Industrial Water Demand Research Articles

A pricing model for water rights trading between agricultural and industrial water users in China

This paper presents a pricing model developed for the Chinese water rights trading market. The model focuses on the transfer of water rights from irrigators to industrial users in areas with limited water resources. Water rights trading is an efficient means of allocating water resources, and the price plays an important role in this market. At present, China lacks formal mechanisms for water rights pricing. Therefore, an integrated pricing model is built for situations when agricultural users implement water conservation measures and sell water rights to meet industrial water demand. The model accounts for project construction costs, operation and maintenance costs, renewal and reconstruction expenses, irrigation frequency compensation, and the economic cost of ecological damage. The marginal value of water rights to the industrial water user is also quantified on the basis of the production function accounting for water inputs. The pricing model is applied to an example of water rights trading between irrigators and industrial users in an agricultural area on the Yellow River near Ordos in Inner Mongolia.

PROSPEK SKENARIO KEBIJAKAN PENGELOLAAN LINGKUNGAN KAWASAN INDUSTRI (Studi Kasus Kawasan Industri Jababeka dan EJIP di Kabupaten Bekasi)

<p align="justify">Abstract:. The key factors which supported to develop sustainaibility in the environmental management in the industrial estate was studied by many approaches. The principles of analysis were elaborated by the multi dimension key factors that affecting the policy of the environmental manager in ecology, economy, social, technology and estate management aspects. This study was initiated by considering and combining the dominant factors which the results of prior researches that using Multi-Dimensional Scaling (MDS) method. The dominants factors were reveiwed by expert judgment approach by Bourgeois matrix as the propective analysis tool. The analysis was focus in the key factors that has low value in the dependence (<1) but has high value in the influence (>1) of the normalized graph of dependence-inluence. The key factors were a) implementation of 3R for hazardous waste; b) industrial wastewater quality; c) industrial estate wastewater quality ;d) labor condition, and e) industrial water demand. The study was analyze that the optimistic scenario can be obtained<br />by the industrial estate manager by conducting the strategic steps. The initial program was recommended by enforcing the industrial companies to improve their waste water quality and increasing 3R of hazardous waste, that will enhance increasing the waste water quality of the centralized wastewater treatment of industrial estate. The environmental synergy between industrial company and industrial estate management will promote the good labour condition and stakeholders trust for more business opportunities that indicated by increasing industrial water demand.</p>

Towards incorporation of potassium into the disaggregation model for determination of soil-specific threshold electrolyte concentration

Use of non-traditional irrigation sources will increase with industry water demand, with many industry wastewaters (e.g. agri-industry processes such as milk factories, piggeries, wineries and abattoirs) containing appreciable potassium (K), which is known to result in soil structural decline if the concentration is sufficient. The threshold electrolyte concentration (CTH) is generally understood to represent the electrolyte concentration (directly proportional to electrical conductivity) at which a soil will remain stable when subjected to a solution of given sodium adsorption ratio, without limiting dispersion. However, current approaches to determine CTH do not incorporate K. Hence, this work seeks to investigate incorporation of K into the disaggregation model for CTH and validate this against equivalent sodium (Na) systems using an ionicity approach. A single generalised coefficient of equivalence for K relative to Na did not appropriately describe the system changes; this coefficient was specific to a soil and appeared to vary with the percolating electrolyte concentration. Incorporation of K into the disaggregation model, although not accurate with a universal coefficient of equivalence for K, was considered reasonable where no other approach could be used. This conclusion was drawn on the basis that the model would produce a conservative CTH under such circumstances, which would not cause undue degradation to the soil environment.

