To achieve sustainable utilization of urban water resources and sustainable social and economic development and to relieve the supply–demand pressure related to water resources in Jiamusi, a simulation model based on system dynamics theory is established to identify the feedback mechanism and the causal relationship among the factors affecting the sustainable utilization of water resources. The conditions regarding the utilization of water resources in Jiamusi in 2010 are taken as the benchmark for the model, and the supply–demand structure of urban water resources and the geographical characteristics of the region are used as the basis for its establishment. The model is divided into five subsystems described by 64 variables to simulate the supply–demand structure of the water resources in the region, as well as both the individual supply and demand structures, and thus to obtain the supply–demand conditions and the trends of variation in water resources in the short, medium and long terms. The results show that seriously unbalanced supply–demand conditions for water resources will prevail in Jiamusi in the future. By 2030, the supply–demand ratio will be only 0.5987; the level of development and utilization of surface water resources and transit water resources will be relatively low, and the groundwater resources will still be suffering excessive exploitation; the industrial water demand will be greatly increased, and agricultural development will be restricted. With a focus on the problems that may arise in the utilization of water resources at present and in the future, a proposal regarding the realization of the sustainable utilization of water resources and sustainable social and economic development in Jiamusi is presented. The outcomes of this research have important theoretical and practical significance for providing guidance regarding the scientific and reasonable utilization of water resources in Jiamusi.

INTRODUCTION

Water is an important strategic natural resource that people require for survival and development. It is the basic element constituting our environment and an important material basis for maintaining social progress and human civilization. The sustainable utilization of water resources is the basic necessity for supporting sustainable social and economic development and the health of the ecological environment (Wei et al. 2012). In recent years, with the acceleration of the industrialization process and rapid economic development, problems concerning the unreasonable development and utilization of natural resources have become increasingly obvious, leading to environmental pollution, damage to ecological balance and several unexpected disasters posing danger to humans (Yang 2005). The water demand–supply conflict has become the bottleneck that is seriously restricting the sustainable development of the national economy in China, a significant strategic problem that exerts an impact on national security (Kang et al. 2004). The effective management and planning of water resources exerts a relatively large influence on the sustainable utilization of water resources as an important and integral part of the regional economy and sustainable environmental development (van Leeuwen 2013). Therefore, effective planning for the development and utilization of regional water resources and the realization of their sustainable utilization is of great significance for sustainable regional social and economic development and the establishment of a virtuous circle to support the ecological environment.

Studies on the sustainable utilization of urban water resources have been conducted for many years at home and abroad, and some practical problems related to this issue have been resolved. However, most studies focus on specific aspects of the use of water resources, such as urban water supplies (Hamid et al. 2013), the water conservation field (He et al. 2012), recycled water (Stephen et al. 2013), and the economics of water resources (Fu et al. 2010), and address only local and specialized problems concerning the sustainable utilization of water resources. Studies addressing the overall background of the complex system of the urban social, economic and ecological environment remain in the exploratory stage, and the relevant theories and methods for application require further development (Song et al. 2004). Based on the principle of achieving the harmonious development of society, the economy, the population, the available resources and the environment, various countries have begun to examine and solve problems regarding sustainable development in a systematic manner.

To achieve the sustainable utilization of urban water resources, support sustainable social and economic development, and alleviate the supply–demand pressure on water resources, this article adopts sustainable development as the guiding ideology and system dynamics (SD) as the theoretical basis for dynamic simulation of the present conditions and future trends of water resource utilization in Jiamusi, with the intent of providing a reference and recommendations for the realization of the sustainable utilization of water resources.

STUDY AREA AND METHODOLOGY

Study area

Situated in the northeastern region of Heilongjiang Province (129°30′–135°5′30″ E, 45°56″–48°27′55″ N) and the hinterlands of Sanjiang Plain, where the Songhua River, the Amur River and the Wusuli River intersect (see Figure 1), Jiamusi is the major political, economic and cultural center and the major grain-producing region in Heilongjiang Province. Its area is 32,704 km2, and it extends 340 km from north to south and 190 km from east to west. The average annual precipitation is 563.9 mm, the average annual evaporation capacity is 719.8 mm (Model E601), and the average annual total water resources amount to 5.239 × 1010 m3, of which the average annual surface water resources account for 3.125 × 1010 m3, and the average annual groundwater resources account for 3.307 × 1010 m3. (Li 2012). At present, a low utilization rate of surface water resources, severely excessive exploitation of groundwater resources, wastage of water resources and serious pollution of water resources have become important factors hindering the sustainable utilization of water resources in Jiamusi (Dong & Song 2007; Sun et al. 2012).
Figure 1

The location of the study area.

