China is actively exploring water resources management considering ecological priorities. The Shaying River Basin (Henan Section) serves as an important grain production base in China. However, conflicts for water between humans and the environment are becoming increasingly prominent. The present study analyzed the optimal allocation of water while considering ecological priorities in the Shaying River Basin (Henan Section). The ecological water demand was calculated by the Tennant and the representative station methods; then, based on the predicted water supply and demand in 2030, an optimal allocation model was established, giving priority to meeting ecological objectives while including social and comprehensive economic benefit objectives. After solving the model, the optimal results of three established schemes were obtained. This revealed that scheme 1 and scheme 2 failed to satisfy the water demand of the study area in 2030 by only the current conditions and strengthening water conservation, respectively. Scheme 3 was the best scheme, which could balance the water supply and demand by adding new water supply based on strengthening water conservation and maximizing the benefits. Therefore, the actual water allocation in 2030 is forecast to be 7.514 billion (7.514 × 109) m3. This study could help basin water management departments deal with water use and supply.

  • Assigning greater weight to the ecological user in an optimization model to meet ecological priorities.

  • Calculating the ecological flow processes inside a river to better reflect seasonal variation.

  • Combining an optimization algorithm and multiple schemes comparison to obtain the optimal water allocation scheme and improve the benefits of water users.

Water provides an important resource for human survival (Oki & Kanae 2006). In recent years, China has been actively exploring a new high-quality development route oriented to ecological priorities and green development (Cheng & Li 2021). The Shaying River Basin (Henan Section) serves as an important grain production base and lies in the Central Plains Economic Zone in China (Zuo et al. 2016). Since the 1960s, a large number of water conservancy projects have been built in the area (Luo et al. 2018). However, variations in runoff, topography, and regional economic development have caused a contradiction between water supply and demand in the area that has existed for many years; unreasonable development and land use has also damaged the riverine environment (Li et al. 2020). Currently, the construction of water conservation projects alone cannot completely solve the problems related to water shortages and worsening environmental conditions in the area, so it is particularly important to seek a reasonable allocation scheme to realize the optimal allocation of limited water resources.

The allocation of water resources refers to the scientifically sound and reasonable allocation of limited water resources, so as to improve the overall water use efficiency of the region and promote the coordinated development of society while conserving other natural resources (Chakraei et al. 2021). Many scholars have conducted extensive and in-depth research on the allocation of water resources and made excellent progress in developing the basic concepts involved (Wang et al. 2002; Pei et al. 2007; Wang & You 2016), water sources and water users (Moreno et al. 2010; Song et al. 2016; Terêncio et al. 2018), methods and model construction (Leenhardt et al. 2004; Adamowski 2008; Santos & Filho 2014; Abdulbaki et al. 2017), and objective optimization methods and solutions (Liu & Chen 2009; Davijani et al. 2016; Abdulbaki et al. 2017; Yan et al. 2020). For example, Zuo (2005) proposed a multi-level optimal allocation model of water resources in support of sustainable development. Davijani et al. (2016) established an optimization model of water resource allocation in arid areas based on the maximization of social and economic efficiency, which weakened the ecological factor. Abdulbaki et al. (2017) proposed a model designed to minimize the total water cost, including economic and environmental costs, while addressing water supply and demand. Terêncio et al. (2018) optimized the role of rainwater collection in the allocation of agricultural water resources while balancing economic and ecological factors.

In summary, attention has been paid to the comprehensive benefits of water resource allocation for society, the economy, and ecological needs, but few studies have been based on the special consideration or prioritizing of ecological demand. Similarly, researchers have paid little attention to ecological water demand in the Shaying River Basin (Ni et al. 2012; Zuo et al. 2019; Ding et al. 2020). Here, ecological water demand is defined as the need for good water quality and adequate water quantity for the ecosystem. Therefore, this study attempts to define the optimal allocation of water resources oriented to ecological priorities in the Shaying River Basin (Henan Section), with 2018 as the current year and 2030 as the planning year. The ecological water demand of the study area was calculated by various methods; then, an optimal model of water resource allocation was established based on forecasted water supply and demand, and more weight was given to ecological water uses, so as to balance water supply with demand. This study provides guidance for improving the ecological conditions of the Shaying River and for realizing a new situation that harmonizes human water needs with environmental conditions, and also provides reference for water resource allocation in other basins in a way that is oriented to prioritizing ecological needs for water.

The Shaying River is the largest tributary on the left bank of the Huai River, which crosses Henan and Anhui provinces. The Shaying River (Henan Section) flows for 410 km, accounting for 66% of the total length of the Shaying River. The Shaying River Basin (Henan Section) covers 32,540 km2, accounting for 82% of the area of the Shaying River Basin, and includes nine cities (Zhengzhou, Kaifeng, Luoyang, Pingdingshan, Xuchang, Luohe, Nanyang, Zhoukou, and Zhumadian). The basin experiences a warm temperate semi-humid monsoon climate, with large interannual variation in precipitation rates and uneven distribution of precipitation within the year; the flood season is mainly concentrated in June to September (Zuo et al. 2016).

There are many tributaries in the basin, including the Shahe, Yinghe, Jialu, and Beiru rivers, with an annual average total of 7.62 billion (7.62 × 109) m3 of water. The water supply sources mainly involve the existing water storage projects, water diversion and lifting projects, groundwater projects, and inter-basin water diversion projects (mid-route of the South-to-North Water Transfer Project, Yellow River Diversion Project, and water diversion project from the Yangtze to Huaihe rivers, which should be completed and put into operation in 2030) (Zuo et al. 2019; Li et al. 2020). Figure 1 shows the general situation of the Shaying River Basin (Henan Section), while Figure 2 shows the distribution of the main water conservation projects and hydrological stations. At present, the main problems in the basin are as follows: (1) There are contradictions between water supply and use in the basin with water shortages hindering the economic and social development of the basin. (2) Domestic and production water uses consume water needed for ecological uses so that the degree of satisfaction for ecological flow is poor. (3) Groundwater is excessive, and water supply in most areas depends too much on groundwater.

