Constraining a physically based Soil‐Vegetation‐Atmosphere Transfer model with surface water content and thermal infrared brightness temperature measurements using a multiobjective approach

Demarty, Jérôme; Ottlé, Catherine; Braud, Isabelle; Olioso, Albert; Frangi, Jean-Pierre; Gupta, H. V.; Bastidas, L. A.

doi:10.1029/2004wr003695

Cited by 47 publications

(54 citation statements)

References 58 publications

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“…The method has been widely applied in calibration of hydrological models [e.g., Vrugt et al, 2003;Leplastrier et al, 2002;Xia et al, 2002;Demarty et al, 2005].…”

Section: Methods For Multiple-criteria Optimizationmentioning

confidence: 99%

On the use of spatial regularization strategies to improve calibration of distributed watershed models

Pokhrel

Gupta

2010

Water Resources Research

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[1] Hydrologic models require the specification of unknown model parameters via calibration to historical input-output data. For spatially distributed models, the large number of unknowns makes the calibration problem poorly conditioned. Spatial regularization can help to stabilize the problem by facilitating inclusion of additional information. While a common regularization approach is to apply a scalar multiplier to the prior estimate of each parameter field, this can cause problems by simultaneously changing both the mean and the variance of the distribution. This paper explores a multiple-criteria regularization approach that facilitates adjustment of the mean, variance, and shape of the parameter distribution, using prior information to constrain the problem while providing sufficient degrees of freedom to enable model performance improvements. We also test simple squashing functions to help in maintaining conceptually reasonable parameter values throughout the spatial domain. We apply the method to three basins in the context of the Distributed Model Intercomparison Project (DMIP2), obtaining considerable performance improvements at the basin outlet. However, the prior parameter estimates are found to give much better performance at the interior points (treated as ungauged), suggesting that the spatial information has not been properly exploited. The results also suggest that basin outlet hydrographs may not be particularly sensitive to spatial parameter variability and that an overall basin mean value may be sufficient for flow forecasting at the outlet, although not at the interior points. We discuss weaknesses in our study approach and suggest diagnostically more powerful strategies to be pursued.Citation: Pokhrel, P., and H. V. Gupta (2010), On the use of spatial regularization strategies to improve calibration of distributed watershed models, Water Resour. Res., 46, W01505,

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“…The method has been widely applied in calibration of hydrological models [e.g., Vrugt et al, 2003;Leplastrier et al, 2002;Xia et al, 2002;Demarty et al, 2005].…”

Section: Methods For Multiple-criteria Optimizationmentioning

confidence: 99%

On the use of spatial regularization strategies to improve calibration of distributed watershed models

Pokhrel

Gupta

2010

Water Resources Research

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“…It has also been used successfully in a variety of other complex, physics-oriented applications, such as isotopic tracing (e.g., Rothfuss et al, 2012) and remotesensing simulations (e.g., Demarty et al, 2005).…”

Section: Model Principlesmentioning

confidence: 99%

Building a field- and model-based climatology of local water and energy cycles in the cultivated Sahel – annual budgets and seasonality

Velluet

Demarty

Cappelaere

et al. 2014

Hydrol. Earth Syst. Sci.

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Abstract. In the sub-Saharan Sahel, energy and water cycling at the land surface is pivotal for the regional climate, water resources and land productivity, yet it is still very poorly documented. As a step towards a comprehensive climatological description of surface fluxes in this area, this study provides estimates of long-term average annual budgets and seasonal cycles for two main land use types of the cultivated Sahelian belt: rainfed millet crop and fallow bush. These estimates build on the combination of a 7-year field data set from two typical plots in southwestern Niger with detailed physically based soil-plant-atmosphere modeling, yielding a continuous, comprehensive set of water and energy flux and storage variables over this multiyear period. In the present case in particular, blending field data with mechanistic modeling makes the best use of available data and knowledge for the construction of the multivariate time series. Rather than using the model only to gap-fill observations into a composite series, model-data integration is generalized homogeneously over time by generating the whole series with the entire data-constrained model simulation. Climatological averages of all water and energy variables, with associated sampling uncertainty, are derived at annual to subseasonal scales from the time series produced. Similarities and differences in the two ecosystem behaviors are highlighted. Mean annual evapotranspiration is found to represent ∼ 82-85 % of rainfall for both systems, but with different soil evaporation/plant transpiration partitioning and different seasonal distribution. The remainder consists entirely of runoff for the fallow, whereas drainage and runoff stand in a 40-60 % proportion for the millet field. These results should provide a robust reference for the surface energy-and water-related studies needed in this region. Their significance and the benefits they gain from the innovative data-model integration approach are thoroughly discussed. The model developed in this context has the potential for reliable simulations outside the reported conditions, including changing climate and land cover.Published by Copernicus Publications on behalf of the European Geosciences Union.

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“…bey, 2005; Demarty et al, 2005;Cao et al, 2006;Engeland et al, 2006;Bekele and Nicklow, 2007). With the recent development of distributed hydrologic models that can spatially simulate hydrologic variables, the use of multi-site observed data to evaluate model performance is becoming more common.…”

mentioning

confidence: 99%

Multi-Site Calibration of the SWAT Model for Hydrologic Modeling

Zhang¹,

Srinivasan²,

Liew³

2008

Transactions of the ASABE

137

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n recent years, hydrologic models have been increasingly used by hydrologists and water resource managers to understand and manage natural and human activities that affect watershed systems. These hydrologic models can contain parameters that cannot be measured directly due to measurement limitations and scaling issues (Beven, 2000). For practical applications in solving water resources problems, model parameters are calibrated to produce model predictions that are as close as possible to observed values. When calibrating a hydrologic model, one or more objectives are often used to measure the agreement between observed and simulated values. The objectives to be optimized can be the combination of multiple goodness-of-fit estimators (e.g.,Ărelative error, coefficient of determination), multiple variables (e.g., water, energy, sediment, and nutrients), and multiple sites

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Constraining a physically based Soil‐Vegetation‐Atmosphere Transfer model with surface water content and thermal infrared brightness temperature measurements using a multiobjective approach

Cited by 47 publications

References 58 publications

On the use of spatial regularization strategies to improve calibration of distributed watershed models

On the use of spatial regularization strategies to improve calibration of distributed watershed models

Building a field- and model-based climatology of local water and energy cycles in the cultivated Sahel – annual budgets and seasonality

Multi-Site Calibration of the SWAT Model for Hydrologic Modeling

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