Impact of climate and land-use changes on hydrological processes and sediment yield—a case study of the Be River catchment,Vietnam

Abstract

The impact of climate and land-use changes on hydrological processes and sediment yield is investigated in the Be River catchment, Vietnam, using the Soil and Water Assessment Tool (SWAT) hydrological model. The sensitivity analysis, model calibration and validation indicated that the SWAT model could reasonably simulate the hydrology and sediment yield in the catchment. From this, the responses of the hydrology and sediment to climate change and land-use changes were considered. The results indicate that deforestation had increased the annual flow (by 1.2%) and sediment load (by 11.3%), and that climate change had also significantly increased the annual streamflow (by 26.3%) and sediment load (by 31.7%). Under the impact of coupled climate and land-use changes, the annual streamflow and sediment load increased by 28.0% and 46.4%, respectively. In general, during the 1978–2000 period, climate change influenced the hydrological processes in the Be River catchment more strongly than the land-use change.

Editor Z.W. Kundzewicz; Associate editor Q. Zhang

Citation Khoi, D.N. and Suetsugi, T., 2014. Impact of climate and land-use changes on hydrological processes and sediment yield—a case study of the Be River catchment, Vietnam. Hydrological Sciences Journal, 59 (5), 1095–1108.     

Distribution of clay minerals in marine sediments off Chennai,Bay of Bengal,India： Indicators of sediment sources and transport processes

Clay mineralogy, texture size and statistical analyses were carried out on surface sediments from the continental shelf of Chennai, Bay of Bengal, India. The purpose of this study is to characterize the clay mineral distribution and its relation to the hydrodynamics off Chennai to identify the sources and transport pathways of the marine sediments. Characterization of clay minerals in coastal sediments by Fourier Transform Infrared （FTIR） spectroscopy has provided the association of quartz, feldspar, kaolinite, chlorite, illite and iron oxides （magnetite and hematite） derived from river catchments and coastal erosion. Kaolinite, chlorite, illite, iron oxides, and organic matter are the dominant minerals in Cooum, and Adayar region. High quartz and feldspar zones were identified in Marina, which are being confined the sand zone and paralleling the coast. The strong relationships among the wave energy density, sand, quartz and carbonate revealed that wave induced littoral drift system play a dominant role in transportation and deposition of sediments in the Chennai coast. The sediment texture and minerals data are in agreement well with the previous results of hydrodynamics and littoral drift models in this region. Multivariate statistical analyses （correlation, cluster and factor analyses） were carried out and obtained results suggested that clay minerals and organic matter are trapped in silt and clay particles, whereas quartz, feldspar and carbonate are associated with sand particles. Results of sediment sources and transport processes from this study will be useful to predict the fate of the pollutants released from land or the potential change in sediment delivery to coastal areas.     

Assessment of calanchi and rill–interrill erosion susceptibilities using terrain analysis and geostochastics: A case study in the Oltrepo Pavese,Northern Apennines,Italy

Soil erosion is one of the most important environmental problems distributed worldwide. In the last decades, numerous studies have been published on the assessment of soil erosion and the related processes and forms using empirical, conceptual and physically based models. For the prediction of the spatial distribution, more and more sophisticated stochastic modelling approaches have been proposed – especially on smaller spatial scales such as river basins. In this work, we apply a maximum entropy model (MaxEnt) to evaluate badlands (calanchi) and rill–interrill (sheet erosion) areas in the Oltrepo Pavese (Northern Apennines, Italy). The aim of the work is to assess the important environmental predictors that influence calanchi and rill–interrill erosion at the regional scale. We used 13 topographic parameters derived from a 12 m digital elevation model (TanDEM-X) and data on the lithology and land use. Additional information about the vegetation is introduced through the normalized difference vegetation index based on remotely sensed data (ASTER images). The results are presented in the form of susceptibility maps showing the spatial distribution of the occurrence probability for calanchi and rill–interrill erosion. For the validation of the MaxEnt model results, a support vector machine approach was applied. The models show reliable results and highlight several locations of the study area that are potentially prone to future soil erosion. Thus, coping and mitigation strategies may be developed to prevent or fight the soil erosion phenomenon under consideration. © 2020 John Wiley & Sons, Ltd.     

