1. Introduction
Mountain rivers are important corridors that link upland and lowland environments and mediate the supply, transport, andstorage of organic and inorganic materials [
1,
2]. Mountain rivers play an important role in flood control and perform other functions, such as conserving water resources, regulating the microclimate, and maintaining water ecology and biodiversity. However, they often face problems such as short-term flood responses, water shortages in the dry season, and river channel artificialization [
3].
Mountain rivers are often confined by immobiletopographic features, such as bedrock and large boulders with channel gradients commonly exceeding 1% [
2,
4,
5]. This leads to these types of rivershaving steep hydraulic rating curves that initiate rapid transport of small sand and gravel fractions within the large structural matrix formed by large, century-scale floods nested within an even larger geological context [
2,
6]. Stream network characteristics are the basic parameters of hydrological and water environment research, as well as one of the important contents of terrain analysis and hydrological analysis. A stream network is a conduit that links the upstream catchment processes and its impacts on the downstream streams and floodplains [
7]. The stream network structure is established through its branches, confluence and bifurcation. Basin parameters, such as river type, drainage density (
Dd), stream number and length, affect the process of rainfall and runoff [
8]. While
Dd is defined as the ratio of total channellength in a catchment to the total catchment area [
9], it is a scale-independent parameter that is influenced by the accurate representation of topography, which is primarily represented in the form of digital elevation models (DEMs). A plethora of studies have sought to understand how the resolution of topographic data governs basin parameters [
7,
10,
11,
12] and the algorithm for extraction of river networks, including the flow direction algorithm and convergence threshold determination [
8,
13]. In fact, river network structuresand their embedded hydrological dynamics play an important role in ecohydrological processes [
14]. Therefore, after obtaining stream networks from DEMs, further studies need to reveal the relationship between the features of extracted drainage networks and other natural factors based on the widely available and easily accessible DEM, the significance of the characteristics of stream networks in typical rivers and how the underlying geomorphic processes governing the initiation, growth and development of channel networks, not just how the features of the DEMs affect stream networks, for example, the resolution.
The mountain rivers in China are seasonal and have the following characteristics [
15]: they have steep slopes with short runoff generation and confluence times [
16]; they are subject to serious soil and water erosion, which increases the pressure on river flood controls [
17]; and they are associated with strong river channel scouring, simple river channel forms and vegetation, and severe riverbed erosion [
18]; and they experience cold, long winters, low rainfall with uneven seasonal distribution, and severe non-point source pollution that is difficult to control during flood and snowmelt periods [
3].
The plan to construct the Xiongan New Area, which was reported by China’s Central Committee and State Council, is regarded as “a strategy crucial for the millennium to come” by the Chinese government (
http://politics.people.com.cn/GB/n1/2017/0401/c1001-29185929.html, in Chinese; access date: 8 October 2021). The Xiongan New Area prioritizes eco-environmental protection and green living environments. One noticeable characteristic of Xiongan is that it is located next to Baiyangdian Lake, the largest natural freshwater wetland on the semiarid North China Plain (NCP), which is known as the “Pearl of North China” and the “Kidney of North China” [
19,
20,
21]. The lake is located in the middle and lower reaches of the Daqing River basin, which is a typical mountain basin in northern China and has an important impact on the central North China Plain in terms of climate regulation and environmental characteristics [
22]. Due to the steep terrain, thin soil cover, poor vegetation and fan-shaped tributary distribution of the area and the characteristics of high intensity, short duration, uneven distribution and sudden occurrence of the storm events that occur in the Daqing River basin, floods with high and concentrated peaks with short lead timesare often triggered [
23], which easily cause significant flooding and serious soil erosion. The New Area is located in a region of slow flooding and stagnation on the Daqing River, and its current flood recurrence period is only one in ten years; the area has suffered many flood disasters [
24]. Sudden flash floods cause a large amount of coarse sand gravel to pile up in the downstream channel, destroying villages, burying farmland and causing siltation of river channels, which all bring considerable economic losses to the local people.
Previous studies about the Daqing River focus on the water environment (Xu and Wang, 2000) and the runoff and sediment characteristics [
25,
26,
27,
28]. Therefore, the objective of this paper is to study the characteristics of drainage networks and watershed geometry of the mountain watersheds of the Daqing River; the relations of drainage density with topography, vegetation coverage and surface material composition; and discuss the implications of indices of drainage network and watershed geometry for water yield and watershed evolution. Our results may provide some basic watershed characteristic data for other scholars in this basin study and a reference for further study of the water cycle process and effective utilization of water resources in the Daqing River basin and a scientific basis for the formulation of flood control policies and water conservation in the Xiongan New Area.
