Agricultural Benefits of Salinity Control on the Red River

David H. Laughlin and Ronald D. Lacewell

Control of salinity offers an opportunity to increase agricultural production along the Red River of Texas and Oklahoma. However, absolute benefits and the distribution of those benefits are sensitive to the crop yield effect of SAR (sodium absorption ratio). The effect of SAR on crop yield is not well defined. This study estimates agricultural benefits of a chloride control project as $65 million, not considering any SAR effect and $117 million with an SAR effect. Further, distribution of benefits was reversed between the eastern and western portions of the study area.

Salinity of irrigation water and the poten- yield reductions may occur when the SAR tial accumulation of salts in the soil constitute (sodium absorption ratio) becomes a prob- a very important problem to agriculture in lem. SAR problems arise when the percent- the Western United States any in many other age of sodium ions in the residual salts is high parts of the world [Yaron]. The effect of relative to calcium and magnesium. In gener- salinity on agricultural crops is typically ex- al, the result of high soil SAR values is low pressed as a decrease in yield associated with rain and irrigation water permeability, soil a given level of soil salinity as compared with crusting, increased soil compaction, reduced yield under non-saline conditions [Maas and germination, and, hence, reduced emer- Hoffman]. Repeated applications of highly gence and stand establishment [Gerard]. saline irrigation water and subsequent re- Thus, waters containing high salt concentra- moval of pure water by the growing plant tions may be either partially or completely often results in significant salt accumulation. precluded from use for agricultural irriga- In addition to the toxic effects on the growing tion. plant, increased soil salinity results in signifi- Projections of increased worldwide de- cant reduction in water uptake by the plant mands for food and fiber through the coming and thus inhibits plant growth and reduces decades increasingly focus attention on the yield [Longenecker and Lyerly]. Further need to increase agricultural output [Hjort]. Reduction of salinity levels of irrigation water David H. Laughlin is Assistant Professor in the Depart- in portions of the Southwest can increase ment of Agricultural Economics at Mississippi State agricultural output of that region. However, University and Ronald D. Lacewell is Professor in the significant reduction of salinity concentra- Economics at Texas A&M Department of Agricultural tions in irrigation water may require substan- University. tial capital investment. To attract the needed Technical article 17081 of the Texas Agricultural Experi- capital investment, the contribution of salini- ment Station. This research was funded in part by the ty control for irrigated agriculture must be Corps of Engineers, Texas Water Resources Institute, demonstrated. and Texas Agricultural Experiment Station. The authors are most grateful to Don Moore, Rod Martin, Jack The economic importance of agricultural Runkles, Bob Taylor, Bill Harris, and John Sparlin for irrigation to the Western U.S. has been es- assistance in collecting and organizing data, developing tablished by numerous articles and publica- procedures, and generally providing many of the compo- tions on the subject, e.g., [Adams, et al., to complete this study. The authors also nents required Casey et al., Condra, et gratefully acknowledge the comments and suggestions of Mapp and Dobbins, Dow Welch and three anonymous reviewers. al., and Lacewell and Condra], for example. 195 December 1981 Western Journal of Agricultural Economics

