Within China's Loess Plateau there have been concerted revegetation efforts and engineering measures since the 1950s aimed at reducing soil erosion and land degradation. As a result, annual streamflow, sediment yield, and sediment concentration have all decreased considerably. Human-induced land use/cover change (LUCC) was the dominant factor, contributing over 70 % of the sediment load reduction, whereas the contribution of precipitation was less than 30 %. In this study, we use 50-year time series data (1961–2011), showing decreasing trends in the annual sediment loads of 15 catchments, to generate spatio-temporal patterns in the effects of LUCC and precipitation variability on sediment yield. The space–time variability of sediment yield was expressed notionally as a product of two factors representing (i) the effect of precipitation and (ii) the fraction of treated land surface area. Under minimal LUCC, the square root of annual sediment yield varied linearly with precipitation, with the precipitation–sediment load relationship showing coherent spatial patterns amongst the catchments. As the LUCC increased and took effect, the changes in sediment yield pattern depended more on engineering measures and vegetation restoration campaign, and the within-year rainfall patterns (especially storm events) also played an important role. The effect of LUCC is expressed in terms of a sediment coefficient, i.e., the ratio of annual sediment yield to annual precipitation. Sediment coefficients showed a steady decrease over the study period, following a linear decreasing function of the fraction of treated land surface area. In this way, the study has brought out the separate roles of precipitation variability and LUCC in controlling spatio-temporal patterns of sediment yield at catchment scale.
Streamflow and sediment transport are important controls on biogeochemical processes that govern ecosystem health in river basins (Syvitski, 2003). Changes in soil erosion on landscapes and the resulting changes in sediment transport rates in rivers have great environmental and societal consequences, particularly since they can be brought about by climatic changes and human-induced land use/cover changes (LUCC) (Syvitski, 2003; Beechie et al., 2010). Understanding the dominant mechanisms behind such changes at different timescales and space scales is crucial to the development of strategies for sustainable land and water management in river basins (Wang et al., 2016).
In recent decades, streamflows and sediment yields in large rivers throughout the world have undergone substantial changes (Milly et al., 2005; Nilsson et al., 2005; Milliman et al., 2008; Cohen et al., 2014). Notable decreases in sediment yields have been observed in approximately 50 % of the world's rivers (Walling and Fang, 2003; Syvitski et al., 2005). Many studies have investigated the dynamics of streamflows and sediment yields at different spatial and temporal scales (Mutema et al., 2015; Song et al., 2016; Gao et al., 2016). In addition to climate variability, LUCC, soil and water conservation measures (SWCMs) and construction of reservoirs and dams have substantially contributed to the sediment load reductions (Walling, 2006; Milliman et al., 2008; Wang et al., 2011). While previous studies have certainly provided valuable insights into the streamflow and sediment load changes, the distinctive roles of LUCC and precipitation variability in changing sediment loads still need further investigation in large domains and across gradients of climate and land surface conditions (Walling, 2006; Mutema et al., 2015). A particularly useful approach to the development of generalizable understanding of the effects of precipitation variability and LUCC is a comparative analysis approach focused on extracting spatio-temporal patterns of sediment yields based on observations in multiple locations within the same region, or even across different regions. This is especially valuable and crucial in areas with severe soil erosion and fragile ecosystems, e.g., the Loess Plateau (LP) in China, which is the motivation for the work presented in this paper.
The LP lies in the middle reaches of the Yellow River (YR) basin, and
contributes nearly 90 % of the YR sediment (Wang et al., 2016). The
historically severe soil erosion in the LP is due to sparse vegetation,
intensive rainstorms, erodible loessial soil, steep topography, and a long
agricultural history (Rustomji et al., 2008). To control such severe soil
erosion, several SWCMs, including terrace and check-dam construction,
afforestation and pasture reestablishment, have been implemented since the
1950s (Yao et al., 2011; Zhao et al., 2017). A large ecological restoration
campaign, the Grain-for-Green (GFG) project converting farmland on slopes
that exceed 25
These substantial LUCC have notably altered the hydrological regimes of the LP in combination with the climate change. Consequently, the sediment yields within the LP have showed a predictable declining trend over the past 60 years (Zhao et al., 2017), resulting in approximately a 90 % decrease in sediment yield in the YR (Miao et al., 2010, 2011; Wang et al., 2016). Many other studies have detected the influences of LUCC and precipitation variability on sediment load changes within the LP. Rustomji et al. (2008) estimated that the contribution of catchment management practices to the decrease in annual sediment yield ranged between 64 and 89 % for 11 catchments in the LP during the 1950s to 2000. Zhao et al. (2017) examined the spatio-temporal variation of sediment yield from 1957 to 2012 across the LP, and indicated that the adoption of large-scale SWCMs led to significant reduction of sediment yield between Toudaoguai and Tongguan stations, and large reservoir operation played a critical role in sediment yield reduction between Tongguan and Huayuankou stations. Zhang et al. (2016) pointed out that the combined effects of climate aridity, engineering projects, and vegetation cover change-induced significant reductions of sediment yield between 1950 and 2008. Wang et al. (2016) found that engineering measures for soil and water conservation were the main factors for the sediment load decrease between the 1970s and 1990s, but large-scale vegetation restoration campaigns also played an important role in reducing soil erosion since the 1990s.
