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viewed in a user-friendly graphical environment. The WMS software
package is divided logically into well-integrated task-oriented mod-
ules including map module, GIS module, terrain data module, two-
dimensional grid module, drainage module, hydrologic-modeling
module, river-modeling module, and scatter-point module. The WMS
modules can perform automated watershed delineation, floodplain
modeling and mapping, stochastic modeling, and two-dimensional
(distributed) hydrologic modeling. Typical applications include flood
forecasting (depth and velocity over the entire two-dimensional
domain), thunderstorms (localized rainfall) flood analysis, surface
ponding and infiltration analysis, and groundwater/surface water
interaction modeling. WMS utilizes ArcGIS GIS software.

5.5 Future of GIS-based Watershed Modeling Systems
Widely used current GIS-based watershed modeling systems provide
a common GUI for a variety of models. One of the major limitations
of this approach is that the user is still able to use only one complete
model, with all of its components, at a time. This approach does not
allow combining submodels from different models to construct a new
model that is most appropriate in representing the hydrologic condi-
tions of a specific watershed. In future, development of modular
structures under a common GIS-based GUI for sets of popular mod-
els will allow more accurate prediction of watershed responses. Such
a modular structure should also allow various parts of the water-
sheds to be modeled using a unique combination of submodels. For
example, the parts of watershed where infiltration excess runoff
mechanism dominate should be allowed to use the rainfall-runoff
models that are based on infiltration excess theory (e.g., curve num-
ber approach, Green–Ampt infiltration equation, and Horton infiltra-
tion equation), whereas the parts dominated by saturation excess
mechanisms should be allowed to use models that are based on
saturation excess theory.
Development and expansion of customized GIS modules that are
capable of representing and incorporating time series input and out-
put datasets will greatly assist modelers, researchers, and decision
makers. For example, land-use in a watershed model is currently
modeled using a dataset that is fixed in time. To quantify the effect of
changes in land-use, multiple model setups are constructed for fixed
times to represent land-use change over a period of time. However,
the fact is that land-use changes occur continuously. In the GIS com-
munity, effort is underway to capture land-use change in real time.
Once this approach is sufficiently developed, GIS-based modeling
systems should be configured in such a way to allow incorporation of
time series land-use input. Similarly, incorporation of time series out-
put would be crucial for modelers and decision makers.