HESSHydrology and Earth System SciencesHESSHydrol. Earth Syst. Sci.1607-7938Copernicus PublicationsGöttingen, Germany10.5194/hess-20-13-2016Effects of cultivation and reforestation on suspended sediment
concentrations: a case study in a mountainous catchment in ChinaFangN. F.ChenF. X.ZhangH. Y.WangY. X.ShiZ. H.shizhihua70@gmail.comState Key Laboratory of Soil Erosion and Dryland Farming on the
Loess Plateau, Northwest A & F University, Yangling 712100, People's Republic of ChinaInstitute of Soil and Water Conservation of Chinese Academy of
Sciences and Ministry of Water Resources, Yangling 712100, People's Republic of ChinaCollege of Resources and Environment, Huazhong Agricultural
University, Wuhan 430070, People's Republic of ChinaZ. H. Shi (shizhihua70@gmail.com)15January201620113252July20157August201530November201520December2015This work is licensed under a Creative Commons Attribution 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/3.0/This article is available from https://hess.copernicus.org/articles/.htmlThe full text article is available as a PDF file from https://hess.copernicus.org/articles/.pdf
Understanding how sediment concentrations vary with land use/cover is
critical for evaluating the current and future impacts of human activities on
river systems. This paper presents suspended sediment concentration
(SSC) dynamics and the relationship between SSC and discharge (Q) in
the 8973 km2 Du catchment and its sub-catchment (4635 km2). In
the Du catchment and its sub-catchment, 4235 and 3980 paired SSC–Q
samples, respectively, were collected over 30 years. Under the influence of
the Household Contract Responsibility System and Grain-for-Green projects in
China, three periods were designated, the original period (1980s),
cultivation period (1990s) and reforestation period (2000s). The results of a
Mann–Kendall test showed that rainfall slightly increased during the study
years; however, the annual discharge and sediment load significantly
decreased. The annual suspended sediment yield of the Du catchment varied
between 1.3 × 108 and 1.0 × 1010 kg, and that of
the sub-catchment varied between 6.3 × 107 and
4.3 × 109 kg. The SSCs in the catchment and sub-catchment
fluctuated between 1 and 22400 g m-3 and between 1 and
31800 g m-3, respectively. The mean SSC of the Du catchment was
relatively stable during the three periods (±83 g m-3). ANOVA
(analysis of variance) indicated that the SSC did not significantly change under
cultivation for low and moderate flows, but was significantly different under
high flow during reforestation of the Du catchment. The SSC in the
sub-catchment was more variable, and the mean SSC in the sub-catchment varied
from 1058 ± 2217 g m-3 in the 1980s to
1256 ± 2496 g m-3 in the 1990s and 891 ± 1558 g m-3
in the 2000s. Reforestation significantly decreased the SSCs during low and
moderate flows, whereas cultivation increased the SSCs during high flow.
The sediment rating curves showed a stable relationship between the SSC and
Q in the Du catchment during the three periods. However, the SSC–Q of
the sub-catchment exhibited scattered relationships during the original and
cultivation periods and a more linear relationship during the reforestation
period.
Introduction
Suspended sediment is conventionally regarded as sediment that is transported
by a fluid and is fine enough to remain suspended in turbulent eddies
(Parsons et al., 2015). Suspended sediment plays important roles in the
hydraulics, hydrology and ecology of rivers (Luo et al., 2013). Land
use/cover is thought to affect hydrology and suspended sediment yield (SSY)
(Van Rompaey et al., 2002; Casalí et al., 2010). Although many studies
have assumed that forest cover is an effective method for controlling
sediment yield throughout the world (e.g., Mount et al., 2005; Hopmans and
Bren, 2007; Garzía-Ruiz et al., 2008; Stickler et al., 2009; Verbist et
al., 2010; Lü et al., 2015; Wei et al., 2015), other studies have
disagreed (e.g., Mizugaki et al., 2008; Ide et al., 2009). Additionally, many
studies have implicated farmland as a major contributor of sediments (Gafur
et al., 2003; Shi et al., 2004; Izaurralde et al., 2007; Cerdan et al.,
2010). However, whether changes in land use/cover alter soil loss by changing
the runoff volume or by changing the suspended sediment concentration (SSC)
has received little attention. The relationships between SSC and discharge
(Q have been discussed using sediment rating curves (Walling, 1977), a
fuzzy logic model (Kisi et al., 2006), artificial neural networks (Liu et
al., 2013) and other multivariate regression methods (Francke et al., 2008).
