Forecasting industrial water demand in Huaihe River

Mitig Adapt Strateg Glob Change DOI 10.1007/s11027-017-9744-1 O R I G I N A L A RT I C L E

Forecasting industrial water demand in Huaihe River Basin due to environmental changes Xiao-jun Wang 1,2,3 & Jian-yun Zhang 1,2 & Shamsuddin Shahid 4 & Shou-hai Bi 5 & Amgad Elmahdi 6 & Chuan-hua Liao 7 & You-de Li 8

Received: 21 May 2016 / Accepted: 20 March 2017 # Springer Science+Business Media Dordrecht 2017

Abstract 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 subbasin where industrial water demand is already very high. On the other hand, the lowest

* Xiao-jun Wang [email protected]

1

State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Nanjing Hydraulic Research Institute, Nanjing 210029, China

2

Research Center for Climate Change, Ministry of Water Resources, Nanjing 210029, China

3

State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China

4

Faculty of Civil Engineering, Universiti Teknologi Malaysia, Johor Bahru 81310, Malaysia

5

Department of Water Resources, Ministry of Water Resources, Beijing 100053, China

6

Urban Water Balance, Climate and Water Division, Bureau of Meteorology, Melbourne 3008, Australia

7

Nanjing Tech University, Nanjing 211800, China

8

Huaihe River Water Resources Commission, Beijing 233001, China

Mitig Adapt Strateg Glob Change

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. Keywords Water demand forecasting . Climate change . Industrial water use . Water resources management . Huaihe River basin

1 Introduction Climate change, socio-economic development, and population growth are the main factors for increasing water demand and growing water stress across the world (Frederick 1997; PahlWostle et al. 2007; Arnell and Lloyd-Hughes, 2013; Wang et al. 2015a, b). Ensuring continuous supply of sufficient water in the context of these environmental changes is a major challenge in water resources management (Butler and Memon 2006; Kim et al. 2014; Wang et al. 2016a, b). Prudent management of finite water resources is considered as the most appropriate option for adaption to environmental changes. The projection of possible future changes in water demand is the most crucial component for water resources management. However, reliable projection of water demand is an extremely difficult task as it depends on various socio-economic, behavioral, and physical factors (Wang et al. 2016a). This emphasizes the need to forecast water demand in a holistic way. Industrial water demand is the amount of water used for cooling, processing and manufacturing operations, and power generation. It shares 22% of total water use globally but increasing rapidly with economic development. For example, industrial water use is only 10% for low-income countries, whereas it is 59% for high-income countries. Globally, industrial water consumption tripled from ∼100 to 300 km3 year−1 over the past 50 years. It is projected to increase continuously and reach to ∼550 km3 year−1 in 2050 (Wada and Bierkens 2014). The Organization for Economic Cooperation and Development (OECD 2012) projected that global water demand will increase by 55% between 2000 and 2050, which is mainly due to increased demand in manufacturing (+400%), electricity (+140%), and domestic use (+130%). WRG (2009) projected that share of industrial water use to total water use will increase, while it will decrease for agriculture. WWAP (2012) also projected increase in water demand in all sub-sectors of the industry. Asia will need on average 65% more freshwater withdrawals for their industry and energy sectors by 2030 to meet the forecasted national economic growth rate (WRG 2009). In India, the water demand by the industries will rise from 6% of the total freshwater abstraction in 2010 to 8.5% and 10.1% in 2025 and 2050, respectively (FICCI, Federation of Indian Chambers of Commerce and Industry, 2011). The increase in industrial water demand is more prominent in China compared to other countries. Despite the decrease in agricultural water demand, which shares 70% of total water use, the total water demand in China increased by 37.6% between 1980 and 2011. This increase is mostly due to increasing demand by industries, from 45.7 billion m3 in 1980 to 146.2 billion m3 in 2011 (Pahl-Wostl et al. 2016). Rapid industrialization with per annum gross domestic product (GDP) growth of 9 to 10% in last several years is the major cause of this sharp increase in industrial water demand. An efficient and productive industrial sector is


