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2022, Europan journal of science and technology
Drinking water is becoming a crucial problem all over the world because of global warming. In crowded metropolises such as Istanbul, the problem of drinking water is a serious problem. In this study, it is aimed at developing a forecasting model by using the occupancy rates of Istanbul's dams between 2011 and 2020. The occupancy rate of each dam is then estimated using the best model for the years 2021 and 2022. According to the results of the estimation model, a decrease in the occupancy level of the dams in Istanbul is predicted. Therefore, it is thought that necessary measures should be taken to avoid water shortages.
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 technologies in households and reduction in water supply loss through investments on distribution infrastructure.
The distribution of water to every household is vital in cities nowadays. Its key role in all spheres of human existence and development has lead to human society facing the problem of water scarcity in many regions of the world. The problem gains proportion with the increase in population and in water demand per capita associated with economic development. With an increased migration to cities registered in the last decades, urban water supply planning is a challenging, complex task, leading to a growing pressure on the watersheds and to the need of identifying and bringing in water from additional sources. In Istanbul – one of the 25 biggest cities in the world – the effect of growing population on water availability is especially obvious. Drinking water resources in Istanbul have been insufficient to satisfy the need of the increasing population since historical times, and water stress has been a driver of many water infrastructure projects throughout centuries. Using the system dynamics modelling approach, we try to analyse in this paper the influence of population growth on water availability in Istanbul, with particular emphasis on in-migration. We focus as well on city’s need for water input from other watersheds. By building a system model, the problem of urban water demand and supply in Istanbul is visualized, giving an analytical background for managerial and political decision-making.
Water Supply
Water scarcity is becoming a progressively more serious global issue. Assosa town in Ethiopia faces serious water scarcity problems due to rapid population growth and urban expansion. This study aims to model the water demand of Assosa town using a forecasting model. Four scenarios were developed: population growth, living standards, water loss reduction, and a combination of these. The water demand and unmet demands for each scenario were evaluated. Results show that the demand for water and supply will vary significantly if the present state continues. In the base year (2018), the overall water demand is 2.07 gigalitres (GL) and the unmet demand is estimated as 0.096 GL. The water demand grows to 3.71 GL under the reference scenario in 2035. The combination of population growth and improved living standard scenarios is observed to impact greatly on water demand. The total water demand of this scenario was estimated to be 7.14 GL latterly in the projection period and the unmet dema...
Medium-term Forecasting for City Water Demand and Revenue, 2018
The combination of forecasting and planning has increased prominence within few decades and now receives considerable attention from both academics and practitioners. Palestine municipalities are facing complex circumstances because of the climate change (lack of rainfall) and due to the Israeli occupation. Water resources are decreasing by the passage of time. Therefore, it is necessary to focus on water service projects for best exploit of resources given the growth of population. In this research, we forecasted the consumption used by citizen in the medium-term future and forecasted revenues from water service. We conducted the forecasting using the following forecasting algorithms: Auto-Regressive Integrated Moving Average (ARIMA), Hybrid ARIMA, Singular Spectrum Analysis (SSA), and Linear Regression. We applied them on dataset collected from KhanYounis municipality (KHM)-department of customer services. We found that the best algorithm is Hybrid ARIMA which gave the Mean Absolute Percentage Error (MAPE) of 17.38%. Finally, we forecasted the whole city of KhanYounis city. Generally, we found that the maximum water consumption for the overall city after five years will increase to about 8.4% compared to 2017, but the minimum water revenue will decrease to about 3.8% compared to 2017.
Water, 2023
Water demand forecasting plays an important role in the sustainable management of water resources, especially in countries facing water scarcity challenges, such as the United Arab Emirates (UAE). Al-Ain, the second-largest city within the Emirate of Abu Dhabi and the fourth largest in the UAE, faces the dual challenge of anticipated population growth and forthcoming development initiatives. These factors are set to exert added pressure on the city's water resources. Hence, Al-Ain City requires an immediate assessment of future water demands as a critical step toward achieving sustainable development. The main objective of this study is to conduct a systematic analysis of historical consumption patterns and other relevant factors to predict future water demand and to present a water demand forecasting model to project the water requirements of Al-Ain City up to the year 2030. The proposed "Linear Forecast Model" for Al-Ain City is developed using the IWR-MAIN software (Version 6.0), with its core code developed by the U.S. Army Corps of Engineers' Institute for Water Resources. The results of this model suggest that the total water demand is projected to increase by 45% by the year 2030. Among the sectors, the residential sector is expected to have the highest water demand, accounting for approximately 61% of the total water demand by 2030. The governmental and agricultural sectors are estimated to contribute 20% and 10% to the total demand, respectively, with the remaining 9% distributed across the other four sectors.
