Abstract

Changchun is a major city in East Asia, and is both an industrial and agricultural base in China. Unfortunately, the volume of surface water available to the city has restricted its development. To monitor the status of surface water resources, this study used a combination of remote sensing and a geographic information system to analyze the volume of surface water and the water use force of both land use types. The areas with surface water were extracted when the maximal value of the normalized difference water index (NDWI) was greater than 0.1. The volume of the surface water was calculated from the digital elevation map (DEM) data. Finally, the water use force was assessed using ArcGIS software. The results indicated that there was an available volume of 18.23 × 109 m3 of surface water in Changchun, and 21% of the available area had little surface water. Changchun City and Jiutai County had more surface water than other areas in the vicinity of Changchun. It was found that 7% of the urban-industrial area was located in areas with the worst surface water availability, while 66% of the arable land area was located in areas which exceeded the worse surface water availability areas.

INTRODUCTION

Water is a vital circulating resource. Although 70% of the earth's surface is covered by water, only 2.5% of global fresh water is available (Change 1999). Fresh water is essential for subsistence and the development of human society (Nirmal 1997; Everard 2002; Ballantine et al. 2012). Most of the world's fresh water is stored in glaciers or as groundwater, which is not directly used (Sanda & Marioara 2009). Conversely, the recharge period of some groundwater aquifers is considered to be hundreds or even thousands of years. Once water is extracted from groundwater aquifers, they can take a very long time to recharge (Oki et al. 2003; Zhai et al. 2013).

Surface water is an important water resource for human society, and sources include glaciers, lakes, rivers, and swamps. These sources can be replenished efficiently by water circulation systems (Kellogg 1997). However, surface water has the characteristic of being unevenly distributed (Dzhamalov et al. 2015; Zhou & Lim 2015; Kanakoudis et al. 2016). In addition, rapid population growth and economic development directly influence the state of the terrestrial water cycle (Vörösmarty et al. 2000). Further, water resources are vulnerable as a result of changes in land use and saltwater intrusion (Kanakoudis et al. 2017a, 2017b).

The fresh water per capita available in China is only about a quarter of the average global figure (Dabuxilatu et al. 2008). China is one of several countries with a severe shortage of fresh water (Tong et al. 2016). In northern China for example, the available fresh water is only 19% of the national average (Wang 2001; Geng 2011).

Changchun is one of the main cities in northern China, and is highly water-stressed (Zhou et al. 2011). The fresh water per capita is 16% of the national average (Liu 2008). The city is an important location for the automobile industry, with the largest production sites of the China First Automobile Works (FAW) Group Corporation and the Changchun Passenger Car Works being located in the city. Changchun is not only an industrial city, but also an agricultural city. Yushu and Nong'an counties, which are the top two grain-producing counties in China are also located in the region (Er 2015).

Water shortages have severely restricted the development of Changchun City (Jing 2000). However, with the economic development associated with the automobile industry, some of the population from the surrounding rural areas has moved to the urban area, and water shortage problems have become increasingly common (Shao 2005; Han & Zhou 2008; Lei et al. 2008).

Remote sensing offers the potential for spatial observations, which enable timely observation, multispectral analysis, and large and periodic coverage. Remote sensing has played an increasingly important role in the study of global environmental change (Jensen 1996; Richards 1999; Blaschke 2010). From observations of the water environment, Lyzenga (1978) proposed a method for extracting water depth and bottom type information using multispectral remote sensing data. The normalized difference water index (NDWI) was constructed by McFeeters (1996) based on the spectral characteristics of water, and can provide useful surface water information. The use of the NDWI has facilitated the use of surface water mapping (Xu 2006; Wang et al. 2008; Li et al. 2013).

Based on the available water volume and its spatial distribution, there is a need to determine effective policies for water use. Thus, to ensure the sustainable development of agriculture and industry in Changchun, the aim of this study was to monitor the availability of surface water through a combination of remote sensing and a geographic information system.

