Hydrology and Water Resources in Arizona and the Southwest, Volume 20 (1990)

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Journal Hydrology and Water Resources in Arizona and the Southwest

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Link to Item http://hdl.handle.net/10150/296447 VOLUME 20 HYDROLOGY and WATER RESOURCES inARIZO \A and the SOUTHWEST

Proceedingsofthe 1990 Meetings ofthe Arizona Section American Water Resources Association and the Hydrology Section Arizona- Nevada Academy of Science

April 21, 1990, Arizona State University Tempe, Arizona Volume 20

Hydrology and Water Resources in Arizona and the Southwest

Proceedings of the 1990 Meetings of the Arizona Section -- American Water Resources Association and the Hydrology Section -- Arizona- Nevada Academy of Science

April 21, 1990 Arizona State University Tempe, Arizona TABLE OF CONTENTS

PAGE Introduction

Ordering Information for AWRA Publications vii

Groundwater Quality in the Bullhead City Area, Mohave County, Arizona

Cynthia M. Darr 1

Site Investigation of Underground Storage Tank Contamination Kevin D. Hebert 13

Site Remediation of Underground Storage Tank Contamination Scot Journell 19

Use of Biotoxicity Tests for Estimating Impact of Stormwaters on Aquatic Life Frederick A. Amalfi, Elizabeth M. Atkinson, and Julie D. McNaughton 27

Recent Hydraulic Change in the Santa Cruz River System Near Tucson, Arizona: Structural Control and Tectonic Processes Jeffery Zauderer 37

A Geographically -Based Land Use Suitability Assessment and Land Capability Classification Rex Victor O. Cruz and Peter Ffolliott 51

A Taxonomy of Small Watershed Rainfall- Runoff Richard H. Hawkins 63

Evaluating the Role of Flooding in a Southwestern Riparian System Brian Richter, Duncan T. Patten, and Julie C. Stromberg 75

Quantification of Evaporation and Seepage Losses with a Floating Evaporation Pan: Lee Valley Reservoir, Arizona Don W. Young, Gerald Colmer, and Scott Goodwin 85

Proposed Methodology for Soil Loss Prediction From Southwestern Forest A. Tecle, D.P. Dykstra, W.W. Covington, and L.D. Garrett 113

Effects of Plant Growth Regulators, Nitrogen Fertilization, and Irrigation on Eldarica Pine Seedlings Amal O. Darwiche and Peter F. Ffolliott 131 INTRODUCTION

The Arizona Section of the American Water Resources Association and the Hydrology Section of the Arizona -Nevada Academy of Science met at Arizona State University on April 21,1990. The annual meeting provides a forum to discuss water issues and present current research results. This docu- ment is made up of the proceedings of that meeting.

Papers presented at the meeting were submitted camera -ready by their authors for this publication.

These proceedings were produced by the editorial and graphics section of the Office of Arid Lands Studies and the Water Resources Research Cen- ter, University of Arizona.

v ORDERING INFORMATION FOR AWRA PUBLICATIONS

Copies of the following documents can be ordered from Arizona Section, American Water Resources Association, 845 North Park Avenue, Tucson, Arizona 85719, c/o Dale Wright.

Hydrology and Water Resources in Arizona and the Southwest. Volumes 7 through 10 (proceedings of the 1977 -1980 meetings) $12 per copy. Volumes 11 through 18 (proceedings of the 1981 -1990 meetings) $14 per copy.

Urban Water Management: Augmentation and Conservation (October 21, 1983, sym- posium) $10 per copy.

Water Quality and Environmental Health (November 9,1984, symposium) $10 per copy.

Conjunctive Management of Water Resources (October 18,1985, symposium) $10 per copy.

Water Markets and Transfers: Arizona Issues and Challenges (November 7,1986, symposium) $12 per copy.

Instream Flow: Rights and Priorities (October 30, 1987, symposium) $12 per copy.

Adjudication of Water Rights: Gila River Watershed, Arizona (October 28, 1988, symposium) $14 per copy.

Effluent: Yours, Mine, or Ours? (October 27, 1989, symposium) $14 per copy.

vii GROUNDWATER QUALITY IN THE BULLHEAD CITY AREA, MOHAVE COUNTY, ARIZONA

Cynthia M. Darr Arizona Department of Environmental Quality 2005 N. Central Ave Phoenix, AZ. 85004

Introduction Bullhead City is located along the Colorado River in Mohave County in the northwestern section of the state (figure 1). The Bullhead City study area encompasses a thirty square mile area including old Bullhead City, Riveria and a part of Fort Mohave. The Bullhead City area is the fastest growing area in the state at this time. In September 1987, the Arizona Department of Environmental Quality (ADEQ) conducted a field reconnaissance of groundwater quality in the Bullhead City area.Additional information was collected in August 1988 for a nitrogen isotope study and in May of 1989 as part of a state -wide virus study.Hydrologists measured water table depth and sampled groundwater quality in an attempt to better understand the regional hydrogeology. Our objectives in this investigation were to assess the impact of current wastewater disposalpracticeson groundwater quality and to obtain background information to be used in reviewing permit applications for discharging facilities. The majority of the wastewater disposal in the study area has predominantly been through septic systems. Although there are three sanitary districts in the area they serve only a small percentage of the area. A map showing the distribution of sewered areas is included in figure 2. Due to the rapid growth of BullheadCityandsurroundingareasandthe increased use of septic systems the potential for groundwater contamination exists. The constituents of concern from these systems arenitrates, phosphates, salts, microbiological organisms, andtotal dissolved solids. Hydrology The Colorado River is the dominant surface hydrologic feature and bounds the western part of the study area. Davis Dam impounds the River five miles to the north forming Lake Mohave. The fairly narrow river bed incises the alluvial flood plain and is enclosed by mountain ranges to the east and west. Lithology is divisible into three broad categories: riverbed alluvium, fanglomerates, and crystalline rocks.The primary aquifer is the riverbed alluvium of Quaternary ( ?) age

1 (Metzger and Loeltz, 1973). The depositional environment is a meandering river bed, with a typical stratigraphy of gravel, sand, silt and mud. The mountain - forming units are mid to late Tertiary volcanic and igneous rocks, but it is unlikely that these units are water bearing in the study area. Along the mountain fronts are the fanglomerates formed by the erosion of the mountain - forming units.The fanglomerates are composed of angular poorly sorted pebbles cemented in a sandy matrix (figure 3). A few wells located further east from the river and away from the riverbed alluvium probably withdraw water from the fanglomerate unit. Depth to groundwater in wells measured in this study ranges from 30 feet near the river to 183 feet one and a quarter miles away from the river. The water elevation data was inconsistent and could not becontoured. Therefore, a groundwater flowdirection for the area could not be determined. Inconsistent water elevation data could result from changing river stages, differences in total depth and perforated interval of the wells measured, and local pumping of wells. However, the most likely groundwater flow direction is to the south -southwest along the axis of the Colorado River with a localized component of flow to the east -southeast away from the axis of the river.The data supports the premise that the aquifer is being recharged by the Colorado River because in mostcases theelevation of the river is higherthan groundwater elevation. Results of Groundwater Quality Investigation Groundwater samples were collected during three separate sampling events. In 1987 a field reconnaissance of groundwater quality was conducted,samples including two duplicates and one field blank were collected from twenty - two wells. An additional five samples were collected for a nitrogen isotope study in 1988. Recently in May of 1989, as part of a state wide virus study, 15 samples including one duplicate were collected. In all 36 wells were sampled. Three of these wells were sampled more than once. The Super 8 monitor well (B- 20- 22)01da was sampled four times once during each sampling event including one duplicate. The Riviera well (B- 20- 22)09dcd was sampled three times one sample and one duplicate were collected in 1987 and one sample was collected in 1988. A duplicate sample of the Tierra Verde well(AV40, AV41) was collected in 1989. A total of 42 samples were collected during the three sampling periods.All samples were analyzed for primary and secondary drinking water parameters. Bacteria samples were collected from 22 wells. A number of sample results in the study area are above the Primary(MCL) or Secondary(SMCL)drinking water maximum contaminant level. The two parameters detected above primary

2 MCLsarenitrateandarsenic. Below is a summaryof constituents detected at levels of concern:

o Nitrate is above background (typically 3 mg /1 as N) in nine wells and exceeded the MCL (10 mg /1 as N) in one well. o Chloride exceeds the SMCL(250 mg /1) in fifteen wells, o Total Dissolved Solids exceeds the SMCL (500 mg /1) in thirty six wells. o Arsenic exceeds the MCL (0.05 mg /1) in three wells. o Iron exceeds the SMCL(0.33 mg /1) in five wells. o Manganese exceeds the SMCL (0.05 mg /1) in ten wells. o Sulfate exceeds the SMCL (250 mg /1) in twenty

four wells . As indicated above, every well exceeded the SMCL (500 mg /1) for total dissolved solids. Many of the wells, also exceeded other SMCL's. However, only four wells sampled exceeded an MCL. One well exceeded the MCL for nitrate (10 mg /1) and three other wells exceeded the MCL for arsenic (.05 mg /1). All other results were below primary drinking water maximum contaminant levels. Coliform bacteria were not found in any of the samples from the 22 wells for which bacteria was tested. A map showingthe wells whichexceeded MCL's presented in Figure 4 for nitrate. As part of a state wide virus study, 14 virus samples were taken in the study area. Although there are no water quality standards for viruses in groundwater, samples were taken to determine the prevalence of microbiological organisms in Arizona's groundwater. Laboratory analysis included waterborne enteroviruses which are harmful to humans. Virus samples taken from the study area indicated that no viral contamination was present. A survey of 87,000 wells (Madison and Brunett, 1984) with nitrate analyses using the United States Geological Survey's National Water -Data Storage and Retrieval System (WATSTORE) of nitrate concentrations in groundwater indicates the following:

o Less than 0.2 mg /1 - assumed to represent natural background concentrations. o 0.21 to 3.0 mg /1 - Transitional; concentrations that may or may not represent human influence. o 3.1to 10.0 mg /1 - May indicate elevated concentrations resulting from human activities. o Greater than 10 mg /1 - Exceeds maximum contaminant limit.

3 Arsenic exceeded the MCL in three wells, all located within the same area. Although the source of the arsenic is unknown, there is no evidence of an anthropogenic source such as pesticides. Therefore, itis believed the source of arsenic is naturally occurring. There are several different natural environments with which arsenic is typically associated (Welch, Lico, Hughes, 1988). Two of these environmentsmay bepresent inthestudyarea. These environments are: 1) Sedimentspartiallyderivedfrom volcanic rocks of intermediate acidic composition and 2) Evaporite deposits. No specific evaporite deposits have been documented in the area. However, they are known to occur in the Bouse Formation south of the study area and can be expected to occur in Quaternary meandering river deposits. Interpretation of Results

We have identifiedthreepotentialmajorinfluences on groundwater quality in the Bullhead City area:recharge from surface water,discharge from septic systems, andlocal hydrogeology. How these threeimportant factorsaffect groundwater quality depends on many factors such as the location ofthe well,total depth ofthe welland the stratigraphic units penetrated, and proximity to discharging septic systems.

Surface /groundwater Interplay. Figure 5 shows the stiff diagramsrepresentative of waterquality for thewells sampled. A surface water sample of the Colorado River (B- 33) was included on figure 5 for comparative purposes.Stiff diagrams of similar shapes have ratios of concentrations of major ions though not necessarily the same chemical concentrations. Thus, these diagrams allow a qualitative assessment of groundwater geochemistry. Comparison of the stiff diagram for surface water with those of groundwater samples shows that samples B -6 and B -9 are similar to the surfacewater sample B -33, indicating that groundwater obtained from these wells is primarily derived from the river. This similarity indicates that wells which are strongly influenced by surface water are located closest to the river. Other groundwater samples show varying degrees of deviation from surface water quality indicating that other factors, either natural (lithologic changes) or anthropogenic (domestic sewage), are influencing groundwater quality. Wastewater Impact. Recharge from domestic sewage contains nitrates, salts, phosphates, metals, bacteria, viruses and a variety of household contaminants. The major constituent of concern is nitrate which ranges from 40 to 70 mg /1 (as N) in domestic sewage or 4 to 7 times the maximum contaminant level of 10 mg /1. Nitrate is not appreciably attenuated in the vadose zone. Consequently, most nitrate from septic tank discharge will reach the aquifer. Impacts of septic effluent are generally first observed in the upper portion of the

4 aquifer. Therefore, shallow wells will most likely exhibit high nitrates before other wells in a region. Increase of total dissolved solids (TDS)is another signature of the influence of septage. A rule of thumb is that water which passes through a septic tank experiences a TDS increase of about 100 to 300 mg /l. (Kaplan, 1987).

To assess thepotential impacts of domesticsewage on groundwater quality a map of nitrate concentrations and stiff diagrams representing groundwater quality (figure5) were prepared. The impact of domestic sewage on groundwater quality is shown by increases in nitrate, chloride and TDS concentrations, and by a distinct shape of the stiff diagram. To determine where the impact of domestic sewage would most likely occur, a map illustrating the distribution of sewered areas and population density was produced and is included as figure 2. This figure shows that development in the study area are predominantly on septic systems except along the northern reach of the river bend where both Riverside Sanitary District and Citizens Utilities service areas are located. Examination of figure 2 suggests that domestic sewage recharge would probably be greatest in the Old Bullhead City and Riviera areas, since these areas have the highest density of development dependent on septic tank systems for wastewater disposal. To characterize the shape of the stiff diagram representing groundwater affected by municipal sewage, the three monitor wells at the Sierra Wastewater Treatment Plant were examined. Monitor wells B 21 -1 andB 21 -3 are upgradient ofthe percolation ponds and show identical stiff diagram. However, the downgradient well B 21 -2 illustrates an increase of nitrate, chloride, sulfate and total dissolved solids, all of which are indications of wastewater impact. The characteristic Stiff diagram shape in the downgradient monitor well is an excellent example of groundwater contamination by wastewater. A comparable signature might be expected for septic effluent. Wells exhibiting this stiff configuration were found in the old Bullhead City area (B -28, B -30, B -18, A -36) and in Riviera (A -34, B -15, B -17, B -22). All these wells contain nitrate concentrations above 3 mg /1, chloride above 180 mg /1, sulfate above 250 mg /1 and TDS above 1000 mg /1. An increase of all these parameters is indicative of wastewater impact. In addition, preliminary results from the Nitrogen Isotope Study currently being conducted by ADEQ indicate that the nitrogen stable isotope ratio (N15 /N1`) at B 21 -2 (Sierra Wastewater Treatment Plant) and B 28 (Super 8 Motel) represents a nitrate source from septic or wastewater effluent. The ratio was too high to indicate a synthetic source. The final results will be presented in a report entitled "The Application of Nitrogen Isotopes in Groundwater as an identifier of Nitrate Sources in Arizona" by Melanie Redding and Dave Totman.

5 There are three reasons why old Bullhead City is the most likelyarea toexhibitimpacts from discharging septic systems: 1) this area has been inhabited the longest; 2) shallow groundwater (depth to water is approximately 30 feet) and 3) this area has the highest density of discharging facilities in the study area, over 5 houses per acre. Indeed, high nitrate values are found in the old Bullhead City area (B -18, B -28, B -30, A -36). Since there are a number of discharging facilities inthearea, it isdifficult to pinpoint specific facilities as sources of nitrate. In addition it appears that the elevated nitrate levels may extend across a large area because all wells sampled in the area contain above 7 mg /1 total nitrogen. However, to determine the extent of nitrate contamination, additional sampling in this area will be required. Lithology and Water Quality. The local geology in the study area has not been studied in any great detail.At this time, it is difficult to assess the total impact of lithology on water quality. However, thepresenceof some elevated constituents, such as chlorides in the southern end of the study area and arsenic (B -3, B -4, B -5) in the Riviera area might be related to geology since there is no other identifiable source. Mountain -front recharge and recharge along individual surface streams may impact individual wells. Conclusions Our study identified three influences on groundwater quality in the study area: recharge from the Colorado river, recharge from septic systems, and possibly local geology. Groundwater duetorechargefrom theColorado River is characterized by lower sodium and chloride levels. Groundwater quality has been affected by discharging septic systems in the old Bullhead City area and other parts of the Riviera area, as evidenced by high nitrate, elevated chlorides, sulfates and total dissolved solids. Individual wells in the southern end of the study area exhibit unique chemical signatures indicative of the influence of the local hydrogeology. It is possible that nitrate concentrations measured in groundwater as a result of septage discharges will increase due to a lag between the first appearance of high nitrates in groundwater and the equilibrium (full impact) condition. Finally, the impact of the tremendous population growth both within and outside the 208 plan area which are dependant on septic systems represents the most significant threat to groundwater quality in the study area.

6 References Cited Canter, L.W. and Knox, R.C., 1955, Septic Tank System Effects on Groundwater Quality Collin,W.D., 1923, Graphic Representation of Water Analysis: Industrial and Engineering Chemistry v. 15 pg. 394 Hem, J.D., 1985, Study and Interpretation of the Chemical Characteristic of Natural Water: United States Geological Survey Water Supply Paper 2254 Lounsberry, J.F. and Lawrence, S.M., 1988, Boomtown Growth and Land Use Policy issues along the Arizona -Nevada Colorado River Border: The Case of Laughlin -Bullhead City Madison, R.J. and Brunett, J.O., 1984, Overview of the Occurrence of Nitrate in Groundwater of the United States.nATIONAL Water Summary, 1984: Water Quality Issues, p. 93 -105 Metzger, D.G. and Loeltz, O.J., 1973, Geophydrology of the Needles Area, Arizona, California, and Nevada; U.S. Geological Survey Professional Paper 486 -J Owen, Joyce, Sandra, 1987, Estimates of Average Annual Tributary Inflow to the colorado River, Hoover Dam to Mexico, U.S. Geological Survey, Water- Resources Investigation Report 87 -4078

Piper, A.M., 1944, A graphic procedure in geochemical interpretation of Water Analysis: American Geophysical Union Transaction, v. 25 pg. 914 -923 Stiff, Jr., H., 1951, The Interpretation of Chemical Water Analysis by Means of Patterns: Journal Petroleum Technology v. 3, No. 10, Section 1, 15 -16; Section 2,3 Welch, Lico and Hughes, 1988, Arsenic in Groundwater of the Western United States Groundwater, v. 26, May 1988

7 Figure 1. Located across the river from Old Bullhead City is Laughlin Nevada.

8 HOUSING DENSITIES 29 BULLHEAD CITY, AZ and vicinity

32 SEWERED AREAS

SUNRIDGE ESTATES

CITIZENS UTILITY DENSITY VALUES all RIVERSIDE SANITARY DISTRICT in houses per acre' 12 (approximate)

wa rter-ar. Tndn w t , no,a 0 -.99 I/`T/, 13 + + + 1 - 1.99 ++ 4+

20 iar«smi °` 2 - 2.99 Mwtwrtr PlatTrost:mat. 30 2e 25

t 3 - 3.99

38 N 4 - 4.99 t adla 5 - 5.99" wale

new development

data latarprtad from 1907 alr photo Tort 14 13 data darinod from actual oouat (1909) Mohave Figure. 2. Note that the most populated area T2ON 23 24 R22W Sc.l is not sewered. Rseerntloa

127E. 28

12

9 scaleFigure 1 "=3. 550'. Horizontal scale 1 "= 2000', vertical Bullhead OUP.ad vfNndp INFERRED HYDROGEOLOGIC CROSS- SECTION Blackinns --> studyAlocation -A' withinorso of frontmountain recharge TN o . A 4 aVolosalos Bullhead terracesriver .o o o O O n Ó. T ..r.ru.ry. City si, septic . . '0 Colorado o . 4River 1 recharge y I L well Ó o . o . b .fánglómérotés. o O o o Q p .14 I .O a 0. .6)0 quansurr'ALLUVIUM 0'_?N`VllA channel O o o ° ó ° o D O.O O O . O . O 0, ° ° ' . ° O "pe.N. 0. ° o ° ° O O O 0 O O OOp ta ° O O ' ° Q ° t. 7 . o. o O , ___D...no o O o ° z ° . ° °. ° D O D o , ° O p t O O ? o ° ° ° . 0 ° p° Oci . O -°O. _ o . ° o s Q o \° O .o ° O D O fl 1 NITRATE LEVELS 29 BULLHEAD CITY, AZ andvIctnity 91 32 NITRATES a0 -3I,LG /L Total Nitrates 3 -6 MG/L Total Nitrates 5 -7MG/L Total Nitrates 7 -10 MG/L Total Nitrates *> 10 MG/L Total Nitrates (mars= oonissrumt lewdis to NO )

13

a 29 24 * 20

90 26 25 aa a a L

N

2 1

\ 10 11 12

Fort 14 19 Mohave a

24

Reservation

Figure 4. Note the elevated nitrate levels in old Bullhead City are4.

11 CHEMICAL QUALITY DIAGRAM Shows major chemical constituents in milliequivalents per liter. Number, 500 is total disolved solids in milligrams per liter.

20 100 10 20 /í/i; \' / /.%I Calcium In All Bicarbonate 1 YaaleelnmX500 Sulfate Anions

%/,%// 'G%. %//%/'

WI / %% %/

N LEGEND Groundwater predominantly influenced by

Colorado River h + semis Septic Recharge

Local Geology /r.

ii Combination of the above

Figure 5. The stiff diagram illustrates that there are three influences on groundwater: Colorado River, septic recharge and local geology. SITE INVESTIGATION OF UNDERGROUND STORAGE TANK CONTAMINATION

Kevin D. Hebert (Water Resources Associates, Inc., 2702 North 44th Street, #1018 Phoenix, Arizona 85008)

Abstrae

New regulations concerning the management of underground storage tanks (USTs) have resulted in increased awareness of environmental contamination resulting from leaking USTs. The objective of the typical underground storage tank investigation is to determine if any subsurface contamination has occurred as a result of tank or product line leakage, fuel spills or overfills.Soil contamination at underground storage tank sites is usually discovered during the removal and replacement of USTs. Techniques that can be used to detect the presence of soil contamination adjacent to existing USTs include soil vapor analysis, exploratory boring, and soil and ground water sampling.

The lateral and vertical extent of contamination must be determined at any site which contains detectable quantities of contamination. Two common methods for determining the extent of contamination are over -excavation and borehole drilling and sampling. Boring design and location considerations include number of borings, borehole depth and spacing, and site sub -surface conditions. Differentiation between perched sub -surface water and aquifers is critical. Once an appropriate boring plan has been established, then a sampling and analysis plan must be adopted that meets the needs of the particular investigation.The determination of the extent of contamination at an underground storage tank site is the first step leading to site closure and remediation.

Introduction

There are currently millions of underground storage tanks (USTs) in the United States that contain hazardous constituents such as petroleum products and other chemicals. It is estimated that as much as 25 percent of all USTs may currently be leaking (Evans, 1988). New regulations established by the Environmental Protection Agency (EPA) have resulted in an increased awareness of environmental contamination caused by leaking USTs. The new regulations were developed by the EPA to protect human health and the environment with much of the emphasis placed on the nations ground water resources. The EPA regulations have placed the burden of regulatory authority on each state and local agency.It is the responsibility of each state to establish a program which either meets or is more stringent than the federal regulations.

The focus of the new regulations is to locate all leaking tanks, clean-up existing contaminated tank sites and prevent future leaks or spills. These regulations have had an immediate impact on the tank owner. Because of the new regulations, all USTs installed prior to December 1988 must be retrofitted to contain corrosion protection and spill and overfill prevention devices.In addition, leak detection monitoring must be conducted on each tank periodically. Many tank owners have opted simply for replacing the old tank systems to comply with the new regulations. In any case, many of the existing problems were discovered during the process of replacing or upgrading the UST system.

13 When a UST leak has been discovered, the first step is to report the incident to the proper regulatory authorities, who will request that a site investigation be conducted to evaluate the extent of the problem. In areas where shallow ground water is encountered, it may be necessary to first remove free product that may be encountered prior to determining the extent of contamination.

Site Investigation Methods

Several methods can be utilized to determine the extent of contamination.One of the simplest methods can be employed during the excavation and removal of the tanks. This method involves over excavating the tank pit to remove all or as much of the contamination as possible. This method is very effective in situations where limited contamination has occurred.Soil is monitored during the excavation with a hand held photo -ionization detector (PID) or flame - ionization detector (FID) to detect the presence of potential contamination. Based on the levels indicated by the instrument, contaminated soilis segregated from non-contaminated soil. Contaminated soil can either be placed on plastic sheeting and remediated on -site or be removed from the site and disposed of in a hazardous waste facility.

There are several limitations to over -excavation as a means of determining the extent of contamination. One limitation is that the depth of the excavation is limited to the vertical reach of the excavation equipment on hand. Another limitation is that space needed for stock piling contaminated soils or expanding the size of the tank pit laterally may be limited. If contaminated soil cannot be treated on -site, it is usually very expensive to dispose of off -site.

Another method that can be used to determine the extent of contamination is through the analysis of soil vapor. Volatile compounds from a UST leak in most cases will leave a traceable "signature" in the soil profile that can be mapped using field analytical instruments. The soil vapor survey can be used to delineate the lateral extent of contamination, and is also useful in determining appropriate locations for borings or monitoring wells.

At each soil vapor sample location, a stainless steel probe is driven or pushed into the subsurface to the depth of interest. The probe is then connected to the gas chromatograph in the mobile laboratory by a sampling line. Soil vapor is withdrawn from the ground by a peristaltic pump and is injected into the gas chromatograph where it is then analyzed. A PID is generally used when lower concentrations are encountered and an FID is used when higher concentrations occur (Water Resources Associates, 1989).

The use of soil vapor analysis is limited in that it may be difficult to determine the vertical extent of contamination. Depending on the subsurface conditions encountered, the soil probes generally can only be driven to depths averaging approximately ten to fifteen feet below ground surface.It is also sometimes difficult to extract soil vapor from tight clay bearing formations.

