Differences in hydrological responses for different vegetation types on a steep slope on the Loess Plateau, China

Extensive vegetation restoration practices have been implemented to control soil erosion on the Loess Plateau, China. However, no strict guidelines are available to determine the most suitable plant species for vegetation restoration within a given area. The objective of this study was to quantify the changes of each component (soil water storage, surface runoff, and actual evapotranspiration) of a water balance model and soil loss over time under eight different vegetation types, and to further determine the optimal vegetation type for soil and water conservation and sustainable ecological restoration on the steep slopes (&gt;25 ) on the Loess Plateau. The results indicated that vegetation type substantially affected soil water storage and that the greatest soil water storage in both the shallow (0&ndash;2 m) and the deep soil layers (2&ndash;5 m) occurred under Bothriochloa ischaemum L. (BOI). Vegetation type also affected surface runoff and soil losses. The most effective vegetation types for reducing soil erosion were BOI and Sea-buckthorn (Hippophae rhamnoides L.), while Chinese pine (Pinus tabulaeformis Carr.) and Chinese pine + Black locust (Robinia pseudoacacia L.) were the most ineffective types. Soil water dynamics and evapotranspiration varied considerably among the different vegetation types. A soil water surplus was only found under BOI, while insufficient water replenishment existed under the other seven vegetation types. The higher water consumption rates of the seven vegetation types could result in soil desiccation, which could lead to severe water stresses that would adversely affect plant growth. This study suggested that both vegetation type and its effect on controlling soil erosion should be considered when implementing vegetation restoration and that BOI should be highly recommended for vegetation restoration on the steep slopes of the Loess Plateau. A similar approach to the one used in this study could be applied to other regions of the world confronted by the same problems of water scarcity along with the need for vegetation restoration.</div

Relative Importance of Land Use and Climate Change on Hydrology in Agricultural Watershed of Southern China

Quantitative assessment of the impact of land use and climate change on hydrological processes is of great importance to water resources planning and management. The main objective of this study was to quantitatively assess the response of runoff to land use and climate change in the Zhengshui River Basin of Southern China, a heavily used agricultural basin. The Soil and Water Assessment Tool (SWAT) was used to simulate the river runoff for the Zhengshui River Basin. Specifically, a soil database was constructed based on field work and laboratory experiments as input data for the SWAT model. Following SWAT calibration, simulated results were compared with observed runoff data for the period 2006 to 2013. The Nash-Sutcliffe Efficiency Coefficient (NSE) and the correlation coefficient (R2) for the comparisons were greater than 0.80, indicating close agreement. The calibrated models were applied to simulate monthly runoff in 1990 and 2010 for four scenarios with different land use and climate conditions. Climate change played a dominant role affecting runoff of this basin, with climate change decreasing simulated runoff by &minus;100.22% in 2010 compared to that of 1990, land use change increasing runoff in this basin by 0.20% and the combination of climate change and land use change decreasing runoff by 60.8m3/s. The decrease of forestland area and the corresponding increase of developed land and cultivated land area led to the small increase in runoff associated with land use change. The influence of precipitation on runoff was greater than temperature. The soil database used to model runoff with the SWAT model for the basin was constructed using a combination of field investigation and laboratory experiments, and simulations of runoff based on that new soil database more closely matched observations of runoff than simulations based on the generic Harmonized World Soil Database (HWSD). This study may provide an important reference to guide management decisions for this and similar watersheds

Estimation of spatial mean soil water storage using temporal stability at the hillslope scale in black locust (Robinia pseudoacacia) stands

Black locust (Robinia pseudoacacia) has been extensively planted on the Loess Plateau for soil and water conservation, but afforestation with this non-native tree has produced some negative effects such as soil desiccation. Knowledge of the soil water storage (SWS) within soil profiles in black locust stands is thus critical for optimization of forest management for sustainable production. The objectives of this study were to evaluate the temporal stability of SWS to identify the most time-stable locations (MTSLs) for reliably estimating the mean SWS and to further investigate the factors influencing its temporal stability. The SWS values of various soil layers (0-1, 1-2, and 2-3 m) were measured from May 2014 to October 2015 at 70 locations along two 187-m long transects on a hillslope covered with black locust in the Loess Plateau, China. A total of 18 SWS datasets were collected over the period of measurement. Results indicated that the temporal variation of spatial mean SWS decreased and the spatial variation of SWS increased with increasing soil depth. A strong temporal persistence in all soil layers was demonstrated by high Spearman's rank correlation coefficients (P 0.91). Elevation, soil saturated hydraulic conductivity, leaf area index, and fine root area density were the major factors influencing the temporal stability of SWS. The results of this study were useful for estimating mean SWS and could improve soil water management and hydrological applications in sloping black locust forested areas of the Loess Plateau

How shallow and how many points of measurements are sufficient to estimate the deep profile mean soil water content of a hillslope in the Loess Plateau?

