computer program for estimating losses from …
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COMPUTER PROGRAM FOR ESTIMATING LOSSESFROM UNLINED AND LINED LATERAL
AND MAIN CANAL REACHES
prepared for
Imperial Irrigation Districtunder Work Order KB-02
prepared by
Keller-Bliesner Engineering95 West 100 South
Logan, Utah
June 30, 1992
COMPUTER PROGRAM FOR ESTIMATING LOSSESFROM UNLINED AND LINED LATERAL
AND MAIN CANAL REACHES
prepared for
Imperial Irrigation Districtunder Work Order KB-02
prepared by
Keller-Bliesner Engineering95 West 100 South
Logan, Utah
June 30, 1992
TABLE OF CONTENTS
LIST OF FIGURES ........................................... ii
INTRODUCTION ............................................ 1
OVERVIEW ............................................... 2Passive Losses ......................................... 3
Start-Up Canal Seepage Losses and Canal Filling Water ............ 3Steady-state Seepage ................................. 3
Important Parameters Affecting Steady-State Seepage ............. 5Evaporation Losses .................................. 6
Active Losses .......................................... 7Shutdown Losses ................................... 7Flow-Management Losses .............................. 10
DEVELOPMENT OF THE SEEPAGE INFERENCE MODEL ................ 10Ponding Test Data ....................................... 10Seepage Model Development ................................. 12Limitations of the Seepage Inference Model ........................ 14
CYCLIC AND GEOMETRIC DATA INPUT AND MANIPULATION ........... 17Cyclic Analysis ......................................... 17Canal Geometry and Depth to Water Table ........................ 17Soil Permeability ........................................ 19
COMPUTATION OF LATERAL LOSSES AND SAVINGS FROM LINING ....... 19Start-up Seepage Loss Savings ............................... 19Steady-State Seepage Loss Savings ............................. 21Evaporation Loss Savings ................................... 22Shutdown Loss Savings .................................... 22
SCREENING TEST RUNS USING LATERAL PROBE ..................... 24
RECOMMENDATIONS AND CONCLUSIONS ......................... 24
REFERENCES ............................................. 26
APPENDIX A - Data Summary of Ponding Test Data Used to Developthe Steady-State Seepage Inference Model ............. 27
APPENDIX B - Lateral Canal Screening for Lining Candidates ................ 29
LIST OF FIGURES
Figure 1.
Figure 2.
Figure 3.
Figure 4.
Figure 5.
Figure 6.
Figure 7.
Canal seepage geometry for different boundary conditions ............ 4
Schematic drawings depicting shutdown losses resulting from a typical sequenceof turnout gate and corresponding check operations ................. 8
Typical canal cross-sections for lined and unlined lateral canals ......... 9
Geometry and symbols for channels in soil underlain by impermeable material(from Bouwer, 1969) ................................... 13
Scatter and residual plots for laterals with a water surface widthgreater than 20 ft ..................................... 15
Scatter and residual plots for laterals with a water surface width equalto or less than 20 ft .................................... 16
Typical lateral canal cross-sections showing changes between the time theearly E-drawings were made and conditions prior to lining ............ 18
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COMPUTER PROGRAM FOR ESTIMATING LOSSESFROM UNLINED AND LINED LATERAL
AND MAIN CANAL REACHES
INTRODUCTION
Lateral canal lining is a major project activity under the IID/MWD Water ConservationAgreement. In fact, the initial Agreement document assumed 29,150 Acre-Feet per year ofwater savings would be realized from lining 265 miles of lateral canals at a capital cost of$42,674,000.
The assigned task for this activity was to develop a computer program for screeningunlined lateral canal reaches to identify candidates for lining that will provide the most watersavings at the least cost. The program is to provide for the estimation of water losses due tostart-up seepage, steady-state seepage, evaporation, and shutdown losses.
We call the computer program developed in response to this assigned task Lateral Probe.The program flows as follows:
First it determines the cyclic nature (number of on-off cycles per year, thenumber of days on per cycle, the average flow rate per cycle, etc.) for each reachof a given lateral.
Then from the cycle characteristics, reach geometry, and seepage parameters, theprogram estimates (calculates) the start-up and steady-state seepage, evaporation,and shutdown losses for each unlined reach. Estimates of these losses are alsomade for each unlined reach as it would be if it were lined.
The estimated conservation water savings that are expected from lining each reachare then assumed to be the difference between the estimated unlined and linedreach losses.
Three separate visits were made to Imperial under this work order. The first visit wasmade to discuss the data requirements for lateral screening with IID staff and verify that theprogram development was progressing in line with the perceived needs. The second visit wasmade upon completion of the first phase of program development to review the results for ourscreening test runs on 29.0 miles of laterals with IID staff and transfer a preliminary version ofLateral Probe to them. The purpose of the third visit was to transfer Lateral Probe to IID’stechnical staff and instruct them on how to efficiently do the necessary data take-off for programinput.
We began our initial work involving conservation savings resulting from lining lateralcanals by developing a rational analytical overview and technical background of the mechanicsof unlined and lined canal operational losses. This is presented in our report "Critique of theConservation Program’s Lateral Canal Lining Verification Plans and Procedures" submittedFebruary 12, 1992 in fulfillment of our Work Order KB-01. The overview section that followsgives a condensation of the analytical overview and technical background sections presented inour earlier report to provide a foundation for understanding the logic and development of LateralProbe.
OVERVIEW
We separated unlined lateral canal operational losses into five elements (or categories)that would be reduced by lining a canal. These are:
1. Seepage losses during the start-up period;
2. Steady-state seepage losses following the start-up period;
Evaporation losses from the canal water surface (and evapotranspiration fromassociated weeds along canals);
Flow-management losses resulting from the necessary daily changes in deliverylocations and flow rates; and
5. Losses associated with the water remaining in canals when they are shutdown.
Except for evaporation the relative magnitude of each of these losses and the potentialwater conservation resulting from lining a canal depends on the physical site characteristics andcanal operational activities. For example, the ponding tests demonstrate that canal start-upseepage loss rates are significantly greater than steady-state seepage rates. For canals that arealmost always operating full the effect of accounting for the additional losses during theoccasional start-up periods would be relatively small. However, for canals that are cycled onand off frequently, accounting for the higher seepage loss rate during the start-up of unlinedcanals can add appreciably to the expected savings of lining. Similar statements or argumentscan be made for losses following shutdown.
The five classes of losses listed above can be divided into two groups: those independentof and those dependent on how the operators manipulate the flows, or "passive losses", and"active losses" respectively. Being independent of operator finesse, the passive losses(associated with evaporation and seepage) are mainly functions of physical factors. They canbe objectively defined and estimated using suitable numerical models based on field data.
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Defining and estimating the active losses require subjective reasoning since they aredependent on the interactions between operational skills and physical conditions. They dependon the manner in which flows are manipulated as well as the physical site conditions and flowchanges required. Thus estimates of the active losses (associated with shutdown) based on thedirect physical analysis used in devdoping Lateral Probe are subject to interpretation.
The conservation savings resulting from reductions in flow-management losses due tolining must be determined indirectly. Unfortunately estimating losses using inflow and outflowdata is even more difficult due to the inaccuracies of flow measurement and to the additivenature of active losses with other system losses.
Passive Losses
We consider start-up seepage, steady-state seepage, and evaporation as passive losses.Other than the opportunity time and cyclic nature of their occurrence they are independent oflateral operation and operator skills and are mainly dependent on canal geometry, soilcharacteristics, and evaporative demand.
Start-Up Canal Seepage Losses and Canal Filling Water
For canals cycled on and off, the cumulative seepage volume over a given length of timeis greater during the initial wetting period than after reaching a steady-state seepage rate. Thehigher accumulation during the initial wetting results from saturating the soil near the canal andthe generally higher energy gradients during the start-up period. We call this difference betweenthe two accumulations the start-up seepage loss.
In addition to the water loss through start-up seepage there is the volume of waterrequired to fill the canals and to build the check ponds. None of this canal filling water isactually loss until shutdown. Therefore, we deal with any potential losses of this water as ashutdown loss to avoid the possibility of double counting.
Steady-state Seepage
The three basic canal steady-state seepage conditions of primary interest in developingLateral Probe are described below.