critical for rapid economic growth. Therefore, the Chinese government will pay more attention to economic development to keep the GDP growth rate at 7%, which will certainly increase industrial water demand in future. As the increase in future water demand will be mainly due to increased industrial water demand, managing industrial water use is considered as a major option to alleviate foreseen water stress. However, compared to agricultural and residential water demand, less attention have been paid on modeling industrial water demand by considering various economic and social factors (Reynaud, 2003; Jia, 2006; Horie 2011; Tarnacki 2013; Li and Ma 2014). Only a few studies have been conducted to assess the impact of meteorological factors, particularly surface temperature on industrial water demand (Mote et al., 1999; Protopapas et al., 2000; Downing et al. 2003; Koch and Vögele 2009; Zachariadis 2010; Rübbelke and Vögele 2011; Jessberger 2011; Averyt et al. 2011; Linnerud et al. 2011; Förster and Lilliestam 2010; Khan et al. 2012; Jampanil et al. 2012). The studies by Koch and Vögele (2009), Rübbelke and Vögele (2011) and Khan et al. (2012) reported that if intake water temperature for cooling increases from 18 to 23 °C, the water required to dissipate 42 MJ of heat increases from 1 to 2 m3. It is very likely that an increase in air temperature will result in a corresponding increase in the water temperature of rivers and lakes (Hammond and Pryce 2007; Luoto and Nevalainen 2013) and therefore, water demand for cooling. Mote et al. (1999) and Downing et al. (2003) reported a small increase in industrial water demand due to climate change. Koch and Vögele 2009 and Downing et al. (2003) also projected an indirect but small (>5% by the year 2050) secondary effect on industrial water demand. Averyt et al. (2011) reported that water demands for industrial cooling and thermoelectric power production are likely to increase with warmer air and water temperatures. Jampanil et al. (2012) estimated an increase in industrial water demand indirectly by 0.2% in Thailand in the mid of twentieth century. Jessberger (2011) projected a change in industrial water usage ranging between −5.58% and +11.64% in 2025 relative to the base year 2012 in the upper Danube river basin. Above studies indicate that the increase in industrial water demand depends more on the local climatic conditions, especially on the intake water temperature. The studies also reported the difficulties in estimating climate change impacts on industrial water demand. Industrial water demand depends on a number of socio-economic factors like economic growth, behavioral factors like water-saving strategy and physical factor like rainfall and temperature. Therefore, it is required to forecast industrial water demand by considering various physical and socio-economic factors. The objective of the present study was to develop a framework for forecasting industrial water demand under changing environment. The framework has been used for forecasting industrial water demand in different sub-basins of Huaihe River in China due to climate change, economic growth, and technological advancement. The framework used statistical model developed through the analysis of historical climate and industrial water use data. The Huaihe River is the 6th largest river in China, located between 111°55′–121°25′E and 30°55′–36°36′N (Fig. 1). The river basin is situated in the climatic transition zones of China, where south of the basin belongs to the subtropical climate, while the northern part belongs to the warm temperate climate. Because of its special geographical features and climate conditions, the Huaihe River basin is one of the most populated regions of China. The basin experienced a rapid industrialization in the recent years, which caused a significant increase in water demand. Consequently, the gap between water supply and demand in the basin widened (Wang et al. 2017a). Though a number of measures have been taken to reduce industrial water use, it is anticipated that temperature rise due to climate change may increase industrial water demand, which in turn may aggravate the condition of water shortage in the basin. Therefore, assessment of the impacts of climate and other environmental changes on industrial water demand is very important for water resources planning and management of the basin.


Figure 1 Different sub-basins of China’s Huaihe river basin

2 Data and methods 2.1 Data and sources The annual industrial water use data for different sub-basins of Huaihe River (Fig. 1) namely, the 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) for the period 1980 to 2012 were collected from the Huaihe River water resources bulletins (HRCC, 1998). The industrial water demand data was available only for 15 years between 1980 and 2012. Available data was randomly distributed over the period. Daily temperature data recorded at 36 stations in the basin for the same period were obtained from National Climate Center of China. Daily temperature data for all stations of a sub-basin were averaged to get the areal average temperature of each subbasin. The annual mean temperature in Huaihe River basin projected by 7 general circulation models (GCMs) namely, BCC-CSM1–1, BNU-ESM, CNRM-CM5, GISS-E2-R, MIROC-ESM, PI-ESM-LR, MRI-CGCM3 under Representative Concentration Pathways (RCP) 4.5 scenario for the period 2006–2099 were also collected from National Climate Center of China. The RCP 4.5 is an intermediate pathway scenario which assumes stabilization of radiative forcing at 4.5 W/m2 in the year 2100 without ever exceeding that value, which will cause an average increase of global temperature by maximum 2.4 °C in the end of the century. The RCP4.5 provides a common platform for climate models to explore the climate system response to stabilizing the anthropogenic components of radiative forcing (Thomson et al. 2011). The latest policy of Chinese government is environmental sustainability and lower greenhouse gas emission, and therefore, the RCP4.5 scenario can be considered as most realistic for China (Wang et al. 2016c, Wang et al. 2017a). Furthermore, comparison of land use and land cover changes (LUCC) in China under RCP4.5 and


