Chapter 1PRIVATE

                                                    Introduction

Soil Erosion

            Recently the Environmental Protection Agency (EPA) and locally, the Department of Pollution Control and Ecology (DPC&E),  has sought to reduce the problem of soil erosion from construction sites. Soil erosion causes a loss of the productivity in the land, dumps millions of tons of sediment into waterways,  and provides a substrate for toxic chemicals which are carried into the water supply. The EPA estimates that over $13 billion is spent each year mitigating man-made erosion [2]. Those involved in construction work, developments and other disturbances of the land are now faced with large costs to comply with state and federal regulations. The Arkansas Highway and Transportation Department (AHTD) seeks to limit the amount of soil erosion from new construction sites. It is preferable and more effective to prevent soil erosion than to correct the damaging effects of erosion after it has occurred. The AHTD could receive substantial benefit from a software system designed to predict potential soil erosion from future and present construction sites. This project provides such a predictive tool for evaluating potential soil erosion for construction sites by using a mathematical model to predict soil loss in conjunction with a geographic information system (GIS).

Geographic Information Systems

            A Geographic Information System (GIS) is an information system that is designed to work with data referenced by spatial or geographic coordinates.  A GIS provides an automated manner of collecting, storing, manipulating, and displaying this data. A GIS provides a way in which to facilitate the management of geographic information. Francis Hanigan defined a GIS as the following:

 "Any information management system which can:

Ë Collect, store, and retrieve information based on its spatial location.

Ë Identify locations within a targeted environment which meet specific criteria.

Ë Explore relationships among data sets within that environment.

Ë Analyze the related data spatially as an aid to making decisions about that environment.

Ë Facilitate selecting and passing data to application-specific analytical models capable of assessing the impact of alternatives on the chosen environment.

Ë Display the selected environment both graphically and numerically either before or after analysis." [5]    

            A significant aspect of such systems is that they incorporate both a data base for spatially referenced data, as well as a set of operations for manipulating the data itself. Although the operations involved with a GIS can vary, the concept of layers in the data organization and structure is the basic principle on which a GIS operates. This data base layering concept is illustrated in the Figure 1-1.

            Figure 1-1 illustrates the data layering concept. Each layer represents a single attribute. For instance, the soils attribute would contain information on the type of soil (clay, loam, silt, etc.), while the topographic layer would contain information about variation in the surface of the land (mountains, hills, etc.). By combining this information about different layers the user can get information regarding different situations through the overlay of pertinent data.

            The data layers in a GIS are generally handled in one of two ways, either by a raster or a vector method. Raster data are represented by  uniform grid cells of specified resolution, and data are stored as a matrix of cells. Vector data layers are handled as lines between points. Figure 1-2 shows an example of a polygon represented in vector mode and in raster mode [6].

Generally, operations involving these two types of data are primarily oriented to either raster structures or vector structures, although a GIS usually incorporates algorithms that convert these structures from one to the other form depending on the actual system being used.

Geographic Resources Analysis Support System

            The Geographic Resources Analysis Support System (GRASS) is the GIS that is to be used for this research. GRASS is a public domain, general purpose, grid-cell based geographical modeling and analysis software package developed at the U.S. Army Corps of Engineers Research Laboratory (CERL). GRASS data bases consist of three major forms,  site or point, vector or line, and raster or grid. While the users of GRASS can model and conduct operations with vector data, it is primarily oriented to raster data.

            The GRASS system was chosen for use in this research because it is available on the University of Arkansas Campus through the Center for Advanced Spatial Technologies (CAST). Also there are large data bases with the actual data for parts of the state of Arkansas available through CAST.

                                            Chapter 2PRIVATE

                                     Review of Soil Erosion Models

Introduction

            Mathematical models to predict soil erosion are available in a variety of forms. Each of these erosion predicting models seek to predict erosion over a given time event (i.e. day, month, year). Soil erosion models seek to mathematically represent the actual erosion process. Critical to the use of any soil erosion model for this research is that the model must be usable with a GIS such as GRASS. Soil erosion models will be evaluated on the basis of the ease with which they can be understood by practitioners, their applicability for implementation with a GIS, and for the availability of data that their implementation would require.

             It is not within the time and scope of this project to cover all the possible models that exist in the current literature, but rather to take an in-depth look at the most commonly used erosion models. This will provide representative examples of soil erosion predictive models, and from these examples, the model will be chosen for implementation with GRASS. To that end, a classification scheme in Table 2-1 is presented that seeks to represent the variety of soil erosion prediction models found in the current literature. The table shows four basic levels, with Level 1 being the most simple of the models to understand and implement and Level 4 being the most complex and difficult.

             As stated above  there exists a great variety of soil erosion models in the current literature. This research focuses on the most commonly used models because,  "most models [soil erosion models] are sufficiently modular that component relationships can be changed to meet the specific needs of the user [11].  Models were chosen to cover in detail the four levels of mathematical difficulty and complexity (see Table 2-1). The models  analyzed were the Universal Soil Loss Equation (USLE), the Revised Universal Soil Loss Equation (RUSLE), Meyer and Wischmeier's Simulation of the Process of Soil Erosion By Water, the Nonpoint Source Pollutant Loading Model (NPS), the Watershed Erosion and Sediment Transport Model (WEST), and Storm Water Models (SWM). Most all of these models incorporate some or all of the factors of the hydrologic cycle  with some degree of success [10].

TABLE 2-1: Classification Scheme for Soil Erosion Prediction Models

 The levels of mathematical difficulty and complexity are shown in Table 2-1 [19]. Models will be examined from each of these four levels so that an accurate examination of soil erosion

prediction models can be researched. The mathematical difficulty along with ease of use, compatibility with GRASS, and availability of data, will determine which of the models is best for the prediction of soil erosion for highway construction projects.

                                               Universal Soil Loss Equation: USLE

Background Information

            The development of equations for calculating field soil erosion losses began in the 1940's with emphasis being placed on the prediction of soil loss for agricultural lands. Throughout the past years, these equations have been intensely studied and "improved" so as to provide improved prediction accuracy and validity. One of the more commonly used erosion prediction models developed is the Universal Soil Loss Equation (USLE). Developed with over forty years of data, it seeks to provide simplicity and accuracy for erosion modeling [32]. The USLE is a mathematical model that is used to compute the longtime average soil losses from sheet and rill erosion under specified conditions. It can be used for construction sites and other non-agricultural conditions. The USLE  does not predict deposition or compute the sediment yields from gullies, streambanks, and streambed erosion  [11, 33]. The USLE groups the primary factors of soil erosion into six groups which are described in later sections. As a result of the unpredictable short-time changes in the levels of influential variables, the USLE is less accurate for prediction of specific events than for prediction of longtime averages. However, since the primary purpose of this research is dedicated to construction projects that take a large amount of time to complete, for example six months to a year, specific events are not as great a factor, therefore the USLE is suitable for evaluating soil erosion for the present purpose.

Model and Components

            The Universal Soil Loss Equation is as follows [34]:

                                                          A=R x K x L x S x C x P

            where:

A         is the computed soil loss per unit area expressed in the units selected for K        and for             the period selected for R. In practice, these are usually selected so that they compute A       in tons per acre per year, but other units can be selected.

R,        the rainfall and runoff factor is the number of rainfall erosion index units, plus a    factor for runoff from snowmelt or applied water where such runoff is significant.

K,        the soil erodibility factor is the soil loss rate per erosion index unit for a specified soil      as measured on a unit plot, which is defined as a 72.6-ft length under identical         conditions.

L,         the slope-length factor is the ratio of soil loss from the    field slope length to that from     a 72.6-ft length under identical conditions.

S,         the slope-steepness factor is the ration of soil loss from the field slope gradient to that     from a 9-percent slope under otherwise identical conditions.

C,        the cover and management factor is the ratio of soil loss from an area with specified       cover and management to that from an identical area in tilled continuous fallow.