Location of the studied catchments in the Coarse Sandy Hilly Catchments (CSHC) region within the Loess Plateau.
On the basis of the outcomes of these studies, it is now generally accepted that the largest reductions of sediment yield within the LP resulted from LUCC. However, this is general knowledge covering the whole region, and given the significant variability of climate and catchment characteristics across the LP (Sun et al., 2015a, b), it is important to go further and explore how these might affect spatio-temporal patterns of sediment yield. Exploration of these patterns is important for sustainable ecosystem restoration and water resources planning and management within the LP. They will also serve as the basis for future research aimed at the development of a more generalizable understanding of landscape and climate controls on sediment yields at the catchment scale.
Most of the sediment yield of the LP was produced in the Coarse Sandy Hilly Catchments (CSHC) region (Fig. 1) located in the central region of the LP. The CSHC supplied over 70 % of the total sediment load in the YR, especially coarse sand (Rustomji et al., 2008). This region was the focus of our efforts to investigate the variation of sediment load from 15 catchments within the region within the LP. The specific objectives of this study were, therefore, to (1) attribute the temporal changes in sediment yield to changes in both precipitation variability and LUCC over the entire study period (1961–2011) within the CSHC region, (2) extract spatio-temporal trends in sediment yields on the basis of annual sediment yield data, and (3) separate the contributions of precipitation variability and the fractional area of LUCC to the observed spatio-temporal patterns of sediment yields, and pave the way for more detailed process-based studies in the future.
Long-term hydrometeorological characteristics (1961–2011) and growing season leaf area index (LAI) (1982–2011) of the studied catchments in the Loess Plateau.
Spatial distribution of
Annual precipitation, streamflow, and sediment load for the whole CSHC region during 1961–2011.
The CSHC region covers the area between the Toudaoguai and Longmen
hydrological stations in the main stream of the YR (Fig. 1). The main stream
that flows through the CSHC region is 733 km long and its drainage catchment
covers 12.97
Fourteen main catchments along a north–south transect within the CSHC study
area were chosen for the study (Fig. 1). These catchments account for
57.4 % of the CSHC area, and contribute about 70 and 72 % of the
streamflow and sediment load of the overall CSHC, respectively, based on
observed hydrological data during 1961–2011 (Rustomji et al., 2008; Yao et
al., 2011). Characteristics of these catchments are presented in Table 1 and
Fig. 2, showing that the catchments present strong climate and land surface
gradients. The catchments in the northwestern part (nos. 1–6) had relatively
lower mean annual precipitation (380 mm <
The entire CSHC region is considered as an additional “catchment”, and it
is also examined independently. The streamflow and sediment load for the
whole region were taken to be equal to the differences of corresponding
measurements between the Toudaoguai and Longmen gauging stations. The average
annual precipitation, streamflow, and sediment load of the region during
1961–2011 were 437.27 mm, 33.30 mm and 5.17 Gt, respectively. Both the
annual river discharge and sediment load across the region showed significant
decreasing trends (
Monthly streamflow and sediment load data during 1961–2011 were provided by
the Yellow River Conservancy Commission of China. Daily rainfall data from
1961 to 2011 at 66 meteorological stations in and around the region (Fig. 1)
were obtained from the National Meteorological Information Center of China.