Figure 1

The location of the study area.

Research method

The concept of SD was presented by Professor Forrester of the Massachusetts Institute of Technology in 1956. It is a scientific approach in which systems science theory is closely integrated with computer simulation to study the structure and behavior of information feedback in a system, and it is an important branch of systems science and management science, as well as a transverse discipline linking the fields of natural science and social science (Forrester & Karnopp 1971; Forrester 1987). Since the 1980s, SD has gradually become the effective tool for modern scientific decision-making and prediction. Moreover, it has also been widely applied in relevant studies of water resources: He et al. (2010) used the SD method to simulate the conflict between the supply of and demand for water resources in different water conservation modes in Tianjin from 2005 to 2030; Zhu & Chai (2010) established an SD model of the environmental carrying capacity of a city depending on the problems present in the city's water environment and presented a scheme for simulating the water environment under nine protective measures; Maryam et al. (2013) used SD to perform a dynamic analysis of a hydrological system at the perimeter of the basin; Hassanzadeh et al. (2012) used the SD method to identify the major factors leading to the decline of the water level of Lake Urmia; Bagheri et al. (2010) used an SD model to evaluate the urban water supply system of Bam after an earthquake disaster and analyze the water resource management system.

Data source

To establish an SD model for the sustainable utilization of water resources in Jiamusi, the administrative boundary of Jiamusi is taken as the boundary of the system space, which includes four districts, two county-level cities, four counties and 17 state-owned farms. The considered time period is from 2000 to 2030. Historical statistical data are used for the years from 2000 to 2010, and the years from 2011 to 2030 are treated as the subject of simulation-based prediction, within this period, the short-term planning level corresponds to the years from 2010 to 2015, the medium-term planning level corresponds to the years from 2016 to 2020, and the long-term planning level corresponds to the years from 2021 to 2030. To reduce the error introduced by the discretization of time, a time step of one year is chosen for the model simulation. The modeling data are drawn from the Statistical Yearbook of Heilongjiang Province (Heilongjiang Province Statistical Bureau 2000–2011), Economic Statistical Yearbook of Jiamusi (Jiamusi Municipal Statistical Bureau 2000–2011) and Local Standard Water Consumption Quota in Heilongjiang Province (Heilongjiang Quality and Technology Supervision Bureau 2009). Of the data used in model equations, historical data are used from 2000 to 2010, whereas an extrapolation from the present level of 2010 is used from 2011 to 2030.

SD MODEL FOR THE SUSTAINABLE UTILIZATION OF WATER RESOURCES

Causal relationship analysis of the model

Causal dendrograms contribute to a clear understanding of the reasons for variations in variables in the causal feedback relationship of a system and the results of such variations (Jiang 2011; Cai 2013). The ratio between the supply of and demand for water resources is the major variable in a system for the sustainable utilization of water resources. Therefore, the causal dendrograms for the supply–demand ratio of water resources (see Figures 2 and 3) are a convenient means of understanding the relations among major variables in the water resource utilization system of the study area.
Figure 2

Cause dendrogram for the supply–demand ratio of water resources.

Figure 2

Cause dendrogram for the supply–demand ratio of water resources.

Figure 3

Result dendrogram for the supply–demand ratio of water resources.

Figure 3

Result dendrogram for the supply–demand ratio of water resources.

Figures 2 and 3 show that the supply–demand ratio is determined by both water supply and water demand and that its magnitude directly impacts the output value of tertiary industry, the total industrial output value and the effective area of irrigation farmlands.

Establishment of the SD model

In accordance with the structure of the water resource system and the purpose of the model (Hoekema & Sridhar 2013), the system is divided into five subsystems (see Figure 4). Among them, the water resource supply–demand subsystem is an important and integral part of the SD model for the sustainable utilization of water resources. This subsystem organically combines the social, agricultural, industrial and ecological water demand subsystems to constitute a complete water resource utilization system (Jiang 2011).
Figure 4

System structure diagram for the water resource system.