existing land use structures revealed that the simulated LUCC is more close to the real conditions (Deng et al. 2014). Therefore, the RCP4.5 scenario was chosen for the study. Daily temperature data was converted to the annual mean temperature in order to assess the impact of temperature on industrial water demand. Besides temperature, the other factors that determine industrial water use are industrial growth, water-saving measures, and technological advances. These factors are required to consider together for reliable projection of future industrial water demand. The planning authority of Huaihe River basin projected industrial water demand in the basin based on the projected advances in technology and effect of planned water-saving measures. The projected data of industrial growth and industrial water demand due to technological advances and watersaving measures were collected from Huaihe River basin authority and used in the present study.

2.2 Methodology The framework proposed for the modeling of industrial water demand due to changes in climate and other economic and technological factors is shown in Fig. 2. According to the framework, industrial water demand was estimated using the following steps: 1. Historical climate and industrial water demand time series were detrended and then used to assess the climate elasticity of industrial water demand. 2. The climate elasticity factor was used to estimate possible future changes in industrial water demand from GCM projected climate under RCP4.5 scenario. 3. Industrial growth and changes in industrial water demand per unit industrial value added projected by planning authority of Huaihe River basin were used to estimate possible changes in industrial water demand due to economic development and technological advances. 4. Projections of industrial water demand due to climate change in Step 2 and economic development in Step 3 were added to forecast future changes in industrial water demand due to total environmental changes. Climate change

Precipitation Temperature

GCMs: BCC-CSM11BNU-ESM CNRM-CM5 GISS-E2-R MIROC-ESM MPI-ESMLRMRICGCM3

Industrial water consumption

Climatic elasticity of Industrial water demand

Future climateinduced Industrial water demand

Future total Industrial water demand

Industrial value added

Water demand per 4 10 Yuan of industrial value added

Industrial value added projection

Future Water demand per 104 Yuan of industrial value added

Industrial Water demand

Fig. 2 Framework for forecasting industrial water demand under climate change, economic development, and advances in water-saving technology


The proposed framework was used to project industrial water demand in different subbasins of Huaihi River. The planning and development authorities of China estimates future changes in industrial water demand by multiplying industrial value added and water demand per 104 Yuan of industrial value added. Therefore, the influence of climatic factors in forecasting industrial demand is ignored. The framework proposed in this study can project industrial water demand by considering all the important influential factors together. The framework considers the influence of both rainfall and temperature in industrial water demand. However, no significant change in rainfall in Huaihe river basin has been projected by GCMs, and therefore, only the influence of temperature was considered to assess the impact of climate change on industrial water demand. A linear regression function was developed to relate historical temperature with industrial water use: y ¼ β0 þ β1 x þ ε

ð1Þ

where y is industrial water demand and x is temperature. A ridge regression model was developed by fitting the data through minimizing a penalized version of the least squares loss function (Wang and Fu 2011; Sajil Kumar et al. 2013) as Q β̂ 0 ; β̂ 1 ¼

min

−∞< β 0 ;β1 < ∞

Qðβ 0 ; β 1 Þ

ð2Þ

which gives, 8 > > β ̂ 0 ¼ y−β 1 x > > > n < ∑ xi −x yi −y > β ̂ 1 ¼ i¼1 n > 2 > > > : ∑ xi −x

ð3Þ

i¼1

n

n

i¼1

i¼1

where x ¼ 1n ∑ xi , y ¼ 1n ∑ yi . Then ŷ ¼ β ̂ 0 þ β ̂ 1 x ¼

¼ y þ β ̂ 1 x−x

ð4Þ

where, β1 is the slope, which gives the changes in industrial water use due to temperature rise by 1 °C. It is known as temperature elasticity of industrial water use. The regression method assumes that the data are normally distributed. Therefore, a test of normality of data was carried out using Kolmogorov–Smirnov one-sample test. The Kolmogorov–Smirnov statistic for a given cumulative distribution function F(x) is Dn ¼ supx j F n ðxÞ−F ðxÞj

ð5Þ

where, F(x) is the empirical distribution function based on the random sample X1, X2,…, Xn; F(x) is the hypothesized distribution function, which is considered as normal distribution in the present study; and supx is the greatest vertical distance between Fn(x) and F(x). If the sample comes from distribution F(x), then Dn converges to 0. In the present study, a significance level of 0.05 was considered to test the normality of water use and temperature data.