P,         the support practice factor is the ration of soil loss with a support practice like    contouring, stripcropping, or terracing to that with straight-row farming up and down             the slope.

 Rainfall and Runoff Factor (R)

            The numerical value of R in the USLE quantifies the raindrop impact effect and provides relative information on the amount and rate of runoff likely to be associated with the rain. The rainfall erosion index that is used by the USLE comes from Wischmeier's derivations [31, 35]. For studies in the state of Arkansas, R can be determined from Figure 2-1. A full map of the United Sates R values is included in Appendix B.

For example, to determine the R factor in Fayetteville, AR, the location of the site is examined in relation to the isoerodent lines on the map. In the case of Fayetteville, this site lies in-between the 250 R line and the 275 R line and would therefore be approximately 275. Since the erosive forces of runoff from thaw, snowmelt, and irrigation are considered negligible for the state of Arkansas, these factors will not be included in the factor R.

Soil Erodibility Factor (K)

            The soil erodibility factor quantifies soils that potentially erode more readily than other soils even when all other factors are the same. For instance, a loosely packed sandy soil might have a greater potential to erode than tightly packed clay soil. Values used for K were taken from Table 2-2 which can be found in the soil survey for Madison County in the state of Arkansas [28].

Table 2-2:  Computed K values for soils in Madison County, Arkansas

Topographic Factor (LS)

            The topographic factor (LS) comes from the steepness and length of the land from which the entire slope length drains into a particular spot. These two factors have a substantial effect on the rate of soil erosion by water. They are combined into a single factor for convenience and simplicity. The equation used to evaluate LS is:

                                        LS = (l / 72.6)^e( 65.41sin² q + 4.56sin q + .065 )

where:              l  = slope length in feet

                        e =  0.5 if percent slope is greater than 5

                        e =  0.4 on slopes of 3.5 to 4.5

                        e =  0.3 on slopes of 1 to 3 percent

                        e =  0.3 on slope of less than 1 percent

Cover and Management Factor (C)

            The cover and management factor (C) comes from land use and land cover from such things as vegetative canopies and trees. Factor C in the soil loss equation is the ratio of soil loss from land cropped under specified conditions to the corresponding soil loss from clean-tilled, continuous fallow [34]. The factor seeks to measure the combined effect of all the interrelated cover and management variables. Table 2-3 shows the C factors for current land use and land cover [15]. Although the values for C are available for various farm and land use conditions, this study will focus primarily on those values that pertain to construction areas. Since part of this study evaluates the amount of soil erosion that takes place after construction modifications are made to the land area, the factor C for mulches in this study is included in the Table 2-4. This table can be used when mulches are used and construction work has removed all vegetation and the root zone of the soil which removes the residual effects of prior vegetation. Table 2-4 gives the Cover and Management factors for a variety types of mulches which may be applied to the cleared construction area.

Table 2-3 : C factors for Land Use and Land Cover

Table 2-4 : Factor C for Various Mulches

Support Practice Factor (P)

            The support practice factor, P, is used primarily in croplands. When the sloping soil is to be cultivated and exposed to erosive rains, the protection offered by sod or close-growing crops in the system needs to be supported by practices that will slow the runoff water and thus reduce the amount of soil loss [22, 34]. Such practices for croplands are contour tillage, stripcropping on the contour, and terrace systems. In general, the value for P will usually equal 1.0 for construction sites because the erosion-reducing effects of shortening slopes or reducing slope gradients are accounted for through the LS factor [36].

Conclusions

            The USLE has several advantages over other models. The first and foremost is its simplicity: "The Universal Soil Loss Equation (USLE) is the most widely accepted, user-friendly erosion prediction model currently available [29]." Also, the USLE requires the use of certain data which are available, such as soil types and slope,  parameter values which are readily available, adaptable to nonuniform areas where deposition does not occur [10],  and is widely used by agencies like the USDA-Soil Conservation Service. The model can be implemented in GRASS with the development of the appropriate software for the calculation of parameters such as the LS factor. The model does have some disadvantages, which are listed below:

            (1)        The USLE methodology does not account for the effects of                   antecedent soil moisture or the availability of detached soil particles.

            (2)        The USLE contains no term to specifically account for the effects of overland                 flow,  the major transport mechanism by which soil erosion occurs. Research has                        shown that runoff is the best single indicator of sediment yield from small                  watersheds [1,7]. This is reflected in recent modifications of the USLE to                       specifically include the effects of runoff [8, 30].

            (3)        Although the factors in the USLE are directly relevant to the soil                        erosion process (especially K, C, P) , the formulation of the USLE does not                        specifically evaluate the mechanisms of soil detachment and transport;                                  these are the major determinants of erosion during storm events.

            (4)        The USLE was originally developed for estimates ofaverage annual soil loss from                       croplands east of the Rocky Mountains. It has had limited success in other areas                and has been modified numerous times to adapt to local conditions [6].

            (5)        Soil losses computed with the USLE are best available estimates, not absolutes.                         They will generally be most accurate for medium-textured soils, slope lengths of                less than 400 ft, gradients of 3 to 18 percent, and consistent cropping and                 management systems that have been represented in the erosion  plot studies. The                  farther these limits are exceeded, the greater will be the probability of                 significant extrapolation error [37].

While these disadvantages may be important, the real value of the USLE lies in its ease of use and knowing its limitations.

                                       Revised Universal Soil Loss Equation: RUSLE

Background Information

            The Revised Universal Soil Loss Equation is being developed by the USDA's Agricultural Research Service. The model will refine and improve the accuracy of the original Universal Soil Loss equation (USLE) to estimate the effects of various conservation systems on soil erosion  [21]. As of this date the revised model is not yet completed [20]; however, it remains an important extension of the work done in this research because the model's basic structure remains the same while the data tables associated with the components have changed. Since the data tables are the only elements to change, the RUSLE could be used with the existing code.

            The USLE was initially designed to assist farmers and soil conservationists in farm planning. The data provided for in the USLE was oriented and developed for use on cropland, but by the early 1970's it was being applied to rangeland, disturbed forest land, urban construction areas, highway embankments. Due to the widespread application of the USLE, much of the accuracy and "technical soundness" were causing controversy [23].  The basic RUSLE changes seek to provide improvements in knowledge and technology  and put them into the older, USLE model. The results provided in the RUSLE will be an improved soil loss estimate primarily by changing or updating the database and tables that are referenced for the various factors in the model [21].

Model and Components

Even though the model is not yet done, the importance in examining  the RUSLE is that the primary factors (A=R x K x L x S x C x P) do not change; only the data tables associated with the primary factors change. Thus, once the improved model is finished, it should be relatively easy to use the RUSLE in GRASS and this research. Table 2-5 shows some of the major differences as well as similarities between the RUSLE and the USLE [21] .

Table 2-5: USLE vs. RUSLE: Similarities and Differences

Table 2-5 (continued): USLE vs. RUSLE: Similarities and Differences

Conclusions

             In terms of complexity the RUSLE would remain a Level 1 model because no delivery mechanism exits for the movement of sediment and water. While both the USLE and the RUSLE do not represent fundamental hydrologic and erosion processes, the RUSLE does provide an excellent  simplified representation of the first-order effect of the factors that affect sheet and rill erosion [23]. The final drafts of the documentation on the RUSLE are being reviewed by technical specialists in the USDA and in addition to updates in the tables for the primary factors, the model is designed to run on a personal computer with a DOS or UNIX operating system [20, 23]. The Revised Universal Soil Loss Equation will provide much better prediction capabilities and could be implemented with the software system that will result from when the revisions are available.

                              SIMULATION OF THE PROCESS OF SOIL EROSION

Background Information

            In 1969 L.D. Meyer and W.H. Wischmeier developed a mathematical model for predicting soil erosion. Empirical relations were determined from collected data and then were combined in equations designed to predict long-term soil losses from the particular tracts of land under various combinations of land use and management. "The model presented seeks to detail soil erosion as a dynamic process and is concerned with the feasibility of separating the soil-erosion process into several component processes rather than obtaining quantitative results [18]."

