Assessing water resources carrying capacity based on integrated system dynamics modeling in a semiarid river basin of northern China

Transcription

1 1057 IWA Publishing 2014 Water Science & Technology: Water Supply Assessing water resources carrying capacity based on integrated system dynamics modeling in a semiarid river basin of northern China Ying Xie, Xuyong Li, Chunsheng Yang and Yang Yu ABSTRACT Water shortage is a major problem in northern China, because of a huge population and rapid economic growth. Taking the Luanhe River Basin (LRB) as a study area, we set up a System Dynamics (SD) model of the basin for the period , and considered various important socioeconomic and environmental factors and their correlation. Significant trends for the period were simulated and the water resource carrying capacity (WRCC) of the LRB and its trends over the next 30 years were analyzed. The results indicate a decreasing trend of WRCC in the basin and that current economic growth is not sustainable. The study investigated possible optimized allocation projects. The most apt project would involve a combination of strategies that could considerably increase the WRCC, reduce demand, and improve water quality. Key words Luanhe river basin, sustaining utilization, system dynamics model, water resource carrying capacity Ying Xie Department of Water Environment, Institute of Water Resources and Hydropower Research, Beijing, China Ying Xie Xuyong Li (corresponding author) State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, China xyli@rcees.ac.cn Chunsheng Yang Harbin Bureau of Hydrology, Harbin, China Yang Yu Department of Water Environment, Institute of Water Resources and Hydropower Research, Beijing, China and State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, Institute of Water Resources and China Hydropower Research, Beijing, China INTRODUCTION Water is an indispensable and fundamental resource for the protection of ecological environments, national or regional socioeconomic development, and a regional strategic resource for economic sustainable development (Shi & Qu 1992; Feng et al. 2000). With population growth and economic development, water scarcity is increasingly becoming a crisis that constrains regional sustainable development. It is very important to achieve sustainable harmony between economic development, residential living and the water environment (Zhu et al. 2010; Huang et al. 2012). Scientific knowledge of water resource carrying capacity (WRCC) is a foundation for sustainable development and water security strategy. Combined with characteristics of water resources and previous research results of WRCC, we propose a definition of WRCC in this paper. We use foreseeable development levels of technology, economy and society as a basis, sustainable social development and utilization of water resources as a principle, protection of a healthy ecological environment as a condition, and reasonable development and deployment of water resources as a precondition. We thereby obtain a degree of support for coordinated development of the social, economic and ecological environment in a given area on various time scales in the future. It is said that WRCC is the maximum bearing capacity of water resources for human activity at a certain stage of socioeconomic development or living standard in a favorable ecological system. doi: /ws

2 1058 Y. Xie et al. Assessing water resources carrying capacity in semi-arid basin Water Science & Technology: Water Supply The answers to several important questions about the exact population level that can be supported by water resources, whether sustainable development of a social economy can be successfully achieved, and whether a favorable ecological system can be smoothly realized, depend exclusively upon policy parameters such as economic policy, development speed and strategic policy (Gilmour et al. 2005; Ward 2009; Bassi et al. 2010). The choice of these parameters is a difficult problem, which can be effectively solved through a mathematical method derived from system dynamics (SD) (Motohashi & Nishi 1991; Feng et al. 2009). SD is a method used to study complex systems that is based on the theory of feedback control, and is processed by means of computer simulation. This approach can be effective in resolving relationships between these systems. In association with rapid growth of the economy in recent years, river water quality has been seriously degraded and pollution within most rivers of northern China now exceeds national drinking water quality standards. Problems in the Luanhe River Basin (LRB) are strongly representative of those of semiarid northern China. These problems include a shortage of water resources, surface water strongly affected by artificial regulation, unsustainable industrial development and structure, and delay in implementation of water environmental measures and means. Therefore, results of in-depth research on the WRCC of the LRB have high priority for semiarid river basins in northern China. In this paper, a SD model (Vensim) is used to simulate future trends of the WRCC in LRB, in order to resolve the best solution for optimizing the WRCC. The objectives were to: (1) develop a model based on dynamic balance between socioeconomic development and the WRCC; (2) predict the WRCC under different development policies; and (3) put forward the amount of pollutant reduction in terms of chemical oxygen demand (COD) for each planning year. METHODS elevation range m (average 766 m). The Luan River is 888 km long with drainage area 44,070 km 2, of which 98% is mountainous (Figure 1). The watershed receives an average precipitation of 560 mm/a, mostly during summer (70 80%) and especially during July and August. Average runoff is m 3 /a (Li & Feng 2007). Results of in-depth research on the WRCC of the LRB provide a meaningful reference for northern river basins of China. Over recent years, the economy in the basin has developed considerably. The gross domestic product (GDP) grew by a factor of three from 2000 to 2010, and population increased nearly one million over that period. Industrial water consumption increased from 570 million m 3 during 2000 to 740 million m 3 during Data collection It was necessary to obtain time series socioeconomic and water resource data for the LRB. Socioeconomic data such as total population, amount of livestock, GDP irrigation area, GDP in industry and tertiary industry, and agriculture output values used as a basis for model building were obtained from the Statistical Yearbook of Chengde, Xilinguole, Qinhuangdao and Tangshan. Water resource demand and supply data were obtained from the Water Resources Bulletin ( ) of the Haihe River Basin, issued by the Haihe River Water Conservancy Commission of the Ministry of Water Resources, and the Water Resources Bulletin ( ) of the four cities. Data used to calculate water environmental capacity, such as pollutant concentration and flow, were collected from the Chengde Branch of the Hebei Provincial Survey Bureau of Hydrology and Water Resources. System dynamics System structure reflects units that make up the system and interaction of the units. Any system can be expressed as (A, 2008): Study area S ¼ (E, R), The LRB in northeastern China has drainage area 33,700 km 2 and lies between 115 W W 20 0 Eand39 W W 35 0 N, with where S represents the system, E the elements, and R the relationships between the sets of elements E.

