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.
|