Model and Components

            The component parts of the model considered were soil detachment by rainfall, transport by rainfall, detachment by runoff, and transport by runoff as separate but interrelated phases of the process of soil erosion by water [18].

            By looking at the model in flow chart form we can see the basic components and processes at work in Figure 2-2. Figure 2-2 illustrates how the model was simulated by Wischmeier with regard to the basic erosion components, as well as how the movement of sediment is accomplished [18].

An examination of each of the terms that are in the simulation by Wischmeier and Meyer provides insight into how the actual erosionprocess was modeled.

Model & Components

            D_R= The detachment of soil particles due to rainfall. D_R is          calculated by the following equation: 

                                                                D_R = S_DR x A_I x I²

                        where:

                        S_DR=  mathematical constant that is a function of the soil                                    type.

                        A_I =  area of increment.

                        I  =  Intensity.

            D_f = The detachment of soil particles by runoff calculated by:

                                              D_f=S_DFA_I1/2(S_s 2/3Q_s 2/3+S_E 2/3Q_E 2/3)

                        where:

                        S_DF = mathematical constant for soil type/properties

                        S_S  = slope steepness at the start of the increment

                        S_E = slope steepness at the end of the increment

                        Q_S = flow rate at the start of the increment

                        Q_E = flow rate at the end of the increment

                        T_R= the transportation capacity of rainfall calculated by                         the equation:

                                                                     T_R= S_TRS I

                        S_TR= mathematical constant soil effect

                        T_F= the transportation capacity of runoff calculated by               the equation:

                                                                  T_F= S_TFS^5/3Q^5/3

                        where:

                        S_TF= mathematical constant for the effect of particle size                        and density on the soil's transportability

Calculation of D_R

            The detachment of soil particles due to rainfall D_R is      calculated by

                                                                D_R = S_DR x A_I x I²

            where:

                        S_DR is a constant that takes into account such things as               soil type and density.

Calculation of D_F

            The detachment of soil particles by runoff is calculated by:

                                              D_f=S_DFA_I1/2(S_s 2/3Q_s 2/3+S_E 2/3Q_E 2/3)

Computational Steps for the Prediction of Soil Loss

            Step 1: Calculate D_R, D_F, T_R, and T_F.

            Step 2: Calculate the Total Detached Soil = D_R+D_F

            Step 3: Calculate the Total Transport Capacity = T_R+T_F

            Step 4: Compare the Total Detached Soil and the Total                        Transport Capacity. If the Total Detached Soil is less                     than the Total Transport Capacity of the soil, then the                amount of Soil Carried to the next increment is equal to                 the amount of available material.  If on the other hand,               the Total Transport Capacity is less than the soil                              available for erosion, then the sediment load equals the              transport capacity.

            Step 5: Calculate the Total Erosion. This is the value acquired from Step 4 minus the                 previous sediment yield. If the values are negative this indicates a deposition.

Conclusions

            The simulated approach to erosion prediction is a Level 2 type of model because the model uses a routing procedure for the movement of sediment. The primary strength that the model has is that the relationships reflect interactions between detachment and transport by rainfall and runoff. The model is also able to reflect interactions due to spatial variability. However, the model has limitations in that it requires calibration and it does not include such things as channeling [1]. The model also does not include the following items:

            1. Seepage and other subsurface flow phenomena as they affect soil erosion.

            2. Vegetation and crop residues as they affect the erosive potential of rainfall and                       runoff.

            3. Tillage, freezing and thawing and other natural or man-caused actions as they                            influence soil detachment and transport.

            4. Land topography and microtopography as they affect storage, overland flow, and                  exposure to rainfall.

            5. Surface-water depth as it affects detachment and transport.

            6. Accumulation of excess detached soil available for removal during subsequent periods              of greater transportation capacity.

            7. Additional interrelationships among the subprocesses [18].

The model presented by L.D. Meyer and W.H. Wischmeier provides modeling of  interactions between detachment and transport by rainfall and runoff. The approach treats soil detachment by rainfall, transport by rainfall, detachment by runoff, and transport by runoff as separate but interrelated parts of the soil erosion process. The model has additional advantages of reflecting interactions between detachment and transport by rainfall and runoff, and is able to reflect interactions due to spatial variability. However, the model requires a great deal of calibration for a given area and would require a database of such elements as particle size and would also require a continuous simulation type approach. This continuous simulation approach would not be appropriate for implementation with a GIS such as GRASS since a GIS is not designed to handle functions of time in a continuous manner as is required in this model.

                                             Nonpoint Source Pollutant Model: NPS

Background Information

            In examining the literature, the Universal Soil Loss Equation is not applicable to the continuous simulation of soil erosion  processes although it has been used for this purpose [6]. The NPS Model was developed to provide a consistent method of simulating soil erosion and nonpoint pollution transport from both pervious and impervious areas and is shown on the next page [6]. In  July of 1976 a model was developed by Anthony S. Donigian and Norman H. Crawford.  The results of their work was called the Nonpoint Source Pollutant Loading (NPS) Model. The NPS uses subprograms to represent the hydrologic response of a watershed and includes such things as snow accumulation and melt, the processes of pollutant accumulation, generation, and washoff from the land surface. The model's primary use lies in its ability to predict pollutants in a watershed, but it can also be used to predict sediment erosion since this is the major mechanism by which it tracks pollutants.

Model and Components

            The model continuously simulates the hydrologic processes of snow accumulation and melt, sediment generation, pollutant accumulation, and pollutant transport. NPS is made up of three major components which are shown in Figure 2-3 [6]. The flow chart represents the basic operations of the NPS model. The MAIN section acts as the master or executive routine and does those tasks contained within the dashed line in  Figure 2-3. The NPS model integrates the hydrological cycle in the LANDS module which was originally derived from the Stanford Watershed Model [5, 38]. The QUAL subroutine simulates erosion processes, sediment accumulation, and sediment and pollutant washoff from the land surface.

Table 2-6: Parameters of the LANDS Module

            The major parameters of the LANDS subroutine are given in Table 2-4 [6]. The flowchart provided in Figure 2-4 shows the subprogram of LANDS. The LANDS subprogram (see Figure 2-4) operates continuously on a 15-minute interval throughout the simulation period. Daily potential evapotranspiration and precipitation for 15-minute or hourly intervals are required inputs. If snowmelt simulation is not performed, precipitation first  encounters the interception function. The storage function of interception is dependent on vegetation and land cover. In many areas interception capacity will vary with the season of the year.

When interception storage is filled, any remaining precipitation is added to the moisture supply of the infiltration function, which performs the basic division of available moisture into surface detention, interflow detention, and infiltration. Surface detention includes overland flow and an increment to upper zone soil moisture storage. Interflow detention is a delay mechanism controlling the release of interflow to the stream. Infiltration and percolation from the upper zone provide the means by which moisture reaches lower zone storage. From lower zone storage, moisture moves to active ground water storage from which the ground water component of streamflow is derived ." [6]  The  evapotranspiration values occur at different rates form each of the moisture storage.

            The QUAL portion of the model, as stated earlier, is used for simulating nonpoint pollutant accumulation and transport. A flow chart is provided for the QUAL subroutine in Figure 2-5. Operation of the QUAL subroutine in Figure 2-5 is directly controlled by the MAIN part of the NPS model. The subroutine consists of two alternate loops, each one iterated with different frequency, depending on the rainfall and runoff conditions as they are transferred from the LANDS subprogram. "The major portion of the QUAL algorithm pertains to the 'storm day' path. The key portions of this loop are the analytical representations from pervious and impervious areas. Simulation of these processes is carried out for each land use within the watershed. The aggregate quantities of the washed-off sediments and pollutants are summed to yield the total mass and the equivalent concentration of pollutants in the overland flow." [6]

Conclusions

            The NPS has potential for simulation in a continuous environment. For purposes of this research, the model would be classified as a Level III model because it incorporates hydrograph theory as well as water-quality modeling where concentration of sediment is a  significant indicator of pollution. To validate the model, simulations were conducted and actual data was compared against that found in the simulated runs and the results compared favorably in terms of accuracy and precision. NPS provides a means for simulating sediment runoff; however, the complexity and amount of data required to calibrate the model, as well as its continuous simulation nature, preclude its use with a GIS.

