An imprecise fuzzy risk approach for water quality management of a river system

Rehana, S.; Mujumdar, P. P.

doi:10.1016/j.jenvman.2009.07.007

Cited by 60 publications

(28 citation statements)

References 28 publications

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“…Thereby, it is crucially important to make scientific water allocation policy for balancing economic development and environmental protection of every county in Heihe River Basin. Conventional water allocation researches that only concentrates on water demand and supply but ignores the interplay between water resources and land use, cannot reveal the impacts of land use on water resources utilization and allocation [7,8].…”

Section: Introductionmentioning

confidence: 99%

Optimal Water Resources Allocation under the Constraint of Land Use in the Heihe River Basin of China

et al. 2015

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Abstract:In recent years, water scarcity and irrational utilization have become the pivotal issues for the sustainable development of river basins in China. This paper attempts to propose a new perspective for the optimization of water resources allocation in a typical river basin. In order to conduct an accurate and feasible program for water resources allocation in the water-deficient river basin, a multi-objective and multi-constraint programming model was developed by embedding land use effect as a constraint on water allocation, which was currently solely decided by water resources demand in different water use sectors. The program includes two layers, namely water allocation among different counties located in the middle reaches of the Heihe River Basin and among domestic, industrial, agricultural and ecological uses within one county. Empirical analysis shows that the structural change of land use has an important influence and restriction on the water resources allocation in the river basin. The least cultivated areas that ensure food security and the constraint of construction land quota have great impact on agricultural and industrial water allocation. Moreover, the quantitative change of ecological land greatly affects ecological water allocation. The results demonstrate that the optimal program calculated from land use embedded model can well predicate the actual situation of water allocation in the future. To ensure regional sustainable development, it is vital that reasonable water-saving measures in each water use sector and ecological protection policies be taken. OPEN ACCESSSustainability 2015, 7 1559

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Section: Introductionmentioning

confidence: 99%

Optimal Water Resources Allocation under the Constraint of Land Use in the Heihe River Basin of China

et al. 2015

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“…Several authors studied various AI techniques in environmental modelling, water quality monitoring and assessment, predicting the concentrations of heavy metals and other quality parameters, and estimation and forecasting in climatic sciences (Soyupak et al, 2003;Altunkaynak, Özger, & Çakmakcı, 2005;Kisi, 2005;Ocampo-Duque, Ferré-Huguet, Domingo, & Schuhmacher, 2006;Sengorur, Dogan, Koklu, & Samandar, 2006;Terzi, Keskin, & Taylan, 2006;Dahiya, Singh, Gaur, Garg, & Kushwaha, 2007;Icaga, 2007 2008; Hanbay, Turkoglu, & Demir, 2008;Dogan, Sengorur, & Koklu, 2009;Lermontov, Yokoyama, Lermontov, & Machado, 2009;Rehana & Mujumdar, 2009;Singh, Basant, Malik, & Jain, 2009;Ranković, Radulović, Radojević, Ostojić, & Čomić, 2010;Akkoyunlu, Altun, & Cigizoglu, 2011;Ay & Kisi, 2011Areerachakul, 2012;Hisar, Sönmez, Kaya, & Aras Hisar, 2012;Kisi & Ay, 2012;Qasaimeh et al, 2012;Sönmez, Hisar, & Yanık, 2012, 2013bSönmez, Hasiloglu, Hisar, Aras Mehan, & Kaya, 2013a;Chen & Liu, 2014;Emamgholizadeh, Kashi, Marofpoor, & Zalaghi, 2014;Heddam, 2014;Nemati, Naghipour, & Fazeli Fard, 2014;Yılmaz Öztürk, Akköz, Aşıkkutlu, & Gümüş, 2014;Ahmed & Shah, 2015;Alte & Sadgir, 2015;Csábrági, Molnár, Tanos, & Kovács, 2015, 2017...…”

Section: Introductionmentioning

confidence: 99%

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Sönmez¹,

Kale²,

Ozdemir³

et al. 2018

Turk. J. Fish. Aquat. Sci.

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Water quality is one of the main characteristics of a river system and prediction of water quality is the key factor in water resource management. Different physical, biological and chemical parameters including heavy metals can be used to assess river water quality. Evaluation of the water quality in the rivers is quite difficult and requires more time and effor t because of the fact that many factors affect water quality. Traditional data processing methods are insufficient to solve this problem. Therefore, in this study, an adaptive neuro-fuzzy inference system (ANFIS) model was developed to predict the concentrations of cadmium (Cd) in the Filyos River, Turkey. For this purpose, water samples collected at 7 sampling locations in the river during December 2014-2015 were used to develop ANFIS model. The available data set was apportioned into two separate sections for training and testing the ANFIS model. Developed models aimed to use the least parameters to estimate Cd concentration. As a result, a relatively higher correlation (R 2 =0.91) was found between observed and modelled Cd concentrations. The results indicated that the ANFIS model gave reasonable estimates for the concentrations of Cd with a high degree accuracy and robustness. In conclusion, this paper suggests that ANFIS methodology produce very successful findings and has the ability to predict Cd concentration in water resources. The outcomes of this research provide more information, simulation, and prediction about heavy metal concentration in natural aquatic ecosystems. Therefore, ANFIS can be used in further researches on water quality monitoring.

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“…Most of the hazards cannot be controlled or predicted with an acceptable degree of accuracy [3]. Therefore, uncertainty plays an important role in water quality management problems [4]. One of uncertainty theories that has been arisen in these last decades is fuzzy theory [5], which can be utilized to incorporate epistemic uncertainty [6].…”

Section: Introductionmentioning

confidence: 99%

Water Pollution Risk Assessment for Water Transfer Projects

Song¹,

Zhang²

2017

Proceedings of the 2nd 2016 International Conference on Sustainable Development (ICSD 2016)

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Abstract-Due to the imprecision of water environmental system and the repeated scarcity of quantitative information during transfer project, fuzzy theory might be an effective tool of the water pollution risk evaluation. Firstly, triangular fuzzy numbers of environmental parameters were defined. Then, fuzzy α-cut technique is introduced to figure out the fuzzy expected values. Based on the concept of fuzzy reliability of "recipient" water quality, the water pollution risk in fuzzy terms is calculated. Finally, the implementation process of the water risk assessment method is explained by the case study.

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An imprecise fuzzy risk approach for water quality management of a river system

Cited by 60 publications

References 28 publications

Optimal Water Resources Allocation under the Constraint of Land Use in the Heihe River Basin of China

Optimal Water Resources Allocation under the Constraint of Land Use in the Heihe River Basin of China

Untitled

Water Pollution Risk Assessment for Water Transfer Projects

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