Figure 4

System structure diagram for the water resource system.

Based on a complete understanding of the present situation regarding water resource utilization in Jiamusi and in accordance with SD principles, the feedback relationship among the various variables in the system is analyzed. In combination with a great amount of historical statistical data, the SD software Vensim (Abadi et al. 2015) was utilized to establish the flowchart of the SD model for the sustainable utilization of water resources in Jiamusi (see Figure 5).
Figure 5

SD model for the sustainable utilization of water resources in Jiamusi.

Figure 5

SD model for the sustainable utilization of water resources in Jiamusi.

The model for the sustainable utilization of water resources in Jiamusi contains 64 variables, including four state variables, five velocity variables, 44 auxiliary variables and 11 constants. The major variables and equations of the established model are presented in Table 1, in which L stands for state variable; A, an auxiliary variable; C, a constant; and T, a table function.

Table 1

Major variables and equations of the SD model for the sustainable utilization of water resources in Jiamusi

Name of variable Unit Type of variable Type of variable 
Annual supply–demand ratio of water resources Dmnl Annual supply of water resources/Annual demand for water resources 
Annual supply of water resources 104 m3 Groundwater supply + Surface water supply + Repetitive used water in industry + Sewage handling capacity + Water supply from water transit project 
Groundwater supply 104 m3 Level of development and utilization of groundwater * Quantity of groundwater resources 
Level of development and utilization of groundwater Table(time) 
Quantity of groundwater resources 104 m3 Constant 
Surface water supply 104 m3 Level of development and utilization of surface water * Quantity of surface water resources 
Level of development and utilization of surface water Table(time) 
Quantity of surface water resources 104 m3 Constant 
Repetitive used water in industry 104 m3 Industrial water demand * Repetitive utilization rate of industrial water 
Repetitive utilization rate of industrial water Table(time) 
Sewage handling capacity 104 m3 (Urban domestic sewage discharge + Industrial sewage discharge) * Sewage disposal rate 
Sewage disposal rate Table(time) 
Water supply from water transit project 104 m3 Table(time) 
Annual demand for water resources 104 m3 Agricultural water demand + Industrial water demand + Domestic water demand + Ecological water demand 
Agricultural water demand 104 m3 Water consumption for irrigation/Utilization coefficient of irrigation water + Water demand of the fishery industry + Water demand of animals 
Utilization coefficient of irrigation water Table(time) 
Water consumption for irrigation 104 m3 Water consumption quota for irrigation * Effective area of irrigated farmlands 
Water demand of the fishery industry 104 m3 Water consumption quota for fishery industry * Fishpond area 
Water demand of animals 104 m3 Water consumption quota for large animals * Number of large animals bred + Water consumption quota for small animals * Number of small animals bred 
Industrial water demand 104 m3 Industrial water consumption quota * Total industrial output value/10,000 
Industrial water consumption quota 104 m3/104 yuan Table(time) 
Total industrial output value 104 yuan Constant 
Ecological water demand 104 m3 Water demand of urban environments + Water for replenishment of wetlands 
Water demand of urban environment 104 m3 Water consumption quota for green land * Urban green area 
Water replenishment amount of wetland 104 m3 Water consumption quota for wetland * Wetland area 
Domestic water demand 104 m3 Rural domestic water demand + Urban domestic water demand 
Rural domestic water demand 104 m3 Domestic water consumption quota for rural residents * Rural population 
Urban domestic water demand 104 m3 Urban population * Domestic water consumption quota for urban residents + Water consumption of urban public facilities 
Total population 104 Constant + Population increment – Population decrement 
GDP 104 yuan Output value of primary industry + Total industrial output value + Output value of tertiary industry 
Name of variable Unit Type of variable Type of variable 
Annual supply–demand ratio of water resources Dmnl Annual supply of water resources/Annual demand for water resources 
Annual supply of water resources 104 m3 Groundwater supply + Surface water supply + Repetitive used water in industry + Sewage handling capacity + Water supply from water transit project 
Groundwater supply 104 m3 Level of development and utilization of groundwater * Quantity of groundwater resources 
Level of development and utilization of groundwater Table(time) 
Quantity of groundwater resources 104 m3 Constant 
Surface water supply 104 m3 Level of development and utilization of surface water * Quantity of surface water resources 
Level of development and utilization of surface water Table(time) 
Quantity of surface water resources 104 m3 Constant 
Repetitive used water in industry 104 m3 Industrial water demand * Repetitive utilization rate of industrial water 
Repetitive utilization rate of industrial water Table(time) 
Sewage handling capacity 104 m3 (Urban domestic sewage discharge + Industrial sewage discharge) * Sewage disposal rate 
Sewage disposal rate Table(time) 
Water supply from water transit project 104 m3 Table(time) 
Annual demand for water resources 104 m3 Agricultural water demand + Industrial water demand + Domestic water demand + Ecological water demand 
Agricultural water demand 104 m3 Water consumption for irrigation/Utilization coefficient of irrigation water + Water demand of the fishery industry + Water demand of animals 
Utilization coefficient of irrigation water Table(time) 
Water consumption for irrigation 104 m3 Water consumption quota for irrigation * Effective area of irrigated farmlands 
Water demand of the fishery industry 104 m3 Water consumption quota for fishery industry * Fishpond area 
Water demand of animals 104 m3 Water consumption quota for large animals * Number of large animals bred + Water consumption quota for small animals * Number of small animals bred 
Industrial water demand 104 m3 Industrial water consumption quota * Total industrial output value/10,000 
Industrial water consumption quota 104 m3/104 yuan Table(time) 
Total industrial output value 104 yuan Constant 
Ecological water demand 104 m3 Water demand of urban environments + Water for replenishment of wetlands 
Water demand of urban environment 104 m3 Water consumption quota for green land * Urban green area 
Water replenishment amount of wetland 104 m3 Water consumption quota for wetland * Wetland area 
Domestic water demand 104 m3 Rural domestic water demand + Urban domestic water demand 
Rural domestic water demand 104 m3 Domestic water consumption quota for rural residents * Rural population 
Urban domestic water demand 104 m3 Urban population * Domestic water consumption quota for urban residents + Water consumption of urban public facilities 
Total population 104 Constant + Population increment – Population decrement 
GDP 104 yuan Output value of primary industry + Total industrial output value + Output value of tertiary industry 

