1. Introduction
It is widely documented that changes in climate and land use are key factors that modify flow regimes [
1,
2]. On the one hand, climate variation, reflected by the rising temperature and evapotranspiration, as well as by the intensities and patterns of rainfall, is considered to have a significant impact on local, regional, and even global hydrological processes [
3]. For example, Mexico and Turkey have suffered much damage from decreasing precipitation [
4,
5]. Drought stress has increased in southern Europe due to greater atmospheric evaporative demand as a result of temperature rise [
6]. On the other hand, land use changes, primarily caused by human activities [
7], can influence water distribution along different hydrological pathways through vegetation interception, soil water infiltration, and streamflow, hence altering hydrological processes [
8]. One of the well-known examples of such land use change-induced effects in the world is the Aral Sea in Eurasia [
9,
10], where ~92% of the total water volume has been lost over the past four decades [
11]. This has been put down to large-scale irrigation water consumption due to the increase of paddy field areas [
12,
13]. In addition, the impact of land use on hydrological processes is also well-supported by the evidence from hydrological changes caused by dam construction [
14,
15]. It can be seen that the effect of climate variation and land use changes on hydrological regimes are significant, and that such effects will likely continue to increase. Therefore, there is a need to investigate the hydrological response to these two factors.
Many previous studies have focused on changes in hydrological processes induced by climate variation or land use change. For instance, streamflow variation is closely related to precipitation, temperature, and evapotranspiration. The response of streamflow to changes in precipitation has been shown to be more sensitive than to changes in temperature and evapotranspiration, despite the fact that the latter two factors can also increase or decrease streamflow [
16,
17,
18]. In terms of the effect of land use change on streamflow, rangeland makes a great contribution to streamflow decrease; in contrast, the expansion of cultivated and built-up land areas and the shrinking of forest areas will increase streamflow [
19,
20]. These findings show a consistency with the results reported by Nunes et al. [
21]. Although these studies have provided crucial insights into the ongoing changes in hydrological processes, they focus only on the qualitative evaluation of streamflow change with a single factor (either land use or climate). Few quantitative attempts have been made to thoroughly understand the effects of changes in climate and land use on hydrological process, because their contributions to hydrological alterations are difficult to separate and change over time.
According to previous studies, paired catchments have been widely studied to compare the impacts of climate (mainly precipitation and temperature) and human activities (mainly land use) on hydrological alteration. For instance, Huang et al. [
22] demonstrated that cumulative runoff yield in a afforestation watershed was reduced by 32% compared with that in a natural grassland watershed. Arrigoni et al. [
23] and Vogel et al. [
24] found that human activities had greater effects on the changes in streamflow and flood peaks in the United States. This method, however, requires a long duration and is only available in small catchments, since significant differences in the underlying surface exists in large catchments [
25]. In reality, it is also difficult to find a comparable catchment free of human influence for such an experiment. With further research, based on GIS technology, some physical-based hydrological models have been established and applied to identify the contribution of climate and land use to streamflow changes in a specific catchment. Such models include SWAT (Soil Water Assessment Tool) [
14], the Precipitation–Runoff Modeling System [
26], the BASINS (Better Assessment Science Integrating Point and Non-point Sources) model [
27], and MIKE (Alluvial River and Floodplain Model) [
28], which provide effective tools for promoting the development of hydrological research. However, too many parameters are needed to implement these models, involving hydrological, meteorological, remote sensing, and topographical details for hydrological study of long-time series. Anyway, the lack of standard paired catchments and sufficient data has partly impeded the development of hydrology. Consequently, an alternative is desirable to counter these deficiencies. The method proposed by Budyko [
29] based on water balance was a useful approach to normalize hydrological observation among a wide range of ecological and hydroclimatic conditions, and it could assess the secondary controls of climate, vegetation, and landscape on water balance at the watershed scale [
30,
31]. Although the Budyko framework was only meant to explain the long-term or mean annual water balance in a certain catchment, it has been developed to account for temporal and spatial variability [
32]. This method has been confirmed to be applicable in northern and southern China [
33,
34], though not in central China, especially in the hilly watershed.
Notable evidence of economic and demographic changes has been found in the hilly areas during the past decades [
35]. The hilly regions, especially in China, have suffered depopulation and abandonment of traditional farming practices because a large number of farmers have migrated to cities. The reduction in population and agricultural activities has negatively affected the extension and intensity of agricultural drainage systems, hence ditching and channelization activity has decreased accordingly [
36]. As a result, the lack of runoff controlling facilities (i.e., favorable drainage systems) and other conservation practices (i.e., afforestation) lead a hilly watershed to be less resilient to heavy rainfall and lead to the increased frequency of extreme events. As such, it is necessary to carry out research in hilly watershed areas.
