multiple error sources and the difference between synthetic and real observations) are needed to achieve the evaluation of the method

Ob' river discharge from TOPEX/Poseidon satellite altimetry (1992–2002)

The paper discusses an application of the TOPEX/Poseidon (T/P) altimetry data to estimate the discharge of one of the largest Arctic rivers—the Ob' river. We first discuss the methodology to select and retrieve the altimeter water levels during the various phases of the hydrological regime. Then we establish the relationships between the satellite-derived water levels and the in situ river discharge measurements at the Salekhard gauging station near the Ob' estuary. The comparison of in situ and satellite-derived estimations of the Ob' discharge at Salekhard shows that the T/P data can successfully be used for hydrological studies of this river. We address the problems affecting the accuracy of the discharge estimations from altimeter measurements, identify potential solutions and suggest how satellite altimetry data may benefit hydrological studies of Arctic rivers

The Hydrological Modeling and Analysis Platform (HyMAP) : evaluation in the Amazon Basin

Recent advances in global flow routing schemes have shown the importance of using high-resolution topography for representing floodplain inundation dynamics more reliably. This study presents and evaluates the Hydrological Modeling and Analysis Platform (HyMAP), which is a global flow routing scheme specifically designed to bridge the gap between current state-of-the-art global flow routing schemes by combining their main features and introducing new features to better capture floodplain dynamics. The ultimate goals of HyMAP are to provide the scientific community with a novel scheme suited to the assimilation of satellite altimetry data for global water discharge forecasts and a model that can be potentially coupled with atmospheric models. In this first model evaluation, HyMAP is coupled with the Interactions between Soil-Biosphere-Atmosphere (ISBA) land surface model in order to simulate the surface water dynamics in the Amazon basin. The model is evaluated over the 1986-2006 period against an unprecedented source of information, including in situ and satellite-based datasets of water discharge and level, flow velocity, and floodplain extent. Results show that the model can satisfactorily simulate the large-scale features of the water surface dynamics of the Amazon River basin. Among all stream gauges considered, 23% have Nash-Sutcliffe coefficients (NS) higher than 0.50 and 68% above zero. About 28% of the stations have volume errors lower than 15%. Simulated discharges at Obidos had NS = 0.89. Time series of simulated floodplains at the basin scale agrees well with satellite-based estimates, with a relative error of 7% and correlation of 0.89. These results indicate nonnegligible improvements in comparison to previous studies for the same region

The impact of snow depth and snowmelt on the vegetation variability over central Siberia

We report the results of a joint analysis of NDVI data derived from NOAA-AVHRR and snow parameters (snow depth and snowmelt timing) derived from satellite passive microwave measurements over Central Siberia. We investigate the influence of interannual variability in snowmelt and snow depth on vegetation activity from 1989 to 2000. In addition to the effects of temperature and precipitation, we observe significant correlations between the snow parameters and the NDVI. Later snowmelt dates and thicker winter snowpacks are related to higher NDVI values over a large latitudinal band at about 65°N. This may be explained by either increased water availability for plants after snowmelt or thermal insulation of soil by snow. These results reflect the importance of snow-related winter processes on the vegetation development and on the carbon cycle in boreal regions