One of the most common and widely accepted methods used to determine the extent of contamination is the drilling and sampling of boreholes.There are several different drilling methods that can be used. The selection of the drilling method is based on the subsurface

14 conditions expected to be encountered at the site.Selection of the proper drilling method is probably the most important part of planning a drilling program. Other important points that need to be addressed during the development of a drilling plan include the number of borings needed to determine the lateral extent, the depth of the borings and available site access.

In most cases, approximately six to ten borings are needed to determine the lateral extent of contamination. Borings are terminated whenever the vertical extent of contamination has been determined or when auger refusal occurs. When two sample intervals show non -detectable concentrations of contamination with use of the field instrument, the boring is discontinued. Site access can be affected by the existence of overhead power lines or subsurface structures such as USTs, product lines and private or public utilities. All underground structures are located using professional locating instruments prior to drilling at each site.

If it is determined during the drilling program that groundwater has been contaminated, then a series of groundwater monitoring wells would need to be installed. In most cases, at least three wells are needed to determine the extent of groundwater contamination and the groundwater flow direction. By measuring the static water level in each monitor well, a plane depicting the surface of groundwater can be constructed by plotting the measurements of at least three wells, and contours can be drawn which show the direction and gradient of flow. This information is useful in determining the potential for lateral migration of contaminated groundwater. Samples can be collected from the monitor wells to determine the extent of free product or dissolved contaminants in the ground water.

Drilling Methods

Hollow -Stem Auger Method. As stated before, the drilling method is selected basedon the conditions expected to be encountered at each site. In situations where finer grained materials, such as silt, sand and clay are expected to be encountered, one of the best drilling methods is with the use of a hollow stem auger drilling rig.

Hollow -stem augering is one of the most effective and cost efficient drilling techniques used to determine the extent of contamination. This drilling method is accomplished by rotating the augers into the soil thereby advancing the boring. Sections of augers are added at the surface to the downhole string in order to advance the boring to the desired depth. Sampling at depth is facilitated by using augers with hollow centers. This system allows sampling devices to be lowered down through the auger string to the bottom of the boring where relatively undisturbed samples can be collected. The sample device is attached directly to a smaller diameter steel rod and is either driven or pushed ahead of the auger bit into the undisturbed soil to collect a sample. When Bedrock or course grained sediments such as gravel and cobble are encountered in the borehole, drilling with the use of a hollow stem auger rig is no longer practical and in mostcases auger refusal will occur. Alternate drilling methods must be used in these situations.

Dual Wall Hammer Method.In unconsolidated course grained deposits, the dual wall hammer drilling method is commonly employed.This method is accomplished by physically driving a dual -wall or triple -wall temporary casing into the subsurface.Compressed air is circulated down into the outer wall of the casing and up through the inner wall carrying the drill

15 cuttings to the surface. The cuttings are discharged at the surface through a flexible hose and cyclone. Down -hole sampling can be conducted to obtain relatively undisturbed samples similar to the sampling techniques utilized with a hollow stem auger rig. However, soil sample recovery is usually poor when attempting to sample from course grain deposits.

One advantage to this method is that monitor wells can be installed inside the temporary casing which eliminates the risk of borehole collapse associated with other methods. This method also limits the vertical migration of contaminants during the drilling process and needs little or no drilling additives, which may potentially effect the quality of groundwater in the vicinity of the boring.

Disadvantages of this method are that it is significantly more expensive than hollow -stem augering and since the percussion hammer is diesel powered, there is a potential for introducing diesel oil to the air compressor and eventually into the formation. (Sale and Rhoades, 1987)

Core Drilling. When drilling and sampling into consolidated bedrock formations, a core rig is typically used. Relatively undisturbed insitu soil samples can be collected using this method without removing the drill string. Samples can be collected at intervals or continuously. In most situations, a temporary stabilization casing must be installed in the upper unconsolidated formation prior to core sampling. Drilling fluids are circulated during the core drilling process to remove the drill cuttings.Core samples are collected using a core barrel sampler which is wirelined into place through the drill string. The inner core barrel sampler locks into place ahead of the drill bit and accepts the representative sample as the drill string is advanced. When the drill string has advanced the proper distance, the core barrel sampler is wirelined to the surface.

Core drilling is a time consuming process that involves extensive preparation and set -up. Due to these considerations, this method can be considerably more costly than other site investigation methods.

Rotary Drilling. Rotary drilling methods are less commonly used for the investigation of UST leaks. However, when the installation of monitor wells is necessary, and the water bearing unit is relatively deep, rotary drilling is a viable method.

Rotary drilling is accomplished by circulating either a drilling fluid or air through the center of the drill string and bit.Drill cuttings are transported to the surface through the annulus between the drilling string and borehole wall. A major disadvantage of this method for the investigation of a UST leak is that down -hole sampling is not easily accomplished.

16 Sample Collection and Preservation

Several steps must be taken during the collection of samples to ensure the quality of each sample and prevent the loss of volatile constituents. When the sample device is retrieved from the subsurface, the sample is sealed and labeled and placed into a cooler containing ice for preservation. Excess soil sample from each interval is monitored at the surface with a hand held field instrument to detect and document the presence of contamination. Samples are generally collected at 5 -foot intervals to develop an adequate profile of subsurface conditions and contamination concentrations. Logs are maintained to document the lithology encountered and the field instrument readings at each boring location. Each sample is listed on a chain -of- custody form, which is a detailed record of the history of each collected sample. When the samplesare transferred from one party to another, the transaction is documented on the chain -of- custody form.

Analytical Test Methods For Soil Samples

The type of analytical method used to quantify the contaminant concentration depends on the type of product that was lost from the leaking UST. For gasoline leaks, the soil sample is usually analyzed by the modified EPA Method 8020 for benzene, toluene, ethylbenzene and xylenes (BTEX) and the EPA Method 8015 for total petroleum hydrocarbons (TPH).Soil samples contaminated with diesel can be analyzed by the EPA Method 8015, modified for diesel or the modified EPA Method 418.1. Both of these analysis methods quantify TPH in the soil sample. To properly quantify waste oil contamination, several analysis methods must be conducted. Samples contaminated with waste oil need to be analyzed for TPH and BTEX by the methods listed above and also for metals and solvents. A typical analysis method for solvents is the EPA method 8010.

Summary

The implementing of current regulations which have required many tank owners to remove or upgrade their UST systems have resulted in the discovery of numerous leaking USTs that were previously undetected. Inventory discrepancies were either discounted or ignored in the past. With an estimated twenty-five percent of all UST systems currently leaking, site investigations at leaking tank sites need to be conducted in order to evaluate the nature and extent of the problem so that remedial measures can be adopted and site clean-up can be accomplished. As previously stated, the most important phase of the site investigation is the delineation of the contamination plume. Several techniques can be utilized to accomplish this task including over -excavation and soil gas analysis. However, the most effective method is through the drilling and sampling of boreholes. At sites where groundwater has been contaminated, monitor wellsare installed to evaluate the extent of groundwater contamination.Once the site investigation has been completed, a site remediation plan can be developed and implemented.

17 REFERENCES CPI'ED

1. Evans, J., 1988, Musts for USTs, A summary of the new regulations for Underground Storage Tank Systems, Environmental Protection Agency (EPA).

2. Water Resources Associates Inc. (WRA), 1989, Soil Vapor Surveys, database

3. Sale, T.C. and S.E. Rhoades, 1987, Installation of Monitoring Wells Using the Dual Wall Hammer Drilling Technique. In: Proceedings of the 8th National Superfund Conference, Washington D.C., Hazardous Materials Control Research Institute.

18 STIE REMEDIATION OF UNDERGROUND STORAGE TANK CONTAMINATION

Scot Journell, P.E., (Water Resources Associates, Inc., 2702 North 44th Street, Suite #101B Phoenix, Arizona 85008)

Abstract

Remedial techniques for sub -surface soil and water contamination are dependent on the lateral and vertical extent of petroleum hydrocarbon contamination and the type of petroleum hydrocarbons which have been released into the sub -surface. Specific remedial technologies are required for diesel fuel and heavy oils compared to the more volatile gasoline compounds.

Available remedial technologies for vadose zone contamination include excavation and treatment; soil vapor extraction and possible vapor burning; bioremediation; and chemical treatment.Remedial technologies for ground -water contamination include water recovery, contaminant volatilization, carbon adsorption, bioremediation and water reinjection. Specialized apparatuses are utilized when petroleum hydrocarbon product floating on the water table surface must be separated from the ground water.

A number of hydrologic considerations must be evaluated prior to any remediation scenario. These considerations include geologic characterization of the sub -surface soil matrix, and aquifer.

Introduction

Remedial techniques for subsurface soil and water contamination are dependent on the lateral and vertical extent of petroleum hydrocarbon contamination. Vadose zone contamination at depths of less than 20 feet is within reach of excavation and treatment methods which include landfill disposal, incineration enhanced vaporization, soil washing or surface bioremediation. When vadose zone contamination extends below depths of 20 feet then insitu methods are typically employed. These methods include soil vapor extraction, bioremediation and chemical treatment. When contamination extends vertically to include ground water then water recovery and treatment, bioremediation or chemical treatment are utilized. Variation in the total lateral extent of contamination primarily affects the unit cost of remediation.For large zones of contamination the higher front end cost of bioremediation or chemical treatment may be absorbed by a higher treated volume to result in reasonable unit cost.In addition to the physical constraints of the vertical and lateral extent of contamination, the selection of remedial techniques is dependent on the chemistry of the released hydrocarbon product.

Petroleum Hydrocarbon Contaminants

The major sources of petroleum hydrocarbon releases are underground storage tanks (USTs) and related piping. Table 1 lists the wide variety of petroleum hydrocarbon products which are stored in USTs.

19 TABLE 1. PETROLEUM PRODUCTS STORED IN UNDERGROUND STORAGE TANKS

Product

Power fuels - civil use

Aviation gasoline and additives Grade 80 Grade 100 Grade 100LL (Low Lead) Jet fuel and additives Jet A (kerosene type) Jet A -1 (kerosene type) Jet B (wide cut or naphtha) Automotive (motor gasoline) and additives Leaded Unleaded Diesel fuel oil and additives, Nos. 1 -D, 2 -D, and 4 -D Gas turbine fuel oils, Nos. 0 -GT, 1 -GT, 2 -GT, 3 -GT, and 4 -GT

Heating and illuminating oils

Fuel oils Nos. 1, 2, 4, 5, and 6 Kerosene

Solvents

Petroleum spirits, types, 2, 3, and 4, and commercial hexane Mineral spirits or Stoddard solvent (Type 1, petroleum spirit) High -flash aromatic naphthas, types I and II VM&P naphthas - moderately volatile hydrocarbon solvents, types I, H, and III Petroleum extender oils, types 101, 102, 103, and 104

(Camp, Dresser, and McKee 1986)

Product Composition

There is a wide variation of chemical properties within the range of hydrocarbon products stored in UST's, however the most commonly stored products are fuels. These fuels are blends of hydrocarbon compounds. The compounds may be described by the number of carbon atoms in the molecule. In gasoline the compounds primarily range from four carbon atoms (04) to twelve carbon atoms (C12). Kerosene ranges from C8 to C15 and diesel fuel ranges from C8 to C21 while fuel oil ranges from C9 to C20. The products with a greater percentage of high carbon compounds are sometimes referred to as being heavier than the products with a lower carbon range.

20 The fractional distillation process used to produce the hydrocarbon products does not completely separate the desired range of compounds from the mailer or lighter compounds. This aspect of the process allows the presence of the C5 through C9 aromatic hydrocarbons in heavier products such as diesel and fuel oil.These aromatic hydrocarbons include benzene, toluene, ethylbenzene and xlenes (BTEX) which are major constituents of gasoline. Table 2 shows typical concentrations of the BTEX compounds in selected products.

TABLE 2

PARAMETER PRODUCT GASOLINE JETA DIESEL FURNACE HEATER OIL OIL

Benzene 0.8 03 0.1 0.3 03 Toluene 12.0 1.4 0.7 1.4 1.6 Ethylbenzene 1.7 0.3 0.2 0.2 0.3

Total Xylenes 7.3 0.9 0.5 0.8 1.0

Total BTEX 21.8 2.9 0.15 2.7 3.2

The reported health effects of the BTEX compounds are greater than those of the heavier C10 through C20 compounds.The regulatory community has therefore focused on these constituent compounds and the presence of these compounds must be addressed in most fuel releases.

Subsurface Affects and Interactions The constituent compounds of the petroleum product have different behaviors in the subsurface environment due to different physical and biological properties of the compounds. Selected properties for a group of constituent compounds are listed in Table 3. In this group of compounds, naphthalene (C10) may be considered representative of the heavier compounds and benzene is representative of the lighter compounds. Although naphthalene is actually an aromatic hydrocarbon the difference in molecular weight compared to benzene allows this comparison.

21 TABLE 3 SELECTED PROPERTIES FOR A SELECTED GROUP OF CONSTITUENT COMPOUNDS

COMPOUND Fate and Transport Water Solubility Vapor Degree of Adsorption at 20°C Pressure Biograd- Coefficient (torr)1 ability (mWL)

Benzene 1.780 75.0 Some 50 Toluene 515 22.0 Some 339 Xylene -M 175 5.0 Some - Xylene-O 162 6.0 Some 255 Xylene -P 198 6.5 Some - Ethylbenzene 152 7.0 Some 565 Naphthalene 31.1 1.0 Readily 976

Adapted from Maynard and Sanders, 1969 and Lyman et al 1982.

1 At 20°C.

As Table 3 shows benzene is approximately 57 times more soluble in water than naphthalene. This results in a preferential partitioning of benzene into subsurface water. For this reason, benzene enters and moves with ground water more readily than the other constituent compounds. This may cause benzene to spread farther and faster than the heavier constituents. The solubility of naphthalene in water is relatively low. This indicates that the C9 and heavier compounds will be less likely to move laterally in ground water.

The vapor pressure of benzene is 75 times greater than that of naphthalene. This will result in a much more rapid volatilization of benzene into subsurface air voids. This difference results in a more rapid reduction of benzene concentrations by diffusion of vapors in the subsurface.

Table 3 shows that benzene is less biodegradable than naphthalene. This reflects the ability of natural processes to more readily attack the longer more complex compounds. Mother important interaction is adsorption. The adsorption coefficient is a measure of the affinity of the compound for subsurface materials. Naphthalene has a higher affinity for subsurface material than benzene.Absorbed contaminants are much more difficult to remove from subsurface materials.

22 The combined effect of the physical properties on the released product over time is that the aromatic fraction of the product will move more readily into the subsurface due to the release and it will move more readily out of the subsurface materials due to remediation. This causes the composition of the released product to move toward the heavier range under natural processes and under remediation. The available remediation methods vary in effectiveness against the physical constraints and chemical properties of individual remediation sites.

Remedial Technologies

Vadose Zone Contaminants

Vadose zone contamination may be treated in situ or at the surface.Excavation and treatment is usually selected in cases where contaminants are within reach of excavating equipment. Rubber tired backhoes with an Extenda -Hoe configuration are able to excavate to depths of 17 feet.

Several limitations affect excavation. The most significant limitation is often imposed by interference of the excavation with the site business operations and site structures. Another significant limitation may be the possible need for shoring due to poor quality soils.

Surface Treatment. Several treatment methods may be applied to the excavated soil. The most rapid return of the site to a useful state may be accomplished through disposing of the material by landfill. In selection of this method the cost of transportation a dumping must be considered along with the cost of potential future liability problems at the landfillThe potential liability problem may be avoided by incineration. However the cost of incineration is so high that it is typically not considered unless the presence of a non -fuel hazardous substance causes the material to be considered a hazardous waste.Surface treatment at the site or a site related facility is another option for the disposition of excavated material. Enhanced volatilization is a surface treatment that works effectively volatile with hydrocarbons. This method ranges in technology from simple mechanical rototilling of the soil pile to enclosed low temperature heating and forced air flow through the soil. Although it is relatively simple, mechanical rototilling is very effective during warm seasons.

Another surface treatment option is soil washing.In this method the soil is slurried with water and surfactant or with a solvent. In the slurried phase the contaminant is separated from the soil particles and moved into the liquid. The liquid is then treated to capture and breakdown the contaminant. This method is effective on heavier, less volatile products such as diesel, heating oil or lubricating oil.The front end cost of constructing the treatment plant may cause this method to be considered only for larger remediations.

Bioremediation is also an effective method of surface treatment. In a surface application the soil is placed in a lined pit and covered with a liner material.The necessary nutrients and microbes are circulated through the soil by a system of pipes installed in the material.

23 In Situ Treatment.In situ methods are used when vadose zone contamination extends more deeply or when site facilities and operations prevent excavation.The most frequently used method for volatile hydrocarbons is vapor extraction. This is an enhanced volatilization method based on airflow through the vadose zone. The air flow is caused by applying a vacuum to a vadose zone well. This causes air to move through the soil mass into the extraction well. The volatile compounds partition into the air stream as it passes through the soil pores. The influx of fresh air through the ground surface and into the subsurface may be enhanced by construction of air injection wells. The effective depth of the method, at the minimum, extends to the full depth of the screened well interval.The radius of influence for extraction wells frequently extends more than 40 feet depending on the length of the perforated interval and the type of soil.

In most jurisdictions the vapor extraction system must be permitted as an emission source and treatment of the vapor stream may be required. Available treatment technologies include thermal destruction, carbon adsorption or catalytic destruction. Thermal units combine proven incinerator technology, moderate initial cost and moderate operating cost with near 100 percent destruction of vapor stream hydrocarbons. Carbon adsorption has a low initial cost however the operating cost for disposal or regeneration of spent carbon is high. This cost increases significantly when the contaminant load in the vapor stream is higher. Catalytic units have a high initial cost and complex systems which may be difficult to permit with local building and safety codes.

Bioremediation may be utilized as an insitu method. This method may be particularly useful for contamination by non -volatile hydrocarbons such as diesel or heating oil. In this application a system of injection and collection wells is used to move nutrients and microbes into and through the soil. Most contractors will perform a bench test on soil collected from the site prior to the remediation. The bench test typically utilizes a soil core of up to 15 feet in length which is collected by drilling. The test which may run for 90 days will verify the selected nutrient mix and group of microbes. In many cases the native soil microbes are effective when the nutrient mixture is applied. After a successful bench test then the field system may be constructed.

Obstructions to the use of bioremedition may be encountered when applying for site permits. The method has not received widespread endorsement by regulators. Objections to the method typically focus on potential impacts to the aquifer due to injection of microbes and nutrient mixtures. Some states may require that an Aquifer Protection Permit is obtained prior to the start of remediation.Such permitting may require extensive, costly site characterization and monitoring.

Chemical treatment is another insitu method that has been used. In this technique a chemical is applied to release the hydrocarbon from the soil and to break the longer carbon chains into lower carbon molecules. This chemical cracking allows remediation of heavier products such as diesel or heating oil.The process is similar to bioremediation in that the chemical is moved through the subsurface by a system of wells. The chemicals used may include surfactants, sulfides or hydrogen peroxide. This process may also require expensive permitting.

24 Ground Water Contaminants

The most commonly applied method of ground water remediation is to utilize recovery wells to pump the water to the surface and treat it with volatilization or carbon adsorption. The withdrawal wells must be located and constructed to maximize the capture of contaminated water. In some cases monitor wells used to delineate the lateral extent of ground water contamination may be converted to withdrawal wells. In other cases the site assessment information gathered from the monitor wells may show that the recovery and treatment effort would be optimized through installation of a separate recovery well or system of wells. These wells may be located downgradient from the contaminated water for the purpose of intercepting the contaminants. In some low transmissivity aquifers it may be possible to locate the wells within the area of contaminated water to reverse the existing gradient by withdrawal from the wells.

The most economical method for treatment of the recovered water is air stripping. In this method the water is cascaded through a column of open packing material as air is forced upward through the water. The volatile contaminants partition from the aqueous phase into the vapor phase. The rate of partitioning is governed by the concentration of contaminants, the ratio of air and water in contact and the length of contact time.

Another treatment method is carbon adsorption. In this application the recovered water is circulated through a bed of carbon. The hydrocarbons are adsorbed onto the carbon material The unit cost of this treatment may be relatively high compared to air striping due to the operating cost of changing, transportating and regenerating or disposing of the exhausted carbon. The rate of carbon use is controlled by the contaminant load in the water. In some cases air stripper discharge is passed through a carbon adsorption bed to remove residual concentrations of less volatile contaminants prior to discharge. Although not commonly applied, another method of treatment for recovered water is bioremediation. In this application the water is circulated through a series of biological reactor beds or vessels.

Treated water generated by a recovery effort may be disposed of by injection or infiltration into the subsurface or transfer to the local wastewater treatment system. Studied placement of infiltration areas for treated water may enable further modification of the site ground water gradient to reduce the number of required recovery wells. The treatment standards for discharge to sanitary sewer may actually be more stringent than applicable standards for re- injection into the subsurface.

Free Product

If free product is present on the ground water surface the remedial effort must begin with recovery of the product. The most common approach is to use a submersible pump to form a cone of depression which captures and holds the product. Another pump is then used to move the product to the surface. The product pump inlet may be placed in a skimmer which floats on the water /product interface or the inlet may be screened with a hydrophobic material that does not allow the water to pass into the pump.

25 Hydrologic Conditions

A number of hydrologic conditions must be evaluated prior to beginning remediation. The quality of the initial site assessment will affect the economy and effectiveness of the remediation. The character of subsurface materials in the vadose zone may exclude the application of some methods. In permeable soils in situ vadose zone methods are very effective because increased air flow, delivery of nutrients and microbes or delivery of chemicals is accomplished with fewer wells. In soils rich in organic matter the stronger adsorption of hydrocarbons may indicate chemical treatment. The presence of thin strata or lenses may reduce the effectiveness of in situ vadose zone methods.

The character of the aquifer will affect the design of recovery and treatment plans.In permeable aquifers with high flow rates the recovery wells must be located to intercept contaminants and treatment systems must be adequate to treat higher volumes of water. Low permeability vadose zone soils and aquifer materials may be well suited to bioremediation due to the reduced potential for nutrients and microbes to impact off site areas. In each case the site operator, consultant and regulators must utilize a thorough site assessment, knowledge of hydrocarbon characteristics and selection of applicable technology to effect site remediation of underground storage tank contamination.

REFERENCES

Camp, Dresser, and McKee, Inc. 1986.Fate and transport of substances leaking from underground storage tanks. Volume 1, Technical Report. Interim report prepared for the U.S. Environmental Protection Agency under Contract No. 68 -01 -6939.

Lyman, WJ., Reehl, W.F., and Rosenbalt, D.H. 1982.Handbook of Chemical Property Estimation Methods. New York: McGraw Hill.

Maynard, J.B., and Sanders, W.N. 1969. Determination of the detailed hydrocarbon composition and potential atmospheric reactivity of full-range motor gasolines. Journal of the Air Pollution Control Association. Vol. 19.

Senn, R.B. and Johnson, M.S., 1985, Interpretation of gas chromatography data as a tool in subsurface hydrocarbon investigations: Proceedings of the Petroleum Hydrocarbons and Organic Chemicals - Prevention, Detection & Restoration.National Water Well Association. 580 p.

26 USE OF BIOTOXICITY TESTS FOR ESTIMATING IMPACT OF STORMWATERS ON AQUATIC LIFE

Frederick A.Amalfi,Elizabeth M.Atkinson,and Julie D.McNaughton (Aquatic Consulting & Testing, Inc., Tempe, Arizona)and Milton R. Sommerfeld (Arizona State University, Tempe, Arizona).

ABSTRACT

A test protocol was evaluated for estimating the acute toxicity of urban stormwater runoff to aquatic life.Potential deleterious effects of storm flows on the aquatic community of small artificial impoundments were examined by application of short-term bioassays. Definitive,static renewal, acute toxicity tests were performed using the fathead minnow, Pimephales promelas, and the crustacean, Daphnia magna. The feasibility study indicated that short -term bioassays may provide an alternative to individual chemical constituent measurements and comparisons to numerical water quality criteria for protection of aquatic life.Biotoxicity tests may identify synergistic interactions to chemicals which individually meet specific water quality criteria but collectively lead to toxicity.

INTRODU(.fION

Background

Urban lakes are found throughout metropolitan areas.They are often designed as stormwater retention structures to meet runoff management requirements. When stormwater runoffenters theseimpoundmentsit transports metallic and organic pollutants originating from automobile oil and wear metals deposited on streets and parking areas (Nance and Harman 1978, Galvin and Moore 1982, Athayde et al. 1983, Fletcher et al. 1983, Milligan et al. 1984, Hoffman et al. 1985, Novotny et al. 1985, Pitt 1985, Amalfi 1988), pesticide and herbicide residues from residential yards and community parks(Cole etal. 1984), and other toxicants improperly disposed on streets and vacant lots.

Conventional physical and chemical analyses are usually conducted to assess the impact of stormwater runoff on aquatic organismsin the receiving stream. Individual constituent concentrations are compared to numerical standards (USEPA 1986) to determine the potential toxicity of the water to aquatic species at different concentrations of the specific constituent. Numerical standards exist for physical characteristics such as temperature and dissolved and suspended solids; inorganic chemicals as heavy metals, ammonia, oxygen, andsulfides; and organic chemicals including chlorinated and aromatic solvents. Although these water quality

27 criteria appear to cover most compounds that could be expected to be present in urban stormwater runoff, comparison of constituent concentrations does not permit evaluation of synergistic or antagonistic effects between the stormwater components.