                         Watershed Erosion and Sediment Transport Model: WEST/ARM

Background Information

            The Watershed Erosion and Sediment Transport (WEST) model was engineered to simulate and predict both water and sediment movement from the land surface and through the stream system of a watershed [13].  The development of the WEST model in 1979 incorporated the ARM model developed in 1976 and the CHANL model. The WEST model is a combination of both the ARM and the CHANL model, which are linked by a simple data management system. The ARM model [13] simulates the land paths processes and the CHANL Model simulates the in-stream or channel process.

Model and Components

            The fundamental principle underlying the WEST Model is that simulation of the processes in a watershed can be performed in two distinct phases: a land phase and a channel phase shown in Figure 2-6 [13]. Figure 2-6 shows the flow  of information involved in the land paths of the WEST simulation [13].  Inputs of hydrometeorologic data are transformed by the ARM model to time series outputs of land surface runoff (LSRO) and land surface erosion (EROS). LSRO is the depth of runoff, both surface and subsurface, flowing into the stream system in each modeling interval for a particular segment. EROS is the mass sediment washoff per unit area reaching the stream system in each modeling interval. Both LSRO and EROS, representing the response from a unit, are written to disk in specially formatted data files for use as input to the CHANL model.  For sake of clarity, the previous figure only shows one LSRO and one EROS file. In practice, for a watershed divided into a number of segments, one LSRO file and one EROS file would be produced for each segment [19].

            The ARM portion of the WEST model simulates the processes of surface and subsurface hydrology, sediment production and removal from the land surface,   absorption / desorption and degradation processes for pesticides, and then outputs both runoff and sediment contributions to the stream channels which are used as input to the channel phase simulation . The CHANL portion of the WEST model operates on the inputs to give flow discharge and sediment transport rates at the required points in the system. The outflow from each segment or reach is computed every time interval and becomes the inflow to the channel immediately downstream [13]. This portion of the model is very complex and uses algorithms which have the principle variables of flow discharge, depth of flow, cross-sectional area, energy slope, sediment transport concentrations, and channel be composition [19]. Hydraulic routing is performed by using a kinematic wave approximation of water flows. Sediment routing is performed by explicitly modeling the component processes such as scour, deposition, and armoring. This is done to keep the range of application of the model as wide as possible and to facilitate its extension to cover other processes dependent on sediment movement, such as those affecting nutrients and pesticides  [13].

Conclusion

            The WEST model was developed to simulate the movement of water and sediment through the land channel phases of the hydrologic cycle. The WEST model is a very complex series of simulations and is classified as a Level 4 model with regard to mathematical complexity. In terms of both precision and accuracy, its estimates for erosion and sediment yield are promising, and in fact the CHANL gave favorable results when tested on laboratory data from the Georgia Institute of Technology and file data collected  by the U.S. Geological Survey on the East Fork River, Wyoming [13].  The strengths of the ARM portion of the model are that it considers the erosion-sediment yield subprocesses and uses hydrologic inputs for both rainfall and runoff to get interaction effects. However, it has certain limitations in that it lumps parameter values over the watershed, requires historical data to calibrate, and there may not be transferable to ungaged areas and to land uses significant different those used during the mode calibration [10]. Of importance to this study, this continuous model cannot be implemented with a GIS.

                                                             Storm Water Models

Background Information

            Storm Water Models known as SWM's are significant in the current research in that they describe both stormwater quantity and quality. Currently, the most commonly used or reference SWM models are  Stormwater Management Model (SWMM) [12, 17, 26, 39],  Storage, Treatment, Overflow, Runoff Model (STORM) [23, 31], and Hydrologic Simulation Program, Fortran (HSPF) [9, 38]. Often times these models provide mechanisms for estimating erosion or stormwater runoff.

            "SWM models can be categorized into the following:

            1. Models for predicting stormwater runoff pollution loadings.

            2. Models for describing the transformation and transport of stormwater generated                       pollutants.

            3. Models for describing pollutant-removal mechanisms.

            4. Models for SWM strategies, for example, models for strategically locating detention    ponds." [39] 

Model and Components

These models typically have three major components consisting of:

            1. Overland flow component: quantity and quality, including pollutant accumulation            and washoff and transport over land surface.

            2. Drainage system component: quantity and quality, including channel or pipe                   flow transport, storage routing (such as detention ponds), etc.

            3. Receiving water component: quantity and quality, including fate and transport of                        pollutants and receiving water response (most SWM models do not include this                          component).

Figure 2-7 shows how these three modules are combined to provide a prediction of stormwater quality and quantity [39].

Stormwater Models

Table 2-7, taken from the Virginia Department of Transportation Manual sums up the basic capabilities of the SWM models in the current literature [39].

Table 2-7: A Comparison of Stormwater Models

Conclusions

            The SWM's presented in this review are more oriented to an urban environment and are particularly useful in estimating stormwater planning and are not necessarily useful for estimating erosion prediction. While they can be used to estimate sediment yield, the use of other models seems more appropriate considering the time and money that would be involved in using these models with GRASS or any GIS. Another complicating factor is that SWM's often require a continuous type simulation while GRASS is oriented towards predicting erosion at a point in time. In addition, these models often require a substantial amount of data taken at short time intervals and under various "environmental" conditions, to enable one to differentiate the previously mentioned factors and obtain definitive estimates of stormwater runoff pollution loads [39].

                           Chapter 3PRIVATE

                Primary Goal & Model Selection

Primary Goal 

            The primary goal of the current research is to design a software system for predicting erosion potential at construction sites. This system will incorporate the GRASS GIS and the data bases for GRASS that have been built and maintained by CAST. The results of the evaluation for various erosion prediction models reported in Chapter 2 and the availability of data for GRASS has resulted in the use of this GIS for this project. The software system will allow the user to simulate the application of preventative erosion practices as well as construction methods such as clearing and grubbing. For example, the designer of a proposed construction site could use this system to simulate the application of various mulches or other erosion reducing products to land that is to be altered and then calculate the effect on the potential soil erosion as compared to no use of such products. The software system will focus on allowing the user to be able to do the following:

            1.         Calculate and display the erosion potential for a                         geographic region based on an erosion prediction model.

            2.         Zoom in on a region for closer examination.

            3.         Define an area proposed for construction where                        modification will take place.

            4.         Display and report the predicted amount of erosion that                         will result from disturbing the land, given certain                 construction methods.

            5.         Simulate the application of mulches to an area to reduce                        erosion and then recalculate the amount of erosion that               will occur.

            6.         Simulate future erosion prevention techniques in the                   software system.

Model Selection

            To accomplish the primary goal a soil erosion model was chosen that could be implemented using a GIS. The Universal Soil Loss Equation (USLE) was selected on the basis of criteria including its prevailing widespread use, its compatibility with GRASS, and the availability of data for the GRASS system. The USLE provides an efficient means of analyzing potential soil erosion as well as a mechanism for simulating different types of mulching factors to modify erosion taking place at construction sites.

            The USLE can be used to accomplish this because values for all of its parameters for erosion can either be obtained directly from primary data layers in existing data bases or can be derived from the primary data layers into secondary data layers that can then be used to predict erosion potential. For example, the USLE requires the use of slope and slope length for a given area to determine a LS factor that is used in the basic equation for predicting erosion. Slope and slope length can be derived from the primary data layer of elevation and would be considered secondary data layers since they derive from a primary data layer. The derivations of secondary data layers are efficient since they do not require the collection of new data for an area. The other models examined would require field collection of data for pertinent parameter values. Because of the factors cited above, the USLE was determined to be the most appropriate choice and will be used throughout the remainder of this research to predict potential soil erosion.

