WaterWare: erosion modeling

Integrated Water Resources
Planning and Management

WaterWare: a Water Resources Management Information System

Erosion and Turbidity: soil erosion, TSS, turbidity, sediment transport, reservoir siltation and non-point source pollution

Modeling of the soil erosion and transport process in watersheds can be based on a number of possible approaches, primarily constrained by the availability of detailed, spatially distributed field data. The choice of the most appropriate model is only possible based on a detailed analysis of the available data. Therefore, exploiting the open architecture of the WaterWare system, several alternative models are being tested for possible use and integration.

WaterWare has several modules dealing with erosion, sediments, turbidity, and non-point runoff/pollution. Primary output are:

Turbidity (TSS) in the channel system;
Specific sediment yield (tons per hectare and year)

which together with the runoff and basin size, defines the sediment yield or export from a given watershed or basin, and the sediment load to the receiving environment, usually the coastal sea.

WaterWare also has an open modular architecture that makes it possible to integrate additional models easily through generic model interfaces and standardized data formats, including compatibility with all major GIS formats.

The primary built-in model is a rule-based cellular automata model derived from the dynamic land use change model (LUC); Basic data are provided by the GIS (soil, land-cover, DEM, from which slopes and aspects are derived) and hydrometeorological time series. The model can be used for a single, lumped sub-catchments (as part of the RRM rainfall-runoff model), a set of linked sub-catchments, or a regular grid (anything from hectares to square kilometers). The model is represented by a Markov chain with a-priori transition probabilities modified by rules and driven by dynamic external events (precipitation, agricultural practice, seasonal vegetation changes).

WaterWare is open to the integration of external alternative models. The built-in approaches are:

A dynamic sub-catchment model that uses estimates of the daily water budget (precipitation, runoff, surface runoff) together with a modified version of the USLE.
Extensions to the dynamic, distributed (network topology) water resources and linked water quality models (WRM and STREAM), primarily dealing with sediment transport in the channel system; non-point source runoff and sediment load is supplied to individual reaches of the channel network as lateral inflow based on the simple sub-catchment model nd its erosion extension.
A rule-based dynamic cellular automata approach implemented within the framework of distributed Markov model;
A grid-based dynamic physically based model Finite Difference model, designed to be incorporated into an innovative multi-criteria optimisation scheme.

Alternative external model that can be implemented include:

AGNPS (Agricultural Non-Point-Source)

AGNPS is an event-based model. It calculates runoff from agricultural watershed and transport processes of sediment, nitrogen, phosphorus, and COD. A Watershed is represented by square cells of 0.4 - 16 ha. Each cell is characterized by twenty-two parameters that include: SCS curve number, terrain description, channel parameters, soil-loss equation data, fertilization level, soil texture, channel and point source indicators, oxygen demand factor. Sediment runoff is estimated from the modified version of USLSE (Universal Soil Loss Equation) and its routing is performed for five particle size classes. Calculations of the nutrients transport are divided into soluble and sediment-absorbed phases. ). The application of AGNPS is limited to about 200 km² watersheds ( Young et al., 1989, DeVries and Hromadka, 1993, Engel et al., 1993.

At least three interfaces between AGNPS and GRASS (Geographical Resources Analysis Support System) have been constructed: in Michigan State University (He et al., 1993, Engel et al., 1993, Mitchell et al., 1993, Cronshey et al., 1993. GRASS is the major public domain GIS. It is widely used by many federal and states agencies. The access to the source code provides the flexibility to modify existing GRASS procedures or to add new ones. This GIS software has a considerable ability to support hydrologic analysis.

AGNPS has also been linked to other GIS programs, such as: Geo/SQL, a vector-based GIS (Yoon et al., 1993); PC-Arc-Info, a vector based GIS (Jankowski and Haddock, 1993), and IDRISI, a raster based GIS (Klaghofer et al., 1993).

