Abstract
The MétéEAU Nappes water-resource-management tool is presented. It is usable on the aquifer or part-of-aquifer scale for real-time observation of the state of the groundwater resource, and it is already operating in France. This online decision support tool is also able to predict the state of the resource in the short- and mid-terms. The paper explains the use of the tool in a case study in the Authion Valley, in the north-west of France, chosen for its context of tension surrounding the groundwater resource resulting from high volumes of abstraction for irrigation. The results of the simulation highlight the advantages of MétéEAU Nappes as a tool for prediction and simulation of the state of the groundwater resource. The results also show the advantages of this type of tool for water resource management, such as supplying local actors with reliable and real-time observations of the aquifer and providing forecasts to anticipate possible water shortage.
Résumé
L’outil de gestion de la ressource en eau MétéEAU Nappes est présenté. Il est utilisable à l’échelle d’un aquifère, ou d’une portion d’aquifère, pour observer en temps réel l’état quantitatif de la ressource en eau souterraine, et il est déjà opérationnel en France. Cet outil web d’aide à la décision permet également de prédire l’état de la ressource en eau à court et moyen termes. L’article présente l’utilisation de l’outil sur un cas d’étude situé dans la vallée de l’Authion, dans le Nord-Ouest de la France, choisi pour son contexte de tension sur les ressources en eau du fait d’importants prélèvements souterrains pour l’irrigation agricole. L’application met en valeur les avantages de MétéEAU Nappes en tant qu’outil de prédiction et de simulation de l’état quantitatif de la ressource en eau souterraine. Les résultats obtenus permettent aussi d’illustrer l’intérêt de ce type d’outil pour la gestion des ressources en eau, par exemple pour fournir aux acteurs locaux des observations fiables et en temps réel de l’état de l’aquifère et fournir des prévisions pour anticiper d’éventuelles pénuries d’eau.
Resumen
Se presenta la herramienta de gestión de los recursos hídricos MétéEAU Nappes. Se puede utilizar a escala de acuífero o de parte de acuífero para la observación en tiempo real del estado del recurso hídrico subterráneo, y ya está en funcionamiento en Francia. Esta herramienta de apoyo a la toma de decisiones en línea también es capaz de predecir el estado del recurso a corto y mediano plazo. El artículo explica el uso de la herramienta en un estudio de caso en el valle de Authion, en el noroeste de Francia, elegido por su contexto de tensión en torno al recurso hídrico subterráneo resultante de los altos volúmenes de extracción para el riego. Los resultados de la simulación ponen de manifiesto las ventajas de MétéEAU Nappes como herramienta de predicción y simulación del estado del recurso hídrico subterráneo. Los resultados también muestran las ventajas de este tipo de herramienta para la gestión de los recursos hídricos, como el suministro a los agentes locales de observaciones fiables y en tiempo real del acuífero y la realización de previsiones para anticipar una posible escasez de agua.
摘要
介绍了 MétéEAU Nappes 水资源管理工具。它可用于含水层或部分含水层的尺度, 用于实时观测地下水资源状况, 并且已在法国运行。这种在线决策支持工具还能够预测在短期和中期的资源状态。该论文解释了该工具在法国西北部 Authion 山谷的案例研究, 该案例研究的背景是由于灌溉大量抽取地下水而导致地下水资源紧张。模拟结果突出了 MétéEAU Nappes 作为预测和模拟地下水资源状态的工具的优势。结果还显示了这种水资源管理工具的优势, 例如为当地参与者提供可靠和实时的含水层观测, 并预测可能的水资源短缺。
Resumo
Apresenta-se a ferramenta de gestão de recursos hídricos MétéEAU Nappes. É utilizável na escala do aquífero ou parte do aquífero para observação em tempo real do estado dos recursos hídricos subterrâneos e já está operando na França. Esta ferramenta online de apoio à decisão também é capaz de prever o estado do recurso a curto e médio prazo. O artigo explica o uso da ferramenta em um estudo de caso no vale Authion, no noroeste da França, escolhido por seu contexto de tensão em torno do recurso hídrico subterrâneo resultante de altos volumes de captação para irrigação. Os resultados da simulação destacam as vantagens do MétéEAU Nappes como ferramenta de previsão e simulação do estado dos recursos hídricos subterrâneos. Os resultados também mostram as vantagens desse tipo de ferramenta para a gestão de recursos hídricos, como fornecer aos atores locais observações confiáveis e em tempo real do aquífero e fornecer previsões para antecipar uma possível escassez de água.
