RUNOFF

There are five sub-water bodies in the Elkhorn Sl ough watershed:

Elkhorn Slough proper, Moss Landing Harbor, Moro Cojo Slough, the Old Sali-

nas River channel, and Bennett Slough. The volumes and sur face areas of

these vary wi th tidal stage and antecedent moisture conditions. In dry

weather, for' exampl e. Elkhorn Slough is confined west of Elkhorn Road; in

wet weather, water covers the adjacent 1 owl ands, flooding sections of

Elkhorn Road particularly at Strawberry Canyon and the junction with Hall

Val 1 ey! .

Al though some of the str earn channel tributary to the sloughs ar'e well

defined, most are fil led wi th sediment and riparian vegetation. The

drainage path at the bottom of Strawberry Canyon, for example, is a sand-

fil 1 ed swal e, interrupted by occasional marshy ponds, whereas the channel

of Carneros Creek Hall Valley! was dredged in 1957 and 1975 by the Mon-

terey County Mosquito Abatement Oi strict, and is well incised.

Infiltration rates are relatively high on the Aromas sands, except

where underlying clay 1 ayers act as barriers to water movement aqui-

cludes!. Because of the high infil tration capacity, surface runoff is pri-

marily limited to periods during and briefly following storms. Creeks and

swales are dry between April and October although marsh and riparian vege-

tati on indicate sub sur face moi sture.

During periods of winter runoff, discharge rates can be quite high,

producing unexpected fl oods and erosion damage. The 1 argest flood remem-

bered by local residents occurred in 1939 when water from the fl ooding

pajaro River flowed through the gap at the lower end of Marner Lake into

A-45

Elkhorn Slough. Total flood discharge is not known. Minter flooding regu-

larly occurs during normal rainfall years in the lowlying, diked mouths of

valleys which open into the slough.

Runoff Data Collection

Runoff data for most major rivers and their tributaries in the United

States are systematical ly compil ed and published by the U. S. Geological

Survey in the "USGS Surface Mater Supply Papers." Local counties may al so

collect and publish runoff data. County flood control and water conserva-

tion districts usually have the most immediate information on the 1 ocal

runoff and water supply.

As is typical of many coastal wetl and watersheds in California, pub-

lished surface runoff data were not available for the Elkhorn Slough area.

The Gabil an Creek watershed to the south provided the closest source of

runoff information. A portion of the Gabil an Creek data �959-1970! was

coll ected by the MCFCWCD-

There were no stream gauging stations in the watershed prior to the

winter of 1978 when two gage plates were established by the Sea Grant pro-

ject. These gauging stations were located on Gap Creek and Carneros Creek,

which are the only incised stream channel s tributary to Elkhorn Slough

with the exception of the Moro Cojo drainage which was excluded for rea-

sons discussed earlier in this section!. Other freshwater drainage to the

slough occurs as non-channel ized overland flow or as subsurface flow.

The Gap Creek station i s 1 ocated about 200 yards upstream of the

marshy edge of the slough on the upstream side of the intersection of

A-46

Elkhorn and sterner Roads. Drafnage area above the statfon is 4.6 square

mil es and represents the channel ized runoff contributed by subwatersheds

�, 18, and 19. The Johnson road station fs located on the north side of

the Johnson Road bridge on Carneros Creek. Station locations. are shown in

Figure A-13b and the subwatersheds contrfbutfng to each station are listed

fn Figure A-14. Cross sections and rating curves for each station are

plotted in Ffgur es A-15 and A-�.

As no runoff data had been collected from any stream in the Elkhorn

Slough study area prior to our measurements in the spring of 1978, it has

been necessary to use published empiric or synthetic methods which attempt

to estimate runoff using cl fmatic and topographic information. Some of

these methods require only very 1 imited input data such as drainage area

and mean annual rainfall for predicting runoff characteristics.

In the following analysis of runoff, two basic technfques were used:

fl ood frequency analysis and hydrograph sfmul ation. The purpose of fre-

quency analysis is to estimate the probabf1 ity of occurence for a specified

hydrologic event, for example, to estfmate the peak discharge of a stream

at a certain recurrence interval, or a recurrence interval for a certain

peak discharge.

