nson ge Spe ornia, Dan D. Marcum Farm Advisor, Shasta County Roger B. Benton County Director, Siskiyou County INTRODUCTION

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1 IRRIGATING ALFALFA FOR MAXIMUM PROFIT Irrigati Univer laine R. and Dra ty of Ca nson ge Spe ornia, cialist Davis Dan D. Marcm Farm Advisor, Shasta Conty Roger B. Benton Conty Director, Siskiyo Conty INTRODUCTION Most groers irrigate for maximm yield assming maxjmm yield eqals maximm profit. Hoever, high irrigation costs and/or 1111 crop prices may mean maximm profits occr at less than maximm yields. The qestion is then, ho mch ater shold be applied for maximm profit, given a set of prices and costs. The economic criteria for maximm profit are ell knon. Mximm profit occrs hen marginal revene eqals margin costs, or, the slope of the eqation relating revene to applied ater eqals the!lope of the cost eqaltion. This eqation depends on the relationship beteen yield and amont of applied ater and on the crop price. The cost fnction depends on factors sch energy costs for irrigation, labor costs, harvesting costs, pest. control costs, and capital costs. Many alfalfa groers in northern California nre considering converting to dry land farming becase of the relatively high energy costs of pmping grondater. This action, they believe, ill increase the!ir profits since irrigation costs ill be eliminated. rot considered, hoever, is the relationship beteen irrigation, crop yield, and revene. Under dry-land farming, no irrigation costs ill occr, bt yields il:l be redced and th1 so ill revene. Assessing the impact of converting to dry-land farltling reqires information on yield verss irrigation amont. A crop prodction eqation relates yield to amont of applied ater. Sch relationships have been developed for alfalfa yield verss evapotranspiration for different locations. Yet, these relationships are very diverse, reslting in little confidence that a relationship developed at one location can be applied elsehere. This limits applying the economic criteria to those locations ith knon prodction fnctions. Several years ago, a techniqe for developing,::rop prodction fnctions sing a line sorce sprinkler as developed. Reslts from this method shoed very high correlations beteen yield and E:T. We modified this method for developing on-farm crop prodction fnctions for alfalfa in the montain valleys of northern California. Or appro,3ch consisted of installing catch cans in locations here sprinkler over:lap as minimal, ths providing a gradient of applied ater over a given area. Small plots, centered arond each catch can, ere harvested for each ctting. We ere then able to compare the plot yields ith the later caght in the can for that plot, and ths, correlate yields ith ater applied. Crrently, \C have three years of data from one site and one year of data from seven other sites. EXPERIMENTAL PROCEDURE Transects of catch cans ere placed normal to the sprinkler lateral here little overlap occrred. Can spacing as abot five feet for all sites, hereas, spacing beteen transects ranged from abot 2 to 3 feet. volme of ater caght as measred for each irrigation. A plot, centered -36-

2 arond each catch can, as harvested for each ctting. 3-lj feet ide and abot 5 feet long. Plot sie as abot Data on harvesting, capital costs and pmp performance ere collected. Uniformity of application as determined on several of the systems for ad.isting the experimental crop prodction fnctions for. nonniform applications. ET data from a CIMIS eather station as sed to estimate maxiltlm ET. RESULTS Figres 1-3 sho reslts from sites M, I, and K in Fall River Valley. The first irrigation at site M ShOlS little correlation beteen applied later and yield, indicating adeqate stored soi 1 moi.'3tre from the inter and spring, and that irrigation contribted little to the yield. For the second ctting, hoever, a linear relationship beteen yield and applied ater occrred for applications less than abot 4-5 inches. For larger applications, yield did not change ith applied ater. Maximm yield \.'as abot 1.9 tons per acre. The third and forth cttings shoed no yield for applications less than abot inches. Thereafter, yield increased linearly ith applied ater p to abot 6 inches, the maximm application of this irrigation system. Eqations for these cttings are in Table 1. Data from Site I (Figre 2) sho behavior similar to that of Site M, hoever, data from Site K sho a mch different behavior (Figre 3). For tho first ctting, no relationship as fond beteen yield and applied at.er, hereas, for the second and third cttings, a linear relationship I.JCJ; fond. Hoever, these relationships shoed a mch smaller yield response than at the other sites. The eqations, in Table 1, sho a yield of abot one-third to one-half of that of sites M and I for a given depth of ater. Reasons for this behavior are nlnon, bt this poor yield res:ponse might be cased by ntrient problems. We hypothesie that the relationships for the last to cttings of site M and the last ctting of site I describe evapotranspiration verss yield. After the second ctting at both sites, little or no stored soil moistre appears to have remained, and ths, the ater sed by the crop as from irrigation only. Evidence for this is the negative vale of b of these ct;tings, hich as somehat similar for each site. Als,o, a relationship of ET verss yield for the Tin Falls, Idaho area, as similar to or rej.at ionships. Sites W1, W2, and W3 (not sho\n) shoed similar behavior as sites M and I althogh positive vales of b occrred for the last cttings. At Sit;e L, yield responded poorly to applied ater for all cttings (only to ct;tings), hoever, the average yields ere abot.85 and 1.43 tons per acre for the respective cttings. At site MI, the sprinkler lateral as inadvertently positioned ithin experiment area, and as a reslt, desired behavior did not occr. For most of the cttings, maximm yield as not obtained, since the irrigation systems lacked the capacity to apply more ater. Hoever, for the economic analysis, e estimated the maximm yield sing the calclated ET of a reference crop (grass) and the eqations of the last cttings. The reference crop ET as estimated from climatic data collected by a CIMIS e;3ther station located in Fall River Valley. Also, since the second cl:.ting of Site M shoed a maximm yield of abot 1.9 tons per acre, this dal;a, copled ith the reference crop ET, as sed to estimated a crop coefficient for ater se beteen cttings, hich coefficient as 1.5. The economic analysis for maximm profit reqires that the experimental crop prodction fnction be adjsted to obtain the field-ide crop prodction fnction. The experimental fnctions, in Table 1, ere assmed to be linear response and platea models, in hich yield responds linearly to applied ater starting at a threshold vale, and beyond some -37-