Free drainage to a deep water table--This is a rare condition for IID lateralsdue to the perched ground water caused by shallow lenses of low permeabilitysoil. However, losses from the start-up of a dry canal is a special case of freedrainage (see Fig. 1 A) until the wetting front reaches the groundwater table.
3
Zonec.,o~%.,o.o.) \
WATER TABLE
Geometry of Flow Zone Following Start-up Before Wetting FrontReaches Water Table.
Flow Zone(Saturated)
Initiol W~ter foble
ao Geometry of Wafer Table After Seepage System has ApproachedEquilibrium.
Clogged Loyer J
¯ WATER TABLE
Geometry of Unsaturated Flow Zone Resulting from Thin Clogged(or sealed) Layer.
Figure 1. Canal seepage geometry for different boundary conditions.
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During this start-up period the seepage rate is unaffected by the position of thewater table and will be relatively high. Of course the length of time involved forthe wetting front to reach the groundwater table is proportional to the distancebetween the bottom of the canal and the water table (Dw - H) in Fig. 1 A. Thismay be the dominate seepage condition for laterals that do not operate for morethan 4 consecutive days and are empty for as long as they are full.
Steady-state seepage affected by the depth to a shallow water table--Figure 1Bshows the geometry of the water table after an unlined channel with negligiblebed clogging has been operating continuously over an existing shallow watertable. This would be a typical case for IID lateral and main canals that areperiodically cleaned and kept nearly filled most of the time. As the seepage flowsystem approaches equilibrium the flow region adjacent to the canal becomes fullysaturated and the water table rises.
Due to the proximity to the water table, the seepage rate is less than the freedrainage situation. The amount of reduction over the "free drainage" situationis a function of: the depth of the water in the channel, H; the channel’s topwidth, B; the saturated permeability of the underlying soil and aquifer; theposition of the water table; and the depth to the impermeable (or lowpermeability) layer causing the high water table. In our analysis we used theavailable1 rationally developed equations, parameters, and techniques for dealingwith the effects of high groundwater table conditions.
Seepage from a channel with a bed clogged by organic matter and/or silt--Asclogging increases between cleaning cycles a canal starts to seal and the seepagerate is considerably reduced. Figure 1C shows the geometry of the unsaturatedflow zone resulting from a thin clogged (or restrictive) layer along the wettedperimeter. In this case the water table may hardly be changed due to the smallamount of seepage water reaching it. The rate of seepage from such cloggedlateral canals is a function of: the permeability and thickness or hydraulicresistance of the clogged layer; the depth of water in the channel, H; and thetension (negative soil water pressure) in the unsaturated flow zone.
Important Parameters Mfecting Steady-State Seepage
The following parameters are necessary to normalize the ponding test data so that seepageis not site and situation specific. Thus they are also the key parameters necessary for developingthe steady-state inference model for Lateral Probe.
See references: Bouwer, H. 1969 and 1991; Harr, M.E., 1962; and U.S.B.R., 1978.
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The hydraulic conductivity, K, which is a measure of the resistance to seepageflow and is the unit flow rate when the head gradient is 1.0. The K must bemeasured either in situ or from undisturbed soil samples, both of which have theirpractical limitations. Typically the horizontal conductivity is greater than thevertical conductivity due to both micro and macro soil layering. Furthermore,K is closely related to soil texture. Since there is extensive spatial variability insoil texture, there is also considerable variability in K.
The most important geometric factors with respect to seepage are the width of thewater surface and the water depth in the center of the channel (Bouwer, 1969).The water surface width, B, (see Fig. 1 A) is important because it is thehorizontal area through which the vertical component of seepage occurs. Thewater depth, H, is critical because it represents the vertical areas through whichthe horizontal seepage component occurs. The water depth is also the head thatprovides a major part of the driving force that induces seepage flow through thewetted perimeter.
Both the depth to the perched water table, Dw, (see Fig. 1 A) and the depth the restricting layers causing the water table affect seepage losses under shallowgroundwater conditions. Canal seepage above shallow groundwater tends tocreate a mound in the water table. As this mound builds the head gradient isreduced, this in turn decreases the rate of seepage. The thickness of thegroundwater zone above the top restrictive layer affects the rate at which themound builds. The thicker the zone is the slower the rise in the groundwatertable mound.
Evaporation Losses
Evaporation losses from unlined canals occur from the water surface, the capillary fringe,and the phreatophytes growing along canal banks. For lined canals the evaporation loss islimited to the canal water surface.
Only the estimated evaporation loss from the free water surface is considered in theponding tests. Thus, any other evaporative losses appear as additional seepage. This is not aproblem except when trying to normalize ponding test data under different evaporative demandand canal vegetation conditions. For example, assume the effect of canal vegetation pluscapillary fringe is equivalent to extending the evaporative surface 3 feet to either side of thecanal. During periods of high evaporative demand (0.5 inch/day) this additional evaporation losswould be roughly 12% of the average steady-state seepage rate. However, during low demand(0.1 inch/day) periods the additional evaporation loss would be less than 3
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Active Losses
Flow-management and shutdown losses are dependent on how the operators manipulateflows. Thus we class them as active losses, and defining and estimating them requires subjectivereasoning since they are dependent on the interactions between operational skills and physicalconditions.
Shutdown Losses
A portion of the volume of water required to fill the canals and build the check pondsis lost after shutdown. The volume of the canal filling water is equal to the average crosssectional area times the length of the canal section involved. At shutdown all of this waterwould be lost through spilling, seepage, and evaporation if there is not a downstream opportunityfor utilizing it.
Figure 2 is a schematic showing a longitudinal-section of a lateral canal with threereaches. It is presented to provide an image of what we mean by shutdown losses. It alsoshows how a typical sequencing of turnout gates and corresponding check operations mightinfluence the shutdown losses.
There is a potential shutdown loss at the end of each canal delivery cycle. Therefore,shutdown losses are relatively small for canals that operate almost continuously. However, theymay be very significant for laterals with many delivery changes and end reaches that are cycledon and off frequently.
To a great extent the amount of shutdown water lost is dependent on the Zanjero’s abilityto utilize the water downstream during that or subsequent delivery cycles. We assume theannual shutdown water saved by canal lining is equivalent to the difference between the unlinedand lined cross-sectional volumes. The annual savings is that difference times the number ofcycles in an average year where the water can not be or is not used downstream and is spilled.
The cross-section areas of unlined channels is often much greater than for thecorresponding lined section, especially in the checked pond areas (see Fig. 3). (For an assumedaverage reach length of one-half mile and a typical difference between unlined and lined crosssectional areas of 16.5 ft 2 the volume difference would be about one AF per reach.) Therefore,the potential shutdown loss saving resulting from lining can be quite significant. Furthermore,the reduction in shutdown losses afforded by lining can be a significant portion of the water thatcould otherwise be saved by lateral intercepter canals.
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Lateral Slope = 0.001 Gives 2.0 ft Fall/ReachDrop =I.0 ft; Checked Depth = 4.0 ft; Normal Flow Depth = 3.0 ft Heading
Gate ~ . ~ .1
Turnout
#2 / Gate v
#3 ~~ ...... M~-~in
Reach = 2000 ft
Days I & 2 -- Delivering Water Through TurnoutDrain
~ater Through Turnout
Shutdown Loss
Figure 2. Schematic drawings depicting shutdown losses resulting from a typical sequenceof turnout gate and corresponding check operations.
TOWNSHIP LATERAL
~ 1990 Survey
~~-- Co~ ~ Ear::re:aen::ning
Difference in CrossSection Area = 81.6 sqft
WISTARIA LATERAL
X~~~ Elev 988 ~-STA 3+00
~ 1991 Survey
Concrete LiningDifference in Cross-/ ~\~y~’x(~z~zYvx~.~ Section Area= 47.4 sqft ~- Earth Canal
5 0 5 10 It
SCALE
Figure 3. Typical canal cross-sections for lined and unlined lateral canals.
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Flow-Management Losses
Flow-management losses result from the necessary daily changes in delivery locations andflow rates. We confirmed the existence of these losses in discussions with zanjeros. They addto the sum of their delivery orders an additional amount of water to cover their estimate ofoperational losses. Some zanjeros order about 1 cfs of operational water for each mile ofunlined canal reach and no operational water for lined reaches. This far exceeds the sum ofcanal filling water, start-up and steady-state seepage losses, and evaporation losses for unlinedas compared to lined canals.