A case study of spatial heterogeneity of soil moisture in the Loess Plateau, western China： A geostatistical approach

Soil moisture distribution shows highly variation both spatially and temporally. This study assesses the spatial heterogeneity of soil moisture on a hill-slope scale in the Loess Plateau in West China by using a geostatistical approach. Soil moisture was measured by time-domain reflectometry （TDR） in 313 samples. Two kinds of sampling scales were used （2 × 2 m and 20 ×20 m） at two soil layers （0-30 cm and 30-60 cm）. The general characteristics of soil moisture were analyzed by a classical statistics method, and the spatial heterogeneity of soil moisture was analyzed using a geostatistical approach. The results showed that the spherical model is the best-fit model to simulate soil moisture on the experimental hill-slope. The parameters of this model indicated that the spatial dependence of soil moisture in the selected hill-slope was moderate. Even the 2 × 2 m sampling scale was too coarse to show the detailed spatial variances of soil moisture in this area. The dependent distance increased from 27.4 m to 494.16 m as the sampling scale became coarse （from 2× 2 m to 20 ×20 m）. A map of soil moisture was generated by using original soil moisture data and interpolated values determined by the Kriging method. The average soil moisture （area weighted） in the different layers of soil was calculated on the basis of this map （10.94% for the 0-30 cm soil layer, 11.88% for the 30-60 cm soil layer）. This average soil moisture is lower than the corresponding average effective soil moisture, which suggests that the soil moisture is not sufficient to support vegetation in this area.     

Complexity analysis of precipitation using the Lempel–Ziv algorithm and a multi-scaling approach: a case study in Jilin province,China

Precipitation is an important part of the hydrologic cycle, and its complexity is closely related to surface runoff and changing groundwater dynamics, which in turn influences the accuracy of precipitation forecasts. In this study, we used the Lempel–Ziv algorithm (LZA) and a multi-scaling approach to assess precipitation complexity for 1958–2011 by analyzing time series data from 28 gauging stations located throughout Jilin province, China. The spatial distribution of normalized precipitation complexity was measured by LZA, a symbolic dynamics algorithm, and by a multi-scaling approach, which is described by fractals. In addition, the advantages and limitations of these two methods were investigated. The results indicate that both methods are applicable and consistent for calculating precipitation complexity, and that the degree of relief is a primary factor controlling precipitation complexity in the mountainous area; in the plain terrain, however, the prominent influencing factor is climate.     

Assessing spatial likelihood of flooding hazard using naïve Bayes and GIS: a case study in Bowen Basin,Australia

Flooding hazard evaluation is the basis of flooding risk assessment which has significances to natural environment, human life and social economy. This study develops a spatial framework integrating naïve Bayes (NB) and geographic information system (GIS) to assess flooding hazard at regional scale. The methodology was demonstrated in the Bowen Basin in Australia as a case study. The inputs into the framework are five indices: elevation, slope, soil water retention, drainage proximity and density. They were derived from spatial data processed in ArcGIS. NB as a simplified and efficient type of Bayesian methods was used, with the assistance of remotely sensed flood inundation extent in the sampling process, to infer flooding probability on a cell-by-cell basis over the study area. A likelihood-based flooding hazard map was output from the GIS-based framework. The results reveal elevation and slope have more significant impacts on evaluation than other input indices. Area of high likelihood of flooding hazard is mainly located in the west and the southwest where there is a high water channel density, and along the water channels in the east of the study area. High likelihood of flooding hazard covers 45 % of the total area, medium likelihood accounts for about 12 %, low and very low likelihood represents 19 and 24 %, respectively. The results provide baseline information to identify and assess flooding hazard when making adaptation strategies and implementing mitigation measures in future. The framework and methodology developed in the study offer an integrated approach in evaluation of flooding hazard with spatial distributions and indicative uncertainties. It can also be applied to other hazard assessments.     

