Residential Water Consumption Research Articles

Residential Water Consumption Patterns: A Theoretical Review

The global water crisis and acute increase in water demand have increased stress on water resources in urban areas, particularly in water-scarce regions like Egypt. Many current strategies of sustainable water demand management show low effectiveness due to a lack of understanding of how water is used in households, and a failure to consider the environmental and urban diversity that shapes water consumption patterns in Egypt. This understanding requires knowing how water is consumed for micro-components of water use (i.e., end-uses such as bathing, cooking, and toilet use). This research aims to develop a conceptual/theoretical framework for probable worldwide water consumption patterns and their shaping factors, to be used as an auxiliary tool in future data collection and analysis in Egypt, which is an essential step to contextualize water consumption patterns and develop more sustainable water demand management strategies. The study reviews and analyzes water end-use data from 39 major cities in developed and developing countries to identify trends and critical factors in household water consumption. It documents six different major trends in household water consumption patterns with main water activities: cooking, bathing, washing machines, faucets, and toilet use. It also identifies and categorizes the patterns-shaping factors into five main groups: socioeconomic characteristics, physical, spatial, climatic conditions, and political restrictions. Moreover, significant correlations emerge between pattern elements and shaping forces such as income and washing machine usage, the presence/absence of children/elders and use of basin, and dietary culture and cooking consumption. Given the research findings, household consumption patterns in Egyptian cities are expected to be high in kitchens, showers, and toilets, and average in laundry and faucets. The study underscores the importance of considering factors such as socio-economic characteristics, water policies, spatial influences, water supply efficiency, and consumer health in forthcoming investigations, as these are believed to substantially influence household water consumption in Egypt.

AMI water meters deliver end-use water and financial savings in leaky households: experimental evidence from California

Abstract Advanced metering infrastructure (AMI) for residential water consumption is exploding globally giving water utilities the ability to improve their water tracking, billing, and distribution systems’ leak detection. With AMI, utilities have also gained the opportunity to provide real-time high-resolution water consumption information to their customers to induce conservation. Using a randomized controlled trial we find that on average homes that install AMI and receive conservation based messaging significantly reduce water consumption by 5.24 gallons per household per day beyond savings already obtained from home water reports. Of the estimated water savings we attribute 92.8% to leak reduction. While the payback period from the deployment of AMI meters and treatment in all homes is over 41 years, homes that experience leaks realize financial savings of $60/year and a treatment payback period of four years. This is because treatment did not induce water or financial savings in homes without leaks. These findings indicate that even on top of existing conservation programs, AMI messaging that targets end-user leaks could result in significant water savings, economic benefits to end-users, and advance conservation goals.

Understanding the Residential Water Demand Response to Price Changes: Measuring Price Elasticity with Social Simulations

Water pricing is an economic instrument traditionally used to reduce water demand. However, its effective implementation requires knowledge of the extent to which users reduce water consumption with increasing water prices. The price elasticity of water demand has been estimated using econometric regression, which relies on cross-sectional and time-series water data. As an alternative, we propose the use of agent-based modelling, which does not require reliable historical data on water prices and consumption and enables the simulation of multiple scenarios with different consumer profiles, behaviour profiles and water price changes, thereby allowing comprehensive understanding of price elasticity estimates. To illustrate the potential use of agent-based modelling for the estimation of water demand price elasticity, we performed an empirical application to a residential area in Chile. Price elasticity estimates ranged from −0.0159 to −0.1036 (mean −0.0250), indicating that residential water consumption is inelastic to price changes. This result is consistent with previous findings. Agent-based modelling is an alternative for the ex-ante assessment of the potential effectiveness of water pricing policies intended to reduce residential water demand.

Uncovering urban water consumption patterns through time series clustering and entropy analysis

Sustainable urban water management is crucial for meeting the growing demands of urban populations. This study presents a novel approach that combines time series clustering, seasonal analysis, and entropy analysis to uncover residential water consumption patterns and their drivers. Using a three-year dataset from the SmartH2o project, encompassing 374 households, we identify nine distinct water consumption patterns through time series clustering, leveraging Dynamic Time Warping (DTW) as the optimal similarity measure. Multiple linear regression reveals key household characteristics influencing water usage behaviors, such as the number of bathrooms and appliance efficiency ratings. Seasonal analysis uncovers temporal dynamics, highlighting shifts towards lower consumption during summer months and increased variability in transitional seasons. Entropy analysis quantifies the diversity and complexity of water consumption at both cluster and household levels, informing targeted interventions. This comprehensive, granular approach enables the development of personalized water conservation strategies and policies, empowering water utilities to optimize resource management and contribute to sustainable urban water practices.