The USEPA (1985a,1985b) has developed bioassay test procedures designed to assessthe toxicity of wastewater effluents on aquatic organisms in the receiving stream. Sensitive aquatic species are exposed to various concentrations of the discharge water for a fixed time period. Organisms response is measured as growth, reproduction,or mortality. These procedures are advantageous because they: (a) evaluate actual organism response, (b) allow for manipulation of physical variables (time, temperature, pH, etc.), (c) provide a definitive effect concentration, (d) permit use of a variety of test organisms including resident species, (e) eliminate the need for expensive chemical tests, (f) allow assessment of receiving water quality impact on toxic response through use of ambient or synthetic waters, and (g) account for synergistic and antagonistic effects between pollutants.

Objective

A study was conducted to determine the feasibility of using acute biotoxicity screening tests for assessing the toxicity of stormwater runoffon aquaticorganismsin urban lakes. Thefathead minnow, Pimephales promelas, and the water flea, Daphnia magna, were selected as representative test organisms. Fathead minnows show sensitivity to metallic pollutants and dissolved gases such as ammonia and sulfides, while Daphnids are more sensitive to organic contaminants. Should toxicity be observed in stormwater runoff samples, the relative responses of the two species could shed light on the general class of compounds responsible for the detrimental effect.

PROCEDURES

Field Methods

Stormwater runoff samples collected at two sites were evaluated. Grab samples of stagnant stormwater runoff was collected from a large stormwater conveyance structure using pre -cleaned, non -toxic, plastic carboys. This type of water,consisting of highway and commercial property runoff, could eventually be discharged into urban impoundments during a major storm event. A second grab sample was collected from a discharging stormpipe which terminates at a small, recreational urban impoundment. The first -flush sample was collected in containers as described above. This sample was assumed to represent stormwater runoff from a residential area, and a worst -case scenario in which a maximum contaminant load would be present in the initial stormwater discharge.

28 Samples were transferred to insulated chests and held at 4 °C during transport and storage.

Laboratory ñethods

Test procedures were in general accordance with those published by USEPA (1985a) forstatic renewal, acutetoxicityscreensandare summarized in Table 1. Mortality was selected as the effect response, with the LC50 (concentration at which 50 percent of the organisms are affected) acting as the end point of the test.

Samples and dilution water were brought to test temperature (18- 22°C). Each sample was diluted with synthetic soft water for the P. promelas assays and synthetic moderately hard water for the D.magna assays (Table 2) to produce concentrations of 10, 25,and 50 percent stormwater. Undiluted stormwaters served as the 100 percent concentrations and synthetic water acted as the control.A 750 -mL aliquot of each soft water dilution was transferred to individual1 -L glass vessels.A total of ten, randomly -selected fathead minnows (nine -day old) were loaded into each vessel. A 50mL aliquot of each moderately hard stormwater dilution was also added to individual 75 -mL glass jars. Ten, randomly -selected Daphnids (less than 24 -hr old neonates) were placed in each vessel. All test organisms were obtained from laboratory- reared organisms to assure that no exposure to contaminants had occurred for multiple generations.

Stormwater dilutions were analyzedfor temperature, dissolved oxygen, pH, alkalinity, total chlorine,and specific conductance as specified in the test protocols using standard laboratory procedures (APHA 1989). Measurements were conducted to assure that no significant change in basic water chemistry, which might affect organism survival, occurred during theexposure period. Accordingly, because ofrapid oxygen depletion during the initial exposure period and potential for mortality due to oxygen deprivation (<40 percent saturation), all sample vessels were aerated at a rate of 100 bubbles per minute using an oil -less diaphragm pump.

The solution in each test vessel was renewed with freshly -prepared dilutions of the appropriate composition at the end of each 24 -hr period. Organisms and a small portion of the sample were carefully removed from the test vessels prior to sample renewal and then immediately returned to the vessels. The number of dead organisms in each test vessel was determined and recorded at this time. The total exposure period was 96 hours for P. promelas and 48 hours for D. magna.

29 Data Analysis

Mortality data were evaluated by Probit Analysis using a computer - driven statistical package provided by the USEPA Environmental Monitoring and Support Laboratory, Cincinnati, Ohio.

RESULTS

Nomortality occurred intests involvingdilutions of both stormwater sources with Daphnia magna as the test organism. Because of the absence of toxicity, statistical analysis of the test data was not warranted.

Considerable mortality was observed for Pimephales promelas in the various concentrationsof both stormwater sources. Ninety -percent mortality occurred in the 100 -percent stagnant stormwater and 100 -percent mortality occurred in the 25- percent first -flush stormwater. Mortality data and results of the Probit analyses are presented in Tables 3 and 4. The computed LC50 for the stagnant stormwater was 22.3 percent, with a 95- percent confidence interval of 7.0 to 40.5 percent. An LC50 of 12.6 percent was computed for the first -flush stormwater, with a 95- percent confidence interval of 7.5 to 27.0 percent.

DISCUSSION

Biotoxicity tests can be used to assess toxicity of stormwater runoff to aquatic life. The procedure may account for synergistic and antagonistic effects of contaminants which may not be apparent by chemical analysis and comparison to numeric water quality standards. It is possible that stormwater contaminants,which individually meet water quality criteria for aquatic life protection, may interact in the the stormwater discharge or with chemicals in the receiving stream to render a cumulative toxic effect on sensitive species. Conversely, chemical interactions in the stormwater or receiving impoundment may transform the pollutants to non -toxic forms.

Initial data indicate that stormwater runoff contributions of 10 to 40 percent of lake volume may be toxic to early life stages of sensitive aquatic species. Based on the response of P. promelas, metals are a likely cause of the toxicity. Although D. magna exhibited no toxic response to the stormwaters of the screening tests, aeration of the test vessels may have negated toxic effects of volatile organic compounds. The runoff samples collected had observable oil sheens on the surface. The data do indicate that non -volatile organics are not a likely source of toxicity in urban runoff samples. These conclusions are in general agreement with previous priority pollutant analyses conducted on urban stormwater runoffentering several urbanimpoundments inthesame geographic location (Amalfi 1988). Few extractable organic compounds and no volatile organic priority pollutants were detectable in urban runoff

30 collected at five sites during the referenced study. However, metals including cadmium, nickel, copper, chromium, and zinc were found in nearly all samples.

Future feasibility studies should utilize ambient receiving water as the dilution water in the bioassays. The procedure would account for physical and chemical characteristics of the impounded water which may affect the environmental fate, longevity, andbioactivity of the stormwater runoff contaminants.

31 TABLE 1

TEST CONDITIONS FOR ACUTE TOXICITY ANALYSES WITH PINEPHALES PROHELAS AND DAPHNIA MAGNA

P. promelas D. magna

Temperature 20 °C +/- 2 °C 20 °C +/- 2 °C Light quality 50 -100 ft c 50 -100 ft c Photoperiod 8 -16 hr light /24 hr 8 -16 hr light /24 hr Test vessel size 1 L 125 mL Test solution vol. 0.75 L 50 mL Age of organisms 1 -90 days < 24 hours No. organisms /vol 10 max 10 max Feeding not required not required Aeration none unless < 40% satn none unless < 40 satn Dilution water soft synthetic moderately hard synth Test duration 96 hr 48 hr Effect measured mortality mortality

TABLE 2

SYNTHETIC DILUTION WATER SPECIFICATIONS

Final Water Quality

Soft Nod. Hard pH, SU 7.2 -7.6 7.4 -7.8

Hardness, mg/L as CaCO3 40 -48 80 -100

Alkalinity, mg /L as CaCO3 30 -35 60 -70

32 EPA PROBIT ANALYSIS PROGRAM USED FOR CALCULATING EC VALUES Version 1.4

TABLE 3. P. PROMELAS ACUTE TOXICITY SCREEN WITH STAGNANT STORMWATER

Observed Adjusted Predicted Number Number Proportion Proportion Proportion Conc. Exposed Responding Responding Responding Responding

10.0000 10 3 0.3000 0.3000 0.2721 25.0000 10 5 0.5000 0.5000 0.5338 50.0000 10 7 0.7000 0.7000 0.7283 100.0000 10 9 0.9000 0.9000 0.8709

Chi - Square Heterogeneity = 0.201

Mu = 1.349155 Sigma = 0.575753

Parameter Estimate Std. Err. 95% Confidence Limits

Intercept 2.656714 0.935480 (0.823173, 4.490255) Slope 1.736855 0.613504 (0.534388, 2.939322)

TheoreticalSpontaneous Response Rate = 0.0000

Estimated EC Values and Confidence Limits

Lower Upper Point Conc. 95% Confidence Limits

EC 1.00 1.0228 0.0005 4.3816 EC 5.00 2.5240 0.0085 7.6508 EC 10.00 4.0857 0.0398 10.3838 EC 15.00 5.6551 0.1123 12.8414 EC 50.00 22.3437 6.9681 40.5240 EC 85.00 88.2806 6.9681 40.5240 EC 90.00 122.1913 46.7703 1182.6928 EC 95.00 197.7932 81.6863 15010.6406 EC 99.00 488.1235 144.6551 272359.5000

33 EPA PROBIT ANALYSIS PROGRAH USED FOR CALCULATING EC VALUES Version 1.4

TABLE 4. P. PRONELAS ACUTE TOXICITY SCREEN WITH FIRST -FLUSH STORIIWATER

Observed Adjusted Predicted Number Number ProportionProportionProportion Conc. Exposed Responding RespondingRespondingResponding

Control 10 1 0.1000 0.0000 0.1000 10.0000 10 3 0.3000 0.2222 0.2222 25.0000 10 10 0.9900 0.9889 0.9889 50.0000 10 10 1.0000 1.0000 1.0000 100.0000 10 10 1.0000 1.0000 1.0000

Chi - Square Heterogeneity = 0.201

Ilu = 1.099727 Sigma = 0.130407

Parameter Estimate Std. Err. 95% Confidence Limits

Intercept -3.433084 3.616706 (- 10.521751, 3.655736) Slope 7.668274 3.349074 ( 1.104089, 14.232460)

Spontaneous 0.100001 0.094868 ( -0.085939, 0.285942) Response Rate

Estimated EC Values and Confidence Limits

Lower Upper Point Conc. 95% Confidence Limits

EC 1.00 6.2569 0.1179 9.2512 EC 5.00 7.6775 0.4699 10.7310 EC 10.00 8.5624 0.9667 11.8013 EC 15.00 9.2166 1.5527 12.7479 EC 50.00 12.5813 7.5413 26.9519 EC 85.00 17.1744 12.4484 167.6621 EC 90.00 18.4866 13.2713 272.8644 EC 95.00 20.6174 14.4328 567.6545 EC 99.00 25.2984 16.5812 2284.8472

34 REFERENCES

Amalfi, F.A. 1988. Urban lake sediment chemistry: lake design, runoff, and watershed impact. Dissertation. Arizona State University, Tempe. 225 pp.

American Public Health Association. 1989. Standard methods for the examination of water and wastewaters. 17th Edition. n.p.

Athayde, D.N., P.E. Shelly, E.D. Driscoll, and D. Gaboury. 1983. Results of the Nationwide Urban Runoff Program. Water Planning Division, USEPA, Washington, D.C. 3 vols.

Cole, R.H., R.E. Frederick, R.P. Healy, and R.G. Rolan. 1984. Preliminary findings of the priority pollutant monitoring project of the National Urban Runoff Program. J. Water Pollut. Control Fed. 55(7):898-908.

Fletcher, I.J., C.J. Pratt, and G.E.P. Elliott. 1983. An assessment of the importance of roadside gully pots in determining the quality of stormwater runoff. Pages 586 -602 in P.R. Helliwell, ed. Urban storm drainage. John Wiley and Sons, New York.

Galvin, D.V. and R.K. Moore. 1982. Toxicants in urban runoff. Munici- pality of Metropolitan Seattle,Water Quality Division, Seattle, Washington. n.p.

Hoffman, E.J., J.S. Latimer, C.D. Hunt, G.L. Mills, and J.G. Quinn. 1985. Stormwater runoff from highways. Water, Air, andSoil Pollut. 25:349 -355.

Mance, G. and M.M.I. Harman. 1978. The quality of urban stormwater. Pages 603 -616 in P.R. Helliwell, ed. Urban storm drainage.John Wiley and Sons, New York.

Milligam, J.D., I.E. Wallace, and R.P. Betson. 1984. The relationship of urban runoff to land use and groundwater resources. Tennessee Valley Authority, Office of Natural Resources and Economic Development. 37 pp.

Novotny,V., H. Sung, R. Bannerman, and J.Baum. 1985. Estimating nonpoint pollution from small urban watersheds. J. Water Pollut. Control Fed. 57(4):339 -348.

Pitt, R. 1985. Characterizing and controlling urban runoff through street cleaning and sewerage. EPA project summary. EPA /600/52- 85 /038. Water and Engineering Research Laboratory, Cincinnati, Ohio. 7 pp.

35 United States Environmental Protection Agency. 1985a. Methods for measuring the acute toxicity of effluents to freshwater and marine organisms. EPA /600/4- 85/013. Environmental Monitoring and Support Laboratory, Cincinnati, Ohio. 216 pp.

United States Environmental Protection Agency. 1985b.Short -term methods for estimating the chronic toxicity of effluents and receiving waters to freshwater organisms. EPA /600 /4- 85/014. Environmental Monitoring and Support Laboratory, Cincinnati, Ohio. 182 pp.

United States Environmental Protection Agency. 1986. Quality criteria for water 1986. EPA /5 -86 -001. Office of Water Regulations and Standards. Washington, D.C. n.p.

36 LOST PERENNIAL RIPARIAN HABITATS OF THE SOUTHEAST SIERRITAS: STRUCTURAL RELATIONS AND THE 1887 EARTHQUAKE

Jeffrey Zauderer Office of Arid Lands Studies University of Arizona Tucson, Arizona 85719

Introduction

The area of study is about 30 miles south of Tucson, Arizona in the southeastern quadrant of the Sierrita Mountains, mostly within the Twin Buttes 7.5 minute quadrangle.

A previous study (Zauderer, 1989) presented some of the basin characteristics for Batamote and Proctor washes wthin the study area, and the evidences for considering them as lost perennial mesquite bosque habitats in the lower elevations, below 4000 feet. Such evidence includes: a) the morphology of abandoned channels in silty tuffaceous alluvium, b) the creation ofnewer high energy erosive channels resulting from increased lateral inputs from denuded slopes, c) lines of tree stumps on higher terrace surfaces where de- watering of the perched water table killed the established older perennial canopy, d) black /dark brown organic A horizon soils on lower floodplain surfaces extending into Sopori Wash fl000dplain silts, including cienega soil lenses, and e)the underlying geologic control of the wash system that provides the perching mechanism common to other perennial habitats in the periferal Santa Cruz system. A barrier to discharge losses, however, is not present.

When the Santa Cruz began a century of hydraulic readjustment, the Sopori Wash and lateral perched perennial habitats were drained and experienced erosional entrenchment through the former riparian floodplains. This episode of regional hydraulic readjustment seems to presently impingeupon existing perennial and cienega habitats perched above the main trunkof the drainage. Based on the late Tertiary and Quaternary geology of the area, and the hydrogeologic history of the Tucsonbasin, the present epeisode of hydraulic adjustment may be a visible result of a broad, long term incremental processes of the region's structural dynamics.

This presentation examines the relation of underlying structure, structural control, and hydro -ecology in the studyarea to the 1887 earthquake, and draws somearm- waving conclusions about riparian and cienega management.

Figure 1 shows the extent and interpretedpower of the May 3rd,1887 Bavispe earthquake (after Dubois and Smith, 1980).

37 Betancourt (1986) found an interesting observation of the effect of the earthquake on tributary discharge into the Santa Cruz: "From his ranch in the Sierrita Mountains, Hiram Stevens reported that the earthquake more than doubled the flow of nearby streams" (in the Arizona Daily Star, June 2,1888). The rainfall in may of that year was under 2 centimeters. This powerful earthquake (estimated at 7.2 at Tucson, on a modified Mercali Intensity Value scale by Dubois and Smith, 1980) affected spring and stream flow in southern Arizona (Dubois and Smith, 1980). In the area of this study, the compression wave could have affected stream flow by de- watering the confined saturated sediments contained within the high -seismic velocity upper- Tertiary tuffaceous conglomerate. Another mechanism of system de- watering and erosion could have been caused by the disturbance of floodplain depositional - erosional balance at several bottle -neck sites along the stream profile. These bottle -necks are associated with surface lineament expressions, vertical displacement faults, and formation contacts.

Results and Discussion

Figure 2 shows the surface topography of the study area below 4200 feet elevation. Several NW -SE trending lineaments seem to be related to middle -Pleistocene scouring of the underlying tuffaceous conglomerate. The parallel NE -SW trending lineaments relate to erosional surfaces on the tertiary bedrock, and parallel or coincide with vertical displacement faults. Also on figure 2 are lines of section, X -X' and Y -Y' for figure 4.

Figure 3 shows the surface geology for the area in figure 2. The line delineates the extent of holocene floodplain deposits derived from tuffaceous conglomeratic sources. (data from field work, and Cooper, 1960, 1973; Drewes, 1980; Kelly 1977; and Smith,1966).

Figure 4 shows the crossections X -X' and Y -Y' indicated on figure 2. Of interest is the successive nesting of late Tertiary to recent fluviatile deposts. The inner holocene floodplain (2400fps) probably lies directly on top of the 6600 fps layer. This is inferred from the seismic data (Sternberg, 1987), and the field mapping of resistant layers in the upper tuffaceous conglomerate (Tuc) that seem to exert a structural control on the depth of initial balleno (swale and channel) formation. This is indicated by the dashed line in the X -X' section. Further upstream, at about 3700 feet elevation, such resistant layers, (zeolites help form the resistant internal structure; cf Kelly, 1977), form the exposed channel beds. The differential weathering and porosity of this formation prior to the present erosive episode probably served as a perched groundwater reservoir transporting water to streams downslope from recharge areas, such as the broad Batamote system, and areas above 4200 feet elevation in the Lobo Peak area.

38 Figure 5 is a map of the Tertiary and Quaternary units and topography above 4000 feet elevation, and hence is a continuation of figures 2 and 3. Of interest is the passage of Proctor Wash through this area dense with structural features.

From the Lobo Peak area a dashed line encloses an area of Holocene floodplain composed of a black organic A horizon 4 to 6 inches thick, overlying increasingly coarse grey alluvium downward. Four to five feet below the surface another buried soil horizon is encountered. The surface canopy is comprised of mature bosque mesquite and Arizona Oak. On hill slopes are scarce old Alligator bark Juniper at 4500 feet elevation. Following the dashed floodplain line southward it enters a funnel- shaped constriction where the stream crosses a lineament that also happens to be a projection of a mapped fault. In this funnel the active channel cuts at an increased gradient. The surface of the oak -mesquite bosque, however, seems to have formed, prior to entrenchment, a retaining deposit across the upstream opening of the funnel.

The steep slopes on the eastern side of the floodplain, particularly along the roughly north -south trending fault that passes by Lobo Peak, and the lineament that also is a projection of a roughly perpendicular running fault along the contact of the Tc unit, have bare scarps where the soil and vegetation cover (mostly perennial grass) has fallen from under the roots of old established trees.

A possible scenario of action for this area of the upper portion of Proctor Wash is that the energy from the Bavispe earthquake was concentrated along older established seismic surfaces, shaking loose the floodplain dam across the constricted hard bedrock outlet, and creating some surface slumpingon the steeper fault related scarps.

Possible evidence of upstream erosion and silting deposition at the entry into Sopori Wash is found in the area seen in figure 6. The stipled areas along Proctor Wash below 3300 feet are comprised of dark brown /black soils that grade into the old Sopori floodplain. Black organic lenses of cienega -marsh habitats are turbulently overlain by tan silts derived from the Holocene floodplain deposits eroded upstream. Eventually, this area at the confluence of Proctor Wash bosque with the Sopori marsh would be cut down from 5 to 10 feet as a result of the erosion in the de- watered and degrading system.

A summary diagram of structures across lower Proctor Wash in the area of profiles AA' and BB' on figure 6 is presented in figure 7.

A long -term trend of channel confinement is seen to develop from the Middle Pleistocene to the present. This may be related to a long term drying of climate, as well asprocesses concerned

39 with the development of the Tucson Basin hydrogeology (e.g. vide Davidson, 1973). The de- watering and degradation of this once perennial bosque -marsh system could be indicated in time by the line of old stumps of trees shown in figure 7 and labelled as event "3.5 ", where the perched water table dropped faster than the higher trees (bosque mesquites) could extend roots to the phreatic surface. This "3.5" event and the turbulent covering of organic cienega lenses by tan silt could indicate quick processes associated with the 1887 earthquake.

Conclusion

A regional change in riparian environment has been occurring since the 1880's (Cooke and Reeves, 1976), and is impacting the perennial riparian and cienega environments today (Hendrickson and Hinckley, 1984). This process of hydraulic change and habitat loss has been documented by Betancourt (1986) for the lower Santa Cruz River at Tucson, and is firmly associated with the confluence of human impacts that de- watered floodplain storage, and fluctuations in rainfall and drought.

The time of human impacts and rainfall- runoff process fluctuations is also imprinted upon long -term broad basin processes and seismic events. The sensitivity shown by the Santa Cruz system to human impacts suggests that hydro -ecosystems can function as geosystem amplifiers that magnify human perturbations.

Figure 8 shows the location of present and lost perennial riparian and cienega locations in the Santa Cruz system. Hydro - environments from Tucson to about 3700 feet elevation have been lost, and hydraulic readjustment is probably affecting existing hydro -environments at about 4000 feet. This suggests that management of the remaining perennial riparian and cienega habitats should be undertaken on a broad regional inter -connected basis; these habitats are prime areas of recharge to the supporting and connecting hydraulic system that feeds back the impacts of land -use policy and management throughout the hydraulic system connections.

40 REFERENCES CITED

Betancourt, J.L. 1986. Historic Channel Changes Along The Santa Cruz River San Xavier Reach, Southern Arizona, in: San Xavier Archeological Project, Vol. II. Cultural and Environmental Systems, Inc., Tucson.

Cooke, R.; Reeves, R. 1976. Afoyos and Environmental Change in the American South -West. Clarendon Press, Oxford.

Cooper, J.R. 1960. Some geologic features of the Pima Mining District, Pima County, Arizona. USGS Bull. 1112 -c.

Cooper, J.R. 1973. Geologic Map of the Twin Buttes Quadrangle. USGS Misc. Geol. Investigations, Map I -745.

Davidson, E.S. 1973. Geohydrology and Water Resources of the Tucson Basin, Arizona. Geological Survey Water Supply Paper 1939 -E. United States Government PRinting Office, Washington, D.C.

Drewes, H. 1980. Tectonic Map of Southeast Arizona. USGS, Map I -1109.

DuBois, S.; Smith, A.W. 1980. The 1887 Earthquake in San Bernardino Valley, Sonora: historic accounts and intensity patterns in Arizona. Special Paper No.3, Bureau of Geology and Mineral Technology, U of A, Tucson.

Hendrickson, D.A.; Minckley, W.L. 1984. Cienegas- Vanishing Climax Communities of the American Southwest. Desert Plants, 6:175 pp.

Kelly, J.L. 1977. Geology of the Twin Buttes copper deposit, Pima County, Arizona. AIME Transactions, vol. 262:110 -116.

Smith, R. 1966. Geology of the Cerro Colorado Mountains, Pima County, Arizona. Ariz. Geol. Soc. Digest, vol VIII, pp 131 -145.

Sternberg, B. 1987. Report on seismic surveys during August, 1986, for Desertron Sierrita site. LASI -86 -1; Laboratory for Advanced Subsurface Imaging, Dept. Mining and Geol. Engineering, U of A, Tucson.

Zauderer, Jeffrey, 1989. Riparian Habitats of the Southeast Sierrita Mountains: Vanished Perennial Habitats, Hydrology and Water Resources in Arizona and the Southwest, vol 19, 59 -78.