Assessment of sediment yield estimations for large watershed areas: a case study for the Seyhan,Demirköprü and Hirfanlı reservoirs in Turkey

Abstract

Analyses of data from reservoir surveys and sediment rating curves are compared to predict sediment yield in three large reservoir watershed areas in Turkey. Sediment yield data were derived from reservoir sedimentation rates and suspended sediment measurements at gauging stations. The survey data were analysed to provide the volume estimates of sediment, the time-averaged sediment deposition rates, the long-term average annual loss rates in the reservoir storage capacity, and the long-term sediment yield of the corresponding watershed areas. Four regression methods, including linear and nonlinear cases, were applied to rating curves obtained from gauging stations. Application of the efficiency test to a power function form of a rating curve with nonlinear regression yielded the highest efficiency values. Based on the analysis of the sediment rating curves, sediment load fluxes were calculated by using average daily discharge data at each gauging station. Comparison of these two sediment yield values for each reservoir showed that the sediment yields from the suspended sediment measurements, SY_GS, are 0.99 to 3.54 times less than those obtained from the reservoir surveys, SY_RS. The results from the reservoir surveys indicate that all three reservoirs investigated have lost significant storage capacity due to high sedimentation rates.     

Modeling the potential distribution of shallow-seated landslides using the weights of evidence method and a logistic regression model： a case study of the Sabae Area, Japan

A number of statistical methods are typically used to effectively predict potential landslide distributions. In this study two multivariate statistical analysis methods were used （weights of evidence and logistic regression） to predict the potential distribution of shallow-seated landslides in the Kamikawachi area of Sabae City, Fukui Prefecture, Japan. First, the dependent variable （shallow-seated landslides） was divided into presence and absence, and the independent variables （environmental factors such as slope and altitude） were categorized according to their characteristics. Then, using the weights of evidence （WE） method, the weights of pairs comprising presence （w^＋（i）） or absence （w^-（i））, and the contrast values for each category of independent variable （evidence）, were calculated, Using the method that integrated the weights of evidence method and a logistic regression model, score values were calculated for each category of independent variable. Based on these contrast values, three models were selected to sum the score values of every gird in the study area. According to a receiver operating characteristic curve analysis （ROC）, model 2 yielded the best fit for predicting the potential distribution of shallow-seated landslide hazards, with 89% correctness and a 54.5% hit ratio when the occurrence probability （OP） of landslides was 70%. The model was tested using data from an area close to the study region, and showed 94% correctness and a hit ratio of 45.7% when the OP of landslides was 70%. Finally, the potential distribution of shallow-seated landslides, based on the OP, was mapped using a geographical information system.     

Modeling urban growth with GIS based cellular automata and least squares SVM rules: a case study in Qingpu–Songjiang area of Shanghai,China

A critical issue in urban cellular automata (CA) modeling concerns the identification of transition rules that generate realistic urban land use patterns. Recent studies have demonstrated that linear methods cannot sufficiently delineate the extraordinary complex boundaries between urban and non-urban areas and as most urban CA models simulate transitions across these boundaries, there is an urgent need for good methods to facilitate such delineations. This paper presents a machine learning CA model (termed MachCA) with nonlinear transition rules based on least squares support vector machines (LS-SVM) to simulate such urban growth. By projecting the input dataset into a high dimensional space using the LS-SVM method, an optimal hyper-plane is constructed to separate the complex boundaries between urban and nonurban land, thus enabling the retrieval of nonlinear CA transition rules. In the MachCA model, the transition rules are yes–no decisions on whether a cell changes its state or not, the rules being dynamically updated for each iteration of the model implementation. The application of the MachCA for simulating urban growth in the Shanghai Qingpu–Songjiang area in China reveals that the spatial configurations of rural–urban patterns can be modeled. A comparison of the MachCA model with a conventional CA model fitted by logarithmic regression (termed LogCA) shows that the MachCA model produces more hits and less misses and false alarms due to its capability for capturing the spatial complexity of urban dynamics. This results in improved simulation accuracies, although with only less than 1 % deviation between the overall errors produced by the MachCA and LogCA models. Nevertheless, the way MachCA model use in retrieving the transition rules provides a new method for simulating the dynamic process of urban growth.     