                           Chapter 4PRIVATE

               System Design & Software Overview

System Design

             The software system is designed to run on a SUN work station under the X Windows System which is a network-based graphics window system. The software developed to predict erosion took into account construction practices and erosion prevention measures. The software system is divided into four main modules that work together to provide an estimate of erosion potential for a variety of construction situations. These four modules are: setup, definition of a construction area, simulation of clearing and grubbing, and the simulation of the application of mulches. Figure 4-1 shows how the four main modules work in the software system and the functions that take place under each module. The system uses the existing GRASS data bases as a source of the primary data layers. Secondary data layers are derived from the primary data layers, such as slope length from elevation. The setup module then uses both the primary and secondary data layers to conduct an initial erosion estimate. The other modules use the information from the setup module to allow the user to simulate altering the land to design considerations and obtain an erosion potential estimate. The software system reports the erosion potential estimate and a visual representation of the erosion that would occur from altering the geographic region.

Setup

            The setup portion of the software system is called setup_erosion. The purpose of this part of the program is to establish the file names of the required primary data layers.  Once the names are known, then the software calculates an erosion estimate for the geographic region under consideration. The setup module prompts the user for the names of primary data layers because the system has to know what the user has defined for these data layers. For example, the user may have digitized a map of elevation values required as one of the primary data layers, and this data layer may have been named  "elevation.values" as the file name. When the setup module prompts the user for the name of the elevation data layer, the user would enter "elevation.values". From that point on the software system would know what the elevation data layer is named so the values from this file may be used in calculating erosion potential. This process is repeated in the setup module for required data layers used by the system. Once the user provides the names of the required primary data layers, the system derives the necessary secondary data layers and then calculates a data layer containing estimates for erosion potential based upon the geographic region defined by the user. Once this has been done for the geographic region of interest, this process need not be done again. However, if a new region is to be assessed for erosion potential, then the setup process must be rerun for the new area. After the setup_erosion portion of the software is done, the user would normally go to the portion of the program for defining of a construction area.

Defining of a construction area

            This portion of the software system is the main area from which the user accesses the erosion prediction ability of the system. This module of the software is called erosion1. The user can view the current erosion map on the monitor screen, zoom in on an area for a closer look, and also define an area (s) for construction. The main purpose of this portion of the software is to define the area on which modifications will be required by the construction design. The user uses a pointing device such as a mouse to establish the boundaries of a proposed construction area. Once the construction area is established the software allows the user to simulate the application of measures such as clearing and grubbing, mulches, and other erosion prevention techniques. The software also reports the amount of erosion potential on a before  and after basis with regard to erosion potential  of the defined construction area.

Clearing and Grubbing

            The name of the program that simulates clearing and grubbing is called erosion2. This portion of the software consists of two major parts. First, once the construction area is established by the user, the user has the option of simulating clearing and grubbing of the area. After this option is selected, a report is generated which gives the predicted amount of erosion potential before clearing and grubbing, and after clearing and grubbing.  The second function of erosion2 allows the user to define a new technique or new material for preventing erosion. For example, suppose that a new type of geotextile blanket is developed that is considerably more effective at reducing erosion than the application of mulches which are currently provided for in the software. The user can enter this new material along with the C factor associated with this particular type of erosion prevention measure. This allows for future improvements to erosion prevention to be used with the software. Once the new type of erosion prevention measure is given, a before and after analysis of the erosion potential will be completed and reported back to the user.

Application of Mulches

            The final portion of the software deals with applying various types of mulches [40]  to the defined construction area and is called erosion3. Erosion3 uses simulates the application of mulches to an area that is already supposed to be cleared and grubbed. Once a mulch such as straw or gravel is supposed to be applied, the software considers such things as slope and type of mulch to determine a new estimate of erosion potential based upon the application of this mulch. Once the application of the mulch is simulated, a before and after analysis allows the user to compare the amount of erosion potential reduction that would be afforded by the proposed mulch.

Menu Structure

            The menu structure is provided in Figure 4-2 to show how the menus interconnected to allow the user to efficiently use the software system. The menu commands are displayed on the graphics monitor running under the GRASS platform. The user selects these menu commands by clicking with the left button of the mouse. Once the user selects a menu option this either executes a series of instructions or accesses another  menu.

Software Overview

            The focus of the software system is to allow the simulation of a change of the  cover and management factors (C factors) as a parameter in the USLE. The GRASS command r.digit is an interactive tool used to draw and save vector and raster features on a graphics monitor using a pointing device such as a mouse. The software system allows the user to select geographically specific areas with a computer mouse. Following the selection of an area, such construction techniques as clearing and grubbing or application of mulches, are simulated to predict the before and after erosion potential. Once a construction area is selected, new C factors are pertinent to that area for simulating different practices. The program recalculates erosion potential taking into account the proposed modifications to the land. Using the C factor data layer, an example is shown below in Figure 4-3 of the basic principles on which the software works. In this example, a  sample area will be supposed to be cleared of all vegetation and root structure ( i.e. cleared and grubbed). The area shaded in gray represents an area selected by the user via a pointing device such as a mouse and the raster values for this area are given. Once this area has been defined the user is asked what modifications are to be simulated in the selected area (gray). In this example the land is proposed to be cleared and grubbed. The original C factors are modified to reflect the clearing and grubbing by changing these factors to higher C factors. After the new  C factors are changed to reflect modifications to the land, new values for the potential erosion are calculated for the areas in gray.

Conclusions

            The major portions of the software, setup_erosion, erosion1, erosion2, and erosion3, work together to provide the user with an estimate of erosion potential for a variety of construction practices. The system allows the user to obtain a prediction for erosion potential based on a before and after scenario, which allows the user to determine the most effective erosion prevention program for a specific area. Also, the software system allows for the computation of the relative differences between different types of erosion prevention techniques.

                           Chapter 5PRIVATE

             USLE Factors and Software Development

Introduction

            Development of  software using the USLE as a model to predict soil erosion potential began with examining the primary data layers  and factors required by the USLE to calculate erosion potential. These data layers are usually input by hand or from  such devices as map digitizers or from digitized satellite imagery. Secondary data layers are those that are derived from the primary data layers. For example, the data layer for elevation values for a given area can be used to determine the slope data layer for the same area. The elevation data layer is considered a primary data layer. The derived data layer of slope is considered to be a secondary data layer since it is calculated from the primary data layer of elevation. For this research the primary data layers are, elevation (in meters), soil classification, cover and management ( C factor), and a data layer that identifies current existing water areas such as lakes and streams.

            Each factor for the USLE (R, K, LS, C, P) is represented in a data layer that is accessed by GRASS to predict the potential erosion at a given location. The data for the USLE factors is manipulated by different raster operations accomplished be GRASS commands,  such as the command r.mapcalc. This GRASS command  is used for manipulating and performing operations on maps represented as raster based data layers. New raster map layers can be created which are arithmetic expressions involving existing raster map layers, integer or floating point constants, and functions [25].

            The maps that GRASS uses for calculations and for displaying images on the screen are data base files stored in raster format, i.e., two-dimensional matrices of integer values. With r.mapcalc, cell position in a map may be followed by a neighborhood modifier that specifies a relative offset from the current cell being evaluated. The format is map_name [ row, column]. As an example, map [1,1] refers to the cell one row below and one column to the right of the current cell. Figure 5-1 shows a representation of how r.mapcalc identifies a particular cell in a data layer name map.

Neighborhood identifiers are used in the developed software system to calculate the slope  length needed for the USLE. In addition, the area that is used to demonstrate the developed system is Huntsville quadrangle which is in northwest Arkansas.