SSCs are highly variable and can vary over many orders of magnitude during
storm events (Naden and Cooper, 1999; Cooper, 2002; Fang et al., 2012). The
mean annual/monthly SSC fails to capture the highly episodic nature of
sediment transport because > 90 % of the sediment load can be
transported in < 10 % of the time (Collins et al., 2011).
Morehead et al. (2003) indicated that the suspended sediment load carried by
rivers varies spatially and temporally and that sediment rating curve
parameters can exhibit time-dependent trends. Warrick et al. (2013) concluded
that the discharge and sediment relationships from six coastal rivers varied
substantially with time in response to land use. In most studies, SSYs were
calculated using SSCs and Q. However, little work has focused on the
effects of land use/cover change on SSCs.
China contains 22 % of the world's population but only 7 % of the
world's croplands (Liu and Diamond, 2005). In China, erosion by water
affects an area of 3.6 × 106 km2, or approximately 37 %
of the country's land area (Ni et al., 2008). Thus, soil erosion has become
an important topic for local and national policy makers. In the 1980s, a
policy called the Household Contract Responsibility System was
implemented in China's rural areas. Consequently, more land was reclaimed
for farming. In the late 1999s, the Grain-for-Green project was introduced
to increase forest and grassland cover. To combat soil erosion on sloped
croplands, farmland with slopes > 25∘ was restored. The
farmers, who agreed to stop cultivating these lands received subsidies to
cover their losses (Gao et al., 2012). Before this project, subtropical
zones with adequate rainfall were often over-exploited due to economic and
demographic pressures. Cultivation of steeply sloping lands in subtropical
areas can result in serious soil erosion during intense rainfall (Fang et
al., 2012). In this study, a mountainous catchment and its sub-catchment
were investigated and analyzed in detail. This catchment is located in the
Danjiangkou reservoir area, which is a source area in the Middle Route Project under the South–North Water Transfer Scheme (the largest water
transfer project in the world). The study catchment has experienced
cultivation and reforestation periods. The first part of this study focuses
on how cultivation and reforestation affect Q, SSC and SSY at different timescales. Then, we discuss the dual roles of cultivation and reforestation
that affect the relationship between SSC and Q. Finally, the SSC dynamics in the
catchment and sub-catchment were determined under land use/cover changes.
Study area and methodsStudy area
This study was conducted in the Du catchment
(31∘30′–32∘37′ N,
109∘11′–110∘25′ E), which is located in Hubei Province,
China, and covers an area of 8973 km2 (Fig. 1). Elevations within the
watershed range from 245 to 3002 m. The sub-catchment (Xinzhou catchment) is
located in the northwest region of the Du catchment and covers an area of
4635 km2. The topography in the Du catchment is undulating and is
characterized by mountain ranges, steep slopes and a subtropical climate with
a mean temperature of 15 ∘C. The mean annual precipitation in this
region is approximately 1000 mm, with 80 % of the precipitation
occurring between May and September. The major soil types include yellow to
brown soils,
Chao soils and purple soils (National Soil Survey Office, 1992), which
correspond to Alfisols, Entisols and Inceptisols, respectively, according to
USDA Soil Taxonomy (Soil Survey Staff, 1999). The major crops in this region
are corn (Zea mays L.) and wheat (Triticum aestivum L.).
There were 1002 villages with total population of 1.9 × 106 based on
the fifth population census of China in 2000.
Location of study area.
Land use/cover change
The land cover was digitized as part of a previous research project.
Reconnaissance field surveys were conducted in 2007. A watershed topographic
map was used in combination with 1999 ETM (enhanced thematic mapper) photographs and Landsat imagery from
1987 and 2007. The land use/cover units were delineated on the photographs
and verified in the field. We assigned the periods of the 1980s, 1990s, and
2000s to original, cultivation, and reforestation periods, respectively. The
areas of the various types of land use/cover are presented in Tables 1 and 2.