Figure 1

Overview of the Shaying River Basin (Henan Section), China; an inset map shows the location of the project area within an outline map of the administrative regions of China.

Figure 1

Overview of the Shaying River Basin (Henan Section), China; an inset map shows the location of the project area within an outline map of the administrative regions of China.

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Figure 2

Main water conservancy projects, hydrological stations, and control sections in the Shaying River Basin (Henan Section), China.

Figure 2

Main water conservancy projects, hydrological stations, and control sections in the Shaying River Basin (Henan Section), China.

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Modeling

Model framework

The general goal of this study was to use an optimization model to calculate the need for water resource allocation based on an analysis of water supply and demand. Through a combination of measures such as prioritizing the protection of the environment, restraining unreasonable water demand, and effectively increasing water supply, various feasible water resource allocation schemes were calculated and compared. Finally, an optimal scheme is recommended that provides the basis for the overall layout of water resources and the implementation of safeguard measures. The allocation of water resources in the Shaying River Basin should abide by the following principles: (1) Prioritize to satisfy the water needs of the environment; (2) Ensure water demand for important industries and agriculture is reasonable while ensuring the water demand for domestic needs is met; (3) Increase and prioritize the use of surface water to reduce the unsustainable use of groundwater; and (4) Consider the benefits to the economy, society, and the environment comprehensively in the scale and methods of water resource allocation.

Based on these principles, a model framework for the optimal allocation of water resources can be determined (Figure 3). The model framework includes four parts: first, determine the water users and water supply sources in the basin; second, determine the objective functions and constraints; third, establish different schemes; and, fourth, solve the model and compare the different schemes.

Figure 3

Model framework for the optimal allocation of water resources.

Figure 3

Model framework for the optimal allocation of water resources.

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Objective function

The study area was divided into nine subareas based on the distribution of cities in Henan Province in the Shaying River Basin (Figure 1); these were identified as k = 1, 2,9 (Table 1). Water users, including ecological, domestic, agricultural, and industrial users, are represented by j = 1, 2, 3, 4, respectively, and sources of surface, ground, and unconventional water are represented by i = 1, 2, 3, respectively. According to the actual situation in the study area, the objective functions of the model were determined as follows:

  • (1)
    Ecological benefit objective: the ecological water is closest to the suitable ecological water demand.
    (1)
  • (2)
    Social benefit objective: total water shortage is the minimum.
    (2)
  • (3)
    Comprehensive economic benefit objective: comprehensive water use benefit (CWUB) is the maximum. CWUB refers to the guaranteed comprehensive water use rate of all users under different priorities and water allocation weights, which can reflect the comprehensive economic benefits for all users. This was investigated because the agricultural and industrial water can produce direct economic benefits, but the ecological and domestic water use cannot produce the same type of direct economic benefits. It is difficult to quantify the economic benefits to all users with money, so the CWUB was selected after comprehensive consideration:
    (3)
    where xijk is the allocated water quantity (108 m3) from water source i to water user j in subarea k, and xi1k is the ecological water (108 m3) allocated to subarea k; Djk is the water demand of user j (108 m3) in subarea k, and D1k is the ecological water demand of subarea k (108 m3); and μj is the weight of water allocation of user j. According to the allocation principle, the weights of ecological, domestic, agricultural, and industrial water users were set as μ1 = 0.35, μ2 = 0.25, μ3 = 0.2, and μ4 = 0.2, respectively.

Constraints

  • (1)
    Water demand constraint of ecology: the ecological water demand in the planning year is in the corresponding water demand range:
    (4)
    where and are the minimum ecological water demand and the suitable ecological water demand in the river channel of subarea k, respectively (in 108 m3), and is the ecological water demand outside the river channel of subarea k (in 108 m3).
  • (2)
    Water demand constraints of other water users: water allocation for domestic, agricultural, and industrial uses should not exceed the upper and lower limits of water demand in the planning year:
    (5)
    where and are the upper and lower limits of the water demand of the user j in subarea k, respectively (in 108 m3).
  • (3)
    Water supply constraints: the water supply of water source i should not exceed the available water supply of subarea k in the planning year:
    (6)
    where is the available water supply of water source i in subarea k (in 108 m3).
  • (4)
    Environmental constraints: the concentration and content of the main pollutant in sewage discharged should not exceed its threshold in the planning year:
    (7)
    (8)
    where is the pollutant concentration (mg/L) in the unit sewage discharged of user j in subarea k, is the specified concentration of pollutants (mg/L), is the sewage discharge coefficient of user j in subarea k, and W0 is the pollutant carrying capacity of the study area in the planning year (104 t/a). According to the water quality of the study area, chemical oxygen demand (COD) was selected as the pollutant index.
  • (5)
    Non-negative constraint:
    (9)

Water demand calculation

Water demand of ecology

The ecological water demand of the study area included ecological water demand for both inside and outside the river:
(10)
where is the ecological water demand of subarea k (108 m3), while and are the ecological water demand inside and outside the river in subarea k, respectively (108 m3).