Some potential causes of these apparently large flow-management losses in unlined canalsare: priming and filling canals; building ponds at checks; and handling check and gate settingsduring the 4 to 6 hours of unsteady fiow conditions following the setting of a new deliveryschedule. However, we did not attempt to make a detailed analyses of flow-management lossesbecause they are essentially dynamic losses dependent upon how each zanjero operates hislaterals. Therefore, flow management losses depend almost exclusively on human behavior andwe did not attempt to simulate this in Lateral Probe.
DEVELOPMENT OF THE SEEPAGE INFERENCE MODEL
The Imperial Irrigation District has been performing ponding tests in numerous lateralsfor screening and verification purposes for the lateral lining project. Our task has been to lookat the test data and develop a reliable seepage inference model that can be used to predictseepage losses on the untested lateral reaches throughout the district. This section of the reportdescribes our analysis of the seepage test results, the steps we used in developing the seepageinference portion of Lateral Probe, and the current form of the seepage inference model.
For the steady-state seepage loss we derived a physically based seepage inference modelthat relates the basic seepage rate to the soil hydraulic conductivity, canal top width and depth,existence of a clogging layer, and depth to the water table and impermeable layer. Then weused statistical analysis to correlate hydraulic conductivity measured in the tests to soil type andother parameters (water temperature, canal maintenance, etc.). This required a rigorous detailedanalysis of the data from all ponding tests completed to date.
Ponding Test Data
We worked with data from all of the ponding tests conducted from lune 1989 throughAugust 1991. The data from the tests consisted of periodic (over time) measurement readingsof water surface elevations, average water surface widths, pan evaporation readings, and watertemperatures.
i0
We applied various seepage models during the process of interpreting the ponding testresults and found that they fit the Philip equation reasonably well. The form of the Philipequation we used is:
where: Vs is the cumulative seepage volume; t is the lapsed time since the beginning of filling;Sp is a soil parameter called sorptivity; and Ap is the basic seepage rate. The sorptivity isdependent on soil water content and is higher for dry soil conditions than for wet conditions.Both Sp and Ap can be estimated by multiple linear regression of the cumulative seepage againstboth the square root of time and time.
The regression fit of each set of ponding test data to the Philip equation was used as anindicator of the validity of the test. Most of the tests appeared to have yielded reasonably gooddata, but the data from a few tests gave erratic results and were excluded from further analyses.
We also corrected the ponding test seepage data for the declining depth of water (head)in the ponded reach using an adaptation of the USBR’s seepage estimation equation. The USBR(1978) channel seepage formula for free drainage conditions (the likely case when the changein head is significant) is:
K(B + 2H) (2)qs"3.5
where qs is the seepage rate, cubic feet per linear foot of channel per day; K is the hydraulicconductivity adjacent to the channel, feet per day; B is the width of water in the channel, feet;H is the depth of water in the channel, feet; and 3.5 is the factor used by the USBR to adjusthydraulic conductivity test values to seepage losses from ponding tests.
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Assuming the effective hydraulic conductivity is the same for the range of depthsoccurring during a ponding test, Eq. 2 can be written to adjust for falling head. Thus,
(B~ + 2H~) (3)
where qs is the corrected steady-state seepage rate; qest is the estimated steady-state seepage ratefrom the ponding test; Bt and H1 are the average water surface width and depth respectively atthe beginning of the ponding test; and B2 and H2 are the average water surface width and depthrespectively at the end of the ponding test.
The table in Appendix A lists the steady-state seepage rates, corrected for falling head,used to develop the seepage inference model.
Seepage Model Development
Choosing a suitable model for calculating seepage losses from unlined channels is difficultbecause hydraulically seepage is a nonlinear phenomenon and the published equations treatseepage as a linear process2. After using several different derivations and attempts at fittingthe ponding test results, we found the test data fit the Ernst equation reasonably well andselected it for our seepage inference model. The Ernst equation makes use of the geometry ofthe channel, the depth to water table, and the presence of impermeable material. The parametersrelevant to the Ernst equation under conditions of free drainage and a perched water table areshown in Fig. 4.
The Ernst equation is a combination method, meaning both regions of curvilinear (radial)flow and Dupuit-Forchheimer (horizontal) flow are considered in the derivation of the equation.The form of the equation we used is:
log((D~ + H.)IWP) Z.+
2x(Di + R,,,-(4)
2An excellent discussion on seepage losses is found in "Theory of Seepage From OpenChannels", by Herman Bouwer, Advances in Hydroscience, vol 5, pp 121-172 (1969).
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IHw~ W,-’ITER TABLE IDw
L
IMPERMEABLE
Figure 4. Geometry and symbols for channels in soil underlain by impermeable material(from Bouwer, 1969).
where Is/K is a dimensionless ratio consisting of the basic seepage rate, Is, with units of velocityand the hydraulic conductivity, K, with units of velocity; Dw is the depth to water table relativeto canal water surface; Ws is the canal’s water surface width; Di is the depth to impermeablelayer; Hw is the depth of water in the canal; WP is the wetted perimeter; and L is the horizontaldistance to Dupuit-Forchheimer flow, taken as 10 times the bottom width.
To apply the ponding test conditions to the Ernst equation, the necessary geometricparameters for each lateral were taken from the cross sections presented in the most recent E-drawings. The depth to the water table was taken from the most recent observation well data(1974-1976) and water table elevations in drains depicted on the E-drawings. The water tabledata obtained in conjunction with the ponding tests were not used since these data were takentoo close to the lateral and were not referenced to the canal invert or any other benchmark.
Dividing the basic seepage rates from the ponding tests by the Is/K ratio calculated in theErnst equation, gives an estimate of the hydraulic conductivity, K, for the test reach. Usingmultiple regression, we correlated these estimates with other test parameters thought topotentially influence the estimated hydraulic conductivity-- the SCS estimate of soil hydraulicconductivity CKscs), maintenance frequency, water temperature, bank vegetation, and the portionof the year water is in the canal (percent on time).
The hydraulic conductivity for each reach was calculated in the manner described aboveand the screening statistics (mean squared error, Mallow’s C, 2, PRESS) for all p ossibleregression equations were calculated. The permeations of soil hydraulic conductivity,maintenance frequency, water temperature, bank vegetation, and the percent on time result ina total of 63 regression equations.
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The most suitable (best fit) value for the soil hydraulic conductivity was found to be themaximum value in the SCS permeability range given for each soil type at the depth of the canalinvert. The percent on time was the percentage of a year that the canal contained water. Watertemperature was coded as degrees Fahrenheit. The maintenance frequency was coded 0 or 1(none or otherwise). Vegetation was treated as 0, 1, or 2 (light, moderate, heavy). Values these parameters are given in the table in Appendix A together with the corrected basic seepagerates and the hydraulic conductivities calculated using the Ernst equation for the lateralsconsidered to have good to excellent ponding test data.
Based on the screening statistics many different multivariate regression models wereinvestigated. As the investigation proceeded, it was found that large canals and laterals (watersurface width Ws greater than 20 ft) appeared to have lower relative seepage losses thannarrower laterals. From our analysis of the ponding test data for large laterals (Ws > 20 ft),74% of the variability in the hydraulic conductivity estimated by the Ernst equation wasexplained by the SCS estimate of permeability (Kses). All other parameters were statisticallyunrelated to the Ernst estimate of hydraulic conductivity. For small laterals (Ws < 20 ft), 74%of the variability in the hydraulic conductivity could be explained by Kses and the percent ontime. All other parameters were statistically unrelated to the Ernst estimate of hydraulicconductivity.
The final regression equation derived for the hydraulic conductivity (Kw) of wide lateralsand canals with water surface widths greater than 20 ft is:
Kw (in/hr) = 0.630904 * Kscs (5)
The best fit regression for narrow laterals with top widths equal to or less than 20 ft is:
Kn (in/hr) = 0.227933 * Kscs + 0.00250 * Percent On Time
Figure 5 shows a plot of the calculated hydraulic conductivities plotted against the lengthweighted SCS estimated permeability for the soil layer at the invert of the wider lateral canals.A plot of the ordinary residuals against the calculated hydraulic conductivities is also includedto show the randomness of the residuals. Figure 6 shows a similar set of plots for the narrowerlateral canals.