Journal of Civil Engineering Frontiers, 2022
The analysis of the water distribution network [WDN] is essential for a sufficient water supply. In the present study, the water distribution network [WDN] of the Narangi village in Virar was analysed using WaterGEMS software. The obtained results from the analysis were used to evaluate the impact of the growing population on the water distribution system in the coming decades, i.e., from 2020 to 2050. For population forecasting, the arithmetical increase and geometrical increase methods were adopted which were later used as “Low Population Growth Scenario" [LGS] and "High Population Growth Scenario" [HGS] respectively. The results obtained show that the maximum flow is observed in pipe 1, and the maximum demand is seen at junction 67. In 2020, the flow rate in Pipe 1 was 1036 litres per minute, but by 2050, it had risen to 1655 litres per minute. Demand at junction 67 was 54 litres per minute in 2020, and it had escalated to 86 litres per minute by 2050. This shows a...
Ekoloji, 2008
In this study, daily water quantity data in the Porsuk Dam which is taken from State Hydraulic Works (SHW) 3 rd Regional Directorate, reaching during January 1992-November 2005 was examined. Then, monthly average values were determined by using these daily data and analyzed through Box-Jenkins method. ARIMA (1,1,1) model was found appropriate to forecast the amount of water in the Porsuk Dam. A forecast related to water quantity which comes to the dam for 12-months is realized. In December 2004, monthly average water quantity reaching to the Dam was 256.000 m 3 and it is forecasted as 360.590 m 3. In November 2005, monthly average water quantity reaching was 244.270 m 3 , and it is forecasted to be 206.560 m 3 .
Desalination, 2012
The forecast of water demand is important for Saudi Arabia which is characterized by a scarcity of its water supplies and a dependence on costly desalination plants to satisfy the water needs of its population. The forecasting task is even more challenging for tourist cities. The paper presents a probabilistic-based methodology for the forecast of future water demand for the city of Mecca in Saudi Arabia. Because of its religious nature, the city attracts visitors all year long. The large and variable number of visitors put considerable strains on the management of water supply especially that the city relies exclusively on desalination. Besides the random influx of visitors, the development of a sound forecast model is further complicated by the uncertainties associated with other key explanatory variables such as the economic activity, which is largely dependent on fluctuating oil prices. All these factors limit the usefulness of any deterministic forecast model. This paper develops a forecast model that incorporates explicitly the uncertainties associated with local population growth, tourist's influx, household size, household income as well as conservation measures. The methodology makes use of historic time series records of water consumption and applies Monte Carlo sampling to describe the associated uncertainties.
This study was carried out in Kılıçkaya Dam Lake in northeastern Turkey. Kılıçkaya Dam is a dam built between 1980-1989 to generate energy on Kelkit Stream. With this study, the water occupancy rates of Kılıçkaya Dam Lake, which has a proportionally large area, between the years 2010-2021 were compared and evaluated. If a general conclusion is drawn for Kılıçkaya Dam Lake, it has been determined that the water occupancy rates between the years 2010-2021 varied between 18.40 and 56.80 percent. The slope line of the water occupancy rates obtained in this study is downward. The results showed that the water occupancy rates in Kılıçkaya Dam Lake have a decreasing trend on an annual basis. When the average of the water occupancy rates between 2010-2021 is evaluated, the water occupancy rate values in Kılıçkaya Dam Lake indicate drought. The results obtained will be of great benefit to various users and decision makers in terms of their future planning within the framework of a comprehensive and large-scale drought management plan that is proposed to be prepared for the Kılıçkaya Dam Lake.
This article provides an overview of water demand management, highlighting its importance in optimizing water usage, reducing waste, and ensuring the sustainability of water resources. Water demand management involves implementing various strategies, including water conservation, leakage reduction, demand-based pricing, public awareness, water recycling, rainwater harvesting, and efficient agricultural practices. The article explores the application of demand management in different sectors, such as households, irrigation, and industries. It emphasizes the need for accurate data, decision-making processes, and regulatory measures to effectively manage water demand. The benefits of water demand management include economic advantages, environmental protection, climate change adaptation, and enhanced water security. The article also acknowledges the challenges in implementing demand management, particularly in underdeveloped regions, and suggests the integration of both water supply and demand management approaches. Finally, it discusses the projected increase in urban population and the significance of water demand management in addressing water scarcity issues and ensuring the adequacy of water supply infrastructure for growing urban areas.
