Changes In Water Demand Research Articles

An Implicit Model for Water Rate Setting Within Municipal Utilities

It is estimated that at least $1 trillion will be required over the next 25 years to maintain the current level of water service in the United States. A pay‐as‐you‐go approach is expected to allow water utilities to pay for these expenses using water price increases. These price increases encourage water conservation, decreasing overall water demand. Financial forecasts that fail to consider this effect will therefore overstate anticipated system revenues and potentially lead to realized shortfalls. Therefore, understanding changes in water demand is crucial for accurate price forecasting. This article combines simple relationships that are relevant to water supply services to develop an implicit model of time‐dependent system revenues, water prices, and water demand. The implicit model provides a theoretical basis for water rate–setting to generate financially sustainable water utility revenues. Results suggest that a comprehensive physical infrastructure model is critical for precision and accuracy in model forecasts.

Integrating Supply Uncertainties from Stochastic Modeling into Integrated Water Resource Management: Case Study of the Saskatchewan River Basin

AbstractA warming climate and land management intensification have altered water supply characteristics in many regions of the world. Incorporation of water supply uncertainties into long-term water resources planning and management is, therefore, significant from both a scientific and societal perspective. This study proposes a set of analyses for integrated water resources management under changing water supply and demand expansion based on a newly developed methodology for vulnerability assessment. The basin of interest for the proposed analysis is the interprovincial Saskatchewan River Basin (SaskRB) in Canada, which supports a wide range of water demands, from municipal and industrial use to irrigated agriculture and hydropower. Proposals for an increase in irrigated area are used as a context for exploring the joint effects of current and future water supply uncertainty and increasing irrigation demand conditions on the water resources system. Changing water supply conditions are represented by pert...

Linking Bayesian and agent-based models to simulate complex social-ecological systems in semi-arid regions

Interdependencies of ecologic, hydrologic, and social systems challenge traditional approaches to natural resource management in semi-arid regions. As a complex social-ecological system, water demands in the Sonoran Desert from agricultural and urban users often conflicts with water needs for its ecologically-significant riparian corridors. To explore this system, we developed an agent-based model to simulate complex feedbacks between human decisions and environmental conditions in the Rio Sonora Watershed. Cognitive mapping in conjunction with stakeholder participation produced a Bayesian model of conditional probabilities of local human decision-making processes resulting to changes in water demand. Probabilities created in the Bayesian model were incorporated into the agent-based model, so that each agent had a unique probability to make a positive decision based on its perceived environment at each point in time and space. By using a Bayesian approach, uncertainty in the human decision-making process could be incorporated. The spatially-explicit agent-based model simulated changes in depth-to-groundwater by well pumping based on an agent’s water demand. Changes in depth-to-groundwater feedback to influence agent behavior, as well as determine unique vegetation classes within the riparian corridor. Each vegetation class then provides varying stakeholder-defined quality values of ecosystem services. Using this modeling approach allowed us to examine effects on both the ecological and social system of semi-arid riparian corridors under various scenarios. The insight provided by the model contributes to understanding how specific interventions may alter the complex social-ecological system in the future.

Securing safe drinking water supply under climate change conditions

Water suppliers worldwide are challenged by climate variations, but so far only the qualitative change in boundary conditions has become clear but not yet the degree and impact on the water supply systems. Short-term quality changes in surface waters can, e.g. be caused by extreme rainfalls after dry periods. Longer heat periods without rain can induce middle-term quality changes in surface waters due to lacking dilution. Furthermore, unsustainable management of groundwater can lead to long-term quality changes and to water shortages, especially in times with higher water demand. Depending on the individual situation, the expected effects on the supply system differ widely, so a general adaptation strategy will not suit the individual problems. The purpose of our work is to enable water supply companies to systematically identify potential risks resulting from climate change and other external factors in a water safety plan approach, and to adapt the supply system in a most effective way by taking advantage of ongoing modernization measures and ‘no-regret’-measures. A suitable adaptation strategy should address climate change conditions as well as other external factors like changing water demand and also to take into account possible effects on every part of the supply system.