Scale effects and implications of the stochastic structure of customer water demands

ABSTRACT The effect of different temporal (from seconds to months) and spatial aggregation scales (from individual users to full urban areas) on water demand behavior has been explored to a limited degree. The effort described here extends those works by evaluating the scale effects of residential water consumption in a unique US data set that covers 10,000 households with a 1-gallon (3.79 L) hourly resolution over 2 years. A preliminary data analysis and a sequential Principal Component Analysis (PCA) is carried out to assess the effect of different temporal (weekly, daily, hourly) and spatial aggregation (individual meters and groups every 10, 100 and 1,000 meters) levels on demand. Results show that individual users act very differently from each other, and individual consumer variability is only canceled out when a significant number of households are aggregated. The implications of this finding are assessed from a hydraulic modeling perspective as the spatiotemporal scale of measurements may condition the type of analysis that can be carried out in practice. However, additional work is needed to explore the point at which it may be worth embracing a micro (per fixture/household) or a macro (per node/network) approach for different purposes.

Mind the tap – how volumetric pricing affects residential hot water consumption

Mind the tap – how volumetric pricing affects residential hot water consumption

Utilizing Waste Materials to Enhance Crop Production: A Review

Waste management is a crucial aspect of modern societies, encompassing various activities to ensure the safe and effective disposal of waste materials. It can be classified as hazardous waste, electronic trash (e-waste), industrial waste, and municipal solid waste (MSW). Sustainable waste management practices aim to reduce environmental impact while protecting public health. Urbanization leads to increased residential water consumption, however reusing wastewater for non-potable applications like agriculture can be cost-effective. The overall costs of delivering wastewater for agricultural reuse, including treatment, storage, and transportation, are less the total costs of safe environmental disposal alternatives. Drainage may also be a source of macronutrients (nitrogen, phosphorus, and potassium), which reduces the cost of wastewater for agricultural reuse. The adoption of these principles could lead to a 48% reduction in global greenhouse gas emissions by 2030. The management of hazardous waste, including toxic, flammable, corrosive, or reactive materials, is also a significant concern. In order to safeguard public health and stop the spread of infectious illnesses, animal manure management is crucial. The global generation of construction and demolition waste is expected to double by 2025, with the majority generated in Asia. Sustainable waste management practices are necessary to ensure public health and the environment.

Heat loss from non-circulating domestic hot water pipes increases water consumption and energy demand

Hot water use in showers is a major contributor to residential water and energy consumption, and associated costs and carbon emissions. This study aims to quantify how heat loss from non-circulating pipes contributes to water and energy consumption in residential showers. Heat loss from pipes was modelled for detached dwellings in Melbourne, Australia, using Monte Carlo analysis to quantify variability. Sensitivity analysis was conducted to identify key factors contributing to heat loss. This is the first study to quantify the variability of the impact of heat loss from pipes into increased water (and hence energy) consumption in showers. Under Melbourne conditions, we predicted that heat loss from pipes contributes approximately 2 to 10 % in average shower hot water consumption. Longer pipes, smaller diameter, longer showers and longer intervals between showers were the primary factors driving additional hot water consumption.

Tracking and tracing water consumption for informed water sensitive intervention through machine learning approach

To develop a water conscious strategy, it is critical to track and trace water from its source to the end users, understand water conservation behaviors, and identify the factors that influence water consumption. However, in developing nations, little research has been done to provide a quantitative picture of how water is consumed and transformed in urban households, as well as the water sensitive interventions needed to improve access to clean water. Hence, the main objective of the study was to determine the most significant residential water consumption variables and to predict residential water consumption in a way that can generate water consumption information for water sensitive intervention decision making using the case study of Adama city in Ethiopia. A combination of top down and bottom up data collection techniques were employed as the data collection instrument. Machine learning was integrated with spatial and socioeconomic analytic techniques to estimate daily household water consumption and identify the factors that significantly influence household water consumption. The results show that there is only “one source option” for the city’s clean water supply and that different water harvesting methods are not likely to be developed. The average daily water consumption per person is 69 liters which falls below the national standard of 80 liters allocated per person per day. The result reveals that the water distribution network covers only 45% of the city master plan. About 38% of the water demand is unmet and 30% of households only receive water once every three days or fewer. This shows that the city is experiencing physical and economic water scarcity. The results demonstrated that family size, housing quality, income, number of rooms, legal status of the parcel, supply reliability, climate, and topographical features are the most important factors in predicting residential water consumption. This study further demonstrates how well supervised machine learning models, such as the Random Forest Regression algorithm, can predict the household’s daily water consumption. The findings also showed that there is a need for significant improvements in water saving habits of the households. Another conclusion that can be drawn is that as long as the city’s business as usual water consumption practice doesn’t change, the water supply problem will worsen over time.

