NDLI: Spatio-temporal optimisation of agricultural drainage using groundwater models and genetic algorithms: an example from the Murray Irrigation Area, Australia

Content Provider	Springer Nature Link
Author	Rana, T. Khan, S. Rahimi, M.
Copyright Year	2008
Abstract	Drainage schemes for salinity management are aimed at lowering the shallow groundwater to help increase production and reduce ecological risks. Once the groundwater levels are lowered to desired agro-ecological thresholds, the drainage scheme’s operation needs to be optimised according to the spatio–temporal variation in groundwater dynamics. Groundwater systems can be modelled if their behaviour is fully known and understood but a key difficulty in optimisation is dealing with non-linear and non-unique spatio-temporal problems. Such problems can be optimised using genetic algorithms (GA) aimed at finding near optimal solutions to highly non-linear optimisation problems. The major advantages of GAs are their broad applicability, flexibility and their ability to find solutions with relatively modest computational requirements. A surface water/groundwater interaction model has been developed in conjunction with GA based spatio-temporal optimisation of pumping operation of a subsurface drainage scheme. The aim has been to achieve a similar or better than on-going level of service both in space and time domains. The Wakool Tullakool Subsurface Drainage Scheme in the Murray Irrigation Area, Australia is discussed to illustrate the modelling process. The model results are being used to plan the cost-effective operation of the tubewells to control water logging and salinisation.Les projets de drainage destinés à la gestion de la salinité sont destinés à rabattre les eaux souterraines peu profondes afin de favoriser l’augmentation de la production et la réduction des risques écologiques. Une fois que les niveaux d’eau souterraine sont rabattus jusqu’aux seuils agro-écologiques désirés, la mise en œuvre du projet de drainage doit être optimisée selon la dynamique spatio-temporelle changeante de l’eau souterraine. Les systèmes d’eau souterraine peuvent être modélisés si leur comportement est tout à fait connu et compris mais une difficulté fondamentale pour l’optimisation est d’avoir affaire à des problèmes non linéaires et spatio-temporels non uniques. De tels problèmes peuvent être optimisés en utilisant les genetic s algorithms (GA) destinés à trouver des solutions presque idéales à des problèmes d’organisation fortement non linéaire. Les principaux avantages des GA sont leur vaste domaine d’application, leur flexibilité et leur capacité à trouver des solutions avec des exigences de moyens de calcul relativement modestes. Un modèle d’interaction eau de surface/eau souterraine a été développé en conjonction avec l’optimisation spatio-temporelle basée sur les GA de l’opération de pompage d’un projet de drainage de sub-surface. L’objectif a été l’obtention d’un niveau de performance semblable ou meilleur que l’actuel dans les domaines de l’espace et du temps. Le Projet de Drainage de Sub-surface de Wakool Tullakool dans le Périmètre d’Irrigation de la Murray, Australie, est examiné afin d’illustrer la procédure de modélisation. Les résultats du modèle sont utilisés pour planifier la réalisation au meilleur coût des puits tubés destinés à contrôler le profil et l’augmentation de salinité de l’eau.Los esquemas de riego para el manejo de la salinidad tiernen por objetivo el descenso de los niveles freáticos someros a fin de incrementar la producción y reducir los riesgos ecológicos. Una vez que se logra el descenso de niveles a los umbrales adecuado desde el punto de vista agroecológico, la operación del esquema de drenaje necesita ser optimizado de acuerdo con las variaciones espacio-temporales de la dinámica hídrica subterránea. El flujo en los sitemas subterráneos puede ser modelado si su comportamiento es enteramente conocido, pero el problema de la optimización se dificulta al trabajar con problemas espacio-temporales no lineales y no únicos. Tales problemas pueden optimizarse usando algoritmos genéticos (AG), que buscan hallar soluciones cuasi-óptimas a problemas de optimización altamente no lineales. Las principales ventajas de los AGs es su amplio campo de aplicación, su flexibilidad y su capacidad para encontrar soluciones con requerimientos computacionales relativamente modestos. Se ha desarrollado un modelo de interacción aguas superficiales/subterráneas en conjunción con una optimización espacio-temporal basada en AG para el bombeo en un esquema de drenaje subsuperficial. El objetivo es alcanzar un nivel de servicio similar o mejor que el existente, tanto en el dominio espacial como temporal. Se presenta el esquema de drenaje subsuperficial Wakool Tullakool en el área de riego Murray, Australia, a fin de ilustrar el proceso de modelación. Los resultados del modelo se están utilizando para planear la rentabilidad del uso de pozos de bombeo para controlar el ascenso de niveles y la salinización.
Starting Page	1145
Ending Page	1157
Page Count	13
File Format	PDF
ISSN	14312174
Journal	Hydrogeology Journal
Volume Number	16
Issue Number	6
e-ISSN	14350157
Language	English
Publisher	Springer Berlin Heidelberg
Publisher Date	2008-04-02
Publisher Institution	International Association of Hydrogeologists
Publisher Place	Berlin, Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Subsurface drainage Salinization MODFLOW Genetic algorithm Australia Hydrogeology Hydrology/Water Resources Geology Water Quality/Water Pollution Geophysics/Geodesy Waste Water Technology Water Pollution Control Water Management Aquatic Pollution
Content Type	Text
Resource Type	Article
Subject	Earth and Planetary Sciences Water Science and Technology

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