A DECISION MODEL TO PREDICT SEDIMENT YIELD FROM FOREST PRACTICES1

ABSTRACT: In order to choose among “best management practices,” forest managers need to predict sediment yield to perennial streams following various forest land operations. The “universal soil loss equation” (USLE) is not directly applicable to forest operations because of the heterogenous soil surface conditions left by harvesting, site preparation, and planting. A sediment hazard index is proposed, to be based on the amount of exposed mineral soil and its proximity to streams. The model offered includes rainfall erosivity, soil erodibility and average land slope, together with the index W. A paired watershed experiment in the central Georgia Piedmont was used to estimate parameters in the model. The experimental basin (80 acres) was clearcut, drum roller chopped twice, and planted by machine. The standard error of estimate of sediment yield was computed to be about 50/lbs/ac per sampling period (four months). Use of William's erogivity index (storm flow times peak flow) reduced the standard error to 33/lbs/ac.     

Allowable use estimates for tracked vehicular training on Pinon Canyon Maneuver Site,Colorado, USA

A method is presented for calculating allowable use of tracked vehicles on the US Army's Pinon Canyon Maneuver Site in southeastern Colorado. The first step in this process is to determine the sheet and rill erosion rate on each soil series using the revised Universal Soil Loss Equation. Soil series are then ranked according to their trainability (e g., ranked based on how much vegetative cover can be lost without exceeding soil loss tolerance) Maximum onetime surface use, allowable surface use per year, usable hectares per year, and tracked vehicle days per year can then be calculated Examples are given to illustrate how these values can be manipulated to assist land managers and military trainers to better plan and match training missions to available land. Also, short- and long-term monitoring schemes are presented that can be used to verify or adjust estimates of allowable use. The methods presented can be converted to determine allowable use of other types of activities that disturb the vegetation and expose the soil surface to the erosive forces of wind and water (e g, recreational and off-road vehicles).     

新疆土壤可蚀性K值空间插值及其分布特征研究

土壤可蚀性是土壤侵蚀预报和土地利用规划的重要参数,本文采用EPIC（Erosion Productivity Impact Caculator）模型中土壤可蚀性因子K值为指标,利用新疆土壤污染状况调查资料,探讨新疆土壤可蚀性K值及分布特征,并采用Kriging插值法进行全疆K值的空间插值。结果表明：新疆各类型土壤表层平均K值为0.238～0.441,主要分布在可侵蚀-易侵蚀-较易侵蚀范围;其中K值最大的土类为石质土和风沙土,均属于岩成土土纲;K值最小的土类为棕钙土;不同的土地利用方式,土壤可蚀性特征也不同,耕地土壤K值最大。从总体上看,土壤经过多年耕种,抗侵蚀能力明显下降。     

INTEGRATION OF GEOGRAPHIC INFORMATION SYSTEMS AND A COMPUTER MODEL TO EVALUATE IMPACTS OF AGRICULTURAL RUNOFF ON WATER QUALITY1

ABSTRACT: This study integrates an Agricultural Non-Point Source Pollution Model (AGNPS), the Geographic Resource Analysis Support System (GRASS) (U.S. Army Corps of Engineers, 1987), and GRASS WATERWORKS (a hydrologic modeling tool box being developed at the Michigan State University Center for Remote Sensing) to evaluate the impact of agricultural runoff on water quality in the Cass River, a subwatershed of Saginaw Bay. AGNPS is used to estimate the amounts, origin, and distribution of sediment, nitrogen (N), and phosphorus (P) in the watershed. GRASS and GRASS WATERWORKS are used to generate parameters needed for AGNPS from digital maps, which include soil association, land use, watershed boundaries, water features, and digital elevation. Outputs of the model include spatially distributed estimates of volume and peak runoff, overland and channel erosion, sediment yields, and concentrations of nitrogen and phosphorus. Management scenarios are explored in the AGNPS model to minimize sedimentation and nutrient loading. Scenarios evaluated include variations in crop cover, tillage methods, and other agricultural management practices. In addition, areas vulnerable to erosion are identified for best management practices.     