Evaluating the potential benefits of float solar photovoltaics through the water footprint recovery period

In the context of higher demands on the development of clean energy technologies due to the issue of water shortage in China and the implementation of the 2060 carbon-neutral objective, floating photovoltaic (FPV) systems present novel opportunities for transforming the energy structure through land conservation and enhancement of power generation efficiency compared to conventional solar systems. However, there is currently a lack of comprehensive analysis on the potential benefits of FPV. Utilizing reservoir databases and employing a professional FPV system design, a methodology for determining the water footprint recovery period was introduced, which enables the assessment of potential FPV benefits. The water footprint recovery period for constructing FPV on 909 reservoirs in China was found that ranges from 1.86 yr to 10.48 yr. It is found that reservoir evaporation, latitude, and climate are closely related to the water footprint recovery period of FPV. Furthermore, by implementing FPV panels with an optimal tilt angle, covering 30% of the area in each reservoir, the annual electricity generation can amount to 1429.19 TWh, leading to savings of 5.76 billion m3 of water. This achievement corresponds to 19.41% of the national electricity consumption and a 6.86% reduction in the national residential water consumption in 2020. The overall economic benefit is 5.61 myriads RMB, equivalent to 5.76% of the national GDP. These benefits are unevenly distributed and mainly concentrated in areas with more reservoirs. The anticipated enhancement of FPV system benefits is foreseen with the ongoing development and implementation of future reservoir power infrastructure and energy storage technology. These results demonstrate the significant potential of installing FPV systems on the reservoirs in China. This study proposes a method to comprehensively evaluate the comprehensive benefits of constructing FPV in China and conduct a thorough analysis of the feasibility of FPV, which could provide reference for the development of regional industries and the achievement of sustainable development goals (SDGs).

The impact of pricing structure change on residential water consumption: A long-term analysis of water utilities in California

California's demand-side urban water management policies, such as shifting water pricing structures from non-conservation to conservation-based rates, have received much attention in terms of meeting the state's short- and long-term water conservation policies. This paper quantifies the effect of pricing structure changes on residential water consumption using a survey dataset of 189 major California water utilities from 1994 to 2019. Results of our study demonstrate that residential per capita per day water consumption was reduced by an average of 2.6% when water agencies switched from non-conservation-based to conservation-based pricing structures. We also found evidence that the longer a utility maintained a non-conservation-based rate structure before switching to conservation-based pricing, the larger the water consumption reduction in that utility's service area. In addition, utilities that reverted to non-conservation rates after having longer-term conservation pricing structures experienced smaller increases compared to having long-term non-conservation ones in water use in their service areas. This suggests evidence of a crowding-in effect for transitions from conservation-based to non-conservation-based pricing structures.

A segmentation approach to understanding water consumption behavioral patterns among households in Saudi Arabia for a sustainable future

Urban water consumption has significant implications for both human welfare and the environment, especially in arid regions. In Saudi Arabia, where 60% of the urban water supply relies on energy-intensive desalination processes, the average per capita water consumption rate of 300 L/day is one of the highest worldwide. This study investigates potential behavioral patterns in residential water consumption among households in Saudi Arabia. A segmentation approach is employed to classify residents into clusters and evaluate their potential water consumption behavioral patterns. Data from 618 households were collected via a structured questionnaire and analyzed using descriptive statistics, principal component analysis (PCA), and cluster analysis (CA). Participants were categorized into six segments based on the relationship between their behaviors and water consumption derived from the factor analysis. The outcomes of PCA and CA analyses indicate a relationship between respondents’ socio-demographic factors and their potential behavioral patterns in residential water consumption. The findings highlight that education, household size, income, housing type, age, and nationality, in increasing order of significance, are the key factors influencing household water consumption and conservation tendencies. The paper concludes that comprehending residential water consumption patterns is crucial for effective interventions, social marketing strategies, and communication campaigns for behavioral changes. The study can inform water conservation policies and programs that promote sustainable water consumption practices, benefiting agencies, policymakers, and scholars in the water sector.