The last interface has been used to evaluate erosion and sediment yields in a lower alpine drainage basin of area of 65 ha in Austria. The interface contained EPIC (Erosion/Productivity Impact Calculator, Williams et al., 1990) a field scale comprehensive model developed to predict the long-term relationship between erosion and productivity. EPICs components include weather simulation, hydrology, erosion-sedimentation, nutrient cycling, plant growth, tillage, soil temperature, economics, and plant environment control.

ANSWERS: Areal Nonpoint Source Watershed Environmental Resources Simulation

Engel (1993) discusses the application of GRASS-ANSWERS (Aerial Nonpoint Source Watershed Environment Response Simulation) interface. ANSWERS (Beasley et al., 1982 after Engel, 1993) calculates runoff, erosion, sedimentation and phosphorus movement from watersheds. The watershed is divided into a grid cells. Runoff, erosion, sedimentation, and water quality related to sediment associated chemicals are computed for each cell and routed.

The current version of the model, ANSWERS-2000, is a continuous simulation model that was developed in the mid 1990s (Bouraoui and Dillaha, 1996). In this version, the nutrient submodels were overhauled and improved infiltration (Green and Ampt), soil moisture and plant growth components were added to permit long-term continuous simulation. Bouraoui (1994) describes the current version of the model in detail. ANSWERS-2000 simulates transformations and interactions between four nitrogen pools including stable organic N, active organic N, nitrate and ammonium. Transformations of nitrogen include mineralization simulated as a combination of ammonification and nitrification, denitrification, and plant uptake of ammonium and nitrate. The model maintains a dynamic equilibrium between stable and active organic N pools. Four phosphorus pools are simulated: stable mineral P, active mineral P, soil organic P and labile P. Equilibrium is maintained between stable and active mineral P and between active mineral P and labile P. Plant uptake of labile P and mineralization of organic P are also simulated.

CAESAR

CAESAR (Cellular Automaton Evolutionary Slope And River model). A high resolution model that has been used to establish the effects of environmental change (climate and anthropogenic land cover change) on river system evolution.

CREAMS

Creams is a field scale model for Chemicals, Runoff, and Erosion from Agricultural Management Systems. The objectives of the model were:

the model must be physically based and not require calibration for each specific application,
the model must be simple, easily understood with as few parameters as possible and still represent the physical system relatively accurately,
the model must estimate runoff, percolation, erosion, and dissolved and adsorbed plant nutrients and pesticides and,
the model must distinguish between management practices.

Based on these objectives, since the management practices were usually on a field basis, the size of a field to represent the scale of the model was needed. A field is defined in the context of the CREAMS model as a management unit having 1) a single land use, 2) relatively homogeneous soils, 3) spatially uniform rainfall, and 4) single management practices, such as conservation tillage or terraces.

The hydrologic component consists of two options. When only daily rainfall data are available to the user, the SCS curve number model is used to estimate surface runoff. If hourly or breakpoint rainfall data are available, an infiltration-based model is used to simulate runoff. The erosion component maintains elements of the USLE, but includes sediment transport capacity for overland flow. The plant nutrient submodel of CREAMS has a nitrogen component that considers mineralization, nitrification, and denitrification processes. Plant uptake is estimated, and nitrate leached by percolation out of the root zone is calculated. Furthermore, both the nitrogen and phosphorus parts of the nutrient component use enrichment ratios to estimate that portion of the two nutrients transported with sediment. The pesticide component considers foliar interception, degradation, and washoff, as well as adsorption, desorption, and degradation in the soil.

REFERENCES: Kinsel, Walter G.[eds.] (1985) CREAMS: A Field Scale Model for Chemicals, Runoff, and Erosion From Agricultural Management Systems. U.S. Department of Agriculture, Conservation Report No. 26, 640 pp., illus.

EPIC: Erosion-Productivity Impact Calculator

The Erosion-Productivity Impact Calculator (EPIC) (Williams et al., 1984) model was developed to assess the effect of soil erosion on soil productivity. It was used for that purpose as part of the 1985 RCA (1977 Soil and Water Resources Conservation Act) analysis. Since the RCA application, the model has been expanded and refined to allow simulation of many processes important in agricultural management (Sharpley and Williams, 1990).