Rainfall and Runoff Factor (R)

            The rainfall and runoff factor is used to approximate the amount and intensity of rainfall for a given area over a period of a single year. The rainfall and runoff factor is the number of rainfall erosion index units, plus a factor for runoff from snowmelt or applied water where such runoff is significant [34]. For northwest Arkansas, this factor is 275 [35] for the Huntsville area (for a more detailed map of R factors see Appendix C for a map of the entire United States). The factor R was input into the potential erosion calculations by using the r.mapcalc statement in GRASS.  In calculating the potential erosion the following  GRASS command was used in Equation [1]:

            r.mapcalc erosion = 'round((275*(kfactor * 0.01)*(lsfactor *                                                            0.01)*(cfactor*0.001) ))'                                                                               

                                                                                                                        Equation [1]

This command uses 275 as a constant for this area so it was not necessary to create data layer for the R factor.

Soil Erodibility Factor (K)

            The soil erodibility factor is the soil loss rate per erosion index unit for a specified           soil as   measured on a unit plot, which is defined as a 72.6-ft length under identical conditions [34]. This factor is specific to the type of soil under consideration for a given area and is between 0 and 1. The soil erodibility factor is a primary data layer and is found in the soil survey document of the area. Since GRASS can only store integer numbers in the data layers, these factors were multiplied by a factor of 100 for relative accuracy. The values  used for K in this analysis were taken from Table 2-1 which can be found in the Soil Survey For Madison County in the state of Arkansas [28].  As an  example, in the soil survey for Huntsville, AR, the  K factor for the soil called Allen is 0.28, this value is stored as the integer 28 representing the soil Allen. A portion of the actual data layer is illustrated in Table 5-1.

Table 5-1: Example of K factors in GRASS

Cover and Management Factor (C)

            Cover and management factors come from land use and land cover from such things as vegetative canopies and trees. The C factor in the soil loss equation is the ratio of soil loss from land cropped under specified conditions to the corresponding soil loss from clean-tilled, continuous fallow land [34]. The factor measures the combined effect of all the interrelated cover and management variables. The  C factor is a required primary data layer and the value is between 0 and 1. These values can be found in Table 2-3 and Table 2-4 for the different types of cover and mulches that can be applied. The values for the C factor can be quite small and as a result a factor of 1000 was applied to the various C factors for relative accuracy. A sample of data for the C factor data layer is shown in Table 5-2 with the applied factor of 1000 illustrated. As an example, the C factor for a residential area is 0.003 and this number multiplied by 1000 would be stored in a GRASS data layer as the integer 3.

Table 5-2: Example of C factors in GRASS

Support Practice Factor (P)

            The support practice factor, P, is used primarily in croplands.  Such practices for croplands are contour tillage, stripcropping on the contour, and terrace systems. As stated in Chapter 2, the value for P is equal to 1.0 for construction sites [34, 36]. Since the value of the P factor is 1 and the data layers are multiplied with each other, it is not necessary to create a specific data layer.

Slope-Length Factor (LS)

            The topographic factor (LS) comes from the steepness and length of the land from which the entire slope length drains into a particular spot [34]. These two factors have a substantial effect on the rate of soil erosion by water. They are combined into a single factor by the USLE model. The equation used to evaluate LS (e is a correction factor) is:

                        LS = (l / 72.6)^e( 65.41sin² q + 4.56sin q + .065 )                                                                                                                                            Equation [2]

where:              l  = slope length in feet

                        q =  slope in degrees from horizontal

                        e =  0.5 if percent slope is greater than 5

                        e =  0.4 on slopes of 3.5 to 4.5

                        e =  0.3 on slopes of 1 to 3 percent

                        e =  0.3 on slope of less than 1 percent

Slope length is the distance from where runoff begins to where deposition begins at a decrease in slope or where runoff enters a well defined channel [14]. The slope is calculated using the GRASS command r.slope.aspect which used the elevation primary data layer to determine slope in degrees (q), as well as percent, from the horizontal. Aspect for the area is calculated which shows the cardinal direction the slope faces. The aspect data layer is generated by the GRASS command r.slope.aspect. The data layer in the software system representing aspect is a reclassification of the original aspect data layer generated by GRASS. Each of the 8 categories represents a 45 degree arc with category 1 facing north and category 5 facing south. Slope length, l, is generated on a cell by cell basis by evaluating all eight surrounding cells. A series of scripts written by Martin McKimmey [14] is used to describe conditions that identify part of a multi-cell slope length using the USDA slope length definition. Conditions for each cell are shown schematically in the Figure 5-2. The conditions in Figure 5-2 show that as long as the neighboring cells are greater in elevation, less than or equal to the slope (degrees), they drain into the current cell, and if they are not water, then they are part of a multi-cell slope length. One portion of a script that does this is given in the following example (the remaining scripts are in Appendix A ).

            count2   = if (( elevation <= elevation [ -1,-1 ] &&\

                                     slope  >=  slope [ -1,-1 ] &&\

                                     aspect [ -1,-1 ] ==  4 &&\

                                     water ==  0 ), 2 , 0 )

The script called count2 is only part of the actual equation used ( see Appendix A ). This  script addresses the upper left neighboring cell only, which is indicated by the [-1,-1] map location identifier. GRASS addresses the actual values for each current cell in the following manner:  "The actual script would duplicate the first three lines seven times with only the addresses of the neighboring cells changing. The script reads: Create a map called count2 with the following conditions; if the elevation at the current cell location is less than or equal to the upper left cell, and the slope at the current cell location is greater than or equal to the upper left cell, and upper left cell drains (aspect map value of 4) into the current cell, and the current cell is not water, then assign a value of 2 to the current cell, else return a value of 0. If one of these criteria was not met, the cell received a zero value indicating that the cell was either water or was not part of a multi-cell slope length [16]." The result of the script called count2 is a new data layer called count2 (not to be confused with the script called count2 ). The data layer count2 showed areas where slope length is two cells or more. All slopes despite actual length are assigned a value of 2 representing  slope length. Since the resolution of the map is 30 meters per cell, this would mean that the slope length is 2 X 30 meters or 60 meters. Actual slope lengths are calculated with a series of 20 scripts (count2-count21). Each software script has the potential of extending the slope lengths by one cell to a maximum of 20 cells ( >= 2000 ft. at a resolution of 30 meters).  The result is a data layer called count21 that has the total number of cells that are part of the a slope length for each individual cell. Once the total number of cells that are part of a slope length are calculated, the cell values are converted into a data layer that takes into account whether bodies of water such as streams and lakes are present. If water is present the cell is considered to have a slope length of zero, indicating no erosion for that cell. After the water checking script is completed,  the cell values are converted into feet and a correction factor called e is applied to the data layer on the basis of percent slope. Finally,  LS factors are calculated using the Equation [2].

This results in a data layer called LS factor, which is multiplied by a factor of 100 for relative accuracy in storing  numbers in GRASS. A sample data for LS factors (Table 5-3) is shown with the applied factor of 100 for LS factors in the Huntsville, AR, area.

Table 5-3: Example of LS factors in GRASS

To summarize the calculation of the LS factors, the following list (Table 5-4 ) in sequential order shows how these scripts are used, what data layers are created, and the purpose or meaning of each data layer.

              Table 5-4: Scripts for calculating LS factors

Calculating Erosion Potential

            After all factors in the USLE are in an appropriate form, Equation [1] calculates the erosion potential for each cell in the data layer called erosion. The equation when executed does the following,  multiplies each cell in the kfactor data layer by 0.01, then  multiplies each cell in lsfactor by 0.01, then multiplies each cell in cfactor by 0.001. Following this it  multiplies the data layers of kfactor, lsfactor, cfactor, and the constant 275. The final number is rounded up or down and then an integer value is placed in the current cell for the data layer called erosion. This process is repeated for each individual cell in the data layer erosion with the result being a specific value of erosion potential for each 30 meter cell in the data layer. Figure 5-3 shows an example erosion potential computation for a single cell in data layer. The cells that are shaded gray show the calculations that are taking place for a current cell.