Similar content being viewed by others
References
Ades (2021) Ades: accès aux données sur les eaux souterraines [Ades: access to groundwater database]. https://ades.eaufrance.fr/. Accessed March 2020
Bessière H (2021) Prévision des niveaux piézométriques des Yvelines (Ile-de-France). Rapport d’expertise [Prediction of the piezometric levels of Yvelines (Ile-de-France). Expert report]. Report BRGM/RP-70645-FR. 20 pp. http://infoterre.brgm.fr/rapports//RP-70645-FR.pdf. Accessed July 2022
BNPE (2021) Banque Nationale des Prélèvements en Eau [BNPE: National Water Abstraction Database]. https://bnpe.eaufrance.fr/. Accessed March 2020
BRGM (2021) MétéEAU Nappes, un outil de suivi en temps réel et de prévision du niveau des nappes [MétéEAU Nappes: a real-time water resource management tool]. https://meteeaunappes.brgm.fr. Accessed July 2021
Falloon P, Betts R (2010) Climate impacts on European agriculture and water management in the context of adaptation and mitigation: the importance of an integrated approach. Sci Total Environ 408:5667–5687
Farooq M, Wahid A, Kobayashi N, Fujita D, Basra SMA (2009) Plant drought stress: effects, mechanisms and management. Agron Sustain Dev 29:185–212. https://doi.org/10.1051/agro:2008021. Accessed July 2022
Gleyses G, Loubier S, Terreaux J-P (2003) Calcul du coût de l’eau d’irrigation [Assessment of irrigation water prices]. La Houille Blanche 3:102–106
Holman IP, Trawick P (2011) Developing adaptive capacity within groundwater abstraction management systems. J Environ Manag 92:1542–1549
Hong N, Hama T, Suenaga Y, Huang X, Ito H, Kawagoshi Y (2017) Simplified lumped groundwater model to simulate nitrate concentration dynamics. J Hydrol Eng 22(10)
Huo A, Wang X, Liang Y, Jiang C, Zheng X (2020) Integrated numerical model for irrigated area water resources management. J Water Climate Change 11(4):980–991. https://doi.org/10.2166/wcc.2019.042
Izady A, Davary K, Alizadeh A, Ziaei AN, Akhavan S, Alipoor A, Joodavi A, Brusseau ML (2015) Groundwater conceptualization and modeling using distributed SWAT-based recharge for the semi-arid agricultural Neishaboor plain, Iran. Hydrogeol J 23:47–68. https://doi.org/10.1007/s10040-014-1219-9
IPCC (Intergovernmental Panel on Climate Change) (2007) Climate change 2007: impacts, adaptation and vulnerability. Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, 976 pp
Jackson-Blake LA, Sample JE, Wade AJ, Helliwell RC, Skeffington RA (2017) Are our dynamic water quality models too complex? a comparison of a new parsimonious phosphorus model, SimplyP, and INCA-P. Water Resour Res 53:5382–5399
Klein KK, Wen Y, Le Roy DGG (2012) Estimating the incremental gross margins due to irrigation water in southern Alberta. Can Water Resour J 37:89–103. https://doi.org/10.4296/cwrj3702930
Knox JW, Morris J, Weatherhead EK, Turner AP (2000) Mapping the financial benefits of sprinkler irrigation and potential financial impact of restrictions on abstraction: a case-study in Anglian Region. J Environ Manag 58:45–59
Letey J, Dinar A, Woodring C, Oster JD (1990) An economic analysis of irrigation systems. Irrig Sci 11:37–43
Louail J (1969) Etude sédimentologie des sables et graviers de Jumelles (Maine et Loire): origine et mise en place des formations situées à la base du Crétacé en Maine-et- Loire [Sedimentology study of the sands and gravels of Jumelles (Maine et Loire): origin and establishment of the formations located at the base of the Cretaceous in Maine-et-Loire]. Stratigraphie. Thèse, University of Rennes, 113 pp
Mehraban A, Tobe A, Gholipouri A, Amiri E, Ghafari A, Rostaii M (2019) The effects of drought stress on yield, yield components, and yield stability at different growth stages in bread wheat cultivar (Triticum aestivum L.). Pol J Environ Stud 28:739–746. https://doi.org/10.15244/pjoes/83350
Mougin B, Nicolas J, Vigier Y, Bessière H, Loigerot S (2020) « MétéEAU Nappes » : un site Internet contenant des services utiles à la gestion des étiages [“MétéEAU Nappes”: a website with useful services for water and drought management]. La Houille Blanche 5:28–36. https://doi.org/10.1051/lhb/2020045