Only a few, however, have investigated the among groups of beneficiaries in the various effects and shown the economic importance geographic sections of the study area. of saline irrigation water on agricultural production. Yaron and Olian investigated man- The Study Area agement strategies to deal with salinity prob- The Corps of Engineers originally lems in a firm-level model for Israeli produc- separated the Red River Basin between Tex- tion conditions. McFarland investigated the as and Oklahoma into 15 evaluation reaches intertemporal effects of saline ground water containing a total of over 666,000 acres of intrusion for a coastal region in Mexico. An- irrigatable land. The Reaches consisted of derson and Klienman report a study for the varying-length strips of land 1.5 miles wide Colorado River basin somewhat similar to the on each side of the Red River and its major reported herein. The Anderson and one tributaries. Each reach was further sub- Klienman study, however, was designed to divided into three zones, the outer borders of help evaluate the impacts of salinity manage- which were respectively 0.5, 1.0, and 1.5 ment options for the Colorado River and miles from the river. Figure 1 illustrates the the damages that occur through- determine Corps of Engineers' original study area speci- regional economy. out a fication. Below Lake Texoma, a major mul- The Red River of the South in Texas and tipurpose lake in the approximate geographic Oklahoma is an area in which the salt pollu- center of the basin, there is sufficient dilution tion is "point-source" and to a large extent of the river water so that the salt pollution is can be controlled. About one-third of the salt not a measurable irrigation problem. Hence, pollution in the Red River is brine from local only reaches west of Lake Texoma (5-15) oil fields. The remaining two-thirds comes were applicable. from 10 salt water springs located in the Among those reaches included, the salinity River Basin in Oklahoma and salt upper Red level of the river water varied significantly, located in Texas [Department of the seeps depending on the reaches' proximity to salt Corps of Engineers has submit- Army]. The sources, hence causing varying levels of crop a plan to construct a system of subsurface ted yield reduction. In general, river water in shallow wells, and collection cut-off walls, the far western reaches (10, 11, 13, 14, and reservoirs to collect and dispose of much of 15) has higher salt concentrations than does source salt waters. As a result, water from the that in the eastern reaches (5, 6, 7, 8, 9 and Red River would be made usable for the 12). Therefore, the opportunity for increased irrigation, though still not com- agricultural crop productivity, and, hence, net project free of salts. The primary purpose of pletely benefits, was expected to vary among reaches study reported herein was to determine the depending upon both the salinity level and agricultural benefits of a pro- the potential on the inherent productivity of the soils in chloride control project posed Red River each reach. [Laughlin, Lacewell and Moore]. Results of suggest that the SAR [Gerard, et al., 1979b], Procedure of irrigation water from the Red River is of considerable importance for soils similar to The estimation of potential economic ben- those in the Red River Basin. However, efits to agriculture from the Red River SAR-induced crop yield reductions are not Chloride Control Project was the second conclusively established for the Red River component of an overall agricultural study for Basin. A second purpose and major objective the project. Soil scientists, agronomists, en- of this paper was to investigate the expected gineers, and irrigation specialists teamed in impact of salinity and SAR-induced yield re- the first part of the study to provide the many duction on the salinity control project bene- agronomic and hydrologic relationships that fits and the distribution of those benefits were necessary for the development of an

196 Laughlin and Lacewell Benefits of Salinity Control

OKLAHOMA

ARKANSAS

- CountyLine ""- River ReachBoundary ( Reach Number

Figure 1. Map of the Study Area.