Limitations of the Seepage Inference Model
The ponding test data covers a range of soil hydraulic conductivities from about 0.2 to4.6 in/hr. However, some unlined lateral reaches that are among the best candidates forconservation savings through lining have Kses values greater than 4.6 in/hr. When we usedLateral Probe to predict the estimated steady-state seepage losses from such laterals we obtainedvalues as high as 500 to 600 AF/Yr/Mi. Such values are higher than we would have expectedas heretofore the usual high values ranged from 200 to 300 AF/Yr/Mi.
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3.5
3.0
2.5
2.0
1.5
1.0
0.5
0.00.0 ~’.o 2’.o ~’.o .’.o ~’.o
Kscs (in/hr)6.0
1.5
1o0°
0.5"
0.0
-1.0
-1.50.0 ~’.o ~’.o z’.o .’.o s’.o ~.o
Kscs (in/hr)
Figure 5. Scatter and residual plots for laterals with a water surface width, Ws, greater than20 ft.
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3.5"
3.0
2.5
2.0
1.5
1.0
0.5 = ¯ Ilk
0,0 ~’.o =’.o ~’.o ,~’.o ~’.o ~.oKscs (in/hr)
1.5
1.0’
0.5"
" ,==-0.0 I m~l
-0.5
-1.0
-1.50.0 ’0 ’ ’~. £o ~.o ~:o s.o 6.0
Kscs (in/hr)
Figure 6. Scatter and residual plots for laterals with a surface width, Ws, equal to or lessthan 20 ft.
16
Extrapolation beyond the study range should be done with caution with any regressionmodel. Our seepage inference model is not an exception as extrapolation into highly permeablesoils appears to give inflated estimates of seepage losses. Fortunately some ponding tests at siteswith very permeable soils are scheduled for later in 1992. The new data obtained from theseponding tests can be easily incorporated into the model.
Observing the plot of the ordinary residuals against the calculated hydraulic conductivityin Fig. 6 for narrow laterals it seems that for the high SCS permeabilities the estimated valuesof K are too low. We suspect that when the new ponding test data for highly permeable soilsis incorporated in the model the K values may be as much 1.5 times as high. This will causethe estimated steady-state seepage from lateral reaches in the most permeable soils to only beabout 67% as high as our current seepage inference model now predicts.
CYCLIC AND GEOMETRIC DATA INPUT AND MANIPULATION
The main inputs required for Lateral Probe are data that describe the cyclic nature, canalgeometry and depth to water table, and soil permeability along each canal reach.
Cyclic Analysis
The cyclic analysis required developing an algorithm that determines the cyclic nature(number of on-off cycles per year, the number of days on per cycle, the average flow rate percycle, etc.) for each reach of a given lateral. It is based on the configuration of checks andturnouts along the lateral and incorporates a "CFS" file spanning multiple years. We completedthe cycle analysis portion of the modeling effort under the final amendment to Work OrderKB-01o
Canal Geometry and Depth to Water Table
For screening purposed we have been using canal cross-section data taken from IID’s E-drawings. Most of these drawings depict channel conditions that existed over 10 or 20 years agoand the present cross-sections may be quit different as indicated in Fig. 7. However, we feelthe E-drawings still represent average conditions that are suitable for lateral screening purposes.When Lateral Probe is used for verification purposes, up-to-date E-drawings will be availablesince new surveys must be made to estimate the quantities of earth work necessary to reshapethe channels prior to lining them.
The depth to the surrounding water table is available from IID’s (1974-1976) observationwell data bank and water table elevations in drains depicted on the E-drawings. Much of this
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TOWNSHIP LATERAL
929~ .......~x 269+50~x Elev.
xxx~1990 Survey
"~ ~x f ~_ STA 270+00~. ..... I968 Survey
WISTARIA LATERAL
V Elev. 984.5
%
STA 17+901991 Survey
STA 18+001979 Survey
5 0 5 10 ft
SCkLE
Figure 7. Typical lateral canal cross-sections showing changes between the time the earlyE-drawings were made and conditions prior to lining.
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data if fairly old and taken from observation wells that are not too well situated for ourpurposes. Nevertheless, we feel the depth to the water table underlying most of the district isfairy constant so the available data is sufficient for lateral screening purposes. However, insome cases it would be prudent to collect better situated and more timely water table data forconservation verification purposes.
Soil Permeability
For the SCS soil survey maps each soil mapping unit is assigned a general permeabilityrange. The ranges used are: slow (0.06 to 0.2 in/hr), moderately slow (0.2 to 0.6 in/hr),moderate (0.6 to 2.0 in/hr), moderately rapid (2.0 to 6.0 in/hr), or rapid (6.0 to 20.0 in/hr).
In developing our steady-state seepage inference model we found characterizing the soilpermeability by using the maximum SCS value given for each soil type at the canal invert gavethe results. Therefore, for entering the soil characteristics in Lateral Probe for reaches withina single mapping unit we use the maximum SCS permeability value given for the soil type at thecanal invert. For reaches traversing multiple mapping units we use the length weightedaverage of these values.
COMPUTATION OF LATERAl, LOSSESAND SAVINGS FROM LINING
Start-up and shutdown losses depend of the number and length of lateral canal delivery/on-off cycles during normal operations for each reach (canal length between checks). determine the number and duration of the cycles, Lateral Probe uses daily lateral deliveryrecords from the appropriate CFS files for the canal under study. On-times for some reachesnear the ends of laterals may be as little as 5 % of the time, while some of the head reaches mayin use practically 100% of the time. The average number of cycles per year ranges from 1 forlateral reaches that are always in use to roughly 100 cycles per year for reaches with the mostcycles. The overall average number of cycles appears to be in the neighborhood of about 30cycles per year.
Start-up Seepage Loss Savings
For this first phase of Lateral Probe development (at least until more ponding test dataare available) we have used the pore filling strategy described below to estimate the start-upseepage losses in unlined lateral reaches. We took this approach because the available pondingtest data do not include the volume of water required to fill the pond and large voids at thebeginning of the test. Nor are the data adequate to differentiate the time dependent portion ofseepage from the steady-state seepage.
19
The length of time a canal reach is dry determines the change in soil water content in thepreviously saturated soil zone below the canal’s wetted perimeter. This in turn affects theamount of start-up water required. Lateral Probe uses a start-up loss estimating procedure thatis dependent upon the change in soil water content as this soil zone becomes saturated againwhen the canal reach is conveying water.
The model applies the following procedure to each unlined lateral reach individually usinglength weighted values for reaches with large cross-section geometry or soil type changes.
The cross-sectional area that can be wetted is assumed to be the sum of the bankand bottom storage areas from the elevation of the water surface down to the topof the capillary fringe above the groundwater table. It is estimated from thelength weighted values for the geometry of the lateral cross sections taken fromthe E-drawings and the depth to the surrounding water table taken fromobservation well data.
The mean time (in days per cycle) between on/off cycles (TBC) for each lateralreach is calculated as:
TBC = (365.25 day/yr - cycles/yr * average on-time)/cycles/yr
This represents the average length of the period when there is no flow in thelateral reach and the wetted soil zone about the lateral can drain to a watercontent less than saturation.
o The percent change in water content for the mean TBC for each soil type (takenfrom SCS Soil Survey maps) is estimated using soil water-content data taken fromIsraelsen and Hansen3. We assumed a free drainage and evaporation rate of twodays from saturation to field capacity and 30 days from saturation to the wiltingpoint. On this basis we fit an exponential curve relating the change in soil watercontent to the drainage/evaporation opportunity time for each soil type. (SeeAppendix A of the Lateral Probe User’s Guide.)
JThe start-up seepage loss is estimated to be the product of the percent water-content change, the average cross sectional area, the reach length, and the numberof on/off cycles per year for that lateral reach.
For lined canals we assume the start-up seepage loss would be negligible. Therefore, allof the start-up seepage loss estimated for the unlined canals would be conserved by lining.
3Table 3.1, page 52, Irrigation Principles and Practices, 4th Ed., 1980.