Environmental Condition Assessment of US Military Installations Using GIS Based Spatial Multi-Criteria Decision Analysis

Environment functions in various aspects including soil and water conservation, biodiversity and habitats, and landscape aesthetics. Comprehensive assessment of environmental condition is thus a great challenge. The issues include how to assess individual environmental components such as landscape aesthetics and integrate them into an indicator that can comprehensively quantify environmental condition. In this study, a geographic information systems based spatial multi-criteria decision analysis was used to integrate environmental variables and create the indicator. This approach was applied to Fort Riley Military installation in which land condition and its dynamics due to military training activities were assessed. The indicator was derived by integrating soil erosion, water quality, landscape fragmentation, landscape aesthetics, and noise based on the weights from the experts by assessing and ranking the environmental variables in terms of their importance. The results showed that landscape level indicator well quantified the overall environmental condition and its dynamics, while the indicator at level of patch that is defined as a homogeneous area that is different from its surroundings detailed the spatiotemporal variability of environmental condition. The environmental condition was mostly determined by soil erosion, then landscape fragmentation, water quality, landscape aesthetics, and noise. Overall, environmental condition at both landscape and patch levels greatly varied depending on the degree of ground and canopy disturbance and their spatial patterns due to military training activities and being related to slope. It was also determined the environment itself could be recovered quickly once military training was halt or reduced. Thus, this study provided an effective tool for the army land managers to monitor environmental dynamics and plan military training activities. Its limitation lies at that the obtained values of the indicator vary and are subjective to the experts' knowledge and experience. Thus, further advancing this approach is needed by developing a scientific method to derive the weights of environmental variables.     

SOIL EROSION AND SEDIMENT YIELD PREDICTION ACCURACY USING WEPP1

ABSTRACT: The objectives of this paper are to discuss expectations for the Water Erosion Prediction Project (WEPP) accuracy, to review published studies related to WEPP goodness of fit, and to evaluate these in the context of expectations for WEPP's goodness of fit. WEPP model erosion predictions have been compared in numerous studies to observed values for soil loss and sediment delivery from cropland plots, forest roads, irrigated lands and small watersheds. A number of different techniques for evaluating WEPP have been used, including one recently developed where the ability of WEPP to accurately predict soil erosion can be compared to the accuracy of replicated plots to predict soil erosion. In one study involving 1,594 years of data from runoff plots, WEPP performed similarly to the Universal Soil Loss Erosion (USLE) technology, indicating that WEPP has met the criteria of results being “at least as good with respect to observed data and known relationships as those from the USLE,” particularly when the USLE technology was developed using relationships derived from that data set, and using soil erodibility values measured on those plots using data sets from the same period of record. In many cases, WEPP performed as well as could be expected, based on comparisons with the variability in replicate data sets. One major finding has been that soil erodibility values calculated using the technology in WEPP for rainfall conditions may not be suitable for furrow irrigated conditions. WEPP was found to represent the major storms that account for high percentages of soil loss quite well—a single storm application that the USLE technology is unsuitable for—and WEPP has performed well for disturbed forests and forest roads. WEPP has been able to reflect the extremes of soil loss, being quite responsive to the wide differences in cropping, tillage, and other forms of management, one of the requirements for WEPP validation. WEPP was also found to perform well on a wide range of small watersheds, an area where USLE technology cannot be used.     

US army land condition-trend analysis (LCTA) program

The US Army Land Condition-Trend Analysis (LCTA) program is a standardized method of data collection, analysis, and reporting designed to meet multiple goals and objectives. The method utilizes vascular plant inventories, permanent field plot data, and wildlife inventories. Vascular plant inventories are used for environmental documentation, training of personnel, species identification during LCTA implementation, and as a survey for state and federal endangered or threatened species. The permanent field plot data documents the vegetational, edaphic, topographic, and disturbance characteristics of the installation. Inventory plots are allocated in a stratified random fashion across the installation utilizing a geographic information system that integrates satellite imagery and soil survey information. Ground cover, canopy cover, woody plant density, slope length, slope gradient, soil information, and disturbance data are collected at each plot. Plot data are used to: (1) describe plant communities, (2) characterize wildlife and threatened and endangered species habitat, (3) document amount and kind of military and nonmilitary disturbance, (4) determine the impact of military training on vegetation and soil resources, (5) estimate soil erosion potential, (6) classify land as to the kind and amount of use it can support, (7) determine allowable use estimates for tracked vehicle training, (8) document concealment resources, (9) identify lands that require restoration and evaluate the effectiveness of restorative techniques, and (10) evaluate potential acquisition property. Wildlife inventories survey small and midsize mammals, birds, bats, amphibians, and reptiles. Data from these surveys can be used for environmental documentation, to identify state and federal endangered and threatened species, and to evaluate the impact of military activities on wildlife populations. Short- and long-term monitoring of permanent field plots is used to evaluate and adjust land management decisions.     