2. Study Area
The Daqing River is a primary tributary of the Haihe River in northern China and is located at 113°34′3″–117°46′7″ E, 38°4′42″–40°3′2″ N. The area of the watershed is 43,060 km
2, with a length of 275 km, an average width of 156 km and an average slope of 5.22%. The average annual runoff is 4.3 × 10
8 m
3. According to the Water Resource Zoning Map of the Haihe River basin, provided by the Haihe River Water Conservancy Commission (HRWCC), the Daqing River basin mainly consists of two geomorphic units: the upper reaches of the west are mountainous areas thataccount for 43% of the basin area, and the middle and lower reaches of the east are plains areas (
Figure 1).The river basin is fan-shaped and divided into northern and southern branches. The southern branches of the mountain basin are mainly composed of six tributaries, including the Ci River (CIR), Sha River (SR), Tang River (TR), Jie River (JR), Cao River (CR) and Bao River (BR). After entering the plain, the Ci River and Sha River converge into the Zhulong River. The northern branches are mainly composed of four tributaries, namely, the Zhongyi River (ZYR), Beiyi River (BYR), Juma River (JMR) and Dashi River (DSR). After entering the plain, the Juma River divides into two branches, namely, the Beijuma River and Nanjuma River. These ten tributaries flow into Baiyangdian Lake. The terrain of the basin is higher in the northwest and lower in the southeast, with an elevation difference of nearly 2800 m (
Figure 1).
The Daqing River has a warm temperate monsoon climate with distinct seasons and an uneven distribution of precipitation during the year that is mainly concentrated from July–September. The average annual rainfall ranges from 500–700 mm and often comes in the form of heavy rain in July and August. The exposed lithology on the surface includes granite gneiss, limestone and loose quaternary deposits. The landform is dominated by mountains and basins. Coarse bone soilis the main soil in the mountains and loess covers the hill platform around the basin [
29].
4. Results and Discussion
Because of the small mountainous area of the Bao River, we extracted the river network and watershed boundaries of the other nine tributaries in mountainous areas from a DEM, including the Ci River, Sha River, Tang River, Jie River, Cao River, Zhongyi River, Beiyi River, Juma River and Dashi River (
Figure 2).
4.1. Watershed Geometry
Many watershed geometry features are related to the drainage area [
43].We analyzed the correlation between the main stream length (
L, km) and area (
A, km
2) (
Figure 3), relief (
H, m/km) and
A (
Figure 4). Both relationships were power exponents, and the variation of trends were significant (
L =
aAb,
b = 0.64–1.87,
R2 = 0.95–0.99,
p < 0.01;
H =
cAd,
d = −1.36–−0.33,
R2 = 0.82–0.99,
p < 0.01); namely, with the increase of area, the main stream length increases and relief decreases significantly, respectively. If
L was proportional to
A0.5, the geometric morphology upstream was similar to that downstream [
44]. As shown in
Figure 3,
L and
A were positively correlated, but the minimum
b value was 0.64, which was greater than 0.5. Therefore, we believe that the basin forms of the mountain watersheds in the Daqing River change along the channel. With the increase in basin area, the basins became longer.
H and
A were negatively correlated, and the relief changed more slowly with increasing basin area. From
Figure 3 and
Figure 4, except for the Dashi River, the
b value and
d value of the other eight rivers were close, which means that their basins had similar forms.
There are many indices expressing the basin shape [
44], but only two parameters are widely used. They are the circularity ratio and elongation ratio (
Table 1).The circularity ratio (
Rc) and elongation ratio (
Re) were additional parameters that were used to describe the watershed geometry morphology. If the drainage basin shape is round, the value of
Rc and
Re should be equal to 1 and 1.275, respectively; if the shape is square,
Rc and
Re should be 0.785 and 1.128. With the increase in stream length,
Rc continues to decease and
Re approaches zero, and the shape becomes narrower and longer [
32,
33]. The
Rc of mountain watersheds in the Daqing River ranged from 0.14 to 0.36, and the values of
Re were 0.36–0.94. We can conclude that the basin shape of the mountain watersheds in the Daqing River was narrow. According to Liu [
45], the flood confluence time is short for a narrow basin. Therefore, the small basin circularity ratio of the Daqing River is favorable to the formation of high flood peaks, which easily delivered a large amount of runoff from the basins during the rainy day to the Xiongan New Area.