Hydrochemical characterization of groundwater using multivariate statistical analysis: the Maritime Djeffara shallow aquifer (Southeastern Tunisia)

Worldwide, groundwater resources have been considered as the main sources of drinking, domestic uses, industrial and agriculture water demands, especially in arid and semiarid regions. Accordingly, the monitoring of the groundwater quality based on different tools and methods becomes a necessity. The aim of this study was to apply several approaches to assess the water quality and to define the main hydrochemical process which affect groundwater of the Maritime Djeffara shallow aquifer. In addition to the hydrochemical approach, two multivariate statistical analyses, hierarchical clusters analysis (HCA) and principal component analysis (PCA), were carried out to identify the natural and the anthropogenic processes affecting groundwater chemistry. Hydrochemical approach, based on 47 analyzed groundwater samples, shows that most of samples present a sulfate to mixed chloride, with sodi-potassic tendency facies. According to their chemically composition, the HCA revealed three different groups (C1, C2 and C3) according to their electrical conductivity (EC) values: C1 (average EC = 4500 µS/cm), C2 (average EC = 7040 µS/cm) and C3 (average EC = 9767 µS/cm). Furthermore, PCA results show two principal factors account 84.05% of the total variance: (1) F1 represents the natural component, and (2) F2 symbolizes the anthropic component. Moreover, the groundwater quality map of the Maritime Djeffara shows three categories: suitable, doubtful and unsuitable water for irrigation. These different results should be taken to protect water resources in arid and semiarid regions, especially at the alluvial coastal regions. Also, they help to make a suitable planning to manage and protect the groundwater resources.

Water-energy and GHG nexus assessment of alternative heat recovery options in industry: A case study on electric steelmaking in Europe

In the last few years, the water-energy nexus concept has emerged as a global issue. However, studies on European countries are relatively few, and often focused on agriculture. Cooling purposes represent the main part of industrial water demand, and waste-heat recovery is a main strategy to improve resource efficiency. This paper presents a real case study of low-temperature waste-heat recovery in an electric steelmaking industry and evaluates the impact of feasible interventions on primary energy and water consumption, as well as on CO2 equivalent emissions. Based on a Europe wide review of energy and water prices, of energy sources and corresponding resource efficiency indicators, a Monte Carlo model was developed to undertake a generalization of the case study to the EU-15. It was found that solutions with the lowest primary energy demand and the lowest CO2 equivalent emissions demonstrate the greatest water footprint. This is the case of some southern European countries, where heat recovery projects with the highest water intensity are feasible due to high electricity and low water prices. As increasing carbon prices may exacerbate this phenomenon, inducing a switch to water intensive technologies, incentives to carbon emission reduction should be carefully designed.

Forecasting of Industrial Water Demand Using Case-Based Reasoning—A Case Study in Zhangye City, China

Forecasting the industrial water demand accurately is crucial for sustainable water resource management. This study investigates industrial water demand forecasting by case-based reasoning (CBR) in an arid area, with a case study of Zhangye, China. We constructed a case base with 420 original cases of 28 cities in China, extracted six attributes of the industrial water demand, and employed a back propagation neural network (BPN) to weight each attribute, as well as the grey incidence analysis (GIA) to calculate the similarities between target case and original cases. The forecasting values were calculated by weighted similarities. The results show that the industrial water demand of Zhangye in 2030, which is the t arget case, will reach 11.9 million tons. There are 10 original cases which have relatively high similarities to the target case. Furthermore, the case of Yinchuan, 2010, has the largest similarity, followed by Yinchuan, 2009, and Urumqi, 2009. We also made a comparison experiment in which case-based reasoning is more accurate than the grey forecast model and BPN in water demand forecasting. It is expected that the results of this study will provide references to water resources management and planning.

Coupling WetSpass and MODFLOW for groundwater recharge assessment: case study of the Takelsa multilayer aquifer, northeastern Tunisia

The water scarcity and its socio-economic significance with respect to water demand for agriculture, industry and tourism, in the northeastern Tunisia (Cap-Bon), are at the origin for prospecting new groundwater resources and for developing groundwater models that can be used to their control and management. The Takelsa multilayer aquifer is one of the important aquifers of the northeast in Tunisia. It is among the aquifers which are still slightly known in spite of its exploitation since the 80s. This paper is aimed to quantify the groundwater recharge of the Takelsa multilayer aquifer. The groundwater recharge is assessed using WetSpass which is a physically based model integrated in GIS ArcView as a raster model. The simulated results are given seasonally and yearly at the grid level. These results are subsequently incorporated in the groundwater flow simulation model MODFLOW in order to simulate the hydraulic head distribution. The steady state groundwater flow calibration was obtained by comparing the observed and the simulated hydraulic heads. The mean annual evapotranspiration, surface runoff and groundwater recharge simulated by WetSpass, are 461, 92 and 22 mm, respectively. The groundwater recharge represented 4.3% of the precipitation while 17.8% and 89% are respectively lost by surface runoff and evapotranspiration.

