1. Introduction
The Yangtze River is the largest river in Asia and the third largest worldwide, with rich resources, tributaries, and lakes. The Yangtze River is generally divided into three portions: extending from its source to the Yichang section, it is referred to as “upstream”; from the Yichang section to the Hukou section is “midstream”; and from the Hukou section to its estuary is referred to as “downstream.” The upstream Yangtze River is located in the southwest region of central China, where it flows through several ecosystems and densely populated regions. It serves critical functions such as forming an ecological barrier and water source in the river basin and alleviating local ecological and environmental degradation [
1].
The variability of ecological and hydrological processes in the basin has been strongly increased by the intensification of global climate change, increase in water demand, and other human activity in recent years [
2]. The complex coupled system in the upstream Yangtze River has made it the focus of international research on the response of the ecological environments to climate change and human activity [
3,
4,
5,
6]. As anthropogenic pressure continues to intensify in the upstream basin of the Yangtze River, the high demand for water for social and economic development has exerted a significant impact on the ecological environment in this basin [
7]. In order to explore the water supply and demand pattern and its variation law of the water resource coupling system in the upstream Yangtze River in the long-term future, and to provide a reference for developing long-term management plans/policies of local water resources, the upstream Yangtze River Basin was selected as the study area to forecast the contradiction between water supply and demand under the influence of climate change and human activity. The research results have important theoretical and practical significance for protecting the ecological barrier and maintaining social and economic development in this basin.
The changes in hydrological processes directly affect the development and utilization of water resources. In the 1980s, the hydrological communities worldwide began focusing on the impact of environmental changes on hydrology and water resources. Researchers have established a variety of climate models (general circulation models; GCMs) to simulate climate changes caused by human activity under multiple scenarios. GCMs are dynamic models that can provide reliable historical, contemporary, and future climate data to explore the mechanisms of climate change and the associated response of the water cycle [
8]. The World Climate Research Program (WCRP) proposed the Coupled Model Intercomparison Project (CMIP) to promote atmospheric, climate system, and regional system models. The CMIP program, implemented in 1995, has produced a fifth revised model (CMIP5) that includes multiple climate system models and earth system models and defines new climate change scenarios, known as representative concentration pathways (RCPs) [
9,
10,
11]. CMIP5 data under three different greenhouse gas emission scenarios—(RCP2.6 (low emissions), RCP4.5 (medium stable emissions), and RCP8.5 (high emissions))—were used to analyze future climate scenarios. Since their first use, climate models have been an important tool for evaluating decadal climate change [
12,
13]. With the development of information technology, combining climate and hydrological models has comprised an important approach for studying the impact of climate change on runoff variation [
14,
15,
16]. The global climate model of CanESM2 in CMIP5 and RCP2.6, RCP4.5, and RCP8.5 were considered for this study, and the variable infiltration capacity (VIC) macroscale hydrological model was utilized to simulate runoff sequences under different discharge scenarios in the study area.
There are many methods for forecasting water demand considering socioeconomic development, including trend analysis, classified water quota, and mathematical model calculation methods. The trend analysis method is mainly applied to forecast industrial water demand and often includes the Kuznets curve method [
17,
18]. The classified water quota method is commonly applied for water resource planning, requiring water quota data and social and economic factor forecasting. The mathematical model method requires statistical data from the past several years to establish a model, determine the factors affecting changes in water consumption, identify the relationship between time and water consumption, and forecast water consumption. Commonly used methods include traditional regression analysis [
19,
20,
21] and gray forecasting models [
22,
23,
24]. There are also intelligent mathematical models such as artificial neural network models [
25,
26,
27]), fuzzy mathematics [
28], and system dynamics models [
29,
30]. The trend analysis method cannot reflect the mechanism of water consumption. The data-driven mathematical model method is limited by the short time series of water consumption data; thus, it is only suitable for short-term water demand forecasting. The water quota, which is set every few years in detail by water management agencies, is actually the maximum water that is allowed to be used by each user. Thus, the quota method will always result in overestimated water demand. The historical data of water use spans only 15 years in the upstream Yangtze River, which is unsuitable for a long-term data-driven water demand forecasting. For long-term forecasting, the impact of water use mechanisms and macro-control in China must be considered.