Temporal and Spatial Changes of Hydrographic Connectivity with the Development of Agriculture, Industry, and Urban Areas: A Case Study of the Yellow River Basin in Henan Province during the Last Two Decades

Hydrographic connectivity stands as a crucial indicator for analyzing the structural dynamics within river and lake systems. Nevertheless, the impact of changes in hydrographic connectivity, including structural and functional connectivity within extensive river basins, on the progression of agriculture, industry, and habitation remain scarcely explored. To bridge this gap, Henan province in China, traversed by the Yellow River, was selected as a case study. The extraction of water information was facilitated by employing a remote sensing-based Modified Normalized Difference Water Index (MNDWI), while Set Pair Analysis was utilized to construct a hydrographic connectivity evaluation system for the study area spanning the preceding two decades (2000–2020). The results revealed that for structural connectivity, agricultural land covers over 50% and prevails as the primary land-use type; reservoir and lake areas initially increased before subsequently decreasing. Human activities have exerted a profound influence on these changes. Meanwhile, the structural form of the water system has gradually improved, exhibiting an increasing complexity of river networks and a stabilizing connectivity configuration. As for functional connectivity, the natural function remains well-preserved, while the social function demonstrates a positive correlation with the expansion of industrial activities, eventually achieving an excellent level from a moderate level. Overall, agriculture dominated the water usage structure, with residential water consumption steadily increasing, thereby positively impacting hydrographic connectivity in the studied area.

Affordability and sustainability in the human right to water

PurposeThe purpose of this study is to analyze the affordability and sustainability of residential water consumption in Ecuador, a developing country.Design/methodology/approachTo determine affordability, the authors assess water consumption and its distribution across different income levels of the population in the three main cities: Cuenca, Guayaquil and Quito. The authors then simulate the effects of a pricing policy on sustainability by deriving demand elasticities through a quadratic almost ideal demand system (QUAIDS).FindingsResults show that Ecuador has low water tariffs with respect to other cities in Latin America, which points to its affordability. However, sustainability might not be guaranteed since consumption is overall higher than the level suggested by the World Health Organization. From an economic point of view, this could be motivated by the low tariffs. Indeed, the simulation of a pricing policy shows that higher prices can significantly reduce demand for most of the sample. However, in low-income households this reduction may compromise vital consumption.Research limitations/implicationsThis research has important implications in terms of stimulating the discussion of how water affordability and sustainability can be achieved. For the case study, Ecuador, the results indicate that sustainability may not be guaranteed and that policies need to be designed to encourage it. Another implication is that population income levels should be considered to avoid negative effects for the most vulnerable groups. The main limitations of this study are methodological. First, the QUAIDS model is based on a conditional demand model (Zhen et al., 2013), which does not take into account spending on other goods. Second, data availability is limited and prevents a deeper analysis.Originality/valueTo the best of the authors' knowledge, this is the first study to analyze these issues in Ecuador, a country that recognizes the human right to water at the constitutional level.

Adapting to climate change: substitution effect of water on residential electricity consumption

PurposeAs climate change impacts residential life, people typically use heating or cooling appliances to deal with varying outside temperatures, bringing extra electricity demand and living costs. Water is more cost-effective than electricity and could provide the same body utility, which may be an alternative choice to smooth electricity consumption fluctuation and provide living cost incentives. Therefore, this study aims to identify the substitute effect of water on the relationship between climate change and residential electricity consumption.Design/methodology/approachThis study identifies the substitute effect of water and potential heterogeneity using panel data from 295 cities in China over the period 2004–2019. The quantile regression and the partially linear functional coefficient model in this study could reduce the risks of model misspecification and enable detailed identification of the substitution mechanism, which is in line with reality and precisely determines the heterogeneity at different consumption levels.FindingsThe results indicate that residential water consumption can weaken the impact of cooling demand on residential electricity consumption, especially in low-income regions. Moreover, residents exhibited adaptive asymmetric behaviors. As the electricity consumption level increased, the substitute effects gradually get strong. The substitute effects gradually strengthened when residential water consumption per capita exceeds 16.44 tons as the meeting of the basic life guarantee.Originality/valueThis study identifies the substitution role of water and heterogeneous behaviors in the residential sector in China. These findings augment the existing literature and could aid policymakers, investors and residents regarding climate issues, risk management and budget management.

Providing procedural knowledge: A field experiment to encourage resource conservation in Namibia

I conduct a large-scale field experiment (N = 14876) with a public water utility in Namibia to encourage water conservation during a drought. Providing a short list of specific conservation strategies via text message decreases residential water consumption by around 5.3 percent. Other treatment arms that ask individuals to use and develop their own strategies are ineffective, suggesting that individuals may lack knowledge on how to reduce their water consumption effectively. This interpretation is corroborated by survey evidence as most respondents struggle to name effective conservation strategies. As a secondary outcome, I examine whether the intervention influences the payment of water utility bills. Utility bills are often not paid in full in my setting, which affects the fiscal sustainability (i.e., cost recovery) of the water utility. I find that payments do not decrease. This implies that customers pay a larger amount of their bill, since they consume less water without reducing payments.