STUDY AREA

Changchun (Figure 1) is one of the main cities in northeastern China, and is the provincial capital of Jilin, which has a semi-arid continental climate. The total area of Changchun is 20,342.98 km2. The regions under its administrative jurisdiction are Changchun City and Dehui, Yushu, Nong'an, Jiutai, and Shuangyang counties. The mean annual precipitation is between 522 and 615 mm, with almost 70% of all rain occurring in summer (Changchun Municipal Bureau Statistics 2015). As a major base for the automotive industry and grain production, the FAW Group Corporation and the Changchun Passenger Car Works are located in the city, while the counties of Yushu and Nong'an have the largest grain output in China. The annual industrial water use is about 270 million m3 (Cao 2010), with 60% of water use being for agriculture, most of which is extracted from groundwater (Na & Yin 2012). This leads to environmental problems such as the pollution of surface water and groundwater. Furthermore, there has been a decline in the groundwater table and surface water has diminished, which has attracted widespread attention in recent times. To ensure the sustainability of water resources, there is an urgent need for the city to monitor and clarify the spatial distribution of surface water resources and to adopt policies through which water can be recycled.

Figure 1

Location map of Changchun.

Figure 1

Location map of Changchun.

SATELLITE DATA ACQUISITION AND PROCESSING

The Landsat 8 satellite data of the Operational Land Imager (OLI) and the Advanced Spaceborne Thermal Emission and Reflection (ASTER) radiometer global digital elevation map (GDEM) were used to monitor the availability of surface water on an annual basis.

The Landsat 8 satellite is one of the Landsat series and has been operational for 40 years. Landsat 8 was launched by NASA in February 2013. The OLI has nine wavelength bands for monitoring purposes (for band information see Table 1). Landsat 8 collects images of the entire earth with a 16 day repeat cycle. The data were downloaded from the United States Geological Survey (USGS) website (https://earthexplorer.usgs.gov/). In this study, for extraction of the surface water area and to determine the status of urban-industry and agriculture, the data sets for path 118 row 29, path 118 row 30, and path 119 row 29 were used. The date covered the whole of 2016. A total of 69 image scenes were used.

Table 1

Operational land imager (OLI) band information

Band name Band length (μm) Spatial resolution (m) 
Band 1 Coastal 0.433–0.453 30 
Band 2 Blue 0.450–0.515 30 
Band 3 Green 0.525–0.600 30 
Band 4 Red 0.630–0.680 30 
Band 5 NIR 0.845–0.885 30 
Band 6 SWIR1 1.560–1.660 30 
Band 7 SWIR2 2.100–2.300 30 
Band 8 Pan 0.500–0.680 15 
Band 9 Cirrus 1.360–1.390 30 
Band name Band length (μm) Spatial resolution (m) 
Band 1 Coastal 0.433–0.453 30 
Band 2 Blue 0.450–0.515 30 
Band 3 Green 0.525–0.600 30 
Band 4 Red 0.630–0.680 30 
Band 5 NIR 0.845–0.885 30 
Band 6 SWIR1 1.560–1.660 30 
Band 7 SWIR2 2.100–2.300 30 
Band 8 Pan 0.500–0.680 15 
Band 9 Cirrus 1.360–1.390 30 

The ASTER GDEM data were downloaded from the Geospatial Data Cloud (http://www.gscloud.cn/). This data set has spatial consistency with the Landsat 8 OLI, and its use makes it easier to calculate the volume of surface water.

The radiometric and atmospheric correction of the Landsat 8 OLI was conducted using ENVI image analysis software. The Landsat 8 OLI was used for the geometric correction of the ASTER GDEM using this software. The software was also used to clip the images of the Landsat 8 OLI and ASTER GDEM.

METHODS

Given that NDWI is useful for revealing water information (McFeeters 1996), it was used to determine the recent spatial distribution of surface water in Changchun. The NDWI was calculated using Formula (1). The ‘BGreen’ and ‘BNIR’ were obtained from the corresponding bands of the processed Landsat 8 OLI data. 
formula
(1)
For evaluating the status of the surface water for a whole year, the maximal value of the NDWI was computed. By band slicing, the surface water areas of Changchun were extracted when the maximal value of NDWI was greater than 0.1.