Some attempts have been made to analyze the streamflow alteration caused by climate variation and land use change for the representative rivers worldwide, such as the Nile [
20], Amazon River [
37], Yangtze River [
38], and Yellow River [
39,
40]. Among these, more attention has been paid to the Yellow River in China. Many investigations have been dedicated to the primary tributaries (e.g., Weihe, Qinhe, and Wudinghe) [
41,
42,
43], while less have been dedicated to the smaller tributaries. Yihe River, a second-order tributary of the Yellow River originating from Xionger Mountain in Henan Province, China, is a typical hilly watershed. Great changes have taken place in terms of climate and land use in this watershed under the influence of global change and human activities [
44]. Zhang et al. [
45] found that the annual mean temperature in the 2000s was 1° higher than that in the 1980s in Luoyang City, in which the watershed is located. The annual mean precipitation presented a nearly 7% increase by the early 21st century, which also contributed to flood occurrence. Additionally, driven by socio-economic development, land use has undergone great changes in this watershed. For example, the increase in built-up land caused by a thriving tourism industry [
46] has altered the runoff-generation condition of the underlying surface, making hydrological processes much more complicated. Previous studies conducted within this watershed have made little progress on the driving force of landscape dynamics [
47], landscape simulation [
44], and the hydrological alteration induced by land use with the SWAT model and statistical analysis [
48]. Not only is there little research in this area, but the information on how much of the change in the historical streamflow record was caused by either climate variation or land use change is lacking. Therefore, the present study aims to thoroughly investigate the streamflow variation with a long-term time series in this hilly watershed, as well as provide some theoretical and methodological references for the study of same-scale hilly watersheds. The objectives of this study are (1) to investigate the spatiotemporal changes in streamflow, precipitation, and potential evapotranspiration with long historical data series, (2) to assess the sensitivity of streamflow to climatic factors and land use change, and (3) to quantify the contributions of climate variation and land use change to streamflow alteration.
4. Discussion
In the present study, a decrease in precipitation and an increase in
PET were found; these findings corresponded to the results of a study in northeast China reported by Li et al. [
61]. Apart from the decreasing trend in streamflow in this area, as revealed by Liang [
62], our study located the abrupt change point in the year 1985 for streamflow, suggesting that the streamflow has declined since 1985 when compared with that of the previous 26 years before 1985. The abrupt change analysis is in accordance with that of Dai et al. [
38], indicating that the change point occurred between the 1980s and 1990s. The two stations had similar trends in
P,
PET, and w despite the slight differences between them.
Although the change in streamflow was closely related to the variations of P and PET, land use changes also played an important role in streamflow alteration. In this section, we mainly focus on how the streamflow responds to land use change and climate variation based on our findings.
4.1. Land Use Change and Its Impact on Streamflow Decline
There was a small change in land use type from period I to period II (
Table 4). The cultivated and forest land were the dominant land use types, with cultivated land (forest land) showing a slight decrease (increase), while there was a noticeable increase in built-up area at a rate of 23.70%. The increase in such land revealed an increasing water requirement that could aggravate the conflict between water supply and demand. In addition, the increased built-up land was mainly from the decline in cultivated and forest areas (
Table 5), which affected the interception, infiltration, and evaporation of precipitation, hence altering streamflow.
Meanwhile, grassland was the third major land use type with an area of 389.01 km
2 in 1985 and an area of 350.73 km
2 in 2005. The grass land area decreased at a rate of 9.02%, mainly due to the transition to cropland and forest land with flow-out areas of 22.09 km
2 and 15.92 km
2 (
Table 5). This increased streamflow interception and infiltration to a certain extent, hence resulting in a greater decline for streamflow in period II (
Table 2). Additionally, the increasing water body area from 87.38 km
2 in 1985 to 95.63 km
2 in 2005 also contributed to the increase in evapotranspiration, thereby reducing streamflow [
55].
To further explore the impact of different land use types on streamflow before and after the change point over the study period, we only quantified the contributions of cultivated land, forest, grass, and built-up land to streamflow decline, considering the lower proportion of water body and unused land (
Table 6).
The impacts of different land use types on the reduction in streamflow were quite dissimilar. The contribution of forest land was the largest in both periods, followed by grass land, implying that forest and grass plays an important role in streamflow decline in the study. On the one hand, forest and grass areas occupied a larger proportion of the total area (
Table 4). On the other hand, the forest and grass cover increase the surface roughness, and thus intercept more precipitation, hence reducing surface streamflow.
However, the development of cultivated land and built-up land increases landscape fragmentation. In particular, the patchy distribution in relatively flat locations further decreased the slope streamflow by hindering the effective area for streamflow convergence, which was also slightly responsible for the reduction of streamflow (
Table 2) [
53], but this contribution was relatively small.