In 1987, forestland, farmland, and shrubland covered areas of 6316 km2
(70.4 %), 919 km2 (10.2 %) and 929 km2 (10.4 %),
respectively. The other land use/cover types covered small areas and included
barren land (0.4 %), grassland (7.3 %), urban land (0.9 %), and
water bodies (0.4 %) (Table 1). During the 2000s, some steep lands with
slopes of more than 25∘ were converted to forestland. The area of
forestland increased to 75.2 % in 2007, whereas the area of farmland
decreased to 6.1 % (Fig. 2). The sub-catchment experienced a similar
change in farmland, which increased from 11.5 % in 1987 to 14.7 % in
1999 and decreased to 6.7 % in 2007. However, the change in forestland in
the sub-catchment was different from that in the Du catchment, in which
forestland increased from 66.3 % in 1987 to 67.9 % in 1999 and
74.0 % in 2007 (Table 2).
Land use/cover type and change ratio during 1978–2007 in the Du
catchment
All of the hydrological data were obtained from the Hubei Provincial Water Resources Bureau. Two gauge stations (Zhushan and Xinzhou) and seven weather
stations (nearly evenly distributed) are located in the study catchment. The
yearly average rainfall measured at three weather stations in Xinzhou was
very similar to the mean rainfall measured at the seven weather stations.
Therefore, we used the average annual values of rainfall obtained from the
seven stations for the Zhushan and Xinzhou stations. A continuously
recording water-level stage recorder and a silt sampler (metal type) were
used to record discharge and sediment (complemented by manual samples),
respectively. The water stage was measured and transformed into discharge by
using the calibrated rating curve obtained through periodic flow
measurements. SSCs were determined using the gravimetric method, in which water
samples were vacuum filtered through a 0.45 µm filter and the residue
was oven dried at 105 ∘C for 24 h. The weight of each dried
residue and the initial sample volume were used to obtain the SSC (g m-3).
Next, the SSY was calculated from the SSC and Q. During a month, the total SSY was the
sum SSY of each event. Monthly SSC was calculated by monthly SSY and Q. During
rainfall events, the sampling measurement frequency was increased several
times each day. Paired SSC–Q data were obtained during rainfall–runoff events.
Because bed-load measurements were not performed in this area, this study
does not consider bed-load sediment transport. From 1980 to 2009, 4235
paired SSC–Q samples were collected at the Zhushan station and 3980 samples were
collected at the Xinzhou station. This study uses several variables, and
their meanings and abbreviations are shown in Table 3. To distinguish
between the variables of the two gauges, we used Qd, Dd, SSYd and SSCd for the Zhushan
station (Du catchment) and Qx, Dx, SSYx and SSCx for the Xinzhou station (sub-catchment).
The variables for D, SSYi and SSY are calculated as follows:
D=Q/A,SSYi=SSCi×Qi,SSY=∫1nSSYi,
where A is the area of the catchment and SSYi, SSCi and Qi are the
suspended sediment yield, suspended sediment concentration and discharge
during period i, respectively.
Variables and associated abbreviations used in the statistical
analysis.
AbbreviationsVariablesUnitsPRainfallmmQStreamflowm3 s-1DDischarge depthmmSSYSuspended sediment yieldkg or g s-1SSCSuspended sediment concentrationkg m-3 or g m-3Statistical analyses
The Mann–Kendall test, which was proposed by Mann (1945) and Kendall (1975),
was used to identify trends in P, Q and SSY during the 30-year study period. The
S statistic was calculated as follows:
S=∑i=1n-1∑j=i+1nsgnxj-xi,
where n is the number of data points, xi and xj are the respective
data values in the time series i and j (j > 1), and
sgn(xj-xi) is the sign function (Gao et al., 2012), which is
determined as follows:
sgnxj-xi=+1,ifxj-xi>00,ifxj-xi=0-1,ifxj-xi<0.
The variance is computed as
VARS=118nn-12n+5-∑i=1qtiti-12ti+5,
where n is the number of data points, q is the number of tied groups and
ti is the number of data values in the ith group. The standard test
statistic, Z, is computed as follows:
Z=S-1VARSifS>00ifS=0S+1VARSifS<0.
A positive value of Z indicates an upward trend, and a negative value of Z
indicates a downward trend. We use the threshold of ±1.96 for
significant difference (Gao et al., 2012). The Mann–Kendall statistical test
has frequently been used to quantify the significance of trends in
hydro-meteorological time series (Gocic and Trajkovic, 2013).
