A Linking Test to reduce the number of hydraulic parameters necessary to simulate groundwater recharge in unsaturated soils

Pollacco, Joseph Alexander Paul; Ugalde, Jose; Angulo-Jaramillo, Rafaël; Braud, Isabelle; Saugier, B.

doi:10.1016/j.advwatres.2007.09.002

Cited by 30 publications

(33 citation statements)

References 45 publications

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“…• We applied and improved the Linking Test developed by Pollacco et al (2008) to look for links between the parameters that need to be calibrated, and thus to investigate whether inverse modelling is feasible, which depends on the accuracy of the calibration data.…”

Section: Introductionmentioning

confidence: 99%

“…The first step of this investigation has been answered by Pollacco et al (2008). Pollacco et al (2008) used a onedimensional Richards' soil water flow model in a temperate oak forest and, assuming vegetation parameters are known, tried to determine groundwater recharge by optimising the hydraulic parameters against time series of soil moisture profiles.…”

Section: Introductionmentioning

confidence: 99%

“…Pollacco et al (2008) used a onedimensional Richards' soil water flow model in a temperate oak forest and, assuming vegetation parameters are known, tried to determine groundwater recharge by optimising the hydraulic parameters against time series of soil moisture profiles. They found that a unique groundwater recharge could be obtained but that the optimal hydraulic parameters were not unique.…”

Section: Introductionmentioning

confidence: 99%

“…This paper presents a case study to determine if the interception and crop factor parameters can tentatively be calibrated by fitting soil moisture profiles. Synthetic data were used and the other vegetation parameters and the soil hydraulic parameters were assumed to be known.• We applied and improved the Linking Test developed by Pollacco et al (2008) to look for links between the parameters that need to be calibrated, and thus to investigate whether inverse modelling is feasible, which depends on the accuracy of the calibration data.• The Linking Test established that interception and evapotranspiration parameters are linked and, therefore, uncertainty on interception compensates for uncertainty on evapotranspiration. Thus in spite of a good match between observed and simulated soil moisture data, inverse modelling is unfeasible.…”

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A Linking Test that establishes if groundwater recharge can be determined by optimising vegetation parameters against soil moisture

Pollacco

Braud²,

Angulo-Jaramillo

et al. 2008

Ann. For. Sci.

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Abstract• The impact of afforestation/deforestation on groundwater recharge can be predicted by using onedimensional soil-vegetation water flow models based on Richards' equation. However simulations depend upon parameters that are not easily measurable.• Pollacco et al. (2008) showed that the hydraulic parameters can be determined, if the vegetation parameters are known, by fitting simulated time series of soil moisture profiles to those measured in situ. This paper presents a case study to determine if the interception and crop factor parameters can tentatively be calibrated by fitting soil moisture profiles. Synthetic data were used and the other vegetation parameters and the soil hydraulic parameters were assumed to be known.• We applied and improved the Linking Test developed by Pollacco et al. (2008) to look for links between the parameters that need to be calibrated, and thus to investigate whether inverse modelling is feasible, which depends on the accuracy of the calibration data.• The Linking Test established that interception and evapotranspiration parameters are linked and, therefore, uncertainty on interception compensates for uncertainty on evapotranspiration. Thus in spite of a good match between observed and simulated soil moisture data, inverse modelling is unfeasible. This is true even if the interception or the crop factor parameters are known, because an error on interception or evapotranspiration will be compensated by an error on groundwater recharge without affecting soil moisture.• This paper recommends that vegetation parameters should not be calibrated by optimisation against soil moisture data. • L'impact de la déforestation/reforestation, sur la recharge des eaux souterraines, peut être quantifié en employant les modèles unidimensionnels d'écoulement dans le continuum sol-plante-atmosphère. Ces modèles sont fondés sur la solution de l'équation de Richards. Cependant, quel que soit le modèle, les simulations dépendent de paramètres qui sont difficilement mesurables. • Le Test de Liaison a permis d'établir le degré de liaison entre les paramètres d'interception et d'éva-potranspiration, et en conséquence d'estimer de combien l'incertitude sur l'interception compense celle sur l'évapotranspiration. Ainsi, malgré une bonne correspondance entre les données d'humidité de sol observées et simulées, la modélisation inverse n'est pas faisable. Ceci reste vrai même lorsque les paramètres d'interception et le coefficient cultural sont connus, car les erreurs sur l'interception ou l'évapotranspiration sont compensées par une erreur sur la recharge. Ces erreurs n'ont pas d'effet sur l'humidité du sol. Mots-clés : test de Liaison• Cet article suggère que les paramètres de végétation ne devraient pas être estimés par optimisation sur des données d'humidité du sol.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