The future industrial value added was projected from the industrial growth rate estimated based on local developments and future plans devices by Huaihe River basin authority. The future water demand per 104 Yuan of industrial value added was estimated by considering economic development and improvement in water-saving technology together. The industrial water demand can be forested by multiplying industrial value added and water demand per 104 Yuan of industrial value added as follows: t t n xi :IQi Iwt ¼ ∑ i¼1

ð6Þ

where t is time, Iwtis the industrial water demand (104 m3), xti is the industrial value added and IQti is the quota of industrial demand. The equation is improved by incorporating the impacts of temperature change on industrial water demand, ΔIwt as follows: ΔIwt ¼ β 1 ⋅ΔT ⋅Iwt

ð7Þ

where, ΔIw is the change in industrial water demand (104m3), ΔT is the change in temperature (°C), and β1 is the temperature elasticity of industrial water demand estimated using eq. (4).

3 Results The industrial water demand in different sub-basins of the Huaihe River was estimated using the proposed framework. Obtained results are presented based on the procedural steps mentioned in the method section.

3.1 Climate elasticity of industrial water use Industrial growth is the most influential factor that determines the long-term trend in industrial water demand. Therefore, it was required to remove the impact of industrial growth on total industrial water use in order to assess the impact of temperature on industrial water use. This was done by de-trending the industrial water use data using simple linear regression with water use as the dependent variable and industrial growth as an independent variable. The rectified water use and temperature time series were then tested for normality using Kolmogorov– Smirnov test. The result revealed that the temperature and water demand data were normally distributed at a significance level of 0.05. Regression analysis was conducted between historical annual mean temperature and annual industrial water use data available for 15 years over the period 1980–2012 to estimate the effects of temperature on industrial water use. The relationships between temperature and industrial water use in different sub-basins of Huaihe River are shown in Fig. 3. The x-axis of the graphs in Fig. 3 represents industrial water demand in 108 m3, and y-axis represents temperature in degree Celsius. The result showed that changes in temperature have direct effect on industrial water demand in the basin. However, the effect was different for different sub-basins. The highest increase in industrial water use was found in UH sub-basin of Huaihe River by 14.675 × 108 m3 for every increase of temperature by 1 °C. On the other hand, the lowest increase was observed in YSSR sub-basin by 0.393 × 108 m3 for every increase of temperature by 1 °C.


Fig. 3 Relationships between mean temperature and annual industrial water use in (a) UH, (b) MH, (c) DH, (d) YSSR, and (e) CSP sub-basins of Huaihe River during 1980–2012

Industrial water use was found to increase nearly by 44.6% for every rise of temperature by 1 °C in UH. Therefore, UH sub-basin can be considered as the most vulnerable region to climate change-induced temperature rise in term of industrial water demand.

3.2 Climate change impacts on industrial water demand in Huaihe River basin The projection of temperature in Huaihe River basin by GCM BCC-CSM1-1, BNU-ESM, CNRM-CM5, GISS-E2-R, MIROC-ESM, PI-ESM-LR, and MRI-CGCM3 under RCP4.5 are shown in Fig. 4. The figure shows a continuous increase in temperature in the basin until the end of this century. The changes in industrial water demand in Huaihe River basin due to changing in temperature was estimated using equations given in Fig. 3. Results revealed an increase in industrial water demand with increasing temperature. Projected change in industrial water demand in different sub-basins of Huaihe River in years 2020 and 2030 are shown in Figs. 5 and 6, respectively. The industrial water demand was projected to increase continuously in all the sub-basins of Huaihe River. However, the highest increase was projected in MH sub-basin and the lowest in CSP sub-basin. The projected change in water demand was found to vary widely with GCMs. The BCC-CSM1-1 projected the highest increase, while GISS-E2-R projected the lowest increase in industrial water demand in 2020. On the other hand, BCCCSM1-1 projected the highest and CNRM-CM5 projected the lowest increase in industrial


Fig. 4 Temperature projected by different GCMs in Huaihe River basin under RCP4.5 scenario

water demand in 2030. This indicates high uncertainty in projected increase in industrial water demand in Huaihe River basin.