In contrast, hydrograph simulation generates a graph of the amount and

tfming of water transported past a given point in the stream, usually over

8The recurrence interval is the average number of years in which a givenrunoff event will be equaled or exceeded.

A-47

Figure A-13b

Location of Runoff Ga in Stations

Gap Creek

2. Johnson Road

3. Nursery

Elkhorn Slough Watershed StudyInatltote of Urban and Regional Development

Unbreraity of California, Sar ke icy 8erkeley, CA

A-48

Al 0

WCQ Q

A-49

C Ch ILI0G cIl MD 0 III

0OIII CIl QPVJ4 M IIlCJ

Cl

'0 0IZo

40

Figure A-15 Cross-section of Channel and Rating Curve of Gap Creek Station

A-50

Figure A-16 Cross-section of Channel and Rating Curve of Zohnson Road Station

A-51

the perfod of a specified size storm.

Four methods of frequency analysis analysis of recorded data, the

Rational Method, the Rantz Regional Frequency Method, and the Rantz Modi-

fied Synthetic Unfty Hydrograph/Recurrence Curve method! were fnvestigated

for possible appl fcation to the limited Elkhorn Slough data. Of these only

the two Rantz methods were found to be suitable. For hydrograph simul a-

tion, the Unit +drograph method, the Runoff Coefficient method, and the

SCS Curve Number method were investigated, of which the 1 atter two were

used for El khorn Slough analysis� . General comments on the appl fcabil ity of

each of these methods and the results are included belo~.

A graph showing stage, discharge, velocfty, or . other properties of

water flow with respect to time is known as a hydrograph. If discharge

f.e., volume of water passing a point at a given time! is plotted against

time, the g raph i s c al 1 ed a "df sc harg e hydrog raph" or canmonE y just "hydro-

graph." The hydrograph can be regarded as a simpl e expression of the ccm-

plex physiographic and climatic characterfstfcs that govern the relatfons

between rainfall and runoff in a particular drainage basin.

The horizontal axis of a hydrograph is tfme, and the vertical axfs is

the discharge commonly noted as !!. Common units of dfscharge are CFS

cubic feet per second!, acre-feet/day, or inches total discharge in a

unit time divided by the total area of the basfn, in inches! .

Hydrographs can be obtained directly if a continuous r eading of stream

height, over tfme is avaflable. In many cases, however, gauging records are

A-52

not available, and ft is necessary to use varfous other methods to calcu-

late the hydrograph,

Flood ~Fre uenc Analysis

Rantz �971! of the U.S. Geological Survey has developed a set of mul-

tiple regression equations for predicting peak discharges at selected

recurrence interval s based on the record of forty stream gauging stations

located between southern Mendocino and southern Santa Cruz counties. Peak

discharges for 2, 5, 10, 25, and 50 year recurrence intervals were conputed

for each of the forty stations by fitting a logarithmic Pearson Type Ill

distribution to observed annual peak flows.

Peak discharges were correl ated wi th climatologic and topographic

parameters for each of the five recurrence intervals. The parameters found

to have the most significant effect on peak discharge were �! size of

drainage area and �! mean annual basinwide precfpitatfon. These two fac-

tors became the variables in the mul tiple regression equations which were

derf ved for each recurrence interval . The regression equations and the

method are presented fn Figure A-17. Al though Elkhorn Slough lies south of

the Rantz study area, three stations in southern Santa Cruz county are

relatively close to the Elkhorn watershed two on Corralitos Creek and one

on Soquel Creek! . Since there were no similar regression equations avail-

able for the Monterey area, the Rantz equations were appl ied to the

Elkhorn data. A discharge curve was plotted for the 70.6 square miles of

drainage area of the sl ough see Figure A-18! . Di scharges for each

recurrence interval can be determined from this curve,

Figure A-17 Rantz Regional Frequency Method

Data Required Calculations

References: S. E, Rantz, "Sugg sted Criteria fo..- d.ologic Designof Store-Dra'nage Facil'-.ies in .he San Francisco BayRegion., Califorria," U.S.G.S. i>en ."ile Re~crt, Nove=ier24, 1971.

