Abstract
Dünyadaki tatlı su kaynakları içme suyu, tarımsal sulama ve enerji için yoğun bir şekilde kullanılmakta, ancak artan kentleşme, değişen iklim koşulları ve yanlış yönetim nedeniyle su kaynakları giderek azalmaktadır. Özellikle küresel iklim değişimleri karşısında geçmiş yıllarda ülkemizde de görüldüğü gibi, kentlerdeki su talebinin karşılanmasında güç durumlarla karşı karşıya kalınmaktadır. Dolayısıyla su talebinin belirlenmesi, dönemsel tahminlerinin yapılması ve bu tahminler sonucunda ayrıntılı planlamaların yapılması, kentlerdeki su hizmeti sunan kuruluşlar ve bu hizmetten yararlanan tüm çevreler için hayati derecede önemli bir konudur.
Kentsel su ihtiyacını neredeyse tümüyle sondaj kuyularından sağlayan ve zaman içinde nüfusu hızla artan Manisa’da mevcut su kaynaklarının etkin bir şekilde yönetilmesi ve talebin sorunsuz bir şekilde karşılanması için güvenilir öntahminlere ihtiyaç vardır. Bu çalışmada, çeşitli ekonometrik tekniklerden yararlanarak Manisa’da kentsel su tüketiminin öntahmini yapılmış, alternatif yöntemlerin performansları karşılaştırılmıştır.
Supporting Institution
Manisa Celal Bayar Üniversitesi Rektörlüğü Bilimsel Araştırma Projeleri Birimi
Project Number
2017-056
Thanks
Çalışmayı maddi olarak destekleyen Manisa Celal Bayar Üniversitesi Rektörlüğü Bilimsel Araştırma Projeleri Birimi'ne teşekkür ederiz.
References
- Altunkaynak, A., Özger, M. & Çakmakçı, M. (2005). Water consumption prediction of Istanbul city by using fuzzy logic approach. Water Resources Management, 19(5), 641-654. https://doi.org/10.1007/s11269-005-7371-1
- Alvisi, S., Franchini, M. & Marinelli, A. (2007). A short-term, pattern-based model for water-demand forecasting. Journal of Hydroinformatics, 9(1), 39-50. https://doi.org/10.2166/hydro.2006.016
- Arbués, F., Garcia-Valiñas, M. Á. & Martınez-Espiñeira, R. (2003). Estimation of residential water demand: a state-of-the-art review. The Journal of Socio-Economics, 32(1), 81-102. https://doi.org/10.1016/S1053-5357(03)00005-2
- Babel, M. S., Gupta, A. D. & Pradhan, P. (2007). A multivariate econometric approach for domestic water demand modeling: an application to Kathmandu, Nepal. Water Resources Management, 21(3), 573-589. https://doi.org/10.1007/s11269-006-9030-6
- Bougadis, J., Adamowski, K. & Diduch, R. (2005). Short‐term municipal water demand forecasting. Hydrological Processes, 19(1), 137-148. https://doi.org/10.1002/hyp.5763
- Fırat, M., Yurdusev, M. A. & Mermer, M. (2008). Uyarlamalı Sinirsel Bulanık Mantık Yaklaşımı ile Aylık Su Tüketiminin Tahmini. Gazi Üniversitesi Mühendislik-Mimarlık Fakültesi Dergisi, 23(2).
- Firat, M., Turan, M. E. & Yurdusev, M. A. (2009a). Comparative analysis of fuzzy inference systems for water consumption time series prediction. Journal of Hydrology, 374(3), 235-241. https://doi.org/10.1016/j.jhydrol.2009.06.013
- Firat, M., Yurdusev, M. A. & Turan, M. E. (2009b). Evaluation of Artificial Neural Network Techniques for Municipal Water Consumption Modeling. Water Resource Management, 23, 617–632. https://doi.org/10.1007/s11269-008-9291-3
- Firat, M., Turan M. E. & Yurdusev, M. A. (2010). Comparative analysis of neural network techniques for predicting water consumption time series. Journal of Hydrology, 384, 46–51. https://doi.org/10.1016/j.jhydrol.2010.01.005
- House‐Peters, L. A. & Chang, H. (2011). Urban water demand modeling: Review of concepts, methods, and organizing principles. Water Resources Research, 47(5), 1-15. https://doi.org/10.1029/2010WR009624
- Jain, A., Varshney, A. K. & Joshi, U. C. (2001). Short-term water demand forecast modelling at IIT Kanpur using artificial neural networks. Water Resources Management, 15(5), 299-321.