3.3 Economic development and industrial water use in Huaihe River basin Huaihe River basin has experienced a rapid economic development in recent years. The development was much faster in MH sub-basin, which is the most populated region of the basin. The historical growth and future projection of industrial value added in different subbasins of Huaihe River from 1980 to 2030 are shown in Fig. 7. According to the future plans of the Huaihe River basin, total industrial value added will reach 31,659 × 104 Yuan or U$47.5 million by 2020 and 57,159 × 104 or U$85.8 million by 2030. The historical changes and future projection of water demand per 104 Yuan of industrial value added in different sub-basins of Huaihe River from 1980 to 2030 are shown in Fig. 8. The industrial water demand projected by planning authority of Huaihe River basin due to technological advances and water-saving measures were used to estimate the changes. The figure shows that the technological advances and water-saving measures caused a continuous decrease of the water demand per 104 Yuan of industrial value added in the basin in past years. The water demand per 104 Yuan of industrial value added decreased from 927 m3/104Yuan in 1980 to 84 m3/104Yuan in 2000. According to the future plans of the Huaihe River basin, the

Fig. 5 Projected changes in industrial water demand in different sub-basins of Huaihe River due to climate change in 2020


Fig. 6 Projected changes in industrial water demand in different sub-basins of Huaihe River due to climate change in 2030

water demand per 104 Yuan of industrial value added will further decrease to 39.4 m3/104Yuan in 2020 and 23.9 m3/104Yuan in 2030. However, the total industrial water demand will increase because of the industrial development.

3.4 Changes in industrial water demand due to total environmental changes The changes in industrial water demand due to industrial growth, technological advances and water-saving measures were estimated by multiplying the growth in industrial value added (Fig. 7) and changes in water consumption per 104 Yuan of industrial value added (Fig. 8) projected by planning authority of Huaihe River basin due to technological advances and water-saving measures. Obtained changes were added with the changes in industrial water demand estimated due to climate change to get the changes in industrial water demand due to total environmental changes. Figures 9 and 10 show the projected industrial water demand in 2020 and 2030 due to total environmental changes. The GCM BCC-CSM1-1 estimated the highest increase in industrial demand (179.16 × 108 m3) in Huaihe River in 2020. On the other hand, the GCM GISS-E2-R projected the lowest increase (132.4 × 108 m3) due to the changes in climate and other factors. However, the result was found different for 2030. The GCM BNU-ESM projected the highest (190.57 × 108 m3) and CNRM-CM5 projected the lowest (160.41 × 108 m3) increase in industrial water demand in 2030. Among the different subbasins, industrial water demand was found to increase much faster in MH sub-basin. On the other hand, the lowest increase in industrial water demand was found in UH sub-basin.

Fig. 7 The growth in industrial value added in different sub-basins of Huaihe River over the period 1980–2030


Fig. 8 Changes in water consumption per 104 Yuan of industrial value added in the Huaihe River basin

Competition for water among water users increases the risk of localized conflicts and inequities in access to services (WWAP, 2012). Demand for water in all water using sectors of Huaihe River basin is expected to increase. Therefore, it can be anticipated that the sharp increase in industrial water demand will increase the competition with other water using sectors and water stress in the region.

4 Discussion The majority of water withdrawn by industry is used for the cooling process (Koch and Vögele 2009). For example, power plant cooling is responsible for 43% of total freshwater withdrawals in Europe, nearly 50% in the USA, and more than 10% in China (UNESCO 2014). There is a direct relationship between cooling water demand and temperature of water used for cooling (Koch and Vögele 2009; Khan et al. 2012). Therefore, water demand in power plants and manufacturing facilities increases with the increases in temperature. The main industries in the Huaihe River basin are coal, electrical power, food, light industry and textiles (United Nations 2006). Huaihe River basin is the largest national coal production base. A large number of thermal power plants have also been developed in the basin in last decades. Besides that, other high water-consuming industries like coal chemical industry has been greatly developed (Lai 2013). This has caused a large increase in industrial water demand in Huaihe River basin

Fig. 9 Projected changes in industrial water demand in different sub-basins of Huaihe River due to total environmental changes in 2020


Fig. 10 Projected changes in industrial water demand in different sub-basins of Huaihe River due to total environmental changes in 2030