The ecological water demand outside the river refers to the water demand for ecological uses in the land area outside the river (Lemos et al. 2013), which mainly includes water demand for both the urban environment and forest/grasslands. Through a comprehensive analysis of historical data, the areas of the urban environment and forest/grassland, and the water consumption quota per unit area in the planning year can be determined, and the ecological water demand outside the river can be calculated.

The ecological water demand inside the river refers to the water demand to maintain the environmental functions of the river (Yan et al. 2012); this demand was mainly determined by the suitable ecological flow at control sections of the river (Singh 2017; Ma et al. 2019). The distribution of existing hydrological stations and related relevant observation data in the study area were used to select the river control sections (Figure 2). The names and serial numbers of these sections are shown in Table 2.

The ecological flow was calculated by the Tennant method, which is a commonly used method of measuring historical flow (Santacruz & Aguilar 2009; Huang et al. 2014). However, considering that the runoff of the Shaying River is significantly affected by seasonal precipitation and water uses, the monthly average ecological flow in each year was used to replace the annual average flow in the original method, so as to reflect the seasonal flood and dry periods of the river and improve the accuracy and rationality of the data. Considering the balance between the main rivers, tributaries, and the control sections of upstream and downstream regions of the Shaying River, the suitable ecological flow of each section was calculated as 10–30% of the average monthly flow for many years (10% outside of the flood season from October to May, and 30% in the flood season from June to September). Based on the ecological flow of the control sections, the ecological water demand of each section can be determined:
(11)
(12)
where Qs is the suitable ecological flow of section s (m3/s), is the average flow for many years of section s (m3/s), β is the proportion of suitable ecological flow, t is the period length (s), and Ws is the ecological water demand of section s (m3).
Based on the ecological water demand of control sections, this type of demand of subareas was determined by referring to the representative station method (Huth 2006). One or several hydrological stations with a long series of runoff data and sufficient accuracy were selected in each subarea. When the control area of a station is close to the area of the subarea, the ecological water demand of the subareas can be directly calculated:
(13)
where Wk and Ws are the ecological water demand in the river of division k and section s, respectively (m3), while Fk and Fs are the area of subarea k and control section s, respectively (m2).

Water demand of other users

Other water users include domestic, agricultural, and industrial users. Domestic water demand (D2) was divided into urban and rural domestic water demand, which were calculated using per capita daily water consumption. Agricultural water demand (D3) mainly includes irrigation water demand, which was calculated by the predicted irrigation area, water use coefficient of the canal system, and irrigation quotas. Industrial water demand (D4) was calculated by the comprehensive water consumption of industrial added value per 10,000 yuan. The calculation formulas are as follows:
(14)
(15)
(16)
where and are urban and rural populations in subarea k, respectively (person), and are daily water demand per capita of urban and rural residents, respectively (m3/person/d), sk is farmland irrigation area (mu; where 1 mu ≈ 666.67 m2), is the irrigation quota (m3/mu), ck is the industrial added value (104 yuan), and gk is water consumption of industrial added value per 10,000 yuan (m3/104 yuan).

The basic scheme and strengthened water-conservation scheme were considered when predicting water demand by considering the renewal and transformation of municipal infrastructure, enterprise innovation, promotion and application of water-conservation technology, improvement in the level of water resource management, adjustment of water price policies, and other factors expected to affect water use in the future in Henan Province. The basic scheme was based on the actual situation of the study area, the water demand scheme under the current level of water conservation, and the strengthened water-conservation scheme was considered an increase in water-conservation investment based on the basic scheme under the condition of reasonable economy and feasible technology.

Scheme settings

This study focuses on the scenario of a dry year (P = 75%). When the planning year of 2030 was a dry year, the combination of various measures for water demand and supply in the study area was selected to construct different configuration schemes, such as increasing water supply and strengthening water conservation. Scheme 1 is the basic scheme, which adopts the prediction results of the basic water demand scheme and available water supply of the existing water conservation projects. The existing projects include surface and groundwater supply projects as well as unconventional water use projects. The surface water projects include the existing reservoirs, gate dams, and water diversion projects (Yellow River Diversion Project and Mid-route of South-to-North Water Transfer Project). The groundwater projects include the pre-existing mechanical and electric wells in the study area. Meanwhile, the unconventional water use projects include existing sewage treatment and reuse projects as well as rainwater collection and use projects. Scheme 2 is the strengthened water-conservation scheme and is based on scheme 1; this scheme considers reducing water demand for water users when the available water supply remains unchanged. Scheme 3 increases water supply based on scheme 2; it mainly increases surface water supply through a water diversion project from the Yangtze River to the Huaihe River that is currently under construction, and further increases unconventional water supply such as further increasing sewage water reuse and rainwater use. The optimization results of schemes 1–3 can be obtained by solving the model, and the best scheme can be determined by comparing schemes 1–3.

Model solving

NSGA-II was used to solve the model. This algorithm can reduce the difficulty of individual selection by non-dominated quick sorting and crowding distance; moreover, it has good applicability to solving the problem of the optimal allocation of water resources (Chen et al. 2019). In the present study, the initial population number is 100, the iteration number is denoted by n, the maximum iteration number is 100, the optimal front-end individual coefficient is 0.3, and the fitness function deviation is 1−10−100. The model solving steps are shown in Figure 4.

Figure 4

Flow chart of the Non-dominated Sorting Genetic Algorithm-II (NSGA-II). (Note: n represents the number of iterations, Max n = 100).

Figure 4

Flow chart of the Non-dominated Sorting Genetic Algorithm-II (NSGA-II). (Note: n represents the number of iterations, Max n = 100).