Evaluation of the effectiveness of the model

An evaluation of the effectiveness of the model is a necessary step before a simulation model can be applied. The purpose is to verify the agreement between the established model and the real system and to assess the accuracy and reliability of the model simulation (Sun 2005).

The start time of the SD model established in this study is the year 2000 and the historical statistical data from 2000 to 2010 were taken as the basis for its evaluation; in the evaluation the year 2005 was treated as the base year, and the period of 2006–2010 was treated as the year for prediction. Because of the relative complexity of the model, the large number of variables and the spatial limitations of the paper, the evaluation results based on the historical data are presented for only four representative variables (see Table 2).

Table 2

Evaluation results for four model variables

  2006 2007 2008 2009 2010 
Total population Recorded value 104 246.3 248.2 250.5 252.4 252.7 
Simulation value 104 246.915 248.609 250.308 251.874 253.307 
Error −0.25 −0.16 0.76 0.21 −0.24 
Increase in industrial output value Recorded value 104 yuan 118.1 132.9 170.6 204.2 279.9 
Simulation value 104 yuan 117.678 138.202 170.161 205.55 268.87 
Error 0.36 −3.99 0.59 −0.66 3.94 
Effective area of irrigated farmlands Recorded value 104 hm2 51.42 61.56 64.57 72.02 79.82 
Simulation value 104 hm2 49.789 56.877 64.396 71.448 77.213 
Error 3.17 7.61 0.28 0.79 3.27 
Urban green area Recorded value 104 hm2 0.226 0.230 0.241 0.249 0.257 
Simulation value 104 hm2 0.230 0.235 0.242 0.247 0.253 
Error −1.77 −2.17 −0.42 0.81 1.56 
  2006 2007 2008 2009 2010 
Total population Recorded value 104 246.3 248.2 250.5 252.4 252.7 
Simulation value 104 246.915 248.609 250.308 251.874 253.307 
Error −0.25 −0.16 0.76 0.21 −0.24 
Increase in industrial output value Recorded value 104 yuan 118.1 132.9 170.6 204.2 279.9 
Simulation value 104 yuan 117.678 138.202 170.161 205.55 268.87 
Error 0.36 −3.99 0.59 −0.66 3.94 
Effective area of irrigated farmlands Recorded value 104 hm2 51.42 61.56 64.57 72.02 79.82 
Simulation value 104 hm2 49.789 56.877 64.396 71.448 77.213 
Error 3.17 7.61 0.28 0.79 3.27 
Urban green area Recorded value 104 hm2 0.226 0.230 0.241 0.249 0.257 
Simulation value 104 hm2 0.230 0.235 0.242 0.247 0.253 
Error −1.77 −2.17 −0.42 0.81 1.56 