Spatial and Temporal Assessment of Cumulative Disturbance Impacts Due to Military Training,Burning, Haying,and Their Interactions on Land Condition of Fort Riley

The effects of military training activities on the land condition of Army installations vary spatially and temporally. Training activities observably degrade land condition while also increasing biodiversity and stabilizing ecosystems. Moreover, other anthropogenic activities regularly occur on military lands such as prescribed burns and agricultural haying—adding to the dynamics of land condition. Thus, spatially and temporally assessing the impacts of military training, prescribed burning, agricultural haying, and their interactions is critical to the management of military lands. In this study, the spatial distributions and patterns of military training-induced disturbance frequency were derived using plot observation and point observation-based method, at Fort Riley, Kansas from 1989 to 2001. Moreover, spatial and variance analysis of cumulative impacts due to military training, burning, haying, and their interactions on the land condition of Fort Riley were conducted. The results showed that: (1) low disturbance intensity dominated the majority of the study area with exception of concentrated training within centralized areas; (2) high and low values of disturbance frequency were spatially clustered and had spatial patterns that differed significantly from a random distribution; and (3) interactions between prescribed burning and agricultural haying were not significant in terms of either soil erosion or disturbance intensity although their means and variances differed significantly between the burned and non-burned areas and between the hayed and non-hayed areas.     

QUANTITATIVE EVALUATION OF SEDIMENT DELIVERY RATIOS1

Ability to adequately estimate sediment yield is an important step in dealing effectively with soil erosion problems. Predictions of sediment yield made using the Universal Soil Loss Equation (USLE) with different forms of sediment delivery ratio (SDR) are compared with those made by Modified USLE (MUSLE) and a fundamentally derived Erosion-Deposition Model (EDM). The USLE and USLE with SDR are poor predictors of sediment yield for individual storms compared to the MUSLE and EDM. Although MUSLE gave better results than USLE it showed somewhat more scatter of data points than the recently developed EDM.     

Uncertainty analysis of predicted disturbance from off-road vehicular traffic in complex landscapes at fort hood

The US Army Engineering Research Development Center (ERDC) uses a modified form of the Revised Universal Soil Loss Equation (RUSLE) to estimate spatially explicit rates of soil erosion by water across military training facilities. One modification involves the RUSLE support practice factor (P factor), which is used to account for the effect of disturbance by human activities on erosion rates. Since disturbance from off-road military vehicular traffic moving through complex landscapes varies spatially, a spatially explicit nonlinear regression model (disturbance model) is used to predict the distribution of P factor values across a training facility. This research analyzes the uncertainty in this model's disturbance predictions for the Fort Hood training facility in order to determine both the spatial distribution of prediction uncertainty and the contribution of different error sources to that uncertainty. This analysis shows that a three-category vegetation map used by the disturbance model was the greatest source of prediction uncertainty, especially for the map categories shrub and tree. In areas mapped as grass, modeling error (uncertainty associated with the model parameter estimates) was the largest uncertainty source. These results indicate that the use of a high-quality vegetation map that is periodically updated to reflect current vegetation distributions, would produce the greatest reductions in disturbance prediction uncertainty.     