Estimating the impacts of land-cover change on runoff using the soil and water assessment tool (SWAT): case study of Nzoia catchment,Kenya / Estimation des impacts du changement d'occupation du sol sur l'écoulement à l'aide de SWAT: étude du cas du bassin de Nzoia,Kenya

Abstract

The SWAT model was used to investigate the impact of land-cover changes on the runoff of the River Nzoia catchment, Kenya. The model was calibrated against measured daily discharge, and land-cover changes were examined through classification of satellite images. Land-cover change scenarios were generated, namely the worst- and best-case scenarios. Historical land-cover change results showed that agricultural area increased from 39.6 to 64.3% between 1973 and 2001, while forest cover decreased from 12.3 to 7.0%. A comparison between 1970–1975 and 1980–1985 showed that land-cover changes accounted for a difference in surface runoff ranging from 55 to 68% between the two time periods. The land-cover scenarios used showed the magnitude of changes in runoff due to changes in the land covers considered. Compared to the 1980–1985 runoff, the land-cover scenarios generated changes in runoff of about ?16% and 30% for the best and worst case scenarios respectively.     

The sediment delivery ratio in a small catchment in the black soil region of Northeast China

The black soil region of northeast China,which covers the Provinces of Heilongjiang,Jilin and the Inner Mongolia autonomous region with black soil,chernozem and meadow soil,has experienced soil erosion since intense agricultural reclamation began approximately 100 years ago.However,the sediment delivery ratio,defined as the fraction of gross erosion that is transported from a given area in a given time interval,is still unclear.In this study,we calculated the delivery ratio and analysed changes in erosive processes within Hebei catchment from 1977 to 2007 based on an analysis of sediments of the Liudui reservoir.The original vegetation layer clearly identified the bottom of the reservoir when it was constructed in 1977;thus,the reservoir sediments could be precisely dated.The delivery ratio,calculated by comparing the sediment deposition in the reservoir with the total soil erosion in the upstream catchment,was found to be exponentially correlated（r² = 0.95,P < 0.01） with decreasing grain size,except for the fraction <0.002 mm.The delivery ratio for the clays（<0.002 mm） was low,averaging 0.10 during the study period, which indicated partial removal of clays from the reservoir.The changes in the reservoir deposition rate reflected the temporal changes in the erosion processes.The exceptionally high rainfall in 1998 was confirmed by the distributions of ¹³⁷Cs,²¹⁰Pb,and the grain-size of the sediments.Beginning from the position of the original grass layer,we defined three periods from 1977 to 2007 based on deposition rates:2.40 cm year^-1 from 1977 to 1997,5.60 cm year^-1 in 1998 due to unusually high rainfall,and 1.55 cm year^-1 from 1999 to 2007.The overall average deposition rate for the entire period was 2.26 cm year^-1.Precipitation was found to be the main factor affecting the soil erosion of the study area.     

Modelling soil erosion in tropical environments using remote sensing and geographical information systems

Abstract

Soil erosion probability maps were produced under various case scenarios by accounting for uncertainties in the data and in the decision rule, using the Universal Soil Loss Equation (USLE), remote sensing and geographical information systems (GIS). This objective was realized by applying the Bayesian Probability Theory within IDRISI, a raster based GIS. The outcomes were two continuous probability soil erosion maps ranging from zero to 1. Comparing these maps with an earlier study indicates that accounting for the uncertainties has, in general, decreased the probability of soil erosion. Based on average readings for specific sites on the maps, increases in erosion risk under the second case scenario have had the highest impact on the highlands that is in the central, eastern, and northern regions of Langkawi Island, Malaysia. Assuming a 10% risk, this impact has increased by 11.98, 11.83 and 5.741% for high, medium and low soil erosion risk areas on the island respectively.     