Among the variables selected for the evaluation of the model's effectiveness, the total population, the increase in industrial output value, the effective area of irrigated farmlands and the urban green area are all state variables and are representative of the social, industrial, agricultural and ecological water demand subsystems, respectively. The relative errors between the simulated and recorded values from 2006 to 2010 are all within ±8%. Because the relative error is below 10% (Yang et al. 2015) and thus is relatively small, the model satisfies the necessary performance requirements, that is, the SD model for the sustainable utilization of water resources offers reasonable accuracy and reliability.

SD SIMULATION RESULTS FOR THE SUSTAINABLE UTILIZATION OF WATER RESOURCES

Analysis of the simulation results regarding the supply–demand structure of water resources in the study area

As the core of the SD simulation model for the sustainable utilization of water resources, the water resource supply–demand structure not only predicts the future conditions regarding the supply of and demand for regional water resources but also provides guidance for the harmonious development of industry, agriculture, ecology and economy in the study area. Therefore, an analysis is presented of the dynamic simulation results regarding this supply–demand structure obtained based on an extrapolation of the present situation in Jiamusi (see Table 3 and Figure 6).
Table 3

Dynamic simulation of the supply–demand structure of water resources in the study area by planning-level year

  2010 2015 2020 2030 
Water supply structure (104m3Available transit water resources 103,747 103,747 103,747 103,747 
Surface water supply 165,281 165,281 165,281 165,281 
Groundwater supply 283,412 283,412 283,412 283,412 
Repetitive use of industrial water 10,449.5 25,330.8 48,543.9 94,251.9 
Sewage handling capacity 218.43 341.24 524.94 888.4 
Total water supply 563,108 578,112 601,509 647,580 
Water demand structure (104m3Agricultural water demand 703,303 784,693 786,171 786,224 
Industrial water demand 27,820.8 67,441 129,244 250,937 
Ecological water demand 33,234 33,283.4 33,332.8 33,431.6 
Domestic water demand 8,474.65 9,240.41 9,899.13 11,040.4 
Total water demand 772,832 894,658 958,647 1,081,636 
Balance between supply of and demand for water resources (104m3−209,724 −316,546 −357,138 −434,056 
Annual supply–demand ratio of water resources 0.7286 0.6462 0.6275 0.5987 
  2010 2015 2020 2030 
Water supply structure (104m3Available transit water resources 103,747 103,747 103,747 103,747 
Surface water supply 165,281 165,281 165,281 165,281 
Groundwater supply 283,412 283,412 283,412 283,412 
Repetitive use of industrial water 10,449.5 25,330.8 48,543.9 94,251.9 
Sewage handling capacity 218.43 341.24 524.94 888.4 
Total water supply 563,108 578,112 601,509 647,580 
Water demand structure (104m3Agricultural water demand 703,303 784,693 786,171 786,224 
Industrial water demand 27,820.8 67,441 129,244 250,937 
Ecological water demand 33,234 33,283.4 33,332.8 33,431.6 
Domestic water demand 8,474.65 9,240.41 9,899.13 11,040.4 
Total water demand 772,832 894,658 958,647 1,081,636 
Balance between supply of and demand for water resources (104m3−209,724 −316,546 −357,138 −434,056 
Annual supply–demand ratio of water resources 0.7286 0.6462 0.6275 0.5987 
Figure 6

Dynamic simulation of the supply–demand structure of water resources in the study area.

Figure 6

Dynamic simulation of the supply–demand structure of water resources in the study area.