4.2. The Impact of Climate Variation on Streamflow Change
Generally, climate variation is the primary reason for streamflow alteration in the study area. This finding is in agreement with the results of a study conducted in northwestern China by Yin et al. [
63], indicating that the contribution of climate change to streamflow increase was 14.08%, while land use change only accounted for 7.12%. Precipitation was the major factor controlling streamflow change. The significant downward trend for the two stations (
Table 2) could be partly caused by the decline of precipitation, since precipitation and streamflow were well synchronized and they had a strong positive correlation [
53]. There was a significant upward trend for
PET in the whole period, which was consistent with the results from Zhang et al. [
56] and Piao et al. [
64], suggesting that most parts of China have been become warmer and
PET has increased accordingly in recent years. However, land use condition (
w) although showed an upward trend but without significance in different periods. This is primarily due to less interference of human activities on land use [
32], and the changes reported by Liang [
62], similar to those shown in
Table 4 and
Table 5, further confirm this. In general, the sensitivity of streamflow to
P was much greater than that to
PET and
w (
Table 2,
Figure 3), and the similar findings have been well documented by other researchers [
41,
58].
The attribution analysis indicated some differences between the two stations (
Table 3). It was found that the change in
P was still the major contributor to streamflow change, which also confirmed the proposition that the evolution of streamflow was mainly impacted by natural factors, especially precipitation [
65]. However, the precipitation change in Dongwan was greater than that in Luhun (
Table 2), while the streamflow variation induced by precipitation in Dongwan was smaller than that in Luhun (
Table 3). The possible reasons for this can be attributed to the different elevation and land use types. Dongwan is located in the upper part of the study area with high elevation (
Figure 1), which made streamflow more prone to flowing downhill [
66], whereas Luhun is located in the lower part of the study area accompanied by relatively flat terrain, with patchy distribution of grass and forest land (
Figure A1) contributing to increases in interception and infiltration. Moreover, the previous studies suggested that grass and forest played important roles in water-holding [
67,
68]. In addition, the reservoir located above the Luhun station intercepts the flow path, hence decreasing runoff downstream [
14]. The same holds true in the present study. Land use change in Dongwan and Luhun was responsible for 14.09 mm and 14.76 mm reductions in streamflow, respectively. The change in streamflow caused by
PET in Luhun (−17.76 mm and 24.45%) was greater than that in Dongwan (−13.53 mm and 25.25%), which was similar to
PET variation. This finding was in good agreement with the results of Ning et al. [
58] and Xu et al. [
32], indicating that streamflow has a negative relationship with
PET.
4.3. Uncertainty of Quantitative Assessment and Future Research
This study provides critical insight into the hydrological dynamics of the Yihe River watershed, but there are several limitations concerning the theoretical analysis. First, the available hydrological gauge stations and meteorological stations were limited; the results would be better if sub-basins could be divided to analyze the spatiotemporal change in streamflow in greater detail. For example, comparisons would be more evident if more ΔQp, ΔQpet, and ΔQw were found, hence more detailed information about streamflow and strategies can be detected and put forward. Secondly, the Budyko framework used in the present study is based on the assumption that land use change is independent from climate change, which may deviate from the fact that interactions are usually strong between the land and the climate system. In addition, the Budyko framework was mainly focused on long-term hydrology or climate changes at the annual scale. In fact, research on various time scales (such as monthly and seasonal scales) is also necessary, which requires further exploration. Thirdly, this study simplified the non-natural factors that affect streamflow into land use due to higher vegetation coverage and local land development, based on a field investigation. However, the comprehensive effects of a variety of specific non-natural factors involve many aspects, such as the implementation of water and soil conservation projects, the construction of dams, the Grain for Green program, etc. Therefore, in future work, more specific non-natural factors should be taken into account to further explore the isolated and joint effects of climate and non-natural factors on streamflow.
Although the streamflow alteration induced by land use change was not as noticeable as that reported in other research [
69], its importance in streamflow decline cannot be ignored. Streamflow can be effectively inhibited through the adjustment of land type and the optimization of its spatial distribution. For instance, converting the sloping cultivated land to terraces, or converting orchards to forests can substantially decrease streamflow, especially for hilly watershed areas [
70]. In addition, the parameters impacting climate change not only refer to
P and
PET but also include weed speed, relative humidity, and sunshine hours, therefore it would be better if the contribution of all the climate factors to streamflow change could be assessed in the future. It should be also acknowledged that the present study is a preliminarily tentative work for an attribution analysis of streamflow change. The impact of climate variation on streamflow is more evident than the impact of land use change but it is difficult to control, therefore more attention should be paid to land use optimization and management for the sustainable development of water resources.