To discuss relationships between SSC and Q, hydrologists often use sediment rating
curves. The most common approach is to fit a power curve to the normal data
(Khanchoul et al., 2008) as follows:
SSC=αQβ.
Here, αand β are constants in the non-linear regression
equation. The non-linear model assumes that the dependent variable (SSC) has a
constant variance (scatter), which typically does not occur because the
scatter around the regression generally increases with increasing Q
(Harrington and Harrington, 2013). The Mann–Kendall test was performed in
MATLAB 7.0.
ResultsStreamflow and sediment yield during different periods
Figure 3 shows the annual P, D and SSY for the hydrological years of 1980–2009
from the Zhushan and Xinzhou gauges. The annual P fluctuated between 665 and
1219 mm. The annual Dd and Dx varied between 253 to 873 mm and 279 to 931 mm,
respectively. The annual SSY varied between 1.3 × 108 and
1.0 × 1010 kg yr-1 from the Zhushan gauge and between
6.3 × 107 and 4.3 × 109 kg yr-1from the
Xinzhou gauge. To identify the relationships between the annual P, Dd, Dx, SSYd and SSYx, we
generated a Pearson's correlation matrix, as shown in Fig. 4. The analysis
showed significant correlations between all of the variables (n= 30,
p < 0.0001). During the low-flow years (e.g., 1997 or 2001), SSYd was
similar to SSYx. However, during the high-flow years (e.g., 1983 or 2005), SSYd was
several times greater than SSYx.
Annual P, D and SSY for the hydrological years of 1980–2009 from the
Zhushan and Xinzhou gauges.
Bivariate scatter-plot matrix of selected variables.
The Mann–Kendall test was applied to the annual P, D and SSY data for 1980–2009.
The test shows a decreasing but not significant trend for P, a significant
(5 % level) decreasing trend for Qd, and highly significant decreasing
trends for Qx, SSYx and SSYd (1 % level) (Fig. 5). After 2000, P shows an increasing
trend and Q and SSY show decreasing trends.
Results of the Mann–Kendall test.
To better understand the dynamics of Q and SSC, Tables 4 and 5 compare the
observed average monthly Q and SSC among the three periods monitored at the
Zhushan and Xinzhou gauges.
During 1980s–1990s, the annual Qd showed a decreasing trend (Table 4), with
only 3 of 12 months showing a slightly increasing trend. The rate of
decrease varied from -3.3 to -53.0 %. In addition, Qx exhibited a
decreasing trend that was similar to that of Qd during the same period. During
1990s–2000s, Qd greatly increased from 1 to 34 % during 9 of 12 months.
Meanwhile, Qx increased over 8 months and fluctuated between 10 % and
42 %. During 1990s–2000s, Qd and Qx both exhibited a more obvious increasing
trend during the winter than during the flow seasons.
Monthly mean streamflow from the Xinzhou and Zhushan gauges.
Note: C1 is the change for 1990–1980; C2 is the change for 2000–1990.
Table 5 shows the monthly mean SSC from the two gauges. SSCd decreased (-1 to
-66 %) during the flow seasons (May to September), except in August, when
it slightly increased (2 %) during 1980s–1990s. The decrease of SSCd did not
coincide with that of Qd. During 1990s–2000s, the decrease in SSCd was more
obvious than that in 1980s–1990s. In all, 8 of 10 months experienced a
decreasing change, and the change over 7 months was > -40 %.
In addition, the SSCx decreased over 6 months and increased during
the other 4 months during 1980s–1990s. During 1990s–2000s, the SSCx decreased
over 7 months, and 4 out of 5 months showed a decreasing trend
during the flow season. However, the monthly SSC is calculated by SSY and Q and is
not the actual SSC. To better understand SSC dynamics, paired SSC–Q data collected by
monitoring should be discussed.
Monthly mean suspended sediment concentration from the Xinzhou and
Zhushan gauges.
Note: C1 is the change for 1990s–1980s; C2 is the change for 2000s–1990s.
Suspended sediment primarily loads during the flow season. Rainfall is rare
in the winter (Dec, Nov and Jan), and the streamflow is dominated by a base
flow; thus, in most years, there is no suspended sediment load.