A-54

1, Total DrainageArea in SquareMiles

2. Annual ArealAverage AAA!,Rainfall inInches

l. Using Rantz Regression Equations, calculate

= a A ~ P

where Q is discharge of' t year recurrencein cfs, A is total Drainage Area in squareud.les, P is AAA rainfall in Inches, anda,b,c are coefficients for recurrenceinterval t. The values are listed below:

Several methods have been developed for constructing synthetic hydro-

graphs from rainfall data; however, most of these methods are designed to

be used in any location within the United States. Rantz �971! has modf-

ffed one synthetic unft hydrograph method to account for more regionally

specific var iables-- this modified method incor porates such factors as

water loss, infil tration, 1 and use, so f1 type, and drainage area. The

study area used for developing the method included seven stations in the

San Francisco Bay area, of which one station, Corral itos Cr eek, is located

just north of the Elkhorn Slough watershed boundary. Because this was the

only such analysis available for the region, the equations were applied to

the El kho rn d ata .

The construction of unit hydrographs fs a common engineering tool for

rel ating rafnfal 1 to runoff. The unit hydr ograph is a single peaked

discharge hydr ograph resul ting from one inch of dfrect runoff generated

uniformly over the watershed at a unf form rate during a specified period of

time. The data required for deriving a unit graph are �! simu'l taneous

measurements of rainfall and runoff from the basin for a nmber of years,

and �! some estimate of the fnfil tration rate. The procedure requires

choosing several preferably four or five! rainstorm periods for which the

resul ting runoff hydrographs are avaf1 able. The storm periods shoul d be

those of high intensfty and with sfmilar areal distributions of rainfall,

and should be isolated storms of uniform intensity. These hydrographs are

reduced to unit graphs from which an average unft graph for the basin is

derived .

As shown in Figures A-18 and A-19, there are smaller disc harges at the

lower ~ecurrence fnterval s using the synthetic unf t hydr ograph method than

Figure A-18 Rantz Regional Recurrence Curve

2,++0 4 ' ~ ~ I ~ ~aaml, e gals

Figure A-19 Rantz Recurrence Curve - L'edified "-;wtheti c <..it ii~.""cgra-:.Methad

A-S6

obtained using the regional frequency method e.g., 0~ = 35Q cfs vs, 01000 cfs!. This lower discharge resul ts from Rantz's assumption that most

rainfall from small storms will infiltrate and not produce significant run-

off, whereas rainfall from large storms will quickly satur ate the soil and

become almost entirely runoff. Thus the effect of differ ences in soil

types or slope within a watershed which determine infiltration rate! would

be proportionately less for the large storms.

The discharge for the longer recurrence interval s computed using the

two methods are more similar e.g ~, 050 11,3pQ vs ~ 050 11,50p cfs! .If the pl armer is only concerned wi th the 1 arge runoff resul ting from

episodic events, then differences in soil types in the watershed can almost

be ignored .

In the following disucssion, two methods for constructing synthetic

hydrographs are desc ribed and the resul ts obtained for El khorn Sl ough

watershed are presented- The empirical runoff coefficient method and the

SCS curve number method were appl ied after certain modifications were made.

Runoff Coefficient thethod

Due to water loss by evaporation, infiltration, and transpiration, not

all water which falls as precipitation can be accounted for as surface run-

off. For this reason, the ratio of runoff to rainfall is always less than

one. This ratio, called the runoff coefficient, can be used to estimate a

runoff hydrograph when only rainfall data is known.

The runoff coefficient method is best used when at 1 east thir ty years

of complete rainfall and runoff records are avail able. If runoff records

are not avail able for the study watershed, runoff data from other simil ar

A-57

watersheds may be used, but care must be taken to sel ect "surrogate"

watersheds which have simil ar drainage areas, soil type, rainfal l charac-

teristics, vegetation, and infil tration conditions.

Rainfall and runoff data were obtained for Gabilan Creek, a watershed

with similar hydrologic conditions located immediately south of the Elkhorn

Slough watershed. To obtain monthly . runoff values for Elkhorn, runoff

coefficients calcul ated for Gabil an Creek were mul tipl ied by the average

monthly rainfall data for Elkhorn. The monthly r unoff values for Elkhorn

are listed in Figure A-20 and the resul tant hydrograph for Elkhorn Slough

is pl otted in Fi gur e A-21, A-22, and A-23.

