Hillslope and point based soil erosion – an evaluation of a Landscape Evolution Model

Excessive soil erosion and deposition is recognised as a significant land degradation issue. Quantifying soil erosion and deposition is a non-trivial task. One of these methods has been the mathematical modelling of soil erosion and deposition patterns and the processes that drive them. Here we examine the capability of a landscape evolution model to predict both soil erosion rate and pattern of erosion and deposition. This numerical model (SIBERIA) uses a Digital Elevation Model (DEM) to represent the landscape and calculates erosion and deposition at each grid point in the DEM. To assess field soil redistribution rates (SRR) and patterns the distribution of the environmental tracer ¹³⁷Cs has been analysed. Net hill slope SRR predicted by SIBERIA (a soil loss rate of 1.7 to 4.3 t ha^-1 yr^-1) were found to be in good agreement with ¹³⁷Cs based estimates (2.1 – 3.4 t ha^-1 yr^-1) providing confidence in the predictive ability of the model at the hillslope scale. However some differences in predicted erosion/deposition patterns were noted due to historical changes in landscape form (i.e. the addition of a contour bank) and possible causes discussed, as is the finding that soil erosion rates are an order of magnitude higher than likely soil production rates. The finding that SIBERIA can approximate independently quantified erosion and deposition patterns and rates is encouraging, providing confidence in the employment of DEM based models to quantify hillslope erosion rates and demonstrating the potential to upscale for the prediction of whole catchment erosion and deposition. The findings of this study suggest that LEMs can be a reliable alternative to complex and time consuming methods such as that using environmental tracers for the determination of erosion rates. The model and approach demonstrates a new approach to assessing soil erosion that can be employed elsewhere. © 2018 John Wiley & Sons, Ltd.     

Using high resolution images and elevation data in classifying erosion risks of bare soil areas in the Hatila Valley Natural Protected Area, Turkey

Soil erosion is one of the most important environmental problems. In the case of small scale areas where soil properties and climate have relatively uniform characteristics, vegetation cover and topography (i.e. ground slope) are the main factors that affect the amount of soil erosion. Lack of vegetation cover on bare soil areas, including forest road side slopes, especially in mountainous regions with steep slopes, may significantly increase the erosion rate. Determining and classifying erosion risks in such areas can help preventing environmental impacts. In this study, remotely sensed data and elevation data were used to extract and classify bare soil erosion risk areas for a study area selected from Hatila Valley Natural Protected Area in northeastern Turkey. High resolution IKONOS imagery was used to apply land use classification in ERDAS Imagine 9.0. To generate erosion risk map of the bare soil areas, classified image was superimposed on top of slope map, generated based on a Digital Elevation Model (DEM) in ArcGIS 9.2. The results indicated that 1.43, 5.85, 34.62, 53.16, and 4.94% of the bare soil areas in the study area were under very low, low, medium, high, and very high erosion risks, respectively. The overall classification accuracy of 82.5% indicated the potential of the proposed methodology.     

DEM-based numerical modelling of runoff and soil erosion processes in the hilly–gully loess regions

For sake of improving our current understanding on soil erosion processes in the hilly–gully loess regions of the middle Yellow River basin in China, a digital elevation model (DEM)-based runoff and sediment processes simulating model was developed. Infiltration excess runoff theory was used to describe the runoff generation process while a kinematic wave equation was solved using the finite-difference technique to simulate concentration processes on hillslopes. The soil erosion processes were modelled using the particular characteristics of loess slope, gully slope, and groove to characterize the unique features of steep hillslopes and a large variety of gullies based on a number of experiments. The constructed model was calibrated and verified in the Chabagou catchment, located in the middle Yellow River of China and dominated by an extreme soil-erosion rate. Moreover, spatio-temporal characterization of the soil erosion processes in small catchments and in-depth analysis between discharge and sediment concentration for the hyper-concentrated flows were addressed in detail. Thereafter, the calibrated model was applied to the Xingzihe catchment, which is dominated by similar soil erosion processes in the Yellow River basin. Results indicate that the model is capable of simulating runoff and soil erosion processes in such hilly–gully loess regions. The developed model are expected to contribute to further understanding of runoff generation and soil erosion processes in small catchments characterized by steep hillslopes, a large variety of gullies, and hyper-concentrated flow, and will be beneficial to water and soil conservation planning and management for catchments dealing with serious water and soil loss in the Loess Plateau.     