Figure 6 shows the statistical characteristics of the SSC and Q during the three
periods. The mean SSCd was relatively stable during the three periods (±83 g m-3),
and the mean SSCx varied from 1058 g m-3 in the 1980s to 1256 g m-3
in the 1990s and then decreased to 891 g m-3 in the 2000s.
In the 1980s, the max SSCd and max SSCx were 22400 and 31800 g m-3,
respectively. Next, the max SSCd shape decreased to 20 000 g m-3 during
the 1990s and to 17800 g m-3 during the 2000s. Meanwhile, the max
SSCx decreased to 26 900 and 19 200 g m-3 during the 1990s and 2000s,
respectively. The max Qx was more variable than the max Qd and
was 12 400 g m-3 in the 1980s, 3610 g m-3 in the 1990s and 3010 g m-3 in
the 2000s. However, the rate of change of the mean Qx was similar to that of
the mean Qd.
Descriptive statistics of Q and SSC.
Figure 7 shows that the SSCs varied by several orders of magnitude for a given
discharge at both gauges. SSCd and SSCx fluctuated between 1 and 22 400 g m-3
and between 1 and 31 800 g m-3, respectively. The maximum SSCx (31 800 g m-3)
was larger than the maximum SSCd (21 400 g m-3). In Fig. 7,
SSCd-Qd maintained a stable relationship during the three periods (1980s, 1990s and
2000s). However, SSCx-Qx showed a scattered relationship from 1980s and 1990s and
showed a more liner relationship from 2000s. During the three periods, the
max Qd decreased from 9880 to 6140 and 5070 m-3 s-1, respectively.
Meanwhile, the max Qx was reduced from 5960 to 3580 and 2990 m-3 s-1, respectively.
SSC–Q relationships during the three periods for the two gauges.
The relationship between SSC and Q is complicated. To better understand the
dynamics of SSC, SSC was sorted by ranking the paired Q values, which were
classified using a threshold level approach (e.g., low flow (Q≤ 25 %),
moderate flow (25 < Q < 75 %), and high flow (Q≥ 75 %).
The SSC dynamics were compared under different flow regimes. For the
sub-catchment, the thresholds were 188 and 674 m3 s-1 for the
minimum 25 % and maximum 25 %, respectively. For Qd, the thresholds of the
minimum and maximum 25 % were 332 and 1100 m3 s-1, respectively.
Figure 8 presents box plots for SSCd and SSCx during the three periods for the three
flow grades. The box plots indicate the maximum, 75, 50 and 25 %, and
minimum values for each SSC (outliers are excluded). For the sub-catchment,
SSCx increased between the original period and the cultivation period for
moderate and high flow, but not for low flow. Then, SSCx decreased during the
reforestation period for all flows. At the Zhushan station, SSCd was larger
during the cultivation period for both moderate and high flows. During the
reforestation period, the SSCd during low flow was higher than during the other
periods.
Box plots of SSC.
Six ANOVA tests were performed using SSC as the dependent variable and using
the different periods (land use) as independent variables. ANOVA was only
conducted for the same flow during different periods. One-way ANOVA (Table 6)
revealed that SSCx showed significant differences among the different periods
for all three types of flows (p < 0.001). However, a significant
difference in SSCd was only observed among high flows (p < 0.001). No
statistically significant differences were observed among the SSCd values during
the different periods for low or moderate flows.
Mean SSC values and one-way ANOVA of SSCs during the different
periods.
Note: ANOVA was only conducted for the same flow during different periods;
* means significant difference at α= 0.05.
Discussion
Land use/cover has been widely documented to have dire environmental
consequences through their adverse impacts on soil and water qualities (Zhang
et al., 2015). Olang et al. (2014) indicated that 40 % and 51 of forest
and agriculture land revealed reduced runoff volumes by about 12 %, while
86 % land cover of agriculture increased runoff volumes by about
12 %. Buendia et al. (2015) studied the effects of afforestation on
runoff at a Pyrenean Basin (2807 km2), and the results showed that an
increase ranging between 19 % and 57 % in the forest of sub-basins
accounted for ∼ 40 % of the observed decrease in annual runoff. Liu
et al. (2014) demonstrated that afforestation leads to increased runoff in
dry seasons in the Yarlung Zangbo River basin. In this study, land use/cover
changes significantly affect Q and SSY (Tables 4 and 5). During the
cultivation period, an increase in farmland resulted in an obvious decreasing
trend in Q in the Du catchment and its sub-catchment. The sediment
concentration in the direct runoff from a slope consists of a combination of
the sediment stored on the slope and that generated by flow erosion during
the current rainfall event (Aksoy and Kavvas, 2005; Rankinen et al., 2010).