Change of water demand and regional characteristics of water supply-demand system in the Ashida River Basin

Change of water demand and regional characteristics of water supply-demand system in the Ashida River Basin

Changing tourism patterns, capital accumulation, and urban water consumption in Mallorca, Spain: a sustainability fix?

This paper presents interdisciplinary research based on in-depth, comparative analysis of water consumption and land use patterns over a range of urban-tourist forms in Mallorca. The changing tourism patterns towards residential and quality tourism are studied, on the basis that capital investment for capital accumulation and increasing gains are its main drivers. Social awareness about overcrowding and resource limitations has moved the regulatory planning framework toward allowing further urban sprawl, based on the alibi of quality tourism. The rhetoric of this framework represents a first sustainability fix, a fix that hides the higher water demand and climate change issues. The socio-metabolic dimension of this process is analyzed in relation to how it has resulted in an uneven socio-spatial urban landscape of water consumption. This urban-tourist landscape is vulnerable to changes in climate, because it is sustained by an excessive use of water. Water supply is a serious constraint which has been resolved through its commodification and supply privatization, which are considered as a second sustainability fix. This tourism development process worsens rather than solves the metabolic rift, resulting in the second contradiction of capital accumulation between the imperative of continual growth and finite natural resources.

Industrial versus Laboratory Clinker Processing Using Grinding Aids (Scale Effect)

The evaluation of grinding aid (GA) effect on clinker processing in laboratory grinding mills is relatively simple. Yet, the results obtained cannot be directly transposed to industrial mills, given the fundamentally different operational modes and grinding parameters. This paper seeks to evaluate the scale effect by comparing the results obtained from a closed-circuit tube mill operating at 90 ton/hr to those determined using a 50-liter laboratory mill. Tests results have shown that the decrease in specific energy consumption (Ec) due to glycol or amine-based GA can be evaluated under laboratory conditions. However, such tests underestimate the actual performance that could be achieved in real-scale mills; the Ec reduction due to GA is around twofold higher when grinding is performed in real-scale mill. Compared to industrial tests, the cement particle size distribution curves widened and shifted towards higher diameters when grinding was performed under laboratory conditions, particularly with GA additions. This led to remarkable changes in water demand, setting time, and 1- and 28-day compressive strengths.

M516 多機能CO_2ヒートポンプ給湯システムの数値シミュレーションによる性能分析 : 需要量の日変化条件下における性能分析(GS6,8,12 動力エネルギーシステム,修士研究発表セッション)

M516 多機能CO_2ヒートポンプ給湯システムの数値シミュレーションによる性能分析 : 需要量の日変化条件下における性能分析(GS6,8,12 動力エネルギーシステム,修士研究発表セッション)

Statistical Trend Analysis of Residential Water Demand in Kisumu City, Kenya

This study sought to analyse trend in the monthly water demand data series in Kisumu city at both seasonal and non-seasonal levels using the parametric method of Ordinary Least Squares (OLS) and non-parametric methods of Mann-Kendall tau and Sen's T test. Sen’s test was applied to validate the Mann Kendall trend test and to estimate the magnitude of the trend and its direction. The significance of the slope of the OLS equation was tested using the F-Test based on the Analysis of Variance (ANOVA). Secondary monthly water consumption data obtained from KIWASCO for the period January 2004 to December 2013 were used. Using logarithmically transformed data, the study established by OLS that residential water demand in Kisumu City had a significant increasing trend (FCalc=(105.13) > F(1;119)(α=0:05)=(5.15)). Kendall's tau test corroborated the OLS results of a significant increasing trend. The Sens T test indicated that most of the months registered significant upward trend with Sen’s slope estimates showing positive rates of change in residential water demand for these months.

The Water Transfer Process as a Management Option for Meeting Changing Water Demands, Vol. I.

This report summarizes the research conducted in six states examining the laws governing water transfers, the processes, and the use of these processes during a 10-year period.