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Data sources

The data and sources are as follows: (1) societal and economic data mainly included population, industrial output value, and industrial added value data for the Shaying River Basin (Henan Section), which came from the statistical yearbook of administrative regions of Henan Province; (2) the hydrological data mainly included the measured discharge data of hydrological stations in the Shaying River Basin; (3) the water resource development and use data mainly included data related to various water supply projects, water supply quantity, water consumption of different industries, sewage water discharge quantity, and water quota data, which came from the water resources investigation and evaluation report of the Shaying River Basin and the water resources bulletin of Huaihe River Basin (http://www.hrc.gov.cn/main/szygb/21448.jhtml), the water resources communique of Henan Province, local standard water quotas of Henan Province, and so on; (4) land use data, including data for cultivated land, urban, ecological forest, and grassland areas, were acquired from the statistical yearbook of Henan Province and the resource and environmental science and data center of the Chinese Academy of Sciences (https://www.resdc.cn/).

Ecological water demand

Ecological water demand in the river at control sections

Figure 5 shows the minimum and suitable ecological flow processes at 15 control sections. According to the processes of ecological flow, the ecological water demand at control sections in the Shaying River Basin (Henan Section) was calculated (Table 2).

Figure 5

Minimum and suitable ecological flow processes at 15 control sections along the Shaying River (Henan Section), China. Please refer to the online version of this paper to see this figure in colour: http://dx.doi.org/10.2166/ws.2021.331.

Figure 5

Minimum and suitable ecological flow processes at 15 control sections along the Shaying River (Henan Section), China. Please refer to the online version of this paper to see this figure in colour: http://dx.doi.org/10.2166/ws.2021.331.

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Ecological water demand in subareas

The representative station method was used to determine the ecological water demand inside the river for subareas based on the results of ecological water demand of control sections in the study area, the balanced relationship between upstream and downstream areas of the Shaying River, the catchment area of various hydrological stations, and the spatial extent of subareas (Table 1). The ecological water demand outside the river in nine subareas was predicted based on the relevant water quotas outside the river (Table 1). As shown in Table 1, the ecological water demand was largest in Pingdingshan and smallest in Kaifeng because the annual runoff of the Sha River in Pingdingshan was larger than that of the Jialu River in Kaifeng. The ecological water demand outside the river in Zhengzhou was largest, which was mainly caused by the high level of urbanization and the large area of the urban environment.

Table 1

Ecological water demand of nine subareas the Shaying River Basin (Henan Section), China (im 108 m3)

No.SubareaInside RiverOutside RiverTotal
k1 Zhengzhou 1.13 1.22 2.35 
k2 Luoyang 0.70 0.09 0.79 
k3 Pingdingshan 2.59 0.29 2.88 
k4 Xuchang 1.09 0.40 1.49 
k5 Kaifeng 0.18 0.11 0.29 
k6 Luohe 0.63 0.19 0.82 
k7 Zhumadian 0.22 0.02 0.24 
k8 Nanyang 0.50 0.08 0.58 
k9 Zhoukou 1.42 0.17 1.59 
 Total 8.44 2.59 11.03 
No.SubareaInside RiverOutside RiverTotal
k1 Zhengzhou 1.13 1.22 2.35 
k2 Luoyang 0.70 0.09 0.79 
k3 Pingdingshan 2.59 0.29 2.88 
k4 Xuchang 1.09 0.40 1.49 
k5 Kaifeng 0.18 0.11 0.29 
k6 Luohe 0.63 0.19 0.82 
k7 Zhumadian 0.22 0.02 0.24 
k8 Nanyang 0.50 0.08 0.58 
k9 Zhoukou 1.42 0.17 1.59 
 Total 8.44 2.59 11.03 
Table 2

Suitable ecological water demand at 15 control sections in the Shaying River Basin (Henan Section), China (in 108 m3)

No.NameCorresponding riverSuitable ecological water demandNo.NameCorresponding riverSuitable ecological water demand
Huangqiao Ying River 1.37 Zhongmou Jialu River 0.38 
Ziluoshan Beiru River 1.08 10 Zhoukou Shaying River 6.49 
Dachen Beiru River 1.91 11 Huaidian Shaying River 8.35 
Zhaopingtai Sha River 1.30 12 Shenqiu Fenquan River 1.01 
Luohe Sha River 4.38 13 Baisha Ying River 0.26 
Guanzhai Li River 0.80 14 Baiguishan Sha River 2.03 
Hekou Li River 1.38 15 Gushitan Li River 0.21 
XInzheng Jialu River 0.24 Total 8.44 
No.NameCorresponding riverSuitable ecological water demandNo.NameCorresponding riverSuitable ecological water demand
Huangqiao Ying River 1.37 Zhongmou Jialu River 0.38 
Ziluoshan Beiru River 1.08 10 Zhoukou Shaying River 6.49 
Dachen Beiru River 1.91 11 Huaidian Shaying River 8.35 
Zhaopingtai Sha River 1.30 12 Shenqiu Fenquan River 1.01 
Luohe Sha River 4.38 13 Baisha Ying River 0.26 
Guanzhai Li River 0.80 14 Baiguishan Sha River 2.03 
Hekou Li River 1.38 15 Gushitan Li River 0.21 
XInzheng Jialu River 0.24 Total 8.44 

Supply and demand forecast results

The water demand of schemes 1–3 of the Shaying River Basin (Henan Section) in 2030 under the scenario of a dry year (P = 75%) was predicted based on the calculation methods for water demand of water users. The water supply of schemes 1–3 of the Shaying River Basin (Henan Section) in 2030 under the scenario of a dry year (P= 75%) was predicted based on the available amount of water resources in the study area, the water supply projects and their water supply capacity, along with the total water consumption control target. The forecast results of schemes 1–3 are shown in Table 3.