20
We believe this procedure for estimating start-up seepage losses may give conservativeestimates. This is because the information available from the existing ponding test data is notsufficient for estimating the potentially large volume of water required to fill cracks and burrowholes. However, data being collected form the constant head tests planned under the revised on-going ponding test program should be sufficient for validating and calibrating the aboveprocedure and estimating the quantity of water used in filling large voids.
Steady-State Seepage Loss Savings
The following procedure is used in Lateral Probe to compute an estimate of the seepagelosses for unlined canal reaches. It is applied to each individual unlined canal reach using lengthweighted values for reaches with large cross-section geometry or soil type changes.
1. The geometry of the lateral cross sections is determined from IID’s E-drawings.
The depth to surrounding water table is calculated from observation well anddrain data.
o Characteristic soil permeability data are taken from SCS Soil Survey maps usingthe maximum value given for the soil type at the canal invert. A net permeabilityweighted by the lengths of the different soil types along each reach is calculated.
o The ratio of the basic seepage rate to hydraulic conductivity (Is/K) is thencalculated using the Ernst equation, Eq. 4.
Then the estimated hydraulic conductivity, I~ or Ka, is calculated using theappropriate equations for wide or narrow channels as presented in Eqs. 5 and 6.
° An estimate of the appropriate average seepage rate I~ for the canal reach is thencomputed by multiplying the Is/K ratio found in step 4 by the hydraulicconductivity, Kw or Ka, found in step 5.
The estimate of the steady-state seepage loss for the unlined reach is thencomputed as the product of the reach’s estimated average seepage rate, width ofwater surface, length, and annual on time. The reach’s annual on time iscomputed in the cycle analysis using data from the appropriate CFS files.
Lateral Probe then computes an estimate of the seepage/leakage loss from thecorresponding reaches of lined canals as follows:
o The wetted perimeter of the lined reach is calculated from the canal geometry anddepth of water data.
21
The seepage loss is estimated as the product of the wetted perimeter, the reachlength, an assumed seepage/leakage rate for concrete lining and the annual ontime.
The final step is to compute an estimate of the potential conservation savings expectedfrom lining the reach to reduce the steady-state seepage losses that occurred along it prior tolining.
10. The estimated steady-state seepage loss conservation savings is the estimated lossalong the unlined reach found in step 7 minus the estimated seepage/leakage lossthat would (or does) occur after the reach is (or was) lined.
Evaporation Loss Savings
In Lateral Probe the same procedure is used to calculate an estimate of the evaporationlosses for both unlined and lined laterals. The loss savings attributed to lining are calculated inthe following order:
The area of the water surface is calculated from the canal geometry, water depthand reach length.
o The estimated evaporation loss is the product of the water surface area, thepercent on time for the lateral reach, and the net annual evaporation.
The estimated evaporation savings resulting from lining is the difference betweenthe estimated evaporation loss from the unlined compared to the lined reaches.
Shutdown Loss Savings
We assume the annual shutdown water saved by canal lining is equivalent to thedifference between the unlined and lined cross sectional volumes times the number ofdelivery/on-off cycles that cause lateral spillage during an average year. The volume differencedepends on whether the reach is checked and thus operating at a high stage or unchecked andoperating at a lower level or stage.
The same procedure is used in Lateral Probe to calculate shutdown losses for both theearth and lined laterals. It is applied individually to each lateral reach and length weightedvalues are used for unlined reaches with large cross-section geometry changes. It is designedto allow for water released from up-stream ponds to be used for downstream deliveries providingthere is a down-stream delivery order within one, two, or three days. In other words theprogram provides the option of conserving some of the ponded water by holding it in the ponds
22
for up to three days after shutdown; then releasing the water that remains (after allowing forseepage and evaporation losses) for use downstream.
The program calculates the shutdown losses and loss saving attributed to lateral liningin the following order:
The canal cross-section and slope geometry (taken from E-drawings) and thedepth at the high water mark (or estimated depth in the lined case) are used calculate an estimate of the static volume of each checked pond.
o The normal water depth and canal geometry are used to calculate an estimate ofthe volume of carriage (flowing) water in the portion of the reach above the pond.
o The sum of the static volume of water in each pond and the volume of carriagewater in the reach above give an estimate of the potential shutdown loss assumingneither the ponded or the carriage water is used downstream. If the option ofholding the ponded water is exercised, then that portion of the ponded water thatis lost to seepage, evaporation, or usable downstream within the pond holdingperiod is not included in the shutdown loss. Since there is still the possibility thatsome of the carriage water might also be beneficially delivered and used, themodel user must make an estimate of the usable percentage and include it in themodel inputs.
o The estimated shutdown loss savings resulting from lateral lining is the differencebetween the estimated shutdown losses determined in step 3 for the lined andunlined reaches.
The shutdown loss that would be saved by lining is about half the total shutdown loss.Thus there are still considerable shutdown losses after lining. This water could be conservedby lateral intercepter canals.
It is obvious that Lateral Probe can be used both as an important part of the process forscreening unlined canal sections to find reaches that are cost effective candidates for lining andto estimate the conservation savings afforded by lining. We feel the current version of it issatisfactory for screening purposes. However, we recommend waiting until additional pondingtest data are available and has been incorporated into the seepage inference model routinesbefore Lateral Probe is used for estimating conservation savings for verification purposes.
23
SCREENING TEST RUNS USING LATERAL PROBE
In order to regain the momentum of the lateral lining project we were ask to beginscreening laterals to find some promising candidates for lining as soon as we felt Lateral Probewas sufficiently developed. This provided us with the opportunity to use it in a pragmatic andvery helpful way while debugging it, making it easier to use, and developing data takeoff andinput procedures.
Our experience from using Lateral Probe to screen this initial set of 29.0 miles of lateralreaches from throughout IID’s service area formed the basis for developing the users manual andtraining program for it. We developed and submitted a brief report to present the findings fromthese screening test run and have included it as Appendix B to preserve its content and providea peek into the type of findings one can expect from using this new screening and conservationverification tool.
RECOMMENDATIONS AND CONCLUSIONS
Development of Lateral Probe and its test application have led to the followingrecommendations. We have already discussed most of these with IID staff. We know that someof them are already scheduled for implementation, but we have included them here forconsistency.
Use Lateral Probe to screen all remaining unlined laterals within the ImperialIrrigation District for lining candidates that will provide the most water savingsat least cost.
o Continue the ponding test program following the guidelines we recommended inour previous report, modified by IID Water Resources Staff, and approved by theWater Measurement Committee. Continued testing will provide the datanecessary to refine and better calibrate the seepage inference model. As manytests as possible should be conducted in lateral reaches within higher permeablesoils (Kses _> 2 in/hr). It is critical that timely groundwater data are obtained inconjunction with the ponding tests and that accurate surveys of the ponded reachesare made.
Conduct constant head ponding tests whenever possible. Such tests will providethe data necessary to calibrate and validate the start-up seepage calculationprocedure. Data from these tests will also be useful in determining the effect ofthe falling head during the other ponding tests and can be employed to developa better correction strategy.
24
Improve the quality of the existing ponding test data base by surveying theponded test reaches and obtaining current and appropriate groundwater data. Thisalone will greatly facilitate calibration of the seepage inference model since wehad to rely on outdated E-drawings for most of the canal geometry data requiredby the model.
So When sufficient data from additional ponding tests and the resurveying ofpreviously tested reaches are available, review the start-up and steady-stateseepage inference models and make necessary changes.
Once the model has been recalibrated and validated, revise the conservationestimate using Lateral Probe for all lateral lining completed to date under theConservation Agreement.
In addition to the above, we make the general recommendation that the methods andassumptions used for screening lateral canal lining candidates should be the same as those usedfor the verification of conservation savings. Furthermore, we believe whole reaches whichdemonstrate cost effective water savings should be lined rather than only subsections having highsavings potential.
In addition to screening laterals for and verifying conservation savings from lining, thereare numerous other possible applications of Lateral Probe. It can be used to estimate theoperational water required to meet specific delivery schedules, applied as a training tool whenworking with zanjeros, operated to help allocate conservation savings among interlinked projects,and employed for estimating capacity requirements in the design of lateral interceptor canals.
There are some minor improvements we would like to make to Lateral Probe whichwould enhance its ease of use and overall appearance. These changes would not affect theprogram’s functionality, nor would they change the input data requirements or the modeloutputs.