Water Resources Management, 2010
IWR-MAIN software is used in this paper to forecast water demand in the Emirate of Umm Al-Quwain (UAQ), located in the northern part of the United Arab Emirates (UAE), for the next twenty 5 years. Two different databases are used. The first one provides average yearly water consumptions since 1980, while the second provides more detailed monthly water consumptions from 2000. The correlation between three different independent variables and water consumption is studied. These variables are population of UAQ, average temperature, and average rainfall. Results show that population is the most significant variable that affects water consumption in Umm Al-Quwain. Several calibration simulations are performed and each simulation is divided into two periods. In the first period the software "Statistical Package for the Social Sciences" (SPSS) is used to determine the correlation coefficients between the independent variables and actual water consumptions. These coefficients are used in IWR-MAIN over the second period to calculate values of water demand which are compared against actual water consumptions. Model calibration indicates that starting the calibration in 1999 in database one and 2006 in database 2 minimizes differences between actual and simulated water demands. Therefore, these simulations were used as the bases for several forecasting scenarios of water demand in Umm Al-Quwain. Results of one of these scenarios show that 50% increase in water demand is expected by the year 2015 and double of the current demand will be needed before 2025. In another forecasting
The study assessed water demand in WA municipality. The methodology employed time series technique using Box-Jenkins methodology to describe the water demand situation in WA municipality. The findings revealed that water demand are skewed to the left, indicating that most of the values are concentrated at the left of the mean and this means that majority of the values are below the average indicating high water demand in the WA municipality. The peakness demonstrated that a platykurtic has a flattened than normal peak and this suggests that most of the water demands are spread to the extreme sides of the curve also exhibiting high water demand in the WA Municipality . The findings also revealed that ARIMA (1, 1, 0) best fit the water demand in WA municipality. Based on the findings of the study the researcher can conclude that water demand in the WA municipality is likely to experience steady increase from 2019-2021. ARIMA (1, 1, 0) was identified to be the best fit model for water demand situation in the WA municipality. Nevertheless, quadratic trend model was noted to be the best model that described the water demand. The management of Ghana Water Company can resort from Donor countries to come to the aid of the company by donating money or equipment for the improvement of the water demand situation in the urban areas. The government of Ghana should allocate more resources to the water companies in order to acquire water plants so as to increase water distribution in the urban areas.
Water resources management, 2005
Water Resources Management, 2014
With concerns relating to climate change, and its impacts on water supply, there is an increasing emphasis on water utilities to prepare for the anticipated changes so as to ensure sustainability in supply. Forecasting the water demand, which is done through a variety of techniques using diverse explanatory variables, is the primary requirement for any planning and management measure. However, hitherto, the use of future climatic variables in forecasting the water demand has largely been unexplored. To plug this knowledge gap, this study endeavored to forecast the water demand for the Metropolitan Waterworks Authority (MWA) in Thailand using future climatic and socioeconomic data. Accordingly, downscaled climate data from HadCM3 and extrapolated data of socioeconomic variables was used in the model development, using Artificial Neural Networks (ANN). The water demand was forecasted at two scales: annual and monthly, up to the year 2030, with good prediction accuracy (AAREs: 4.76 and 4.82 % respectively). Sensitivity analysis of the explanatory variables revealed that climatic variables have very little effect on the annual water demand. However, the monthly demand is significantly affected by climatic variables, and subsequently climate change, confirming the notion that climate change is a major constraint in ensuring water security for the future. Because the monthly water demand is used in designing storage components of the supply system, and planning inter-basin transfers if required, the results of this study provide the MWA with a useful reference for designing the water supply plan for the years ahead. Keywords ANN. Climate change. Climate downscaling. Sensitivity analysis. Thailand. Water demand forecasting 1 Introduction The reliable supply of safe drinking water is the primary objective of any water utility and over the years rapid advances have been made in this regard worldwide. However, with time, the
Musa Muhammed Muhammad Ridwan, 2020
Abstract This research was conducted to forecast the population of the year 2030 by using geometric progression method, and also to know the average growth rate and daily water demand of Maiduguri town. From the year 1970 to 2030 Average growth rate, population for the year 2030, daily water demand, maximum daily rate, maximum daily flow, maximum hourly rate and maximum hourly flow were calculated and presented.