基于CryoSat-2测高数据的全南极冰盖DEM的建立与精度评估

数字高程模型(DEM)是南极冰盖变化研究的基础,由于现场实测数据的稀缺,卫星测高数据是南极地区构建DEM的'主要数据来源.CryoSat-2是新一代用于极地冰盖、海冰监测的测高卫星,本文利用2012-12-2015-01两个完整周期的CryoSat-2测高数据建立一个新的南极冰盖DEM.坡度是影响卫星测高精度的重要因素之一,利用改进的重定位方法对CryoSat-2数据进行坡度改正.插值方法是影响DEM精度的重要因素,通过对几种常用插值方法的比较,最后选用克里金插值方法对测高数据进行插值,建立了1km分辨率的南极DEM.在88°S以南的CryoSat-2数据空白区,利用南极数字数据库(ADD)的等高线数据对DEM进行填补,建立了全南极冰盖DEM.利用ICESat卫星测高数据、IceBridge航空测高数据以及GPS地面实测数据对新建立的CryoSat-2 DEM进行精度验证,并与Bamber 1 km DEM、ICESat DEM、RAMPv2 DEM以及JLB97 DEM等四种国际上常用的南极DEM进行比较.结果表明:新建立的CryoSat-2 DEM的整体精度约为0.730±8.398 m;在冰弯顶部区域,DEM精度优于1 m;在冰架上,DEM精度约为4 m;在内陆冰盖大部分地区,DEM精度优于10 m;在地形复杂的山区和沿海边缘地区,DEM误差超过150 m.     

Modelling soil erosion with a downscaled landscape evolution model

The measurement and prediction of soil erosion is important for understanding both natural and disturbed landscape systems. In particular numerical models of soil erosion are important tools for managing landscapes as well as understanding how they have evolved over time. Over the last 40 years a variety of methods have been used to determine rates of soil loss from a landscape and these can be loosely categorized into empirical and physically based models. Alternatively, physically based landscape evolution models (LEMs) have been developed that provide information on soil erosion rates at much longer decadal or centennial scales, over large spatial scales and examine how they may respond to environmental and climatic changes. Both soil erosion LEMs are interested in similar outcomes (landscape development and sediment delivery) yet have quite different methodologies and parameterizations. This paper applies a LEM (the CAESAR model) for the first time at time and space scales where soil erosion models have largely been used. It tests the ability of the LEM to predict soil erosion on a 30 m experimental plot on a trial rehabilitated landform in the Northern Territory, Australia. It then continues to discuss the synergies and differences between soil erosion and LEMs. The results demonstrate that once calibrated for the site hydrology, predicted suspended sediment and bedload yields from CAESAR show a close correspondence in both volume and timing of field measured data. The model also predicts, at decadal scales, sediment loads close to that of field measured data. Findings indicate that the small‐scale drainage network that forms within these erosion plots is an important control on the timing and magnitude of sediment delivery. Therefore, it is important to use models that can alter the DEM to reflect changing topography and drainage network as well as having a greater emphasis on channel processes. Copyright © 2012 John Wiley & Sons, Ltd. and Commonwealth of Australia     

An automatic approach for rill network extraction to measure rill erosion by terrestrial and low‐cost unmanned aerial vehicle photogrammetry