The spatial average of rainfall data was calculated using the co-kriging
interpolation algorithm with the DEM as an additional input. The
hydro-meteorological data (including annual precipitation,
The mean catchment slope gradient based on the ASTER GDEM data with a
resolution of 30 m and soil data (scale
The non-parametric Mann–Kendall (M–K) test method proposed by Mann (1945)
and Kendall (1975) was used to determine the significance of the trends in
annual meteorological and hydrological time series. A precondition for using
the MK test is to remove the serial correlation of climatic and hydrological
series. In this study, the trend-tree pre-whitening (TFPW) method of Yue and
Wang (2002) was used to remove the auto-correlations before the trend test.
There was no residual autocorrelation remaining after performing the TFPW. A
Land use and cover of the study area in
The changes in soil and water conservation measures area and growing season LAI in the study area.
The time-trend analysis method was used to determine the quantitative
contributions of LUCC and precipitation variability to sediment yield
changes. This method is primarily designed to determine the differences in
hydrological time series between different periods (reference and validation
periods) with different LUCC conditions (Zhang et al., 2011). In this method,
a regression equation between precipitation and sediment yield is developed
and evaluated during the reference period, and the established equation is
then used to estimate sediment yield during the validation period. The
difference between measured and predicted sediment yields during the
validation period represents the effects of LUCC, and the residual changes
are caused by precipitation variability. The governing equations of the
time-trend analysis method can be expressed as
Long-term trends in growing season LAI changes over
The CSHC region has undergone extensive LUCC caused by the implementation of
SWCM and vegetation restoration projects (e.g., the GFG project). Figure 4
shows the distribution of land use types of the region in 1975, 1990, 2000,
and 2010. More than 90 % of the whole area was occupied by the cropland,
forestland, and grassland. The area of cropland decreased by 26.72 % and
forestland increased by 53.15 %, and there was no significant change for
the area of grassland (increase of 4.21 %) in the CSHC region from 1975
to 2010. The majority of changes occurred during 2000–2010 due to the GFG
(reforestation) project (26.67 % decrease and 36.21 % increase for
cropland and forestland, respectively). The transition from cropland to
forestland was greater in the catchments of the southeastern part (especially
in catchment nos. 7–9) than that in the northwestern part (Fig. 4). In the
period 1975–2000, the increase in forestland was 26.34 and 4.55 % in the
southeastern and northwestern parts, respectively, and the change in cropland
was negligible (only
The SWCMs implemented in the LP included both biotic treatments (e.g., afforestation and grass-planting) and engineering measures (e.g., construction of terrace and check-dam and gully control projects). Afforestation, grass-planting, and construction of terraces were seen as the slope measures, while building of check-dams and gully control projects were the measures on the river channel. Although the area utilized for engineering measures was much smaller than the biotic treatments, they immediately and substantially trap streamflow and sediment load. The fraction of the treated area (area treated by erosion control measures relative to total catchment area) increased from 3.95 % in the 1960s to 28.61 % in the 2000s (Fig. 5). The increase in the treated area was greatest during the 1980s as a result of comprehensive management of small watersheds and the 2000s due to the GFG project since 1999. Some decreases in SWCM areas (i.e., afforestation and check-dams) occurred during the 1990s (Fig. 5) as some planted trees died due to drought and some small and medium check-dams were fully deposited by sediment and then subsequently destroyed by floods.
The growing season LAI of the whole region changed from 0.74 during
1982–1999 to 0.81 during 2000–2011, an increase of 10.16 % (Fig. 5).
The LAI did not show a significant increase during 1982–1999
(0.003 yr
Mann–Kendall trend analysis results for the annual precipitation
(
The changes in
Table 2 shows the trends in annual
The mean and the coefficient of variation,
The linear regression equations between the square root of specific
sediment yield and annual precipitation (
Contributions of precipitation and land use/cover to reductions of
sediment load from
Spatial distribution of slope
The effects of precipitation change and LUCC on sediment yield reductions in period-2 and period-3 were quantified using Eqs. (2)–(6) and the results are shown in Fig. 8. The form of Eq. (5) during the reference period is shown in Table 3. The analysis showed that both decreased precipitation and increased area treated with erosion control measures contributed to the observed sediment load reduction, and that LUCC played the major role. On average, LUCC and precipitation change contributed 74.39 and 25.61 %, respectively, to sediment load reduction from the reference period to period-2, with their respective contributions to sediment load reduction from the reference period to period-3 being 88.67 and 11.33 %. The effect of LUCC in period-3 was greater than in period-2 as the land use/cover (see Figs. 4–5) and vegetation coverage (see Fig. 6) had undergone substantial changes due to the ecological restoration campaigns launched during period-3. From period-2 to period-3, the contribution of precipitation was negative for sediment yield reduction in 11 catchments where the annual precipitation slightly increased, and thus the contribution of LUCC was larger than 100 % (Fig. 8c). In the remaining four catchments, the average contribution of LUCC increased to 83.96 %.