4.2. River Network Morphology
As mentioned above, the upper and lower reaches of the Daiqing River have distinctive landforms. In the lower reaches of the Daiqing River, there are no tributaries on both banks. Thus, the river network morphological characteristics of the upper reaches of the Daiqing River, including river bifurcation ratio and drainage density were analyzed here.
4.2.1. Stream Order
The ordering scheme proposed by Strahler [
43] was used here. The bifurcation ratio
Rb =
Nu/
Nu+1, where
Nu and
Nu+1 denote the number of stream segments of order
u and
u+1, respectively. Watersheds with different natural geographical conditions tend to have different drainage bifurcation ratios [
46]. For the watersheds in flat or hilly and gully regions, the
Rb is close to 2; for the watersheds in mountainous regions, it is 3–5. The
Rb in the mountain area is larger than that in the plain area. The
Rb grows with the development of a drainage system [
44].
Strahler [
43] pointed that, except for the areas with hard geological substrata, the differences of
Rb between regions were small. Morisawa [
47] proved that the
Rb in fifteen small watersheds on the Appalachian Plateau was close to a constant. Therefore, the average drainage bifurcation ratio is the most reasonable parameter to reflect the drainage structure.
We ordered the extracted drainage network using the Strahler criterion [
43]; namely, the primary finger-tip stream is the order I, and the new stream formed by the convergence of the two order I streams is the order II, and in this way, the streams in the whole basin will be ordered until the end. The channel that flows through the whole basin with the amount of water and sediment is called the highest order stream. Therefore, the stream orders of the mountain watersheds in the Daqing River ranged from five to seven. Specifically, the upper reaches of the Jie River and Beiyishui River were 5th-order streams, Ci River, Cao River and Dashi River were 6th-order streams, and the other four rivers were 7th-order streams. The average bifurcation ratio of nine rivers was calculated according to the stream order results. For mountain watersheds, the bifurcation ratio ranged from 3–4. The bifurcation ratio of areas with loose rocks, sparse vegetation, and heavy rainfall was high [
46]. The average bifurcation ratio of those nine mountain watersheds was 3.8–4.8. In other words, the order of the
u + 1 rivers in each basin of the Daqing River was on average 4 times larger than that of order
u rivers.
4.2.2. Drainage Density
The drainage density of mountain watersheds in the Daqing River ranged from 2–2.3 km/km
2, and the spatial difference was small. According to the method mentioned above, we obtained a spatially continuous distribution of drainage density (
Figure 5).
Dd can be divided into four areas, including 0–1 km/km
2, 1–2 km/km
2, 2–3 km/km
2 and above 3 km/km
2. For mountain watersheds in the Daqing River,
Dd was mainly distributed from 1–2 km/km
2 and 2–3 km/km
2; specifically, the distribution areas of the southern watersheds fluctuated little, and the average distribution area of 1–2 km/km
2 and 2–3 km/km
2 was 71%. The 1–2 km/km
2 distribution area of the Juma River and Dashi River in northern watersheds increased significantly, and the average distribution area from 2–3 km/km
2 was 68%.
4.3. Relationship between Dd and Rainfall and Vegetation Cover
Collins and Bras [
40] summarized the feedback of vegetation and runoff under varying mean annual precipitation levels in a schematic representation showing an initial increase in drainage density in arid areas, followed by a decrease in semiarid regions and an increase in humid environments.
We drew rainfall and
Dd with SPSS as follows:
Dd = −0.001
xrainfall + 2.501 (
R = 0.542,
N = 9,
p = 0.132). Rainfall is negatively correlated with drainage density, which agrees with the results of Collins and Bras [
40] in semiarid regions, but the correlation between them did not show no significance at the 0.05 level. Although rainfall is the driving force behind gully development, for the small areas of mountain watersheds in the Daqing River, the average spatial variation in rainfall is not obvious.