Investing in recovering water for the environment in Australia's Murray-Darling Basin

Irrigated agriculture makes an important contribution to the economy of Australia's Murray-Darling Basin. Competing water demand, recurring drought and climate change have ushered in an era of water policy reform. To recover water for the environment, surface water extraction is capped and investment in irrigation infrastructure is prioritized. This article applies a computable general equilibrium model to evaluate the economic impacts of investment in irrigation in a case study of the Murrumbidgee subcatchment. Results indicate an increase in regional output, income and employment, while at the national level there is a small negative impact resulting from the transfer of resources to the basin and the crowding out of private investment.

A mobile application to calculate optimum drip irrigation laterals

The parameters to be taken into account when installing a drip irrigation system include the diameters of piping to be used in the irrigation installation. Certain applications developed for PC permit an approximate calculation of these diameters outside the installation environment, which makes on-site optimization of the system difficult. This paper presents a software application developed for Android mobile devices by which the user can immediately evaluate the responsiveness of all of the available optimum commercial diameters to operational changes, such as changing water demands (e.g., cultivation, water needs, and spacing), types of emitters used in the installation, or lateral feeding (from an extreme or from an intermediate point). The input data mainly required by the application are: emitter flow rates, the number of emitters, the space between emitters, the average pressure in the lateral, and the pressure tolerance. As a result, the application indicates if each irrigation lateral is valid or not for the situation provided by the user, and displays some graphics of the pressures in the lateral that indicate the pressures at the system's extremities, which permits identification of the critical points of the irrigation lateral.

Use of artificial and natural tracers to assess groundwater transit-time distribution and flow systems in a high-alpine karst system (Wetterstein Mountains, Germany)

Groundwater in mountainous karst regions is vital for regional water budgets and freshwater supply. Owing to increasing water demand and climate change, detailed knowledge of the highly heterogeneous alpine aquifer systems is required. Multi-tracer analyses have been conducted in the steep karstic Wetterstein Mountains, which includes Germany’s highest summit, Zugspitze (2,962 m asl). Results of artificial tracer tests demonstrate well-developed flow paths through the unsaturated zone (up to 1,000 m thickness). Flow paths cross topographic divides and contribute to deep drainage systems underneath alpine valleys. Cross-formational flow has been identified. Quantitative analysis of tailing-dominated breakthrough curves and stable isotopes (18O) has enabled determination of the mean transit-time distribution. A fast-flow component with transit times between 3 and 13 days was found in karst conduits and open fissures, dependent on flow conditions. An intermediate-flow component, showing mean transit times of about 2.9–4.9 months, was found in well-drained fissures and fractures. A slow-flow component with mean transit times greater than 1 year is attributable to slow flow and low storage in the poorly drained fissures and rock matrix. The conceptual model enables a better understanding of drainage, water resources and vulnerability of the high-alpine karst system.

Adaptive water demand forecasting for near real-time management of smart water distribution systems

This paper presents a novel methodology to perform adaptive Water Demand Forecasting (WDF) for up to 24 h ahead with the aim to support near real-time operational management of smart Water Distribution Systems (WDSs). The novel WDF methodology is exclusively based on the analysis of water demand time series (i.e., demand signals) and makes use of Evolutionary Artificial Neural Networks (EANNs). It is implemented in a fully automated, data-driven and self-learning Demand Forecasting System (DFS) that is readily transferable to practice. The main characteristics of the DFS are: (a) continuous adaptability to ever changing water demand patterns and (b) generic and seamless applicability to different demand signals. The DFS enables applying two alternative WDF approaches. In the first approach, multiple EANN models are used in parallel to separately forecast demands for different hours of the day. In the second approach, a single EANN model with a fixed forecast horizon (i.e., 1 h) is used in a recursive fashion to forecast demands. Both approaches have been tested and verified on a real-life WDS in the United Kingdom (UK). The results obtained illustrate that, regardless of the WDF approach used, the novel methodology allows accurate forecasts to be generated thereby demonstrating the potential to yield substantial improvements to the state-of-the-art in near real-time WDS management. The results obtained also demonstrate that the multiple-EANN-models approach slightly outperforms the single-EANN-model approach in terms of WDF accuracy. The single-EANN-model approach, however, still enables achieving good WDF performance and may be a preferred option in engineering practice as it is easier to setup/implement.