The regression models for sediment yield change (
In broad terms there are two factors that govern the annual sediment yield of a catchment: precipitation and landscape properties (soil, topography, and vegetation). Precipitation is the primary driver of runoff and, therefore, directly influences the sediment transport capacity of streamflow and sediment yield at the catchment scale. Higher precipitation means higher streamflow, which is the immediate driver of erosion and sediment transport. Landscape properties not only have an impact on the volume or intensity of streamflow, but also determine the erodibility of the soil. Correlations between the potential factors (precipitation, percentage area of afforestation, pasture plantation, terracing, check-dams and construction land, and LAI) and sediment yield change between different stages (see Table 4) showed that check-dam construction was the dominant factor for sediment yield reduction from the reference period to period-2. Pasture plantation and check-dam construction acted as the dominant factors for sediment yield from the reference period to period-3. The increase in precipitation mitigated the reduction of sediment yield to some degree from period-2 to period-3.
Based on the above results, the variation of SSY mainly depended on precipitation in the reference period before LUCC took effect and any spatial patterns of SSY in the catchments were controlled by differences in annual precipitation and land surface conditions. During the validation period (period-2 and period-3) when increased LUCC had taken effect, SSY decreased considerably. The decrease in precipitation was insignificant and LUCC contributed over 70 % of the sediment yield reduction. In this case, the temporal changes in SSY depended more on the fraction of treated surface area, and precipitation possibly played a secondary role. The spatial pattern of the impacts of precipitation on sediment yield was dependent on the landscape properties among catchments. Guided by this framework, data were next analyzed to generate separate spatial and temporal patterns constituting respective components of the spatio-temporal patterns.
The regression equations of
Compared to the reference period, the correlation between precipitation and
sediment yield during period-2 decreased in the catchments, as indicated by
lower
During period-3, the correlation between precipitation and sediment yield was
weaker compared to the reference period and period-2 (Table 3). The
relationships between precipitation and sediment yield were not significant
in all the catchments (Table 3). The slopes of the regression lines during
period-3 decreased sharply (Table 3). Six catchments (five in the
northwestern part and one in the southeastern part) had negative regression
slopes (Fig. 9c). This result indicates that the sediment production
capability of annual precipitation decreased greatly during period-3, and the
increase in precipitation amount in some catchments did not lead to increased
sediment yield. Furthermore, the spatial patterns of the
precipitation–sediment relationship during period-3 were clearly different
from those during the reference period and period-2 (compare Fig. 9c against
Fig. 9a–b). There were only three groups, with two catchments having
regression slopes of 0.1 <
Regression equations between the decadal sediment coefficient and
percentage of the area affected by soil and water conservation measures
(
The aforementioned analysis of the precipitation–sediment yield relationship in different periods clearly indicates that the impacts of precipitation on sediment yield declined with time. The impacts were different among catchments, with a clear spatial pattern. The effects of precipitation on the sediment yield were greater in the northwestern part compared to those in the southeastern part. The decreased effects of precipitation on sediment yield with time were consistent with the significant reductions of sediment coefficient (Table 2) and the decreased contribution of precipitation to sediment load reduction (25.61 and 11.33 % in period-2 and period-3, respectively). During period-2, the LUCC were mainly induced by SWCM, especially engineering measures. During period-3, the combined effects of substantial vegetation cover and conservation measures further weakened the effects of precipitation on sediment load reduction.
Spatial distribution of slope
Daily precipitation and sediment load of the Yanhe catchment during
the rainy season (May–October) in
In order to quantify the effects of SWCM on sediment load reduction, the
relationships between the decadal sediment coefficient and the fraction of
area treated with erosion control measures in the 15 catchments were analyzed
and the results are presented in Table 5. The decadal sediment coefficient
(
Pearson correlation coefficients (
Differences in catchment characteristics, including land use/cover, soil properties, and topography, as well as precipitation characteristics, are clearly the reason for the spatial patterns in the precipitation–sediment yield relationship (Morera et al., 2013; Mutema et al., 2015). The lower vegetation cover was the main reason for the greater effects of precipitation on sediment yield in the northwestern part. In order to fully explore this, the mapping of information of catchment characteristics into sediment yield models and simulations under different climate scenarios would be needed (Ma et al., 2014; Achete et al., 2015). In this context, the inter-annual and intra-annual patterns of variability of precipitation, including the distribution of storm events, may also contribute to the observed spatial patterns of the precipitation–sediment yield relationship.