For an erosion event (October 2016) occurred at the Sparacia experimental area (Southern Italy), both terrestrial and low‐altitude aerial surveys were carried out by consumer grade camera and quadcopter (low‐cost unmanned aerial vehicle [UAV]) to measure rill erosion on two plots with steepness of 22% and 26%. Applying the structure from motion (SfM) technique, the three‐dimensional digital terrain models (3D‐DTMs) and the quasi three‐dimensional models (2.5D‐digital elevation model [DEM]) were obtained by the two surveys. Furthermore, 3D‐DTM and DEM were built using the available aerial photographs (166) and adding 40 terrestrial photographs. For the first time, the convergence index was applied to high‐resolution rill data for extracting the rill network, and a subsequent separation into contributing and non‐contributing rills was carried out. The comparison among the three surveys (terrestrial, UAV, and UAV + terrestrial) was developed using two morphometric parameters of the rill network (drainage density and drainage frequency). Moreover, using as reference the weight of sediment stored on the tanks located downstream of the plots, the reliability of soil loss measurement by 3D models was tested. For both contributing and non‐contributing rills, the morphometric parameters were higher for the terrestrial than for UAV and UAV + terrestrial surveys. For both plots, SfM always provided reliable soil loss measurements, which were affected by errors ranging from ?8% to 13%. Although the applied technique used a low‐cost UAV and a consumer grade camera, the obtained results demonstrated that a reliable estimate of rill erosion can be obtained in an area of interest.     

People’s perception and socioeconomic determinants of soil erosion:A case study of Samanalawewa watershed,Sri Lanka

Though soil erosion is an important concern in Sri Lanka, there is a dearth of baseline information on soil erosion in many ofits watersheds, which obstructs monitoring of soil erosion and mitigating its effects. In order to assess soil erosion in a critical watershed and to identify its determinants, the Samanalawewa watershed, which contains one of the main hydropower generating reservoirs in Sri Lanka, was selected for this study. Remote-sensing (RS) and geographic information system (GIS) based modeling...     

The Daily Erosion Project – daily estimates of water runoff,soil detachment,and erosion

Water runoff and sediment transport from agricultural uplands are substantial threats to water quality and sustained crop production. To improve soil and water resources, farmers, conservationists, and policy‐makers must understand how landforms, soil types, farming practices, and rainfall interact with water runoff and soil erosion processes. To that end, the Iowa Daily Erosion Project (IDEP) was designed and implemented in 2003 to inventory these factors across Iowa in the United States. IDEP utilized the Water Erosion Prediction Project (WEPP) soil erosion model along with radar‐derived precipitation data and government‐provided slope, soil, and management information to produce daily estimates of soil erosion and runoff at the township scale (93 km² [36 mi²]). Improved national databases and evolving remote sensing technology now permit the derivation of slope, soil, and field‐level management inputs for WEPP. These remotely sensed parameters, along with more detailed meteorological data, now drive daily WEPP hillslope soil erosion and water runoff estimates at the small watershed scale, approximately 90 km² (35 mi²), across sections of multiple Midwest states. The revisions constitute a substantial improvement as more realistic field conditions are reflected, more detailed weather data are utilized, hill slope sampling density is an order of magnitude greater, and results are aggregated based on surface hydrology enabling further watershed research and analysis. Considering these improvements and the expansion of the project beyond Iowa it was renamed the Daily Erosion Project (DEP). Statistical and comparative evaluations of soil erosion simulations indicate that the sampling density is adequate and the results are defendable. The modeling framework developed is readily adaptable to other regions given suitable inputs. © 2017 The Authors. Earth Surface Processes and Landforms published by John Wiley & Sons Ltd.     