Large storms generate sufficient surface runoff to deliver sediment from the
uplands to the stream. In forest catchments overflow typically occurs only in
a small fraction of the catchment, and it is most likely to occur very close
to the stream (Underwood et al., 2015). Reforestation may increased the
return period of peak flow and peak sediment yield (Keesstra, 2007). Borrelli
et al. (2015) illustrated that a disturbed forest sector could produce about
74 % more net erosion than a 9 times larger, undisturbed forest sector.
High SSCs are not detected in the absence of a high-flow velocity to carry
the suspended sediment to the outlet of a catchment. SSCs are determined by
onsite sediment production and the connectivity of sediment sources to the
channel. Sediment delivered to the channel can be deposited (Keesstra et al.,
2009). When runoff is decreased, its erodibility is reduced (Bakker et al.,
2008; Van Rompaey et al., 2002). Reduced streamflow can reduce the sediment
transport capacity and increase the probability for further sediment
deposition in the river (Zhu et al., 2015). Human-induced modifications of
land use/cover in river basins may cause strong geomorphic responses by
disturbing sediment supply, transport and deposition processes (Liébault
et al., 2005).
Hydrological studies rely on the analysis of processes at different spatial
scales (García-Ruiz et al., 2008). Sediment yield and watershed areas
have been elucidated in many studies (e.g., Renschler and Harbor, 2002; de
Vente and Poesen, 2013). The mean SSC was stable during the study years in
the Du catchment, and the mean SSC varied in the sub-catchment. The increase
in Qx was larger than the increase in Qd. The monitored sub-catchment
covered approximately half of the entire catchment. Likewise, the combined
mean annual discharge volume of the sub-catchment was nearly half of the
total catchment output (i.e., a deficit of approximately 50 % at the
outlet). However, the SSC dynamics were more variable. Due to sediment
delivery problems, sediment is generated on catchment slopes and is either
stored on the surface or removed (Rankinen et al., 2010). Only a fraction of
the gross soil erosion within a catchment will reach the outlet and be
represented in the sediment yield. In addition, streamflow erodes the
sediment directly from the surface or causes channel erosion, which removes
the stored surface layer of detached sediment.
Our previous study in Du catchment showed that the area scale dominates the
sediment delivery ratio (Shi et al., 2014). The sediment stored in the
gullies is flushed to the river when a certain threshold is exceeded, and
the deposition of sediment in channels is flushed at higher discharges. The
max SSCx is greater than the max SSCd (31 800 vs. 22 400 g m-3). One possible
explanation is that the sediment stock is depleted during a flood; this
process does
not occur simultaneously within the entire river basin and results in
gradually decreasing SSCs downstream (Doomen et al., 2008). Cultivation or
reforestation alters the slope surfaces but does not remove gullies and
channels. The SSCs in Zhushan were only significantly different during high-flow and the reforestation period when the forest cover greatly increased.
Conclusions
This study investigated Q and SSC dynamics for 30 years under cultivation and
reforestation. The results of a Mann–Kendall test showed that rainfall
slightly increased during the study years; however, the annual discharge and
sediment load significantly decreased. The sediment flux is extremely
spatially and temporally variable. The relationship between SSC and Q is
complicated. Reforestation caused significant differences in the SSC for both
low and moderate flows. For low and moderate flow, the changes in SSY primarily
resulted from runoff, while the SSC showed little change. For the
sub-catchment, the changes in the SSC were more sensitive to land use/cover
changes. Meanwhile, cultivation resulted in significant differences in the
SSC for high flow. Overall, our results provide useful information regarding
SSC dynamics relative to land use/cover changes in mountainous catchments in a
subtropical climate, which have largely been undocumented in the literature.
Acknowledgements
Financial support for this research was provided by the National Natural
Science Foundation of China (41525003 and 41301294), and the Fundamental
Research Funds for the Central Universities (2014YB053).
Edited by: M. Mikos
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