Runoff Analysis for the Malibu Creek
Watershed
by Bradley Owens
August, 1998
Printable version of this document in Adobe Acrobat format:
malibu.pdf
Introduction (top)
This analysis is undertaken as part of a water quality monitoring
program of Heal the Bay, funded by the California Coastal Conservancy,
and created by the 606 Studio as a degree fulfillment masters project for
the Graduate Department of Landscape Architecture at California Polytechnic
State University, Pomona.
This document is prepared as an appendix to the main document
called "A Framework for Monitoring and Enhancement of the Malibu Creek
Watershed".
Timothy Kovacs, Lance Nielsen, and Christopher Smemoe of
ECGL have been instrumental in the development of this analysis, as well
as Mark Abramson of Heal the Bay. Their willingness to help, and
attention to detail is greatly appreciated.
Software used for modeling the watershed is called Watershed
Modeling System (WMS) created by Environmental Computer Graphics Laboratory
(ECGL) of Brigham Young University. With this model, runoff was estimated
utilizing data supplied by Los Angeles County and digital elevation data
from DEM's. The watershed was modeled for two conditions, pre-development
and current developed conditions. Results show approximately a 100%
increase in runoff from the pre-developed condtion to the current developed
condtion.
Background (top)
The Malibu Creek watershed is located in Los Angeles and
Ventura counties in southern California. The creek drains approximately
109 square miles and empties into Santa Monica Bay at Malibu Lagoon; elevations
range from sea level to greater than 3,000 feet. The watershed has
seven main subsheds and each has varying degrees of development ranging
from rural low density to urban medium density. Also included in
the watershed are many industrial, agricultural, and recreational developments.
For a more in-depth description of the watershed, see the main document
called "A Framework for Monitoring and Enhancement of the Malibu Creek
Watershed".
Increasing the amount of impervious surfaces in a watershed
can result in increased runoff and increased stream discharge; this can
have a deleterious effect on habitats in the watershed and at the outflow,
as well as on downstream development due to flooding and erosion.
A working model of runoff in the watershed is helpful in
evaluating the impact of development on Santa Monica Bay, as well as for
identifying suitable locations for future development. The runoff
model is also used predictively when analyzing impact of potential development
in the watershed.
The modeling tool chosen for this task is a modeling software
called Watershed Modeling System (WMS) developed by Environmental Computer
Graphics Laboratory (ECGL) of Brigham Young University in Provo, Utah.
WMS provides a graphical interface for standard computer
models such as HEC-1 and TR-20; HEC was developed by the United States
Army Corps of Engineers, and TR-20 was developed by the Soil Conservation
Service (SCS, now the National Resource Conservation Service or NRCS).
In addition to the graphical interface, WMS provides many utilities for
computing and converting data inputs required for the standard models.
When using this software program, the model can be updated and refined
as new information becomes available, thus adding to the effectiveness
with which analyzing and predicting changes in the watershed can occur.
Model Inputs and Methods (top)
The WMS software requires that certain data sets are available
depending on the model type and accuracy desired. A typical model
would be developed based on Digital Elevation Models (DEM's) that are readily
available on the World Wide Web. A DEM is spatial data that provides
gridded elevation for a given land area and usually corresponds to a USGS
quad map.
For this model, data was provided by LA County Dept. of Public
Works; this included land use, soil types, vegetation, and watershed and
subshed boundaries. This data was modified by the Cal Poly team to
reflect the latest conditions using digital aerial photography and 3D modeling
and input into the model in GIS shapefile format (except for the vegetation
data, which is not used directly by the model; this will be discussed later
in this document). In addition to the shapefiles, DEM's were also
utilized in the model for elevation dependent computations such as slope
and subshed curve number averaging.
There are several dams within the Malibu watershed. Of these,
four were used in the model due to their size and/or location within the
watershed. Information about the dams is available on the World Wide
Web (see references), and the dams used for this model (with the DWR number)
are Lake Sherwood (765-000) in Hidden Valley, Westlake Lake (786-000) in
Westlake, Lindero Lake (785-000) in Agoura Hills, and Malibou Lake (771-000)
in the Malibou Lake subshed.
HEC-1 was chosen as the hydrograph method within WMS due
to its ability to utilize the landuse and soils data, thus providing more
precision than other models such as TR-20; within HEC-1, the SCS curve
number method was chosen to compute losses (runoff) for the same reason.
The curve number method was developed by the SCS (now NRCS) as a way to
index various surface runoff conditions based on land use conditions and
soil characteristics.
