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

Triangle of Environment, Water and Energy: A Sociological Appraisal

Prediction of urban residential end-use water demands by integrating known and unknown water demand drivers at multiple scales II: Model application and validation

As water scarcity becomes the new norm in the Western United States, states such as California have increased their efforts to improve water resilience. Achieving water security under climate change and population growth requires an integrated multi-sectoral approach, where adaptation strategies combine water supply and demand management interventions. Yet, most studies consider supply-side and demand-side water management strategies separately. Further, publicly available data to assess the effectiveness of these strategies and their dependency on individual and collective human behavior is often hard to find and unstructured. Water conservation efforts are driven by water scarcity and policy requirements, with conservation targets and water use restrictions often designed assuming a degree of rationality of human behavior and based on cost-effective options and ease of implementation. In this work, we develop a data-driven analysis aimed at evaluating historical synergies and possible trade-offs between water supply and demand management strategies in California. Our analysis is based on CaRDS – the statewide California Residential water Demand and Supply open dataset, which contains monthly values of water supply and residential water demand for 404 water suppliers in California from 2013 to 2021. In this time span, Californian water agencies had to adapt and mitigate the effects of two droughts (in 2012-2016 and 2020-2022) through residential water demand reductions, as well as address rapid changes in demand associated with the global COVID-19 pandemic (2020). Our trade-off analysis integrates the following three sequential steps: (i) trend analysis – we use Random Forest regression to control for seasonal factors (i.e., temperature and precipitation) that affect water supply and demand at the utility scale; (ii) multi-criteria trade-off analysis – we examine the temporal relationship between water supply and demand by utilizing Dynamic Time Warping to identify trade-offs and management patterns. Next, we cluster water suppliers in 6 groups based on their combined management patterns; (iii) and driver analysis – we utilize explainable Machine Learning by combining SHAP (Shapley values) with LGBM (Light Gradient Boosting Method) to identify the drivers of each cluster. Potential drivers include climatic region, water supply portfolio, indoor vs. outdoor water use, local and state policies,  population, supplier size, and income. We finally validate the results of our analysis by comparing our findings with responses from water supplier interviews carried out in 2017 and reveal differences between intended and actual water management outcomes. This research contributes insights into the combined effects of policies on water supply and demand at a statewide level. Further it facilitates the formulation of adaptive resilience strategies for human actors in water management and decision makers alike to address vulnerability of small and large water systems to a rapidly changing climate and a society with non-linear changes in human behavior.

Lower reaches of the Amu Darya River Basin (LADB) is one of the typical regions which is facing the problem of water shortage in Central Asia. During the past decades, water resources demand far exceeds that supplied by the mainstream of the Amu Darya River, and has resulted in a continuous decrease in the amount of water flowing into the Aral Sea. Clarifying the dynamic relationship between the water supply and demand is important for the optimal allocation and sustainable management of regional water resources. In this study, the relationship and its variations between the water supply and demand in the LADB from the 1970s to 2010s were analyzed by detailed calculation of multi-users water demand and multi-sources water supply, and the water scarcity indices were used for evaluating the status of water resources utilization. The results indicated that (1) during the past 50 years, the average total water supply (TWS) was 271.88 × 108 m3/y, and the average total water demand (TWD) was 467.85 × 108 m3/y; both the volume of water supply and demand was decreased in the LADB, with rates of −1.87 × 108 m3/y and −15.59 × 108 m3/y. (2) percentages of the rainfall in TWS were increased due to the decrease of inflow from the Amu Darya River; percentage of agriculture water demand was increased obviously, from 11.04% in the 1970s to 44.34% in 2010s, and the water demand from ecological sector reduced because of the Aral Sea shrinking. (3) the supply and demand of water resources of the LADB were generally in an unbalanced state, and water demand exceeded water supply except in the 2010s; the water scarcity index decreased from 2.69 to 0.94, indicating the status changed from awful to serious water scarcity. A vulnerable balanced state has been reached in the region, and that water shortages remain serious in the future, which requires special attention to the decision-makers of the authority.