and competition among water users. The preset study revealed that rising temperature is another major cause of increased industrial water demand in the basin. Like Huaihe River basin, industrial water demand has also increased in many other river basins of China. Consequently, the total industrial water demand in China has increased from 45.7 billion m3 in 1980 to 145 billion m3 in 2010. The share of industrial water demand to total water demand has also increased from 10.3% in 1980 to 24.6% in 2010. The water supply capacity of the country was also increased continuously to meet the increasing demand in order to ensure the industrial development. However, water is a finite resource, and therefore, ever-increasing water demand cannot be met only by supply augmentation. Therefore, the need of water demand management along with water supply augmentation strategy has been realized for adaptation to global environmental changes (Wang et al. 2016a). The Chinese government adopted strictest water resource management (SWRM) system in 2010 for ensuring water security under the scenarios of rapid economic development and population growth (Wang 2011; Liu et al. 2013; Global Water Partnership 2015; Wang et al. 2017b). One of the major targets of SWRM was to limit water use per 104 Yuan of industrial added value by 30% below the 2010 value in 2015, 65 m3 in 2020, and 40 m3 in 2020. Chinese government has taken number of measures in order to increase industrial water use efficiency and strengthen water resources management system which include strengthening legislations on water saving, reduce fragmentation in water resources management system, increase the capacity of hydrological monitoring, efficient management of water quota, and mandatory standards of water saving. It has been reported that water use per 104 Yuan industrial added value in the end of 2014 was less than 31.9% of 2010 value (MWR 2015), which indicates the progress achieved in industrial water resources management in China through the implementation of SWRM system. The targets of SWRM were made based on the assumption that industrial water demand will increase according to the growth of economy and advances in water-saving technologies. However, the impacts of climate change in industrial water demand were ignored. Therefore, climate change alone with other influential factors are required to considered for forecasting industrial water demand. The framework developed in this study is capable of forecasting industrial water demand in a holistic way and, therefore, can be a valuable tool to set targets in industrial water management (Wang et al. 2017b). Industrialization is growing rapidly particularly in developing countries. Rapid industrialization has contributed to achieving high growth in GDP. Industrial water demand has also increased sharply due to rapid industrial development, which eventually has made water resources scarcer in many developing regions. According to IFPRI (2012), approximately


45% of the global GDP will be exposed to severe water scarcity by 2050 if proper adaptation measures are not taken. In order to achieve sustainability in water management, focus on water demand-side management alone with supply augmentation has been urged all over the world. However, the selection of appropriate water management strategy largely depends on possible future changes in water demand. Water demand modeling is a very important tool in this regard. The framework developed in this study can be used for reliable forecasting industrial water demand, which in turn can help in the selection of an appropriate water management strategy for adaptation to global environmental changes in rapidly industrializing catchments.

5 Conclusion A framework has been developed and applied to forecast industrial water demand due to climate change, industrial development, technological advances, and water-saving measures. Different climate change scenarios projected by seven GCMs and the future water demand per 104 Yuan of industrial value added projected by considering economic development and water-saving technological advances were used together to forecast the possible changes in industrial water demand in different sub-basins of Huaihe River in 2020 and 2030. Results revealed that though the water demand per 104 Yuan of industrial value added will decrease continuously due to technological advances and water-saving measures, total industrial water demand will increase in all sub-basins of Huaihe River mainly due to climate change-induced rise in temperature. Among the subbasins, the highest increase is projected in MH sub-basin. The GCM BCC-CSM1-1 estimated the highest (179.16 × 108 m3) and GISS-E2-R the lowest increase in industrial water demand (132.4 × 108 m3) in Huaihe River basin in 2020. On the other hand, the GCM BNU-ESM projected the highest (190.57 × 108 m3) and CNRM-CM5 projected the lowest (160.41 × 108 m3) increase in industrial water demand in 2030. High variation in projection by different GCMs indicates high uncertainty in projected changes in industrial water demand in Huaihe River basin. The present study proposed a simple but effective framework for projection of industrial water demand in a holistic way using readily available data. However, some issues are required to consider for further study in this regard: (1) the impacts of climatic factors on water demand in different types of industries are required to assess in order to understand the mechanism of climate change impact on industrial water demand. (2) The model developed in this study only considered average temperature as the climatic factor. Other climatic variables, namely maximum and minimum temperature and humidity. are required to consider for development of a more reliable model. (3) It is also required to quantify the uncertainty in projected industrial water demand. Furthermore, more attention should be paid to industrial water demand management to mitigate water stress due to increase in industrial water demand. The framework tested in this study can be used for forecasting of industrial water demand and inform global adaptation strategies considered by water resource managers worldwide. Acknowledgements We are grateful to the National Natural Science Foundation of China (No. 51309155, 41330854), Strategic Consulting Projects of Chinese Academy of Engineering (NO: 2016-ZD-08-05-02), China water resource fee funded project (No. 126302001000150001), National Basic Research Program of China (No. 2010CB951104 and 2010CB951103), Open Research Fund of State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin China Institute of Water Resources and Hydropower Research)

Mitig Adapt Strateg Glob Change (NO: IWHR-SKL-201515) and the Special Fund of State Key Laboratory of China (No. Y515023 and Y513004) for providing financial support for this research. We are also thankful to anonymous reviewers and editors for their helpful comments and suggestions.