Hierarchical prediction of industrial water demand based on refined Laspeyres decomposition analysis.

A recent study decomposed the changes in industrial water use into three hierarchies (output, technology, and structure) using a refined Laspeyres decomposition model, and found monotonous and exclusive trends in the output and technology hierarchies. Based on that research, this study proposes a hierarchical prediction approach to forecast future industrial water demand. Three water demand scenarios (high, medium, and low) were then established based on potential future industrial structural adjustments, and used to predict water demand for the structural hierarchy. The predictive results of this approach were compared with results from a grey prediction model (GPM (1, 1)). The comparison shows that the results of the two approaches were basically identical, differing by less than 10%. Taking Tianjin, China, as a case, and using data from 2003-2012, this study predicts that industrial water demand will continuously increase, reaching 580 million m3, 776.4 million m3, and approximately 1.09 billion m3 by the years 2015, 2020 and 2025 respectively. It is concluded that Tianjin will soon face another water crisis if no immediate measures are taken. This study recommends that Tianjin adjust its industrial structure with water savings as the main objective, and actively seek new sources of water to increase its supply.

Development of urbanization in arid and semi arid regions based on the water resource carrying capacity -- a case study of Changji, Xinjiang

The arid and semiarid region in China where have a relatively weak economic foundation, independent development capacity, and the low-level of urbanization. The new urbanization within these regions is facing severe challenges brought by the constraints of resources. In this paper, we selected the Changji Hui Autonomous Prefecture, Xinjiang Uyghur Autonomous Region as study area. We found that agricultural planting structure is the key water consumption index based on the research about the main water demands of domestic, agriculture and industry. Finally, we suggest that more attentions should be paid to the rational utilization of water resources, population carrying capacity, and adjust and upgrade the industrial structure, with the purpose of coordination with the Silk Road Economic Belt.

Multi‐model and multi‐scenario assessments of Asian water futures: The Water Futures and Solutions (WFaS) initiative

AbstractThis paper presents one of the first quantitative scenario assessments for future water supply and demand in Asia to 2050. The assessment, developed by the Water Futures and Solutions (WFaS) initiative, uses the latest set of global climate change and socioeconomic scenarios and state‐of‐the‐art global hydrological models. In Asia, water demand for irrigation, industry, and households is projected to increase substantially in the coming decades (30–40% by 2050 compared to 2010). These changes are expected to exacerbate water stress, especially in the current hotspots such as north India and Pakistan, and north China. By 2050, 20% of the land area in the Asia‐Pacific region, with a population of 1.6–2 billion, is projected to experience severe water stress. We find that socioeconomic changes are the main drivers of worsening water scarcity in Asia, with climate change impacts further increasing the challenge into the 21st century. Moreover, a detailed basin‐level analysis of the hydro‐economic conditions of 40 Asian basins shows that although the coping capacity of all basins is expected to improve due to gross domestic product (GDP) growth, some basins continuously face severe water challenges. These basins will potentially be home to up to 1.6 billion people by mid‐21st century.

A dynamic model for exploring water-resource management scenarios in an inland arid area: Shanshan County, Northwestern China

Water scarcity is a challenge in many arid and semi-arid regions; this may lead to a series of environmental problems and could be stressed even further by the effects from climate change. This study focused on the water resource management in Shanshan County, an inland arid region located in northwestern China with a long history of groundwater overexploitation. A model of the supply and demand system in the study area from 2006 to 2030, including effects from global climate change, was developed using a system dynamics (SD) modeling tool. This SD model was used to 1) explore the best water-resource management options by testing system responses under various scenarios and 2) identify the principal factors affecting the responses, aiming for a balance of the groundwater system and sustainable socio-economic development. Three causes were identified as primarily responsible for water issues in Shanshan: low water-use efficiency, low water reuse, and increase in industrial water demand. To address these causes, a combined scenario was designed and simulated, which was able to keep the water deficiency under 5% by 2030. The model provided some insights into the dynamic interrelations that generate system behavior and the key factors in the system that govern water demand and supply. The model as well as the study results may be useful in water resources management in Shanshan and may be applied, with appropriate modifications, to other regions facing similar water management challenges.