Impact of climate change on regional irrigation water demand in Baojixia irrigation district of China

Water scarcity in China would possibly be aggravated by rapid increase in water demand for irrigation due to climate change. This paper focuses on the mechanism of climate change impact on regional irrigation water demand by considering the dynamic feedback relationships among climate change, irrigation water demand and adaptation measures. The model in implemented using system dynamics approach and employed in Baojixia irrigation district located in Shaanxi Province of China to analyses the changes in irrigation water demand under different climate change scenarios. Obtained results revealed that temperature will be the dominant factor to determine irrigation water demand in the area. An increase of temperature by 1 °C will result in net irrigation water demand to increase by about 12,050 × 104 m3 and gross water demand by about 20,080 × 104 m3 in the area. However, irrigation water demand will not increase at the same rate of temperature rise as the adaptation measures will eventually reduce the water demand increased by temperature rise. It is expected that the modeling approach presented in this study can be used in adopting policy responses to reduce climate change impacts on water resources.

댐 운영방식에 따른 이수안전도의 비교

댐의 이수안전도는 물 수요량, 저수량, 가뭄에 의한 유입량에 의해서 주로 영향을 받는다. 그러나 댐 운영방식에 따라 댐의 이수안전도는 차이가 발생할 수 있다. 우리나라의 수자원장기종합계획은 K-WEAP모형을 이용하여 댐 하류의 물부족이 발생하면 물 부족량만큼 공급하는 부족량공급(Deficit supply) 방식을 이용하고 있으나 일정방류(Prime flow) 방식을 적용하면 이수안전도가 달라질 수 있다. 본 연구의 목적은 댐 운영방식에 따른 댐의 이수안전도의 변화를 분석하는 것이다. 이들 결과는 하류의 유지유량공급, 수력 발전을 위하여 일정방류가 고려되는 환경에서 댐의 이수안전도를 재평가하는데 활용될 수 있을 것이다. A water supply reliability is mainly influenced by water demand, reservoir storage, and inflow change caused from drought. The water supply reliability can vary depending on the method of dam operation. In Korea, the deficit-supply method which complements water deficit as water shortage occurs in downstream areas has been used for the national water resources master plan using K-WEAP, but the prime flow method, an alternative approach, would show different results of water supply reliability in comparison to the deficit-supply method. The objective of this research is to compare and analyze differences in water supply reliability according to dam operation methods. These results can be used to re-evaluate water supply reliability of dam in a circumstance considering steady dam release for instreamflow in downstream and hydroelectric power generation.

Prediction of cotton yield and water demand under climate change and future adaptation measures

Cotton is the main cultivated cash crop in Northwest China. This study is motivated by the challenge of economically growing cotton in the face of climate change, which could lead to changes in cotton variety, phenology, water demand, heat requirement and yield. The APSIM-OzCot crop growth model is used to simulate cotton cultivation at two sites with different climatic conditions (Shihezi and Alaer, Xinjiang Province). The model is fully calibrated and validated using observations. Simulations forced with future climate data downscaled from the HadCM3 Global Climate Model show that the response of cotton phenology, yield and water use to climate change is different for different cultivation, sites, greenhouse gas emission scenarios and time horizons. Under the SRES A1B and B1 emissions scenarios, cotton yield and water use are greater in the future than in the 1961–1990 period while the growing season is shorter. Under the SRES A2 emissions scenario, however, yields at cold sites drop after 2070 due mainly to the shortening of cotton growth periods. Thus, in the cold regions, varieties with short growth periods are replaced by those with long growth periods. The results show that, compared with current local varieties, cotton yields increase by 356kg/ha with the medium maturity variety “K7” and 473kg/ha with the late maturity variety “ZM49” under the A2 scenario by 2070. Total evapotranspiration correspondingly increases by 69mm (“K7”) and 92mm (“ZM49”). However, water use efficiency increases by 0.32kg/m3 to 0.34kg/m3 (6.3%) and 0.35kg/m3 (9.4%) for “K7” and “ZM49”, respectively. A reasonable adaptive strategy to maintain cotton yields in the future may be to decrease the area over which cotton is planted and raise water use efficiency.