41 I soseisrk4l Me.?e{Areo. Fclt by 1887 E&rTlbtAke

FIGURE 1 42 FIGURE 2

43 TtAjt_ ` +.. % ` /: /+ / /. \ .. ... i { / /4 / / \ ` V ; \ r t rtttn-L 4iwvivn on soilsoQOnó mi iila. Q..itrnarY Ni. ; /, `J¡ \ / \ .4 N ` earlylate Q.oftrnary t2rtcon9lo i ary - mera{ e. N .. N.4 \ f . m:dJltT.+ffaceo.+a -arlr Tcrfiaryconglontt.ro-lt.AA la, Tertiary and. . /b. '.\ ...JN / \ J volc4nitX Cretctceovs tryc txtrvsis S ive S v t s S E. Sie r a. Ge otossj --- r-K- ..._.. - bovnóarfbrown Floodplt;nF SiltsI.na.a.menf ` or OC i o

in o o o h r r M A [

o

_ .,..i O a -a w

d 3

o o vN r M M

FIGURE 4 45 Structure, Lineaments,UPTart PE Ri ary PROCTOR. - ToPograpky WASH Recent Dalph.t,graty.f..., refer( aces4í.1è tista doh, GeologyLsoi oat , atrial cant *Cis _..p fault 0 L:naaa,eat Nolobrown cone and Stn Pleistocene:ComanttDcl+onnalsoni.í/s alluvialloci(loot an ttrracts alluvium,ptaína ira..ally reJJiskJtposi alons ta aui Joe av.11yC.n(oentrate.TvffaceousCon/Comeratac(rnantai ansIsyars Tvffaceovs , nvm,btContour rtJ Saciions si we lcaLe250' Interval C Kan nel andof B afa YIN ofe and Proctor Wank attuvi at Jcafures

LEGEND channelChannelact( ve ~r` _ _ 4toolnsie ;nearIsletolder nextent red of siltTer rC e. '4!---- I 1 MI LE fN.+ Y B loo-too2o-15o15*- to. fo Icvelyrswwsiovtsr : Cltwt).c)rtrenw:l ct.fi, store tA/y:..3;eriscc c1.ww.4 1s, level 3 faresi esfdbl.;sktJ sta6/;s/Iiwswf fwreft I vc BGS derivedof Brownfromfvffaceo inner 3r&velly sc(ts Sorec5 Floe tip(a:vl; s SVmm" of S.E. Sfructurt and Event-5 Ripfi'rian. KGS red 9ravcilly LOIM1 Q/ffrsnehTue "Wit we(( ;cemented Some ce Men í0.0 Ba{l.noi' -forw4fcon 1silts, .ka{conglomerate t o f F. c..,.s I \ 1 l / \ I I // / `I 1 / 10 - = \ \, ¡ 11 RG5 i 4 -t-.s yt BGS ---5 ^ " s '> RS 6 Tu FIGURE 7 1 MajorDrainer, o f+hQ5ant14 Cruz System major ripariancorw111vA:rits, ciendas, sad S.E. SierrifaSystem

` N1,,, I 4 O S 4.. _ a xaíer . t ..4' vgila ....,6e5\., \,iri

40a

Streams Perennin( arrrir, Forme r ow Giant's. Ri pari an F arm

FIGURE 8

49 A GEOGRAPHICALLY -BASED LAND USE SUITABILITY ASSESSMENT AND LAND CAPABILITY CLASSIFICATION Rex Victor O. Cruz and Peter F. Ffolliott School of Renewable Natural Resources University of Arizona Tucson, Arizona 85721

Introduction

Land capability classification generally refers to the description and classification of lands relative to their biophysical features and ability to sustain various kinds of uses. The USDA Soil Conservation Service land capability classification guide is perhaps the most popular system ever developed so far (Klingebiel and Montgomery, 1961; and Brakensiek, et al., 1979). It has been modified and used in other countries including Israel, the Philippines, and Zimbabwe (Hudson, 1981). In spite of its popularity, however, the USDA guide is based only on agronomic land uses and is qualitative in nature. Classification systems developed in recent years are more quantitative in nature as theunderstanding of the relationships among the different factors influencing soil productivity and stability increases. For example, Larson et al. (1988) and Warren et al. (1989) developed classification systems based on estimated measures of productivity, soil resistivity, and soil erosion, respectively. Land use suitability assessment is defined here as the measurement and rating of the impacts of a land use on the productivity and stability of an area.The impacts could be measured in terms of actual volume of production, decline in soil fertility, and the amount of soil erosion.

It is the purpose of this paper to describe a methodology for land use suitability assessment and land capability classification based on estimated soil loss using the modified universal soil loss equation or MUSLE (Williams, 1975), with the aid of a geographic information system (GIS).

The GIS

Soil erosion is influenced by many factors which are geographic in nature, such as topography, soil properties, vegetation, and land use. As such, the use of a GIS would enhance the accuracy of soil erosion estimation. By dividing an area into smaller cells, the significance ofgeographic

51 characteristics which would otherwise be diminished as a result of parameter lumping when the area is treated as one who'e unit is preserved.

Through the years, GIS has been defined in several ways (Burrough, 1986; Berry, 1986; Parker, 1988). It has been defined as a set of tools, a technology, and an automated spatial information system capable of processing spatial or geographically- referenced information. Most GIS are capable of data input, data storage and retrieval, data manipulation and analysis, and data reporting.

Essentially, GIS can be applied to any activity where spatial considerations are important, and where large quantities of data need to be processed and reprocessed over a number of times. It has found many uses in natural resources management, economics and marketing, regional and urban planning, and engineering.

Works by Berry and Sailor (1987), Gilliland and Potter(1987), Vasconcelos (1988), and Warren et al. (1989) are examples of the many uses of different kinds of GIS. In this study, Map Analysis Package (MAP) developed by Tomlin (1986) was used.

Study Area

The study area is located in the Ibulao Watershed, Philippines. It is a 65,000 -ha subwatershed of Magat River Basin which supports vast areas of agricultural lands. Existing land uses in Ibulao includes, forestry, grazing, and agriculture. The climate generally is humid, with an average annual rainfall of 2,200 mm. Soils are mostly clay loam, with topography ranging from flat to very steep and rugged terrain.

Assessment Method

There are four basic components to the methodology described in this paper, namely MUSLE, capability classification, land use suitability assessment, and GIS (Figure 1). Other components, RAINGEN, CREAMS, and IRSX are incidental to MUSLE for the estimation of the runoff factor.

The study area generally was divided into 10 -ha cells. For the entire watershed, different data overlays, such as slope map, soils map, elevation map, and land use map, were prepared using MAP. From the data overlays, the features and parameters needed in the estimation of soil erosion, capability classification, and land use suitability

52 RAINGEN GIS Operations - organize and analyze rainfall data MAP - simulate rainfall - organize and create duration source data base maps - create derived maps (soils, slope, eleva- CREAMS tion, landuse maps) - perform water budget classify the Ibulao analysis watershed into cells - compute for the soil of homogenous soil, moisture slope, and landuse features - estimate soil erosion from each cell IRSX - create output over- - simulate surface runoff lays (surface runoff volume and the peak and soil erosion maps) runoff rate from each evaluate suitability cell of landuse for each cell based on present legal land classifica- tion, LCCG, and soil MUSLE erosion - estimate the soil erosion create suitabililty from each cell (for each maps based on present storm event, annual) legal land classifica- tion, LCCG, and soil erosion - create erodibility map CAPABILITY CLASSIFICATION based on soil erosion - calculate the erosion index of each cell index for each cell create capability map - classify cells into based on soil erodi- capability classes bility map based on soil erosion index IDRISI - refine and organize i output overlays SUITABILITY ASSESSMENT - print out copies of - evaluate the suitability source maps, derived of each landuse based on maps, and output current legal land clas- maps sification, LCCG of the Philippine Bureau of Soils, and soil erosion

Figure 1. Schematic Representation of the Generation and Flow of Information.

53 assessment for each cell were extracted. In turn, the results from these components were passed back to MAP for processing the various output overlays.

MUSLE

The general form of the MUSLE is shown as:

E = 11.8 (Q *q)0.56 K L S C P where E is soil loss (Mg /ha) estimated as the product of runoff factor consisting of surface runoff depth (Q) and peak flow (q), soil erodibility factor (K), topography factor (LS), soil cover factor (C), and conservation practice factor (P).

The factors KLSCP were estimated using the procedures described by Williams and Berndt (1972), Wischmeier and Smith (1978), Dissmeyer and Foster (1980), and David (1985). A detailed description of the parameter estimation is presented by Cruz (1990).

The surface runoff and peak flow for each cell were simulated using IRSX, which is a modification of the infiltration- kinematic routing program (IRS9) developed by the USDA -ARS (Stone and Shirley, 1985). Most of the parameters used by IRSX, such as soil porosity, hydraulic conductivity, depth- discharge coefficient, and soil moisture, also are geographic in nature.

The soil moisture for each cell was estimated by the hydrology component of CREAMS, a field -scale model for chemical, Runoff, and erosion from Agricultural Management aystems model (Knise1,1980). Likewise, most of the soil related parameters used in CREAMS simulation are geographic in nature.

Land Capability Classification Land capability classification is based on soil erosion index (I). For each cell, the erosion index was estimated by: I = [11.8 (Q*g)056 KLS] / T where T is the soil loss tolerance which represents the amount of annual soil erosion that can be sustained by an area without jeopardizing its long term productivity. (The value of T usually ranges between 2.2 and 11.2 t /ha depending upon

54 the locally intrinsic rate of soil formation and soil depth; in this case, T was assumed to be 20 t /ha /year).

The capability class of a cell was identified using the estimated average annual erosion index (Table 1 and Figure 2). The different land use recommendations were determined by solving for the maximum CP value (using the erosion index equation) for a given capability that would yield an annual soil erosion value not greater than the tolerance limit.

Land Use Suitability Assessment Land use suitability in each cell was evaluated on the basis of the estimated annual soil erosion. A land use in a cell was rated suitable if the average annual soil erosion is less than or equal to the tolerance limit. Otherwise, land use was rated unsuitable (Table 2 and Figure 3).

Applications

The land use suitability assessment and land capability classification procedure described could be useful in identifying the land use most suitable to a given area. It also could provide a method of examining the status of existing land uses as far as impacts on soil productivity is concerned. It could be used to identify which existing land uses need to be changed or if they cannot be changed, the tool could help identify what kind of measures need to be taken to mitigate the adverse impacts of such land uses. Finally, the method would be instrumental in determining the different intensities of land uses that would best complement the capability of an area.

Recommendations

An erosion -based land capability classification and land use suitability assessment is only as useful as the soil erosion estimation component. Therefore, improvements in the existing tools for soil erosion estimation or development and use of methods applicable to the area of concern always should be considered. The accuracy of results obtained from the method described in this paper also is largely a function of the accuracy of the different input or source maps. In overlaying

55 Table 1. Erosion -Based Land Capability Classification of Ibulao Watershed.

Capability Erosion Area Maximum Recommended class index (10ha)allowable landuse CP

1 0 -2 286 0.500 unrestricted

2 3 -5 146 0.200 grassland,rice terrace /paddy, agroforestry

3 6 -10 311 0.100 grassland,rice terrace /paddy, limited agro- forestry

4 11 -20 1069 0.050 rice terraces, limited agro- forestry with conservation measures, forestry

5 21 -30 408 0.030 rice terrace, forestry

6 31 -50 2176 0.020 limited rice terrace, forestry

7 > 50 2052 0.010 limited to forestry ,,,,` .,..,

LEGEND ,.'';..,,:,.; class 1 INM class 5 ii i:

class 2 MIND class 6

class 3 class 7 -

class 4 -

Figure 2, Erosion -Based Land CapabilityClassification of Ibulao Watershed.

57 Table 2. Erosion Classes Coverage Under Different Land Uses in Ibulao Watershed. (The values represent the number of 10 -ha cells).

Present Landuse Erosion Class

1 2 3 4 5 6 7 8 TOTAL

Forest

mossy 178 178

closed canopy 264 264

open canopy 2289 2289

Rice padd /terr 1177 320 1497 * Open grass 68 234 62 112*116*103*583*1278

Diverse crop 49 7 2 12* 126*260*251* 707

Nonvegetated 41 16 11* 14* 2* 11* 95

Residential 8 1* 4* 26* 39

Mainstream 45 5 4 2 10 35 101

TOTAL 4119 582 17 75 116 258 375 906 6448

* Rated unsuitable based on the average annual soil erosion loss. LEGEND

suitable - unsuitable

Figure 3. Landuse Suitability Map of Ibulao Watershed Based on Soil Erosion.

59 several maps, format considerations, such as map resolution and projection, should be appropriately defined to keep the joint probability of coincidence the same at all locations.

The success of using geographically -based tools for land use suitability assessment and land capability classification also would depend upon the adequacy of definition and quantification of the different spatial relationships involved. For example, the relationship between neighboring cells as far as surface runoff generated from each cell should be clearly defined and represented to obtain satisfactory prediction or simulation results.

References Cited

Berry, J.K. 1986. Learning computer assisted map analysis. J of Forestry 84(10):39 -43. Berry, J.K., and J.K. Sailor. 1987. Use of geographic information system for storm runoff prediction from small urban watersheds. Environ. Management 11(1):21 -27.

Brakensiek, D.L.; H.B. Osborn; and W.J. Rawls. 1979. Field manual for research in agricultural hydrology. USDA -SEA, Washington D.C. Burrough, P.A. 1986. Principles of geographical systems for land resources assessment. Clarendon Press, Oxford.

Cruz, R.V.O. 1990. Landuse suitability assessment and land capability classification in Ibulao watershed, Philippines. Ph D Dissertation, University of Arizona, Tucson, Arizona. David, W.P. 1985. Erosion and sediment transport. Upland Resource Policy Program. Technical Report Series No. 87 -01. Philippine Institute for Development Studies. Quezon City, Philippines.

Dangermond, J., and C. Killpack. 1988. Mapping for the future. Landscape Architecture. July /August:46 -51. Dissmeyer, G.E., and G.R. Foster. 1984. A guide for predicting sheet and rill erosion on forest land. Technical Publication R8 -TP 6. USDA -FS Southern Region. Atlanta, GA.

60 Foster, G.R., L.J. Lane, J.D. Nowlin, J.M. Laflen, and R.A. Young. 1980. A model to estimate sediment yield from field -sized areas: Development of model. In CREAMS: A field scale model for chemicals, runoff, and erosion from agricultural management systems. Vol 1. Model Documentation, Ch 3. USDA Conser. Res. Report No.26.

Gilliland, M.W. and W. Potter. 1986. A geographic information system to predict non -point source pollution potential. Water Resources Bulletin 23(2):281 -291.

Hudson, N. 1981. Soil conservation. Batsford Academic and Education, Ltd., London.

Klingebiel, A.A., and P.H. Montgomery.1961. Land capability classification. USDA Agricultural Handbook 210.

Knisel, W.G., Ed. 1980. CREAMS: a field -scale model for chemicals, runoff, and erosion from agricultural management systems. USDA Conservation Research Report No. 26. Larson, G.A., G. Roloff, and W.E. Larson. 1988. A new approach to marginal agricultural land classification. J of Soil and Water Conservation. 43:103 -106.

Marble, D.F., and S.E. Amundson. 1988. Microcomputer -based geographic information systems and their role in urban and regional planning. Environmental and Planning B: Planning and Design. 15:305 -324.

Mein, R.G., and C.L. Larson. 1973. Modeling infiltration during a steady rain. Water Resources Res. 9: 384 -394.

Parker, D.H. 1988. The unique qualities of geographic information system: A commentary. Photogrammetric Eng. and Remote Sensing. 54:1547 -1549. Smith, D.D., and W.H. Wischmeier. 1957. Factors affecting sheet and rill erosion. Trans. Amer. Geophys. Union. 38:889 -896.

Stone, J.J.; L.J. Lane; and E.D. Shirley. 1989. Program IRS, model documentation. Personal communication.

Stone, J.J., and E.D. Shirley. 1985. Unpublished model documentation of IRS9. USDA -ARS. Tucson, AZ.

61 Tomlin, D.C. 1986. The IBM personal computer version of the Map Analysis Package. Laboratory for Computer Graphics and Spatial Analysis. Harvard Graduate School of Design, Harvard University.

Van Roessel, J.W. 1986. Guidelines for forestry information processing with particular reference to developing countries. Food and Agricultural Organization- United Nations. Rome. Vasconcelos, M. 1988. Simulation of fire behavior with a geographic information system. Masters Thesis. SRNR, University of Arizona, Tucson, AZ. Warren, S.D., V.E. Diersing, P.J. Thompson, and W.D. Goran. 1989. An erosion -based land classification system for military installations. Environ. Management. 13:251 -257.

Welch, R., and M.M. Remillard. 1988. Remote sensing and geographic information system techniques for aquatic resource evaluation. Photogrammetric Eng. and Remote Sensing. 54:177 -185.

Williams, J.R. 1975. Sediment yield predicted with universal equation using runoff energy factor. In: Present and Prospective Technology for Predicting Sediment and Resources. USDA- ARS -S- 40:244 -252.

Williams, J.R. and H.D. Berndt. 1972. Sediment yield computed with universal equation. Proc. of the Amer. Soc. of Civil Eng. Journal of the Hydraulics Division. HY 12. Wischmeier, W.H. 1976. Use and misuse of the universal soil loss equation. Jo. of Soil and Water Conservation. 31:5 -9.

Wischmeier, W.H.; and D.D. Smith. 1978. Predicting rainfall erosion losses. Agric. Handbook 537. USDA - SEA -ARS.

62 A TAXONOMY OF SMALL WATERSHED RAINFALL - RUNOFF

Richard H. Hawkins Watershed Sciences Program, School of Renewable Natural Resources, University of Arizona, Tucson, Arizona 85721

ABSTRACT

A study of over 11,000 event rainfall and associated direct runoff events from 100 small watersheds was done, in a search for distinct patterns of runoff response and /or association with land type. The results show unexpected variety in the geometry and scale of the rainfall -runoff response. Groupings of similar response type and magnitude were made, and the associations with vegetative cover were tested.Five separate response groups were identified as follows: 1) Inactive, characterized by no recorded responses to any rainstorm in an extended period of record; 2) Complacent, characterized by a very small part of the rainfall (ca 0.1 to 3 percent) being converted to direct runoff, often as a linear response;3) Standard behavior, the expected "textbook" response common to agricultural lands and humid sites, and in which the runoff slope increases with increasing rainfall, and the scale of runoff farexceedsthecomplacentresponse; 4) Violent behavior, in which an abstraction threshold of 2 -6 cm clearly precedes a sudden high response; and 5) Abrupt response in which a very high portion of the rainfall is converted to event runoff without appreciable abstraction, as typified by extensively urbanized drainages. The responses and the group identifications were parameterized by a simple broken -line linear rainfall -runoff equation, and a dichotomous key based on coefficient values is proposed. Only mild associations between response type or coefficient values and the four vegetative covers (Forest, Range, Agriculture, and Urban) were found. The variety of hydrologic behavior onforested watersheds encompassed that of the other three land types.

63 INTRODUCTION A watershed's response to a rain event is an expression of its hydrologic characteristics. These events are major sources of floods and erosion, and in some situations, the sole source of water supply. Though other flow sources (baseflow and snowmelt) maydominate locally, the rainstormand its accompanying runoff are conspicuous manifestations of hydrologic response. They usually form the basis for flood design and environmental impact analysis. Furthermore, the currentinterestin chemicalecology places value on a contributing watershed'sability tostoreand transform (buffer) a rainstorm's chemical load. With this in mind, the identification of regional or land -linked watershed characteristicscould lead to generalizedenvironmental strategies and management applications for ungaged basins or for hydrologic regions. Purpose: The purpose of this work is to 1) demonstrate and document the observed spectrum of hydrologic response in scale and structure, 2) identify the clustering and /or classification of these responses, and 3) test their associations with land type. Data: Data from a large number of rainstorm events on 100 different small watersheds were used. The data sets were taken froma variety of opportunistic sources: theses, agency reports, journal articles, progress reports, data summaries, publications, data files from other research organizations, etc., utilizing considerable personal contact and follow -up. Twenty -two (22) US states and two (2) foreign countries are represented.The data set contains 10,910 events, an average of about 109 events for 100 watersheds. Though a complete tabulation of watershed and data details is too bulky to be given here,copies are available in limited supply upon request to the author. The drainage areas were from 0.30 to 11,200 hectares (0.74 to 27,675 acres), with a mean 394 hectares (974 acres), and a median was 60.9 hectares (150.5 acres). Thus there was a strong positive skew. The event rainfalls varied from 0.025 cm to 25.92 cm (mean 3.00 cm), and runoffs from 0.0003 cmto 23.10 cm (mean 0.6952 cm). Events which had rainfall but no runoff were not included, even though this information was available for some data sets. Data Quality: It should be stressed that these event rainfall (P) and direct runoff (Q) depths were taken as given in the source publications.These in turn were extracted from basicrainfall and streamflowrecords bythe original investigators. The fundamental integrity of the research

64 installations, the rainfall sampling and data reduction, etc., was accepted "as -is" with the data sets. Only when aberrations or errors were obvious or well -known were any data rejected outright. Given the aim to gather the large data set from diverse locations, no other option was realistically possible.

ANALYSIS

Expression: For orderly description and analysis of the rainfall -runoff response patterns, the followingwas used:

Q = bi *P Pa [1.2] where b1 and b2 are coefficients with the constraints of 0<= b1<= b2 < =1.0, and 0 a, and that the two limbs of equation 1 meet at P=a at the value of Q =b1 *a. Also,it should be noted that when b1 =0, and a >0, the equation reduces to Q=b2*(P-a)[for P >a], a form sometimes used in semi -arid areas 1Fogel and Duckstein, 1970).

An even simpler form was also used, i.e.,

Q = b*P [2] with the only constraint being that 0

65 given in Table 1, and a sampling for selected watersheds is given in Table 2. The data was also plotted for all cases, giving a visual impression of the response pattern.

Table 1. Statistical Characteristics of Fitted Coefficients and Goodness -of -Fit

ItemMean StDev CV( %) Skew N

b 0.2379 0.1916 80.53 0.6243 100 r2 0.5292 0.1967 37.16 -0.4812 100

a(cm) 3.7730 3.5566 94.26 1.3636 100 bl 0.1311 0.1443 111.07 1.3546 100 b 0.4336 0.3377 77.80 0.2510 100 0.6521 0.2325 35.65 -0.9458 100

n 109.1 146.7 134.5 3.5116 100

Note: n= number of events per watershed. N= number of watersheds.

Table 2. Fitted coefficients for selected watersheds.

Watershed b a b1 b2 n r2 name and state (cm) (%)

Missouri Gulch,CO 0.0030 0.00 0.0000 0.0030 1442.34 Cabin Creek, ID 0.0046 1.01 0.0013 0.0066 4348.77 W Donald Cr, OR 0.0034 1.11 0.0016 0.0054 4876.51 3Bar D, AZ 0.0594 17.04 0.0356 0.1991 9388.93 Klingerstown, PA 0.0909 1.91 0.0368 0.1820 14448.53 Coweeta 2, NC 0.0936 5.25 0.0276 0.2142 79969.72 Coweeta 8, NC 0.1303 8.92 0.0779 0.2955 20280.34 Coweeta 37, NC 0.3627 4.59 0.2465 0.5807 8980.00 Treynor 1, IA 0.2572 6.17 0.1855 0.9336 32469.95 Badger Wash 2A,CO 0.3169 1.67 0.2183 0.6557 6672.64 Ava 3, MO 0.4840 5.24 0.2732 1.0000 11888.50 Beaver17, AZ 0.6689 4.47 0.0734 1.0000 2296.46 Berea 6, KY 0.5514 4.10 0.2964 0.9838 8479.38 Commerce, FL 0.8991 1.16 0.6743 1.0000 7897.89

Note: The coefficients b1, b2, and b are dimensionless.

The goodness of fit statistics (r2) varied from -1.90% to 97.89% with a mean of 65.21 %. Thus, as an average value, the broken -line model (Equation 1) accounted for about 2/3 of the variance in direct runoff.

66 CLASSIFICATION

General: In most scientific endeavors classification is an early step in development. In biology, for example, classification is a major component on the path to objective description, the recognition of order, and to shedding light on such as origins, evolution, purpose, and processes. Similar classifications can be found in almost every well -developed scientific field, including the social sciences. In hydrology, classification might eventfully lead to similar benefits: perspective, understanding,and the ability to reference behavior on standard previously described examples. Classification and naming gives a common basis for labelling, or an instant identification for a mutually understood more complex identity or idea.

The classification here is done on an empirical or output - based foundation. That is, on the response patterns observed in the data sets,without conscious regard to the more fundamental underlying processes. This coincides with an unstated aim of maintaining minimum data requirements (simple storm and runoff depths). As shown previously in Table 2, these two event descriptors are in relatively high association (average r2 is about 65 %), thus suggesting a successful choice.To dwell deeper into process inference on a watershed basis would require more data (storm and runoff durations, hydrograph peaks, rainfall intensity patterns, etc.). This approach this treats the watershed as a fundamental unit of natural organization. For this study at least, inferences about the underlying on -land processes are not pursued.

Groupings: Drawing from the previously- described variety observations, and fromthe familiaritythatcomeswith experience, the categories of rainfall -runoff response were formed, as outlined in Table 3. Knowledge of the watersheds themselves, the individual characteristics of the data sets, and the necessity for crisp clusters played a role in forming the groups.

Table 3. Categories of Rainfall- Runoff Response (Tentative)

COMPLACENT

1. Defining Concept: The mein attribute is consistently 10 event runoff with respect to rainfall. Runoff ratios in the 0.5 to 2 percent range typify this behavior. 2. Data Behavior: 0 /P4 ca 0.05. The relationship between P and 0 may be either linear or non- linear. There seems to be no or little rainfall threshold. 3. Possible Mechanisms:Either channel or near-channel sources. Variable source areas are possible, but total source is a small part of the watershed area under most experienced conditions. This can be overland flow (from a road, for example), quick flow from selected wet spots, or direct channel interception. 4. Type Examples: Missouri Gulch, Colorado, Cabin Cr.,Idaho, W. Donald Creek, Oregon, 3Bar D, Arizona. 5. Attributes: Mostly flowing streams and forest cover.

67 VIOLENT

1. Defining Concept: Substantial rainfall needed to cause a distinct sudden increase in runoff. A threshold precedes a high fraction response. A "two - phase" system. 2. Data Behavior: A "high" runoff threshold (with respect to the experienced storm depths), with or without a complacent lead-in. High runoff fractions for the rainfallincrements above the threshold. 3. Possible Mechanisms: Shallow porous soils overlying impervious strata, or vertisots sealing with extended event rainfall. Overland flow or quickftows. 4. Type Examples: Beaver Creek #17, Arizona, Berea #6, Kentucky. 5. Attributes: Big storms (compared to threshold) in data set. Complacent examples may behave violently under extreme events.

STANDARD

1. Defining Concept: Traditional response expected between complacent and violent, with indications of effects of watershed wetness and/or storm intensity. P -0 appears to approach a maximum asymptotically given sufficient rainfall and in a distinct curvelinear fashion.04(d0 /dP) =f(P) <1 2. Data Behavior: Fits equations meeting above definition. Initial rainfall threshold is usually absent or small. 3. Possible Mechanisms: Most overland flow situations show this behavior, but also many apparent quick flow and channel contributions. There is a strong suggestion of variable source areas with increasing storm depth. 4. Type Examples: Treynor, Iowa watersheds (USDA,ARS), Badger Wash Colorado (USGS), Coweeta, North Carolina watersheds (USFS), Edwardsville 4 ,Illinois (USDA,ARS) watershed. 5. Attributes: Variety of covers: forest, rangelands, and agricultural. Most bare -soil, rain -fed agricultural watersheds exhibit a standard response. Asymptotically consistent with the Curve Number runoff equation. The most common pattern encountered.