Based on the change in NDVI in the upper reaches of each watershed in 2018, the correlation between the NVDI and drainage density was analyzed, and the correlation equation was obtained by SPSS as
Dd = −0.198x
NDVI + 1.227 (
R = 0.738,
N =9,
p = 0.02). This indicated that gullies developed in places with poor vegetation cover but not in places with good vegetation cover. Of course, it is difficult to determine the causal relationship between these factors because there may be a positive feedback mechanism; that is, the development of gullies in places with poor vegetation is conducive to the development of gullies, while the development of gullies, strong erosion and soil erosion inhibit the growth of vegetation [
8].
4.4. Relationship between Dd and Soil Type
Basin lithology affects the extent of landscape dissection. Some variation in
Dd by lithology type was also observed; the average
Dd for shale and schist was well above the observed mean
Dd, whereas the values for limestone and acidic volcanic rocks were well below the mean
Dd [
48]. The national soil database was used to obtain the classification of surface substances in the Daqing River (according to the classification standard of FAO90). The extracted river networks in the study area were superimposed on the soil type, and the distribution of gullies on each soil type was analyzed. The drainage density of each soil type was calculated (
Figure 6). There are seven types of surface materials in mountain watersheds of the Daqing River, namely, cambisols (CM), luvisols (LV), regosols (RG), fluvisols (FL), leptosols (LP), anthrosols (Atc) and gleysols (Glm). The proportional distribution area of each soil type and the percentages of sand, silt and clay are shown in
Figure 6. The main soil types in the mountain watersheds of the Daqing River were CM, LV and RG, with a distribution area of 91%. These three soil types all had a high content of sand gradation, approximately 50%, followed by silt. Clay made up the lowest proportion of the soil content, at approximately 20%.
Dd was the lowest in Glm (1.15 km/km
2) and the highest in FL (2.54 km/km
2). For the other soil types,
Dd was between 2 and 2.5 km/km
2. If soil particles are coarse and the permeability of the soil is high, the soil corrosion factor K value is low [
49]. Melton [
50] also found that
Dd decreased with soil infiltration capacity.
Figure 6 shows that the coarse gradation content of FL was the highest, at 85.5%. Thus, we can explain why the
Dd of FL was the largest. The ability to resist soil erosion influences
Dd. In addition, although the sand content of Atc was low, the
Dd as relatively high, at 2.44 km/km
2. It can be concluded that soil erosion is affected not only by soil properties but also by anthropic factors.
4.5. The Drainage Density and Terrain
4.5.1. The Drainage Density on Different Slopes
The drainage density on different slopes is of particular interest as it helps to understand the relationship between erosion rates and patterns of channelization, which are critical for testing eco-geomorphic landscape evolution models [
38,
51].
Except for the maximum slope of the Juma River, which was 47°, the slopes of all other river basins were below 42°. We divided the slope into seven grades: 0–6°, 6–12°, 12–18°, 18–24°, 24–30°, 30–36° and over 36°. We calculated the distributions of gullies on different slope grades (
Figure 7). The
Dd in each study area decreased with increasing slope; there were no gullies with slopes higher than 36° in the Ci River, Jie River, Cao River, Zhongyi River or Beiyi River. In addition, the slopes of the Juma River and Dashi River mainly ranged from 6–18°, and the slopes in the other research areas were mainly distributed in the range from 0–12°, accounting for 62–81% of the whole mountain area. All gullies were concentrated between 0° and 12°, and the density value was above 2 km/km
2. When the slope was greater than 24°, the value of
Dd decreased to 0.8 km/km
2 and below. The maximum
Dd of all rivers was between 0 and 6°, but the value of maximum
Dd was different.
Dd was highest in the Dashi River (4.1 km/km
2), followed by the Juma River (3.6 km/km
2), and the rest of the rivers were all approximately 3.0 km/km
2. The
Dd values were high in the north and low in the south.
