System dynamics modeling for complex urban water systems: Application to the city of Tabriz, Iran

Zarghami, Mahdi; Akbariyeh, Simin

doi:10.1016/j.resconrec.2011.11.008

Cited by 101 publications

(42 citation statements)

References 16 publications

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“…A detailed description of the methodology is presented by Forrester (1968). This methodology has been applied into various fields, including environmental sustainability (Forrester, 1961(Forrester, , 1968, environmental management (Mashayekhi, 1990), transport and land use planning (Heimgartner, 2001;Shen et al, 2009;Luo et al, 2010), mining ressources (Elshkaki, 2013), land and water resource planning (Ford, 1996;Zarghami and Akbariyeh, 2012), ecological modelling (Li et al, 2012), agricultural sustainability (Saysel et al, 2002;Turner et al, 2013), regional planning and management (Guo et al, 2001).…”

Section: Methodsmentioning

confidence: 99%

Dynamic System Modelling and Land Suitability to Define Priority Areas of Soybean Plantation in Paddy Fields in Karawang, West Java

Widiatmaka

Ambarwulan²,

Firmansyah³

et al. 2014

Agrivita.J.Agr.Sci

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One of the agricultural public commodities in Indonesia which still can not fulfill the domestic consumption needs is soybean. The objectives of this research were: (i) to identify the suitable area for soybean plantation in paddy fields, (ii) to assess the development of soybeans in land use and socio-economic context, and (iii) to plan the spatial plantation of soybean. A land evaluation for soybean was completed. IKONOS imagery was analyzed to delineate paddy fields, while a dynamic system modelling was developed integrating physical and socio-economic aspects. The research results showed that the land suitability class for soybean plantation in the paddy fields in Karawang Regency ranged from not suitable (N) to suitable (S2), with limiting factors such as temperature, fertility, nutrients retention, slope, erosion, rooting media and toxicity. Very limited arable land has been used actually for soybeans plantation due to low economic returns. The model predicts that if the development of soybean continues in its business as usual path, a deficit of soybean will increase in 2030. The model provides alternative scenarios to reduce the deficit. Prioritization was done spatially using the suitable land gradually.

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Section: Methodsmentioning

confidence: 99%

Dynamic System Modelling and Land Suitability to Define Priority Areas of Soybean Plantation in Paddy Fields in Karawang, West Java

Widiatmaka

Ambarwulan²,

Firmansyah³

et al. 2014

Agrivita.J.Agr.Sci

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show abstract

“…Three were used in this study: matrix extension (to solve the groundwater flow equations), Matlab extension, (to generate geostatistical realisations of hydraulic parameters); and BehaviourSpace (to perform automated parameter sweeping in a parallelized way). Other packages not shown here but relevant for GW-ABM workflows allow working with GIS files, System Dynamics models (Ahmad and Simonovic, 2000;Zarghami and Akbariyeh, 2012), and the R statistical package to perform parameter estimation (Thiele and Grimm, 2010;Thiele et al, 2014).…”

Section: Flowlogo Architecturementioning

confidence: 99%

An agent-based platform for simulating complex human–aquifer interactions in managed groundwater systems

Castilla-Rho

Mariethoz

Rojas

et al. 2015

Environmental Modelling & Software

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“…Therefore, for future research, the authors suggest to model the water supply and demand projections of Istanbul using the system dynamics approach. In this way, the model will be able to take into account the interactions among economic and social dimensions, offering a realistic platform for practical use for sustainable urban water management by city-planners [39][40][41][42].…”

Section: Conclusion and Recommendationsmentioning

confidence: 99%

A Framework for Sustainable Urban Water Management through Demand and Supply Forecasting: The Case of Istanbul

et al. 2015

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Abstract:The metropolitan city of Istanbul is becoming overcrowded and the demand for clean water is steeply rising in the city. The use of analytical approaches has become more and more critical for forecasting the water supply and demand balance in the long run. In this research, Istanbul's water supply and demand data is collected for the period during 2006 and 2014. Then, using an autoregressive integrated moving average (ARIMA) model, the time series water supply and demand forecasting model is constructed for the period between 2015 and 2018. Three important sustainability metrics such as water loss to supply ratio, water loss to demand ratio, and water loss to residential demand ratio are also presented. The findings show that residential water demand is responsible for nearly 80% of total water use and the consumption categories including commercial, industrial, agriculture, outdoor, and others have a lower share in total water demand. The results also show that there is a considerable water loss in the water distribution system which requires significant investments on the water supply networks. Furthermore, the forecasting results indicated that pipeline projects will be critical in the near future due to expected increases in the total water demand of Istanbul. The authors suggest that sustainable management of water can be achieved by reducing the residential water use through the use of water efficient OPEN ACCESSSustainability 2015, 7 11051 technologies in households and reduction in water supply loss through investments on distribution infrastructure.

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System dynamics modeling for complex urban water systems: Application to the city of Tabriz, Iran

Cited by 101 publications

References 16 publications

Dynamic System Modelling and Land Suitability to Define Priority Areas of Soybean Plantation in Paddy Fields in Karawang, West Java

Dynamic System Modelling and Land Suitability to Define Priority Areas of Soybean Plantation in Paddy Fields in Karawang, West Java

An agent-based platform for simulating complex human–aquifer interactions in managed groundwater systems

A Framework for Sustainable Urban Water Management through Demand and Supply Forecasting: The Case of Istanbul

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