ABRUPT

1. Defining Concept: Near - impervious behavior, with most events having high fractional runoff, P -0 is nearly constant for most events. 2. Data Behavior: 0/P ca 0.7 to 0.95. Threshold is low, absent, or undetectable. P -0 approaches a constant for most events. 3. Possible Mechanisms: Impervious areas and overland flow. 4. Type Examples: Commercial watershed, Miami Florida (USGS) 5. Attributes: Typical of highly urbanized watersheds.

INACTIVE

1. Defining Concept: Inactive.No flow of any sort experienced in period of record, and scant evidence of anything except catastrophic happenings. 2. Data Behavior: All 00. 3. Possible Mechanisms: High infiltration capacities and soil storage,tow rainfall intensities. Snowmeit situations. 4. Type Examples: Anecdotal only: Records of no flow not published for smell watersheds. 5. Attributes: Rounded swates for channels. Forest and/or range cover. Semi -arid, tow intensity situations. When provoked thru extreme events of rainfall and/or watershed wetness,these situations can provoke geomorphic events. No base flows because of inopportune geologic plumbing.

The above concepts can be related to Equation 1, using the equation coefficients a, b1, and b2 to express the nature of the hydrologic responses groupings. For example, a low values of b,b1, and b2 would be consistent with the "Complacent" category. Low or absent values of "a" combined with a high value of b would be consistent with "Abrupt" behavior. High values of5a"with a major change from b1 to b2 would support the "Violent" category. Roughly, then, the following may be seen as the relative coefficient attributes of the runoff response groups already described:

68 Complacent:low b, low a, low b and low b

Violent : medium to high b, high a, and -high to very high b2 Abrupt high b, low a, and very high b2 Standard medium values of all coefficients. Inactive b1 =0, a exceeds highest rainfall, b2 undefined. Note that the coefficient b1 plays little role, except in describing the change of runoff at the threshold for the Violent case. From this approach, the classifications have been assigned trial values of coefficients.As before, these are subjectively defined, and draw from the knowledge of the watersheds and the data's observed tendencies to cluster into reasonable groups. This information fits easily into a dichotomous key, given below in Table 4.

Table 4. Proposed Dichotomous Key for the Classification of Watershed Rainfall- Runoff Response Groups

Definitions: 1. Q =b *P 2. Q =b1 *P Pa

where 0

1. b =0 INACTIVE category 1. Not as above, b >0 2. b<0.06 COMPLACENT category 2. Not as above, b <0.06 3. a <= 1.25 cm 4. b2 = >0.8 ABRUPT category 4. Not as above, b2 <0.8 STANDARD category 3. Not as above, a >1.25 cm 5. a >2 cm 6. (b-b1) =>0.6 VIOLENT category 6.Notas above, (b2- b1) <0.6 STANDARD category 5. Not as above, a <2cm STANDARD category

Note that therearethreeroutesto getting tothe "Standard"category. An earlier version of this Table (Hawkins, 1989) broke the major categories down further into subsets of "low" and "high ". For simplicity, these are not given here.

Using these criteria (based on a, b, b1, and b2) the entire 100 watersheds were placed into the categories as given in Appendix III. The frequency count of the classes in the data set are as follows: Inactive, none; Complacent, 25; Standard, 57; Violent, 17; Abrupt, 1.Note that most of the most of the

69 watersheds (57 %) fell into the "Standard" category, and there were no representatives of the "Inactive" category in the sample.

ASSOCIATION

There exists a widely held notion that hydrologic behaviors are closely linked to surface vegetation. This would justifiably proceed from a philosophy of a grand scale cause- and- effect ecology, whereby specific soils are formed from specific geologic and climatic sources, and vegetation exists in response to these same items. Since hydrology is an expression of these same natural inputs, it then should be associated with the vegetation. Furthermore, intuitive argumentsare often made. For example, the observed processes of ideal forests such as canopy and litter interception, soil biologic activity, and the condensation of fog, are often extolled, and by extension, their moderating effects on hydrology stressed. These are contrasted to other land types - such as rangelands, agricultural fields, and urban lands - with accompanying extension to their hydrologies.The work here will compare the land "types" with the response hydrology already described.

Land Types: The basic data sources almost always included some description of the watershed lands.In fact, in several cases, the data were drawn from reports in which the influence of land was a major study objective. However, there is no standard or uniform protocol for describing land use and condition: the land use /type isqualitative rather than quantitative,and uses adjectives rather than classes or numbers. Thus, only broad categories can be made: the lands wereclassed as either "Forest ", "Range ", "Urban ", or Agricultural ". Mixed types were classified according to the major cover /use component, and a sub -category allowed further descriptivedetail. The descriptivejudgementsorthe adjectives of the original source author were used whenever possible, and dominated the choices. The term "Forest"included a wide variety of covers: hardwoods in the midwest, pinyon -juniper in the southwest, "...dry broad sclerophyll open forests..." in Australia, and old growth conifers in central Idaho. "Agriculture" generally was assigned to lands known to be under active cultivation in the traditional cropping sense, but also included some pasture lands. "Range" was mainly an arid land default category, as is the range (or grazing) land use, and included near -bare lands in western Colorado and Wyoming, mixed grassland- forest lands in eastern Oregon, and desert shrub lands in Arizona. Clearly, the lack of resolution here is a major problem.

70 The associations are made quite simply: by statistical comparison of thelandtypeandthe previously- derived response categories and /or coefficients. Table 4 following shows the array of coefficients for the land types.

Table 4. Means and standard deviations of Fitted Coefficients for Land Classes

Category b a(cm) b1 b2 r2($) N

MEANS Forest 0.2114 4.22 0.0966 0.3951 68.17 54 Range 0.2421 2.19 0.1226 0.4223 59.87 28 Agriculture0.2742 5.32 0.1923 0.5812 56.27 13 Urban 0.4052 2.20 0.2965 0.5283 86.55 5

All(means) 0.2379 3.77 0.1311 0.4336 65.21 100

STANDARD DEVIATIONS Forest 0.1941 3.64 0.1135 0.3570 21.87 54 Range 0.1461 3.19 0.1036 0.2636 25.05 28 Agriculture0.1772 3.05 0.1776 0.3326 19.80 13 Urban 0.2939 1.71 0.2551 0.3807 13.91 5

Comparison with at"Tests: The abovefindings were analyzed with series of"t"tests. Considering just the coefficient "b" showed no significant differences between the hydrology of the land classes, in spite of the apparent trend in the meansfrom Forest to Urban types. The highest associated probabilities were about 84 %, between Forest and both Urban and Agriculture.

Differences inrunoff response betweenland typesas indicated by the coefficients "a ","b1, and "bare spotty. Probabilities in excess of 90% were for thefollowingcases:

For "a" : Between Forest and Range( >99.5 %) Forest and Urban(96 %) Range and Agric( >99.5 %) Agric and Urban(98 %)

For "b1" : Between Forest and Agric(92 %)

For "b2" : Between Forest and Urban(94 %) Range and Urban(91 %) Although there was no pair of land types which displayed profound differences in all three coefficients, there were significant difference between the coefficients of some land classes, when taken as a vector. The "t" tests were combined using the Bonferroni inequality, as discussed previously. The

71 results are given in Table 5.

Table 5. Probability of "t" (in %) for Coefficient Vector Land Type Classifications

Forest Range Agric Urban

Forest 98.5 76 88 Range 98.5 73 Agriculture - - -- 94 Urban

These suggest that there are significant differences in the mean coefficient vectors between Forest and Range, and between Range and Agriculture. The difference between Urban and Agriculture is close to being significant, and the conservative nature of the Bonferroni inequality should be kept in mind when considering this comparison. (See Mendenhall et al,1981). Furthermore,it should be stressed that the differences implied are in the means, of the data, and not in all points. There is enormous overlap for individual group members. That is to say, although they are differences on the average, a high fraction of forested watersheds act (empirically, tobe sure) like range and agricultural watersheds, and vice versa.

Hydrologic Domains: Additional insight to the behavior of the land types and their hydrologies is given in Figure 1. Here the difference in their runoff slopes (b2 -b1) is plotted against the threshold coefficient "a" with the land type identified. Note the broad spread of data for the forested situations, encompassing nearly all the domain of the other three land types. The "forest" description thus says very little about the associated hydrology: it is not a distinctive association.The only apparent uniqueness isa shell of watershed experience surrounding the other three land types. Urban watersheds, on the other hand, show an tightly clustered behavior group.

SUMMARY /CONCLUSIONS Diversity: There is a large diversity in the rainfall - runoff behavior of small watersheds.The differences are both in scale(i.e., the size of the coefficients) and in the structure of the response. Much of this is unanticipated and /or unappreciated.

72 Figure 1. Plot of (b2 -b) vs threshold coefficient "a ", with the land types identified, and the Complacent and Abrupt watersheds omitted. Note that the "FOrest" type encompasses almost all experience in the other types.

Classification: Based onthe observed properties, a convention for orderly description of watershed eventresponse has been worked out. Watershed response is placed into five groups: Inactive, Complacent, Standard, Abrupt, and Violent. Coefficient arrays for group membership have been provided.

Association: There is substantial overlap in individual watershed hydrologic performance between the land types. However, the mean values of coefficients and membership tables suggest strongest hydrologic contrasts betweenrange and forest lands, range and agricultural lands, and urban and agriculture lands. All other comparisons are inconclusive. Forested watersheds cover all hydrologic categories (except Abrupt), while range and agriculture covers tend to be of Standard response. There were no agricultural watersheds

73 with Complacent response. The behavior domain of forested watersheds included those of range, urban and agricultural watersheds.

ACKNOWLEDGEMENTS Much of this work was supported by the US Environmental Protection Agency, via the Distinguished Visiting Scientist Program at the Corvallis Environmental Research Laboratory, Corvallis, Oregon. However, this paper has not undergone EPA review. This work was also supported by both the Utah and the Arizona Agricultural Experiment Stations. I thank the many whosupplied mewithdatathat madethesecomparisons possible.

REFERENCES

FOGEL, M.M., and L. Duckstein. 1971. Predictionof Convective Storm Runoffin Semiarid Regions. IASH- UNESCO Symposium on the results of research on representative and experimental basins, Wellington (NZ), December 1979, 465 -478.

HAWKINS, R.H.1989. Variety in small watershed response: what's so special about forested watersheds? American Geophysical Union Chapman Conference on Hydrogeochemical Responses of Forested Watersheds, Bar Harbor, Maine, Sept 18- 21. (Poster)

MENDENHALL, W., R.L. Scheaffer, and D.D. Wackerly. 1981. Mathematical statistics with applications, second edition. Duxbury Press, Boston, Mass.

74 EVALUATING THE ROLE D)F FLOODING IN A SOUTHWESTERN RIPARIAN SYSTEM

by

Brian Richter. Preserve Manager Hassayampa River Preserve The Nature Conservancy P.O. Box 1162 Wickenburg. Arizona 85358 and Dr. Duncan T. Patten and Julie C. Stromberg Center for Environmental Studies Arizona State University

Abstract

Although riparian system researchers intuitively understand the general role of flooding in these plant communities, very little quantitative analysis or physical modelling of these flooding effects has been undertaken. This paper describes a methodology for analyzing flood influences by utilizing vegetation monitoring along river transects and a sophisticated flood hydraulics computer model (HEC 2). The project is addressing important questions such as "What magnitude of foods will alter the physical structure and species composition of the plant community? Are major floods essential in creating open floodplain areas wherein regeneration of riparian plants can take place? How does flood timing during the growing season affect the germination of seeds and survival of seedlings ?"

The flood hydraulics study described herein provides an analysis method that is readily transferrable to other riparian systems, and anticipated results may offer some quantificatton ct flooding characteristics which translate to any system composed of similar plant species. For instance. if mortality threshccds of such physical forces as flow velocity. depth. tractive shear stress, and stream power can be identified for selected riparian species, such information may be quite valuable to those engaged in restoration of disturbed systems. in specifying reservoir releases needed to maintain riparian vegetation downstream of dams, and in instream flow protection efforts seeking to protect essential environmental processes which sustain natural riparian systems. (Key words: floods, riparian, hydraulic modeling)

75 Introduction

During the past decade. land managers in the western U.S. have witnessed a rapidly building momentum of concern focused on a tiny fraction of the ecosystems they manage: the riparian zone. Largely ill- defined and misunderstood prior to the 1970's. riparian systems are now attracting research attention in great disproportion to the overall land surface they occupy: in arid Southwestern states such as Arizona these riparian areas comprise Less than 0.1% of the landscape. Much of the drive behind this focused research is in response to their present endangerment. In most of the West. more than 90% of this community type has been destroyed or severely degraded in the past century. The Nature Conservancy (TNC). whose mission is focused on the protection of endangered species. communities, and ecosystems, has in recent years greatly accelerated their efforts to acquire and protect riparian lands held in private ownership. The Arizona Nature Conservancy currently manages 6 riparian preserves: on the Hassayampa River near Wickenburg; Aravaipa Creek below Klondyke: Patagonia Creek near Patagonia: the Bass. Hot Springs. and Redfield Creeks (Muleshoe Ranch Preserve) near Willcox: O'Donnell Creek (Canelo Hills Cienega Preserve) near Canelo; and a tributary to the San Pedro River (Bingham Cienega Preserve) near San Manuel. Research at Hassayampa River Preserve

Since the acquisition of a 5 -mile perennial stretch of the Hassayampa River below Wickenburg in December of 1986. a number of riparian research projects have been formulated and are now underway at the preserve. The overall unifying objective of these research efforts is to develop a more thorough understanding of environmental influences acting in the regeneration and sustenance of this globally -rare Fremont cottonwood -Goodding willow forest community (Populus fremontii- Salix gooddingii association). These inter -related research efforta are directed at the development of a conceptual ecological model of the riparian system, and research is targeted at defining specific linkages in the directional flows of energy and matter through the system. The study of flood hydraulics and flood timing described here is an example of such an investigation. Floods in Riparian Systems

As our consortium of researchers working at Hassayampa began to formulate a rough framework of a conceptual ecological model. we identified some substantial gaps in our understanding of how flooding "drives" various processes in the system. What magnitude of flood will significantly alter the physical structure and species composition of the plant community (by removing or damaging seedlings. saplings. shrubs or trees)? is

76 there a flood threshold (such as a 10 -year flood) which substantially removes trees in the seedling and sapling stages. thereby resetting the regeneration clock?What flood magnitudes benefit the creation and abundance of habitat critical to continued recruitment of these relatively short -lived riparian species? How does flood timing during the growing season affect the germination of seeds and survival of seedlings? Although riparian researchers intuitively know that flooding plays a significant role in the evolution cf riparian plant communities and in restructuring animal habitat opportunities (Reichenbacher 1984), a review of the literature revealed very little in the way of quantifying or modelling the physical influences of flooding in riparian systems. There is a plethora of general statements about the role of flooding. however. as exemplified by these:

As is widely recognized. hydroperiod is the key external or forcing function that determines (riparian) vegetative composition and productivity. What is perhaps not so well understood is that the intensity of flooding is as important as the frequency. Flooding can both enhance and stress a riparian ecosystem, depending on frequency, timing, and intensity." (Odum 1578) "Flow regulations may lead to substantial decreases in discharge and reduces flooding of floodplains. Aggradaticn of floodplains can. therefore, not occur. which is the trigger mechanism for shifting channels. Shifting floodplain channels are considered prerequisite for regenerating of certain riparian species. Flow regulations may also decrease the soil moisture of floodplains and thus aid in destroying the riparian plant communities. (DeBano and Heede 1987) One investigation of the role of flooding in western riparian zones was conducted by a team of researchers from the University of New Mexico led by Dr. Loren Potter. under contract with the National Park Service to study the potential impacts cf a proposed dam on the Yampa River upstream of Dinosaur National Monument. Contrasting the plant community characteristics they found on the dam -regulated Green River with those of the free - flowing Yampa, Potter's group summarized some important conclusions about the influences of natural flooding regimes on the riparian vegetation (Potter et al 1983):

"Scouring can affect plants in several ways. The shear stress exerted by moving water on stems may exceed their elastic limits, causing breakage. If the root system of the plant is poorly developed or is in loose substrate. the entire plant may be pulled out. This may be aided by trie movement of the substrate by the water, particularly if the substrate is sand. Finally, the particulate matter carried by the water can abrade aboveground plant tissues.

77 Abrasion is probably greatest at the plant base from larger particles moved along the bed. but not lifted into the current. "Most plants found in the floodzone exhibited character- istics which enabled them to resist the effects of scouring. Since seeds and seedlings would be highly susceptible to removal. it is not surprising that the floodzone plants were almost exclusively perennials capable of vegetative reproduction. Most of these exhibited annual aboveground parts which could be scoured away each year and perennial below - ground tissues. either roots or rhizomes.

"Willow and tamarisk stems are capable of surviving the direct effects of scouring. The frequent occurrence of willow suggests that willow is more resistant. Young stems of these species are flexible, allowing them to resist breakage. The absence of stems much exceeding 1 cm in diameter in the floodzone indicates an age limit to this resistance. Both species are capable of sprouting from roots. "Young cottonwoods were limited to the upper part of the floodzone and the quieter water of side channels. indicating less resistance to scouring than either willow or tamarisk. "...If the peak flow is higher than normal, seedlings may become established above the floodline and escape scouring if floods in the following year are not excessively high.- Although such literature references are instructive (in a Qualitative sense) for understanding general hydrologic and hydraulic processes active in floodplain areas. there is a near complete absence of quantitative data to document these effects. particularly in a form which could possibly translate or be extrapolated to other river systems. The river hydraulics study described herein is an attempt to gain some new insight and definition into the physical effects of floods of various magnitudes. Study Methodology The river hydraulics study now underway at Hassayampa utilizes a computerized flood simulation model known as 'HEC -2." When using the HEC -2 model. the user specifies the peak magniude of the flood to be modelled and also provides input data describing the physical characteristics of the floodplain reach through which the flood is to be simulated. The model then computes various energy relationships to create instantaneous "snapshots" of the flood at user -input floodplain "cross - sections." by providing output information such as flow depth and velocity.

The HEC -2 model. developed by the U.S. Army Corps of

78 Engineers, is most frequently applied in urban floodplain studies designed to evaluate the extent of inundation resulting from a flood of a targeted "return interval' (such as a 100 -year eventi. The HEC -2 thereby provides the basis for most floodplain management planning and for assessing federal flood insurance rates. The HEC -2 model is now available in PC- compatible software.

Rather than using the model to anticipate the impacts of future floods. the model is used in this study to recreate actual flood events alone a 3 -mile stretch of the Hassayampa River within The Nature Conservancy's preserve, in order to assess the impact of the flood on riparian vegetation. Riparian vegetation characteristics are being concurrently measured in 153 monitoring plots situated along 15 river cross -sections. Specific vegetative parameters being monitored are listed in Table I. After a significant flood event. the HEC -2 model will be used to recreate hydraulic conditions acting on each of the vegetation plots.

Four hydraulic parameters are presently being investigated for their abilities to explain vegetational changes following significant flood events. Flow velocity and depth at the location of each vegetation plot are being considered along with "tractive shear stress" and "stream power."

Tractive shear stress is calculated as: TSS = mDS where TSS is tractive shear stress in pounds per square foot; m is the specific weight of water in pounds per cubic foot: D is depth of water over the plot in feet; and S is the slope of the energy grade line in feet per feet.

Stream power is calculated as: SP = (TSS)V where SP is stream power in pounds per foot -second; TSS is tractive shear stress as above; and V is velocity over the plot in feet -per- second.

It is anticipated that mortality thresholds may be identified for particular species of riparian plants in the seedling, sapling, tree or shrub phases. This analysis will be very useful in understanding the regenerative processes active on the floodplain, hopefully leading to better understanding of the forest community's structural and species diversity.

Recommendations for Other Users

Some recommendations pertaining to needed equipment, expertise, and techniques may be of interest to other researchers wishing to apply this methodology to other riparian systems. PC -- compatible software is available from a number of distributors.

79 The model should, however, be run by an individual trained in its use, as the estimation of values for numerous input variables will require some "professional judgement." Training in the use of HEC -2 is now available from a number of agencies and universities. The U.S. Army Corps of Engineers' Hydrologic Engineering Center (916- 551 -1748) can provide listings of software suppliers and training courses. An accurate measurement of the peak flood discharge is essential. Our Hassayampa study utilizes an automated (continuous record) streamgage located within the study reach. In lieu of streamgage records, the peak discharge can be determined from indirect survey methods such as those 'described in Rantz (1982). The HEC -2 model relies heavily upon a user -input phys_cai description of the river's floodplain. as defined by a sequence of floodplain cross- sections. To ensure the accuracy of the cross -section data needed for thisapplication. these cross - sections were surveyed (using standard two -person level -and -rod techniques) from one edge of the floodplain to the opposite edge, along a line running perpendicular to the direction of streamflow. Elevation readings are taken to define topographical variations across the floodplain. using up to 100 data points in the model. In addition to the elevation data. a key descriptor of the floodplain cross- section is the" roughness coefficient' (also known as the "Manning "s n- value'). This coefficient. representing the frictional resistance to water flow resulting from vegetative obstruction and substrate conditions, can be used to describe roughness variations for up to 20 different sub- sections within each floodplain cross -section. A first approximation of these roughness coefficients is made from the field observations, but can then be calibrated for actual flood events by field surveying post -flood high water marks and adjusting n- values to yield a computer -simulated match for the high water elevation at each cross -section. This is greatly facilitated by establishing permanent "benchmark monuments" at one end of each floodplain cross- section during initial field surveys. At Hassayampa we are also attempting }:c relate these n- values to specific vegetation characteristics such as sapling and /or tree density. as measured in thevegetation sampling plots, such that growth or mortality changes will be continually reflected in the model simulations. The cross - section topography may also need to be re- surveyed to reflect changes following significant flooding. The vegetation monitoring plots are located along each of the river cross -sections. Vegetative parameters are measured using square wooden plot frames or a measuring tape grid for larger plots.

80 Some final guidelines can be made pertaining to selection of an appropriate river reach for study. The river stretch encompassed by this study on the Hassayampa offers optimal field conditions for such a study, owing to a relatively narrow (600 to 1000 feet wide), confined river canyon and the substantial magnitudes of flash -flooding events (see Table II) generated within the 750 - square mile drainage basin. Flow velocities exceeding 20 feet -per- second have been estimated for the 100 -year event, although base flow conditions average only 2 -8 cubic feet - per- second (cfs). Other researchers would be prudent to select a study reach within which some evidence of flooding impacts can be anticipated during relatively frequent (i.e. 2 to 5 year) flood events, so that results can be obtained within the expected lifetime of the study.

Summary

The development of a well -calibrated flood hydraulics model (HEC -2) for this study reach along the Hassayampa River. along with the availability of extensive vegetation sampling, promises to reveal new insights into the role of flooding in this Southwestern riparian system.

The flood hydraulics model described herein also provides an analysis method that is readily transferrable (although highly labor intensive) to other riparian systems, and anticipated results may offer some quantification of flooding characteristics which translate to any system composed of similar plant species. For instance, if mortality thresholds of such physical forces as velocity. depth, tractive shear stress, and stream power can be identified for selected riparian species, such information may be quite valuable to those engaged in restoration of disturbed systems, in minimizing adverse impacts from controlled (dam- regulated) hydrologic regimes, and in instream flow protection efforts seeking to protect essential environmental processes which sustain natural riparian systems.

Although we are just now beginning to "get our feet wet" in our research efforts at Hassayampa, we stand poised and ready for a few good tree - smashing floods that might teach us a thing or two.

References

DeBano, Leonard F. and Burchard H. Heede 1987. Enhancement of riparian ecosystems with channel structures. Water Resources Bulletin 23(3):463 -470.

Odum, Eugene P. 1978. Ecological importance of the riparian zone. Pages 2 -4 in R. Roy Johnson and J. Frank McCormick. editors. Proceedings of the Symposium on Strategies for Protection and Management of Floodplain Wetlands and Other Riparian Ecosystems.

81 Potter, Loren D., N. Timothy Fischer, Mollie S. Toll, and Anne C. Cully. 1983. Vegetation Along Green and Yampa Rivers and Response to Fluctuating Water Levels, Dinosaur National Monument: Final Report. Biology Dept.. University of New Mexico. Rantz, S.E. and others 1982. Measurement and Computation of Streamflow: Volume 1. Measurement of Stage and Discharge. U.S. Geological Survey Water -Supply Paper 2175. Reichenbacher. F.W. 1984. Ecology and evolution of Southwestern riparian plant communities. Desert Planta, Vol. 6:15 -22.

82 TABLE I. Vegetation parameters measured in study plots

2 x 2 decimeter subplots: seedling density - woody species seedling survival seedling height herbaceous cover( %) tree canopy cover ( %) sediment deposition

1 x 1 meter plots: density of tree saplings and shrubs by height class survival of saplings and shrub species herbaceous cover ( %)

2 x 10 meter plots: density of trees diameter of trees age of trees

83 TABLE II. Flood Frequencies for the Hassayampa River Preserve

Return Interval Peak Discharge Estimate

2-year 2.550 cfs 5-year 8,090 cfs 10-year 14,600 cfs 25-year 27.100 cfs 50-year 40,300 cfs 100-year 57,300 cfs

84 QUANTIFICATION OF EVAPORATION AND SEEPAGE LOSSES WITH A FLOATING EVAPORATION PAN: LEE VALLEY RESERVOIR, ARIZONA1/

Don W. Young, Gerald Colmer, and Scott Goodwin2'

ABSTRACT

During the summer of 1989, a water balance study was conducted at Lee Valley Reservoir, located approximately 19 miles southwest of the town of Eagar in Apache County, Arizona. The objectives of this study were to quantify evaporation and seepage losses from the lake and substantiate the use of a land -based evaporation pan to estimate lake evaporation.