Table 3

The forecast results of water supply and demand of nine subareas of the Shaying River Basin (Henan Section), China in 2030 in a dry year (P = 75%) (108 m3)

SubareasScheme 1 (Basic Scheme)
Scheme2 (Strengthen water-conservation)
Scheme 3 (Increase water supply)
Water demandWater supplyWater demandWater supplyWater demandWater supply
Zhengzhou 22.94 20.18 21.75 20.18 21.75 22.57 
Luoyang 1.76 0.97 1.70 0.97 1.70 1.04 
Pingdingshan 12.83 11.67 12.35 11.67 12.35 12.65 
Xuchang 13.09 10.72 12.31 10.72 12.31 12.01 
Kaifeng 3.04 2.20 2.88 2.20 2.88 2.64 
Luohe 6.29 5.02 5.92 5.02 5.92 5.81 
Zhumadian 0.74 0.71 0.71 0.71 0.71 0.81 
Nanyang 1.26 1.10 1.23 1.10 1.23 1.20 
Zhoukou 17.17 15.95 16.29 15.95 16.29 16.47 
Total 79.12 68.53 75.14 68.53 75.14 75.20 
SubareasScheme 1 (Basic Scheme)
Scheme2 (Strengthen water-conservation)
Scheme 3 (Increase water supply)
Water demandWater supplyWater demandWater supplyWater demandWater supply
Zhengzhou 22.94 20.18 21.75 20.18 21.75 22.57 
Luoyang 1.76 0.97 1.70 0.97 1.70 1.04 
Pingdingshan 12.83 11.67 12.35 11.67 12.35 12.65 
Xuchang 13.09 10.72 12.31 10.72 12.31 12.01 
Kaifeng 3.04 2.20 2.88 2.20 2.88 2.64 
Luohe 6.29 5.02 5.92 5.02 5.92 5.81 
Zhumadian 0.74 0.71 0.71 0.71 0.71 0.81 
Nanyang 1.26 1.10 1.23 1.10 1.23 1.20 
Zhoukou 17.17 15.95 16.29 15.95 16.29 16.47 
Total 79.12 68.53 75.14 68.53 75.14 75.20 

The results by model optimization

Based on the forecast of future water supply and demand, the water allocation of schemes 1–3 in 2030 under the scenario of a dry year (P= 75%) was obtained by solving the model (Figure 6). The total water allocation of schemes 1–3 was 6.853 billion m3, 6.853 billion m3, and 7.514 billion m3, respectively (Figure 6). Among the subareas, Zhengzhou had the largest water allocation and Zhumadian had the smallest. Among the water users, social and economic development are predicted to cause agricultural and industrial users to remain as the largest water users in 2030, followed by the users of domestic water and ecological water. Surface water is predicted to be the main water supply source in 2030, because groundwater exploitation will be limited while the supply of surface water will increase through water diversion projects and unconventional water use projects.

Figure 6

The optimization results of schemes (a) 1, (b) 2, and (c) 3 for nine subareas of the Shaying River Basin (Henan Section), China in 2030 (P= 75%) (Note: 1, 2, 3, and 4 in the abscissa of Figure 6 are ecological water, domestic water, agricultural water, and industrial water for each of the nine subareas, respectively). Please refer to the online version of this paper to see this figure in colour: http://dx.doi.org/10.2166/ws.2021.331.

Figure 6

The optimization results of schemes (a) 1, (b) 2, and (c) 3 for nine subareas of the Shaying River Basin (Henan Section), China in 2030 (P= 75%) (Note: 1, 2, 3, and 4 in the abscissa of Figure 6 are ecological water, domestic water, agricultural water, and industrial water for each of the nine subareas, respectively). Please refer to the online version of this paper to see this figure in colour: http://dx.doi.org/10.2166/ws.2021.331.

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Benefits analysis based on the results of model optimization

Ecological benefits analysis

The ecological benefit of water is expressed as the water shortage between the supply of ecological water and suitable ecological water demand. The closer water availability is to the suitable ecological water demand, the better the ecological benefits. Figure 7 displays the ecological water shortage of schemes 1–3 of nine subareas. The figure shows that an obvious ecological water shortage still exists for subareas in scheme 1. After strengthening water conservation in scheme 2, the ecological water shortage in most subareas reduced except in Luoyang. The main reason for this is that the water supply in Luoyang cannot meet the demands of ecology, industrial and agricultural production, and domestic use at the same time. After increasing the supply of water in scheme 3, the ecological water shortage of subareas can be eliminated, and the ecological benefits will be maximized.

Figure 7

Ecological water shortage of nine subareas of the Shaying River Basin (Henan Section), China, of schemes 1–3 in 2030 (108 m3). Please refer to the online version of this paper to see this figure in colour: http://dx.doi.org/10.2166/ws.2021.331.

Figure 7

Ecological water shortage of nine subareas of the Shaying River Basin (Henan Section), China, of schemes 1–3 in 2030 (108 m3). Please refer to the online version of this paper to see this figure in colour: http://dx.doi.org/10.2166/ws.2021.331.

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Social benefit analysis

The social benefit of water is expressed by water shortage, which refers to the difference between the actual water allocations and the predicted water demands of each scheme. Figure 8 shows the predicted water shortage of the nine subareas of schemes 1–3. The total predicted water shortages of schemes 1–3 were 1.073 billion m3, 0.661 billion m3, and 0 billion m3, respectively, under the scenario of a dry year (Figure 8). Among the water users in schemes 1 and 2, agricultural, industrial, domestic, and ecological water users were forecasted to experience water shortages from high to low (Figure 8(a)). Among the nine subareas, the water shortage of scheme 2 would be lower than that of scheme 1 based on model optimization, but an obvious water shortage would still be forecasted to exist in most subareas (such as Zhengzhou and Xuchang) (Figure 8(b)); this indicates that the water shortages of the basin cannot be effectively reduced only by strengthening water conservation. After increasing water supply in scheme 3, no water shortages were forecasted in the nine subareas after model optimization, and the social benefits would be maximized.

