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Solving inverse problems of groundwater-pollution-source identification using a differential evolution algorithm

Résoudre les problèmes inverses d’identification de la source de pollution des eaux souterraines au moyen d’un algorithme d’évolution différentielle

Resolución de problemas inversos de identificación de fuentes de contaminación de las aguas subterráneas usando un algoritmo diferencial de evolución

利用差分进化算法解决地下水污染源识别的逆问题

Resolvendo problemas inversos de identificação de fontes de poluição das águas subterrâneas usando um algoritmo de evolução diferencial

Yeraltısuyu-kirlilik-kaynağı belirlenmesi problemlerinin bir diferansiyel gelişim algoritması kullanılarak çözümü

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Abstract

In this study, an accurate model was developed for solving problems of groundwater-pollution-source identification. In the developed model, the numerical simulations of flow and pollutant transport in groundwater were carried out using MODFLOW and MT3DMS software. The optimization processes were carried out using a differential evolution algorithm. The performance of the developed model was tested on two hypothetical aquifer models using real and noisy observation data. In the first model, the release histories of the pollution sources were determined assuming that the numbers, locations and active stress periods of the sources are known. In the second model, the release histories of the pollution sources were determined assuming that there is no information on the sources. The results obtained by the developed model were found to be better than those reported in literature.

Résumé

Dans cette étude, un modèle précis a été développé pour résoudre les problèmes d’identification de la source de pollution des eaux souterraines. Dans le modèle développé, les simulations numériques d’écoulement et de transport de polluant dans les eaux souterraines ont été réalisées en utilisant les logiciels MODFLOW et MT3DMS et les processus d’optimisation ont été conduits au moyen d’un algorithme d’évolution différentielle. La performance du modèle développé a été testée sur deux modèles d’aquifères hypothétiques en utilisant des données d’observation réelles et bruitées. Dans le premier modèle, les historiques d’émission par les sources de pollution ont été déterminés en faisant l’hypothèse selon laquelle les nombres, les localisations et les périodes d’activité des sources sont connus. Dans le second modèle, les historiques d’émission par les sources de pollution ont été déterminés en faisant l’hypothèse qu’il n’y a pas d’information sur les sources. Les résultats obtenus au moyen du modèle développé sont meilleurs que ceux rapportés dans la littérature.

Resumen

En este estudio, se desarrolló un modelo exacto para la resolución de problemas de identificación de fuentes de contaminación de agua subterránea. En el modelo desarrollado, las simulaciones numéricas de flujo y de transporte de contaminantes en el agua subterránea se llevaron a cabo usando los softwares MODFLOW y MT3DMS, y el proceso de optimización fue realizado utilizando un algoritmo diferencial de evolución. El rendimiento del modelo desarrollado se probó con dos modelos de acuíferos hipotéticos usando datos observacionales reales y ruidosos. En el primer modelo, las historias de los vertidos de las fuentes de contaminación se determinaron suponiendo conocidos los números, ubicaciones y períodos activos de las fuentes. En el segundo modelo, las historias de los vertidos de las fuentes de contaminación se determinaron suponiendo que no hay ninguna información sobre las fuentes. Se encontró que los resultados obtenidos por el modelo desarrollado eran mejores que los informados en la literatura.

摘要

在这项研究中,建立了准确模型来解决地下水污染源识别问题。在开发的模型中,采用MODFLOW和MT3DMS软件进行了地下水水流和污染物运移的数值模拟,并且采用差分进化算法进行了最优化处理。利用真实和众多的观测数据在两个假设含水层模型上对开发模型的性能进行了测试。第一个模型中,假定污染源的数量、位置和有效压力期已知,确定了污染源的释放历史。第二个模型中,假定没有污染源的任何信息,确定了污染源的释放历史。发现,所开发的模型获取的结果比文献记载的要好。

Resumo

Nesse estudo, um modelo acurado foi desenvolvido para solucionar problemas de identificação de fontes de poluição das águas subterrâneas. No modelo desenvolvido, as simulações numéricas de fluxo e transporte de poluentes foram conduzidas usando os softwares MODFLOW e MT3DMS, e o processo de otimização foi conduzido usando um algoritmo de evolução diferencial. O desempenho do modelo desenvolvido foi testado em dois modelos de aquíferos hipotéticos usando dados de observações reais e com ruído. No primeiro modelo, os históricos de liberação de fontes de poluição foram determinados assumindo que os números, locais e períodos de estresse ativo das fontes são conhecidos. No segundo modelo, os históricos de liberação de fontes de poluição foram determinados assumindo que não existe informação sobre as fontes. Os resultados obtidos pelo modelo desenvolvido foram considerados melhores do que aqueles referenciados na literatura.

Özet

Bu çalışmada, yeraltısuyu-kirlilik-kaynağı belirlenmesi ters problemlerinin çözümü için doğruluğu yüksek bir model geliştirilmiştir. Geliştirilen modelde, yeraltısuyunda akım ve kirletici taşınımı denklemlerinin sayısal simülasyonları MODFLOW ve MT3DMS yazılımları, optimizasyon işlemleri ise diferansiyel gelişim algoritması kullanılarak gerçekleştirilmiştir. Geliştirilen modelin performansı, iki adet kurgusal akifer modeli üzerinde gerçek ve hatalı gözlem verileri kullanılarak test edilmiştir. Birinci modelde, kaynakların yerleri ve sayılarının bilindiği varsayılarak kirletici kaynakların boşalım geçmişleri elde edilmiştir. İkinci modelde ise kaynaklarla ilgili herhangi bir bilgi olmadığı varsayılarak kirletici kaynakların boşalım geçmişleri belirlenmiştir. Geliştirilen modelden elde edilen sonuçların, literatürde verilen sonuçlardan daha iyi olduğu görülmüştür.

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Acknowledgements

This study is sponsored by Pamukkale University, Scientific Research Projects Coordination Unit (PAUBAP) with project number 2007FBE015. The authors would like to thank PAUBAP for their support.

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Correspondence to Halil Karahan.

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Published in the theme issue “Optimization for Groundwater Characterization and Management”

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Gurarslan, G., Karahan, H. Solving inverse problems of groundwater-pollution-source identification using a differential evolution algorithm. Hydrogeol J 23, 1109–1119 (2015). https://doi.org/10.1007/s10040-015-1256-z

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