Evaluation of land surface model simulations of evapotranspiration over a 12-year crop succession: impact of soil hydraulic and vegetation properties

Garrigues, Sébastien; Olioso, Albert; Calvet, Jean‐Christophe; Martin, E.; Lafont, S.; Moulin, Sophie; Chanzy, André; Marloie, Olivier; Buis, Samuel; Desfonds, Veronique; Bertrand, Nadine; Renard, D.

doi:10.5194/hess-19-3109-2015

Cited by 28 publications

(71 citation statements)

References 82 publications

(99 reference statements)

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“…We provide here the main characteristic of the Avignon experimental site, details can be found in Garrigues et al (2015).…”

Section: Site and In Situ Datamentioning

confidence: 99%

“…The total latent heat flux is simulated by computing individual estimates of soil evaporation and plant transpiration fluxes. Detailed explanations on how soil evaporation is computed can be found in Garrigues et al (2015). The stomatal conductance used to compute the plant transpiration is simulated using the A-gs version of ISBA.…”

Section: The Isba-a-gs Modelmentioning

confidence: 99%

“…The irrigation was accounted for by adding the actual irrigation amount to rainfall. We use the local values of the soil moisture at saturation, the soil moisture at field capacity and the soil moisture at wilting derived from field measurements of soil moisture (Garrigues et al, 2015) instead of the pedotransfer function estimates used in the standard implementation of the model. The rest of the model parameters take the standard values given by the ECOCLIMAP-II database for the C3 crop, the C4 crop and the bare soil patches (Gibelin et al, 2006;.…”

Section: Control Runmentioning

confidence: 99%

“…Their spatial and temporal resolution may not be fine enough to represent the cropland dynamic. Garrigues et al (2015) highlight the large impact of the succession of crop cycle and inter-crop periods on the temporal dynamic of ET over a long period of time. Finally, agricultural land management such as irrigation can significantly influence the surface energy and water balance (de Rosnay et al, 2003;Olioso et al, 2005;Puma and Cook, 2010) but irrigation is rarely accounted for in land surface modelling at large scale.…”

Section: Introductionmentioning

confidence: 95%

“…The soil texture is generally used to infer the soil hydrodynamic properties through pedotransfer functions (Espino et al, 1996;Baroni et al, 2010). It is a key variable for the spatial integration of the model since the soil properties explain a large part of ET uncertainties (Braud et al, 1995;Garrigues et al, 2015). The vegetation dynamic is represented by the leaf area index (LAI) cycle.…”

Section: Introductionmentioning

confidence: 99%

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Impact of climate, vegetation, soil and crop management variables on multi-year ISBA-A-gs simulations of evapotranspiration over a Mediterranean crop site

Garrigues

Olioso

Carrer³

et al. 2015

Geosci. Model Dev.

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Abstract. Generic land surface models are generally driven by large-scale data sets to describe the climate, the soil properties, the vegetation dynamic and the cropland management (irrigation). This paper investigates the uncertainties in these drivers and their impacts on the evapotranspiration (ET) simulated from the Interactions between Soil, Biosphere, and Atmosphere (ISBA-A-gs) land surface model over a 12-year Mediterranean crop succession. We evaluate the forcing data sets used in the standard implementation of ISBA over France where the model is driven by the SAFRAN (Système d'Analyse Fournissant des Renseignements Adaptés à la Nivologie) high spatial resolution atmospheric reanalysis, the leaf area index (LAI) time courses derived from the ECOCLIMAP-II land surface parameter database and the soil texture derived from the French soil database. For climate, we focus on the radiations and rainfall variables and we test additional data sets which include the ERA-Interim (ERA-I) low spatial resolution reanalysis, the Global Precipitation Climatology Centre data set (GPCC) and the MeteoSat Second Generation (MSG) satellite estimate of downwelling shortwave radiations.The evaluation of the drivers indicates very low bias in daily downwelling shortwave radiation for ERA-I (2.5 W m −2 ) compared to the negative biases found for SAFRAN (−10 W m −2 ) and the MSG satellite (−12 W m −2 ). Both SAFRAN and ERA-I underestimate downwelling longwave radiations by −12 and −16 W m −2 , respectively. The SAFRAN and ERA-I/GPCC rainfall are slightly biased at daily and longer timescales (1 and 0.5 % of the mean rainfall measurement). The SAFRAN rainfall is more precise than the ERA-I/GPCC estimate which shows larger inter-annual variability in yearly rainfall error (up to 100 mm). The ECOCLIMAP-II LAI climatology does not properly resolve Mediterranean crop phenology and underestimates the bare soil period which leads to an overall overestimation of LAI over the crop succession. The simulation of irrigation by the model provides an accurate irrigation amount over the crop cycle but the timing of irrigation occurrences is frequently unrealistic.Errors in the soil hydrodynamic parameters and the lack of irrigation in the simulation have the largest influence on ET compared to uncertainties in the large-scale climate reanalysis and the LAI climatology. Among climate variables, the errors in yearly ET are mainly related to the errors in yearly rainfall. The underestimation of the available water capacity and the soil hydraulic diffusivity induce a large underestimation of ET over 12 years. The underestimation of radiations by the reanalyses and the absence of irrigation in the simulation lead to the underestimation of ET while the overall overestimation of LAI by the ECOCLIMAP-II climatology induces an overestimation of ET over 12 years.This work shows that the key challenges to monitor the water balance of cropland at regional scale concern the representation of the spatial distribution of the soil hydrodynamic Published by Cop...