Use of remote sensing,GIS and C++ for soil erosion assessment in the Shakkar River basin,India

Soil is an essential resource for human livelihoods. Soil erosion is now a global environmental crisis that threatens the natural environment and agriculture. This study aimed to assess the annual rate of soil erosion using distributed information for topography, land use and soil, with a remote sensing (RS) and geographical information system (GIS) approach and comparison of simulated with observed sediment loss. The Shakkar River basin, situated in the Narsinghpur and Chhindwara districts of Madhya Pradesh, India, was selected for this study. The universal soil loss equation (USLE) with RS and GIS was used to predict the spatial distribution of soil erosion occurring in the study area on a grid-cell basis. Thematic maps of rainfall erosivity factor (R), soil erodibility factor (K), topographic factor (LS), crop/cover management factor (C), and conservation/support practice factor (P) were prepared using annual rainfall data, soil map, digital elevation model (DEM) and an executable C++ program, and a satellite image of the study area in the GIS environment. The annual rate of soil erosion was estimated for a 15-year period (1992–2006) and was found to vary between 6.45 and 13.74 t ha^?1 year^?1, with an average annual rate of 9.84 t ha^?1 year^?1. The percentage deviation between simulated and observed values varies between 2.68% and 18.73%, with a coefficient of determination (R²) of 0.874.     

Identification of soil erosion and fluvial sediment problems

A computer model has been used to estimate soil loss and sediment yield from irregular field-size units of small watersheds. Input to the model includes spring data (i.e. relating to February through May) for the independent variables of the Universal Soil Loss Equation, and for factors such as surface roughness, an index of overland runoff, and proximity to the stream. Output from the model includes maps of seasonal estimates of potential soil losses, field sediment delivery ratios, and expected sediment yields. On the basis of selected erosion and sediment yield tolerances, the output information has been analysed to identify watershed areas which (1) exhibit both erosion and sediment yield problems; (2) exhibit only erosion problems; (3) exhibit only sediment yield problems; and (4) exhibit neither erosion nor sediment yield problems. The percentage of the watershed area in each category and the percentage of the watershed soil loss and sediment loads contributed by each category are also identified. Application of the procedure for planning remedial control programs for five watersheds is discussed.     

Impact of land use changes on catchment soil erosion and sediment yield in the northeastern China: A panel data model application

Land use is an important factor influencing soil erosion and sediment yield (SESY). Regressing soil erosion intensity (SEI) and sediment yield (SY) to land use characteristics can provide necessary information for controlling soil loss. However, current simple regression methods emphasize cross sectional parameters, with less emphasis on temporal variability of relevant land use parameters so that the derived effects of land use change on SESY can be biased. Here, a panel data method was applied to quantify the impact of land use change on SESY in 1954, 1975, and 2015, based on the WaTEM/SEDEM model and seven landscape metrics for 25 reservoir catchments in northeastern China. The results indicate that SEI and area-specific SY (SSY) continuously decreased from 1954 to 2015, which were significantly correlated with landscape metrics such as area-edge metrics of mean patch area (AREA_MN), shape index of the mean related circumscribing circle (CIRCLE_MN), aggregation index of effective mesh size (MESH), patch cohesion index (COHESION), and diversity metrics such as Shannon's diversity index (SHDI), patch richness density (PRD), and modified Simpson's evenness index (MSIEI). The results suggested that catchment SESY can be reduced through decreasing mean patch area, patch mesh size, and physical connectivity of patches, enriching landscape types, and elongating land use patches. These findings are helpful to effectively implement soil conservation measures in northeastern China and similar regions worldwide. The current study also implies that the panel data approach will have beneficial potential applications in earth-science research fields.     