This first phase of model development has focused on generating a tool to aid inscreening unlined lateral reaches for candidates to line. The seepage inference portion of themodel does not need to be as well calibrated for screening as it will when used for conservationverification. Enhancements to the model necessary for conservation verification and otherapplications would be the focus of a recommended second phase of development. This wouldbe a natural follow up to the work already completed. The first phase of model developmenthas established the look and feel of the program and general logic flow keeping in mind potentialsecond phase applications.
25
REFERENCES
Bouwer, H., 1969. "Theory of Seepage from Open Channels." Ch. 2 in Advances inHydroscience, Vol. V. V.T. Chow, ed. Academic Pr., New York, NY, pp. 121-170.
Bouwer, H., 1990. Effect of Water Depth and Groundwater Table on Infiltration fromRecharge Basins. Irrigation and Drainage Conference Proceedings, ASCE, Durango,CO.
Bouwer, H., 1991 (in press). Effect of Groundwater Depth on Seepage into or out of Channelsand Lakes. Journal on Irrigation and Drainage, ASCE.
Hanks, R.J. and Ashcroft, G.L., 1980. Applied Soil Physics. Advanced Series in AgriculturalSciences 8. Springer-Verlag, Berlin, Heidelberg, and New York.
I-Iansen, V.E., O.W. Israelsen, and G.E. Stringham, 1980. Irrigation Principles and Practices.Fourth Edition. John Wiley and Sons, New York, Chichester, Brisbane, and Toronto.
Imperial Irrigation District, Water Resources Unit, September 1991. Prediction of CanalSeepage Through Multiple Regression Analysis, Technical Report.
Imperial Irrigation District. General Shallow Groundwater Table Observation Well Map & Data,1974-1976.
Imperial Irrigation District. CFS Data Files (diskettes).
Imperial Irrigation District. Ponding Test Raw Data Sheets.
Imperial Irrigation District. Soil & Water Table Investigations for Canal Ponding Studies.
Keller-Bliesner Engineering, February 1992. Critique of the Conservation Program’s LateralCanal Lining Verification Plans and Procedures. Prepared for Imperial Irrigation Districtunder work order KB-01.
U.S. Department of Agriculture, Soil Conservation Service, 1981. Soil Survey of ImperialCounty California Imperial Valley Area.
U.S. Department of the Interior, Bureau of Reclamation, 1978. Drainage Manual. FirstEdition. A Water Resources Technical Publication.
26
Data Summary of Ponding Test Data Used to Developthe Steady-State Seepage Inference Model
27
Data Summary of Ponding Test Data Used to Develop the Steady-State Seepage InferenceModel.
Seepage Catc K=c~ Percent ~ater Maintenance VegetationRate K O~ Temperature Frequency Density
Large Laterals (Top ~idth ¯ 20 ft)
Acacia Canal Gates 46-46A 9.5 0.168 0.200 95 88 1Alder Canal 12.3 0.195 0.200 95 62 0Ash Main Canal Headgate to Lat 2 269.7 2.982 4.320 95 54 IDogwood Canal Gates 41-44 53.8 0.272 0.200 38 85 0Elder Canal Del. Gates 1 to 3A 84.5 1.041 0.420 97 85 0Rockwood Canal Gates 132-134 87.3 1.471 1.230 94 90 0Rockwood Canal Gates 13~-146 53.5 0.378 0.504 94 91 0Rositas S.Canal Ex.Lining-Sta.8760 103.6 1.461 4.0~ 100 60 0Rositas S.Canal By Pal~tto 20-20A 74.5 2.092 3.300 100 60 0Rositas S.Canal Ck 1-Sperber Res. 93.9 1.220 3.030 100 58 0South Alamo Canal Hiway 98-Gate 31 176.5 2.492 2.920 100 59 0Spruce Main Canal Headgate-Gate 37 325.3 3.163 4.492 99 55 1Vail Supply Canal Nectarine A Check 10.2 0.346 0.600 100 52 0~estside Main Gates 90-91 47.0 1.405 2.000 100 54 0~estside Main Canal Tri Lats. 10-11 88.8 1.413 1.650 100 62 0
Small Laterals {Top ~idth ~ 20 ft)
Acacia Canal Lat 6 to Gate 65 166.8 1.788 6.000 93 84 1Ash Lateral 39 #1 Gate 168-169 41.4 0.082 0.200 17 53 1Ash Lateral 39 #2 Gate 168-169 55.8 0.108 0.200 17 65 1Ash Lateral 39 #3 Gate 168-169 58.0 0.108 0.200 17 72 1Ash Lateral 39 #4 Gate 168-169 71.6 0.133 0.200 17 82 1Ash Lateral ] Headgate to Check 15 187.8 0.526 2.136 27 84 1Best Canal Delivery 116-118 11.9 0.061 0.200 10 57 0Daffodil Canal Gates 11-12A 33.9 0.162 0.200 68 78 0Dahlia Canal 52-53 80.1 0.453 0.200 98 84 1Dandelion Canal Gates 2-3 88.3 0.193 0.400 34 85 1Date Lateral 9 #1 Gates 83-85 90.5 0.242 0.460 24 64 0Date Lateral 9 #2 Gates 83-85 82.5 0.227 0.460 24 70 0Date Lateral 9 #3 Gates 83-85 112.6 0.310 0.460 24 82 0Date Lateral 9#4 Gates 83-85 129.3 0.356 0.460 24 87 1Date Lateral 10 Gates 81-81A 90.8 0.150 1.230 24 88 1Dogwood Lateral 2 Gates 17-18 99.5 0.571 0.600 95 68 1Fillaree Canal Gates 27-28 100.2 0.392 0.420 98 88 1"F" Lateral Gates 18-20 19.6 0.112 0.200 76 66 0Forgetmenot Lat 17-19 88.6 0.350 3.400 37 82 1Flax Canal Gate 24-End 51.9 0.377 0.600 14 65 1"K" Lateral Gates 12-13 101.1 0.223 0.200 66 85 0Moss Canal Gates 6-7 40.2 0.366 1.464 98 54 1Newside Lat 3 Gates 31-32 21.6 0.094 0.312 45 56 0Pear Lat 1 Gates 42A-44 130.6 0.442 0.600 8 80 1Rockwood Lat 5 #1 Gates 138-139 77.4 0.252 0.428 43 70 1Rockwood Lat 5 #2 Gates 138-139 114.8 0.351 0.428 43 84 1Rockwood Lat 5 #3 Gates 138-139 86.5 0.281 0.428 43 87 1Rose[[e Canal Gate 6-End 94.2 0.844 4.542 37 B4 1Thistle Main Canal Gates 36-38 51.9 1.725 4.600 40 54 0Township Lateral Gates 25-26 5.3 0.092 0.600 44 87 1Vail Lateral 3A Gates 363-365 62.2 0.216 0.200 60 52 0Vail Lateral 6 Gates 606-608 40.3 0.252 2,000 73 54 0~isteria Lateral 6 Gate 79-Lat &A 24.0 0.108 0.280 51 72 0
28
APPENDIX B
Lateral Canal Screening for Lining Candidates
29
Lateral Canal Screening for Lining Candidates
The attached table summarizes the results from screening 29.0 miles of potential lateral liningcandidates on 14 different lateral systems. The table represents those whole reaches which, if lined,would provide an estimated conservation savings of 120 AF/Yr/Mi or better. The screened reachesrepresent what liD staff believed to have good water savings potential and for which preliminary surveyand design work has already been completed.
We used as the screening tool the lateral conveyance loss computer simulation program, LateralProbe, that we are developing under contract for liD. This model analyzes the cyclic nature of a lateralfrom daily delivery records, CFS datafiles. This determines the percent on time, number of on/offcycles per year, mean flow, opportunities to use ponded water downstream, etc. for each check on thelateral. The CFSfiles used for this screening covered an average of 4.5 years each.
The seepage estimate for unlined reaches is based on an inference model which currently explains76% of the variation in seepage rate observed from the ponding tests completed to date. For linedreaches we assumed a seepage rate of 0.01 fta/ft2/day. Start-up losses are calculated as a function of thechange in soil water for the wetted envelope about the canal. Evaporation estimates are based on anannual rate of 8.5 ft.