Beginning in the starting year of 2000, the annual water supply cannot satisfy the annual water demand in Jiamusi. Although the annual water supply and annual water demand both increase yearly, unbalanced supply–demand conditions for water resources are consistently observed, and the supply–demand ratio is always less than 1. In 2004, the supply–demand ratio reached its historical maximum value of 0.9329, after which it rapidly decreased. After 2004, the rice planting area in the study area rapidly expanded and industrial enterprises also underwent rapid development, placing an increasing demand on water resources; however, the rate of development of water resources was much slower than the rate of consumption, and thus, the supply–demand ratio severely decreased. In the year 2010, representing the present conditions, the supply–demand ratio of water resources decreased to its historical minimum value of 0.7286, and the difference between supply of and demand for water resources reached 2.097 × 1010 m3.

From the dynamic simulation results regarding the supply–demand structure of water resources based on an extrapolation from the present situation, it is evident that the supply–demand ratio will continue to decline from 2011 to 2030; the rate of decrease is slightly lowered, indicating an improvement in the supply–demand conditions regarding water resources, but the trend of a year-by-year increase in the difference between the supply of and demand for water resources remains unchanged. By 2030, the supply–demand ratio of water resources will be reduced to 0.5987; the total water supply will reach 6.476 × 107 m3, an increase of 8.45 × 109 m3 compared with that in 2010, whereas the total water demand will reach 1.082 × 1011 m3, an increase of 3.088 × 1010 m3 compared with that in 2010, meaning that the difference between supply and demand will be increased by 2.243 × 1010 m3. Under the conditions that the annual increase in water demand remains greater than the annual increase in water supply and that this difference continues to increase year by year, it is certain that the supply–demand ratio of water resources will also continue to decrease year by year, which will pose a major hindrance to industrial and agricultural development, residential life and the construction of the ecological environment in the study area.

Analysis of the simulation results regarding the water supply structure in the study area

Because of the particular characteristics of the geographical position of the study area, the water supply obtained through water diversion and lifting and the water supply obtained from surface water are analyzed separately, where the latter refers to additional sources of surface water other than water diversion and lifting. Figure 7 shows the simulation results regarding the water supply structure obtained by extrapolating from the present water resource situation in Jiamusi.
Figure 7

Dynamic simulation of the water supply structure in the study area.

Figure 7

Dynamic simulation of the water supply structure in the study area.

The equations of the water resource supply–demand model reflect an increase in the level of development and utilization of surface water resources in the study area from 0.1 in 2010 to 0.5289 in 2010 and a yearly increasing water supply from water diversion and lifting from 2000 on. As shown in the graph of the dynamic simulation results, the trends of variation in the water supplies from water diversion and lifting and from surface water in the study area increased each year from 2000 to 2010. Because the extent of the exploitation of groundwater was being consciously controlled, the water supply from groundwater was simultaneously decreasing. By 2010, the water supply from water diversion and lifting had reached 1.037 × 1010 m3, accounting for 18.42% of the total annual water supply; the water supply from surface water was 1.653 × 1010 m3, accounting for 29.35% of the total annual water supply; and the water supply from groundwater was 2.934 × 1010 m3, accounting for 50.33% of the total annual water supply. Although the level of exploitation of groundwater in the study area is being controlled, groundwater remains the major water supply source and still faces the threat of excessive exploitation; the level of development and utilization of surface water is only 8.2%, which is quite low, meaning that the potential water supply from this source is extremely large. Moreover, the transit water resources in the study area are very rich, but the effective percentage of this water source that is subject to development and utilization has been only 1.53% on average for many years, meaning that the potential additional water supply available from water diversion and lifting is immense.

From the simulation results regarding the water supply structure in the study area obtained by extrapolating the present situation concerning the water supply from water diversion and lifting, it is evident that the water supplies from surface water and from groundwater will both remain at the same level as in the present year and that the curvilinear trend remains unchanged. The industrial and domestic water demands are increasing year by year, directly resulting in corresponding increases in repetitive water consumption for industrial use as well as both industrial and urban domestic sewage discharge, in turn resulting in a yearly increase in sewage disposal. However, the rates of repetitive industrial water consumption and sewage disposal in the study area are very unsatisfactory. The rate of repetitive water consumption for industrial use is only 12.73% in the present year, which is far lower than the rate of 85% in developed countries; similarly, although the total amount of industrial and urban domestic sewage discharge in the present year is 7.801 × 108 m3, the annual sewage disposal volume is 2.184 × 107 m3, corresponding to a sewage disposal rate of only 2.79%. Thus, there is considerable room for improvement in this respect.