To determine the spatial extent of water shortages (water shortage force, i.e., the status of an uneven distribution of water resources), the volume of surface water was estimated (see Figure 2). First, a certain number of enclosed sub-surface water areas were separated from the extracted areas of surface water. Second, each sub-surface water area was assumed to be calm water and each pixel covered with a sub-surface water area was treated as a cube filled with water to calculate its volume. The length and width of the cube was 30 m. The altitude of the cube was calculated by the difference between the tallest height and the in-situ height in a cross-section of the sub-surface water area. The altitude of the tallest cube was estimated as 0.5 m (the altitude indicated the depth of an extracted pool).

Figure 2

Method used to estimate water volume.

Figure 2

Method used to estimate water volume.

Considering the range of surfaces in Changchun and to analyze the spatial surface water shortage force, a 5-km mesh grid, where the grid indicated the total water volume per 5 × 5 km, was constructed. The coefficient of surface water shortage force was considered to be one. Formula (2) was used to calculate the surface water shortage force per 5 × 5 km for the Changchun area. Because Changchun is extremely water deficient, the coefficient ‘’ was used to assess the relative surface water shortage force: 
formula
(2)
where is the coefficient of relative surface water shortage force, Vpixel is the value of the total water volume per 5 × 5 km, and Vtotal is the total surface water volume in Changchun.
The availability of surface water in agricultural and urban-industrial areas was also investigated. For arable land areas and urban-industrial areas, the seasonal changes of the maximal value of the normalized difference vegetation index (NDVI) (for the computational method refer to Formula (3); the ‘BNIR’ and ‘BRed’ were obtained from the band information from the processed Landsat 8 OLI data) and the NDWI were recorded. 
formula
(3)
These seasonal changes are shown in Figure 3. Given that ploughing begins at the end of May, and crops grow in summer (June to August), the maximal value of the NDVI in summer was four times greater than in spring for the arable land areas. The NDWI was less than 0 because the arable land was bare in spring. This feature was used for the extraction of the arable land areas. For the extraction of the urban-industrial areas, features whereby the NDWI was less than 0 in spring, summer, and autumn and greater than 0 in winter, and the NDVI was less than 0.1 in summer were deemed appropriate. This is because urban-industrial areas have little vegetation cover throughout the year, and generally have a higher temperature than vegetated land; hence, snow would have a greater tendency to melt in the winter.
Figure 3

Seasonal changes of the normalized difference vegetation index (NDVI) and the normalized difference water index (NDWI) for arable land areas and urban-industrial areas. The maximal values of the NDVI and NDWI for each season were calculated and the region of interest (ROI) for each type of land use was extracted. The values shown in the figure are the average values of each extracted ROI.

Figure 3

Seasonal changes of the normalized difference vegetation index (NDVI) and the normalized difference water index (NDWI) for arable land areas and urban-industrial areas. The maximal values of the NDVI and NDWI for each season were calculated and the region of interest (ROI) for each type of land use was extracted. The values shown in the figure are the average values of each extracted ROI.

The land use results were resampled to a 1-km mesh grid, in which the proportional land use per 1 × 1 km grid square could be determined (as the parameter ‘Spixel’). The maximal value for all grids for each land use type was used as the maximal scale (as the parameter ‘Smax’). The spatial surface water use force (the available extent of surface water for each type of land use) for agricultural and urban-industrial areas was estimated by Formula (4). The value of ‘’ was calculated as follows: 
formula
(4)

RESULTS AND DISCUSSION

The distribution of the extracted surface water, and urban-industrial and arable land are shown in Figures 4, 5(a) and 5(d), respectively. ArcGIS geospatial information analysis software was used to locate random points from within these results. Google Earth was used to verify the accuracy of the position of the random points. This information indicated the extent of the different types of land use. As shown in Figure 4, the ‘Statistical Yearbook of Changchun’ was also used to determine the volume of surface water. Although the extents of the Xinlicheng and Shitoumen reservoirs were underestimated, the surface water volume for the whole of Changchun was overestimated. This may be due to the volume calculation containing information for pools or paddy fields.