Forecasting industrial water demand in Huaihe River Basin due to environmental changes

A framework is proposed for forecasting industrial water demand in the context of climate change, economic growth, and technological development. The framework was tested in five sub-basins of Huaihe River of China, namely Upstream of Huaihe River (UH), Middlestream of Huaihe River (MH), Downstream of Huaihe River (DH), Yishusi River (YSSR), and Coastal River of Shandong Peninsula (CSP) to project future changes in industrial water demand under different environment change scenarios. Results showed that industrial water demand in Huaihe River basin will increase in the range of 10 to 44.6% due to economic development, water-saving technological advances, and climate change. The highest increase was projected by general circulation model (GCM) BCC-CSM1–1 (179.16 × 108 m3) and the lowest by GCM GISS-E2-R (132.4 × 108 m3) in 2020, while the GCM BNU-ESM projected the highest increase (190.57 × 108 m3) and GCM CNRM-CM5 the lowest (160.41 × 108 m3) in 2030. Among the different sub-basins, the highest increase was projected in MH sub-basin where industrial water demand is already very high. On the other hand, the lowest increase in industrial water demand was projected in UH sub-basin. The rapid growth of high water-consuming industries and increased water demand for cooling due to temperature rise are the major causes of the sharp increase in industrial water demand in the basin. The framework developed in the study can be used for reliable forecasting of industrial water demand which in turn can help in selection of an appropriate water management strategy for adaptation to global environmental changes.

An approach for forecasting of public water scarcity at the end of the 21st century, in the Timiş Plain of Romania

The balance between water demand and availability in Romania, as well as in many areas of Europe, will soon reach a critical level if predictions by simulated climate change scenarios are correct. The article is focused on the risk of water shortages, due to the climate change, in the Timiş Plain in Romania, a densely populated region, with 346,818 inhabitants. Estimates of future water availability for public water supply consider relevant socio-economic scenarios for major water users, estimate their future water demand, and assess water shortage for the main users. The water demand components were estimated for households, industries, services, and livestock, based on specific socio-economic assumptions. A non-probabilistic risk assessment, using simplified fuzzy sets mathematics, considers water supply, water demand and the consequences of water shortage. The results of the study revealed a vulnerability of the water supply and sewerage networks, an expected increase in households' demand, in the rural and in the urban, an expected increase for industrial and services water demand and a positive dynamic for the livestock water demand and finally a water shortage in the study area.

A forecast of public water scarcity on Leu-Rotunda Plain, Romania, for the end of the 21st century

ABSTRACTThe article examines the risk of water shortages due to the climate change on Leu-Rotunda Plain, which is part of Oltenia Plain in Romania. The region has been exposed to several extreme climatic phenomena, mostly droughts, which has created several problems related to water quality and quantity. The authors defined climate change scenarios using two regional climate models. Water resources under climate change were estimated by a regional numerical groundwater model covering a deep aquifer. The water demand components were estimated for households, industries, services, and livestock, based on specific socio-economic assumptions. A non-probabilistic risk assessment, using simplified fuzzy sets mathematics, was used to estimate water supply, water demand, and the consequences of water shortages. The results of the study revealed significant vulnerability in the water supply, a limited territorial expansion of sewerage networks, an expected increase in households’ demand, an expected increase in industrial and services water demand, a relatively stable demand for water for livestock farming, and an important water shortage in the study area. The authors conclude by highlighting a set of actions to mitigate the risk of the potential crisis.

