Abstract
Parameterisation of unsaturated flow models for estimating spatial-scale groundwater recharge is usually reliant on expert knowledge or best-estimated parameters rather than robust uncertainty analysis. This study chose the Campaspe catchment in southeastern Australia as a field example and examined the uncertainty of spatial groundwater recharge by performing uncertainty analysis. The study area was first divided into 13 zones according to different vegetation types, soil groups and precipitation. Individual models were then established for these zones using the biophysically based modelling code WAVES (Water Atmosphere Vegetation Energy and Solutes), which is capable of simulating unsaturated flow. The Monte Carlo method, together with the Latin-Hypercube sampling technique, was employed to perform uncertainty analysis by comparing modelled monthly evapotranspiration (ET) to MODIS ET. The results show that the common one-estimate-per-site approach can still identify the spatial pattern of groundwater recharge in the study area due to the presence of a precipitation pattern. In comparison, the uncertainty analysis not only identifies the spatial pattern, but also provides confidence levels in groundwater recharge that are critical for water resources management. The results also show that recharge absolute uncertainty is directly proportional to the amount of water input, but relative uncertainty in recharge is not. This study indicates that spatial recharge estimation without model calibration or knowledge of model uncertainty could be highly uncertain. MODIS ET can be used to reduce recharge uncertainty, but it is unlikely to lower the recharge uncertainty by a large extent because of the MODIS ET estimation error.
Résumé
Le paramétrage des modèles d’écoulements non saturés pour estimer la recharge des eaux souterraines à l’échelle spatiale dépend habituellement de connaissances d’experts ou de paramètres les mieux estimés plutôt que d’une analyse d’incertitude robuste. Cette étude a choisi le bassin versant de Campaspe dans le sud-est de l’Australie comme un exemple de terrain et a examiné l’incertitude de la recharge spatialisée des eaux souterraines en réalisant une analyse d’incertitude. La zone d’étude a été tout d’abord divisée en 13 zones en considérant les différents types de végétation, de groupes de sol et des précipitations. Des modèles individuels ont été ensuite établis pour ces zones en utilisant le code de modélisation WAVES (Water Athmosphere Vegetation Energy and Solutes) basé sur la biophysique, qui est. capable de simuler les écoulements non saturés. La méthode Monte Carlo, associé à la technique d’échantillonnage Latin-Hypercube, a été employée pour réaliser l’analyse d’incertitude en comparant l’évapotranspiration (ET) modélisée au pas de temps mensuel à l’ET MODIS. Les résultats montrent que l’approche commune à une estimation par site peut encore identifier la configuration spatiale de la recharge des eaux souterraines dans la zone d’étude en raison de la présence d’un modèle de précipitation. En comparaison, l’analyse d’incertitude n’identifie pas seulement une configuration spatiale, mais fournit des niveaux de confidence dans la recharge des eaux souterraines qui sont importantes pour la gestion des ressources en eau. Les résultats indiquent également que l’incertitude absolue concernant la recharge est. directement proportionnelle à la quantité d’eau qui s’infiltre, mais l’incertitude relative dans la recharge ne l’est. pas. Cette étude indique que l’estimation de la recharge à l’échelle spatiale sans calibration du modèle ou sans connaissance de l’incertitude du modèle pourrait être fortement incertaine. MODIS ET peut être utilisé pour réduire l’incertitude sur la recharge, mais il est. peu probable qu’il puisse abaisser l’incertitude sur la recharge en grande partie en raison de l’erreur d’estimation de MODIS ET.
Resumen
La parametrización de los modelos de flujo no saturado para estimar la recarga del agua subterránea a escala espacial generalmente depende del conocimiento experto o de los parámetros mejor estimados en lugar de un sólido análisis de incertidumbre. Este estudio eligió la cuenca de drenaje de Campaspe en el sureste de Australia como un ejemplo de campo y examinó la incertidumbre de la recarga espacial del agua subterránea mediante la realización de un análisis de incertidumbre. El área de estudio se dividió en principio en 13 zonas según los diferentes tipos de vegetación, los grupos de suelos y la precipitación. Luego se establecieron modelos individuales para estas zonas utilizando el código de modelado WAVES (Water Atmosphere Vegetation Energy and Solutes), basado en la biofísica, que es capaz de simular el flujo no saturado. El método de Monte Carlo, junto con la técnica de muestreo Latin-Hypercube, se empleó para realizar el análisis de incertidumbre mediante la comparación de la evapotranspiración (ET) mensual modelada con MODIS ET. Los resultados muestran que el enfoque común de una estimación por sitio puede identificar el patrón espacial de recarga del agua subterránea en el área de estudio debido a la presencia de un patrón de precipitación. En comparación, el análisis de incertidumbre no solo identifica el patrón espacial, sino que proporciona niveles de confianza para la recarga del agua subterránea que son críticos para la gestión de los recursos hídricos. Los resultados también muestran que la incertidumbre absoluta de la recarga es directamente proporcional a la cantidad de ingreso de agua, pero no la incertidumbre relativa en la recarga. Este estudio indica que la estimación de la recarga espacial sin calibración del modelo o el conocimiento de la incertidumbre del modelo podría ser altamente incierto. MODIS ET se puede usar para reducir la incertidumbre de la recarga, pero es poco probable que reduzca la incertidumbre de la recarga en gran medida debido al error de estimación MODIS ET.