- Liu, J., Savenije, H. H. & Xu, J. (2003). Forecast of water demand in Weinan City in China using WDF-ANN model. Physics and Chemistry of the Earth, Parts A/B/C, 28(4), 219-224. https://doi.org/10.1016/S1474-7065(03)00026-3
- MASKİ – Manisa Büyükşehir Belediyesi Manisa Su ve Kanalizasyon İdaresi Genel Müdürlüğü (2015), 2014 Yılı Faaliyet Raporu.
- MASKİ – Manisa Büyükşehir Belediyesi Manisa Su ve Kanalizasyon İdaresi Genel Müdürlüğü (2017), 2016 Yılı Faaliyet Raporu.
- MÇŞM – Manisa Valiliği Çevre ve Şehircilik İl Müdürlüğü (2015). Manisa İli 2014 Yılı Çevre Durum Raporu.
- Sebri, M. (2016). Forecasting urban water demand: A meta-regression analysis. Journal of Environmental Management, 183, 777-785. https://doi.org/10.1016/j.jenvman.2016.09.032
- Şen, Z. & Altunkaynak, A. (2009). Fuzzy system modelling of drinking water consumption prediction. Expert Systems with Applications, 36(9), 11745-11752. https://doi.org/10.1016/j.eswa.2009.04.028
- Wentz, E. A. & Gober, P. (2007). Determinants of small-area water consumption for the city of Phoenix, Arizona. Water Resources Management, 21(11), 1849-1863. https://doi.org/10.1007/s11269-006-9133-0
- Wong, J. S., Zhang, Q. & Chen, Y. D. (2010). Statistical modeling of daily urban water consumption in Hong Kong: Trend, changing patterns, and forecast. Water Resources Research, 46(3), 1-10. https://doi.org/10.1029/2009WR008147
- Yurdusev, M. A. & Fırat, M. (2009). Adaptive neuro fuzzy inference system approach for municipal water consumption modeling: An application to Izmir, Turkey. Journal of Hydrology, 365(3), 225-234. https://doi.org/10.1016/j.jhydrol.2008.11.036
- Zhou, S. L., McMahon, T. A., Walton, A. & Lewis, J. (2000). Forecasting daily urban water demand: a case study of Melbourne. Journal of Hydrology, 236(3), 153-164. https://doi.org/10.1029/2009WR008147
Abstract
World freshwater resources are used intensively for drinking water, agricultural irrigation and energy, but water resources are gradually decreasing due to increasing urbanization, changing climatic conditions and mismanagement. Especially in the face of global climate change it is faced with difficult situations in meeting the water demand in the cities, as seen in our country in the past years. Therefore, determining water demand, making periodic forecasts and preparing detailed plans as a result of these forecasts is vital for the organizations that provide water services in cities and all the beneficiaries who benefit from this service.
To manage the available water resources effectively and meet the demands without problems reliable forecasts are needed in Manisa which provides urban water needs almost entirely from drilling wells and which is rapidly increasing in population over time. In this study, urban water consumption in Manisa was estimated by using various econometric techniques and the performances of alternative methods were compared.
Keywords
Urban Water Consumption Forecasting Artificial Neural Network Analysis ARIMA Models Exponential Smoothing Manisa
Project Number
2017-056
References
- Altunkaynak, A., Özger, M. & Çakmakçı, M. (2005). Water consumption prediction of Istanbul city by using fuzzy logic approach. Water Resources Management, 19(5), 641-654. https://doi.org/10.1007/s11269-005-7371-1
- Alvisi, S., Franchini, M. & Marinelli, A. (2007). A short-term, pattern-based model for water-demand forecasting. Journal of Hydroinformatics, 9(1), 39-50. https://doi.org/10.2166/hydro.2006.016
- Arbués, F., Garcia-Valiñas, M. Á. & Martınez-Espiñeira, R. (2003). Estimation of residential water demand: a state-of-the-art review. The Journal of Socio-Economics, 32(1), 81-102. https://doi.org/10.1016/S1053-5357(03)00005-2
- Babel, M. S., Gupta, A. D. & Pradhan, P. (2007). A multivariate econometric approach for domestic water demand modeling: an application to Kathmandu, Nepal. Water Resources Management, 21(3), 573-589. https://doi.org/10.1007/s11269-006-9030-6
- Bougadis, J., Adamowski, K. & Diduch, R. (2005). Short‐term municipal water demand forecasting. Hydrological Processes, 19(1), 137-148. https://doi.org/10.1002/hyp.5763
- Fırat, M., Yurdusev, M. A. & Mermer, M. (2008). Uyarlamalı Sinirsel Bulanık Mantık Yaklaşımı ile Aylık Su Tüketiminin Tahmini. Gazi Üniversitesi Mühendislik-Mimarlık Fakültesi Dergisi, 23(2).