adequate economic model [Grossman and Irrigation water requirements for each Keith]. Data provided by the physical scien- crop were based on "average" consumptive tists for each evaluation reach included: (1) use of water for each crop. Average consump- irrigation water requirements for each crop tive use calculations for each crop were based grown in the study area, adjusted for normal on methodology used by McDanields. Con- precipitation and leaching requirements; (2) sumptive use estimates of water which would reduction in yield attributable to the chloride need to be supplied by irrigation were fur- concentration with and without the project; ther refined by consideration of effective av- (3) acreages in each zone and reach potential- erage monthly precipitation differences ly suitable for irrigation (classified by soil among reaches.l In addition, a 20% leaching type, slope, and land capability class); (4) fraction was assumed to be the standard prac- recommended irrigation systems for each soil tice [Gerard et al., 1979a]. Further, irriga- type (furrow, border, or sprinkler); and (5) tion system efficiency rates of 75 and 85 current acreages of major crops. Further, percent for sprinkler and surface systems, estimates of the amount of water available for respectively, were used to adjust the total irrigation from the Red River alluvium, by amount of irrigation water that must be reach, were provided by the Corps of Engi- pumped to account for losses within the wa- neers. ter distribution system. Of the items listed above, the information Reduction in crop yields attributable to in items 3 through 5 require substantial time chloride concentrations of the Red River irri- and effort to determine, but their determi- and subject to nation is rather sraightforward 1Effective rainfall for the different reaches was estimated little controversy. Items 1 and 2, on the other using U.S. Department of Agriculture Soil Conserva- hand, are critical to this analysis and are tion Service Engineering Division Technical Report worthy of further explanation. No. 21 [Gerard, et. al., 1979a]. 197 December 1981 Western Journal of Agricultural Economics gation water with and without the project based on a 100-year (years 1990-2090) plan- and with and without SAR crop yield effects ning horizon using OBERS Series E' [U.S. is a critical issue of this paper. Estimated Water Resources Council, 1978b] projection salinity and SAR values for water in the Red yield adjustments through the first 50 years River are given for both with and without the and the 50th year cropping plan for the re- project in Gerard, et al., [1979a.]. Yield remaining years.2 OBERS yield projections are ductions due to salinity alone were estimated based on historically derived rates. An inves- for both the with and without project condi- tigation of historical data from Texas and tions by using procedures described in U.S. Oklahoma indicated no long-term increasing Salinity Handbook No. 60 [Richards]. These trend for yields of grazed forages and alfalfa. estimates were based on river water salt con- Since OBERS does not include increased centration estimates made by the Corps of forage yield projection and none were found Engineers. Yield reduction equations were in our investigation, none were assumed in developed for each crop from data given by this study. Ayers and Westcot [Gerard, et al., 1979a]. The general model developed was a recur- Yield reductions that would result from a sive linear program with two FORTRAN combination of saliity and SAR effects were components: a matrix generator and a report estimated from research experience, obser- writer. The matrix generator served to de- vation, and yield data collected at the Texas velop a unique enterprise budget for each A&M Experiment Station at Iowa Park. Ef- combination of crop, soil type, irrigation sys- forts to measure the yield reduction effects tem, and zone in each reach, and to create using standard soil testing procedures proved the initial matrix for the linear programming inconclusive as to combined salinity and SAR model for five 10-year intervals from 1990 to effects. Thus, the best estimates of these 2040. The report writer greatly simplified the effects from soil scientists were used to inves- analysis by organizing and summarizing the tigate the impacts of the additional SAR in- linear programming solutions, which con- duced yield reduction [Gerard, et al., tained more than 8,000 activities each and 1979b]. Table 1 gives the estimated percent writing concise reports, by evaluation reach, yield reduction for both with and without for the entire period of analysis. SAR crop yield effects and with and without the project. Evaluation of each reach with The Model and without the project and with and without The objective of the linear program for SAR crop yield effects makes possible an each evaluation reach was to maximize net investigation of the distribution of expected returns constrained by (1) the amount of land benefits throughout the river basin for both in each soil type in each zone and each reach, situations, as well as an estimate of the total and (2) the amount of water available for agricultural benefits of the salinity control irrigation in each reach. Net revenue max- project in each case. imization was performed for each 10-year was de- A linear programming model interval (i.e., for years 1990, 2000, 2010, ... , veloped and used to obtain normative esti- 2040). Temporal yield adjustments [OBERS returns mates of cropping patterns and net Series E'] caused changes in many of the of two from agricultural production for each calculations that were originally based on scenarios - (1) where SAR causes crop yield reduction in addition to salinity effects, and (2) where SAR is not included as a problem. Model evaluation with and without the project formed the basis of analysis with profit 2A much more extensive analysis including several other maximization assumed the goal of the pro- scenarios was performed in this study. The complete ducers in each reach. Each scenario was study is published in Laughlin, Lacewell and Moore.

198 Laughlin and Lacewell Benefits of Salinity Control

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199 December 1981 Western Journal of Agricultural Economics