Analysis of the simulation results regarding the water demand structure in the study area

Figure 8 shows the simulation results regarding the water demand structure based on an extrapolation of the present water resource situation in Jiamusi.
Figure 8

Dynamic simulation of the water demand structure in the study area.

Figure 8

Dynamic simulation of the water demand structure in the study area.

Beginning in the starting year of 2000, the industrial, domestic and ecological water demands have all increased yearly, whereas the agricultural water demand has increased considerably from 2004 on because of a rapid increase in the agricultural irrigated land area and rice planting area in the study area. Up through the present year of 2010, the rate of increase in the industrial water demand has risen year by year. It is evident that the rapid development of industrial enterprises in the study area in recent years has exerted a great impact on industrial water demand. Meanwhile, the relatively low rates of repetitive water consumption for industrial use and industrial sewage disposal in the study area have exacerbated the increasing annual increment in industrial water demand. The simulation results indicate that by 2030, the industrial water demand will reach 2.509 × 1010 m3, 9.02 times the industrial water demand in 2010.

The continual increases in the agricultural, domestic and ecological water demands and the considerable increase in the industrial water demand are directly responsible for the increasing annual demand of water resources in the supply–demand structure. In 2015, the representative year for short-term planning, the continuous decline in the supply–demand ratio of water resources will lead to shortage of water resources in the study area, thus restricting the development of irrigable farmlands; as a result, the agricultural water demand will remain essentially unchanged on the medium-term and long-term planning scales, and the proportion of agricultural water demand in the water demand structure will be reduced. The agricultural water demand will be reduced from 91% of the total water demand in 2010 to 72.68% by 2030, whereas the industrial water demand will increase from 3.6% in 2010 to 23.2% by 2030. By contrast, there will be no great change in the proportion of the total water demand represented by the domestic and ecological water demands. Although a reduction in the proportion of the agricultural water demand achieves the goal of optimizing the water consumption structure, it is infeasible because it requires that agricultural development in the study area be restricted. The water demands from various industries in the water resource demand structure all exhibit increasing trends of future development. Based on the present water consumption quotas of various industries, by 2030, the demand for water resources will be 1.4 times that in 2010.

CONCLUSIONS AND RECOMMENDATIONS

In the present study, an SD model was used to simulate the supply–demand structure and the individual supply and demand structures of water resources in Jiamusi. The results show that the supply–demand ratio of water resources is 0.728 in Jiamusi in the present scenario represented by the year 2010, indicating that the annual water supply cannot satisfy the annual water demand. If development continues in accordance with the present water resource utilization conditions, then by 2030, the representative year for long-term planning, the supply–demand ratio of water resources will be reduced to 0.598 and seriously unbalanced supply–demand conditions will prevail. This will not only change the water demand structure in Jiamusi, but also exert an impact on the harmonious development of the relationship between the available water resources and the societal, economic and ecological environments of Jiamusi.

Therefore, to achieve the sustainable utilization of water resources in Jiamusi, Jiamusi should first reduce the amount of groundwater used and increase the utilization ratio of surface water, especially transit water; increase its investment in science and technology; and improve the sewage treatment rate to avoid wastage of water resources. Secondly, Jiamusi should rapidly develop water-saving methods of irrigation, especially for rice, and disseminate these controlled irrigation techniques to improve the agricultural water utilization ratio. Meanwhile, because of the complexity of the water resource supply–demand relationship and the shortage of water quality data in Jiamusi, to improve the simulation accuracy and practicality of the SD model, Jiamusi should improve its water quality monitoring network to facilitate further research on the relationship among the various subsystems that influence the supply–demand relationship of water resources, namely, society, the economy, the available resources and the environment.

ACKNOWLEDGEMENTS

This research was supported by the Natural Science Foundation of China (51179032, 51279031), the special funds project for scientific research in the public welfare industry of the Ministry of Water Resources (201301096), and the backup support plan program for the Yangtze River Scholars of the colleges and universities in Heilongjiang.

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