Figure 8

The water shortage for (a) four types of users and (b) nine subareas of the Shaying River Basin (Henan Section), China, of schemes 1–3 in 2030 (P= 75%). Please refer to the online version of this paper to see this figure in colour: http://dx.doi.org/10.2166/ws.2021.331.

Figure 8

The water shortage for (a) four types of users and (b) nine subareas of the Shaying River Basin (Henan Section), China, of schemes 1–3 in 2030 (P= 75%). Please refer to the online version of this paper to see this figure in colour: http://dx.doi.org/10.2166/ws.2021.331.

Close modal

Comprehensive economic benefit analysis

The comprehensive economic benefit of water is expressed by a comprehensive water use benefit (CWUB) coefficient. Figure 9 shows the CWUBs of the nine subareas of schemes 1–3 when considering ecological priorities. In scheme 1, the CWUBs of most subareas would be lower than 0.9, and that of the entire study area is forecast to be 0.8805, which would represent a low level. In scheme 2, the CWUBs of most subareas would have improved slightly after strengthening water conservation, and that of the whole study area is forecast to improve to 0.9124. In scheme 3, the CWUBs of the subareas would reach 1.0, providing maximal comprehensive economic benefits.

Figure 9

The comprehensive water use benefit (CWUB) of nine subareas of the Shaying River Basin (Henan Section), China, in 2030 for schemes (a) 1, (b) 2, and (c) 3 with different μj.

Figure 9

The comprehensive water use benefit (CWUB) of nine subareas of the Shaying River Basin (Henan Section), China, in 2030 for schemes (a) 1, (b) 2, and (c) 3 with different μj.

Close modal

Figure 9 also compares the CWUBs of schemes 1–3 in the case of the prioritization of ecological (μ1 = 0.35, μ2 = 0.25, μ3 = 0.2, μ4 = 0.2) and domestic water (μ1 = 0.25, μ2 = 0.35, μ3 = 0.2, μ4 = 0.2). In both cases, different users correspond to different weights, μj. When considering ecological priority, the CWUBs of most subareas were forecasted to be higher than those considering domestic water priority (Figure 9). The difference in the CWUBs between the two cases was significant in schemes 1 and 2, but this difference does not exist in scheme 3, which is mainly a result of increasing the water supply in scheme 3. Therefore, it can be considered that the optimal allocation of water resources oriented to ecological priority can improve the comprehensive economic benefits when there is a water shortage in the study area.

Water allocation for the optimal scheme

According to the benefits analysis of the model optimization results of schemes 1–3, it can be seen that only relying on the water supply capacity of the current water conservation projects in scheme 1 cannot satisfy the demand for water in the Shaying River Basin (Henan Section) in 2030. Strengthening water conservation in scheme 2 can help to alleviate the water shortage and improve the benefits for the study area in 2030, but the effect is not obvious. After increasing the water supply based on strengthening water conservation in scheme 3, no water shortage was forecasted for 2030; the water supply and demand of the entire study area and subareas were forecasted to be in balance, and the ecological, social, and comprehensive economic benefits peaked. Therefore, scheme 3 was selected as the optimal scheme. The actual water allocation of the Shaying River Basin in 2030 is forecast to be 7.514 billion m3. The allocation results of water users and water sources of the nine subareas are shown in Table 4, and the corresponding water supply routes are shown in Figure 10.

Table 4

Water allocation for four types of water users and three types of water sources in nine subareas of the Shaying River Basin (Henan Section), China, in 2030 (P = 75%) (108 m3)

SubareasDifferent Water Users
Different Water Sources
Ecological waterDomestic waterAgricultural waterIndustrial waterTotalSurface waterGroundwaterUnconventional waterTotal
Zhengzhou 2.35 6.19 6.28 6.92 21.75 15.16 3.69 2.91 21.75 
Luoyang 0.79 0.18 0.41 0.32 1.70 0.70 0.95 0.05 1.70 
Pingdingshan 2.88 1.67 3.42 4.38 12.35 9.81 2.14 0.40 12.35 
Xuchang 1.49 1.81 4.79 4.23 12.31 7.03 4.44 0.84 12.31 
Kaifeng 0.29 0.16 2.06 0.38 2.88 1.10 1.54 0.24 2.88 
Luohe 0.82 0.78 2.40 1.91 5.92 3.12 2.38 0.41 5.92 
Zhumadian 0.24 0.09 0.37 0.00 0.71 0.22 0.44 0.05 0.71 
Nanyang 0.58 0.09 0.48 0.08 1.23 1.01 0.14 0.07 1.23 
Zhoukou 1.59 2.69 8.76 3.25 16.29 5.94 9.83 0.52 16.29 
Total 11.02 13.67 28.98 21.47 75.14 44.09 25.55 5.50 75.14 
SubareasDifferent Water Users
Different Water Sources
Ecological waterDomestic waterAgricultural waterIndustrial waterTotalSurface waterGroundwaterUnconventional waterTotal
Zhengzhou 2.35 6.19 6.28 6.92 21.75 15.16 3.69 2.91 21.75 
Luoyang 0.79 0.18 0.41 0.32 1.70 0.70 0.95 0.05 1.70 
Pingdingshan 2.88 1.67 3.42 4.38 12.35 9.81 2.14 0.40 12.35 
Xuchang 1.49 1.81 4.79 4.23 12.31 7.03 4.44 0.84 12.31 
Kaifeng 0.29 0.16 2.06 0.38 2.88 1.10 1.54 0.24 2.88 
Luohe 0.82 0.78 2.40 1.91 5.92 3.12 2.38 0.41 5.92 
Zhumadian 0.24 0.09 0.37 0.00 0.71 0.22 0.44 0.05 0.71 
Nanyang 0.58 0.09 0.48 0.08 1.23 1.01 0.14 0.07 1.23 
Zhoukou 1.59 2.69 8.76 3.25 16.29 5.94 9.83 0.52 16.29 
Total 11.02 13.67 28.98 21.47 75.14 44.09 25.55 5.50 75.14 
Figure 10