A GIS-BASED DISTRIBUTED SOIL EROSION MODEL： A CASE STUDY OF TYPICAL WATERSHED, SICHUAN BASIN

Based on the measuring data and Digital Elevation Data (DEM) in a typical watershed--Hemingguan Watershed, Nanbu County, Sichuan Province of China, a GIS-based distributed soil erosion model was developed particularly for the purple soil type. It takes 20 m × 20 m grid as calculating unit and operates at 10-minute time interval. The required input data to the model include DEM, soil, land use, and time-series of precipitation and evaporation loss. The model enables one to estimate runoff, erosion and sediment yield for each grid cell and route the flow along its flow path to the watershed outlet. Furthermore, the model is capable of calculating the total runoff; erosion and sediment yield for the entire watershed by recursion algorithm. The validation of the model demonstrated that it could quantitatively simulate the spatial distribution of hydrological variables in a watershed, such as runoff, vegetation entrapment, soil erosion, the degree of soil and water loss. Moreover, it can evaluate the effect of land use change on the runoff generation and soil erosion with an accuracy of 80% and 75% respectively. The application of this model to a neighboring watershed with similar conditions indicates that this distributed model could be extended to other similar regions in China.     

Effects of grass contour hedgerow systems on controlling soil erosion in red soil hilly areas,Southeast China

Soil erosion by water is a well-recognized serious environmental problem in the world.While contour hedgerow systems are an effective method for soil water conservation,there are a few studies on its effect in the red soil hilly areas in Southeast China.With a fixed field experiment,we constructed a runoff plot at hilly area in Zhuji County,Zhejiang province,to evaluate the effect of the grass hedgerows in soil water conservation,and to determine the optimized hedgerow patterns.Hemerocallis citrine(HC)and Ophiopogon japonicas(OJ) were selected to build the hedgerows in patterns of one row and two rows.The REE method was used to trace the source of the sediment for a better understanding of the characteristic and mechanism of erosion with hedgerows control.Our results showed that(1) hedgerows reduced erosion and surface runoff by 31.99-67.22%and 15.44-45.11%,respectively;(2) hedgerows delayed the development of rills;(3) hedgerows reduced the soil nutrients loss;(4) hedgerows reshaped the soil physical properties,especially in increasing > 0.25 mm water-stable aggregates.Taken together,our results suggest that two-row OJ is the optimized contour hedgerow pattern in the experiment condition,and downward sloping land should have the highest priority to take measures for soil water conservation.This research comprehensively studied the effects and mechanism of contour hedgerows in controlling soil and water loss in red soil hilly areas,Southeast China,so that the practice of soil and water conservation can be implemented more effectively in these areas.     

EFFECT OF DIGITAL ELEVATION MODEL RESOLUTION ON EMPIRICAL ESTIMATION OF SOIL LOSS AND SEDIMENT TRANSPORT WITH GIS

The horizontal accuracy of topographic data represented by digital elevation model (DEM) resolution brings about uncertainties in landscape process modeling with raster GIS. This paper presents a study on the effect of topographic variability on cell-based empirical estimation of soil loss and sediment transport. An original DEM of 10m resolution for a case watershed was re-sampled to three realizations of higher grid sizes for a comparative examination. Equations based on the USLE are applied to the watershed to calculate soil loss from each cell and total sediment transport to streams. The study found that the calculated total soil loss from the watershed decreases with the increasing DEM resolution with a linear correlation as spatial variability is reduced by cell aggregation. The USLE topographic factors (LS) extracted from applied DEMs represent spatial variability, and determine the estimations as shown in the modeling results. The commonly used USGS 30m DEM appears to be able to reflect essential spatial variability and suitable for the empirical estimation. The appropriateness of a DEM resolution is dependent upon specific landscape characteristics, applied model and its parameterization. This work attempts to provide a general framework for the research in the DEM-based empirical modeling.     