Comparison of monthly runoff wi th rainfall records shows a dramatic

change in the magnitude of runoff coefficients during a year. Runoff coef-

ficients are approximately zero during the fall and winter when rainfall is

low and soil is dry. The coefficient gradual ly increases during the wet

season from December to early June, reaching a maximum in May and dropping

almost to zero again by July.

The low runoff coefficient at the beginning of the wet season is due

to the high rate of infiltration into dry soil. Even with 1 arge amounts of

rainfall and runoff in December, the ratio of runoff to rainfall remains

relatively low until the soil becomes saturated in late January and Febru-

ary.

For later comparison wi th SCS method, daily hydrographs were con-

structed for each of two representative ~ater years 1964, a wet year, and

196'. a dry year! . Monthly runoff coeffic ients were multiplied by daily

rainfall amounts to generate the hydrographs shown in Figures A-21 and A-

A-58

ttt ~ tt'4 C

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0

OO

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~880 0

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0

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0'

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00

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A-59

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0 8 w 0 8 v ~ 0 8 0 0 00 0 0 0 0 0 ct 0 0

0 0 0 0 0 0 0 ~ 0 0 0 0 0 00 0

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o n 3 0 R Q 0 8 w ttt o 00 0 0, 0 0 0 0 0 0 0

0 a ~ 0 v 0 ~ 0 t

v w < w w Ct A A cT OH At Ct V' m M m m 8 W t C III0 w ttt A a hatt ttt 0 < W A N

QZZOBPQB2

a $ $ $ $ 4 8 g f 4 $ t c, ~c

O

0

C 0

c ltt0o

~ r

a'V

Raf nf ~ 11

Ruoof f P acliarga!

Jaovune July AND. Sep

a mu o

Rainfalln

Runott D ecbarae!

Julv Aoe, Sep.Apr. Hay J uoefeb. NarDac. JanOct. Nov

I

. I

Figure A-21 Rainfall and Hydrograph of Water Year1964

Gabilan Runoff Coefficient-Daily Rai.,f '' ,'.

,IFigur«-22 Rainfall and Hydrograph of Water Year

1965 Gabilan Runoff Coefficient-Daily Rainfall !

22.

SCS Curve Number Method

The curve number method for estimating runoff has been developed by

SCS hydrologists for use in watersheds where there is no available runoff

data, but there is information on soil type, 1 and use and rainfall. This

is a common situation for many smal 1 California watersheds where the

streams have not been gaged but soil/vegetation maps and regional rainfal 1

data are avail able. The method accounts for variation in soil and cover

types within the watershed, and is particularly useful in that it allows

the comparison of runoff which occurs under different assumptions of urban

and agricul tural land use mix.

The method utilizes an index, known as the Runoff Curve Number, which

represents the combined effects of soil type and land use on runoff. Curve

numbers have been empirically determined for various soil-cover compl exes

and scaled ordinally from 0 to 100. A curve number of 100 would represent

all rainfall becoming runoff, whereas a curve number of 0 would represent

no runoff at all. In actuality, curve numbers range from about 30 e.g.,

for well-sodded meadows! to 98 for paved surfaces!.

The effect o f so il type i s incorpo r ated into the method by the hydro-

logic soil group factor. This factor aggregates all soil types into one of

four classes A to 0! refl ecting the minimize rate of infil tration obtained

A full description of this method and illustrated exampl es are presentedin the SCS National Engineering Handbook, Hydrology Section. SCS, 1964!.Chapter 2, Suppl ement 1 of the Fngineering Field Manual lists the curvenumbers for use in California.

for the bare soil after prolonged wetting. Hydrologic Soil Group A

includes soil s with a high infiltration rate even when thoroughly wetted,

such as well-drained sands and gravel s. These have low runoff potential .

At the other end of the scale, soils in hydrologic group 0 have a low

infil tration rate and high runoff potential. These include clay soil s,

soil s wi th a high water cable, or shallow soil s over nearly impervious

material . Groups B and C are intermediate in infil tration rate and runoff

potential . The hydrologic group of a soil can be found in the published

Soil Survey Reports of the SCS. The curve number method estimates "direct

runoff" i.e., surface runoff, channel runoff, and an unknown proportion of

subsurface flow! . Base flow i.e., the steady flow from natural storage in

soil or aqui fers! is assumed to be insignifiant. The method was determined

to be suitable for this study because it could be assumed that most runoff

was surface runoff rather than base flow. This assumption was made on the

basis that:

e The flow on small water sheds in other arid areas is usually surfacerunoff.

e Most channel beds in the Elkhorn watershed are dry in summer.