Residential water and energy consumption prediction at hourly resolution based on a hybrid machine learning approach

Predicting water and energy consumption at high resolution over a short-term horizon is critical for water and energy resource management. Water and energy are shown to be closely interlinked in household consumption. However, hourly predictions are often based only on historical consumption data for the resource being predicted, with activity or appliance information and household attribution as additional information. Few studies have used aggregated water and energy consumption for predictions. Within this context, the current study proposed a novel hybrid machine learning model based on the Prophet time-series model, Gated Recurrent Unit network, and self-adaptive weights, called the Prophet-GRU model, which could jointly include historical water and electricity consumption as inputs for hourly water or electricity prediction. Data on hourly water and electricity consumption in six households in Beijing during January–March 2020 were used to train and validate the Prophet-GRU model. The goodness of fit indicator (R2) and prediction accuracy (mean squared error and mean absolute error) for the water and electricity predictions were evaluated. Compared with the single input of water or electricity, with the combined input of data of these two resources, the proposed Prophet-GRU model achieved improvements of 29.2 % and 48.5 % in R2, for water and electricity consumption prediction, respectively. Our results could help better understand water-energy linkages and promote collaborative water and energy management practices.

Pricing for Water Conservation and Equity Consideration: The Case of Texas

Water utility providers in Texas have been trying to coordinate demand for and supply of water to ensure a stable source of water given the state’s recent rapid population growth and persistent drought-like conditions. Their efforts, however, vary across municipalities throughout Texas. The paper provides a broad analysis of pricing practices in 423 municipalities across Texas from 2014 to 2020 and their impact on residential water consumption. We also assess how other socio-demographic and climatic conditions may influence water use and water rates decisions across municipalities. Besides investigating the potential determinants of water demand, the paper also looks at several supply-side variables and the income gap to address the endogeneity of water block prices. Our results shed light on how current water pricing practices in Texas incorporate aspects of the Integrated Water Management Practices that have been shaping water management for decades.

Poisson rectangular pulse (PRP) model establishment based on uncertainty analysis of urban residential water consumption patterns

The commonly used Poisson rectangular pulse (PRP) model, employed for simulating high-resolution residential water consumption patterns (RWCPs), relies on calibration via medium-resolution RWCPs obtained from practical measurements. This introduces inevitable uncertainty stemming from the measured RWCPs, which consequently impacts the precision of model simulations. Here we enhance the accuracy of the PRP model by addressing the uncertainty of RWCPs. We established a critical sampling size of 2000 household water consumption patterns (HWCPs) with a data logging interval (DLI) of 15 min to attain dependable RWCPs. Through Genetic Algorithm calibration, the optimal values of the PRP model's parameters were determined: pulse frequency λ = 91 d−1, mean of pulse intensity E(I) = 0.346 m3 h−1, standard deviation of pulse intensity STD(I) = 0.292 m3 h−1, mean of pulse duration E(D) = 40 s, and standard deviation of pulse duration STD(D) = 55 s. Furthermore, validation was conducted at both HWCP and RWCP levels. We recommend a sampling size of ≥2000 HWCPs and a DLI of ≤30 min for PRP model calibration to balance simulation precision and practical implementation. This study significantly advances the theoretical foundation and real-world application of the PRP model, enhancing its role in urban water supply system management.

Fast in the pandemic, durable after droughts, inequal during economic downturn. A 20 year multi-dimensional retrospective analysis of water demand change in Southern California

Determining changes in water consumption behavior due to recurring external stressors (e.g. droughts and socio-economic fluctuations) and previously unseen shocks like the COVID-19 pandemic can support future demand-side management (DSM) programs and identifying vulnerable social groups. Yet, most studies analyzing external drivers of water consumption change are noncomparative as they examine only one stressor at the time, mainly droughts. Here we develop a multi-dimensional retrospective analysis (MDRA) to quantify residential water consumption changes in Southern California over the last two decades under compound hydroclimatic, economic, and pandemic stressors. We then uncover what socio-economic groups relate to predominant behavioral changes under each stressor. We observe a long-lasting decreasing water consumption trend for more than 76% of the analyzed households. Socio-economically vulnerable households were more likely to reduce water consumption during the economic and pandemic stressors. Differently, affluent neighborhoods tended to increase water consumption during or after droughts and the pandemic. Our MDRA supports utilities and policy makers to discern the impacts of different stressors on water demand and helps to identify social and economic sensitivities across a service area to develop adaptive DSMs and assistance programs.