Comparison of different mass transport calculation methods for wind erosion quantification purposes

Quantitative estimation of the material transported by the wind under field conditions is essential for the study and control of wind erosion. A critical step of this calculation is the integration of the curve that relates the variation of the amount of the material carried by the wind with height. Several mathematical procedures have been proposed for this calculation, but results are scarce and controversial. One objective of this study was to assess the efficiency of three mathematical models (a rational, an exponential, and a simplified Gaussian function) for the calculation of the mass transport, as compared to the linear spline interpolation. Another objective of this study was to compare the mass transport calculated from field measurements obtained from a minimum of three discrete sampling heights with measurements of nine sampling heights. With this purpose, wind erosion was measured under low surface roughness conditions on an Entic Haplustoll during 25 events. The rational function was found to be mathematically limited for the estimation of wind eroded sediment mass flux. The simplified Gaussian model did not fit to the vertical mass flux profile data. Linear spline interpolation generally produced higher mass transport estimates than the exponential equation, and it proved to be a very flexible and robust method. Using different sampling arrangements and different mass flux models can produce differences of more than 45% in mass transport estimates, even under similar field conditions. Under the conditions of this study, at least three points between the soil surface and 1·5 m high, including one point as closest as possible to the surface, should be sampled in order to obtain accurate mass transport estimates. Additionally, the linear spline interpolation and the non‐linear regression using an exponential model, proved to be mathematically reliable methods for calculating the mass transport. Copyright © 2010 John Wiley & Sons, Ltd.     

Changes of soil surface roughness under water erosion process

The objective of this study was to determine the changing characteristics of soil surface roughness under different rainfall intensities and examine the interaction between soil surface roughness and different water erosion processes. Four artificial management practices (raking cropland, artificial hoeing, artificial digging, and contour tillage) were used according to the local agriculture customs of the Loess Plateau of China to simulate different types of soil surface roughness, using an additional smooth slope for comparison purposes. A total of 20 rainfall simulation experiments were conducted in five 1 m by 2 m boxes under two rainfall intensities (0.68 and 1.50 mm min^?1) on a 15° slope. During splash erosion, soil surface roughness decreased in all treatments except raking cropland and smooth baseline under rainfall intensity of 0.68 mm min^?1, while increasing for all treatments except smooth baseline under rainfall intensity of 1.50 mm min^?1. During sheet erosion, soil surface roughness decreased for all treatments except hoeing cropland under rainfall intensity of 0.68 mm min^?1. However, soil surface roughness increased for the artificial hoeing and raking cropland under rainfall intensity of 1.50 mm min^?1. Soil surface roughness has a control effect on sheet erosion for different treatments under two rainfall intensities. For rill erosion, soil surface roughness increased for raking cropland and artificial hoeing treatments, and soil surface roughness decreased for artificial digging and the contour tillage treatments under two rainfall intensities. Under rainfall intensity of 0.68 mm min^?1, the critical soil surface roughness was 0.706 cm for the resistance control of runoff and sediment yield. Under rainfall intensity of 1.50 mm min^?1, the critical soil surface roughness was 1.633 cm for the resistance control of runoff, while the critical soil surface roughness was 0.706 cm for the resistance control of sediment yield. These findings have important implications for clarifying the erosive nature of soil surface roughness and harnessing sloped farmland. Copyright © 2013 John Wiley & Sons, Ltd.     

Exploring the interaction of surface roughness and slope gradient in controlling rates of soil loss from sloping farmland on the Loess Plateau of China