~ There is evidence of overpumping of groundwater for irrigation, sug-gesting that subsurface water is usually not avail able for reemer-gence as stream flow.

was constructed as previously described and a hydrologic soil group map

prepared fran existing soil information SCS, 1964!. Measurements of

urbanization and crop type were obtained from a 1977 land use map obtained

fr om the County.

Acreages of each soil/cover combination were measured by subwatershed

from overlays of the hydrologic soil groups, 1 and use and crop maps. A

single modified curve number was computed for each subwatershed by weight-

ing the curve number of each soil/land use combination by the area it occu-

pied.

Curve nvnbers for the 1 and uses occur ring in the El khorn study area

are listed in Figure A-23b. Note that urban uses have higher curve nNnbers

than undisturbed vegetation, which is expected. However, note al so that

curve numbers for urban uses are not necessarily higher than agricul ture.

For example, within hydrologic soil group D, CN = 93 for strawberries,

whereas CN 92 for urban lots less than one-quarter acre. Similarly, CN

86 for brussel s sprouts conpared to CN 84 for urban lots greater than one

acre. These values reflect the greater influence on runoff from compacted

bare soil in row crops than from the 1 awn or pasture cover on residential

yards.

The weighted curve nNnbers ccmputed for 1977 land uses by subwater shed

are contained in Figure A-24, Part l.

Runoff is computed by applying the curve number to known rainfall,

after adjusting for soil saturation and periods of crop dormancy. Al though

some rainfall records were avail able from 1881 on, daily rainfall records

from 1964 to 1975 were used since a larger nanber of stations about seven!

were in operation during that period than previously. Mi ssing data and

disaggregation of summed weekend readings were compl eted by estimation

methods described in the section on rainfall data collection. Daily rain-

fall for each subwatershed was determined by the weighted average of nearby

stations. The 5-day antecedent moisture condition ANC! was cal cul ated by

summing the rainfal 1 of the previous five days. Curve numbers were modi-

fied according to the AHC and the growing season.40

The dormant season was assumed to be October 1 to April 15.A-64

Figure A-23b SCS Curve Numbers for Land Use/Vegetation Typeswithin the Elkhorn Slough i"atershed

Land Use/Vegetation Hydrologic Soi Group

6

10

lla

11

11c

12

A-65

Orchard - Fair Condition

Brussels Sprouts � Fair

Trees, Brush - Fair

Mushrooms - Fair

Non Agri-Vegetation in Slough � Fair

Grassland. Pasture - Poor Condition

Grassland Pasture - Fair Condition

Strawberries, Barren � Fair

Artichokes - Fair

Nurseries � Fair

Interchangable Crops � Fair

Urban, Lot size less than 1/4 acre

Urban, 1/4 acre Lot Size 1 acre

Urban, Lot size .! 1 acre

Open Sps.ce, Empty Land

Slough Water

A B C D

42 64 76 82

65 75 82 86

44 65 76 82

51 68 79 84

58 70 78 84

65 7S 86 89

49 69 79 84.

77 86 91 93

65 75 82 86

36 60 73 79

65 75 82 86

77 85 90 92

61 75 83 87

68 79 84

39 61, 74 BG

100 100 100 100

Figure A-24 5CS Curve Numbers by Subwatershed

Scenario

CurveÃunber

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A-66

Part 1: Existing Use

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A-67

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A-68

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A-69

Figure A-24 cont'd!

Part 2: Full 8uild-out Scenario, convert existing agriculture

Figure A-24, Part 2 cont'dj

Land Dee! HydrologicSubeetershed Ve etesian Scil Gros- Cures

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A-71

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A-72

Figure A-24 cont'd!

Part 3: Full Build-out Scenario, maintain existing agriculture

Figure A-24, Part 3 cont'd!