Considering the impact of climate change on utilizable water, social and economic development on long-term water demand, and various factors on supply and demand contradictions in terms of different measures, an analytic method for determining available water supply and a long-term water demand forecasting model are proposed. The proposed methods were developed to analyze the supply and demand characteristics of water resource coupling systems in the upstream Yangtze River under changing environments. By comprehensively considering the influence of water use mechanisms and macro regulation on future long-term water demand, the classified water use index method under macro regulation was used to construct a long-term water demand forecasting model. The forecasting period was divided into several parts based on the time nodes of macro regulation to enhance the reliability of the forecasting results. The contradiction between supply and demand was analyzed, and a discussion on countermeasures from the perspectives of water supply capacity and utilizable water constraints is presented. The utilizable water constraint is also referred to as ecological constraint, because of the relation of ecological water (in channel) demand and utilizable water. After introducing the study area and describing the socioeconomic structure in
Section 3, an analysis of current water supply-use patterns, available water supply, and long-term water demand is presented in
Section 4 to evaluate the contradiction between water supply and demand in the water resource coupling system. Finally, conclusions are presented in
Section 5.
3. Study Area
The Yangtze River has important ecological barrier and water supply functions in the river basin and plays a key role in alleviating local ecological environment degradation, forming a complex coupled system. The upstream Yangtze River covers an area of approximately 1 million km
2. The major tributaries of the Yangtze River include the Jinsha, Yalong, Mintuo, Jialing, and Wujiang tributaries and span 38 cities across 6 provinces, including Sichuan, Qinghai, Guizhou, Yunnan, Gansu, and Hubei. The upstream Yangtze River is characterized by complex and variable topography as an important part of the Qinghai–Tibet Plateau with karst and other special terrain and more mountainous and hilly areas [
41,
42]. In the basin, the population presents a regional aggregation feature in the area that is sparse above the Shigu section and gradually increases from the Shigu section to the bottom, with human activity gradually increasing in frequency. The climate of the upstream Yangtze River belongs to the Qinghai–Tibet alpine region and subtropical monsoon region. The water sources in the region are mainly the melting snow and rainfall on the plateau. The flood season in this area generally spans May to October, and the rainfall during the flood season accounts for more than 70% of total annual rainfall. The precipitation in the basin ranges from 800 to 1200 mm per year, exhibiting uneven spatial and temporal distribution [
43].
To analyze the spatial distribution of the contradiction between supply and demand in the upstream Yangtze River, seven main control sections—Shigu, Panzhihua, Xiluodu, Xiangjiaba, Zhutuo, Cuntan, and Yichang—were selected from the upper reaches to divide the upstream Yangtze River into seven sub-basins, as shown in
Figure 2. The seven sub-basins are distributed in the Jinsha, Yalong, Mintuo, Jialing, Wujiang, and main streams.
The study area is sparsely populated with low-intensity human activity above the Shigu section, which gradually increases from the Shigu section to the bottom. According to the national, provincial, and city data from China [
44] obtained during 2011–2015, the population of this basin continued to rise at a rate of 5‰, which is higher than the national average growth rate of 2‰, and reached 155 million in 2015 with a lower urbanization rate of 50.0% (compared with the national rate 56% in 2015).