References Arnell N, Lloyd-Hughes B (2013) The global-scale impacts of climate change on water resources and flooding under new climate and socio-economic scenarios. Clim Chang. doi:10.1007/s10584-013-0948-4 Averyt K, Fisher J, Huber-Lee A, Lewis A, Macknick J, Madden N, Rogers J, Tellinghuisen S (2011) Freshwater use by U.S. power plants: electricity’s thirst for a precious resource. A report of the Energy and Water in a Warming World initiative. Union of Concerned Scientists, Cambridge, MA Butler D, Memon FA (2006) Water Demand Management. London: IWA Publishing. Deng X, Guneralp B, Zhan J, Su H (2014) Land use impacts on climate. Springer, London Downing TE, Butterfield RE, Edmonds B (2003) Climate change and the demand for water, research report, Stockholm Environment Institute Oxford Office, Oxford, 2003. FICCI (Federation of Indian Chambers of Commerce & Industry) (2011) Water use in Indian industry survey, September 2011. Water mission: New Delhi Förster H, Lilliestam J (2010) Modeling thermoelectric power generation in view of climate change. Reg Environ Chang 10(4):327–338 Frederick KD (1997) Adapting to climate impacts on the supply and demand for water. Clim Chang 37(1):141–156 Global Water Partnership (2015) China’s water resources management challenge: The ‘three red lines’. Technical Focus Paper. Elanders: Sweden Hammond D, Pryce AR (2007) Science report: climate change impacts and water temperature. Report No. SC060017/SR, Environment Agency: Bristol (UK) Horie S, Daigo I, Matsuno Y (2011) Comparison of water footprint for industrial P roducts in Japan, China, and USA. Towards Life Cycle Sustainability Management:154–160 HRCC (Huaihe River Conservancy Commission) (1998-2012) Huaihe River water resources bulletin. Huaihe River Conservancy Commission, Bengbu. IFPRI (International Food Policy Research Institute) (2012) 2012 Global Hunger Index, chapter 3: sustainable food security under land, water, and energy stresses. International Food Policy Research Institute, Washington, DC Jampanil D, Suttinon P, Seigo N, Koontanakulvong S (2012) Application of input-output table for future water resources management under policy and climate change in Thailand: rayong province case study. Change 27:29 Jessberger C, Sindram M, Zimmer M (2011) Global warming induced water-cycle changes and industrial production—a scenario analysis for the upper Danube River basin. J Econ Stat 231(3):415–439 Jia SF, Yang H, Zhang SF (2006) Industrial water use Kuznets curve: evidence from industrialized countries and implications for developing countries. J Water Resour Plan Manag 132(3):183–191 Khan I, Chowdhury H, Alam F, Alam Q, Afrin S (2012) An investigation into the potential impacts of climate change on power generation in Bangladesh. J Sustain Energy E 3:103–110 Kim SJ, Kim BS, Jun H (2014). Assessment of future water resources and water scarcity considering the factors of climate change and social–environmental change in Han River basin, Korea. Stoch Environ Res Risk Assess DOI: 10.1007/s00477-014-0924-1 Koch H, Vögele S (2009) Dynamic modelling of water demand, water availability and adaptation strategies for power plants to global change. Ecol Econ 68(7):2031–2039 Lai WL (2013) Mineral resources development Huaihe River Basin Ecological and Environmental Change Research new road to industrialization (Chinese Edition). Economic Management: Beijing Li J, Ma XC (2014) Econometric analysis of industrial water use efficiency in China. Environ Dev Sustain. doi:10.1007/s10668-014-9601-2 Linrterud K, Mideksa TK, Eskeland GS (2011) The impact of climate change on nuclear power supply. Energy J 32(0):1 Liu J, Zanga C, Tian S, Liu J, Yang H, Jia S, You L, Liu B, Zhang M (2013) Water conservancy projects in China: achievements, challenges and way forward. Glob Environ Chang 23(3):633–643 Luoto TP, Nevalainen L (2013) Long-term water temperature reconstructions from mountain lakes with different catchment and morphometric features. Scientific Reports 3, Article number: 2488 (2013), doi:10.1038/srep02488 Mote P. (ed.) et al, (1999) Impacts of Climate Variability and Change: Pacific Northwest, Regional Report for the PNW to the National Assessment of the Impacts of Climate Variability and Change, JISAO Climate Impacts Group, University of Washington, Nov. MWR (Ministry of Water Resources) (2015) Water management: use the most stringent system tighten faucet. Ministry of Water Resources (MWR), China. http://english.ahshunyu.com/Article.Asp?pid=156&id=380