Lake level, inflow, controlled releases, precipitation and evaporation were measured on a twice weekly basis for six months from May 1 to October 31. Evaporation was measured in a Class A evaporation pan designed to float in the reservoir. Evaporation was also measured at a Class A land pan near the town of Eagar. A 1.0 inch difference in the estimated rate and the measured rate for a 147 -day period of common record represents a 3.6% error between the land - based pan and the floating pan.

Total losses from the lake over the six -month period were 224 acre -feet. Of this loss controlled releases accounted for 8.2 acre -feet, and evaporation was measured at 116 acre -feet. The remaining loss of 100 acre -feet is due to seepage, much of which can be seen as seeps rising within 800 feet downstream from the dam. Using average data from past years, an annual water balance for the lake was also calculated.

Key Words: Evaporation, Floating evaporation pan, Lake seepage, Water balance

INTRODUCTION

This project was undertaken as part of efforts by the Arizona Game and Fish Department (AGAF) to sever and transfer water rights from irrigation to wildlife and recreation uses on the Apache -Sitgreaves National Forest near Springerville, Arizona. In 1989, a state court administrating local water uses approved a severance and transfer to the Lee Valley Reservoir but the court left open the quantity involved and the ultimate use of the water.Further hydrologic studies were suggested.

1/ A project conducted jointly between the Arizona Office of the Attorney General, Civil Division, Water Rights Adjudication Team (WRAT), 1275 W. Washington, Phoenix, Arizona; and the United States Department of Agriculture, Apache -Sitgreaves National Forest, P.O. Box 640, Springerville, Arizona 85938.

2/ Chief Hydrologist, WRAT; Forest Hydrologist, U.S.D.A; and Hydrogeologist, WRAT, respectively. 85 Hydrologists from the state and federal governments noticed that a discrepancy existed between observed and calculated losses from Lee Valley Reservoir.Observed losses indicated that evaporation rates at the site far exceed the predicted rates based on published data. This study was originally undertaken to (1) determine the sources of this discrepancy and to (2) identify and quantify actual losses from the reservoir. One other objective of this study was to verify the use of existing land - pan evaporation data for the estimation of evaporative losses from remote lake sites, thereby minimizing the need for costly instrumentation and time - consuming data collection at relatively inaccessible locations within the watershed.

PHYSIOGRAPHIC SETTING Southern Apache County is within the Colorado Plateau Region and includes the White Mountains volcanic field and associated highlands. The creeks in this area drain rugged terrain, alternately flowing through forest, open meadow and steep canyons. Vegetation is characterized by spruce -alpine fir forest at the higher elevations, giving way to montane forest of ponderosa pine and douglas fir near Greer.Interspersed among these forests are large tracts of mountain meadows, dominated by various bunch grasses. The transition between pine forest and grassland is sharp, occurring at about 7,400 ft. near the town of Eagar. This transition zone is characterized by juniper and pinon pine, and the grassland is dominated by grama grasses. Southern Apache County is characterized by mild summers and cold winters.In Greer the average January temperature is 25 °F and the average July temperature is 59 °F. The average January temperature in Springerville is 32 °F, with an average July temperature of 65 °F.Greer receives an annual average of 20 inches of precipitation, while Springerville receives 12 inches annually. The precipitation pattern is distinctly bimodal. Convection storms, receiving moisture from the Gulf of Mexico, are common from July through September. Large cyclonic storms bring moisture to the area from the Pacific Ocean from December to March. Late spring and fall are characteristically dry (ADHS, 1982).

Lee Valley Reservoir is located within Section 4, Township 6N, Range 27E, Apache County, Arizona. The reservoir can be accessed via dirt road by traveling Forest Service Road 87, off State Highway 373 from just north of Greer, approximately 5.5 miles to Highway 273 and continuing another 2.8 miles southeast on 273 to Lee Valley Reservoir.Elevations near Lee Valley are approximately 9,400 ft. and range from 8,500 ft. near Greer to 11,400 ft. at the top of Mount Baldy (Figure 1).

86 Becker Lake

Spring rville

0 Area in Detail Eagar

canYOn

Mexican Hay Lake è ,. White Mnt. Res.

Water Canyon Res. Atcheson Res.

Slade Res.

j Seven Springs 0 Research Station Sheep (

,LMt. Baldy 0 3 Mi.

FIGURE 1: LEE VALLEY RESERVOIR AREA MAP

87 PREVIOUS RESEARCH Existing studies on the use of floating pans to estimate evaporation from lakes are limited.It is reported in the A.S.C.E. Proceedings, "Evaporation From Water Surfaces: A Symposium" (A.S.C.E., 1934) that the floating pan is subject to the same conditions as those that occur in the reservoir. Consequently, the theoretical coefficient for computing the equivalent evaporation from the large surface should be nearer to unity than the coefficient for land pans.This report, however, recommends that a coefficient of 0.8 be used to estimate lake evaporation from a floating pan. In a study at Lake Mead Harbeck, et al. (1958) presents 15 years of data comparing floating pans and land -based pans which support the 0.8 coefficient. Evans, et al. (1979), in a study of Lake Patagonia in southeast Arizona, report a floating pan coefficient of 0.92.In the literature (A.S.C.E., 1934; Evans, et al., 1979), individual studies usually of short duration, report floating pan coefficients ranging from 0.78 to 0.92. Floating pan designs varied considerably among the researchers. Certain floatation devices would appear to have a masking affect on ambient air and water conditions affecting exposure of the water surface within the pan itself. Elevations, physiographic settings and lake size also varied significantly from the conditions present at the Lee Valley site.The floating pan design by Evans, et al. (1979) appears to have yielded a coefficient closest to unity and therefore was selected for the current project (Appendix A). Colmer (1987) developed and confirmed a reduction of the Eagar land - pan data to estimate evaporation from a reservoir at a higher elevation. The 1987 study estimated evaporation losses at Mexican Hay Lake, located at approximately 8,900 ft., for a period from May to October using reduced data from the Eagar pan located approximately eight miles northeast of Mexican Hay Lake at an elevation of approximately 7,500 ft.Actual losses from the lake were measured at 27.35 inches, while the Eagar site estimate was 27.45 inches.This 0.10 inch represents a 0.4 percent ( %) difference.This method was developed from 1965 to 1978 evaporation data collected at the the Seven Springs site, a Forest Service research weather station located approximately four and one -half miles south of Mexican Hay Lake at an elevation of approximately 9,200 ft. Average yearly pan evaporation for the Seven Springs site was 63.0 inches, compared to 79.1 inches for the Eagar site, or approximately an 80% ratio. Eagar data are further reduced to estimate lake evaporation by multiplying the data by 0.7, which is the published Class A pan coefficient (A.S.C.E., vol. 99, 1934; Kohler, 1954; Harbeck, et al., 1958). Thus, the evaporation data at the Eagar site are reduced to 56% of the measured value to accurately reflect the evaporation losses at Mexican Hay Lake.

88 METHODOLOGY

Water Balance:

Floating evaporation pan coefficients may vary due to site -specific and design variables.Because of the uncertainty of the correct coefficient for a floating pan, evaporation derived at the Lee Valley floatingpan is assumed to equal total evaporation from the lake, i.e., the pan coefficient is takenas 1.0. In this study, a slight overestimation of evaporative losses was acceptable for the purposes of the study. The basis for using a water balance approach for the quantitative evaluation of water resources is well established (Sokolov and Chapman, 1974; Milne and Young, 1989; Young and Dozer, 1988).Therefore, a simple water balance approach was used to estimate losses from Lee Valley Reservoir using the following equation:

Seepage(Si) = OHi - (Oi+Ei) +

where Atliis the change in lake volume, Oi is the measured controlled releases from the reservoir, Eiis the evaporation from the reservoir surface, Iiis the measured inflow to the reservoir, Piis the direct precipitation onto the reservoir surface and iis the period of the study ( May 1 to October 31, 1989 ) Changes in lake level were measured in relation to a fixed elevation. Controlled releases from the reservoir were measured with a Parshal flume located at the outlet of the reservoir, as well as an additional Parshal flume located approximately 0.6 of a mile downstream on Lee Valley Creek (Figure 2).Direct lake evaporation was measured in a Class A evaporation pan, based on a modified design by Evans, et al. (1979), located within the reservoir (See Figures 3 & 4). Evaporation was also measured in a Class A evaporation pan located near the town of Eagar, approximately 18 miles northeast of the reservoir.Inflow to the reservoir was measured over a broad crested weir upstream from the reservoir on Lee Valley Creek.Precipitation was measured at the reservoir site in a non -recording rain gauge (Figure 2).All instruments were read twice weekly.

The Eagar Soil Site evaporation pan is at an elevation of approximately 7,500 ft., 18 miles northeast of Lee Valley Reservoir.It is the only pan having a sufficiently long period of record currently operated within the watershed. Evaporation measured at the Eagar site must be reduced by 0.56 to estimate the evaporation from Lee Valley Reservoir, at an elevation of approximately 9,400 ft. (Colmer, 1987). During the Lee Valley study there were 147 days of common period of record between the Eagar pan and the floating pan in Lee Valley Reservoir. The Eagar site estimated 27.1 inches of evaporation during this period, while the evaporation pan in Lee Valley Reservoir measured 28.1 inches. 89 LEGEND

AFloating Pan Parshal flume

Figure 2: Lee Valley Direction of Ground water Rain Gauge ------). Reservoir Map Flow 3 Weir - Seep or Spring

0 1320 FT.

90 Figure 3:Floating Evaporation Pan Installed in Lee Valley Reservoir

Figure 4:Measuring Evaporative Losses From Lee Valley Floating Pan

91 This 1.0 inch for the 147 -day period represents a 3.6% difference.Both the Mexican Hay and Lee Valley studies indicate that Eagar pan data may be used to estimate evaporation from reservoirs at higher elevations with acceptable accuracy. As Table 1 shows, monthly comparisons do vary. These differences in evaporation are occurring as a result of wind, temperature and atmospheric pressure variations that should be expected (Chow, 1964).

Eagar SiteLee Valley LakeDifference Inches ** Inches Inches

May* 3.95 4.05 -0.10 June* 5.02 5.55 -0.53 July 6.76 6.35 0.41 August 4.53 4.34 0.19 September* 3.96 4.73 -0.77 October* 2.91 3.05 -0.14

TOTALS 27.13 28.07 -.94

*Partial month * *Reduced value

TABLE 1:Monthly Comparisons of Estimated vs. Actual Evaporation

Because of the ability of the land pan at Eagar to estimate the evaporation losses at Lee Valley Reservoir, within acceptable limits, missing data points for the evaporation pan in Lee Valley during the six -month study are estimated using reduced Eagar data.These missing data points for the floating pan were caused by high wind conditions swamping the pan or limiting access to it.Results of the study indicate a total net loss of 139 af over the six -month period.During this period of time, there were 33 af of precipitation and 52 af of inflow. Total losses from the lake would therefore be 224 af. Of this loss, controlled releases accounted for 8.2 af, and evaporation was measured at 116 af.There were no losses over the spillway during the period of this study. The remaining loss of 100 af is due to seepage, much of which probably contributes to the numerous springs and seeps seen rising within 800 feet downstream of the dam. These data are presented in Table 2 and graphically represented in Figure 5.

At least 19 seeps and springs rise within one -half mile downstream from the dam, with most located along the toe of a basalt slope on the north side of Lee Valley Creek within 800 feet of the dam. Flow rates for individual seeps or springs were estimated between two and six gallons per minute (gpm) with flow observed from June to October 1989.Elevation and flow rates of the seeps on the basalt slope fluctuate with lake levels, with higher flow rates

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AVERAGE 1989 % OF AVERAGE EST. MONTH INFLOW INFLOW AVERAGE INFLOW INFLOW L.V. Cr. L.V. Cr. S. TRIB S. TRIB. (af)1 -' (af) (af)11 (af)

MAY 85.8 16.8 19.6 14.1 2.8 JUNE 31.0 5.7 18.4 3.2 0.6 JULY 16.3 11.0 67.5 2.2 1.5 AUG. 38.2 8.5 22.3 9.9 2.2 SEPT. 47.8 5.4 11.3 11.6 1.3 OCT. 34.8 4.1 11.8 5.9 0.7 9.1 1/ Averaged U.S.G.S. data water years 1967 -1972

TABLE 3:Monthly Comparisons of 1989 vs. Average Lee Valley Inflow Data

Lake Geochemistry: Although the volume of seepage was surprising, regional geology and recent investigations indicate that reservoirs in this area may be prone to seepage losses.The White Mountains of Arizona, including the Lee Valley Reservoir site, were subjected to volcanism during the middle to late Tertiary period. Volcanics in the reservoir area were deposited from late Miocene (13 million years ago) to middle Pliocene (nine million years ago).Deposits associated with this event in ascending order are the intermediate rock -type volcanics of the Mount Baldy Formation, the colluvial sandstones, volcanic debris and mudflows of the Sheep Crossing Formation and a series of olivine basalt flows and cinder cones. During the Quaternary period, stream erosion of the Pliocene olivine basalts and deposition of interbedded fluvial and lacustrine deposits predominated (Merrill, 1970; 1974; Merrill and Péwé, 1971). Only the Pliocene olivine basalts and fluvial deposits are exposed at the Lee Valley Reservoir site.Recent core drilling at the Colter Reservoir site, approximately one mile east of Lee Valley Reservoir, indicated that these basalts are usually horizontally and vertically fractured, with hydrous iron oxides lining the fractures. The basalts are interbedded with old soil horizons, possible fluvial deposits and volcanic ejecta (Miller, 1987; Dozier and Young, 1987; Goodwin andYoung, 1989). Water samples were collected in October 1989 from Lee Valley Creek above the reservoir, from one foot above the bottom of the reservoir northwest of the dam, from a seep 78 ft. downstream of the dam, from a seep 160 ft. downstream of the dam and from a developed spring approximately 94 100 - INFLOW PRECIP. 52 50 - 33 A C o R -50 RELEASES E 8 -100 - F SEEPAGE -150 - 100 EVAP. T 116 0 -200 STORAGE 139 -250 - TOTAL LOSSES 224

FIGURE 5: Water Balance for Lee Valley Reservoir - May To October, 1989

from higher elevations when the lake is at higher levels.As Table 2 indicates, the flume 0.6 mile downstream from the dam measured 95 af, or 87 af more than the flume at the outlet from Lee Valley Reservoir. This increase in the flow of Lee Valley Creek represents 87% of the 100 af lost toseepage from Lee Valley Reservoir. Lee Valley Reservoir is situated in a unique location, very near the surface water divide, and presumed ground water divide between the East and West Forks of the Little Colorado River.As Figure 2 indicates, with the exception of the reservoir area, the seeps near the dam have a very small upgradient area to the north to supply ground water flow. In addition, most of the immediate upgradient area to the north is a paved parking lot. (Lake seepage is discussed further under Lake Geochemistry.)

During this study, a 0.5- square -mile (mil) unnamed drainage that flows into Lee Valley Reservoir from the south was unmonitored (Figure 2).A linear regression was used to estimate inflow from this tributary (Reid, 1968). The equation was developed by using U.S.G.S streamflow records from the southern tributary and Lee Valley Creek for May to October over the period of 1967 to 1972. The equation y= .24857(X)- 2.7291, where X equals flow on Lee Valley Creek and y equals flow on the southern tributary, yields a coefficient of correlation of 0.86.Using this equation and the May to October 1989 monthly flows on Lee Valley Creek, the southern tributary would contribute only an estimated 1.4 af during the period of this study.Using measured inflow on Lee Valley Creek and comparing these values to data of pastyears, a percent of normal inflow was also developed to estimate inflow from the southern tributary (Table 3).This method indicates approximately nine acre- feet of additional inflow into the reservoir, a figure still within the 10 -15% error expected in hydrologic analyses (Domenico, 1972; Steel and Torrie, 1960; Water Resource Data, 1970). Contributions to the lake from this side -channel

95 1,320 ft. downstream of the dam. Three samples were takenat each site, with two fractions preserved in nitric and sulfuric acid. Sampleswere refrigerated and delivered through chain of custody to the State Laboratory at Arizona Department of Health Services for analysis. The analyses of these samplesare included as Table 4.

In Figure 6, the piper diagram would suggest that a relationship exists between the surface waters and the seep and spring waters. An increase in calcium, magnesium and bicarbonate is indicated along this flow path. Both calcium and magnesium are common constituents of the igneous rocks found in this region. The source for bicarbonate is usually assumed to be soil- zone and unsaturated -zone air enriched in carbon dioxide, due to respiration by plants and the oxidation of organic matter (Hem, 1985). A computer program for calculating chemical equilibria of natural waters-- WATEQF, (Plummer, 1976)-- indicates this is possible, as seep and spring waters down- stream from Lee Valley Dam are undersaturated with respect to calcium and magnesium carbonate minerals. The iron content of these waters presents an interesting analytical problem.Igneous rock minerals whose iron content is relatively high include the pyroxenes, amphiboles and especially olivine (Hem, 1985). All of these minerals are common constituents of the basalts in this region. Water flowing into the reservoir has a relatively low concentration of 0.61 milligrams per liter (mg /L) total iron, with iron concentration increasing to 3.12 mg /L in the lake- bottom sample. The iron concentration peaks at 7.57 mg /L in seep #1, located 78 feet downstream from the dam, then declines to 0.1 mg /L in the spring located 1,320 ft. downstream from the dam. In lakes and reservoirs, sediments and water near the bottom become enriched in organic matter and depleted in oxygen. Under these conditions water can contain greater amounts of iron in the ferrous state (Fe +2) or combined with organic compounds. An iron enrichment of the sediments in lakes that have winter ice cover, as Lee Valley Reservoir does from December to April, is possible.Dissolved oxygen levels taken at a depth of 13 ft. --or approximately two feet off the bottom of the reservoir --are lowest in March, ranging from 0.0 mg /L to 0.6 mg /L (AGAF, 1988). Throughout the duration of stagnation, the iron content of the bottom water constantly increases. As iron -rich waters begin to flow into the reservoir, high levels of ironare also present in the hypolimnion as suspended materials. With the onset of total circulation, the iron content of the whole water mass disappears toa trace because of the precipitation and sedimentation of ferric hydroxide (FeO OH nH2O). The result of this process is an iron enrichment within the bottom sediments. This occurs because other dissolved minerals are not precipitated but remain in solution and are gradually lost to the lake by outflow (Buttner, 1963).

Most of the outflow in the vicinity of seeps #1 and #2 support what appears to be a healthy growth of an iron bacteria (Figure 7).Iron bacteria obtain energy by oxidizing ferrous iron present in theiraqueous habitat and

96 ArsenicAlkalinity, PhenolTotal COMPOUND < 0.010 mg/1 INFLOW< 2 mg/120 mg/1 LAKE< BOTTOM 0.010 mg/I < 2 mg/119 mg/1 < 0.010 mg/1 SPRING 1< 2 mg/156 mg/1 < 0.010 mg/1 SPRING 2< 2 mg/152 mg/1

8 0 8 0

80

20

0o °oCa ó o ti á CI e CATIONS PERCENT OF TOTAL ANIONS MILLIEOUIVALENTS PER LITER

FIGURE 6: Piper Diagram of Lee Valley Water Samples

98 depositing it in the form of hydrated ferric oxideon or in their mucilaginous secretions. Some bacteria that do not oxidize ferrous iron may nevertheless cause it to be dissolved or deposited indirectly.In their growth, they either

Figure 7:Seeps Below Lee Valley Dam Showing Evidence of Iron Bacteria liberate iron by utilizing organic radicals to which the iron is attached, or they alter environmental conditions to permit the solution or deposition of iron (A.P.H.A., 1989).As indicated earlier, cores drilled in the area have encountered fractures coated with hydrous iron oxides.The WATEQF program indicates that these waters are oversaturated with respect to iron hydroxides, and precipitation along the fracture faces may or may not require the presence of iron bacteria.

ADHS (1982) reports that total iron concentrations in Lee Valley Creek are among the highest at any site sampled in a study of the watershed above Lyman Lake. During this 1982 study, Lee Valley Creek was sampled at State Highway 273 below Lee Valley Reservoir in June, July, September and October. The sample collected in October, when there should be no controlled releases from the reservoir, contained the highest concentration with 2.68 mg /L of total iron.This value is more than nine times the average background concentration encountered in streams sampled in this portion of the watershed. A possible source for the elevated iron concentrations in the seeps and in Lee Valley Creek below Lee Valley Reservoir may very likely be the waters seeping from the reducing, iron -rich environment on the lake bottom. Verification ofthis phenomenon isthe subject of further investigations of Lee Valley Reservoir. 99 RESULTS AND CONCLUSIONS

Annual Water Balance: On average Lee Valley Reservoir has a surface area of 35 acres and a volume of 399 af (AGAF, 1982).Using average inflow, precipitation and evaporation data from past years and an average lake size of 35 acres, an annual water balance for the lake was calculated. Admittedly, this is a short period of available record of inflow data.Average data for the region are presented in Table 5. Months when the lake is frozen over are listed as zero.

Average stream inflow to the lake is calculated at 469 af/a. An additional 91 af/a enter as direct precipitation for a combined total of 560 af/a. Projecting the results of this study over an annual period, 108 af/a of water are lost from the lake surface to evaporation. The reduced annual lake evaporation from the Seven Springs data of 37.0 inches agrees with published the lake evaporation figure for the Mt. Baldy area of less than 40 inches (N.O.A.A., 1982).Based on a constant seepage rate, the annual seepage loss is estimated at 198 of /a, or 49% of the average 399 af volume of the lake. Therefore, on an average annual basis, Lee Valley Reservoir could expect to discharge roughly 254 af /a over the spillway. These spills, together with the seepage amount of 198 of /a naturally contribute about 452 af/a to downstream reaches of Lee Valley Creek (and eventually to the East Fork of the Little Colorado River), and to the West Fork of the Little Colorado River above the town of Greer (Figure 8).

1 2 3 4 5 6 MONTHEVAPORATION LAKEEVAP. PRECIP. INFLOW INFLOW SEEPAGE DATA (in) (in) (in) L.V. Creek (al) S. Trib. (af) EST. (af)

JAN. 13 0.0 2.70 6.3 0 FEB. 2.5 0.0 2.68 7.3 0.9 MAR. 5.0 0.0 2.81 13.9 6.4 APR. 6.9 4.8 1.60 50.2 19.1 MAY 8.8 6.2 1.01 85.8 14.1 JUNE 11.3 7.9 1.24 31.0 3.2 JULY 7.6 5.3 4.30 16.3 2.2 AUG. 5.7 4.0 4.36 38.2 9.9 SEPT. 5.0 3.5 2.82 47.8 11.6 OCT. 4.4 3.1 2.43 34.8 5.9 NOV. 3.2 2.2 2.20 44.4 3.7 DEC. 13 0.0 2.90 14.8 0.7

TOTALS 63.0 37.0 31.05 390.8 77.7 198

1. SEVEN SPRINGS EVAPORATION DATA I965.1978 2. EVAPORATION DATA REDUCED BY 0.7 TO ESTIMATE LAKE EVAPORATION (LAKE FROZEN DEC.-MAR) 3. AVERAGED SHEEP CROSSING AND MAVERICK FORK DATA 1953 -1985 4. AVERAGED U.S.GS. DATA WATER YEARS 1967 -1972 5. AVERAGED U.S.G.S. DATA WATER YEARS 1967 -1972 6. ANNUAL SEEPAGE ESTIMATE 1989 STUDY

Table 5: Average Annual Data for Lee Valley Reservoir 100 A 900

R 300 E A 200 N PRECIP. 91 F N 100 T U M 0 P -100 E \ -200 EVAP. R 108 h SEEPAGE -300 198 SPILLS 254

Figure 8:Average Annual Water Balance of Lee Valley Reservoir

Geochemistry:

ADHS (1982) reports that total iron concentrations in Lee Valley Creek below the reservoir are among the highest at any site sampled in a study of the watershed above Lyman Lake. Concentrations as high as 2.68 mg /L of total iron were measured.This value is over nine times the background concentration encountered in other streams sampled in this portion of the watershed. A possible source for the elevated iron concentrations in Lee Valley Creek below Lee Valley Reservoir may very likely be the waters seeping from the reducing, iron -rich environment on the lake bottom. Additional sampling of the lake, seeps and bottom sediments during 1990 are planned in order to gain a better understanding of the geochemistry of Lee Valley Reservoir.

Existing Evaporation Pan Data: The results of this investigation also support the methodology developed to predict evaporative losses from remote alpine lakes that are often inaccessible and do not easily lend themselves to instrumentation and primary data collection. Extrapolation of existing long -term Class A land -pan data such as that from the Eagar or Seven Springs sites allow for reasonably accurate prediction of lake evaporation associated with these remote recreational reservoirs.

101 REFERENCES

American Public Health Association, 1989.Standard Methods for the ExaminationofWater and Wastewater, 17th edition, American Public Health Association, Washington, D.C. 1,533 p.

American Society of Civil Engineers, 1934. Evaporation From Water Surfaces, A Symposium, American Society of Civil Engineers Transactions vol. 99, pp. 671 -718

Arizona Department of Health Services,1982. The Little Colorado River Watershed Above Lyman Lake: Water Chemistry, Nutrients and Nutrient Standards, 64 p.

Arizona Game and Fish Department, Planning Branch. 1982,Arizona Lakes Classification Study, Work Element 103.230: Lakes Survey, 184 p.

Arizona Game and Fish Department, 1988. Lee Valley Lake Fish Management Report 1983- 1987, Statewide Fisheries Investigation, Survey of Aquatic Resources, Federal Aid Project F- 7 -R -30, 26 p.