Figure 4

The volume and surface water shortage force of Changchun surface water.

Figure 4

The volume and surface water shortage force of Changchun surface water.

Figure 4 shows that the total volume of surface water was 18.23 × 109 m3, with most of it being located south of Changchun, where it is stored in reservoirs. Based on the upper right panel of Figure 4, it was established that 21% of the area of Changchun had little surface water. In the south of Changchun, Changchun City and Jiutai County had more surface water than the other areas of Changchun. In these two areas, the lowest volume of surface water per 5 km mesh was 450 m3. In the lower right of Figure 4, the equal interval method (a classification procedure of ArcGIS software) was used to divide the surface water shortage force into five levels. It was found that 99% of the area of Changchun had a surface water shortage force of level 5, suggesting likely surface water shortages. It was also found that 14% of the surface water was located in reservoirs that accounted for 0.1% of the area of the region, which was classed as level 1. Clearly, reservoirs are essential for relieving the surface water shortage force in Changchun.

From Figure 5, it was determined that the area of urban-industrial land was 176.3 km2 and the area of arable land was 10,206.3 km2 for Changchun. The equal interval method was also used to divide the level of surface water use force for each type of land use into five levels. It was found that 7% of the urban-industrial area had a surface water use force of level 5. In Changchun City, almost a third of the urban-industrial area had a surface water use force above level 4 (>0.60). It was also found that 34% of the urban-industrial area had a surface water use force of level 1. These areas were villages and did not contain dense urban residential areas.

Figure 5

Types of land use and their associated surface water use force: (a) urban-industrial areas; (b) proportional cover of urban-industrial areas in 1-km mesh grids; (c) urban-industrial surface water use force; (d) arable land areas; (e) proportional cover of arable land in 1-km mesh grids; (f) agricultural surface water use force.

Figure 5

Types of land use and their associated surface water use force: (a) urban-industrial areas; (b) proportional cover of urban-industrial areas in 1-km mesh grids; (c) urban-industrial surface water use force; (d) arable land areas; (e) proportional cover of arable land in 1-km mesh grids; (f) agricultural surface water use force.

For the agricultural surface water use force, 66% of the area was above level 4, with 24% of this area having the strongest surface water use force. A total of 12% of the arable land was located near to rivers and reservoirs, where the surface water use force was less than level 2 (<0.40).

CONCLUSIONS

Changchun is a major city in East Asia, and is both an industrial and agricultural base in China. The volume of surface water available to the city has restricted its development. To ensure the sustainable use of the region's surface water, this study determined the volume and distribution of the surface water resource. The results showed that the total volume of surface water was 18.23 × 109 m3, although 21% of the Changchun area had little surface water. Changchun City and Jiutai County had more surface water than other areas of Changchun. It was found that 14% of the surface water was contained in reservoirs, accounting for 0.1% of the region. To assess the current situation regarding surface water use for urban-industrial and agricultural purposes, the areas for urban-industrial and arable land use were extracted, and the proportional cover of each land use type per 1 km2 was determined to calculate the surface water use force. It was found that 7% of the urban-industrial area was located in areas of level 5 surface water use force. In Changchun City, the surface water use force in almost a third of the area was above level 4. It was found that 34% of the urban-industrial area had a surface water use force of level 1. These areas were villages and did not contain dense urban residential areas. For agricultural surface water use force, 66% of the area was above level 4, with 24% of this area having the strongest surface water use force. A total of 12% of the arable land was located near to rivers and reservoirs, where the surface water use force was less than level 2.

ACKNOWLEDGEMENTS

The study was funded by the Doctor Research Fund of Jilin Jianzhu University (No. 861181). We thank Charlesworth Author Services for linguistic assistance during the preparation of this manuscript.

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