Schematic diagram of the water supply route for optimal allocation of water resources in the Shaying River Basin (Henan Section), China.

Figure 10

Schematic diagram of the water supply route for optimal allocation of water resources in the Shaying River Basin (Henan Section), China.

Close modal

Degree of satisfaction for ecological flow

The degree of satisfaction for ecological flow is measured by the days of daily measured flow reaching the suitable ecological flow, divided by the total number of days in the evaluation period, multiplied by 100%. Taking the Zhoukou section as an example (Figure 11), the average degree of satisfaction for ecological flow in the Zhoukou section in 2009–2018 was 87.44%; however, a very large amount of interannual variation was observed. In 2009, 2013, 2014, and 2016, the degree of satisfaction for ecological flow was relatively low. But in other years, the degree of satisfaction for ecological flow was more than 90%, which remained at a high level. Among the months of 2009–2018, the satisfaction degree outside of the flood season (April to May, October to March) was higher, but the degree of satisfaction for the flood season (June to September) was lower. The degree of satisfaction for the flood season in 2013–2016 remained at less than 60%. Further analysis shows that the change of the degree of satisfaction for ecological flow is related to the runoff of the river. The average surface runoff in the Zhoukou section was 2.123 billion m3 in 2009–2018. Except for 2010–2012, the other years were dry or extremely dry years, and the corresponding degree of satisfaction for ecological flow in these years was also low, such as for 2013–2016. Therefore, it can be considered that the lack of water inflow in dry years is the main reason for the low degree of satisfaction for ecological flow in those times.

Figure 11

The degree of satisfactory ecological flow of the Zhoukou section of the study area in 2009–2018.

Figure 11

The degree of satisfactory ecological flow of the Zhoukou section of the study area in 2009–2018.

Close modal

Measures for safeguarding water resources in extremely dry periods

If the planning year in the study area encounters an extremely dry year (P > 99%) or a continuous series of dry years, the following safeguard measures can be taken based on the above optimal allocation scheme for water resources:

  • 1.

    Strengthen the upstream use of medium- and large-sized reservoirs (Zhaopingtai, Baiguishan, Baisha, Gushitan, Yanshan) and middle and downstream sluices and dams. At the same time, upgrade the existing water network monitoring system, including ecological flow monitoring of different control sections, water quality monitoring of different water sources, water supply network monitoring, water transmission and distribution network construction, and water intake process monitoring of different water users.

  • 2.

    On the premise of ensuring adequate water is available for the minimum ecological water demand of rivers, basic domestic water demand of residents, and basic water demand of important industries, water conservation should be further strengthened, and some agricultural or industrial water use should be appropriately reduced or temporarily stopped when water shortages continue.

  • 3.

    Strengthen the construction of emergency water sources. Determine the possibility and quantity of strategically reserved water resources such as groundwater and water transfer, and fully tap the potential of unconventional water sources in the basin, so as to improve the ability to maintain an adequate water supply.

  • 4.

    Improve drought forecasting. Strengthen the construction of meteorological and hydrological stations, consider the impact of climate change and other variable factors with uncertain effects on water resources in the basin, and continuously improve the capacity to respond to drought risk.

All the authors contributed to the original draft preparation. Methodology and data analysis: LI Hang, TAO Jie and QU Xiao-ning; Data collection: LI Hang and HU Chang-hong; Writing – review and editing: LI Hang and TAO Jie; Supervision: ZUO Qi-ting. All authors read and approved the final manuscript.

The authors declare that they have no conflicts of interest to this work.

This study was funded by the National Natural Science Foundation of China (Grant No. 51709238).

All relevant data are included in the paper or its Supplementary Information.