Chow, V.T. ed, 1964.Handbook of Applied Hydrology: A Compendium of Water Resources Technology, McGraw -Hill Book Company, New York, New York.

Colmer, G., 1987.Mexican Hay Lake Water Level Study, U.S.D.A., Apache -Sitgreaves National Forest, Unpublished Report, 12 p.

Domenico, P.A., 1972.Concepts and Models in Groundwater Hydrology, McGraw -Hill Book Company, New York, New York.

Dozier, G.J., Young, D.W., 1987.Geologic /Hydrologic Evaluation of the Proposed Colter Reservoir Site, Apache County, Arizona, Office of the Attorney General, Civil Division - WRAT, Unpublished Report, 16 p.

Evans, D.D., Young, D.W., Onyskow, L.P., and Bradbeer, G.E., 1979. Water Losses from Small Recreational Lakes in Arid Regions and Possible Effects Downstream, Project Completion Report, OWRT Project No. A- 065 -ARIZ, University of Arizona, Tucson, Arizona.

Goodwin, S.D., Young, D.W., 1989. Colter Reservoir: Dam Siting and Seepage Project Interim Report, Arizona Office of the Attorney General, Civil Division -WRAT, Unpublished Report, 28 p.

Harbeck, E.G., Kohler, M.A., Koberg, G.E., and Others, 1958. Water -Loss Investigations: Lake Mead Studies, U.S. Geol. Survey Prof. Paper 298, 100 p.

Hem, J.D., 1985. Study and Interpretation of the Chemical Characteristics of Natural Water, U.S. Geol. Survey Water -Supply Paper 2,254, 264 p.

Kohler, M.A., 1954. Lake and Pan Evaporation, in Water -Loss Investigations -Lake Hefner Studies, Technical Report: U.S. Geol. Survey Prof. Paper 269, 150 p.

Merrill, R.K., 1970. The Glacial Geology of the Mount Baldy Area, Apache County, Arizona, Arizona State University, Unpublished M.S. Thesis, 118 p. Merrill, R.K., 1974. The Late Cenozoic Geology of the White Mountains, Apache County, Arizona, Arizona State University, Unpublished Ph.D Dissertation, 202 p.

Merrill, R.K., Péwé, T.L., 1971. The Sheep Crossing Formation: A New Late Cenozoic Epiclastic Formation in East -Central Arizona, Arizona -Nevada Academy of Science Journal, vol. 6, no. 3, pp. 226 -229 102 Miller, C.H., 1987.Engineering Geology Report, Proposed Colter Reservoir Basin, Apache- Sitgreaves National Forest, Unpublished National Forest Service Report, FS-- 6200 -28 (7 -82), 26 p.

Milne, .d.M., Young, D.W., 1989. The Impact of Stockwatering Ponds (Stockponds) on Runoff from Large Arizona Watersheds, Water Resources Bulletin, vol. 25, no.1, pp.165 -173

Plummer, L.N.,Truesdell, A.H., and Jones, B.F., 1976. WATEQF- A Fortran IV Version of WATEQ, A Computer Program for Calculating Chemical Equilibrium of Natural Waters, U.S. Geol. Survey Water Resource Investigations 76-13, 63 p.

Reid, J.K., Carroon, L.E., and Pyper G.E., 1968. Extensions of Streamflow Records in Utah, Utah Department of Natural Resources, Technical Publication No. 20, 110 p.

Ruttner, F., 1963. Fundamentals of Limnology, University of Toronto Press, Toronto, Canada.

Sokolov, A.A., Chapman, T.G., eds., 1974.Methods for Water Balance Computation: An International Guide for Research and Practice. UNESCO Press, Paris, France

Steel, R.G.D., Torne, J.H., 1960.Principles and Procedures of Statistics, McGraw -Hill Book Company, New York, New York.

Water Resources Data for Arizona, Water Years 1966 -1972.U.S. Geol. Survey Water -Data Reports.

Young, D.W. and Dozer, G.J., Heuristic Approach To The Evaluation Of Groundwater Uses In The San Pedro Watershed In Southeastern Arizona, Arizona Hydrological Society, 1st. Annual Symposium Proceedings, Phoenix, Arizona, September 16, 1988, pp. 14 -34

103 APPENDIX A

1. Floating Evaporation Pan Design (from Evans, et al., 1979)

2. Photo Al: Construction Phase of Floating Evaporation Pan

3. Photo A2: Construction Phase of Floating Evaporation Pan

104 FLOATING EVAPORATION PAN

TOP VIEW Anchor point eye bolt

1" Angle iron 1"X12"X12' Perforated board attached frame to frame on each side

Styrofoam or PVC floatation collar Standard 12' -0" evaporation pan reinforced at top to support tabs

1"X2" Tab with 1/2" hole for chain attachment

Floatation tubes 4 "X10' PVC with end caps attached to frame on each side

SIDE VIEW

8" Angle iron upright board supports 1 "or11/2" welded to frame 1 "x12 "X12' Perforated board Holes o 0 0 0 00 0 0000000 0 00000 I/r0 000 00 000 000 000000 0000000 000000 i Iv o

Plumber's strapping PVC floatation tube/ used to attach tube to cross supports of frame

105 Figure Al: Modified Class A Evaporation Pan

Figure A2: Floatation Frame For Floating Evaporation Pan

106 APPENDIX B

1. Evaporation Data for Lee Valley Reservoir Floating Pan

2. Evaporation Data for Eagar Soil Site Pan

107 EVAPORATION FOR LEE VALLEY RESERVOIR (Inches)

DATE PREVIOUS FRECH'. TOTAL CURRENT EVAP. RESET READING READING

5/1/89 2.755 5/4/89 2.755 0.00 2.755 2.080 .675 2.300 5/8/89 2.300 0.00 2.300 1.282 1.018 2.300 5/11/89 2.300 0.00 2.300 2.300 5/12/89 0.00 1.083 5/15/89 1.083 0.00 1.083 .333 .750 1.722 5/18/89 1.722 0.19 1.912 1.800 .112 2.600 5/22/89 2.600 0.00 2.600 1.110 1.490 2.300 5/25/89 2.300 0.00 2.300 2.500 5/30/89 2.500 0.00 2.500 2.500 6/8/89 2.500 0.00 2.500 2.500 6/9/89 2.500 0.00 2.500 2.500 6/12/89 2.500 0.00 2.500 2.500 6/15/89 2.500 0.00 2.500 1.689 .811 2.500 6/19/89 2.500 0.00 2.500 1.295 1.205 2.500 6/22/89 2.500 0.00 2.500 1.603 .897 2.500 6/26/89 2.500 0.00 2.500 .954 1.546 2.500 6/29/89 2.500 0.00 2.500 1.745 .755 2.500 7/3/89 2.500 0.00 2.500 1.126 1.374 2.500 7/6/89 2.500 0.01 2.510 1.383 1.127 2.500 7/10/89 2.500 0.27 2.770 1.930 .840 2.500 7/13/89 2.500 0.06 2.560 2.143 .417 2.500 7/17/89 2.500 0.63 3.130 2.578 .552 2.500 7/20/89 2.500 0.30 2.800 2.224 .576 2.500 7/25/89 2.500 1.43 3.930 3.110 .820 2.500 7/28/89 2.500 1.40 3.900 3.347 .553 2.500 7/31/89 2.500 0.10 2.600 2.155 .445 2.500 8/4/89 2.500 0.82 3.320 3.120 .200 2.500 8/7/89 2.500 0.12 2.620 2.026 .594 2.500 8/10/89 2.500 0.22 2.720 2.247 .473 2.500 8/14/89 2.500 0.02 2.520 2.282 .238 2.500 8/17/89 2.500 0.85 3.350 3.042 .308 2.500 8/21/89 2.500 0.82 3.320 2.800 .520 2.500 8/25/89 2.500 0.02 2.520 1.466 1.054 2.500 8/28/89 2.500 0.17 2.670 2.282 .388 2.500 8/31/89 2.500 0.35 2.850 2.287 .563 2.500 9/5/89 2.500 0.11 2.610 1.990 .620 2.500 9/8/89 2.500 0.02 2.520 2.122 .398 2.500 9/13/89 2.500 0.00 2.500 1.162 1.338 2.700 9/19/89 2.700 0.09 2.790 1.618 1.172 2.700 9/25/89 2.700 0.11 2.810 2.700 10/2/89 2.700 0.00 2.700 1.000 1.700 2.000 10/10/89 2.000 2.18 4.180 3.800 .380 3.068 10/18/89 3.068 0.16 3.228 1.855 1.373 2.700 10/25/89 2.700 0.22 2.920 2.100 .820 2.700

108 EVAPORATION FOR EAGAR SOIL SITE (Inches)

DATE PREVIOUS PRECIP. TOTAL CURRENT EVAP. RESET EST. LAKE READING READING EVAP. (.56)

3/23/89 3.650 3/27/89 3.650 0.32 3.970 2.956 1.014 3.650 0.57 3/30/89 3.650 0.00 3.650 3.024 0.626 3.650 0.35 4/3/89 3.650 0.00 3.650 2.290 1.360 3.650 0.76 4/6/89 3.650 0.00 3.650 2.690 0.%0 3.650 0.54 4/10/89 3.650 0.00 3.650 1.862 1.788 3.650 1.00 4/13/89 3.650 0.00 3.650 2.400 1.250 3.650 0.70 4/17/89 3.650 0.00 3.650 2.452 1.198 3.650 0.67 4/20/89 3.650 0.00 3.650 2.590 1.060 3.650 0.59 4/24/89 3.650 0.00 3.650 1.900 1.750 3.650 0.98 4/27/89 3.650 0.00 3.650 2.392 1.258 3.650 0.70 5/1 /89 3.650 0.03 3.680 2.384 1.296 3.650 0.73 5/4/89 3.650 0.00 3.650 2.338 1.312 3.650 0.73 5/8/89 3.650 0.00 3.650 1.856 1.794 3.650 1.00 5/11/89 3.650 0.00 3.650 2.240 1.410 3.650 0.79 5/15/89 3.650 0.00 3.650 2.200 1.450 3.650 0.81 5/18/89 3.650 0.07 3.720 3.094 0.626 3.650 0.35 5/22/89 3.650 0.00 3.650 1.756 1.894 3.650 1.06 5/25/89 3.650 0.00 3.650 1.782 1.868 3.650 1.05 5/26/89 3.650 0.00 3.650 3.044 0.606 3.650 0.34 5/30/89 3.650 0.00 3.650 1.690 1.960 3.650 1.10 6/1/89 3.650 0.00 3.650 2.476 1.174 3.650 0.66 6/5/89 3.650 0.00 3.650 2.010 1.640 3.650 0.92 6/8/89 3.650 0.00 3.650 2.110 1.540 3.650 0.86 6/12/89 3.650 0.00 3.650 1.838 1.812 3.650 1.01 6/15/89 3.650 0.00 3.650 2.118 1.532 3.650 0.86 6/19/89 3.650 0.00 3.650 1.726 1.924 3.650 1.08 6/22/89 3.650 0.00 3.650 2.078 1.572 3.650 0.88 6/26/89 3.650 0.00 3.650 1.482 2.168 3.650 1.21 6/29/89 3.650 0.00 3.650 2.428 1.222 3.650 0.68 7/3/89 3.650 0.00 3.650 1.458 2.192 2.192 1.23 7/6/89 3.544 0.02 3.564 1.784 1.780 3.650 1.00 7/10/89 3.650 0.02 3.670 1.843 1.827 3.650 1.02 7/13/89 3.650 0.06 3.710 3.018 0.692 3.650 0.39 7/17/89 3.650 0.06 3.710 2.310 1.400 3.650 0.78 7/20/89 3.650 0.32 3.970 2.800 1.170 3.000 0.66 7/25/89 3.000 1.93 4.930 2.760 2.170 3.000 1.22 7/28/89 3.000 0.02 3.020 2.640 0.380 3.000 0.21 7/31 /89 3.000 0.85 3.850 2.862 0.988 3.000 0.55 8/4/89 3.000 0.05 3.050 2.426 0.624 3.000 0.35 8/7/89 3.000 0.02 3.020 1.965 1.055 3.000 0.59 8/10/89 3.000 0.21 3.210 2.379 0.831 3.000 0.47 8/14/89 3.000 0.01 3.010 1.893 1.117 3.000 0.63 8/17/89 3.000 0.00 3.000 2.166 0.834 3.000 0.47 8/21/89 3.000 0.59 3.590 2.989 0.601 3.000 0.34 8/25/89 3.000 0.00 3.000 1.634 1.366 3.000 0.76 8/28/89 3.000 0.00 3.000 2.069 0.931 3.000 0.52 8/31/89 3.000 0.03 3.030 2.320 0.710 3.000 0.40 9/5/89 3.000 0.51 3.510 2.413 1.097 3.000 0.61 9/6/89 3.000 0.04 3.040 2.465 0.575 3.000 0.32 9/13/89 3.000 0.00 3.000 1.243 1.757 3.000 0.98 9/19/89 3.000 0.00 3.000 1.117 1.883 3.115 1.05 9/25/89 3.115 0.00 3.115 1.282 1.833 3.300 1.03 10/2/89 3.300 0.00 3.300 0.840 2.460 2.388 1.38 10/4/89 2.386 0.00 2.386 1.787 0.599 3.100 0.34 10/10/89 3.100 1.47 4.570 3.970 0.600 3.650 0.34 10/18/89 3.650 0.00 3.650 1.880 1.770 3.600 0.99 10/25/89 3.600 0.56 4.160 2.667 1.493 3.650 0.84 10/31 /89 3.650 0.06 3.710 2.416 1.294 0.72

109 APPENDIX C

1. U.S.G.S. Water Resources Data for Lee Valley Creek

2.U.S.G.S. Water Resources Data for the South Tributary to Lee Valley Reservoir

110 STATION: 9ABOVELEE -3832 VALLEY LEE VALLEYCREEK RES. DRAINAGE AREA-1.3 sq. mi. YEAR JAN FM MAR APR MAY JUN JUL AUG SEP OCT NOV DEC TOTAL TOTAL 196819671966 4.33.1 2.8 4 9.3 11 6646 157 66 8.1 71 3018 123 17 1176 5.82237 8.1 6031 6.25.415 CW AF 430402 WY AF 394449 1972197119701969 6.26.1 12 5.620 8.36.56.242 68387112 177 271375 133851 5 9.61521 4 11281337 107 263928 963018 139 9.1 19 7.1 4114 397259545 505155288553 PERCENT AVG 6.3 2 7.3 2 13.9 4 50.2 13 85.8 22 31.0 8 16.3 4 38.2 10 47.8 12 34.8 9 44.4 11 14.8 4 406.5 100 390. 8

U.S.G.S. WATER RESOURCES DATA FOR ARIZONA STATION: S. TRIBUTARY TO L.V. RES. 9- 3832.2 DRAINAGE AREA =.5 sq. mi. 1966YEAR .JAN FEB MAR APR MAY JUN JUL AUG SEP OCT 0 NOV 0.7 C C0.4 TOTALCYAF TOTALWY AF 196919681967 0 0.4 0 0.55.2 0 17462224 7.61.4 2153 1.92.1 14 0 1.72.23.55.2 0.71.41137 0.04 4.73620 3.25.82.5 0 4.40.8 0 0.70.4 0 129 389497 118 459894 N 197119701972 0 4.10.7 6.526 4.70.8 0.0214.1 1.7 1.2 0 0.3 0 0.08 9 0.7 8 24 16 2.5 68 77.5 8228 N PERCENT AVG 0.0 0 0.9 1 6.4 8 19.1 25 18 3.2 4 2.2 3 9.913 11.6 15 5.9 8 3.7 5 0.7 1 85.0100

U.S.G.S. WATER RESOURCES DATA FOR ARIZONA PROPOSED METHODOLOGY FOR SOIL LOSS PREDICTION FROM SOUTHWESTERN FOREST Tecle, A., D.P. Dykstra, W.W. Covington, and L.D. Garrett School of Forestry, P.O. Box 4098 Northern Arizona University Flagstaff, Arizona 86011 -4098

Introduction Accounting for environmental impact of forest management is required by law, specifically the National Environmental Policy Act of 1969 (P.L. 91 -190,83 Stat.852). The National Forest Management Act of 1976 (P.L. 94 -588, 90 Stat. 2949) also mandates the Forest Service to manage National Forestsina way that maximizes long -term net public benefits in an environmentally sound manner. One environmental problem of concern to forest managers and other interest groups is loss of soil from the forest area due to erosion and sediment transport. In order to determine the effect of different forest management practices on soil loss, several prediction models have been developed.However, there has not been a scientific assessment for the applicability of these models to southwestern forests. The purpose of this paper is to explore and review existing methods for predicting water - induced erosion and sediment yield applicable to forest areas, and in the process identify appropriate models for further development to make them specifically applicable to southwestern forest conditions.Towards this end, the paper is organized in the following manner. At first a general background on erosion and sediment yield in a forest environment followed by a discussion on the impact of changes in vegetation cover and hydrological conditions on the problem are provided. Then, after a brief review of some existing erosion and sediment yield models applicable to forested areas, identification of two models, WEPP and a remodified USLE, for further development and application to the problem under consideration, specifying some aspects of the proposedUSLE remodification procedure, and a summary and conclusions of the paper are presented. It is hoped that the proposed parallel development of the two methods will meet the short- and long -term erosion and sediment yield modeling needs for the southwestern forest areas.

Erosion and Sediment Yield in a Forest Environment

Water - induced erosion and sediment production are two important related processes that affect the quality of water and soil fertility in a forest ecosystem. In this paper, erosion refers to the mechanical detachment by water of mineral soil

113 particles and organic matter from the upper part of the soil. These mineral and organic soil particles are the lighter and finer soil materials, and they are usually higher in clay, silt and organic matter than the rest of the soil material. After detachment the sediment materials are found either in motion or in sedentary form. Those in motion travel downstream along with the flowing water either in suspension or saltation. The amount of sediment at a particular point is usually a function of the level of erosion and the amount and rate of the flowing surface water. Sediment yield (also known as sediment discharge) is usually described as the amount of sediment moving past the outlet of a particular watershed during a specified time interval. Categorically, sediment yield may be divided into three processes: soil particle detachment or entrainment, transport of the detached sediment, and sediment deposition or aggredation.In any case, the

principal sources of sediment in a forest environment are : (1) sheet and rill erosion from the forest floor and openings within the forest, (2) any fluvial processes that take place in upland gullies, stream channels and valley trenches, (3) erosion from roads, trails and other rights -of -way clearings, and (4) detachments ofsoil materialsgenerated in constructionand development sites. Thus, to use Glymph's words (Glymph 1975), sediment ismostly "... theeffluentfrom thenaturalsoil processing system ", sometimes enhanced by anthropogenic activities.

Erosion and sediment yield can have important on -site and off - site environmental effects as well as regional economic implications. Soil erosion decreases on -site forest soil productivity by removing essential,nutrient -rich top surface soils. It causes soil instability when surface eroded sediments become deposited in upland draws or pockets. Such deposits are usually hazardous as they are easy candidates for future surface erosion or mass wasting. Also erosion - induced sediment may be transported off site and become (1) detrimental deposition on crop land and development sites,(2) deposited in reservoirs and ponds thereby reducing the storage capacity and useful life of such structures,(3) aggredate stream channels causing increased flood hazards, (4) plug canals, ditches, and drains, (5) increase evapotranspiration losses by allowing vegetation to invade widening flood plains, and (6) pollute surface water supplies. It also affects wildlife and fish habitat. As a pollutant, sediment movement in surface water runoff greatly exceeds in volume the combined total of all other substances that pollute surface waters in the United States (Robinson, 1971; Grant, 1971; Branson et al., 1981) .

One other environmental problem associated with sediment yield and erosion processesis the attachment of heavy metals and pesticides from industrial, agricultural, and urban sources located in or near forested watersheds, to sediment particles. Biological and chemical pollutants from heavily used recreational areas as well as livestock and wildlife grazing spots in the forest may also attach themselves to sediments. The clay and silt particles and

114 organic matter in clays have high capacity for absorption of pathogens, viruses, plant nutrients, pesticides, detergents and other chemicals (Glymph, 1975). Thus, knowledge of sediment transport and deposition rates mayhelp to understand the destination of these kinds of sediment -attached pollutants. (Aldon and Garcia, 1973).

Effect of Vegetation Cover on Erosion and Sediment Yield There is plenty of evidence in the literature to indicate that forest cover prevents erosion. Vegetation not only reduces the kinetic impact of raindrops on the soil but also tends to bind the soil materials together, thus preventing easy soil detachment. Reduction of the erosive impact of raindrops by vegetation cover may happen in at least two ways: (1) by canopy interception of the raindrop energy, and (2) through absorption of the erosive energy by the litter mat on the forest floor before it reaches the soil material underneath. In the first case, the amount of erosive energy reduction depends upon the raindrop size and fall distance (Dohrenwend, 1977) . In the second case, the amount of energy reduction is a function of the depth of the litter mat. If the litter mat depth exceeds the penetration depth of the raindrops, there may not be any detachment of mineral soil from the soil surface (Simons et al., 1975). Similarly, the presence of good litter cover on the forest floor reduces the detachment energy of the flowing water and thus the quantity of the runoff -detached soil material. Where the litter layer is removed or disturbed by such activities as falling trees and logging, machine -construction of forest areas such as roads and landings, creating channels, ruts or gouges through the use of heavy equipment and skidding logs across soil surfaces, and burninglitterthroughprescribed fire, on the other hand, infiltration rate is decreased resulting in increased runoff.The resultingincreasedsoil exposure andhigherenergydue to increased runoff end up producing more sediment yield. The presence of dense vegetation cover and thick litter matt helps to increase infiltration thereby reducing overland flow and its effect on erosion. In addition it is understood that different types of vegetation, i.e., forest types and grass species, may have differing effects on erosion and subsequent sediment yield to give the importance of vegetation cover management for sediment yield control much more meaning.

Hydrologic Conditions that Affect Erosion and Sediment Yield Erosion may be caused by dynamic forces exerted on the soil surface by water, wind, ice or other climatic and geologic agents in motion and which vary from place to place.Our interest in this paper, however, is only concerned with water -causederosion,

115 specifically the mechanical detachment and subsequent transport of the eroded particles. Such generation of water flow and sediment yield from a forest watershed with numerous distinct locations would make the physical interactions between rainfall, overland flow, soil erosion and anthropogenic activities that take place in a forest system very complex to deal with (Heede, 1987). And this kind of situation has made the discovery of general relationships between overland flow and sediment discharge difficult (Julien and Frenette, 1985).Overland flow is that part of streamflow reaching a channel without infiltration at any point (Hewlett, 1982) and its amount and duration are functions of precipitation occurrence, antecedent soil moisture condition and baseflow all of which can vary with time and space (Lane and Shirley, 1982). The energy for soil material detachment by water may be provided by the impacts of falling precipitation droplets and /or shear stress from flowing water. The energygenerated by precipitationdropletsresults in breaking down the surface structure of the bare soil upon which the droplets land and cause detachment of soil particles and individual aggregates from the soil. Likewise, the energy from overland flow expended on the soil surface causes detachment of soil materials that may be carried away as suspended load or bed load along with the flowing water.

Suspended sediment is that portion of the total sediment load in transit in the water under varying flow regimes.Suspended load from stream channel erosion is the major contributor to the total annual sediment discharge in some streamsdraining forested watersheds (Anderson, 1975; Flaxman, 1975). Bed load, on the other hand, is that part of fluvial sediment load that moves immediately above the bed in a rolling or saltating mode. Its immersed weight is supported by a combination of fluid and solid reactive forces exerted at intermittent contacts with the stream bed.

In their sedentary form, sedimentparticles are found deposited along the sides and bottom of stream channels, and at the bottom of dams, reservoirs, lakes and river mouths and estuaries. The amount of sediment produced is usually expressed in units of weight (such as tons) or volume (such as ft3) per unit area (such as acres or mil) per unit time (day, month, season or year).

Modeling of Erosion and Sediment Yield The quantity and rate of sediment loss from forest watersheds is influenced by several factors. Some of the most important factors that affect the processes of erosion and sediment yield are: (1) soil, its inherent resistance to dispersion, its water intake and transmission capacities; (2) vegetation cover and canopy including forest floor residues; (3) climate, mainly rainfall and temperature; (4) topography, particularly steepness and length of slope; and (5) land use patterns. Most of these factors and some otherrelatedones areincluded in constructing models for

116 determining the amount and rate of erosion and sediment yield from forested watersheds. A brief review of some common erosion and sediment yield models that may be applicable, at least with some modification, to forested areas is provided below.

Review of Erosion and Sediment Yield Models A number of models have been developed and used to predict event -based or annual average -based soil loss from field -scale and basin -scale watersheds (Pacific Southwest Interagency Committee, 1974; Kniesel, 1980; Renard and Stone, 1982). Some of the better known models include: the universal soil loss equation (USLE) of Wischmeier and Smith (1978) and its two modified (MUSLE) versions, one of which was developed for application to forested lands (DissmeyerandFoster, 1980; 1981), andtheother used for estimating event -based sediment yield as in the problem- oriented computer language for HYdrologic Modeling (HYMO) of Williams and Hann (1973); the WAter- Sediment -CHemical (WASCH) model of Bruce et al.(1975); the Non -Point Source (NPS) pollutant loading model of Donigian and Crawford (1976), and the Ecosystem SIMulation (ECOSIM) model of Rogers et al.(1984). Other basin -scale models that can be applied to wildland and forest conditions include the Agricultural Chemical Transport MOdel (ACTMO) of Frere et al.(1975), the distributed and deterministic model (ANSWERS) developed by Beasley et al.(1977) for predicting runoff and erosion /sediment transport, and the SEDiment SIMulation (SIMSED) model of Simons et al.(1977). Recent developments in computer technology and man's growing analytical capability are encouraging the development of new models that are expected to reflect real world problems better than previous ones. Some of the new models include STREAMS (Soil, Transport, Rainfall, Erosion, and Mapping Systems) of Oslin et al. (1988), the WaTeR YieLD (WTRYLD) model described in Combs et al. (1988), and the Water Erosion Prediction Project (WEPP) of Foster and Lane (1987), Foster et al. (1987) and Lane and Nearing (1989). Other additional recent models include the basin -scale Simulator for Water Resources in Rural Basins (SWRRB) described in Arnold et al. (1987) and Williams et al.(1985), the AGricultural Non -Point Source (AGNPS) pollution model of Young et al.(1987), the South Alaska Multiresource Model (SAMM) of Fight et al. (1990), and ROTO, a continuous water and sediment routing model (Arnold, 1990). A comparative review of the models mentioned above and other related ones is summarized in Table 1 to give a better idea on the direction and efforts made so far in modeling erosion and sediment yield. This would help to provide a background information for selecting and /or developing the most appropriate relevant model for southwestern forest areas.