Nagy J (2003) Effect of irrigation on maize yield (Zea mays L.). Acta agrar Debr 11:30–35. https://doi.org/10.34101/actaagrar/11/3441
Nash JE, Sutcliffe JV (1970) River flow forecasting through conceptual models, part I: a discussion of principles. J Hydrol 10:282–290
Nicolle P, Pushpalatha R, Perrin C, Francois D, Thiéry D, Mathevet T, Le Lay M, Besson F, Soubeyroux J-M, Viel C, Regimbeau F, Andréassian V, Maugis P, Augeard B, Morice E (2014) Benchmarking hydrological models for low-flow simulation and forecasting on French catchments. Hydrol Earth Syst Sci 18:2829–2857. https://doi.org/10.5194/hess-18-2829-2014
Samarawickrema A, Kulshreshtha S (2008) Value of water for drought proofing in the South Saskatchewan River Basin (Alberta). Can Water Resour J 33:273–281
Seiller G, Anctil F, Perrin C (2012) Multimodel evaluation of twenty lumped hydrological models under contrasted climate conditions. Hydrol Earth Syst Sci 16:1171–1189
Rey D, Holman IP, Knox JW (2017) Developing drought resilience in irrigated agriculture in the face of increasing water scarcity. Reg Environ Chang 17:1527–1540
Rosenbrock HH (1960) An automatic method for minding the greatest or least value of a function. J Comput 3:175–184
Takafuji EHD, Rocha MM, Manzione RL (2019) Groundwater level prediction/forecasting and assessment of uncertainty using SGS and ARIMA models: a case study in the Bauru Aquifer System (Brazil). Nat Resour Res 28:487–503. https://doi.org/10.1007/s11053-018-9403-6
Thiéry D (1988) Forecast of changes in piezometric levels by a lumped hydrological model. J Hydrol 97:129–148
Thiéry D (2010) Reservoir models in hydrogeology. In: Tanguy JM (ed) Mathematical models, vol 2, chap 13. Environmental Hydraulics Series, pp 409–418. https://doi.org/10.1002/9781118557853.ch13
Thiéry D (2015) Validation du code de calcul GARDÉNIA par modélisations physiques comparatives [Validation of the GARDENIA calculation code by comparative physical modeling]. Rapport BRGM/RP-64500-FR, 48 pp. http://infoterre.brgm.fr/rapports/RP-64500-FR.pdf. Accessed July 2022
Thiéry D (2018) Logiciel ÉROS version 7.1: guide d’utilisation [EROS Software version 7.1: user guide]. Report BRGM/RP-67704-FR, 181 pp.http://infoterre.brgm.fr/rapports/RP-67704-FR.pdf. Accessed July 2022
Tilmant F, Nicolle P, Bourgin F, Besson F, Delaigue O, Etchevers P, François D, Le Lay M, Perrin C, Rousset F, Thiéry D, Magand C, Leurent T, Jacob E (2020) PREMHYCE: un outil opérationnel pour la prévision des étiages [PREMHYCE: an operational tool for low-flow forecasting]. La Houille Blanche 5:37–44
Sidibé Y, Terreaux J-P, Tidball M, Reynaud A (2012) Coping with drought with innovative pricing systems: the case of two irrigation water management companies in France. Agric Econ 43:141–155. https://doi.org/10.1111/j.1574-0862.2012.00628.x
Vicente-Serrano SM, Domínguez-Castro F, Peña-Angulo D, Peña-Gallardo M, Henriot A, Caballero Y, Mougin B, Coscarelli R, Antronico L, Zimbo F, Petrucci O, Pasqua AA, del Jesus M (2020) Report on comparison of the ISD with sectorial data. Indecis Projet Delivrable 4:5 http://indecis.eu/docs/Deliverables/Deliverable4.5.pdf. Accessed July 2022
Woodward SJR, Wohling T, Rode M, Stenger R (2017) Predicting nitrate discharge dynamics in mesoscale catchments using the lumped StreamGEM model and Bayesian parameter inference. J Hydrol 552:684–703
Acknowledgements
This research has not received any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. MétéEAU Nappes was developed by BRGM within the framework of its own research activities.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflicts of interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Additional information
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary information
ESM 1
(PDF 390 kb)
Rights and permissions
About this article
Cite this article
Surdyk, N., Thiéry, D., Nicolas, J. et al. MétéEAU Nappes: a real-time water-resource-management tool and its application to a sandy aquifer in a high-demand irrigation context. Hydrogeol J 30, 1737–1749 (2022). https://doi.org/10.1007/s10040-022-02509-1
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10040-022-02509-1