3 1059 Y. Xie et al. Assessing water resources carrying capacity in semi-arid basin Water Science & Technology: Water Supply Figure 1 Location of LRB. System structure is the order of system elements and element sets, which represents the feature of system architecture. SD takes the first-order feedback loop as the basis of the system. The feedback loop includes three parts of system status, i.e., variable rates, variable information, and a complex system composed of the interacting feedback loops. Changes of state variable in the system depend on the outcome of decisions or actions. Decisions are made mainly by constructing two situations. One is to rely on the feedback of self-regulation (Figure 2(a)). The other is not to depend on feedback Figure 2 The basic structure of system.

4 1060 Y. Xie et al. Assessing water resources carrying capacity in semi-arid basin Water Science & Technology: Water Supply information, but follow a rule of the system itself under a certain condition (Figure 2(b)). Based on integrity and hierarchy of the system, system levels of general structure are as follows: (1) determine the limits of system S; (2) divide S into several subsystems or sub-structures S i (i ¼ 1,2,,m); (3) define the base unit of the system and structure of feedback loop E j ( j ¼ 1,2,, m); and (4) determine the main state variables and rate variables of the feedback loop. Framework of WRCC study Given the role of water resources in the complex ecology environment society economy system and its relationship to other system elements, we used an input-output multicriteria scenario decision analysis model to study the WRCC of the LRB. This provides an integrated framework for WRCC study by the Vensim model. Vensim is a visualized dynamic simulation analysis tool developed by Ventana Systems, Inc. of Massachusetts, USA. Vensim is used for developing, analyzing and packaging high-quality dynamic feedback models. System architecture diagrams of the WRCC in the LRB are shown in Figure 3. There were four subsystems in the framework, i.e., society, eco-environment, economy and water resource. The water resource subsystem is a multi-purpose, multibenefit and multi-target system that involves social, economic and environmental benefits. Water supply is determined by surface water, groundwater, water diversion from outside regions, water reuse, return of irrigation water, and others. Decision variables in the water resource subsystem involve total annual water supply, total demand of water resources, proportion of water supply and demand, agricultural water consumption, domestic water consumption, water demands of industry and tertiary industry, ecological water requirement, and others. Corresponding parameters include surface water available yield, groundwater available yield, available yield of water reuse, water consumption per unit GDP in industry and tertiary industry, irrigation area, agricultural irrigation water quota, and others. Some parameters in this subsystem are closely related to the economy subsystem. Figure 3 The system architecture diagram of water resources carrying capacity in the LRB.

