Evaluation of performance and optimum valve settings for pressure management using forecasted daily demand curves by artificial neural networks

Yıldız, Evren
For the appropriate operation and correct short term planning, daily demand curve (DDC) of municipal water distribution networks should be forecasted beforehand. For that purpose, artificial neural networks (ANN) is used as a new method. The proposed approach employs already recorded DDCs extracted from the database of ASKI (Ankara Water Authority) SCADA center and related independent parameters such as temperature and relative humidity obtained from DMI (State Meteorological Institute). In this study, a computer model was developed in order to forecast hourly DDCs using Matlab and related modules. Parameters that affect the consumption of the water were determined as temperature, relative humidity, human behavior (weekend or workday) and season. Randomly selected days were taken into account for performance of the ANN model. Forecasted DDC values were compared with recorded data and consequently the model gives relatively satisfactory results, an average of 75% match according to R2 values for Ankara N8-3 network. Same architecture was applied for Antalya network give better results, average of 85%. For planning purposes; total volume and peak water consumption values for the selected recorded days, the day before recorded days, ANN forecasted days and seasonal average was compared and seasonal average gave relatively better results. Using the forecasted DDC, (i) performance analysis of the pressure zone and (ii) optimum valve setting evaluation for pressure management were realized. The results of the study may help water utilities for short term planning of a water distribution network, rehabilitation of elements, taking counter measures and setting the valve openings for minimizing leakage and optimizing customer conformity of the distribution network.


Estimation of river flow by artificial neural networks and identification of input vectors susceptible to producing unreliable flow estimates
Kentel Erdoğan, Elçin (Elsevier BV, 2009-09-15)
Reliable river flow estimates are crucial for appropriate water resources planning and management. River flow forecasting can be conducted by conceptual or physical models, or data-driven black box models. Development of physically-based models requires an understanding of ail the physical processes which impact a natural process and the interactions among them. Since identification of the relationships among these physical processes is very difficult, data-driven approaches have recently been utilized in h...
Periodic stationarity conditions for periodic autoregressive moving average processes as eigenvalue problems
Ula, TA; Smadi, AA (American Geophysical Union (AGU), 1997-08-01)
The determination of periodic stationarity conditions for periodic autoregressive moving average (PARMA) processes is a prerequisite to their analysis. Means of obtaining these conditions in analytically simple forms are sought. It is shown that periodic stationarity conditions for univariate and multivariate PARMA processes can always be reduced to eigenvalue problems, which are computationally and analytically easier to deal with. Two different lumpings of the periodic process are considered along this li...
Effectiveness of combined sewer overflow treatment for dissolved oxygen improvement in the Chicago Waterways
Alp, Emre; ZHANG, HENG; Lanyon, R. (IWA Publishing, 2007-01-01)
An Use Attainability Analysis (UAA) has been initiated to evaluate what water-quality standards can be achieved in the Chicago Waterway System (CWS). There are nearly 200 combined sewer overflow (CSO) locations discharging to the CWS by gravity. Three CSO pumping stations also drain approximately 140 km(2). Because of the dynamic nature of the CWS the DUFLOW model that is capable of simulating hydraulics and water-quality processes under unsteady-flow conditions was used to evaluate the effectiveness of wat...
Performance evaluation of satellite- and model-based precipitation products over varying climate and complex topography
Amjad, Muhammad; Yılmaz, Mustafa Tuğrul; Yücel, İsmail; Yılmaz, Koray Kamil (Elsevier BV, 2020-05-01)
Accuracy assessment of precipitation retrievals is a pre-requisite for many hydrological studies as it helps to understand the source and the magnitude of the uncertainty in hydrological response variables, particularly over regions with complex topography. This study evaluates GPM IMERGv05, TMPA 3B42V7, ERA-Interim, and ERA5 precipitation products using 256 ground-based gauge stations between 2014 and 2018 over Turkey known to have complex topography and varying climate. Error statistics, categorical perfo...
Comparison of prognostic and diagnostic surface flux modeling approaches over the Nile River basin
Yılmaz, Mustafa Tuğrul; Zaitchik, Ben; Hain, Chris R.; Crow, Wade T.; Ozdogan, Mutlu; Chun, Jong Ahn; Evans, Jason (American Geophysical Union (AGU), 2014-01-01)
Regional evapotranspiration (ET) can be estimated using diagnostic remote sensing models, generally based on principles of energy balance closure, or with spatially distributed prognostic models that simultaneously balance both energy and water budgets over landscapes using predictive equations for land surface temperature and moisture states. Each modeling approach has complementary advantages and disadvantages, and in combination they can be used to obtain more accurate ET estimates over a variety of land...
Citation Formats
E. Yıldız, “Evaluation of performance and optimum valve settings for pressure management using forecasted daily demand curves by artificial neural networks,” Ph.D. - Doctoral Program, Middle East Technical University, 2011.