2021
Water and energy are so versatile that play great role in fulfilling the daily requirements of human life. Having knowledge on the future water and energy demand of the world, country, region and even a single city/town helps for planning and establishing water and energy policies. A regression model was used to estimate the energy and water demand considering the socio-economic drivers as parameters. An average population growth rate of 5.2% and a GDP growth rate of 11% were used as base scenarios to predict the residential, commercial and industrial energy demands. Population and GDP per capita based scenario was used to predict the transport (street-lighting) energy demand. The total energy demand for residential, commercial, industrial sectors and street-lighting was around 50 and 190 Peta Joule in 2030 and 2050 respectively. Additional, the energy requirement for water distribution, transmission, and water treatment was determined. Similarly, this scenario was used to determine...
Hydrological Sciences Journal-journal Des Sciences Hydrologiques, 2016
Forecasting future water demands has always been of great complexity, especially in the case of tourist cities which are subject to population fluctuations. In addition to the usual uncertainties related to climate and weather variables, daily water consumption in Mashhad, a tourist city is affected by a significant different fluctuation. Mashhad is the second most populous city in Iran. The number of tourists visiting the city is subject to national and religious events, which are respectively based on the Iranian formal calendar (secular calendar) and the Arabic Hijri calendar (Islamic religious calendar). Since religious events move relative to the secular calendar, the coincidence of the two calendars results in peculiar wild fluctuations in population. Artificial neural networks (ANNs) are chosen to predict water demand under such conditions. Three types of ANNs, feedforward back-propagation, cascade-forward and radial basis functions, are developed. In order to track how population fluctuation propagates in the model and affects the outputs, two sets of inputs are considered. For the first set, based on evaluating several repetitions, a typical combination of variables is selected as inputs, whereas for the second set, new calendar-based variables are included to decrease the effect of population fluctuations; the results are then compared using some performance criteria. A large number of runs are also conducted to assess the impact of random initialization of the weights and biases of networks and also the effect of calendar-based inputs on improvement of network performance. It is shown that, from the points of view of performance measures and unchanging outputs through numerous runs, the radial basis network that is trained by patterns including calendar-based inputs can provide the best domestic water demand forecasting under population fluctuations.
Population projections are necessary to estimate the future population by following the trend (increase) line. Population projections are significant for managing and planning the research area. This study aims to examine the water need and water consumption of Gaziantep province. In order to determine the future population of Gaziantep city, İlbank method was utilized in the calculations. Düzbağ Dam which is considered to supply drinking water to Gaziantep is not sufficient for close future and in order to supply water to city it is estimated that there will be need for new water resources. Therefore, state corporation should take required precautions.
760: 761: 762: 763: The IASTED 2012 African Conferences, 2012
Rapid population growth, accompanied with increase in affluence, continues to put the semi-arid environments' limited water resources under pressure. This study has attempted to compare population projections for two cities of Botswana (Gaborone and Francistown) using various methods including the Logistic Curve, and Artificial Neural Networks (ANNs). For both the cities, the Geometric Increase, Logistic Curve and ANNs performed better. The ANNs (-0.03 % deviation from observed) was the best for Gaborone City followed by the Geometric Increase (+2.97 % deviation from observed) and Logistic Curve (-3.40 deviation from observed). For the City of Francistown, the Logistic Curve outperformed the Geometric Increase and the ANNs with deviations of -0.03 %, -0.27 %, and +11.6 5 respectively. The findings indicate that the Cohort Component method for population projections should be supplemented with the superior methods of Geometric Increase, Logistic Curve and ANNs. As census data increase with time, ANNs might prove to be the best approach. With improved population projections, determining likely future water demands against available water resources could be improved and this can help feed into water resources planning strategies.
International Journal of Advanced Science and Engineering, 2019
n-revenue water remains one of the main challenges facing the town. This study deals on the analysis of water demand scenario and future water demand forecasting for Yejube town. A mixed cross-sectional research method was implemented to analysis the past and future water demand of the town. The outcome of this study found that the municipal average daily water consumption per capita was 14.3l/c/day and 16l/c/day respectively in 2017 and 2018. The water supply coverage of the town is low when we compare the regional and international standards. Water production and demand are unbalanced; due to continuous interruption of the water supply system inhabitants are facing water related problems. And also, 20.38% and 24% of the water production lost in the distribution system before reaching to the end customers. The population of the town in 2040 expected to reach24807 with an average daily per capita water consumption of 36.7l/day. Generally, delivery of hygienic water supply is one of the key influencing factors that significantly subsidize to the socioeconomic renovation of a country by enlightening the health thereby increasing life standard and economic productivity of the society. Therefore, accurate forecast of future water demand plays a crucial role in optimizing the need for potable water resources and effective water allocation among competing users.
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