Water is an essential resource for the well-being of humans as well as for ecosystems. In this regard, the increasing water scarcity areas has become one of the major problems faced by humanity. In Malaysia, Selangor is considered a water-stressed area due to the increase in water demand and limited suitable fresh water resources for treatment and distribution. The increase in population as well as urbanization and industrialization made the rivers in Selangor arguably the most polluted compared to other states. These situations result in a series of unscheduled water supply interruption over the years and negatively impact the majority of consumers. Projected water demand also indicates that the existing water supplies are not sufficient in the long run, therefore, it is deemed required to study the water demand and supply gap in Selangor to ensure the current water management is sustainable for the remote future. This paper mainly discusses on the current water production from Water Treatment Plants as well as projection of water demand which also foresee the future water deficit in Selangor. The method used in this study was based on review of secondary data acquired from available published report and website, while the assessment of water demand conducted comprise of calculation of projected population, projected domestic water demand, projected total water demand and water deficit up to year 2050. According to the result obtained, the existing water demand and supply in Selangor is 4,967 MLD, meanwhile, the projection of water demand in Selangor up to year 2050 is 7,011 MLD with the projected water deficit of 2,044 MLD. The findings of this paper are essential in water resources planning and management, particularly in terms of additional raw water supply that will be required to cater to the future water demand in Selangor.

Book Reviews

Educating Future Water Resources Managers

Climate change and other dynamic changes, such as demographic change, pose challenges for public water supply in Germany. This study contributes to the identification of hot spot regions that could experience increased water shortages in the future through nationwide, regionalized forecasts of water demand in domestic, industry and agriculture sectors and their balancing with projections of groundwater recharge. Multi-sectoral water demand forecasts for the periods 2021-2050, 2036-2065 and 2069-2098 were prepared using a top-down approach at NUTS-3 level (cities and districts).The total water demand in the domestic sector in Germany averages approx. 3.7 billion m³/a in the reference period 1998-2019. In the lower scenario, it decreases to approx. 2.2 billion m³/a by the end of the century. In the upper scenario, total water demand in the domestic sector in Germany increases to around 4.1 billion m³/a. Industrial water demand could fall to around half (10.9 billion m³/a) as early as 2030 compared to the reference period (approx. 21.6 billion m³/a) due to a sharp decline in cooling water demand. From the middle of the 21st century onwards, it is expected to stagnate at around 6.1 billion m³/a. Depending on the scenario, the irrigated agricultural area in Germany will almost double (RCP 2.6) or almost triple (RCP 8.5) by the end of the century, resulting in a near tripling (RCP 8.5) of irrigation volumes. Overall, the total water demand in Germany decreases significantly in both scenarios. In the lower scenario, water demand falls from around 26 billion m³/a to around 9 billion m³/a by the end of the century. In the upper scenario, it is reduced to around 12 billion m³/a by the end of the century. These enormous decreases in total water demand are due to reductions in water demand in the energy sector, which overlay increases in domestic and agricultural water demands.mHM-simulations of groundwater recharge based on climate projections show constant or increasing groundwater recharge rates in large parts of Germany in the ensemble median for the 2021-2050, 2036-2065 and 2069-2098 time slices, assuming both RCP 2.6 (21 RCMs) and RCP 8.5 (49 RCMs). However, declining groundwater recharge rates may also occur in certain regions, particularly in south-western Germany. In the 25th percentile of the model ensemble, falling groundwater recharge rates occur under RCP 2.6 in southern and western Germany. Towards the end of the century, groundwater recharge rates increase in eastern Germany. Under RCP 8.5, the 25th percentile of the model ensemble shows mostly constant or increasing groundwater recharge rates. However, south-western Germany is characterized by a significant decline in groundwater recharge.The risk index water balance RIWB was defined as an indicator to evaluate the regional water supply in relation to the balance between water demand and groundwater recharge. The RIWB shows that the ratio of water demand to groundwater recharge can be expected to remain the same or improve in the most regions, while, depending on the scenario, 4% or 11% of districts/cities, particularly in northern Germany, must prepare for a deterioration in this ratio.