Assessing the vulnerability to soil erosion of the Ukai Dam catchments using remote sensing and GIS

Abstract

The investigation of basins for planning soil conservation requires a selective approach to identify smaller hydrological units, which would be suitable for more efficient and targeted conservation management programmes. One criterion, generally used to determine the vulnerability of catchments to erosion, is the sediment yield of a basin. In India, sediment yield data are generally not collected for smaller sub-catchments and it becomes difficult to identify the most vulnerable areas for erosion that can be treated on a priority basis. An index-based approach, based on the surface factors mainly responsible for soil erosion, is suggested in this study. These factors include soil type, vegetation, slope and various catchment properties such as drainage density, form factor, etc. The method is illustrated with a case study of sub-catchments immediately upstream of the Ukai Reservoir located on the River Tapi in Gujarat State, India. The area is divided into 16 watersheds and different soil, vegetation, topography and morphology-related parameters are estimated separately for each watershed. Satellite data are used to evaluate the soil and vegetation indices, while a GIS system is used to evaluate the topography and morphology-related indices. The integrated effect of all the parameters is evaluated to find different areas vulnerable to soil erosion. Two watersheds were identified as being most susceptible to soil erosion. Based on the integrated index, a priority rating of the watersheds for soil conservation planning is recommended.     

Estimation of temporally averaged sediment delivery ratio using aggradational terraces in headwater catchments of the Waipaoa River,North Island,New Zealand

The sediment delivery ratio was estimated for two periods (28 years and eight years) following reforestation of seven tributary catchments (0·33 to 0·49 km²) in the headwaters of the Waipaoa River basin, North Island, New Zealand. In these catchments, gully erosion, which largely resulted from clearance of the natural forest between 1880 and 1920, is the main source of sediment to streams. Reforestation commenced in the early 1960s in an attempt to stabilize hillslopes and reduce sediment supply. Efforts have been partially successful and channels are now degrading, though gully erosion continues to supply sediment at accelerated rates in parts of the catchment. Data from the area indicate that the sediment delivery ratio (SDR) can be estimated as a function of two variables, ψ (the product of catchment area and channel slope) and A _g (the temporally averaged gully area for the period). Sediment input from gullies was determined from a well defined relationship between sediment yield and gully area. Sediment scoured from channels was estimated from dated terrace remnants and the current channel bed. Terrace remnants represent aggradation during major floods. This technique provides estimates of SDR averaged over periods between large magnitude terrace‐forming events and with the present channel bed. The technique averages out short‐term variability in sediment flux. Comparison of gully area and sediment transport between two periods (1960–1988 and 1988–1996) indicates that the annual rate of sediment yield from gullies for the later period has decreased by 77 per cent, sediment scouring in channels has increased by 124 per cent, and sediment delivered from catchments has decreased by 78 per cent. However, average SDR for the tributaries was found to be not significantly different between these periods. This may reflect the small number of catchments examined. It is also due to the fact that the volume of sediment scoured from channels was very small relative to that produced by gullies. According to the equation for SDR determined for the Waipaoa headwaters, SDR increases with increasing catchment area in the case where A _g and channel slope are fixed. This is because the amount of sediment produced from a channel by scouring increases with increasing catchment area. However, this relationship does not hold for the main stem of the study catchments, because sediment delivered from its tributaries still continues to accumulate in the channel. Higher order channels are, in effect, at a different stage in the aggradation/degradation cycle and it will take some time until a main channel reflects the effects of reforestation and its bed adjusts to net degradation. Results demonstrate significant differences among even low order catchments, and such differences will need to be taken into consideration when using SDR to estimate sediment yields. Copyright © 2001 John Wiley & Sons, Ltd.     