                           Chapter 6PRIVATE

                      Instruction Manual

Introduction

            The instruction manual provided in this chapter  gives the user a knowledge of basic commands and options available in the erosion potential software system. All commands are either input from the keyboard or with a pointing device such as a computer mouse. Commands are in quotation marks and followed by the return key. The software runs under GRASS from a SUN workstation. A recommended setup for displaying both information about maps and the maps themselves requires a graphics monitor (i.e. d.mon start=x0 ) and command tool be running. Once the graphics monitor is initiated, the command to start the software can be given. The user has the option of making the graphics window any size. However, the following arrangement of windows in Figure 6-1  is recommended for optimal displaying of maps and information.

Starting the Software System

            The software system is started by typing the command "erosion1".  At this point the following screen (Figure 6-2) will be displayed on the graphics monitor.

Figure 6-2: Opening screen for the software

            The screen is divided into three basic areas. Figure 6-3 illustrates the areas with the corresponding numbers. Area 1 is the location for the display of maps. Area 2 gives the map legend for the map currently displayed in Area 1. Area 3 shows commands or options that the are selected with a pointing device. The user need only click with the left mouse button on an option in Area 3 and the selected option will be executed.

Opening Screen - > 1 EROSION ANALYSIS

            Once the opening screen (Figure 6-2) is illustrated on the graphics monitor, the user has two options. The first option is -> 1 EROSION ANALYSIS. The user selects this option by using the pointing device to click on option 1. This option starts a session for predicting erosion potential. Option 1 should only be selected after the user has completed the setup program once for a particular region. If the user selects Option 1, a new set of menu options appear on the screen (Figure 6-5). These options allow the user to conduct an erosion potential analysis.

Opening Screen - > 2 RUN SETUP PROGRAM

            The first time a new geographic region is identified, the user must choose this option. This portion of the software system establishes the names of the required primary data layers as well as calculates the erosion potential for the identified region. Once the Setup program is completed, the user need not choose this option for future sessions regarding the same area of analysis. The only time the user needs to run the setup program again would be if a different geographic region is to be analyzed for erosion potential. For example, the data used in this research was from the Huntsville quadrangle. If data from another quadrangle is desired, the Setup Program would have to be run again for the different. The selection of Option 2 runs the Setup Program and new menu options are displayed (Figure 6-4).

Clicking on the BEGIN SETUP option starts the process of defining the required primary data layers. Choosing the BASIC INFORMATION & HELP option gives the user information concerning the Setup program. Lastly, the EXIT option ends the setup program and puts the user back to the screen for analyzing erosion ( Figure 6-5).

Main Menu Screen

            After the user chooses Option 1  (-> 1 EROSION ANALYSIS ) from the Opening Screen, the Main Menu Screen is displayed. Figure 6-5 illustrates the Main Menu Screen with the respective commands available to the user via a pointing device. Each of these menu options will be discussed below.

 Option 1 ( -> 1 CURRENT EROSION )

            Option 1 displays a map which indicates the current erosion potential for the area of interest along with a legend for interpreting the map. Different colors on the map represent differing levels of erosion potential and these levels are identified in the legend. Figure 6-6 illustrates this display. The user may choose this option from any menu screen in the program. The current erosion option allows the return to a map which illustrates the area of interest with no modifications to essentially restart an analysis of the area.

Option 2 ( -> 2 DISPLAY RASTER MAP)

The selection of Option 2  results in the display of the names of all of the raster maps (i.e. data layers) that are in the user's mapset. A file menu shown in Figure 6-8 is displayed on the graphics monitor. Paging up or down is accomplished by clicking on the arrows location on the upper right of lower right corners of the file menu. The user ma either  select a data layer to display or return to the previous menu. The latter is accomplished by double clicking on the top portion of the menu.

A double click on the desired data layer results in the display of the selected map. After a raster map is chosen, the user will be prompted to indicate whether the requested map is to be overlaid on top of any current display or whether the system is to erase any current display before displaying the requested raster map.

Option 3 ( ->3  DISPLAY A VECTOR MAP )

            The result of the choice of Option 3 is similar to that of Option 2; however, with this option vector maps may be displayed. After the selection of Option 3, the user is asked to select the color for the display of the vector map.

Option 4 ( -> 4 ZOOM IN ON A MAP )

            The option to zoom in on a raster map allows the user to see in closer detail a portion of the region currently on the screen. Zooming will be appropriate for a better examination of a proposed construction area than would be accorded by the display of a larger area. The pointing device is used to locate two corners of a smaller region which included the area proposed for modification. The region so identified is displayed on the screen.

Option 5 ( -> 5 DEFINE CONSTRUCTION )   

            Option 5 permits the user to define a specific area of construction. Locating an area of construction is necessary Options 6 or 7 may be selected. The user locates the proposed construction by using the pointing device to define one or more polygons, circles, or lines. The selection of Option 5 results in the presentation of the following choices displayed in the command tool:

                                    Please choose one of the following

                                                A define an area

                                                C define a circle

                                                L define a line

                                                Q quit ( and create map )

                                    >

Entering letter A allows the user to define polygon shapes. Entering the letter C allows a circle to located, and entering the letter L allows the user to locate a line. Any combination of these shapes may be used to define a construction area. After the location of the construction area is completed, a click on the right mouse button presents the following questions in the command tool:

                                    Enter the category number for this area: 1

                                    Enter a label for category 1 [] new area

                                    1 [new area]

                                    Look ok? (y/n) y

                                    Please choose one of the following

                                       A define an area

                                       C define a circle

                                       L define a line

                                       Q quit (and create map)

                                    > Q

                        Enter name of map to be created

                        Enter 'list' for a list of existing raster files

                        Enter 'list -f' for a list with titles

                        Hit RETURN to cancel request

                        > new_area

                        <new_area>

                        Creating raster map new_area

                        writing raster map ...  100%

                        Creating support files for raster map <new_area>

                        Done

The user enters the number 1 for the category value and gives a name to the map being created. The user will again be asked what the name of their map is called. The following message will be displayed in the Command Tool:

                         -------------------------------------------------         

                        |      You now need to enter the name of the area |

                        |       you just drew using your mouse.           |

                        |                    -OR-                         |                 |                                                                                                                       |

                        |      You can enter a previously saved area.             |

                         -------------------------------------------------                     

                        Enter the name for your area-->  new_area

Following the entry of a name for your area of construction the program will display the commands shown in Figure 6-6.

Option 6 ( -> 6 MODIFY LAND )           

            Option 6 displays the menu options in Figure 6-8. Choosing this option allows for clearing and grubbing of the construction area.

Option 7 ( -> 7 ENTER A COMMAND ) 

            Selecting Option 7 permits GRASS commands via the command tool to be executed. Option 7 allows added flexibility to modify what is going on in the Graphics Monitor. For instance, the user might want to temporarily see a three dimensional view of erosion for their region. The user could then use Option 7 to display a three dimensional view.

Option 8 ( -> 8 EXIT )

            Option 8 quits the current menu and sends the returns control back to the Startup Menu screen ( Figure 6-2).

Menu1

Selecting Menu1 options simulated clearing and grubbing of a construction area and application of new erosion prevention techniques and materials. Menu1 is displayed when  Option 6 from the Main Menu (Figure 6-5) is selected. The commands for Menu1 are displayed in Figure 6-8.

Option 1 ( -> 1 EROSION & AREA )

            Option 1 displays a map which indicates the current erosion

potential for the area of interest along with a legend for interpreting the map. Different colors on the map represent differing levels of erosion potential and these levels are identified in the legend. Figure 6-6 illustrates this display. The current erosion option allows the return to a map which illustrates the area of interest with no modifications to essentially restart an analysis of the area. Option 1 is identical to Option 1 found in the Main Menu.

