A simple groundwater scheme in the TRIP river routing model: global off-line evaluation against GRACE terrestrial water storage estimates and observed river discharges

Vergnes, Jean-Pierre; Decharme, Bertrand

doi:10.5194/hess-16-3889-2012

Cited by 44 publications

(63 citation statements)

References 65 publications

(101 reference statements)

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“…The use of a multilayer snow model of intermediate complexity (Boone & Etchevers, ; Decharme et al, ) allows separate water and energy budgets to be simulated for the soil and the snowpack. A two‐way coupling between ISBA DF and CTRIP is set up to account for, first, a dynamic river flooding scheme in which floodplains interact with the soil and the atmosphere through free‐water evaporation, infiltration, and precipitation interception (Decharme et al, ) and second, a two‐dimensional diffusive groundwater scheme to represent unconfined aquifers and upward capillarity fluxes into the superficial soil (Vergnes et al, , ; Vergnes & Decharme, ).…”

Section: Review Of Land Surface Systemsmentioning

confidence: 99%

“…River streamflow can affect the salinity and temperature of the ocean at the mouths of the largest rivers (Durand et al, ; Huang & Mehta, ; Jahfer et al, ; McGuire et al, ; Vinayachandran et al, ). Groundwater has a well‐documented influence on the land water budget, especially on river discharges (Habets et al, ; Vergnes et al, ; Vergnes & Decharme, ). Through their slow response time, they sustain river base flow in humid climates during dry periods, while they receive river seepage in arid climates.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Recent Changes in the ISBA‐CTRIP Land Surface System for Use in the CNRM‐CM6 Climate Model and in Global Off‐Line Hydrological Applications

Decharme

Delire

Marie

et al. 2019

J Adv Model Earth Syst

176

232

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In recent years, significant efforts have been made to upgrade physical processes in the ISBA‐CTRIP land surface system for use in fully coupled climate studies using the new CNRM‐CM6 climate model or in stand‐alone mode for global hydrological applications. Here we provide a thorough description of the new and improved processes implemented between the CMIP5 and CMIP6 versions of the model and evaluate the hydrology and thermal behavior of the model at the global scale. The soil scheme explicitly solves the one‐dimensional Fourier and Darcy laws throughout the soil, accounting for the dependency of hydraulic and thermal soil properties on soil organic carbon content. The snowpack is represented using a multilayer detailed internal‐process snow scheme. A two‐way dynamic flood scheme is added in which floodplains interact with the soil hydrology through reinfiltration of floodwater and with the overlying atmosphere through surface free‐water evaporation. Finally, groundwater processes are represented via a two‐dimensional diffusive unconfined aquifer scheme allowing upward capillarity rises into the superficial soil. This new system has been evaluated in off‐line mode using two different atmospheric forcings and against a large set of satellite estimates and in situ observations. While this study is not without weaknesses, its results show a real advance in modeling the physical aspects of the land surface with the new ISBA‐CTRIP version compared to the previous system. This increases our confidence that the model is able to represent the land surface physical processes accurately across the globe and in turn contribute to several important scientific and societal issues.

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Section: Review Of Land Surface Systemsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Recent Changes in the ISBA‐CTRIP Land Surface System for Use in the CNRM‐CM6 Climate Model and in Global Off‐Line Hydrological Applications

Decharme

Delire

Marie

et al. 2019

J Adv Model Earth Syst

176

232

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“…At last, the groundwater scheme (Vergnes and Decharme, 2012) is based on the two-dimensional groundwater flow equation for the piezometric head. Its coupling with ISBA permits the presence of a water table under the soil moisture column to be accounted for, allowing upward capillary fluxes into the soil (Vergnes et al, 2014).…”

Section: Ctrip River Routingmentioning

confidence: 99%

Sequential assimilation of satellite-derived vegetation and soil moisture products using SURFEX_v8.0: LDAS-Monde assessment over the Euro-Mediterranean area