Industrial water demand for agro-processing and beverage industries in Rwanda

Abstract Background Water play important role in industrial operation of food processing, such ingredient of the product, operation of equipment such as boilers, cooling towers, cleaning purposes to ensure a sufficient level of hygiene and food safety etc. Rwanda is rapidly developing and this development is associated with increase in population, urbanization, industrialization, modification of agricultural practices including rise in area of irrigated land etc. All these could cause increase in water uses and modification of water demand. Assessing future water demand of the country requires the understanding of specific water demand of different sectors mentioned above and its variation within those sectors. Growth of industrial sector is expected to rise in Rwanda especially because of the created enabling environment; this of cause will cause the rise in industrial water demand. In order to understand industrial water demand and be able to project it for the future it is necessary to know specific water demand of different type of industries in the country. However, there is no published evidence of this information country wide. It is therefore necessary to conduct industrial water demand assessment in the country. The main of this study is to quantify industrial water demand for different types of industries in Rwanda. Methods The data used for this study were obtained from records of various food processing industries and breweries, interviews and from relevant organizations such as Rwanda Development Board (RDB), Water and Sanitation Corporation (WASAC), Ministry of Trade (MINICOM), and National Institute of Statistics of Rwanda (NISR). Specific water demand for various products was estimated taking into consideration the amount of water used and quantity of product produced. Correlation method in MATHLAB was used to determine the relationship between water used and production. Results and discussion The results show that industrial water used for some industrial production in Rwanda is within the recommend limit example maize flour 2m3/ton and breweries such as beer production industry 4 to 4.5 m3/m3 and carbonate soft drink industries 4m3/m3, as against internationally recommended water of 2m3/ton, and 6.5 m3/m3 respectively. However water uses for of the following, Sugar making industry 29/m3/t, Meat processing industry 5/m3/t and Tomato paste production industry 6 m3/ton exceeded the internationally recommended which are 25/m3/t, 2/m3/t, 3.58 m3/ton. Tomato Paste production industry shown strong relationship because as water demand is increasing also production is increasing. Thus from this linear model, about 98% of the variation in water demand can be explained by variation of tomato paste production due to high relationship between water demand and tomato paste production. Conclusions The quantity of water consumption differs between types of industries. It was revealed that the brewing industries uses more water than any other kind of industries in Rwanda this could related the amount of production and demand for the product. There is wide difference in specific water consumption between various industries. Brewery industries in Rwanda have shown best practice of water demand with specific water demand of 4 to 4.5 m3/m3 of final product in which is less than the global bench mark of 6.5 m3/m3. Improvements need to be made in order to achieve the recommended best practice of three cubic meters of raw water for every cubic meter of carbonate soft drinks and four cubic meters of raw water for every cubic meter of beer produced.

Modeling the Effects of Conservation, Demographics, Price, and Climate on Urban Water Demand in Los Angeles, California

With a service area population exceeding four million people and with close to 90 % of the water supply being imported from sources outside the city, the Los Angeles water system is subject to multiple stressors, including climate change and population growth. The influence of various factors on water demand in Los Angeles was evaluated through development and application of multiple linear regression models for residential, commercial, industrial, and governmental water demand categories from 1970 to 2014 in the service area of the Los Angeles Department of Water and Power. Performance of the models in describing historical water demand was compared using the coefficient of determination, mean average percent error, and normalized root mean square error. Overall, the results of the linear regression models demonstrated that each water demand category is affected by different parameters. However, price and population were found to have the most significant impact on all categories. The seasonality of residential water demand was well described with the model based on monthly data, with precipitation and temperature being highly significant factors. Fitting of the residential data furthermore revealed that price and conservation have significantly counteracted the impact of population growth on water demand.