A gene–wavelet model for long lead time drought forecasting

Summary Drought forecasting is an essential ingredient for drought risk and sustainable water resources management. Due to increasing water demand and looming climate change, precise drought forecasting models have recently been receiving much attention. Beginning with a brief discussion of different drought forecasting models, this study presents a new hybrid gene–wavelet model, namely wavelet–linear genetic programing (WLGP), for long lead-time drought forecasting. The idea of WLGP is to detect and optimize the number of significant spectral bands of predictors in order to forecast the original predictand (drought index) directly. Using the observed El Nino–Southern Oscillation indicator (NINO 3.4 index) and Palmer’s modified drought index (PMDI) as predictors and future PMDI as predictand, we proposed the WLGP model to forecast drought conditions in the State of Texas with 3, 6, and 12-month lead times. We compared the efficiency of the model with those of a classic linear genetic programing model developed in this study, a neuro-wavelet (WANN), and a fuzzy-wavelet (WFL) drought forecasting models formerly presented in the relevant literature. Our results demonstrated that the classic linear genetic programing model is unable to learn the non-linearity of drought phenomenon in the lead times longer than 3 months; however, the WLGP can be effectively used to forecast drought conditions having 3, 6, and 12-month lead times. Genetic-based sensitivity analysis among the input spectral bands showed that NINO 3.4 index has strong potential effect in drought forecasting of the study area with 6–12-month lead times.

Energy–Water Nexus Analysis of Enhanced Water Supply Scenarios: A Regional Comparison of Tampa Bay, Florida, and San Diego, California

Increased water demand and scarce freshwater resources have forced communities to seek nontraditional water sources. These challenges are exacerbated in coastal communities, where population growth rates and densities in the United States are the highest. To understand the current management dilemma between constrained surface and groundwater sources and potential new water sources, Tampa Bay, Florida (TB), and San Diego, California (SD), were studied through 2030 accounting for changes in population, water demand, and electricity grid mix. These locations were chosen on the basis of their similar populations, land areas, economies, and water consumption characters as well as their coastal locations and rising contradictions between water demand and supply. Three scenarios were evaluated for each study area: (1) maximization of traditional supplies; (2) maximization of seawater desalination; and (3) maximization of nonpotable water reclamation. Three types of impacts were assessed: embodied energy, greenhouse gas (GHG) emission, and energy cost. SD was found to have higher embodied energy and energy cost but lower GHG emission than TB in most of its water infrastructure systems because of the differences between the electricity grid mixes and water resources of the two regions. Maximizing water reclamation was found to be better than increasing either traditional supplies or seawater desalination in both regions in terms of the three impact categories. The results further imply the importance of assessing the energy-water nexus when pursuing demand-side control targets or goals as well to ensure that the potentially most economical options are considered.

Effect of Temperature on Flow Properties of Superplasticized Cement Paste

The effects of the ambient temperature over a range of 5 to 40°C (41 to 104°F) on the flow behavior of cement pastes with superplasticizers of different families were investigated. Tests with the Marsh cone and mini-slump showed that the flow behavior in all superplasticized pastes is influenced by the temperature and that the saturation dosage of superplasticizer increases with an increase in temperature, with the polycarboxylate-based superplasticizer giving the least variation. It was also observed that the loss in fluidity of the cement paste generally increases with an increase in the ambient temperature. Vicat penetration tests showed that water demand of cement increases significantly as the temperature increases from 5 to 40°C (41 to 104°F), and the change in water demand varies with the type and dosage of superplasticizer. It was also seen that an increase in temperature shortens the setting time in all of the superplasticized cement pastes.