Water demand forecasting has become an essential ingredient in effective water resource planning and management. In water-scare urban areas of developing countries, this emphasis on accurate forecasting is particularly important for effective water resource planning and management. This paper presents an econometric water demand model for forecasting future residential water requirements for a densely populated area of Jaipur city. This study used an ordinary least squared (OLS) regression model to measured the impact of household income (I), age of respondent (A_R), household size (SIZE), age of home (A_H), wealth (W), asset score (AS), dwelling status (DWELL), monthly expenditure on water supply (EXP_WS), number of bathrooms (BATHR), and number of rooms (RMS) on residential water use (RWU) using data from a survey of 149 representative households in the study area. Empirical results indicate that residential water demand of the study area is characterized by I, SIZE, AS, and EXP_WS, with SIZE (0.542) and AS (0.418) having a major influence on RWU, as shown by their high standardized model coefficient values at 95% confidence intervals. Therefore major saving should be achieved by technological developments in water efficient appliances combined with education in efficient use of water.

A novel newsvendor model-based framework for regional industrial water resources allocation that considers uncertainties in water supply and demand was proposed in this study. This framework generates optimal water allocation schemes while minimizing total costs. The total cost of water allocation consists of the allocated water cost, the opportunity loss for not meeting water demand, and the loss of the penalty for exceeding water demand. The uncertainties in water demand and supply are expressed by cumulative distribution functions. The optimal water allocation for each water use sector is determined by the water price, the unit loss of the penalty and opportunity loss, and the cumulative distribution functions. The model was then applied to monthly water allocation for domestic, industrial, and agricultural water use in two counties of Huizhou City, China, whose water supply mainly depends on Baipenzhu Reservoir. The water demand for each water use sector and the monthly reservoir inflow showed good fits with the uniform and P-III distributions, respectively. The water demand satisfied ratio for each water use sector was stable and increased for the optimal water allocation scheme from the newsvendor model-based framework, and the costs were lower compared with the actual water allocation scheme. The novel framework is characterized by less severe water shortages, lower costs, and greater similarity to actual water use compared with the traditional deterministic multi-objective analysis model, and demonstrates strong robustness in the advantages of lower released surplus water and higher water demand satisfied ratio. This novel framework yields the optimal water allocation for each water use sector by integrating the properties of the market (i.e., determining the opportunity loss for not meeting water demand) with the government (i.e., determining the water price and the loss of the penalty for exceeding water demand) under the strictest water resources management systems.

BackgroundThe city of Addis Ababa is under rapid development and there are enormous construction activities along with rapid urbanization, and industrialization. These anthropogenic actions combined with population growth rate are affecting the water demand of the city. The overall purpose of this study is to model water supply and demand of the city and to identify potential water management strategies that supports the sustainable development goal number six (SDG6)—clean water and sanitation.MethodsWe employed the Water Evaluation and Planning system (WEAP) modelling framework to analyze different scenarios for water demand and supply. The scenarios include population growth, living standard, as well as other supply and demand strategies.ResultsFor the modelling period, the reference scenario shows unmet water demand increases by around 48%, from 208 to 307 million cubic meter in 2015 and 2030 respectively. High population growth rate and high living standard scenarios have a great negative impact on the water supply system.ConclusionsSatisfying the future water demand of Addis Ababa will depend on the measures which are taken today. The integrated water management practices such as reuse of water and the selected future scenarios are proposed to decrease and manage the unmet water demand of the city. Hence, future predicted scenarios which is the combination of the external factors (i.e. population growth rate and living standard) and water management strategies were considered. From the analyzed scenarios, optimistic future strategies will support the management of the existing water supply and demand system of the city. Similarly, in the integrated management strategies scenario, it was assumed that measures were taken at both the demand and supply side to improve the efficiency of water in the entire chain. Thus, if the water sector professionals and other concerned bodies consider the selected scenarios, it will go a long way to solve the water shortage problem in the city, and this will also help to promote sustainable water management.