Mitig Adapt Strateg Glob Change OECD (2012) The OECD environmental outlook to 2050: the consequences of inaction. OECD and the PBL Netherlands Environmental Assessment Agency, Amsterdam Pahl-Wostl C (2007) Transitions towards adaptive management of water facing climate and global change. Water Resour Manag 21(1):49–62 Pahl-Wostl C, Bhaduri A, Gupta J (2016) Handbook on water security. Edward Elgar: Amsterdam Protopapas AL, Katchamart S, Platonova A (2000) Weather effects on daily water use in New York City. J Hydrol Eng 5(3):332–338 Reynaud A (2003) An econometric estimation of industrial water demand in France. Environ Resour Econ 25: 213–232 Rübbelke D, Vögele S (2011) Impacts of climate change on European critical infrastructures: the case of the power sector. Environ Sci Pol 14(1):53–63 Sajil Kumar PJ, Davis Delson P, Vernon JG, James EJ (2013) A linear regression model (LRM) for groundwater chemistry in and around the Vaniyambadi industrial area, Tamil Nadu. India Chin J Geochem 32:019–026 Tarnacki, K. (2013). Evaluating industrial water saving and water management options in order to mitigate water stress. Mainz, G. Thomson AM, Calvin K, Smith SJ, Kyle GP, Volke A, Patel P, Delgado-Arias S, Bond_Lamberty B, Wise MA, Clarke LE, Edmonds JA D (2011) RCP4.5: a pathway for stabilization of radiative forcing by 2100. Clim Chang 109:77–94. UNESCO (2014) The United Nations World Water Development Report 2014: Water and Energy. Paris, UNESCO United Nations (2006) Good practices on strategic planning and management of water resources in Asia and the Pacific. Water Resources Series No. 85. United Nationa Publication: Thailand Wada Y, Wisser D, Bierkens MFP (2014) Global modeling of withdrawal, allocation and consumptive use of surface water and groundwater resources. Earth System Dynamics 5(1):15 Wang H (2011) The key technical support for implementing the most strict water resources management system. China Water Resources 6:28–30 (in Chinese) Wang X-J, Zhang J-Y, Gao J, Shahid S, Xia X-H, Geng Z, Tang L (2017b) The new concept of water resources management in China: ensuring water security in changing environment. Environment,Development and Sustainability,1–13, doi: 10.1007/s10668-017-9918-8. Wang XJ, Zhang JY, Shahid S, Guan ES, Wu YX, Gao J, He RM (2016a) Adaptation to climate change impacts on water demand. Mitig Adapt Strateg Glob Chang 21(1):81–99 Wang XJ, Zhang JY, Shahid S, Guan ES, Wu YX, Gao J, He RM (2016b) Impact of climate change on regional irrigation water demand in Baojixia irrigation district of China. Mitig Adapt Strateg Glob Chang 21(2):233–247 Wang X-J, Zhang J-Y, Shahid S, He R-M, Xia X-H, Mou X-L (2015a) Potential impact of climate change on future water demand in Yulin city, Northwest China. Mitig Adapt Strateg Glob Chang 20(1):1–19. doi:10.1007/s11027-013-9476-9 Wang X-J, Zhang J-Y, Shahid S, Oyang R-L, Guan T-S, Xue J-G, Zhang X (2016c) Impacts of climate variability and changes on domestic water use in the Yellow River Basin of China. Mitig Adapt Strateg Glob Chang:1– 14. doi:10.1007/s11027-015-9689-1 Wang X-J, Zhang J-Y, Shahid S, Xie W,Du C-Y,Shang X-C,Zhang X (2017a),Modeling domestic water demand in Huaihe River Basin of China under climate change and population dynamics. Environment,Development and Sustainability,1–14, doi: 10.1007/s10668-017-9919-7. Wang X-J, Zhang J-Y, Yang Z-F, Shahid S, He R-M, Xia X-H, Liu H-W (2015b) Historic water consumptions and future management strategies for Haihe River basin of Northern China. Mitig Adapt Strateg Glob Chang 20(3):371–387 Water Resources Group (2009) Charting our water future: economic frameworks to inform decision-making. The 2030 Water Resources Group. (The Barilla Group, The Coca-Cola Company, The International Finance Corporation, McKinsey & Company, Nestlé S.A., New Holland Agriculture, SABMiller plc, Standard Chartered Bank, and Syngenta AG.) WWAP (World Water Assessment Programme) (2012) The United Nations World Water Development Report 4: Managing Water under Uncertainty and Risk. Paris, UNESCO. Zachariadis T (2010) Forecast of electricity consumption in Cyprus up to the year 2030: the potential impact of climate change. Energy Policy 38(2):744–750