4.5.2. The Drainage Density in Different Aspect of Slopes
Aspect is an important terrain factor. Some studies have shown that the differences of rainstorms, rainfall erosivity, soil moisture and vegetation growth conditions make the soil erosion pattern and intensity in different aspects have obvious asymmetry [
52]. For revealing the impacts of aspects on drainage development in the Daqing River, we divided the slope aspect into north (N), northeast (NE), east (E), southeast (SE), south (S), southwest (SW), west (W) and northwest (NW). There were differences in
Dd on each aspect. The maximum
Dd was 2.45 km/km
2, and the minimum was 1.63 km/km
2 (
Figure 8). SPSS was used to compare and test the average
Dd of each aspect, and they had values of 2.16 km/km
2 (N), 2.08 km/km
2 (NE), 2.03 km/km
2 (E), 2.02 km/km
2 (SE), 2.10 km/km
2 (S), 2.20 km/km
2 (SW), 2.16 km/km
2(W) and 2.07 km/km
2 (NW). In the formation process of the gullies, there was a directivity of upstream erosion, subdivision of gullies and development of branches. Relatively speaking, the gullies in the southwest, north and west developed considerably, while gullies in the east and southeast did not develop much. The measurement coefficient of the linear correlation between drainage density and aspect was 0.44,
p = 0.042 < 0.05, which passed the significance test. This indicated that aspect influenced drainage density, but the two did not have a simply linear relationship. This is because the difference in aspect results in differences in other influencing factors, such as rainfall and solar radiation, and the change in vegetation growth caused by different solar radiation leads to different development and evolution of erosion gullies [
52].
4.6. Indicative Significance of Dd
As shown in
Figure 9, the
HI values in the mountain basins of the Daqing River were all below 0.4. The correlation between
HI and
Dd was significant (
R = 0.87,
p = 0.015), but these factors were not simply linearly related. With the increase in
HI,
Dd first decreased and then increased. With 0.3 as the boundary, the closer
HI was to 0.3, the smaller
Dd was, and conversely, the larger
Dd is. It was concluded that the landform of the mountain basin of the Daqing River is in an advanced stage of erosion development and that
Dd will no longer increase [
35].
4.7. Effect of Channel Morphology on Water Yield
The measured runoff data of the Ci River, Sha River, Tang River, Cao River, Zhongyi River, Juma River and Dashi River were analyzed. Based on SPSS, the relationship between A and the water yield modulus (Sr, 104 t/km2•a) was Sr = 5962.3/A + 7.3 (R = 0.421, N = 7, p = 0.346). The relationship between Re and Sr was Sr = −528.6Re3 + 457.5Re − 140.7 (R = 0.714, N = 7, p = 0.202). According to the above two equations, although the correlation coefficient between Sr and A and Re was not low, neither of them passed the significance level of 0.05.
The relationship between the slope of the channel (S, %) and Sr was Sr = e3.6−24.13/S (R = 0.78, N = 7, p = 0.039). There was a significant positive correlation between these factors, that is, the greater the slope was, the greater the water yield.
Drainage density is not only an important index of watershed erosion but also an important factor affecting catchment confluence and sediment transport in gullies. The relationship between
Dd and
Sr was
Sr = 21.5
Dd − 33.27 (
R = 0.214,
N = 7,
p = 0.645). The water yield modulus was proportional to the drainage density; that is, the water yield modulus increased as the drainage density increased. Melton [
50] also observed that
Dd increased with increasing percentage of bare ground and runoff, but in this region, the two were not significantly correlated.
In addition, the impacts of other factors, such as rainfall, relief, slope gradient, etc., may produce large deviations in the constructed relations between specific water yield and indices of basin geometry, so the small number of available data samples do not prove the influence of basin geometry on water yield.
5. Conclusions
Based on the DEM, which had a resolution of 30 m, we extracted the river network of nine mountain watersheds in the Daqing River. The shape of the mountain watersheds in the Daqing River was narrow. The stream orders ranged from five to seven. The average bifurcation ratio was 3.8–4.8. The drainage density was in the range from 2–2.3 km/km2, and there was low spatial variation.
Although rainfall is the driving force of gully development, for the small areas of mountain watersheds in the Daqing River, the average spatial variation of rainfall is not obvious. Rainfall was negatively correlated with drainage density, but the correlation between them was not significant at the 0.05 level. The correlation between NVDI and Dd indicated that gullies developed in places with poor vegetation cover but not in places with good vegetation cover. Dd decreased with increasing slope; it was highest in the Dashi River (4.1 km/km2), followed by the Juma River (3.6 km/km2), and the rest of the rivers had values of approximately 3.0 km/km2. Dd values were high in the north and low in the south. The gullies in the southwest, north and west developed considerably, while gullies in the east and southeast did not develop much.
With 0.3 as the boundary, the closer HI was to 0.3, the smaller drainage density was, and conversely, the larger drainage density was. The landform of mountain basins in the Daqing River was in an advanced stage of erosion development, and the drainage density is no longer increasing. In addition, there was a significant positive correlation between the channel slope and water yield modulus, and the other watershed parameters were not significantly correlated with the yield modulus.