Abdulbaki
D.
,
Al-Hindi
M.
,
Yassine
A.
&
Najm
M. A.
2017
An optimization model for the allocation of water resources
.
Journal of Cleaner Production
164
,
994
1006
.
Adamowski
F. J.
2008
Peak daily water demand forecast modeling using artificial neural networks
.
Journal of Water Resources Planning and Management
134
(
2
),
119
128
.
Chakraei
I.
,
Safavi
H. R.
,
Asce
A. M.
,
Dandy
G. C.
&
Golmohammadi
M. H.
2021
Integrated simulation-optimization framework for water allocation based on sustainability of surface water and groundwater resources
.
Journal of Water Resources Planning and Management
147
(
3
), 05021001.
Chen
M.
,
Dong
Z.
,
Jia
W.
,
Ni
X.
&
Yao
H.
2019
Multi-objective joint optimal operation of reservoir system and analysis of objectives competition mechanism: a case study in the upper reach of the Yangtze River
.
Water
11
(
12
), 2542.
Davijani
M. H.
,
Banihabib
M. E.
,
Anvar
A. N.
&
Hashemi
S. R.
2016
Multi-Objective optimization model for the allocation of water resources in arid regions based on the maximization of socioeconomic efficiency
.
Water Resources Management
30
(
3
),
927
946
.
Ding
T.
,
Du
S.
,
Zhang
Y.
,
Wang
H.
&
He
L.
2020
Hardness-dependent water quality criteria for cadmium and an ecological risk assessment of the Shaying River Basin, China
.
Ecotoxicology and Environmental Safety
198
, 110666.
Huang
S.
,
Chang
J.
,
Huang
Q.
,
Wang
Y.
&
Chen
Y.
2014
Calculation of the instream ecological flow of the Wei river based on hydrological variation
.
Journal of Applied Mathematics
2014
,
1
9
.
Leenhardt
D.
,
Trouvat
J. L.
,
Gonzales
G. B.
,
Perarnaud
V.
&
Bergez
J. E.
2004
Estimating irrigation demand for water management on a regional scale
.
Agricultural Water Management
68
(
3
),
207
232
.
Lemos
D.
,
Dias
A. C.
,
Gabarrell
X.
&
Arroja
L.
2013
Environmental assessment of an urban water system
.
Journal of Cleaner Production
54
,
157
165
.
Liu
B.
&
Chen
X.
2009
Water resources deployment model for river basin based on synergetic theory
.
Journal of Hydraulic Engineering
40
(
1
),
60
66
.
Luo
Z.
,
Zuo
Q.
,
Gan
R.
&
Ma
J.
2018
Effect of human activity intensity on stream structure and connectivity in Shaying River Basin, China
.
Water Science and Technology-Water Supply
18
(
3
),
754
766
.
Ma
D.
,
Luo
W.
,
Yang
G.
,
Lu
J.
&
Fan
Y.
2019
A study on a river health assessment method based on ecological flow
.
Ecological Modelling
401
,
144
154
.
Moreno
R. S.
,
Szidarovszky
F.
,
Aguilar
A. R.
&
Cruz
I. L.
2010
Multiobjective linear model optimize water distribution in Mexican valley
.
Journal of Optimization Theory and Applications
144
(
3
),
557
573
.
Ni
T.
,
Xu
J.
,
Xin
H.
,
Bai
Y.
&
Ping
S.
2012
Surface water quality assessment using multivariate statistical techniques: a case study of shaying river basin lower reach, China
.
Fresenius Environmental Bulletin
21
(
10
),
2969
2976
.
Oki
T.
&
Kanae
S.
2006
Global hydrological cycles and world water resources
.
Science
313
(
5790
),
1068
1072
.
Pei
Y.
,
Zhao
Y.
&
Zhang
J.
2007
On rational deployment of generalized water resources I. Theory
.
Journal of Hydraulic Engineering
38
(
1
),
1
7
.
Santacruz
D. L. G.
&
Aguilar
R. M.
2009
Estimates of ecological flows in the Rio Valles with the Tennant method
.
Hidrobiologica
19
(
1
),
25
32
.
Santos
C. C. D.
&
Filho
A. J. P.
2014
Water demand forecasting model for the metropolitan area of São Paulo, Brazil
.
Water Resources Management
28
(
13
),
4401
4414
.
Song
W. Z.
,
Yuan
Y.
,
Jiang
Y. Z.
,
Lei
X. H.
&
Shu
D. C.
2016
Rule-based water resource allocation in the Central Guizhou Province, China
.
Ecological Engineering
87
,
194
202
.
Terêncio
D. P. S.
,
Sanches Fernandes
L. F. S.
,
Cortes
R. M. V.
,
Moura
J. P.
&
Pacheco
F. A. L.
2018
Rainwater harvesting in catchments for agro-forestry uses: a study focused on the balance between sustainability values and storage capacity
.
Science of The Total Environment
613
,
1079
1092
.
Wang
H.
,
Qin
D.
&
Wang
J.
2002
Concept of system and methodology for river basin water resources programming
.
Journal of Hydraulic Engineering
0
(
8
),
1
6
.
Wang
H.
&
You
J.
2016
Progress of water resources allocation during the past 30 years in China
.
Journal of Hydraulic Engineering
47
(
3
),
265
271
.
282
.
Yan
D. H.
,
Wang
G.
,
Wang
H.
&
Qin
T. L.
2012
Assessing ecological land use and water demand of river systems: a case study in Luanhe River, North China
.
Hydrology and Earth System Sciences
16
(
8
),
2469
2483
.
Yan
Z.
,
Zhou
Z.
,
Liu
J.
,
Wen
T.
&
Zhang
F.
2020
Multi objective optimal operation of reservoirs based on water supply, power generation, and river ecosystem with a new water resource allocation model
.
Journal of Water Resources Planning and Management
146
(
12
), 05020024.
Zuo
Q.
2005
Relationship between carrying capacity and optimal deployment of water resources
.
Journal of Hydraulic Engineering
36
(
11
),
1286
1291
.
Zuo
Q.
,
Han
C.
,
Liu
J.
,
Li
J.
&
Li
W.
2019
Quantitative research on the water ecological environment of dam-controlled rivers: case study of the Shaying River, China
.
Hydrological Sciences Journal-Journal Des Sciences Hydrologiques
64
(
16
),
2129
2140
.
Zuo
Q.
,
Luo
Z.
,
Shi
Y.
,
Rong
G.
,
Liu
J.
&
Chen
H.
2016
Main parameters and physiographic characteristics of Shayinghe River Basin
.
Water Resources and Hydropower Engineering
47
(
12
),
66
72
.
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