5 1061 Y. Xie et al. Assessing water resources carrying capacity in semi-arid basin Water Science & Technology: Water Supply The society subsystem is a complex time-varying system. It is the most active factor in the water resources system, and human initiative gives people the ability to influence system development. The society subsystem reflects changes of its own state and its intrinsic link with water demand. On the one hand, excessive population growth increases pressure on water resources and the water environment. This leads to water shortages and deterioration of the water environment, reducing the WRCC and impacting sustainable development of the economy and society. On the other hand, water shortages constrain population growth. In this way, the total population acts as an important variable in the entire system. The main parameters are natural population growth rate, urban population, rural population, urbanization, and others. The economy subsystem is the core of the WRCC system. Its behavior not only affects activities of the water resource, social, and ecological subsystems but also determines the status of the entire system. It can be said that the economy subsystem is the core of the water-environment-society system. The variables GDP, GDP in industrial, GDP in agricultural, GDP in tertiary industry, and GDP in construction are involved in the economy system. The ecological environment is the space for human survival and development, in which water is the most active factor. It is easy to perceive change of water quantity and quality, so being fully aware of the status and role of water in the ecological environment is significant in water allocation. The main variables of the eco-environment subsystem are total amount of wastewater discharge, discharge of industrial wastewater, discharge of tertiary industrial wastewater, domestic sewage discharge, and the following COD emissions: domestic, irrigation, industrial, tertiary industry, and others. Since wastewater can be reused in the construction industry, its emission is very low, so we set the discharge of construction sewage to zero. Parameters in the eco-environment subsystem include industrial wastewater treatment capacity, COD concentration of domestic sewage, COD concentration of industrial wastewater, and others. Scenarios Through rational adjustment of decision variables, five programs were designed to improve the WRCC in the LRB, namely: Scheme I: The zero program. The program was maintained at 75% of the water supply guarantee rate. Additional variable parameter values were unchanged under conditions of maintaining the status quo. Scheme II: The water conservation program. This scheme is based on Scheme I and considers raising the level of domestic water and increasing the water conservation scope of three major industries. Scheme III: Improve pollution control capability. To decrease water pollution and enhance the WRCC in the region, effective measures must be taken to gradually increase the sewage treatment rate. Scheme IV: Adjust industrial structure. The proportion of water used by agriculture is sustainable within the LRB industrial structure. Thus, this scheme proposes that internal structure of secondary and tertiary industry be organized to realize rational allocation of water resources. Scheme V: An integrated program. In this program, the water supply guarantee rate of the LRB remains at 75% of current, and comprehensive consideration of Schemes II IV was undertaken to simulate trends and improvement of the WRCC in the LRB. Calculation of water environmental capacity The water pollutant carrying capacity is based on water environmental capacity theory, and is an important consideration for water pollution control with the rapid development of society and the economy. We selected a one-dimensional model for calculating water environmental capacity, expressed as follows: W i ¼ 86:4 Q i C si exp K i L i C oi Q i 86400u i W i : Remaining water environmental capacity of reach i (kg/day), Q i : Designed flow of reach i (m 3 /s), K i : Coefficient of contaminant degradation in reach i (1/day), C si : Water quality target value of functional areas in reach i (mg/l), C 0i : Status quo water quality values of the reach above reach i (mg/l),

6 1062 Y. Xie et al. Assessing water resources carrying capacity in semi-arid basin Water Science & Technology: Water Supply u i : Average velocity in reach i (m/s), L i : Flow time of pollutants from initial to control sections (day). RESULTS AND DISCUSSION With different structures and functions in the WRCC system, the special language of SD (Vensim) was applied to describe causal relationships between the various subsystems. As indicated in Figure 3, four subsystems were integrated and the entire system was divided into six parts. These are the sections of available water resource, agricultural water, industrial water, living water, tertiary industrial water, and eco-environment. To more rigorously formulate the internal structure and relationships between system variables, the SD flow chart of the WRCC was constructed (Figure 4). Model testing After establishing the model, statistical data from were used to determine statistical regularity and input determined values of the parameters to the model. A dynamic simulation was constructed and consistency of simulation values with statistical data from the same period was tested. After the testing, errors of all variables were within 10%, with the majority within 5%. Results showed that model structure was correctly formulated and that manipulation of the parameters could represent the development trend of variables. The next step of scenario analysis and speculation was then taken. Simulation test results of demographic variables are shown in Table 1. The maximum relative error of water consumption in the LRB was 8.33% of ecological water consumption. Results of the retrospective examination showed that prediction precisions are at acceptable levels. Table 1 shows little change of total water consumption. The main reason is that 6 years had low flow, and water shortages limited economic development. GDP has not greatly improved in recent years. Therefore, water conservation and water environmental protection are essential in promoting social and economic development. Figure 4 Interface diagram of water resources carrying capacity in Vensim.