Soil water content (SWC) measurements for deep soil profiles involve large and expensive expenditures of time and labor. However, understanding of soil water dynamics for deep soil profiles is very important for soil and water resource management and hydrological modeling. This study was aimed at (1) testing whether the mean SWC for the deep profile of a hillslope could be well estimated using the SWC measurements only made at a limited number of time stable locations (TSLs), which were identified from the SWC measurements of the shallow profile (i.e., within 0-100 cm) and (2) subsequently determining the optimal depth of the shallow profile and the optimal number of TSLs using the relative bias to the mean (RBM) SWC and the corrected Alcaike information criterion (AICc). SWC in the 0-300 cm profile was measured at 40 locations along a 243 m long transect on a hillslope where is located in the semiarid region of the Chinese Loess Plateau with a mean annual precipitation (MAP) of 437 mm. A total of 46 SWC measurements made over three growing seasons at each location were divided into the calibration and validation periods. The same method was repeated on the other two hillslopes in the semiarid and semi-humid regions with the MAP of 505 and 580 mm, respectively, for further assessing the effect of soil moisture conditions on the optimal number of TSLs and the optimal depth of the shallow profile. Results indicated that there were significantly correlations between the spatial patterns of SWC in the shallow soil profiles (0-10, 0-20, ... , 0-100 cm) and that in the 0-300 cm deep soil profile (p &lt; 0.01), and the mean SWC in the deep profile on the hillslope could be well estimated using the SWC measurements only at several TSLs identified from the SWC measurements in the shallow soil profile (within 0-100 cm depth). Moreover, the optimal number of TSLs and the optimal depth of the shallow profile varied with soil moisture conditions. In the semiarid region, the optimal depth of the shallow profile was 0-40 cm and the optimal number of TSLs varied from 2 to 3; in the semi-humid region, the optimal depth of the shallow profile was 0-30 cm and the optimal number of TSLs was 3. The RBM values between the predicted and measured mean SWCs in the 0-300 cm deep profile during the calibration and validation periods were in the range of 1.6 to 4.0% on three hillslopes, which are regarded as the acceptable prediction accuracy in the hydrology community. The proposed approach could greatly reduce the expenditures of time and cost in monitoring the mean SWC for the deep profile at various spatial scales and could be applied well to the regions with similar hydrological and climatic conditions

Soil moisture dynamics and dominant controls at different spatial scales over semiarid and semi-humid areas

Soil moisture dynamics plays an active role in ecological and hydrological processes, and it depends on a large number of environmental factors, such as topographic attributes, soil properties, land use types, and precipitation. However, studies must still clarify the relative significance of these environmental factors at different soil depths and at different spatial scales. This study aimed: (1) to characterize temporal and spatial variations in soil moisture content (SMC) at four soil layers (0-40, 40-100, 100-200, and 200-500 cm) and three spatial scales (plot, hillslope, and region); and (2) to determine their dominant controls in diverse soil layers at different spatial scales over semiarid and semi-humid areas of the Loess Plateau, China. Given the high co-dependence of environmental factors, partial least squares regression (PLSR) was used to detect relative significance among 15 selected environmental factors that affect SMC. Temporal variation in SMC decreased with increasing soil depth, and vertical changes in the 0-500 cm soil profile were divided into a fast-changing layer (0-40 cm), an active layer (40-100 cm), a sub-active layer (100-200 cm), and a relatively stable layer (200-500 cm). PLSR models simulated SMC accurately in diverse soil layers at different scales; almost all values for variation in response (R-2) and goodness of prediction (Q(2)) were > 0.5 and > 0.0975, respectively. Upper and lower layer SMCs were the two most important factors that influenced diverse soil layers at three scales, and these SMC variables exhibited the highest importance in projection (VIP) values. The 7-day antecedent precipitation and 7-day antecedent potential evapotranspiration contributed significantly to SMC only at the 0-40 cm soil layer. VIP of soil properties, especially sand and silt content, which influenced SMC strongly, increased significantly after increasing the measured scale. Mean annual precipitation and potential evapotranspiration also influenced SMC at the regional scale significantly. Overall, this study indicated that dominant controls of SMC varied among three spatial scales on the Loess Plateau, and VIP was a function of spatial scale and soil depth