Surface roughness and slope gradient are two important factors influencing soil erosion. The objective of this study was to investigate the interaction of surface roughness and slope gradient in controlling soil loss from sloping farmland due to water erosion on the Loess Plateau, China. Following the surface features of sloping farmland in the plateau region, we manually prepared rough surfaces using four tillage practices (contour drilling, artificial digging, manual hoeing, and contour plowing), with a smooth surface as the control measure. Five slope gradients (3°, 5°, 10°, 15°, and 20°) and two rainfall intensities (60 and 90 mm/hr) were considered in the artificial rainfall simulation experiment. The results showed that the runoff volume and sediment yield increased with increasing slope gradient under the same tillage treatment. At gentle slope gradients (e.g., 3° and 5°), the increase in surface roughness prevented the runoff and sediment production, that is, the surface roughness reduced the positive effect of slope gradient on the runoff volume and sediment yield to a certain extent. At steep slope gradients, however, the enhancing effect of slope gradient on soil erosion gradually increased and surpassed the reduction effect of surface roughness. This study reveals the existence of a critical slope gradient that influences the interaction of surface roughness and slope gradient in controlling soil erosion on sloping farmland. If the slope gradient is equal to or less than the critical value, an increase in surface roughness would decrease soil erosion. Otherwise, the increase in surface roughness would be ineffective for preventing soil erosion. The critical slope gradient would be smaller under higher rainfall intensity. These findings are helpful for us to understand the process of soil erosion and relevant for supporting soil and water conservation in the Loess Plateau region of China.     

Water and sediment balances of a contour bench terracing system in a semi-arid cultivated zone (El Gouazine,central Tunisia)

Abstract

Contour benches are earthen structures constructed across cultivated slopes, at intervals down the slope, largely used in semi-arid zones. The results of an experiment to monitor water and sediment balance inside a contour bench terrace system are presented. The study site, located in the El-Gouazine watershed (central Tunisia), includes two terraced plots of approximately 3000 m², one of which was left fallow for several years, while the other was tilled. The characteristics of rainfall—runoff processes and erosion inside both terraced plots during a two-year period (2004–2006) are described. Ploughing reduced runoff by 75%. Erosion was monitored following runoff episodes that produced observable deposits in the bench channel. After ploughing, erosion was reduced by 44% between July 2004 and July 2005 and by 50% between October 2005 and July 2006. However, erosion per millimetre of runoff was about twice as great on the tilled soil as on the fallow. Even though ploughing weakens the soil, it seems to reduce erosion by increasing infiltration. For the studied rain events, ploughing used in combination with contour bench terraces seems to have limited erosion and enhanced the effectiveness of contour bench terrace management.     

Spatial distribution and content of soil organic matter in an agricultural field in eastern Canada,as estimated from geostatistical tools

Soil erosion induces soil redistribution within the landscape and thus contributes to the spatial variability of soil quality. This study complements a previous experimentation initiated by the authors focusing on soil redistribution as a result of soil erosion, as indicated by caesium‐137 (¹³⁷Cs) measurements, in a small agricultural field in Canada. The spatial variability of soil organic matter (SOM) was characterized using geostatistics, which consider the randomized and structured nature of spatial variables and the spatial distribution of the samples. The spatial correlation of SOM (in percentages) patterns in the topsoil was established taking into account the spatial structure present in the data. A significant autocorrelation and reliable variograms were found with a R² ≥ 0·9, thus demonstrating a strong spatial dependence. Ordinary Kriging (OK) interpolation provided the best cross validation (r² = 0·35). OK and inverse distance weighting power two (IDW2) interpolation approaches produced similar estimates of the total SOM content of the topsoil (0–20 cm) of the experimental field, i.e. 211 and 213 tonnes, respectively. However, the two approaches produced differences in the spatial distribution patterns and the relative magnitude of some SOM content classes. The spatialization of SOM and soil redistribution variability – as evidenced by ¹³⁷Cs measurements – is a first step towards the assessment of the impact of soil erosion on SOM losses to recommend conservation measures. Copyright © 2009 John Wiley & Sons, Ltd.     