摘要
估算空间尺度地下水补给的非饱和水流模型的参数化通常依赖于专门知识或者最好的估算参数,而不是依赖于强大的不确定性分析。本研究选择澳大利亚东南部Campaspe流域作为一个野外实例,通过进行不确定性分析检查了空间地下水补给的不确定性。根据不同的植被类型、土壤组和降水情况,首先把研究区分为13个区。然后采用基于生物物理学上的模拟编码WAVES(水大气植被能量和溶质)为这些区建立了各自的模型,该模型能够模拟非饱和水流。通过比较模拟的每月蒸发蒸腾和MODIS ET,采用蒙特卡洛法以及拉丁超立方抽样技术进行不确定性分析。结果显示,由于存在着降水模式,普通的一地一估算方法仍然能确定研究区地下水补给的空间模式。相比之下,不确定性分析不仅能够确定空间模式,而且还能提供地下水补给中的置信级别,这对于水资源管理至关重要。结果还显示,补给绝对不确定性与水输入量成正比,但是补给的相对不确定性并不是如此。本研究表明,没有模型校正或模型不确定性知识的空间补给估算可能高度不确定。MODIS ET可用于减少补给不确定性,但是由于MODIS ET估算误差,很可能在很大程度上降低补给不确定性。
Resumo
Parametrização de modelos de fluxo de zona não saturada para estimativa da recarga de águas subterrâneas em escala espacial é normalmente dependente em conhecimento especializado ou parâmetros otimamente estimados ao invés de análise de incerteza. Esse estudo escolheu a bacia Campaspe na porção sudoeste da Austrália como exemplo de campo e examinou a incerteza da recarga de águas subterrâneas espacial através da análise de incerteza. A área de estudo foi primeiro dividida em 13 zonas de acordo com os tipos diferentes de vegetação, grupos de solos e precipitação. Modelos individuais foram então estabelecidos para essas zonas utilizando o código de modelagem baseado em biofísica WAVES (Águas Atmosfera Vegetação Energia e Solutos), queé capaz de simular o fluxo em zona não saturada. O método de Monte Carlo, em conjunto com a técnica de amostragem Latin-Hypercube foram empregados para fazer a análise de incerteza, comparando evapotranspiração (ET) mensalmente modelada e ET do MODIS. Os resultados demonstram que a abordagem comum de uma estimativa por local ainda pode identificar que o padrão espacial da recarga de águas subterrâneas na área estudada pela presença de um padrão de precipitação. Em comparação, a análise de incerteza não apenas identifica o padrão espacial, mas provém níveis de confiança na recarga de águas subterrâneas que são criticos para o gerenciamento dos recursos hídricos. Os resultados também demonstram que a incerteza absoluta da recarga está diretamente proporcional à quantidade de entrada de água, mas a incerteza relativa não o é. Esse estudo indica que estimar recarga espacial sem a calibragem do modelo ou conhecimento da incerteza do modelo poderia ser altamente incerto. ET do MODIS pode ser utilizada para reduzir a incerteza da recarga, mas é improvável que reduza a incerteza da recarga por uma grande extensão por causa do erro de estimativa da ET do MODIS.
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Acknowledgements
This study benefitted from discussions with Dr. John Hutson and Associate Professor Murk Bottema from Flinders University, and Professor Derek Eamus from the University of Technology Sydney.
Funding
The authors are grateful to the Murray-Darling Basin Authority for the financial support for this project.
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Xie, Y., Crosbie, R., Simmons, C.T. et al. Uncertainty assessment of spatial-scale groundwater recharge estimated from unsaturated flow modelling. Hydrogeol J 27, 379–393 (2019). https://doi.org/10.1007/s10040-018-1840-0
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DOI: https://doi.org/10.1007/s10040-018-1840-0