yields, thus requiring a new tableau in each irrigation water available, and (9) acreage of 3 period. each crop grown currently (optional). Data Estimates of current crop yields by soil stored internally included (1) fertilizer rec- type for both irrigated and dryland produc- ommendations as a function of yield by crop, tion were developed for the major crops in (2) harvesting costs as a function of yield by the study area: cotton, grain sorghum, crop, (3) fertilizer prices, (4) water cost equa- wheat, alfalfa, and Coastal bermuda. Native tions, (5) interest rates to be used on variable pasture was included as a dryland option capital costs, and (6) OBERS Series E' yield only. Using these yield estimates, current adjustment coefficients. prices for production inputs, current produc- The matrix generator operated as a series tion practices, and normalized product prices of inner loops to make adjustments to the issued by the U.S. Water Resources Council, base budgets for yield differentials by soil 1978a, base crop enterprise budgets were type and irrigation cost differentials due to developed for each crop for both dryland and differences in quantity of water pumped and irrigated production, based on a common soil method of distribution. Outer loops adjusted type in the study area. The assumed non- yields according to OBERS Series E' projec- changing elements of these base budgets tions for each reach to produce the recursive were then used in the matrix generator in feature. Thus, the first pass through the ma- establishing the activities of the LP matrix. trix generator created the 1990 initial tableau; yields were adjusted by OBERS projec- Matrix Generator tions; and another pass through the matrix generator created The matrix generator was essential to de- the year 2000 tableau, etc. Within velop a complete initial tableau for the linear the inner loops each crop alterna- tive along programming model. With 11 reaches to with its applicable irrigation type (sprinkler, model, an average of 23 different soil types in furrow, or nonirrigated) was matched each reach, five major crops in the region, with each soil type to form the activity base three irrigation types, and three zones (0.5, for the LP model. After this base matrix formation, 1.0, and 1.5 miles from the river), a matrix the matrix generator proceeded generator was the only practicable method of to define enterprise budgets for each crop developing coefficients for this multitude of as follows: (1) adjust inputed high- distinct activities. level management yields for each crop to typical-level In addition to data from the base budgets, management, (2) adjust yield for each crop other vital elements were either read into the for the appropriate salinity level (either matrix generator or stored internally. Data with or without project), (3) adjust inputed irrigation required as input were (1) irrigation water water requirement for distribution system efficiency, requirements for each cropping activity, (2) (4) establish fertilizer crop yield, by soil type, (3) yield reduction application rates on basis of crop yield, (5) calculate due to irrigation water salinity and the com- irrigation water costs holding fixed and variable bination of salinity and SAR level by crop, (4) costs separate for later calculations, costs of production for each crop (only (6) calculate fertilizer costs, (7) estimate specified non-changing costs were included harvesting costs as a function of crop yield, (8) calculate as some cost calculations were made internal- interest on operating capital, (9) calculate ly), (5) crop prices, (6) acreages of each soil management charges, (10) determine type, (7) total current cropland acres, (8) total total revenue as adjusted yield times price, and finally (11) calculate net revenue. Upon completion of these calcula- 30ther scenarios which constrained crop acreages to tions, the matrix generator formats and current cropping patterns, constrained irrigated acreages, and without crop yield increases through time are writes each entry necessary for the linear reported in Laughlin, Lacewell and Moore. programming package. 200 Laughlin and Lacewell Benefits of Salinity Control