Quantitative and Qualitative Assessment of Soil Erosion Risk in Małopolska (Poland), Supported by an Object-Based Analysis of High-Resolution Satellite Images

In 2011 the Marshal Office of Ma?opolska Voivodeship decided to evaluate the vulnerability of soils to water erosion for the entire region. The quantitative and qualitative assessment of the erosion risk for the soils of the Ma?opolska region was done based on the USLE approach. The special work-flow of geoinformation technologies was used to fulfil this goal. A high-resolution soil map, together with rainfall data, a detailed digital elevation model and statistical information about areas sown with particular crops created the input information for erosion modelling in GIS environment. The satellite remote sensing technology and the object-based image analysis (OBIA) approach gave valuable support to this study. RapidEye satellite images were used to obtain the essential up-to-date data about land use and vegetation cover for the entire region (15,000 km²). The application of OBIA also led to defining the direction of field cultivation and the mapping of contour tillage areas. As a result, the spatially differentiated values of erosion control practice factor were used. Both, the potential and the actual soil erosion risk were assessed quantificatively and qualitatively. The results of the erosion assessment in the Ma?opolska Voivodeship reveal the fact that a majority of its agricultural lands is characterized by moderate or low erosion risk levels. However, high-resolution erosion risk maps show its substantial spatial diversity. According to our study, average or higher actual erosion intensity levels occur for 10.6 % of agricultural land, i.e. 3.6 % of the entire voivodeship area. In 20 % of the municipalities there is a very urgent demand for erosion control. In the next 23 % an urgent erosion control is needed. Our study showed that even a slight improvement of P-factor estimation may have an influence on modeling results. In our case, despite a marginal change of erosion assessment figures on a regional scale, the influence on the final prioritization of areas (municipalities) according to erosion control needs is visible. The study shows that, high-resolution satellite imagery and OBIA may be efficiently used for P-factor mapping and thus contribute to a refined soil erosion risk assessment.     

Topographic accuracy assessment of bare earth lidar-derived unstructured meshes

This study is focused on the integration of bare earth lidar (Light Detection and Ranging) data into unstructured (triangular) finite element meshes and the implications on simulating storm surge inundation using a shallow water equations model. A methodology is developed to compute root mean square error (RMSE) and the 95th percentile of vertical elevation errors using four different interpolation methods (linear, inverse distance weighted, natural neighbor, and cell averaging) to resample bare earth lidar and lidar-derived digital elevation models (DEMs) onto unstructured meshes at different resolutions. The results are consolidated into a table of optimal interpolation methods that minimize the vertical elevation error of an unstructured mesh for a given mesh node density. The cell area averaging method performed most accurate when DEM grid cells within 0.25 times the ratio of local element size and DEM cell size were averaged. The methodology is applied to simulate inundation extent and maximum water levels in southern Mississippi due to Hurricane Katrina, which illustrates that local changes in topography such as adjusting element size and interpolation method drastically alter simulated storm surge locally and non-locally. The methods and results presented have utility and implications to any modeling application that uses bare earth lidar.     

Sensitivity studies of a high accuracy surface modeling method

The sensitivities of the initial value and the sampling information to the accuracy of a high accuracy surface modeling(HASM) are investigated and the implementations of this new modeling method are modified and enhanced. Based on the fundamental theorem of surface theory, HASM is developed to correct the error produced in geographical information system and ecological modeling process. However, the earlier version of HASM is theoretically incomplete and its initial value must be produced by other surface modeling methods, such as spline, which limit its promotion. In other words, we must use other interpolators to drive HASM. According to the fundamental theorem of surface theory, we modify HASM, namely HASM.MOD, by adding another important nonlinear equation to make it independent of other methods and, at the same time, have a complete and solid theory foundation. Two mathematic surfaces and monthly mean temperature of 1951–2010 are used to validate the effectiveness of the new method. Experiments show that the modified version of HASM is insensitive to the selection of initial value which is particular important for HASM. We analyze the sensitivities of sampling error and sampling ratio to the simulation accuracy of HASM.MOD. It is found that sampling information plays an important role in the simulation accuracy of HASM.MOD. Another feature of the modified version of HASM is that it is theoretically perfect as it considers the third equation of the surface theory which reflects the local warping of the surface. The modified HASM may be useful with a wide range of spatial interpolation as it would no longer rely on other interpolation methods.     

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.