As LUCC took effect during period-2 and period-3, and despite the much
reduced role of precipitation in driving changes in sediment yield,
within-year temporal rainfall patterns did play an important role in the
observed changes in sediment yield, given that most of the sediment yield was
produced during a few key storm events. The correlation between sediment
yield and storm events with a daily precipitation amount larger than 20 mm
(including storm numbers, precipitation amount of storms) in the CSHC region
during different decades was investigated (see Table 6). The analysis showed
that the sediment yield was significantly correlated with storm numbers in
the 1960s, 1970s, and 1980s (
Looking into this in more detail and taking the Yanhe catchment as an
example, the precipitation amount during the rainy season (May–October when
sediment load was measured) in 2003 and 2004 was 514.31 and 389.05 mm,
respectively, whereas the sediment load in 2004
(2427.37
The sediment load reductions in the CSHC region were primarily caused by the
LUCC and the implementation of SWCMs. The cropland area decreased by
9733.91 km
Through analyses of hydrological and sediment transport data, this study has shown long-term decreasing trends in sediment loads across 15 large sub-catchments located in the CSHC region for the period 1961–2011. The study was particularly aimed at extracting spatio-temporal patterns of sediment yield and attributing these patterns to the broad hydro-climatic and landscape controls. The effects of precipitation variability and land use/cover changes on sediment yield were investigated in detail.
Over the study period, the total area undergoing erosion control treatment went up from only 4 % to over 30 %. This included a decrease in cropland by 27 %, and an increase in forestland by 53 % and grassland by 4 % from 1975 to 2010. Over the same period annual precipitation decreased by no more than 10 %. As a result of the erosion control measures, there were major reductions in streamflow (65 %), sediment yield (88 %), sediment concentration (68 %), and sediment efficiency, i.e., annual sediment yield/annual precipitation (86 %) over the entire 50-year period.
The observed data in the 15 study catchments also exhibited interesting spatio-temporal patterns in sediment yield. The study attempted to separate the relative contributions of annual precipitation and LUCC to these spatio-temporal patterns. Before LUCC took effect, the data indicate a linear relationship between the square root of annual sediment yield and annual precipitation in all 15 catchments, with highly variable slopes of the relationship between the catchments, which exhibited systematic spatial patterns, in spite of some scatter. As LUCC increased and took effect, the scatter increased and the slopes of the sediment yield vs. precipitation relationship became highly variable and lost any predictive power. The study then looked at the controls on sediment coefficient instead of sediment yield, thus eliminating the effect of precipitation and enabling a direct focus on landscape controls. The results of this analysis found that the sediment coefficient was heavily dependent on the area under land use/cover treatment, exhibiting a linear decreasing relationship. Even here, there was a considerable variation in the slope of the relationship between the 15 catchments, which exhibited a systematic spatial pattern.
Preliminary analyses presented in this study suggest that much of the sediment yield in the LP may be caused during only a few major storms. Therefore, the seasonality and intra-annual variability of precipitation may play important roles in annual sediment yield, which may also explain the spatial patterns of sediment yield and the effects of the various LUCC. Also, the precipitation threshold for producing sediment yield would have increased greatly as a result of SWCM and vegetation restoration in the LP. Exploration of these questions in detail will require a more physically based model that can account for fine-scale rainfall variability and catchment characteristics. This is the next immediate step in our investigations, and will be reported on in the near future.
All the data used in this study are available upon request.
The authors declare that they have no conflict of interest.
This research was funded by the National Key Research and Development Program of China (no. 2016YFC0501602), the National Natural Science Foundation of China (no. 41471094), the Chinese Academy of Sciences (no. GJHZ 1502), and the Youth Innovation Promotion Association CAS (no. 2016040). We thank the Ecological Environment Database of Loess Plateau, the Yellow River Conservancy Commission, and the National Meteorological Information Center for providing the hydrological and meteorological data. We thank the three anonymous reviewers for their valuable and detailed comments which greatly improved the quality of this paper. Edited by: Nunzio Romano Reviewed by: three anonymous referees