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A-73

1. 90'G. 10,2. 0120, 2280, 399G.451'1.078

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A FORTRAN IV program was appl ied to cal cul ate the runoff, rainfal 1,

and modified curve numbers for each subwatershed, using the initial curve

numbers, areas and daily rainfall records of the seven stations. The pro-

gram for these calculations is found in Technical Appendix A-ll.

The corresponding rainfall and runoff hydrographs of the SCS method

are pl otted in Fi gures A-8, Yearly rainfal 1, runoff, and peak daily

discharges are listed in Figure A-25. Note the following resul ts of the

SCS cal cul ation:

~ The wettest year is 1969, with an annual regional rainfall of 28.8inches.

~ The year of the highest peak flood is also 1964, calculated at 5721acre-feet per day. Generally speaking, a wet year will tend to havelarger runoff peaks, but the size of peak also depends on the dis-tribution of the rainfal 1 . Several smal 1 storms in a concentratedseries coul d contribute more runoff than a larger total rainfallwhich is distributed over a longer period.

~ The years with lowest runoff are 1968 and 1975, wi th 12.29 inches ofrainfall and 1169 acre-feet per year runoff, and 16.85 inches rain-fall and 1409 acre-feet per year runoff respectively. Al though 1972experienced lower total rainfall than either year 8.77"!, runoffwas higher at 2026 acre-feet/year.

Comparison of the hydrographs of the two methods, shown in Figures A-

26. indicates that the SCS method produces about twice as much runoff as

the runoff coefficient method. Neither numerical value, however, abso-

lutely defines the actual runoff. However, when no runoff data are avail-

able for an area, hydrologists are willing to suggest that runoff estimates

which differ by 100-200 percent are still fairly close.

Comparison of the 1964 and 1965 hydrographs in Figures A-7 and A-8

indicates that the runoff distribution cal cul ated by the runoff coefficient

method has a longer duration than the SCS method. The SCS method indicates

that runoff is concentrated during wet winter months after the soil is

.5

44 ~ I . 4 554.4 5 ~ 5. 4T 5554 la 4*ta

545.a555.4 5 ~ ~ . 4

44 545.4~ I . 4 I at�. ~ t ~ ~ . 0 5 ~ ~ . 4I ~ 5. 4Tlat l a ar Tt

A-75

v ~r

5

r 4. 1

, t

r .5V r

, I

. Irr . I

Figure A-25 Average Oaily Rainfall and Runoff�2 year average!

cp~~y+~<O

'0C

'U 4

4 0Cf!

0 4 d6 0

0 C 0

sz + ~a" F<z z>m rg~

A-76

saturated, and that no runoff occurs in the late spring months. In con-

trast, the coefficfent method indicates surface runoff continues to June.

It should al so be noted that the ~eak dafly flow as calculated by SCS

method �7 CFS! is three times larger than the value calculated by the run-

off coefficient method �1 CFS!. The MRE value fs about six times 1 arger

�7 CFS! however, this hydrograph represents runoff from a smaller drainage

area.~~

The runoff coefficfent method is satfsfactory for estimatfng total

runoff when no other data are avail able. However, since the SCS method

accounts for more variables than the coefffcient method, it is suggested

that the SCS method is more reliable and provides more conclusive evidence

in this study.

Runoff Under Alternate Land-Use Scenarios A useful aspect of the SCS

Curve Number method is that it allows comparisons to be made of the runoff

resul ting from different patterns of 1 and use. By modifying the curve

number accordfng to the area occupied by a land use under alternate plans,

the appropriate runoff value can be determined. For example, an assumption

of expanded urban use may produce a higher cure nvaber, hence higher run-

off.

This technique was appl fed to the Elkhorn watershed data for three

alternate land use assumptions. Scenario I predicts runoff under the 1 and

~ Water Resources Engineers, Inc., Sept. 1969.

The Mater Resources Engfneers estimte was based upon U.S.G.S. data fromthe Sal inas River, MCFCMCD data, and engineering judgement.

A-77

use coverage existing in 1977. Resul ts of this computation were discussed

in the preceeding section. Scenario II assumes ful 1 buil dout of the

current Monterey County Land Use Plan before its modification in the local

coastal program! . Scenario III al so assumes full buildout of the existing

plan, but with maintenance of all existing agricul tural uses rather than

conversion to other designated uses. This assumption was fel t to be real-

istic given the strength of existing coastal Commission policies on mainte-

nance of existing agricul ture.