Assessment of soil erosion in a monsoon-dominated mountain river basin in India using RUSLE-SDR and AHP

The long-term average annual soil loss (A) and sediment yield (SY) in a tropical monsoon-dominated river basin in the southern Western Ghats, India (Muthirapuzha River Basin, MRB; area: 271.75 km²), were predicted by coupling the Revised Universal Soil Loss Equation (RUSLE) and sediment delivery ratio (SDR) models. Moreover, the study also delineated soil erosion risk zones based on the soil erosion potential index (SEPI) using the analytic hierarchy process (AHP) technique. Mean A of the basin is 14.36 t ha^?1 year^?1, while mean SY is only 3.65 t ha^?1 year^?1. Although the land use/land cover types with human interference show relatively lower A compared to natural vegetation, their higher SDR values reflect the significance of anthropogenic activities in accelerated soil erosion. The soil erosion risk in the MRB is strongly controlled by slope, land use/land cover and relative relief, compared to geomorphology, drainage density, stream frequency and lineament frequency.     

Modeling soil erosion using a spatially distributed model in a karst catchment of northwest Guangxi,China

Reliable assessment of the spatial distribution of soil erosion is important for making land management decisions, but it has not been thoroughly evaluated in karst geo‐environments. The objective of this study was to modify a physically based, spatially distributed erosion model, the revised Morgan, Morgan and Finney (RMMF) model, to estimate the superficial (as opposed to subsurface creep) soil erosion rates and their spatial patterns in a 1022 ha karst catchment in northwest Guangxi, China. Model parameters were calculated using local data in a raster geographic information system (GIS) framework. The cumulative runoff on each grid cell, as an input to the RMMF model for erosion computations, was computed using a combined flow algorithm that allowed for flow into multiple cells with a transfer grid considering infiltration and runoff seepage to the subsurface. The predicted spatial distributions of soil erosion rates were analyzed relative to land uses and slope zones. Results showed that the simulated effective runoff and annual soil erosion rates of hillslopes agreed well with the field observations and previous quantified redistribution rates with caesium‐137 (¹³⁷Cs). The estimated average effective runoff and annual erosion rate on hillslopes of the study catchment were 18 mm and 0.27 Mg ha^?1 yr^?1 during 2006–2007. Human disturbances played an important role in accelerating soil erosion rates with the average values ranged from 0.1 to 3.02 Mg ha^?1 yr^?1 for different land uses. The study indicated that the modified model was effective to predict superficial soil erosion rates in karst regions and the spatial distribution results could provide useful information for developing local soil and water conservation plans. Copyright © 2014 John Wiley & Sons, Ltd.     

Unsteady soil erosion due to rainfall impact: a model of sediment sorting on the hillslope

A new method is presented for predicting sediment sorting associated with soil erosion by raindrop impact for non-equilibrium conditions. The form of soil erosion considered is that which results from raindrop impact in the presence of shallow overland flow itself where the flow is not capable of eroding sediment. The method specifically considers early time runoff and erosion when sediment leaving an eroding area is generally finer and thus may have a higher potential for transport of sorbed pollutants. The new mechanism described is the formation of a deposited layer on the soil surface, which is shown to lead to sediment sorting during an erosion event. The deposited layer is taken to have two roles in this process: to temporarily store sediment on the surface between successive trajectories, and to shield the underlying soil from erosive stresses. Equations describing the dynamics of the suspended sediment mixture and the deposited layer are developed. By integrating these equations over the length of eroding land element and over the duration of the erosion event, an event-based solution is proposed which predicts total sediment sorting over the event. This solution is shown to be consistent with experimentally observed trends in enrichment of fine sediment. Predictions using this approach are found to only partly explain measured enrichment for sets of experimental data for two quite different soils, but to be in poor agreement for an aridsol of dispersive character. It is concluded that the formation of the deposited layer is a significant mechanism in the enrichment of fine sediment and associated sorbed pollutants, but that processes in the dispersive soil are not as well described by the theory presented.