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A Linking Test that establishes if groundwater recharge can be determined by optimising vegetation parameters against soil moisture

Pollacco

Braud²,

Angulo-Jaramillo

et al. 2008

Ann. For. Sci.

Self Cite

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“…Physics-based numerical models are powerful tools for the simulation or prediction of temporal and spatial variation of FSL in a given domain. However, they require a large quantity of precise data related to the physical properties of the domain, a lack of which can cause severe deterioration in the accuracy and reliability of their results [9,10]. Time series modeling can be an effective alternative approach for predicting saltwater intrusion where geological and geophysical surveys are limited and monitoring data of temporal variation related to saltwater intrusion are available.…”

Section: Introductionmentioning

confidence: 99%

Comparative Evaluation of ANN- and SVM-Time Series Models for Predicting Freshwater-Saltwater Interface Fluctuations

Yoon

Kim

et al. 2017

Water

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Time series models based on an artificial neural network (ANN) and support vector machine (SVM) were designed to predict the temporal variation of the upper and lower freshwater-saltwater interface level (FSL) at a groundwater observatory on Jeju Island, South Korea. Input variables included past measurement data of tide level (T), rainfall (R), groundwater level (G) and interface level (F). The T-R-G-F type ANN and SVM models were selected as the best performance model for the direct prediction of the upper and lower FSL, respectively. The recursive prediction ability of the T-R-G type SVM model was best for both upper and lower FSL. The average values of the performance criteria and the analysis of error ratio of recursive prediction to direct prediction (RP-DP ratio) show that the SVM-based time series model of the FSL prediction is more accurate and stable than the ANN at the study site.

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A Linking Test that investigates the feasibility of inverse modelling: application to a simple rainfall interception model for Mt Gambier, southeast South Australia

Pollacco

Angulo-Jaramilo

2009

Hydrological Processes

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International audienceInterception loss has an important influence on the water yield of forested areas. Nevertheless, in most studies stemflow is not measured, therefore the question of how to determine the feasibility of optimizing interception and stemflow parameters simultaneously by matching daily simulated throughfall to fortnightly measurements of cumulative throughfall is an important one. By applying a daily empirical interception model, a goodness fit of 2·2 mm/day is obtained between observed and simulated cumulative throughfall. However, by applying the simple but robust Linking Test, it was shown that the parameters are non-unique and falsely linked, i.e. inter-relationships between different vegetation parameter sets give similar throughfall but non-unique net precipitation. The Linking Test investigates the causes of obtaining falsely linked parameters and shows that objective equifinality is not the source of the problem. Objective equifinality occurs when an inappropriate objective function is used. The Linking Test also shows that falsely linked parameters are not caused by measuring throughfall on a non-daily basis (termed frequency sampling equifinality). By expanding the interception model to the second degree, it was found that the non-uniqueness is due to the inherent nature of interception and stemflow functions that behave similarly and therefore can easily compensate each other (termed similarity equifinality). It is also shown that a simple daily empirical exponential interception model developed for conifers in the uplands of the United Kingdom is suitable to model interception in Pinus radiata plantations in the Mediterranean climate of southern Australia by using only daily gross precipitation data and two parameters

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A Linking Test to reduce the number of hydraulic parameters necessary to simulate groundwater recharge in unsaturated soils

Cited by 30 publications

References 45 publications

A Linking Test that establishes if groundwater recharge can be determined by optimising vegetation parameters against soil moisture

A Linking Test that establishes if groundwater recharge can be determined by optimising vegetation parameters against soil moisture

Comparative Evaluation of ANN- and SVM-Time Series Models for Predicting Freshwater-Saltwater Interface Fluctuations

A Linking Test that investigates the feasibility of inverse modelling: application to a simple rainfall interception model for Mt Gambier, southeast South Australia

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