Empirical models based on the universal soil loss equation fail to predict sediment discharges from Chesapeake Bay catchments

The Universal Soil Loss Equation (USLE) and its derivatives are widely used for identifying watersheds with a high potential for degrading stream water quality. We compared sediment yields estimated from regional application of the USLE, the automated revised RUSLE2, and five sediment delivery ratio algorithms to measured annual average sediment delivery in 78 catchments of the Chesapeake Bay watershed. We did the same comparisons for another 23 catchments monitored by the USGS. Predictions exceeded observed sediment yields by more than 100% and were highly correlated with USLE erosion predictions (Pearson r range, 0.73-0.92; p < 0.001). RUSLE2-erosion estimates were highly correlated with USLE estimates (r = 0.87; p < 001), so the method of implementing the USLE model did not change the results. In ranked comparisons between observed and predicted sediment yields, the models failed to identify catchments with higher yields (r range, -0.28-0.00; p > 0.14). In a multiple regression analysis, soil erodibility, log (stream flow), basin shape (topographic relief ratio), the square-root transformed proportion of forest, and occurrence in the Appalachian Plateau province explained 55% of the observed variance in measured suspended sediment loads, but the model performed poorly (r(2) = 0.06) at predicting loads in the 23 USGS watersheds not used in fitting the model. The use of USLE or multiple regression models to predict sediment yields is not advisable despite their present widespread application. Integrated watershed models based on the USLE may also be unsuitable for making management decisions.     

Survey of land degradation in New South Wales,Australia

A survey of land degradation was undertaken in New South Wales, Australia during 1987–1988. The aims of the survey were to assess the location, extent, and severity of ten forms of degradation and to present the data in map and statistical form. Sample points were located on a regular grid. The method was designed so that data could be acquired from aerial photographs, expert local knowledge, and limited field checking. Individual statewide maps were prepared for each form of degradation. Map data were shown in pixel form. Sheet and rill erosion and soil structure decline were confined mostly to lands used for cropping. Gully erosion was commonly found across the state, while mass movement was confined to steeper lands. There were three severe areas of dryland salinity; irrigation salinity was mapped in parts of the southern irrigation lands. Induced soil acidity was severe in some cropping and pasture lands. Absence of tree regrowth was a noticeable feature of lands used for cropping. The survey enabled community awareness of the problems of land degradation to be increased, in addition to assisting regional land managers in resource allocation. The survey also provided the basis for the future location of sites that could be used to monitor the trends in the status of land degradation.     

MODELING UPLAND EROSION1

ABSTRACT: We have developed a computer model of soil loss on an upland watershed from the continuity considerations for sediment transport and from equations describing rill and interrill erosion. The model is based on dividing the upland area into a grid containing rill and interill zones, on the Universal Soil Loss Equation (USLE), and on equations describing detachment and transport capacity of rill flow. The USLE estimates the sediment load from the contributing areas. The location and amount of total erosion and deposition are determined by comparing the transport and detachment capacity of rill flow for specific storms. The model considers the mechanics of erosion process and can serve as basis for reservoir and channel design and land use planning.     

Simulating Spatial Pattern and Dynamics of Military Training Impacts for Allocation of Land Repair Using Images

The land management of US Army installations requires information on land conditions and their history for planning future military training activities and allocation of land repair. There is thus a strong need for methodology development to estimate the land conditions and cumulative military training impacts for the purpose of repair and restoration. In this study, we simulated at Fort Riley, USA, spatial patterns and temporal dynamics of military training impacts on land conditions quantified as percent ground cover using an image-aided spatial conditional co-simulation algorithm. Moreover, we estimated the historical percent ground cover as a measure of the cumulative impacts, and then calculated the allocation of land repair and restoration based on both current and historical land conditions. In addition, we developed a loss function method for allocation of land repair and restoration. The results showed: (1) this co-simulation algorithm reproduced spatial and temporal variability of percent ground cover and provided estimates of uncertainties with the correlation coefficients and root mean square errors between the simulated and observed values varying from 0.63 to 0.88 and from 23% to 78%, respectively; (2) with and without the cumulative impacts, the obtained spatial patterns of the land repair categories were similar, but their land areas differed by 5% to 40% in some years; (3) the combination of the loss function with the co-simulation made it possible to estimate and computationally propagate the uncertainties of land conditions into the uncertainties of expected cost loss for misallocation of land repair and restoration; and (4) the loss function, physical threshold, and probability threshold methods led to similar spatial patterns and temporal dynamics of the land repair categories, however, the loss function increased the land area by 5% to 30% for intense and moderate repairs and decreased the area by 5% to 30% for no repairs and light repairs for most of the years. This approach provided the potential to improve and automate the existing land rehabilitation and maintenance (LRAM) system used for the land management of the U.S. Army installations, and it can be applied to the management of other civil lands and environments. In conclusion, this study overcame the important gaps that exist in the methodological development and application for simulating land conditions and cumulative impacts due to human activities, and also in the methods for the allocation of land for repair and restoration.     