7 1063 Y. Xie et al. Assessing water resources carrying capacity in semi-arid basin Water Science & Technology: Water Supply Table 1 Retrospective examination of water consumption Total water Agricultural water Industrial water Domestic water Ecological water Years AC a RS a RE a AC RS RE AC RS RE AC RS RE AC RS RE a AC: actual consumption (10 8 m 3 ); RS: results of simulation (10 8 m 3 ); RE: relative error (%). Analysis of water demand under different schemes Under the current situation, the main reasons for the WRCC decline in the LRB were inefficient water-use patterns, extensive economic growth, and an unsustainable monetary growth rate. A low level of development and utilization of water resources wastes substantial amounts of those resources (Figure 5). Moreover, defects in pollution control and environmental protection of water resources cause serious pollution. Exceedance of water environment carrying capacity results in a heavy burden on economic and social advance in the LRB, where the water resources supply cannot meet the demand for social economic development, and water resource utilization does not represent the concept of sustainable development. Scheme II was an adjustment scheme with water savings as the foremost objective. It is seen from Figure 5 that under this scheme, the WRCC level in the LRB is greatly enhanced compared with Scheme I. Water supply and demand under the two programs is considerably different. The ratio of water supply and demand under Scheme II is greatly improved, with average increase of 20%. Under Scheme IV, the growth rate of secondary industry has been significantly reduced compared with Scheme I, and water use shows a corresponding reduction. The GDP growth rate of tertiary industry increases, the proportion of industrial GDP steadily rises, and there is corresponding protection of water to ensure industrial development in the national economy. Thus, this program reduces water demand and correspondingly increases the ratio of water supply and demand to a certain extent, although the effect is not very obvious. Scheme V was based on Scheme I and comprehensively considers Schemes II IV. That is, it takes water conservation, pollution control and industrial structure adjustment into account. In this scheme, industrial output growth slows and the tertiary industrial output growth rate improves. The balance of water resource supply and demand also improved during the simulation period. Finally, water demand per unit industrial output value and the irrigation quota were reduced. Analysis of pollutant emissions under different schemes Scheme III was an adjustment scheme for pollution regulation. The principal method was through improvement of domestic and industrial sewage treatment rates to reduce water pollution load. Simulation results are shown in Figure 6. Pollutant (COD) emissions have generally seen a reduction, with the WRCC having an average increase of 10% compared with Scheme I. Thus, increase of overall pollution treatment levels can improve the WRCC, but the effect was not obvious. In Scheme IV, owing to the adjustment of industrial structure, water demand was reduced relative to Scheme I, and pollutant (COD) emissions also decreased somewhat. Under Scheme V, the WRCC in the LRB was greater than under any previous schemes, increasing by 30% on average, and the treatment rate of domestic sewage was greatly enhanced. Taking coordinated social, economic, and environmental development in the LRB

8 1064 Y. Xie et al. Assessing water resources carrying capacity in semi-arid basin Water Science & Technology: Water Supply Figure 5 Water supply and demand under different schemes. into account, Scheme V proved to be the most advanced program. Satisfaction of water environmental capacity under different schemes According to requirements of Haihe River basin water function zoning, water quality of the LRB should match the Class III standard in the environmental quality standards for surface water (GB ). In that standard, the controlled concentration of COD is 20 mg/l. Taking technology advances into account, requirements of water quality will increase. Therefore, we assumed that this quality in the LRB should match the Class II standard, in which the controlled COD concentration is 15 mg/l. Figure 6 shows that, except for Scheme V, water environmental capacity cannot satisfy the requirements of pollutant emissions by 2019 via the other four scenarios.

9 1065 Y. Xie et al. Assessing water resources carrying capacity in semi-arid basin Water Science & Technology: Water Supply Figure 6 Pollutants emissions in various schemes and water environmental capacity. CONCLUSIONS In this paper, SD theory was used as a framework, and the SD model of WRCC was built based on relevant theories of water resources, system analysis, and the socioeconomy. Rationality and maneuverability of this approach were tested by its application to the WRCC within the LRB. According to the LRB developmental pattern of water resources, water environment, population and socioeconomy, the SD model of WRCC in the basin was established based on Vensim software, and supply and demand balance of water resources was established as the primary objective. The results of model testing indicated that the model structure and behavior were coextensive with practice. The SD model of WRCC was applied to simulate the WRCC under contemporary development patterns of water resources, water environment, population, society and economy from 2011 to Five contrasting scenarios were designed, and implementation results of each scheme were simulated. This simulation showed that the optimal development program was Scheme V. This solution was to take water conservation, pollution control and adjustment of the industrialized structure as its primary objective. Therefore, compared with the status quo, the level of WRCC of the LRB under Scheme V is greatly improved. In addition, through calculating the water environmental capacity, that scheme was found to satisfy the requirements of pollutant emission. ACKNOWLEDGEMENTS This work was supported by the RCEES One-Three-Five project (fund number YSW2013B02-4), the Major Science and Technology Program for Water Pollution Control and Treatment in China (fund number 2014ZX , 2013ZX ), and the Commonweal Projects Specific for Scientific Research of the Ministry of Water Conservancy of China (Grant No ). REFERENCES Bassi, A. M., Tan, Z. & Goss, S An integrated assessment of investment towards global water sustainability. Water 2 (4), Feng, D., Cheng, G. D. & Masao, M. K Trends of water resource development and utilization in arid north-west China. Environ. Geol. 39 (8), Feng, L. H., Zhang, X. & Luo, G Research on the risk of water shortages and the carrying capacity of water

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