3 critical vale of applied ater, yield remains constant. Jstification for this model is fond in the experimental prodction fnctions for the forth ctting of site W1 (Scott Valley) in 1984, the third ctting of site W1 in 1985, and the second ctting of site M (Fall River Valley) in These cttings shoed a constant yield for amonts of applied ater in excess of the critical vale, even here the maximm applied ater as abot tice that of the critical vale. The experimental prodction eqations ere sed to develop field-ide eqations for niformities of abot 6%, 8%, and 9% (Christiansen CU). These relationships are shon in Figre 4 for Site M. A profit eqation as developed sing the adjsted crop prodction eqation, a crop price, and a cost eqation. For the irrigation systems sed in the stdy areas, the cost of irrigation depends on the nit price of electricity, the capacity and the total head developed by the pmp, the pmping plant efficiency, and the amont applied. The optimm amont of shon for Site M in Table 2. ater for maximm profit for each ctting is Data sed for this estimate are: Crop Energ Pmpi Pmpi rice : cost 9 plat 9 plar $7; $. err.hea ton, 75/khr, iciency = 55% d = 192 feet. These nmbers ere obtained from pmp test data for a particlar field and from general cost and price data for the Fall River Valley area. From Table 2, e see that the optimm amont of ater increased ith time dring a groing season. ro ater is needed for the first ctting, hich reflects adeqate stored soil moistre from the inter and spring. Hoever, as this moistre is depleted, more irrigation ater is reqired for the optimm amont. We also see that as the niformity of application decreases, the optimm amont increases from 19 inches for a CU = 89% to nearly 3 inches for a CU = 59%. Interestingly, the yield remained at abot six tons per acre for all three levels of niformity. Profit, hoever, decreased becase irrigation costs increased ith decreasing niformity. This analysis does not inclde fixed costs, hich if inclded old redce the profit bt old not affect the optimm depth of applied ater. Figre 5, the relationships of yield verss applied ater for all eight sites, shos significant variability among these locations. The qestion is, hoever, hat effect does this variation have on the optimm amont of ater needed for maximm profit. Table 3, hich shos this optimm amont for five sites, reveals an interesting behavior. For a given niformity of application, the ptimm seasonal amont only varies slightly among these locations, ranging from 16.5 inches for Site W1 to 21. inches for Site K for CU = 77%. Ths, the optimm amont of ater for maximm profit appears somehat insensitive to the variability in the crop prodction eqations. Hoever, Table 3 also shos that yields ranged from 2.6 tons per acre for site K to 7. tons per acre for Site W2, and that variability in maximm profit reflects variability in the crop yields. The coefficient of variability as abot.1 for the optimm depth and abot.34 for the yield at this depth. Ths, althogh the optimm amont of ater is relatively insensitive to variability in the crop prodction eqations, yields and profits are highly sensitive. Variability of the crop prodction eqation ith time mst also be considered. Three years of data at Site Wl, shon in Figre 6, shos a decreasing yield ith time for the first ctting. For the remaining cttings, the slope of the experimental crop prodction fnction decreases ith time, ths yield response to applied ater is less l-lith time. This behavior is believed de to increasing age of the alfalfa. 38-

4 SUM'.'ARY An e onomic evalation of the benefits of irrigation sing on-farm crop prod'tion eqations ShO.'S no economic jstification for converting to dry-land farming. For an application niformity of 77 percent (Christian ens coefficient of niforrnity), maximm profit occrs for a ater application of abot 21 inches. The analysis also shos the optimm amont to be insensitive to variability in the crop prodction eqations, hoever, ield and, sbseqently, profit are highly sensitive. Yield response t applied ater decreased over a three-year period t one site. Table 1. egression coefficients for all eight sites (1986) here yield I(tons/acre) = m x depth (inches) + b. Site Ctting m b RA2 I.' First.< ) t ) 1 Forth.21.2< 18 ) I First K First MI First WI First W2 Forth W L First

5 Table 2. Seasonal applied at.er and yield for optimm profit, Site M, Ctting Applied (inch Water Yield (tons/acre) Profit ($/ton) c = 89% o 6 1-.) T()tal 19.11) c = o 7. J 15. ; Total c = ' Total 29.) 6. O I 355 Table 3. Smmary of five sites. Site Profit ($/Ton) c = 89% Wl W2 M K I Average c = 77% Wl W2 M K I Average q.l c = 59% Wl W2 M K I Average

6 Figre 1. Yield verss applied ater, s; te r, 1986.,.. : (1: '\. (/) o > : <1: ' 1- ''... > : ([ ' In 1- O..J > Figre 2. Vield verss applied ater. Site I

7 Figre 3. Yeld verss applied ater, Site K, 1ge6. c CU=89% CU=77% A CU=59% ' ljj :: a (1) 1-- '' Figre 4. Experimental crop prodction eqation (solid line) and adjsted eqations. I ljj! t-i :>- -42-

8 I I' Iii II UI UJ = <I ' tn 1- ' -l UJ - >! le I FIR9T OSTTI -li9 i ---L :-----I, ---K II I I I e 1 APPLIED WATER (INCHES) Figre 5. Variability of yield verss applied ater, Q r&j... Figre 6. Variability of yield verss applied ater ith time. -43-