Option 2 ( -> 2 CLEAR & GRUB )

            Selection of Option 2 simulates the removal of plant matter and root structure from a construction area  by clearing and grubbing the area. Option 2 gives a choice of a before and after erosion analysis report . If the option YES is selected, the Graphics Monitor Window is changed to illustrate the erosion potential before the construction area is cleared and grubbed, and after the area is cleared and grubbed. Besides a visual to display like that of Figure 6-9, the total amount of erosion for the area is determined and displayed in the command tool window. Choosing the option of NO returns control back to the original menu options.

Figure 6-9: Before and After display in Graphics Monitor Window

The user has the option to go back to the current display with only one map being displayed if Option 1 is chosen. However, the same set of commands in Menu1 will be displayed (Figure: 6-8).

Option 3 ( -> 3 MULCH AREA )

            Option 3 passes control to the Mulch Analysis Menu options and allows for the  use of a variety of mulches ( straw, stone, wood ) to an established area. The area selected is cleared and grubbed prior to selecting this option.

Option 4 ( -> 4 ENTER A COMMAND )

            Option 4 uses GRASS commands via the command tool. Option 4 is identical to Option 7 in the Main Menu.

Option 5 ( -> 5 NEW  TECHNIQUE/MATERIAL )

            Option 5 simulates the application of a new technique or material to the established construction area to prevent erosion. The user is prompted by the software system for the  new technique or material being used to prevent erosion.  The user is prompted to enter a C factor (between 0 and 1) associated with the new material or technique. The C factor comes from the USLE and is determined before initiating this option. Erosion is then calculated and displayed in both a before and after analysis identical to that of clearing and grubbing and the application of mulches.

Option 6 ( -> 6 EXIT )

            This option displays the Main Menu options.

Mulch Analysis

The menu called Mulch Analysis is displayed when the user selects Option 3 from Menu1 ( Figure 6-8 ). The user can simulate the application of mulches such as straw, stone, and wood. Once a mulch is applied to the cleared and grubbed construction area, a before and after report of erosion potential is displayed. The report is identical to that given when the land is cleared and grubbed, except that erosion prior to the application of mulches represents land that has previously been cleared and grubbed. The commands and display are shown in Figure 6-10 below.

Option 1 ( -> 1 EROSION AREA )

            Option 1 displays a map which indicates the current erosion potential for the area of interest along with a legend for interpreting the map. Different colors on the map represent differing levels of erosion potential and these levels are identified in the legend. Figure 6-6 illustrates this display.  The current erosion option allows the return to a map which illustrates the area of interest with no modifications to essentially restart an analysis of the area. Option 1 is identical to Option 1 found in the Main Menu.

Option 2 ( -> 2 STRAW/HAY )

            Option 2 simulates application of  straw/hay once the amount is selected.  The choices are as follows:

                                                                1.0 tons per acre

                                                                1.5 tons per acre

                                                                2.0 tons per acre

The amount is selected and  applied to the construction area and a new erosion potential is calculated. Once the new erosion potential is calculated, the user has the option of generating a before and after erosion potential report ( Figure 6-9).

Option 3 ( -> 3 CRUSHED STONE )

            Option 3 simulates application of  stone once the user decides how much stone to place in the construction area. The choices are as follows:

                                                                135 tons per acre

                                                                240 tons per acre

The amount is selected and  applied to the construction area and a new erosion potential is calculated. Once the new erosion potential is calculated, the user has the option of generating a before and after erosion potential report ( Figure 6-9).

Option 4 ( -> 4 WOOD CHIPS )

            Option 4 simulates the application of  wood chips once the user decides how much wood chips they want to put down. The choices are as follows:

                                                                 7.0 tons per acre

                                                               12.0 tons per acre

                                                               25.0 tons per acre

The amount is selected and  applied to the construction area and a new erosion potential is calculated. Once the new erosion potential is calculated, the user has the option of generating a before and after erosion potential report ( Figure 6-9).

Option 5 ( -> 5 ENTER A COMMAND )

            Option 5 uses GRASS commands via the command tool. Option 5 is identical to that of Option 7 in the Main Menu.

Option 6 ( -> 6 EXIT )

            Choosing this option displays options in Menu1.

Software Installation

            The installation of the erosion prediction software requires the following list of files. The user can run the software in a GRASS session by copying the files to their working directory and giving executable file priveledges.These files are:

erosion1

erosion2

erosion3

seutp_erosion

logo

menu1.data

menu2.data

menu3.data

menu4.data

menu5.data

menu6.data

menu7.data

menu8.data

menu9.data

setup_erosion.data

count2

count3

count4

count5

count6

count7

count8

count9

count10

count11

count12

count13

count14

count15

count16

count17

count18

count19

count20

count21

slope.length.c

cell2ft

e

ls

                                                                      Chapter 7PRIVATE

         Example of Erosion Prediction Software System

Introduction

     The example provided is meant to provide output as well as to show the user how the software works. Commands entered by the user are highlighted in bold italics. Output  from the software and GRASS is in regular non-bold form. Notes about the software are denoted by brackets in the following format [NOTE: XXXXX].

tns@uafsun4:/home/tns 106 % grass4.1

                                 GRASS 4.1

LOCATION: This is the name of an available geographic location. 

          -spearfish- is the sample data base for which all         tutorials are written.

MAPSET:  Every GRASS session runs under the name of a MAPSET.           Associated  with each MAPSET is a rectangular COORDINATE      REGION and a list of any new maps created.

DATABASE: This is the unix directory containing the geographic          databases

          The REGION defaults to the entire area of the chosen           LOCATION.  You may change it later with the command:           g.region

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

LOCATION:   huntsville____  (enter list for a list of locations)

MAPSET:     copy__________  (or mapsets within a location)

DATABASE:   /app/grass/data/__________________________________

              AFTER COMPLETING ALL ANSWERS, HIT <ESC> TO CONTINUE

                            (OR <Ctrl-C> TO CANCEL)

[NOTE: The <ESC>  key was entered]

GRASS 4.1 > d.mon start=x0

Graphics driver [x0] started

[NOTE: Once GRASS and the graphics monitor has been started, the user can start the software ]

Mapset <copy> in Location <huntsville>

GRASS 4.1 > erosion1

[NOTE: Figure 7-1 shows the actual opening screen for the software]

seq Figure  \* Arabic  \h1

Figure 7-1: Opening Screen for Software System

[NOTE: click on BEGIN SETUP]

Entering the SETUP program....

[ NOTE: Figure 7-2 shows the screen for the setup portion of the software system ]

seq Figure  \* Arabic  \h2

Figure 7-2: Screen for the Setup portion of the software system

[NOTE: Use the mouse to click on HELP and basic information about the setup program will be displayed ]

----------------------------------------------------------------

|           BASIC INFORMATION ON THE SETUP PROGRAM        |

|--------------------------------------------------------------|

|                                                              |   | This program is used to 'setup' the erosion analysis program.| |It  has the main purpose of finding out the names of primary  |

| data layers. Once these data layers are chosen by the user the | program calculates the slope-length factors (LS factors).    |  |                                                       |

| THIS PROGRAM ONLY NEEDS TO BE RUN ONE TIME.....                |

| The setup program will provide the necessary alterations to  |

| the area of interest. The program is time consuming, but once| |it is run, the only reason you would need to run it again is if| |you ran it incorrectly, are using a new mapset, or accidentally| | deleted one of the data layers the program generates.          |  --------------------------------------------------------------

Hit [RETURN] to continue.....

[NOTE: return entered and the mouse was used to click on BEGIN SETUP]

You will now be asked to click on the raster map that contains

the primary data for each of these data layers         

Theses data layers are as follows:

 ----------------------------------------------------------------

  ACTUAL NAME OF MAP           WHAT THE MAP STANDS FOR IN USLE    

 ----------------------------------------------------------------