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“…We provide here the main characteristic of the Avignon experimental site, details can be found in Garrigues et al (2015).…”

Section: Site and In Situ Datamentioning

confidence: 99%

Section: The Isba-a-gs Modelmentioning

confidence: 99%

Section: Control Runmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 95%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Impact of climate, vegetation, soil and crop management variables on multi-year ISBA-A-gs simulations of evapotranspiration over a Mediterranean crop site

Garrigues

Olioso

Carrer³

et al. 2015

Geosci. Model Dev.

Self Cite

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Modeling soil evaporation efficiency in a range of soil and atmospheric conditions using a meta‐analysis approach

Merlin

Stefan

Amazirh

et al. 2016

Water Resources Research

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International audienceA 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 ($r_{ss}$) formulation based on surface soil moisture ($\theta$) and two resistance parameters $r_{ss,ref}$ and $\theta_{efolding}$. The data-driven approach aims to express both parameters as a function of observable data including meteorological forcing, cut-off soil moisture value $\theta_{1/2}$ at which SEE=0.5, and first derivative of SEE at $\theta_{1/2}$, named $\Delta\theta_{1/2}^{-1}$. An analytical relationship between $(r_{ss,ref};\theta_{efolding})$ and $(\theta_{1/2};\Delta\theta_{1/2}^{-1})$ is first built by running a soil energy balance model for two extreme conditions with $r_{ss} = 0$ and $r_{ss}\sim\infty$ 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 $(\theta_{1/2} ; \Delta\theta_{1/2}^{-1})$ either from the time series of SEE and $\theta$ 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 $\text{SEE}(\theta)$ relationships and potentially large random deviations of observed SEE from the mean observed $\text{SEE}(\theta)$. The second method parameterizes $\theta_{1/2}$ as a multi-linear regression of clay and sand percentages, and sets $\Delta\theta_{1/2}^{-1}$ to a constant mean value for all sites. The new model significantly outperformed the evaporation modules of ISBA (Interaction Sol-Biosph\`{e}re-Atmosph\`{e}re), 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

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MODIS‐Based Estimates of Global Terrestrial Ecosystem Respiration

Jia

Epstein

et al. 2018

JGR Biogeosciences

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Terrestrial ecosystem respiration (Reco) represents a large carbon source from land to atmosphere and is highly spatiotemporally heterogeneous across scales. Upscaling of field‐measured respiration data using remote sensing information is urgently needed for understanding regional and global patterns of ecosystem respiration. Using Moderate Resolution Imaging Spectroradiometer (MODIS) data with resolutions of 1 km and 8 days and flux measurements from 171 sites (total of 812 site years) across the world from 2000 to 2014, we developed a semiempirical, yet physiologically based, remote sensing model, which can simulate Reco observed across most biomes with a small margin of error (R2 = 0.55, root‐mean‐square error = 1.67 gCm−2d−1, efficiency = 0.46, and mean bias error = 0.18 gCm−2d−1). The reference respiration at the annual mean nighttime land surface temperature (LST) can be well represented by MODIS enhanced vegetation index and LST. A comprehensive comparison of six respiration‐temperature (R‐T) models shows that the more physiologically based R‐T model (extended Arrhenius model) may be most suitable for estimating the respiration rate at higher latitudes. Integrating an effect of vegetation change on Reco in different biomes effectively improves estimates of Reco in almost all of the biomes.

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Evaluation of land surface model simulations of evapotranspiration over a 12-year crop succession: impact of soil hydraulic and vegetation properties

Cited by 28 publications

References 82 publications

Impact of climate, vegetation, soil and crop management variables on multi-year ISBA-A-gs simulations of evapotranspiration over a Mediterranean crop site

Impact of climate, vegetation, soil and crop management variables on multi-year ISBA-A-gs simulations of evapotranspiration over a Mediterranean crop site

Modeling soil evaporation efficiency in a range of soil and atmospheric conditions using a meta‐analysis approach

MODIS‐Based Estimates of Global Terrestrial Ecosystem Respiration

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