et al. 2017

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Abstract. In this study, a global land data assimilation system (LDAS-Monde) is applied over Europe and the Mediterranean basin to increase monitoring accuracy for land surface variables. LDAS-Monde is able to ingest information from satellite-derived surface soil moisture (SSM) and leaf area index (LAI) observations to constrain the interactions between soil–biosphere–atmosphere (ISBA, Interactions between Soil, Biosphere and Atmosphere) land surface model (LSM) coupled with the CNRM (Centre National de Recherches Météorologiques) version of the Total Runoff Integrating Pathways (ISBA-CTRIP) continental hydrological system. It makes use of the CO2-responsive version of ISBA which models leaf-scale physiological processes and plant growth. Transfer of water and heat in the soil rely on a multilayer diffusion scheme. SSM and LAI observations are assimilated using a simplified extended Kalman filter (SEKF), which uses finite differences from perturbed simulations to generate flow dependence between the observations and the model control variables. The latter include LAI and seven layers of soil (from 1 to 100 cm depth). A sensitivity test of the Jacobians over 2000–2012 exhibits effects related to both depth and season. It also suggests that observations of both LAI and SSM have an impact on the different control variables. From the assimilation of SSM, the LDAS is more effective in modifying soil moisture (SM) from the top layers of soil, as model sensitivity to SSM decreases with depth and has almost no impact from 60 cm downwards. From the assimilation of LAI, a strong impact on LAI itself is found. The LAI assimilation impact is more pronounced in SM layers that contain the highest fraction of roots (from 10 to 60 cm). The assimilation is more efficient in summer and autumn than in winter and spring. Results shows that the LDAS works well constraining the model to the observations and that stronger corrections are applied to LAI than to SM. A comprehensive evaluation of the assimilation impact is conducted using (i) agricultural statistics over France, (ii) river discharge observations, (iii) satellite-derived estimates of land evapotranspiration from the Global Land Evaporation Amsterdam Model (GLEAM) project and (iv) spatially gridded observation-based estimates of upscaled gross primary production and evapotranspiration from the FLUXNET network. Comparisons with those four datasets highlight neutral to highly positive improvement.

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“…Vergnes and Decharme (2012) implemented a simple groundwater scheme coupled to the river channel in each model grid cell allowing bidirectional water exchanges through the riverbed.…”

Section: River Dischargementioning

confidence: 99%

“…Several studies have compared LSM simulated land water storage to GRACE estimates (see e.g. Alkama et al, 2010;Becker et al, 2011;Grippa et al, 2011;Vergnes and Decharme, 2012). If integrated with the evaluation of other components of the land water cycle, these 15 comparisons could help back-tracking the error sources of LSM simulations.…”

Section: River Dischargementioning

confidence: 99%

Hydrological assessment of atmospheric forcing uncertainty in the Euro-Mediterranean area using a land surface model

Gelati¹,

Decharme²,

Calvet³

et al. 2017

Preprint

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Abstract. The understanding of land surface hydrology is critical for planning human activities involving freshwater 10 resources. We assess how atmospheric forcing data uncertainties affect land surface model (LSM) simulations by means of an extensive evaluation exercise using a number of state-of-the-art remote sensing and station-based datasets. discharge. The atmospheric forcing data are also compared to reference datasets. Precipitation is the most uncertain forcing variable across datasets, while the most consistent are air temperature, and SW and LW radiation. At the monthly time scale, SSM and LAI simulations are relatively insensitive to forcing uncertainties. Some discrepancies with ESA-CCI appear to be forcing-independent and may be due to different assumptions underlying the LSM and the remote sensing retrieval algorithm. All simulations overestimate average summer and early autumn LAI. Forcing uncertainty impacts on simulated 25 river discharge are larger on mean values and standard deviations than on correlations with GRDC data. Anomaly correlation coefficients are not inferior to those computed from raw monthly discharge time series, indicating that the model reproduces inter-annual variability fairly well. However, simulated river discharge time series generally feature larger variability compared to measurements. They also tend to overestimate winter-spring high flows and underestimate summer-autumn low flows. Considering that several differences emerge between simulations and reference data, which may not be completely 30 explained by forcing uncertainty, we suggest several research directions. These range from further investigating the Hydrol. Earth Syst. Sci. Discuss., https://doi

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A simple groundwater scheme in the TRIP river routing model: global off-line evaluation against GRACE terrestrial water storage estimates and observed river discharges

Cited by 44 publications

References 65 publications

Recent Changes in the ISBA‐CTRIP Land Surface System for Use in the CNRM‐CM6 Climate Model and in Global Off‐Line Hydrological Applications

Recent Changes in the ISBA‐CTRIP Land Surface System for Use in the CNRM‐CM6 Climate Model and in Global Off‐Line Hydrological Applications

Sequential assimilation of satellite-derived vegetation and soil moisture products using SURFEX_v8.0: LDAS-Monde assessment over the Euro-Mediterranean area

Hydrological assessment of atmospheric forcing uncertainty in the Euro-Mediterranean area using a land surface model

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