Report Writer where relatively little yield reduction of cot- The report writer was the final phase of the ton and no yield reduction of grain sorghum mathematical model. It read the linear pro- is caused by salinity even without the programming solution of each 10-year period in ject. With the project in place, this study terms of objective function and cropping pat- indicated that irrigated cotton would move tern. An objective function was linearly in- into the western reaches as well. This move- terpolated for each year between the 10-year ment comes primarily at the expense of dry- solutions and discounted to a present value land cotton in the early years and additional basis at 71/s percent (the project discount rate). acreages of forage crops through time. Irri- Lastly, a summary of cropping patterns for gated sorghum acreages are not changed each reach for each 10-year period and a from the without to the with project condi- summary of annual discounted net returns tion, since all of the sorghum without the for the 100-year period of analysis were print- project was located in the eastern reaches ed by the report writer. where no salinity-induced yield reduction occurs either with or without the project. Results Thus, benefits would accrue primarily to the western reaches since, based on the assump- The primary objective of this study was to tion of optimal land use both with and with- estimate potential agricultural benefits of the out the project and no SAR crop yield effects, proposed chloride control project. Also, the those were the only reaches (10, 11, 13, 14 effect of SAR yield impacts on the total and and 15) that had potential to increase produc- the distribution of benefits and resulting tion as a result of salinity control of the cropping patterns was of equal importance in irrigation water. Table 2 shows the projected this paper. The cropping pattern estimates optimal land use pattern for the entire study identify adjustments required to realize es- area for years 1990 through 2040 with and timated benefits. without the project and without SAR crop yield effects. With SAR crop yield effects included Cropping Patterns and without the salinity control project, the mod- Throughout the study area the major irri- el results indicate that much less cotton and gated crop identified by the model was cot- no grain sorghum should be irrigated. Yield ton. Nonirrigated land was allocated by the reduction due to salinity and the SAR effects model to varying mixes of cotton, grain sor- in the eastern reaches limit irrigation only to ghum, alfalfa, Coastal bermuda, and native cotton on the highly productive soils. With pasture. Wheat production never entered the salt control project, a sizable increase in the optimal land use patterns because of its irrigated cotton acreage is projected through- projected low net returns. In general, a tem- out the study area (except in Reach 5 where poral shift out of forages and into cotton was salinity and SAR are not a problem with or predicted by the model. This resulted from without the project). Further, a small acre- the application of OBERS yield projections age of irrigated grain sorghum is projected and the exclusion of forages from yield in- (primarily on a soil series in Reach 6 well crease estimates through time. adapted to grain sorghum production). In the Without SAR crop yield effects and with- eastern reaches, yield reduction to cotton out the salinity control project, optimal land due to salinity and SAR declines to zero with use involved substantial irrigated and dry- the project in place, and thus a large poten- land cotton and a small amount of irrigated tial for benefits exists. In the western sorghum. Most of the irrigated cotton and all reaches, yield reduction to cotton occurs of the irrigated sorghum was placed in the even with the project but is still not sufficient eastern reaches (Reaches 5, 6, 7, 8, 9 and 12) to make irrigated cotton less profitable than 201 December 1981 Western Journal of Agricultural Economics

TABLE 2. Projected Optimal Land Use with Project Compared With Projected Optimal Land Use Without Project by 10-year Increments, 1990-2040, Without SAR Effects (Acres). Crop 1990 2000 2010 2020 2030 2040 All Reaches Irr. Cotton With 274,817 280,658 280,712 282,067 282,067 282,026 Without 166,760 171,228 171,281 171,282 162,669 162,669 Dry Cotton With 266,320 342,019 343,727 345,366 345,366 345,407 Without 348,175 451,450 453,158 456,151 464,764 464,764 Irr. Sorghum With -- 962 2,200 2,200 1,184 1,231 Without -- 962 2,200 2,200 1,184 1,231 Dry Sorghum With 446 375 15,854 33,620 34,636 34,636 Without 446 375 15,854 33,620 34,636 34,636 Dry Alfalfa With 57,161 13,020 5,292 ------Without 57,161 13,020 5,292 Dry Coastal With 49,814 21,727 15,467 Without 73,776 21,727 15,467 ------Native Pasture With 17,785 7,582 3,091 3,091 3,091 3,044 Without 20,026 7,582 3,091 3,091 3,091 3,091 Total 666,344 666,344 666,344 666,344 666,344 666,344 other alternatives. Table 3 gives the project- control result in increased total benefits ed optimal land use patterns with and with- when the damages are virtually eliminated. out the project for the scenario where addi- Not only are the total benefits higher assum- tional SAR crop yield reduction is included. ing SAR is a problem, but the distribution of benefits is dramatically changed among Benefits reaches. In general, with an SAR yield effect, Net agricultural benefits were estimated benefits shift away from the western reaches using the discount rate for federal project (10-15) near the salt sources and to the east- evaluation at the time of the study - 71/ ern reaches (6-9). Two western reaches (12 percent. Total projected increases in present and 14) gain slightly but not enough to offset value of agricultural net returns to land at- the losses (between scenarios) by reaches 10, tributable to the proposed salinity control 11, 13 and 15. This decrease in benefits of the project were $65.794 million without SAR western reaches results because without the crop yield effects (Table 4) and $117.395 project very little or no irrigation is possible million with SAR effects (Table 5). either with or without SAR crop yield effects. The difference between the with and with- However, even with the project in place, out SAR crop yield effects scenarios is signifi- substantial yield reduction to cotton still re- cant. The total agricultural benefits increased sults where SAR is a problem, while without from $65.8 to $117.4 million where SAR SAR problems much less yield reduction oc- effects were included as an additional yield curs. Thus, in this case, the additional de- reduction; i.e., increased "damages" from crease in yield that occurs as a result of SAR the additional SAR effects without salinity problems even with the project causes de- 202 Laughlin and Lacewell Benefits of Salinity Control