117 Table 1. Water quality models applicable to forest environment: their development, scales of application and basic components

Model Author(s) Date Hydrologic Erosion Chemical Scale of Applicable Applicable to component component component application land type forest conditions

ACTMO Frere 1975 USDAHL MUSLE Pest Basin Agriculturalland Yes et al. á PN and wildland AGNPS Young 1987 Streamflow Sediment N,P á Basin Agricultural Yes it al. rill, Interrill COO and wildland ANSWERS Beasley 1977 USDAHL MUSLE (interrill, None Field á Basin Agriculturalland Yes Beasley 1980 rill, overland. and wildland et al. and channel flow) CREAMS Kniesel 1980 SCSCN Interrill, rill, Pest Field á Basin Agriculturalland Yes overland and á PN channel flow ECOSIM Rogers 1984 Baker- Kovner USLE None Basin Wildland Yes et al. forest areas HYMO Williams 1973 Unit hydro - MUSLE None Basin Agriculturalland Yes and Hann graph method and wildland USLE Wischmeier 1978 Rainfall Interrill, rill None Field á Basin Agriculturalland Ves and Smith MUSLE Dissmeyer 1980 Runoff, Peak Interrill, rill None Basin Agriculturalland Yes and Foster runoff and wildland NPS Donigian & 1976 SWM Negev None Basin Agriculturalland Yes Crawford and wildland PROSPER Goldstein 1974 Network Sediment None Basin Forest land Yes et al. equations RFF Glanessi 1978 Mean river Loading functions Pest,PN Basin Wildland, and Yes et al. flow river basins ROTO Arnold 1990 SCSCn Sediment Nont Basin Agriculturalland Yes Unit Hydrog. MUSLE and wildland SAMM Fight 1990 Water Stdimtnt Noni Basin Forestad land Yes et al. balance routing SIMSED Simons 1977 Infiltration Raindrop splash Nona Basin Wildland Yes et al. kinematic flowoverland flow STREAMS Oslin 1988 HEC -1 á NEC -2 USLE None Basin Wildland Yes et al. SWMM Diniz 1976 Parametric USLE Yes Basin Urban and Yes wildland SWRRB Arnold 1987 SCSCN MUSLE Basin Agriculturalland Yes et.al. and wildland WTRYLD Combs 1988 SNOWMELT Overland and No Basin Wildland and Yes et al. channel flow forest WEPP Lane and 1989 Climatic á Interrill and No Field á Basin Agriculturalland Yes Nearing hydrologic rill flow wildland PN = plant nutrient COD = Chemical oxygen demand Pest = pesticides

Modeling Erosion and Sediment Yield in Southwestern Forests Even though it may be possible to modify all those in Table 1 and other models which are not listed there for application to southwestern forests, the authors have narrowed their interest to work on a parallel development of models similar to that being pursued in rangeland watersheds (Renard et al., 1990). These involve support for the development of a forest watershed version of WEPP and remodifying the USLE for application to southwestern forest lands. A cooperative effort between the USDA's Agricultural Research Service, Forest Service and Soil Conservation Service and the USDI's Bureau of Land Management is underway to develop the first one (Lane and Nearing, 1989; Stone et al., 1990). Only some aspects of the proposed methodology for remodifying the USLE for the problem under consideration is thus proposed herein.

118 Previous Modifications of the USLE The universal soil loss equation (Wischmeier and Smith 1978) has been modified to make itappropriatefor application to different land use patterns.There are two previous and one recent modifications of the LISLE. One of the previous modifications is specifically designed for estimating annual average soil loss from forest environments (Dissmeyer and Foster, 1980; 1981), while the other is intended for predicting event -based soil loss from a particular land area (Williams and Hann,1973). The third and newest modification is the revised RUSLE described in Renard et al. (1990) .

The Modified Soil Loss Equation for Forest Environments: This type of modification is based on substitutingthe factors C, cover management factor, and P, land use practice factor in the LISLE with single vegetation management factor, V (Warrington, 1980; Dissmeyer, 1982). The soil loss equation so modified is expressed in the following form:

A = R*K*L*S*V [2] where A = annual average rate of interrill and rill erosion in tons /acre /year. R = rainfall erosivity factor in foot- tons *10"2/acre -hr- year. K = soil erodibility factor in tons -acre -hr /(acre ft-

tons*10-2) . L = slope length factor (ft). S = slope steepness (gradient) factor( %). V = the vegetation management factor which is composed of many subfactors. The major subfactors of the vegetation management factor V, that are important in a forest environment include:(1) amount of bare soil,or conversely, ground cover, (2) above ground vegetation canopy cover, (3) soil reconsolidation, (4) forest floor organic matter content, (5) fine roots,(6) residual binding effect, (7) on site storage,(8) steps, and (9) contour management practice. These factors are described in detail in Dissmeyer and Smith (1981) and Dissmeyer (1982), where values for each subfactor are provided either graphically or in tabular form for southeastern United States forest watersheds. The overall value for the V factor is then computed by multiplying the relevant individual subfactor values. In order to use the procedurein the southwestern ponderosa pine forests of the United States, however, the subfactors values for representative areas in the region must be determined before hand.

The Event -Based, Runoff -Energy Driven MUSLE: The second modified version of the USLE involves considerable change from the original

119 USLE. It was developed by replacing the rainfall energy factor with a runoff energy factor. The MUSLE runoff energy factor is a function of a product of runoff volume and peak runoff rate for an individual storm event and therefore applicable to larger areas than the original USLE (Dissmeyer and Smith, 1980) does. Since its introduction in Williams and Hann (1973),this version of the modified USLE, has been used in several other erosion /sedimentation models (Williams, 1975 (for areas < 25 mi2); Onstad and Foster, 1975; Fogel et al., 1977 (for areas < 150 mi2); Foster et al., 1977; 1980). The advantages of replacing this modified version over the original rainfall- energy factor driven one include: (1) increased accuracy as runoff provides most of the erosiveforces when compared to rainfall, (2) elimination of the need for delivery ratios as the runoff factor represents energy used in transporting as well as in detaching sediment particles, and (3) application to individual storm events. The third is particularly important when simulatingwater quality trends (Williams and hann, 1973; Blackburn, 1980).

Proposed Remodification of the USLE:The proposed modification will be designed to incorporate attributes of previous modifications plus some additional ones.The idea is to incorporate the modified USLE for forested areas ( Dissmeyer and Foster, 1980; 1981) into the runoff- energy driven one (Williams and Hann, 1973) to get a soil loss equation for individual storms on forest environments. some of the subfactor analysis techniques developed in the revised version( RUSLE) will also be considered in the proposed remodification.For example, the R- factor equivalent approach used to account for the combined effect of freezing soil and rain on snow or partly frozen soil (Renard et al. 1990) will be employed in the cold season module of the proposed remodified soil loss equation( RMSLE) for forest environment. The expression for the RMS LE is

oes Z = 95* (q, *Q) *V *LS (2 ] where Z = sediment yield from an individual storm in tons. qp = peak flow rate in cubic feet per second. Q = volume of storm runoff in acre -feet. K and V are as described above, and LS = the slope length and slope gradient factor. Spatial diversity in the modeling process will be captured using the latest geographical information system (GIS) technology. Map overlays of different forest watershed characteristics such silvicultural treatments, understory vegetation conditions, soil and topographic characteristics, land use and management factors, road density and utilization, climatic and hydrological trends, riparian areas, watershed drainage patterns and boundaries etc.

120 will be developed and integrated to generate spatially homogeneous unit polygons using SPANS software from TYDAC Technologies, Inc. Once these relativelyhomogeneoussubwatershedunits are so constructed, the net sediment yield from each unit is computed and eventually routed to the next unit in a cascading fashion. During this process, the model will allow multiple inputs into but not feedback loops from subwatershed units and there will only be one outlet from each subwatershed unit. Inputs will be in the form of hard data and map digitizing. Climatological and hydrologic data such as rainfall R, and runoff Q, may be measure on site.And such information will be incorporated with the GIS generated information to calculate Z, and determinechannelerosion and sediment deposition volumes in each unit.

In the absence of runoff and peakflow data, the Q and qp values for a particular forest watershed can be determined using the U.S. Soil Conservation Service's (SCS) rainfall- runoff relationship and peak runoff equations. The SCS rainfall- runoff equation is

2 Q R -I [3] (R -I +S) where Q = volume of storm runoff in acre -feet. R = storm rainfall in inches. I = initial abstraction S = potential maximum watershed retention in inches (including infiltration).

The initial abstraction I, is considered to be a function of S such that I = KS in which K is the constant of proportionality and is usually equal to 0.2. Also the value of S can be estimated using equation [4]

s. 1000 (4] CN io Where CN is the SCS curve number which is mainly a function of antecedent soil moisture condition, vegetation cover,and soil characteristics.During the development of the model, methods will be developed for assessing the CN value for each subwatershed unit.

Likewise, the peak runoff (qp) value in equation [2], can be determined using the following expression

ap 484*A*O [5] ( 0 . 5D+0 . 6TJ where qp and Q are as defined above. A= watershed area in square miles. D = duration of excess rainfall in hours, and Tc = Time of concentration in hours.

Substituting the terms Q and qp in equation [2] by equations [3] and [5], respectively, results in equation [6] which expresses the

121 amount of sediment yield per storm event (Fogel et al., 1977):

a o.sa-K(s]- z-95- 4 8 4 *A * ( R- I ) (6] 0.5*D+0.5*Tc)(R-I+S)2 in which all terms are as explained above. Z, in this case, is a function of the rainfall random variables R and D and if this variables are determined to be dependent on each other, then a bivariate distribution of R and D is needed to determine Z. Now, since our purpose is to find the total amount of sedimentyield per season, summer season in this case,the seasonal total, Z, can be determined using the expression Z, = Z1 + Z2 + ... + ZN [7] in which for a random number of events per season, N,the amount of sediment load in the individual events, Z1, Z2, ..., ZN are assumed to be mutually independent identicallydistributed random variables. Also R and N are considered independent from each other. Under these conditions, the probability distribution for the total seasonal sediment yield,ZS can be determined from the distributions of the random numbers N and Z as in Fogel et al. (1976)and Fogel and Tecle (1986). Also the mean, E(Z8)and variance Var(Z,) of the total seasonal amount of sediment load can be determined, respectively, using equations [8]and [9]if the means and variance of N and Z are known or canbe estimated from the data (Benjamin and Cornell, 1970) .

[8] E(Zs) = E(N) . E(Z) Var(Zs) = E(N) .Var(Z) + E(Z)2.Var(N) [9]

And assuming the ZS fits a two parameterprobability distribution function such as normal, log normal, or gamma, seasonalsediment yield values for any frequency can be determinedgraphically or using equations [8] and [9] (Fogel and Tecle, 1986).

The amount Zs is the total sediment yield from rill and interrill erosion only. The overall total sediment yield Sy, from a subwatershed which includes thatresulting from channel erosion can, therefore, be determinedusing

Sy = Z, + channel erosion - deposition [10]

Channel erosion includes gully erosion, streambank erosion, streambed degradation, floodplain scour,and other sources of sediment, excluding rill and interrill erosion. Estimation of channel erosion and sediment deposition can bedetermined using the methods in Chow (1964), and Henderson (1966).

The net sediment yield, Sy from the subwatershedunits is then cascade routed to provide the overall totalsediment yield from a

122 particular forest watershed. This total sediment yield can then be used by forest resources managers as a criterion during forest resource management decision making process.

Summary and Conclusions

Water - induced erosion and sedimentation are relatedprocesses that can adversely affect the economic and environmental conditions of an area. In the case of southwestern forest areas and their surroundings, erosion may remove the top soilfrom the land reducing its fertility and the capacity to support a balanced ecosystem. In addition, the resulting sedimentation may have both economically and environmentally a depressing effecton the area. If uncontrolled, sediment can degrade water quality, absorb and carry chemical and biological pollutants, reduce the aesthetic quality of water bodies, and drastically affect wildlife and fish habitat. Sediment deposits can also reduce the carrying capacity of waterways and channels,decrease the storage capacity and shorten the useful life of reservoirs and ponds.

In the southwest where the forested areas are considered to be major sources of water for both the expanding agro- industrial activities and the growing urban and rural water demand in the valleys downstream, a clear knowledge of the impact of vegetation management on the quantity and quality of water coming from the forested areas is very important. At present there is no any reliable method for estimating the amount of sediment that would be produced under different forest vegetation management schemes.

In spiteof the stern warning against such use by its developers (Wischmeier 1976), the USDA Forest Service stilluses the original USLE in its forest management planningprocess. And review of other models show that there are noany other models calibrated to represented the spatial and temporal variability in the area even though some efforts have been made to model sediment yield on a localscale (Simons et al., 1977;Rasmussen and Ffolliott, 1979).

Under such circumstances, this paper proposes two models that have the potential for reliability.One of the models is intended to meet the short term need while the other would be useful in the long term. The models are respectively, RMSLE and WEPP. The interest for parallel development of these models is basedupon their potentiality and time of applicability. The WEPP isa complex model currently under development and it will takemany years before it can be operationallyapplied in a forest environment. The RMSLE, on the other hand, will be developed by incorporating the most relevant attributes from previously developed and tried models.

The following are the most important attributes for developing the RMSLE for application to southwestern forest lands. (1)

123 Incorporation of a version of the USLE which has been modified for application to forest environments.The major contribution in this case is the specification of the vegetation cover subfactors. (2) Adoption of the event -based, runoff -energy driven version of the USLE which is more appropriate for estimating erosion and sediment yield because runoff and peakflows are the major factors that affect erosion and sediment yield processes. (3) Two part design, separating warm season and cold season erosion and sediment modules are made to reflect the two distinct climatological seasons in the area. However, only the general framework of the warm season module is represented by the methodology described in this paper. And (4)RMSLE will be designed to incorporate the most advanced technology. Such a technology will enable the model to handle the spatial and temporal variability inherent in southwestern forest ecosystem. It is expected that the above attributes will enable RMSLE to reliably assess and forecast the hydrologic and water quality impacts of different vegetation management scenarios. It is further hoped that the information so gained will help forest resources managers make better decisions.

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129 EFFECTS OF PLANT GROWTH REGULATORS, NITROGEN FERTILIZATION, AND IRRIGATION

ON ELDARICA PINE SEEDLINGS

Amal O. Darwiche and Peter F. Ffolliott School of Renewable Natural Resources, University of Arizona, Tucson, AZ 85721

Abstract

Effects of applications of cytokinin -like and gibberellic growth regulators, nitrogen fertilizer, and irrigation on the development of containerized eldarica pine (Pinus brutia var. eldarica) seedlings was studied in a greenhouse for 13 weeks. All concentrations of growth regulators reduced nitrogen content of needles and dry weight of shoots; importantly, medium and high concentrations also adversely affected root collar diameter growth and shoot elongation. Nitrogen fertilization alone was not significant in its effect on seedling development, due probably to the nitrogen -rich nature of the potting medium. It is suggested that contentration is a critical factor when applying growth regulators, as phytotoxicity of seedlings can result at high rates.

Introduction

Use of containerized seedlings is common in establishing forest plantations in dry regions of the world. However, only better -developed seedlings can compete and thrive in these harsh environments, where nutrients and moisture and nutrients generally are limiting. To increase the chances of seedling survival, it may be desirable to enhance the development of propagules in the greenhouse before planting the seedlings in the field.

Attempts to improve developmental growth of seedlings in the greenhouse stage include exogenous applications of growth regulators and applications of mineral nutrients. For example, foliar applications of a cytokinin -like compound (BA) and gibberellic acid4 +7 (CA) in combination with fertilizers applied to foliage have been beneficial to the shoot and root growth of Querucs alba seedlings (Dixon et al. 1984). In another study, gibberellins were reported to enhance shoot growth of Pinus ponderosa seedlings when applied as a root -soak during seedling dormancy (Heidmann 1982). Other studies on effects of growth regulators on tree seedlings can be found in the literature (Al- Kinani et al. 1981, Bidwell 1974, Coffman and Loewenstein 1973, Jensen and Dochinger 1972). The study reported upon in this paper was undertaken to test the effects of foliar applications of growth regulators, nitrogen fertilization, and irrigation on the development of containerized eldarica pine (Pinus brutia var. eldarica) seedlings.

Description of Study

The study, which lasted 13 weeks, was conducted in a greenhouse

131 environment at the University of Arizona, Tucson, in the spring -summer of 1987. One- year -old eldarica pine seedlings were transplanted into plastic pots, approximately 20 1in size, containing a mixture of organic peatmoss, perlite, and vermiculite in proportions of 74'/.,16 %, and 10% (v /v), respectively. One- hundred ppm of elemental phosphorus (from monocalcium) and an equal amount of elemental potassium (from potassium sulfate) were added to each pot on the first day of the study. All pots were irrigated regularly thereafter, with a watering regime such that only the upper 1.25 cm of the potting medium was allowed to dry between waterings, avoiding moisture stress. Average daily air temperatures in the greenhouse ranged between 24° and 32° C.

A four -replicate split -plot experimental design was chosen. Nitrogen fertilizing treatments were the main -plot factor, while growth regulating treatments constituted the sub -plot factor, with 4 treatment levels in the former and 7 treatment levels in the latter. Nitrogen fertilizer was 50% urea and 50% ammonium nitrate, applied at 0,10, 50, and 100 ppm in 2 1of tap water. The low concentration (10 ppm) was applied at each irrigation, while the medium and high concentrations were applied once every 4 weeks.

Growth regulators, specifically BA and a mixture of BA and GA (BA +GA), were applied only once during the study, on day 20. Seven treatment levels included a control and 500, 1,000, and 2,000 ppm of BA, and 500, 1,000, and 2,000 ppm of BA +GA, applied to the foliage in an aqueous solution using a portable sprayer- mister. Each seedling was sprayed from above, until the foliage was covered uniformly with a fine mist. Once dripping occured, spraying was stopped. This method of application had been used in other studies (Dixon et al. 1984, Lewis and Haun 1975). An acidifying -wetting agent was used in conjunction with growth regulators to ensure penetration through the thick waxy cuticle.

On the first day of study and periodically thereafter, root collar diameter and shoot elongation of each seedling were measured. Phytotoxicity was evaluated at the end of the study on a visual scale from (1) to (10),with (1) indicating a healthy seedling and (10) denoting death. Seedlings then were cut at the soil line, put into paper bags, and dried at 18° C.for 48 hours. Dried needles of each seedling were pulverized and digested in a block digestor for determination of nitrogen content by the K.jeldahl method (Bremner 'and Mulvaney 1982).

Analyses of variance were performed on all variables except phytotoxicity. Whenever study results were expressed as decimal ratios or ppm, an arc sine transformation was used. Orthogonal contrasts were employed to test for significant differences between BA and BA +GA. All differences reported are significant at the 5 percent level. Results of the statistical analyses performed are presented only qualitatively in this paper, however.

Results

The highest nitrogen contents of needles were associated with the no- growth- regulating treatment, with all other treatments resulting in lower nitrogen contents. Growth regulators were significant in their effects, while nitrogen fertilization alone was not. Orthogonal contrasts between BA and BA +GA at all levels also were not significant.

Dry weight of shoots at the end of study was lowered by all growth

132 regulating treatments. Nitrogen fertilization and its interaction with growth regulators were not significant, however. Low concentrations of both growth regulators and medium levels of BA +GA were less adverse in their effects than the other treatment levels. These results should be interpreted with caution, as the initial weight of the seedlings was unknown.

Growth regulators were significant in their effect on root collar diameter growth, expressed as a ratio of the increment to the root collar diameter at the start of study. Nitrogen fertilization did not affect root collar diameter growth. Interaction between the two factors, however, was significant.

No-growth-regulating and low nitrogen fertilizing treatments produced the greatest increase in root collar diameter growth. On the average, all growth regulating treatments, especially medium and high concentrations, were detrimental to root collar diameter growth. Moreover, a difference was detected between both growth regulators with a test of orthogonal contrasts, while the contrast between the low concentration of BA +GA and the no- growth- regulating treatment was not significant. This finding suggested that BA had a more adverse effect on root collar diameter growththan did BA +GA, although the latter was harmless when applied at low concentrations.

Results obtained for shoot elongation were similar to those found for root collar diameter growth. Only growth regulating treatments were significant, while both nitrogen fertilization and its interaction with growth regulators were not. Once again, BA +GA was less detrimental in its effects than was BA alone. Orthogonal contrast between the two growth regulators was significant. Contrast between the low BA +GA contentration and the no- growth- regulating treatments was not significant.

Visual evaluation of the seedlings showed that the no- growth -regulating treatment caused no phytotoxic effects, while high concentrations of both growth regulators resulted in phytotoxic symptoms. Other growth regulating treatments were intermediate in their phytotoxic effects. The effects of nitrogen fertilization were inconsistent.

Sixteen of the 112 seedlings initially transplanted into pots died by the end of study. One of the dead seedlings had received a medium concentration of BA,10 received a high concentration of BA, and 5 received a high concentration of BA +GA. It seemed, therefore, that BA alone was more lethal at high concentrations than was BA +GA.

Nitrogen fertilization had no effect on seedling development throughout the study, except in its interaction with growth regulators on root collar diameter growth and nitrogen content of needles. This finding could be attributed to the nitrogen -rich potting medium. Another complicating factor might have been the assignment of nitrogen fertilization regimes to the main - plot in the split -plot experimental design; this could have lessened the precision of measurements of the main -plot effects (Gomez and Gomez 1984). Nitrogen fertilization might have shown a greater effect had another potting medium and a different experimental design been used.

On the other hand, both growth regulators showed significant effects on the growth parameters studied, although these effects do not appear to be favorable to seedling development. Neither growth regulator significantly

133 enhanced root collar diameter growth. However, in an earlier study, gibberellin alone and when applied with auxim had a significant effect on phloem and xylem production in needles of Pinus brutia (Ewers and Aloni 1985).

Discussion

Other studies have shown that major hormonal stimuli for cambial growth comes from auxins, and that cytokinins and gibberellins can enhance auxin action; but, gibberellins and cytokinins rarely have an effect on cambial activity by themselves (Pharis 1976). Increases in root collar diameter growth of Quercus alba seedlings from applications of BA and GA have been reported, although lower concentrations (50 ppm) were used (Dixon et al. 1984). Concentrations of growth regulators applied in the present study, especially those of BA, proved somewhat phytotoxic to the growth processes of eldarica pine seedlings. Perhaps, that is what contributed to the decreasing rate of root collar diameter growth.

Nitrogen fertilization alone and its interaction with the growth regulators tested were not significant in terms of shoot elongation of the eldarica pine seedlings. This result agreed with earlier work (Dixon et al. 1984), indicating that shoot elongation was not affected by nitrogen fertilization, and that although shoot height was enhanced by 500 ppm of GA, this response was decreased by increasing concentrations of BA. In the present study, the fact that shoot elongation was decreased by all concentrations of BA and a high concentration of BA +GA, while low and medium concentrations of the latter were not different in their responses than the control, could be attributed to antagonism between cytokinins and gibberellins. The latter are known to enhance apical dominance, while the former are known to decrease it (Bidwell 1974).

Had GA been applied alone, an increase in shoot elongation likely would have resulted, as demonstrated in a previous study (Al- Kinani et al. 1981). Moreover, it is felt that the present study might have been terminated prematurely, just as shoot elongation in the BA +GA treatments had started to increase at a rapid rate. It would have been interesting to determine whether this sudden increase in shoot elongation was significant.

Nitrogen content of the needles was lowered by all growth regulating treatments, which could have been due to a redistribution of photosynthates and other nutrients within the seedlings. Both cytokinins and gibberellins are known to alter the normal pattern of photosynthate allocation (Dixon et al. 1984, Little and Loach 1975).

Some investigators have indicated that use of cytokinins and gibberellins results in a decrease in dry weight (and, at times, green weight) of seedlings (Bilan and Kemp 1962, Roberts et al. 1963), while others reported an increase (Dixon et al. 1984). However, the observed change in dry weight could be a function of the concentrations of growth regulators used, as reported elsewhere (Bilan and Kemp 1962, Dixon et al. 1984).

Conclusions

The concentrations of BA and BA +GA used in this study do not appear to have a positive effect on the development of eldarica pine seedlings. This conclusion was attributed largely to excessively high concentrations, which

134 caused phytotoxicity in some seedlings. In future studies, it would be interesting to experiment with lower concentrations thatare applied more frequently. Concentration, therefore, seems to be one of the more important considerations when applying growth regulators to promote development of tree seedlings. Timing also is an important factor in applyingexogenous growth regulators. The fact that applying more than one hormon substance had less adverse effects on seedling development than did the application of onlyone deserves further examination. Future studies should use nitrogen -poor potting media if the nitrogen fertilizator- growth regulator interaction is to be further investigated.

References Cited

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