THE EFFECTS OF VEGETATION AND SOIL TYPE ON STREAMBANK EROSION,SOUTHWESTERN VIRGINIA,USA1

The goal of this research was to evaluate the relative effects of root density, freeze/thaw cycling, and soil properties on the erodibility and critical shear stress of streambanks. The erodibility and critical shear stress of rooted bank soils were measured in situ at 25 field sites using a submerged jet test device; several soil, vegetation, and stream chemistry characteristics shown to influence soil erosion were also assessed. Multiple linear regression analysis was conducted to determine those factors that most influenced streambank erodibility and the relative impact of riparian vegetation. Study results indicated that soil erosion is a complex phenomenon that depends primarily on soil bulk density. Freeze/thaw cycling, soil antecedent moisture content, the density of roots with diameters of 2 to 20 mm, soil texture, and the interaction of soil pore water and stream water had a significant impact on soil erodibility and critical shear stress, depending on soil type. Riparian vegetation had multiple significant effects on soil erodibility. In addition to reducing soil erodibility through root reinforcement, the streamside vegetation affected soil moisture and altered the local microclimate, which in turn affected freeze/thaw cycling (FTC). This study represents the first in situ testing of the erodibility of vegetated streambanks and provides a quantitative analysis on the effects of vegetation on streambank erosion, relative to other soil physical and chemical parameters.     

ESTIMATING EROSION RISKS ASSOCIATED WITH LOGGING AND FOREST ROADS IN NORTHWESTERN CALIFORNIA1

ABSTRACT: Erosion resulting from logging and road building has long been a concern to forest managers and the general public. An objective methodology was developed to estimate erosion risk on forest roads and in harvest areas on private land in northwestern California. It was based on 260 plots sampled from the area harvested under 415 Timber Harvest Plans completed between November 1978 and October 1979. Results confirmed previous findings that most erosion related to forest management occurs on a small fraction of the managed area. Erosion features larger than the minimum size inventories in this study (> 13 yd³) occupied only 0.2 percent of the area investigated. Linear discriminant analysis was used to develop two equations for identifying critical sites (sites with erosion >100 yd³ac^?1). The equations were based on slope, horizontal curvature (an expression of local topography), and soil color (on road sites) or the strength of the underlying rocks (on harvest sites). The equations can be used in planning to estimate the erosion risk of proposed activities. They can also be used to estimate acceptable risk thresholds based on the value of competing resources.     

Impacts from Above-Ground Activities in the Eagle Ford Shale Play on Landscapes and Hydrologic Flows,La Salle County,Texas

We assess the spatial and geomorphic fragmentation from the recent Eagle Ford Shale play in La Salle County, Texas, USA. Wells and pipelines were overlaid onto base maps of land cover, soil properties, vegetation assemblages, and hydrologic units. Changes to continuity of different ecoregions and supporting landscapes were assessed using the Landscape Fragmentation Tool (a third-party ArcGIS extension) as quantified by land area and continuity of core landscape areas (i.e., those degraded by “edge effects”). Results show decreases in core areas (8.7 %; ~33,290 ha) and increases in landscape patches (0.2 %; ~640 ha), edges (1.8 %; ~6940 ha), and perforated areas (4.2 %; ~16230 ha). Pipeline construction dominates landscape disturbance, followed by drilling and injection pads (85, 15, and 0.03 % of disturbed area, respectively). An increased potential for soil loss is indicated, with 51 % (~5790 ha) of all disturbance regimes occurring on soils with low water-transmission rates (depth to impermeable layer less than 50 cm) and a high surface runoff potential (hydrologic soil group D). Additionally, 88 % (~10,020 ha) of all disturbances occurred on soils with a wind erodibility index of approximately 19 kt/km²/year (0.19 kt/ha/year) or higher, resulting in an estimated potential of 2 million tons of soil loss per year. Results demonstrate that infrastructure placement is occurring on soils susceptible to erosion while reducing and splitting core areas potentially vital to ecosystem services.     