A hydrograph is a representation of a volume surface flow
in a given time period (cubic feet per second). For this model, a
24 hour storm was used as the time period. After the initial infiltration
of rain into the topsoil, overland flow, or runoff, will occur and a peak
will also occur at some point when the flows are greatest due to factors
such as subshed geometry (area, slope), soil types, cover (land use, vegetation),
and storm pattern. The hydrograph is a graphical representation of
the collection of runoff at a common point (such as at a stream gage).
The model was run for intervals of 2-5-20-25-50-100 year
storms based on rain data available from the National Oceanic Atmospheric
Agency (NOAA) and applied to two conditions- current developed conditions,
and pre-development conditions based on a vegetation survey from 1930-1934
by AE Wieslander of the United States Forestry Service. For pre-development
land use conditions, the Wieslander survey was area averaged visually in
order to input subshed curve numbers into the model
The following table lists the primary data sets used for
the model and the source for the information. Additional source information
is available in the reference section at the end of this document.
Assumptions, Limitations (top)
This model is dependent on the available primary data; it
is assumed that this is the best available at this time. It is known
that the soil survey on which the GIS shapefile was based is an interim
survey by the NRCS and is currently being updated for official release
due in year 2001 (personal communication, Al Wasner, NRCS). In addition,
the land use categories supplied did not have direct correlation to the
SCS curve number table and this was manually interpolated.
As stated previously, this model has many inputs so modification
and refinement over a long period of time will return the best results.
Additional information to add would be channel geometry, reservoir geometry
and conditions, and more exact soils data. Hydrologic modeling is
both art and science so the results are assumed to be estimates and will
differ from actual conditions.
The runoff analysis resulted in two primary results, pre-development
and current developed conditions with modeled estimates of peak runoff
(cubic feet per second) for each subshed and a total at the ocean outlet
for each storm interval. The data is presented below in tabular
form with a hydrograph representing the outlet.
Conclusions (top)
The modeling has shown that the watershed is yielding a large
increase in runoff since predevelopment conditions have changed into the
current state of development. Increases greater than 100% are seen
in every subshed, most approaching 200% for a two year storm, and the Westlake
subshed showing an over 700% increase. Not only is the increase dramatic,
but the relationship between the increase in mapped impervious surface
and the runoff increase is interesting as well because of the logarithmic
relationship borne out by the data.
The tables above show that the increase in impervious surface
area in each subshed has dramatically increased the runoff into Malibu
Creek (with the assumptiion being that the predeveloped condition had zero
impervious surface). The clearest example is in the Westlake subshed
where a 22.89% increase in impervious surface has led to a 722.01% increase
in runoff.
The following graphs demonstrate that a small increase in
impervious area within a watershed will result in large increases in runoff;
two scales, logarithmic and linear, are shown in order to bring out the
relationship visually. For instance, the linear graph
(second graph) shows that the increase has a logarithmic relationship;
small incremental increases of impervious surface leads to greater and
greater amounts of runoff.
Although typical (and costly) structural devices such as
dams and weirs can be used to control runoff, it is clear that this watershed
will yield extreme amounts of runoff as impervious surfaces increase and,
due to the erosive nature of the soils, will render these devices largely
ineffective in relatively short periods of time as seen with Rindge Dam
which has completely filled with sediment. It would seem that a more
comprehensive management of the watershed resources will result in a cost
effective and habitat conserving condition.
References (top)
Bedient, Philip B. Hydrology and Floodplain Analysis. Addison-Wesley Publishing Company. 1992.
Dams Within Jurisdiction of the State of California, Bulletin 17. California State Department of Water Resources. June 1993. http://galaxy.cs.berkeley.edu/kopec/b17.
Environmental Modeling Research Laboratory. Brigham Young University, Provo, Utah. (801) 378-2812. http://www.emrl.byu.edu/wms.htm.
Heal the Bay. Santa Monica, CA. (800) HEALBAY. http://www.healthebay.org.
HEC-1 Users Manual version 4.0, United States Army Corps of Engineers, Hydrologic Engineering Center. 1990.
Maidement, David R., ed. Handbook of Hydrology. McGraw-Hill, Inc. 1992.
Owens, Bradley B. http://owenswatershedplanning.com .
Precipitation Frequency Maps for the Western United States (Return Periods NOAA Atlas 2). http://www.wrcc.dri.edu/pcpnfreq.html.
WMS Reference Manual, version 5.0, Environmental Modeling Research Laboratory. Brigham Young University, Provo, Utah. 1997.
WMS Tutorial, version 5.1, Environmental Modeling Research Laboratory. Brigham Young University, Provo, Utah. 1998.