EPIC is a continuous simulation model that can be used to determine the effect of management strategies on agricultural production and soil and water resources. The drainage area considered by EPIC is generally a field-sized area, up to 100 ha (weather, soils, and management systems are assumed to be homogeneous). The major components in EPIC are weather simulation, hydrology, erosion-sedimentation, nutrient cycling, pesticide fate, plant growth, soil temperature, tillage, economics, and plant environment control.

KINEROS

The kinematic runoff and erosion model KINEROS is an event oriented, physically based model describing the processes of interception, infiltration, surface runoff and erosion from small agricultural and urban watersheds. The watershed is represented by a cascade of planes and channels; the partial differential equations describing overland flow, channel flow, erosion and sediment transport are solved by finite difference techniques. The spatial variation of rainfall, infiltration, runoff, and erosion parameters can be accommodated. KINEROS may be used to determine the effects of various artificial features such as urban developments, small detention reservoirs, or lined channels on flood hydrographs and sediment yield.

KINEROS uses one-dimensional kinematic equations to simulate flow over rectangular planes and through trapezoidal open channels, circular conduits and small detention ponds.

LISEM: LImburg Soil Erosion Model

LISEM, the LImburg Soil Erosion Model, simulates the hydrology and sediment transport during and immediately after a single rainfall event in a small catchment. The model has been used so far in catchments between 10 and approximately 300 ha. LISEM is built to simulate both the effects of the current land use and the effects of soil conservation measures. The model was originally made for the Province of Limburg, the Netherlands, to test the effects of grass strips and other small scale soil conservation measures on the soil loss. In the "Limburg" project, three catchments were fully equipped and monitored for 5 years by the local government (Waterboard Roer en Overmaas), the Free University of Amsterdam (Physical Geography), Alterra and the Utrecht University (Physical Geography). Although it can be used for planning purposes it is essentially a research tool because of its complexity.

RUSLE: Revised Universal Soil Loss Equation

RUSLE2 is an advanced, user-friendly software model that predicts long-term, average-annual erosion by water. It runs under Windows, and can be used for a broad range of farming, conservation, mining, construction, and forestry sites. Its origin was the widely-used DOS-based Revised Universal Soil Loss Equation (RUSLE). The extensive climate, soil, vegetation, and cropping management databases available for that model are currently being enhanced, prior to deploying RUSLE2 in several thousand USDA NRCS field offices.

RUSLE2's engine is adaptive -- the model continually shrinks or expands as outputs are hidden or requested. It provides output immediately from default inputs -- then refines the output as the user provides more accurate data. It automatically recalculates -- just like a spreadsheet. Users can choose from alternate ways of calculating data, or override calculations with known field data. RUSLE2's appearance is flexible -- it can be altered to suit a particular user, group, industry, task, or language. Variables can be moved, hidden, highlighted, or graphed. Displayed units and systems of measurement can be changed. Tables can be expanded and folders rearranged. These user preferences can then be saved and recalled, allowing specialized views of the same model.

RUSLE2 reduces complexity -- it hides detail from novice users, but lets experienced users "drill down". Information is grouped into reusable "objects" (vegetation, soils, climates, field operations, etc.) that an average user understands.

RUSLE2 can be run as a stand-alone application, from a third-party application, from a browser, or from an MS Word document with pictures and text. Because of its view customization, modeling engine, widespread adoption, and extensive data support, the RUSLE2 platform is ideal for delivering a variety of environmental models.

USLE2

Usle2D is designed to calculate the LS-factor in the Universal Soil Loss equation from a grid-based Digital elevation model. In a real two-dimensional situation overland flow and the resulting soil loss does not really depend on the distance to the divide or upslope border of the field, but on the area per unit of contour length contributing runoff to that point. The latter may differ considerably from the manually measured slope length, as it is strongly affected by flow convergence and/or divergence. Usle2D overcomes this problem by replacing the slope length by the unit contributing area. Usle2D provides different routing algorithms for calculating the contributing area and various LS-algorithms.