- Firat, M., Turan, M. E. & Yurdusev, M. A. (2009a). Comparative analysis of fuzzy inference systems for water consumption time series prediction. Journal of Hydrology, 374(3), 235-241. https://doi.org/10.1016/j.jhydrol.2009.06.013
- Firat, M., Yurdusev, M. A. & Turan, M. E. (2009b). Evaluation of Artificial Neural Network Techniques for Municipal Water Consumption Modeling. Water Resource Management, 23, 617–632. https://doi.org/10.1007/s11269-008-9291-3
- Firat, M., Turan M. E. & Yurdusev, M. A. (2010). Comparative analysis of neural network techniques for predicting water consumption time series. Journal of Hydrology, 384, 46–51. https://doi.org/10.1016/j.jhydrol.2010.01.005
- House‐Peters, L. A. & Chang, H. (2011). Urban water demand modeling: Review of concepts, methods, and organizing principles. Water Resources Research, 47(5), 1-15. https://doi.org/10.1029/2010WR009624
- Jain, A., Varshney, A. K. & Joshi, U. C. (2001). Short-term water demand forecast modelling at IIT Kanpur using artificial neural networks. Water Resources Management, 15(5), 299-321.
- Liu, J., Savenije, H. H. & Xu, J. (2003). Forecast of water demand in Weinan City in China using WDF-ANN model. Physics and Chemistry of the Earth, Parts A/B/C, 28(4), 219-224. https://doi.org/10.1016/S1474-7065(03)00026-3
- MASKİ – Manisa Büyükşehir Belediyesi Manisa Su ve Kanalizasyon İdaresi Genel Müdürlüğü (2015), 2014 Yılı Faaliyet Raporu.
- MASKİ – Manisa Büyükşehir Belediyesi Manisa Su ve Kanalizasyon İdaresi Genel Müdürlüğü (2017), 2016 Yılı Faaliyet Raporu.
- MÇŞM – Manisa Valiliği Çevre ve Şehircilik İl Müdürlüğü (2015). Manisa İli 2014 Yılı Çevre Durum Raporu.
- Sebri, M. (2016). Forecasting urban water demand: A meta-regression analysis. Journal of Environmental Management, 183, 777-785. https://doi.org/10.1016/j.jenvman.2016.09.032
- Şen, Z. & Altunkaynak, A. (2009). Fuzzy system modelling of drinking water consumption prediction. Expert Systems with Applications, 36(9), 11745-11752. https://doi.org/10.1016/j.eswa.2009.04.028
- Wentz, E. A. & Gober, P. (2007). Determinants of small-area water consumption for the city of Phoenix, Arizona. Water Resources Management, 21(11), 1849-1863. https://doi.org/10.1007/s11269-006-9133-0
- Wong, J. S., Zhang, Q. & Chen, Y. D. (2010). Statistical modeling of daily urban water consumption in Hong Kong: Trend, changing patterns, and forecast. Water Resources Research, 46(3), 1-10. https://doi.org/10.1029/2009WR008147
- Yurdusev, M. A. & Fırat, M. (2009). Adaptive neuro fuzzy inference system approach for municipal water consumption modeling: An application to Izmir, Turkey. Journal of Hydrology, 365(3), 225-234. https://doi.org/10.1016/j.jhydrol.2008.11.036
- Zhou, S. L., McMahon, T. A., Walton, A. & Lewis, J. (2000). Forecasting daily urban water demand: a case study of Melbourne. Journal of Hydrology, 236(3), 153-164. https://doi.org/10.1029/2009WR008147
Details
| Primary Language | Turkish |
|---|---|
| Subjects | Cross-Sectional Analysis |
| Journal Section | Research Articles |
| Authors | |
| Project Number | 2017-056 |
| Early Pub Date | March 25, 2024 |
| Publication Date | March 30, 2024 |
| Submission Date | February 27, 2024 |
| Acceptance Date | March 24, 2024 |
| Published in Issue | Year 2024 Volume: 4 Issue: 1 |
All works published in this journal are licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.