The curve numbers canputed under Scenarios II and III are presented in

Figure A-24, Parts 2 and 3. It should be noted that the acreages of 1 and

uses under Scenarios II and III were measured from a poor resolution sketch

map of the County General Plan and as such are only rough estimates of true

acreages. Now that more accurate 1980 land use data is avail able, better

curve nunbers can be calculated for existing and projecting land use pat-

terns� .

Al though cal cul ations have not been conpl eted for runoff under

Scenarios II and III, it is predicted that runoff for the watershed as a

whole will not increase significantly under full buil dout since existing

land use plnas prOject rel atively lOw density useS which have characteriSt-

ical ly low impervious surface coverage. Measures of impervious surface for

various development densities occurring in the elkhorn watershed are dis-

cussed in detail in Appendix 0. This prediction does not mean that local-

lized effects of development could not have significant effects on local

runoff. As discussed in Appendix 0 and the main text, a ten percent imper-

vious sur face coverage is a minimum threshold value, above which the

effects of increased discharge become noticabl e. Impervious surface above

this may resul t in downcutting of channel s and local 1 ized flooding. The

subwatersheds in which this may be a problan and a more extensive discus-

sion of this subject is contained iii the main text.

Predicting the effects of increased agricul tural devel opment fn the

water shed is compl icated by the difficul ty in making assumptions about

future crop mixes. As prev fously noted, runoff from intensiv'e row crops

such as strawberries, brussel s sprouts and ar tichokes f s somewhat higher

than low densfty urban uses, and much higher than grassland pasture. Addf-

tional scenarios assuming df fferent mixes of raw crops coul d be tested,

however nef ther the County or the Coastal commfssion have present regula-

tory authority over the crop types produced in agricultural zones.

Field Runoff Measurement

Field measurements of stream runoff were taken at both stations for

three storms in the winters of 1977-78, and two dur ing the wfnter of 1979-

80. Staff gage readings were made at approximately forty minute intervals;

sur face vel oc i ties were measured at al ternate readings. Unfortunately,

gaps in the field data collection resul ted in missed runoff peaks for

several storms which coul d only be estimated I dashed lines! . Hydrographs

and hyetographs are presented in Figures A-27 to A-30 for Gap Creek and A-

31 to A-33 for Johnson Road. Hydrographs were plotted from actual field

measurements of velocity and gage hefght rather than fram the smoothed rat-

ing curve; surface velocitfes were adjusted by 0.8 so as to approximate

mean channel velocity.

Lag tfmes, measured as the time between the approximate centroids of

corresponding peaks of rainfall and runoff, are presented fn Figur e A-34.

A-79

I I I

I �:i I!.Ill}ti} .'."' "

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,II "frI,I Lr

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A-80

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Storm Hydrograph of March 3-5at, Gap Creek Station

I I I»

Figure A-28i

Hydro a h of Feb. 12-

30I Figure Storm Hygrograph of April 24-25 'at Gap Creek Station

I I IStorm Hzdrograph of Feb. 12,

Road StationI I rr II@

I.. I

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Storm Hydrograph of March. 3-5 .;at Johnson Road Station

figure A-

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h of A ril 24-2gp'i~+ A 33 Storm Hydrogr aP PJp~ g pn R.a a p'I Statio n

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Figure A-34 Lag Times--Gap and Carneros Creeks

Date

4,5»5,4*

7

1.5!.53

2.55

3, !.5*

76

S, S.S*

1.82.68

5.46.36

Mean~a culated»*

* Two readings refer to lag times for separate hydrograph peaks wi thin thestorm.

** Lag time calculated accordi~g to the formula: Lag 1.3 D.A.

!978~e. 12-13

Mar/ 3-5Apr. 24-25

1979~an. 14

Feb ~ 160 8 Feb. 20-2!

Lag Time hours!Gap ~ree~ Carneros Creek � Johnson Road

D.A~.rsq.mi.! g!.A~4 sq.~i T

Lag times vary with antecedent moisture conditions but average 1.8 hours

for Gap Creek and 5.4 hours for Johnson Road. The rel atively short lag for

Gap Creek reflects the small drainage area.

A-85