We calculated shutdown losses as 10% of the carriage water and 100% of the unused pondedwater after holding times of 1, 2, and 3 days. The longer a pond is held, the greater the opportunity touse the ponded water downstream; however, the opportunity time for seepage and evaporation alsoincreases. This is demonstrated in the attached table which shows seepage and evaporation increasingwith pond holding time and shutdown losses decreasing. For these laterals more water is lost by holdingponds.
Of the 29.0 lateral miles screened there are 12.7 miles of whole reaches which meet the120 AF/Yr/Mi cutoff criteria. The average estimated conservation savings from lining all 12.7 miles is232 AF/Yr/Mi. The reduction in seepage loss accounts for 74.2% of the estimated savings, start-upaccounts for 18.6%, evaporation accounts for 2.0%, and shutdown accounts for 5.2%.
Recommendations
The methods and assumptions used for screening lateral canal lining candidates shouldbe the same as those used for the verification of conservation savings.
Ponding tests conducted in accordance with our previous recommendations should becontinued to provide the data necessary to refine and better calibrate the seepageinference model.
Revise the conservation estimate using Lateral Probe for all lateral lining completed todate under the Conservation Agreement.
Line whole reaches which demonstrate cost effective water savings rather than onlysubsections having high savings potential.
Keller-Bliesner Engineering Logan, Utah May 20, 1992
Total Conservation Savings for Laterals with an Estimated Savings Greater Than 120 AF/Yr/Mi.
PondHolding Length Seepage Evaporation Startup Shutdown Total Total
Time (Miles) (AF/Yr) (AF/Yr) (AF/Yr) (AF/Yr) (AF/Yr) (AF/Yr/Mi)
1 Day 12.71 2105.6 57.6 549.2 194.2 2906.6 228.6
2 Day 12.71 2195.7 59.7 549.2 145.2 2949.8 232.0
3 Day 12.71 2264.7 61.2 549.2 120.1 2995.3 235.6
Average 12.71 2188.7 59.5 549.2 153.2 2950.6 232.1
Distribution of Conservation SavingsFrom Lateral Lining
Shutdown (5.2%)
Startup (
Evaporation
Seepage (74.2%)
Keller-Bliesner Engineering
Dei 88-01 ~871 54.2 107.1 3.5 8.g 21.4 42.3 8.5 18.8 87.6 173.2~ 2671 1.3 2.8 1.3 3.5 4.8 g.1 7.7 15.3
Oel 91-g5 2850 23.0 45.3 2.4 4,9 33,1lined 2850 0.7 1.3 0.0 1.0
g.g lg.7 68.4 136.43.4 8.0 5.0 10.0
05-06 912 10.8 62.5 0.8 3.7 8.0lined 912 0.2 1.1 0,3 1,8
51.5 §,4 31.3 25.7 149.0
1.4 8.1 1.9 10.0
06-g7 1714 15.4 47.4 1.3 3.0 21.8 ~8.5 31.2 06.1 99.5 214.0lined 1714 0.3 1.1 0.5 1.5 9~ 30.5 10.7 33.1
De107-End 25~7 14.2 29.0 1.8 3.8 18.3 34.3 25.1 51,2 57.9 118.2~ 25~7 0.5 1.1 0.8 1.8 13.1 2~.7 14.4 20.4
Acac.~ Lat 11 Oel Hdg-~4C
H~g-D~ 94.4, 2623 03.6 168.4 3.1 8.2 54.8 118.0 3~.9 80.3 105.2lined 2823 0.8 1.5 1.0 2.1 8,5 13.1 8,3
~2.5 0,99 92.318.7
D~ 94A-04C 2823 43.5 87.8 1.8 3.2 57.3 115.3 17.8 35,4 120.O 241.5lined 2823 0.3 0.7 0.5 1.0 3.7 7.4 4.5 8.1
~ Lst 12 HdgoEnd
Hdg-End 2842 41.5 82.0 1.5 3.0 21.5 43.0 7.5 15.0 72.0 143.9 0.50 87.0lined 2542 0.5 1.2 0.5 1.7 2.3 5.5 4.3 8.5
Nder L.st 70~ 84A-70De~ 64A-~7 1001 22.5 118,7 1.1 5.6 25.4 13g.3 4.3 22.7 54,3 28~.3 0.60 210.o 352.3
lined 1001 0.4 1,9 0.5 2.7 2.7 14.2 3.8 la.-~
Dei 67-70 2150 67,3 185.3 2.1 S.2 85.5 2~.I 12.2 20.8 167.4 400.5lined 2150 0.7 1,7 1.0 2.4 5.5 13.7 7.3 17.5
Hdg-Del 4~ 1290 44.8 183.4 2.3 g.2 0,0 2.5 2.8 10.6 50.3lined 1290 0.8 3.2 1,1 4.4 1.0 4,1 2,0
205.7 0.24 47.411.7
194.0
Be~t De~ 47-48Dei 47-478 3484 12.3 18.6 2.2 14.9 5.3 3.0 8.2 0.4 34.2
lined 3484 2.8 4,0 3.5 5.3 1.8 2.7 7.0
51.8 1.03 49,912.0
Del 47B-48 1935 17.g 44.8 4.0 13.0 1.5 4,1 3.3 |.0 27.5 75.0,ned 1030 1.2 3,3 1.8 4.4 1.0 2.7 3.8 10.4
Be~t Del 100-102Del 100-102 2890 82.8 151.3 8.7 12,2 2.4
lined 2Bg0 1.7 3.1 2.3 4.3
4.4 7.8 13.9 99.5 181.8 0.55 92.9 169.8
2.5 4.6 8.5 12.0
Kelier-Bllesner Eng~needng
N~me Dl~tar~:~ To~alBeh~e~fl Loe~e betv~en Ghecke Total ot AJl Lo~ee Reach To~al S~v~ng ICt~cks Seepage Evapo~t~o~ Stirrup S~utdown between Chm::ka Length from Unlng Reach
(t~ (A~lyt) (AFly~lrni) (AFlyr) (A~/yrlf~’) (A~lyr) (i~lyr,lmO (AF/~r) (AFly~lrnl) (A~lyr) (AFlyrlml) (rid) (AFlyr) (AF/y’tlmi)Byr~nt Hdg-Del S~
I.k~el 45 1332 9.4 37.3 3.4 13.4 0.9 3.8 3.3 13.1 17.0 87.3 0.60 46.5 78.0tined 1332 0.7 2.9 1.0 3.9 1.1 4.4 2.8 11.2
45-,~ 1817 28.5 85.7 3.0 8.8 1.8 4.8 1.2 3.5 35.3 102.5lined 1817 1.0 2.3 1.3 3.8 0.8 1.7 2.9 8.4
Byr~nt Oe~ 56-5~De~ ,56-5~ 2912 55.2 100.1 5.1 8.3 5.0 0.1 2.7 4.9 6~.0
lin~l 2912 1.0 3.5 2.8 4.7 1.5 2.7 8.1
123.4 0.55 82.0 112.411.0
D IJterll Del 21-25Oe~ 21-24 3568 4.0 5.8 1‘5 2.4
lined 3588 0.3 0.5 0‘5 0.77.8 11.5 5.0 7.4 18.4 27.2 0.93 20.5 22.0
1.0 1 ‘5 1.8 2.7
24-25 1350 1,5 8.9 0.4 1.8 2.1 8.2 0.5 2.0 4.5 17.7lined 13~0 0.1 0‘5 0.2 0.7 0.3 1.2 0.8 2.3
Elm Lat 3 Hdg-Oel IOA