A system dynamics simulation model for sustainable water resources management and agricultural development in the Volta River Basin, Ghana

In a rapidly changing water resources system, dynamic models based on the notion of systems thinking can serve as useful analytical tools for scientists and policy-makers to study changes in key system variables over time. In this paper, an integrated system dynamics simulation model was developed using a system dynamics modelling approach to examine the feedback processes and interaction between the population, the water resource, and the agricultural production sub-sectors of the Volta River Basin in West Africa. The objective of the model is to provide a learning tool for policy-makers to improve their understanding of the long-term dynamic behaviour of the basin, and as a decision support tool for exploring plausible policy scenarios necessary for sustainable water resource management and agricultural development. Structural and behavioural pattern tests, and statistical test were used to evaluate and validate the performance of the model. The results showed that the simulated outputs agreed well with the observed reality of the system. A sensitivity analysis also indicated that the model is reliable and robust to uncertainties in the major parameters. Results of the business as usual scenario showed that total population, agricultural, domestic, and industrial water demands will continue to increase over the simulated period. Besides business as usual, three additional policy scenarios were simulated to assess their impact on water demands, crop yield, and net-farm income. These were the development of the water infrastructure (scenario 1), cropland expansion (scenario 2) and dry conditions (scenario 3). The results showed that scenario 1 would provide the maximum benefit to people living in the basin. Overall, the model results could help inform planning and investment decisions within the basin to enhance food security, livelihoods development, socio-economic growth, and sustainable management of natural resources.

Conjunctive Water Use Optimization for Watershed-Lake Water Distribution System under Uncertainty: a Case Study

In this research, a large-scale inexact optimization method was developed for the conjunctive use management of a watershed-lake water distribution system. The modeling framework has the advantages in taking into account the water balance of multi-reservoirs, satisfying the municipal industrial and agricultural water demands in the multi-period context, reflecting the relationship among multi-reservoirs, multiple water related projects, and maintaining the operational rules of certain lake levels. Moreover, such a method can also handle the uncertainty expressed as fuzzy membership functions through integrating the fuzzy credibility chance-constrained programming. The developed method was applied to the conjunctive use management of water resources in the lake Dianchi watershed, China. Cost-effective water allocation schemes for the groundwater project and the water transfer project, and optimal operational rules for the lake and multiple reservoirs were successfully obtained. Also, the annual water balance of the watershed-lake system and the system cost of the conjunctive water use were investigated and analyzed under multiple credibility levels of meeting the water demands for municipal, industrial and agricultural users.

Application of peak load for industrial water treatment plant design

Peak load rate(i.e., maximum daily flow/average daily flow) has not been considered for industrial water demand planning in Korea to date, while area unit method based on average daily flow has been applied to decide capacity of industrial water treatment plants(WTPs). Designers of industrial WTPs has assumed that peak load would not exist if operation rate of factories in industrial sites were close to 100%. However, peak load rates were calculated as 1.10~2.53 based on daily water flow from 2009 to 2014 for 9 industrial WTPs which have been operated more than 9 years(9-38 years). Furthermore, average operation rates of 9 industrial WTPs was less than 70% which means current area unit method has tendency to overestimate water demand. Therefore, it is not reasonable to consider peak load for the calculation of water demand under current area unit method application to prevent overestimation. However, for the precise future industrial water demand calculation more precise data gathering for average daily flow and consideration of peak load rate are recommended.

Agricultural water supply/demand changes under projected future climate change in the arid region of northwestern China

The water resources in the arid region of northwestern China, which are impacted by climate change, tend to be more unstable, and the environment and ecosystems will suffer from severe water shortage. In this paper, potential future climate trends were predicted based on CMIP5 simulations in this region. The water availability and agricultural water demand under future climate change scenarios were estimated. Impacted by increases in temperature, the irrigation water demand will increase by 4.27–6.15billionm3 in this region over the next 60years, compared to the demand of 32.75billionm3 during 1971–2000. However, the annual runoff will only increase by 4.8–8.5billionm3, which is equivalent to or even less than the increased irrigation water demand. In fact, the increased demand for industrial, domestic and ecological water were not considered here. Thus, the water supply/demand contradiction will result in more severe water shortages in the future. According to a comparison with simulated irrigation water demand under three adaptation strategy scenarios, we should take effective measures such as improving the efficiency of irrigation water utilization, reducing crop planting areas and adjusting crop planting structures to alleviate the impacts of future climate changes and human activities on the water supply and water use in this region.