The linkage of Usle2D in a GIS offers several advantages to the one-dimensional and/or manual approach; it may account for the effect of flow convergence on rill development and it has advantages in terms of speed of execution and objectivity. The linking of Usle2D with a GIS facilitates the application of the (R)USLE to complex land units, thereby extending the applicability and flexibility of the (R)USLE in land resources management.

Despite the widespread acceptance of the (R)USLE, it has two important disadvantages: (i) the impossibility to predict where the eroded material will be deposited and (ii) although tillage erosion is shown to be a major soil degradation process, the effect of soil erosion by tillage is not accounted for. An extended version of Usle2D, with a deposition and tillage procedure, called WaTEM (Water and Tillage Erosion Model) was therefore implemented and can be obtained from the LEG Home Page.

SWRRB: Simulator for Water resources in Rural Basins)

Cronshey et al. (1993) report interface that includes GRASS and a watershed scale water quality model SWRRB (Simulator for Water Resources in Rural Basins). SWRRB (Arnold et al., 1990) uses daily time step for calculations of sediment yield, routing, as well as pesticide and nutrient fate. Basins are subdivided to account for differences in soils, land use, crops, topography, weather. Soil profile can be divided into ten layers. Basins of several hundred square miles can be studied, but number of sub-basins is limited to 10.

SWAT: Soil-Water Assessment Tool

In 1993 Arnold, Engel and Srinivasan (from Mamillapalli et al., 1996) developed a new version of the SWRRB--Soil Water Assessment Tool (SWAT). In SWAT, the watershed can be divided into practically unlimited number of cells and/or subwatersheds. New features have been added such as routing of the flow through the basin streams and reservoirs, simulating lateral flow, groundwater flow, stream routing transmission losses, modeling sediment and chemical transport through ponds, reservoirs, and streams. The major components of the SWAT include weather, hydrology, erosion, soil temperature, crop growth, nutrients, pesticides, subsurface flow, and agricultural management. The QUAL2E (Enhanced Stream Water Quality Model) water quality component has been incorporated into SWAT. First-order decay relationship for algae, dissolved oxygen, carbonaceous biochemical oxygen demand, organic nitrogen, ammonium nitrogen, nitrate nitrogen, nitrite nitrogen, organic phosphorus, and soluble phosphorus used in QUALE2E were adopted in SWAT with necessary adjustments (Ramanarayanan et al., 1996). In 1994, a GRASS GIS - SWAT interface was developed by Srinivasan and Arnold (1994). In 1996 Bian et al. linked SWAT with Arc/Info.

WATEM

WATEM is spatially distributed model to simulate erosion and deposition by water and tillage processes in a two-dimensional landscape. Unlike more sophisticated dynamic models, WATEM focuses on the spatial, and less the temporal, variability of relevant parameters. As such, WATEM allows the incorporation of landscape structure or the spatial organisation of different land units and the connectivity between them. In order to avoid major problems with respect to the spatial variability of parameter values and uncertainty of parameter estimates, WATEM is a simple topography-driven model. The water component of WATEM uses an adapted version of the Revised Universal Soil loss equation (RUSLE) since (approximate) parameter values are readily available for many areas. Recent studies have recognised the relevance of direct soil movement by tillage for soil erosion on agricultural land. The tillage component of WATEM uses a diffusion-type equation whereby the intensity of the tillage process is described by one parameter (tillage transport coefficient or ktil-value). WATEM can be used to estimate/evaluate:

water erosion/deposition rates and patterns
tillage erosion/deposition rates and patterns
combined effect of water and tillage erosion
the effect of changes in landscape structure on water and tillage erosion
delineate erosion prone areas in an agricultural landscape.

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