Quantifying and spatial mapping the ecosystem services driven by land use change will help better manage land and formulate relevant ecological protection policies. However, most studies to date just focused on water supply services, and ignore water demand services and their supply–demand coupling mechanisms. Ecosystem service flow could be used to evaluate the imbalance between water supply and demand. Therefore, this study takes the Yellow River Basin as the research object to quantify the supply, demand, and spatial flow of water provision services. The results showed that land use and land cover (LULC) played a critical role in the spatial distributions of water supply and demand in the Yellow River Basin. The total water supply was 3.03 × 1011 m3, with a range of 3.29 × 108 m3 to 7.35 × 1010 m3 for different sub-watersheds. The spatial patterns of water supply were strongly different from those in water demand, resulting in obvious spatial mismatches. There was a higher water demand for constructional areas and agricultural lands, which had relatively lower water supply. Most water areas and natural lands provide much more water supply than demand. We used a water flow process to assess the water provision service between water supply side and demand side. The water flow process suggested that the Yellow River Basin had an obvious imbalance between water supply and demand depending on land use and populations, which would help policy makers to manage water resources through optimizing land management in different cities and finally achieving a balance between water supply side and demand site.

Increasing urbanisation and climate change uncertainties are putting pressure on regional authorities to revisit water management strategies in Western Sydney (Australia). This chapter examines water use patterns, demand and supply options in the South Creek catchment—a typical peri-urban catchment in Western Sydney. If present water management practices are continued, the water demand in the catchment is estimated to be more than double, growing from 53 GL/yr under the ‘current’ scenario, to 107 GL/yr under the ‘future’ scenario representing the expected conditions around the year 2025. Most of this increase will be due to residential and non-residential water use, followed by increases in irrigation requirements for recreational space (parks and golf courses). The macro water use, demand and availability analysis suggests that nearly 50 % of the ‘current’ and 47 % of the ‘future’ potable water demand could be replaced with non-potable water. The potential availability of non-potable water resources is estimated to be more than double of the potential demand for non-potable water in the catchment. This provides an opportunity to meet the region’s domestic, industrial, agricultural and environmental water demands provided all water resources are integrated, used and reused in a harmonised fashion. The stormwater and wastewater is to be seen as a ‘resource’, rather than a ‘waste’ in this new paradigm of integrated water supply management.

Water Economics and PolicyOnline Ready No AccessPolicy Nook — Policy Note: An Alternative Approach to Designing Tariffs for Household Water Use: The Case of Los AngelesMichael HanemannMichael HanemannDepartment of Economics, Arizona State University USAhttps://doi.org/10.1142/S2382624X22710047Cited by:0 PreviousNext AboutSectionsView articleView Full TextPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack CitationsRecommend to Library ShareShare onFacebookTwitterLinked InRedditEmail View article References Araya, F, K Osman and KM Faust [2020] Perceptions versus reality: Assessing residential water conservation efforts in the household. Resources. Conservation and Recycling, 162, 105020. Crossref, Google Scholar Attari, SZ [2014] Perceptions of water use. Proceedings of the National Academy of Sciences, 111(14), 5129–5134. 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China is planning to expand its coal power generation to meet its energy demand and support the economic development. The current level of water use for thermal power generation is 8% of total water use, China is a water-stressed country which is facing many new challenges including climate change and population growth. China’s future coal power industry will add further pressures on already stressed water resources. This raised the key question on how the limited water resources can be managed to meet the demand of planned coal power expansion. A great level of understanding on the present status of water use and forecasting future demand in coal power plant is very important to answer this question. However, knowledge gap, data availability and accessibility are the major challenge in this regard. This paper attempts to improve the knowledge of the water demand in the coal power generation plant in China by using a simple water use model. Furthermore, a method is proposed to forecast future water demand in coal power plant. The proposed method is applied for forecasting water demand in Shaanxi coal power bases in Northern China under four scenarios. The results showed that the future water demand for Shaanxi coal power base will increase by 102–161% compared to current use under different scenarios in order to increase the production capacity by 206%. Adopting the optimum level of current status of water use, it is possible to limit the increase in water demand by 102% or 47.119 million-m3. It is expected that the finding of the study would help decision-making processes in water resources management in Chinese coal power generation.