Hdg-D~ IOA 13~ 32.7 123.8 2.0 7.5 19.4 73.4 11.7 44.3 85,8 249.0 0.26 56.1lined 13~5 0.8 2.0 1.0 3.8 7.0 29.9 9.7 36.8
212.4
Elm Lat30el 18-21084 16-18 t505 18.5 87.9 2.0 T.f 10.7 37.5 15.0 82.8 44.2 155.2 0.53 84.5 12~.0
lined 1505 0.7 2.4 0.9 3.3 7.8 27.4 8.4 33.1
De416-21 1285 10.0 41.1 1.4 5.8 17.8 73.1 4.2 17.3 33.4 137.3~ 1285 0.5 2.0 0.7 2.7 2.8 10.7 3.7 15.4
Elm L~t 3 De~ 29-29De~ 26-2~8 1505 11.7 41.0 0.8 2.8 10.1 35.4 1.0 3.5 23.8
lined 1505 0.2 0.8 0.3 1.1 0.5 1.8 1.0
82.8 0.53 67.4
3.6
De~ 288-29 1285 20.2 83.0 0.7 3.0 29.3 83.4 7.5 30.8 48.7 200.3lined 1285 0.2 0.9 0.3 1.2 3.4 14.0 3.9 16.1
J Lat~r~ D~ 10-14
D~ 10-12 2743 13.9 28.8 4.2 8.1 5.2 10.0 2.0 §‘5 28.2 50.5 1.02 67.2 65.5lined 2743 1.0 2-0 1.4 2.7 0.0 1.7 3.3 8.4
12-14 2867 ~’,1 53.7 3.3 8,5 13.8 28.9 3.5 8.9 47.~ 94.0I~ned 2867 0.9 1.8 1.3 2.5 1.1 2.2 3.3
Keller-Bliew~er Engineering
OccidentD~ 3-5 1383 12.7 48.5 3.0 11.5 5.9 22.5 2.3 8,8 23.9 81.3 1.40 140.5
lined 1383 0.7 2.8 1.0 3.8 0.g 3,4 2.8 10.0100.3
De~ 5-6 1415 23.1 88.2 2.6 9.8 7.1 28.5 4.1 15.3 36.9 137.8lined 1415 0.8 3.1 1.1 4.1 1.8 8,7 3,7 13.g
D~I 8.8A 128~ 24.7 102.8 2.0 8.3 7.2 30.0 1.O 4.2 34.9 145.2
~ 128~ 0,8 2.5 0.8 3.4 0,5 2.1 1.g 7.g
Del 6A-7 1353 lg.8 77.3 2.0 7.7~ 1353 0.8 3.1 1.1 4.1
4.8 16.0 5,8 21.9 32.0 124.83.3 12.9 5.1 20.0
D~ 7-8 1878 17.7 47.3 3,6 8.7Ikled 1878 1.0 2.8 1.3 3.5
3.2 0.8 5.4 t4,4 29.9 80,0
1.4 3.7 3.7 9.8
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71.0 2.30 151.111.8
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lined 386~ 1.8 2.5 2.4 3.4 3.8 5,5 7.9 11.4
D~ 10-20 4815 43.6 47.8 7.2 7.9 20.1 22‘0 IO.7 11,7 81.8 89.5~ 4815 2.0 2.2 2.8 3.0 3.2 3.5 8.0 8.8
Occident De~ 22-23O~ 22-23 2588 10.4 21.2 2.7 5.5 2.4 4.9 9.3 19.0 24.8 50.8 0.49 21.1
lined 25~8 0.8 1.8 1.1 2.2 1.9 3.9 3.8 7.743.0
Orange Del 4-8
D~ 4-5 2841 88.4 136.7 8.3 12.0
Uned 2841 1.5 3.0 2.0 4.1
0.6 1.2 0.5 1.0 75.8 151.5 1.00 121.4 121.70.2 0.4 3.7
5.8 2828 44.8 90.1 8.1 12.3 1.8 3.2 0.7 1.4 53.2 107.0Nned 2828 1,5 3.1 2.1 4.3 0.2 0.4 3.g 7.8
D~ 0.6A 24~2 23.9 51.3 8.7 14.3
lined 2462 1.5 3,2 2.0 4.4
0.5 1.1 1.2 2.0 32.3
0.4 0.0 4.0
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8.5
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Keller-Bllew~m’ Engineering
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lined 1643 0.6 2.7 1.1 3.7 0.4 1.3 2.4 7.6
Odent D~ 2.2A2-2A 12~5 12.9 52.6 2.7 11.2 1,7
lined 12~5 0.5 3.4 1.1 4.6
8.9 2,0 11,4 20,1 52.1 0.25 15.7 86.1
1.5 8.1 3.5 14.1
20-21 783 17.3 116.7 1.0 12.2 8.7 54.7 1.0 0,7 28.8 194.3 0.68 137.0 ~08.0lined 783 0.3 1,9 0.4 2.0 0.4 2.7 1.1 7.3
21-22 20~4 61.4 120.2 4.8 9,1 27,1 53.1 23.8 4~.6 116.9 229,0
lined 2~6 1.1 2.2 1.5 3.0 5.0 8.3 7.7 15.0
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7,1 13.9 9.4 15.5
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30.4 0.50 12.94.7
Hdg--O~2 1790 276.4 815,3 5.2 15.3 10.5 31.0 5.5 18.2 ~7.5lined 1790 1.1 3.2 1.3 4.3 1.2 3.5 3.7
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Oxalis D~ 7-10Del 7-8 2045 12.2 24,4 4.3 6.9 1.0 3.2 3.7 7.4 21.0 43.5 1.01 50.4 50.0
#ned 2545 1.3 2.5 1.7 3.4 1 .O 3.2 4.6 9,2
Oel 6-10 2886 17.4 34.2 4.9 9.6 10.1 19.0 11.5 22.6 43.9 86.3
lined 2686 1.5 2.9 2.0 3.9 7.2 14,2 10.7 21.0
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lined 2812 0.5 1.0 0.8 1.4 1.3 2.4
drop-Det 27 2510 47.0 9~.5 2.3 4.7 6.4 13.4 0.3 14.5 62.6 131.1lined 2510 0.5 1.2 0.3 1.7 2.0 4.2 3,4 7.1
Rubber tat 4 D~ 21-24Oe~ 21-24 2879 23.3 47.1 3.0 5.9 5.9 11.6 17.0 33.5 4~,8 . 98,1 0.51 43.1 85.0
lined 2679 0.9 1.9 1.3 2.8 4.4 8.7 6.7 13.1
droc~Del ~47 1074 28.0 131.8 1.8 8.0 0.7 3.4 3.6 17.7 32.7 1~0.9li~cl 1074 0.5 2.3 0.8 3.2 1.8 8.8 2.0 14.3
Trllolium Lit 13 De~ 248-253D~ 248-250 5748 1.9 1.7 7.0 7.0 0.8 0.7 8.0 8.1 18.1
lihed 574~ 2.4 2.2 3.3 3.1 4.3 4.0 10.117.0 1.58 36.88.3
250-253 2585 21.8 43.9 3.5 7.2 3.2 8.5 2.3 4.7 30.0 82.3lined ~05 0.g 1.9 1.3 2.8 0.8 1.8 3.0 0.1
Trifollum t,,t 13 OK 255-F.nd
Del 255-25~ 1088 25.4 87.5 2.3 0.1 5.8 15.4 8.2 21.8 41.7 110.7 2.24 390.2 178.6
lined 1988 0.8 1.7 0-g 2.4 2.0 5.3 3.5 9.4
Del 256-257A 1843 167.1 478.7 2.3 8.8 10.0 g~.5 8.7 24.8 188.1 53~.0
lined 1843 0.5 1.5 0.7 2.0 1.3 3.7 2.5 7.2
D~ 257A-258A 2640 82.9 105.8 2.3 4.6 2.2 4.4 8.0 17.2 ~6.0 132.0lined g~840 0.4 0.8 0.6 1.2 0.8 1.5 1.8 3.7
25~A-25~ 2872 gO.5 178.6 2.8 5.1 0.8 1.8 8.4 1 2.6 100.3 198.2
lined 2872 0.3 0.7 0.5 1.0 0.3 0.5 1.1 2.3
OK 25g-End 28~0 8.3 12.5 0.7 1.3 4.4 8.7 1.2 2.4 12.8 24.9lined 2860 0.1 0.3 0.2 0.4 0.1 0.2 0.4 0.6
V~I Lit4 Del 40~4150¢~ 40e-411 2574 91.7 18~.1 4.5 li.2
~l~ed g574 1.2 2.4 1.8 3.32.4 4.0 2.4 4.0 101.0
0.7 1.4 3.5207,2 1.4g 62g.g 424.0
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4.8 9.5 1.0 2.0 253.8 ~3.80.4 0.8 3.3 0.5
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Keller-Bllemer Englneedng