Assessing Degradation of Abandoned Farmlands for Conservation of the Monte Desert Biome in Argentina

Land abandonment is a major issue worldwide. In Argentina, the Monte Desert is the most arid rangeland, where the traditional conservation practices are based on successional management of areas excluded to disturbances or abandoned. Some areas subjected to this kind of management may be too degraded, and thus require active restoration. Therefore, the aim of this study was to assess whether passive succession-based management is a suitable approach by evaluating the status of land degradation in a protected area after 17–41 years of farming abandonment. Soil traits and plant growth forms were quantified and compared between sites according to time since abandonment and former land use (cultivation and grazing). Two variables were calculated using the CORINE-CEC method, i.e., potential (PSER) and actual (ASER) soil erosion risk. PSER indicates the erosion risk when no vegetation is present, while ASER includes the protective role of vegetation cover. Results showed that land use history had no significant effect on plant growth forms or soil traits (p > 0.05). After more than 25 years since abandonment of farming activities, soil conditions and vegetation cover had improved, thus having a lower ASER. Nevertheless, the present soil physical crusts may have delayed the full development of vegetation, enhancing erosion processes. Overall, this study indicates that succession-based management may not be the best practice in terms of conservation. Therefore, any effort for conservation in the Monte Desert should contemplate the current status of land degradation and potential vegetation recovery.     

Conservation strategies for effective land management of protected areas using an erosion prediction information system (EPIS)

This research demonstrates the predictive modeling capabilities of a geographic information system (GIS)-based soil erosion potential model to assess the effects of implementing land use change within a tropical watershed. The Revised Universal Soil Loss Equation (RUSLE) was integrated with a GIS to produce an Erosion Prediction Information System (EPIS) and modified to reflect conditions found in the mountainous tropics. Research was conducted in the Zenzontia subcatchment of the Río Ayuquíla, located within the Sierra de Manantlán Biosphere Reserve (SMBR), México. Expanding agricultural activities within this area will accentuate the already high rate of soil erosion and resultant sediment loading occurring in the Río Ayuquíla. Two land-use change scenarios are modeled with the EPIS: (1) implementation of soil conservation practices in erosion prone locations; and (2) selection of sites for agricultural expansion which minimize potential soil loss. Confronted with limited financial resources and the necessity for expedient action, managers of the SMBR can draw upon the predictive capacity of the EPIS to facilitate rapid and informed land-use planning decisions.     

Assessment of Soil Erodibility Indices for Conservation Reserve Program Lands in Southwestern Kansas Using Satellite Imagery and GIS Techniques

The soil erodibility index (EI) of Conservation Reserve Program (CRP) lands, which was the major criterion for CRP enrollment, was assessed for six counties in southwestern Kansas using USGS seamless digital elevation model data and Geographical Informational System techniques. The proportion of land areas with EI values of 8 or lower was less than 1% of the entire study area and most of the land areas (72.5%) were concentrated on EI values between 8 and 24. Although land acreage with EI values of 24 or higher decreased dramatically, the proportion of CRP lands to the other land-use types did not change much from low to high EI levels. The soil EI and physical soil characteristics of the CRP lands were compared to those of other land-use types. In general, the mean EI values of the land-use types were strongly correlated with physical soil properties, including organic matter content, clay content, available water capacity, permeability, and texture. CRP lands were compared in detail with cropland in terms of their soil characteristics to infer the pivotal cause of the land transformation. Although there was no significant statistical difference in EI between cropland and CRP soils, soil texture, soil family, and permeability were statistically different between the two. Statistical analyses of these three variables showed that CRP soils had coarser texture and higher permeability on average than cropland soils, indicating that CRP lands in the study area are drier than cropland soils. Therefore, soil moisture characteristics, not necessarily soil erosion potential, might have been the key factor for CRP enrollment in the study area.