In 2015, the total upstream gross domestic product (GDP) reached 6.14 trillion yuan, with a per-capita GDP of 39,600 yuan, which was less than the national per-capita average of 49,900 yuan. Upstream regions of Chongqing and Hubei, whose economies are relatively developed, have a per-capita GDP of more than 50,000 yuan. The provinces of Sichuan, Yunnan, Gansu, and Guizhou have a per-capita GDP of approximately 30,000 yuan, with less developed economies and high potential. From 2011 to 2015, GDP maintained a continuous growth trend, but the growth rate slowed down to 6% in 2015 from 18% in 2011 in the upstream, which was consistent with the national GDP change trend. According to the “Classification of Three Industries” established by New Zealand economist Fisher, agriculture, including farming, forestry, animal husbandry, and fishery, is classified as the primary industry; manufacturing/construction industry is classified as secondary industry; and circulation/service industry is classified as tertiary industry. From the perspective of industrial structure, the agricultural output (primary industry) in 2015 was 664.6 billion yuan, secondary industry was 2692 billion yuan, and tertiary industry was 2783.2 billion yuan, with an industry structure of 10.8:43.8:45.3 in the upstream. The proportions of primary industrial output in Yunnan, Sichuan, Gansu, Guizhou, and Hubei were 15%, 12%, 14%, 15%, and 11% higher than the upstream average, respectively. Qinghai, Chongqing, and Hubei exhibited advantages in secondary industry, while Gansu and Chongqing had advantages in tertiary industry. Compared with the national industry structure in the same year of 8.4:41.11:50.46, as shown in
Figure 3, the industries in the upstream exert stress on agriculture and the secondary industry, while the tertiary industry lagged.
In terms of agricultural patterns, a well-known agricultural production base, Sichuan Basin, is located in this area and is among the main grain-producing areas in China. The main crops in this region are food crops, which are supplemented by cash crops; among cash crops, rice, wheat, corn, and sweet potato occupy dominant positions. Rice accounts for 47.1% of total grain output, wheat accounts for 15.3%, corn accounts for 18.0%, and sweet potatoes account for 10.7%. Cash crops include a wide variety of plants such as cotton, oil, sugar cane, fruit, tea, tobacco, hemp, and medicinal materials. The total area of cultivated land in the basin was 13.49 million ha in 2015, of which only 4.61 million ha was irrigated, with an irrigated ratio of only 34.2%. The proportion of the irrigated area in Sichuan and Hubei was relatively higher, while that in other regions was less than 40%, which is far lower than the national average of 48.8%.
5. Conclusions
A climate model was introduced, and development plans/data of local socioeconomic/water use indicators were collected to systematically forecast the water supply and demand pattern and its changes in the coupled water resources system of the upstream Yangtze River over the next 85 years. By analyzing the historical water supply structure of the water coupling system of the study area, the main water supply source in this basin was identified as surface water. Considering the different influences onwater supply and demand patterns, the utilizable water resources and supply capacity were evaluated as preparation. The utilizable water resources are determined by simulated runoff and water utilization threshold. Comprehensively considering the influence of water use mechanism and macro regulation on future water use change, the classified index method under macro regulation was used to extend the forecasting period and construct a long-term water demand forecasting model. Further, contradiction analysis was conducted in terms of water supply capacity and ecological condition limitations. It was found that the simulated runoff increased slightly under different RCPs; the water demand generally showed a trend of first increasing and then decreasing; the contradiction between supply and demand was more prominent on a monthly basis than on annual basis and became obvious gradually from top to bottom in the study area for the next 85 years.
The water use situation in the upstream Yangtze River was analyzed systematically from two aspects of water supply and demand under the changing environment of climate change and socioeconomic development. Compared with data-driven models, the water demand model based on the relationship between socioeconomic factors and water use is less reliant on historical data of water use and more feasible for long-term forecasting, especially in China, where macro regulation policies could provide socioeconomic scenarios for the future. It provides an overview of the water demand in the long term under the scenario that society and economy develop as planned. This study provided a longer forecast period than other studies on the water supply and demand. A large number of socioeconomic plans and water use data were collected, and the water use situation and its changes in further future were explored, which can be used as references for the water resources management agencies to develop future water management plans or policies about the upstream Yangtze River Basin.
There are also many points that could be further improved. Short-term forecasting of water demand, which are more accurate, would be conducted in further study to develop a water supply and demand pattern analysis system coupled with long–medium–short-term forecast. And the relationship between local environment condition and its environmental water use (in channels) also remains to be explored.