TABLE 3. Projected Optimal Land Use with Project Compared With Projected Optimal Land Use Without Project by 10-year Increments, 1990-2040, With SAR Effects (Acres). Crop 1990 2000 2010 2020 2030 2040 All Reaches Irr. Cotton With 235,877 238,341 232,068 230,454 228,989 228,411 Without 93,030 85,396 85,132 78,836 78,836 78,247 Dry Cotton With 298,260 384,337 392,372 396,979 398,444 399,022 Without 408,850 537,282 539,308 548,597 548,597 549,186 Irr. Sorghum With -- 962 2,200 2,200 1,184 1,184 Without ------Dry Sorghum With 446 375 15,854 33,620 34,636 34,636 Without 446 375 18,054 35,820 35,820 35,820 Dry Alfalfa With 57,161 13,020 5,292 ------Without 57,161 13,020 5,292 Dry Coastal With 56,407 21,727 15,467 Without 86,831 22,689 15,467 ------Native Pasture With 18,193 7,582 3,091 3,091 3,091 3,091 Without 20,026 7,582 3,091 3,091 3,091 3,091 Total 666,344 666,344 666,344 666,344 666,344 666,344

TABLE 4. Estimated Present Value of Total Project Benefits Over the 100-year Period 1990- 2090, Profit Maximizing Objective, With and Without the Project, and Without SAR Effects, 71/8% Discount Rate. Present Value of Present Value of Net Revenues Net Revenues Present Value With Project Without Project of Net Benefits Reach

------.------. $1,000 ------5 99,396 99,396 0 6 186,920 186,920 0 7 32,036 32,036 0 8 205,322 205,322 0 9 48,770 48,770 0 10 21,577 15,812 5,765 11 18,885 13,047 5,838 12 44,783 44,783 0 13 100,209 71,609 28,600 14 144,598 126,902 17,696 15 51,929 44,034 7,895 Total 954,425 889,375 65,794

203 December 1981 Western Journal of Agricultural Economics

TABLE 5. Estimated Present Value of Total Project Benefits Over the 100-year Period 1990- 2090, Profit Maximizing Objective, With and Without the Project, and With SAR Effects, 71/8% Discount Rate. Present Value of Present Value of Net Revenues Net Revenues Present Value With Project Without Project of Net Benefits Reach

.------..---.------.$1,000 ------5 99,396 99,396 0 6 186,920 170,198 16,722 7 32,036 26,036 6,000 8 205,322 164,923 40,399 9 48,770 34,812 13,958 10 19,390 15,812 3,578 11 16,535 13,791 2,744 12 42,528 41,221 1,307 13 83,575 71,608 11,967 14 133,866 114,330 19,536 15 45,218 44,034 1,184 Total 913,556 796,161 117,395

creased benefits in the western reaches of the As a sidelight, considering municipal and study area as compared to the analysis where industrial benefits and irrigation benefits of SAR yield effects do not occur. the chloride control project, the benefit/cost In the eastern reaches (6-9) somewhat of ratio was estimated to be 1.068 where an the reverse occurs. Damages to cotton with- SAR effect on crop yield was not included out the project and without SAR crop yield and 1.291 where an SAR crop yield effect was effects are zero, thus resulting in no benefits included. from salinity control in those reaches. How- ever, with SAR crop yield effects some dam- Conclusions and Limitations age does occur without the project. When the project is installed and salinity con- The results of this study indicate substan- trolled, yield reduction in cotton no longer tial agricultural benefits from salinity control occurs, and substantial benefits from in- on the Red River under two assumptions- creased crop yields occur. Thus, the eastern one which included SAR crop yield effects reaches are estimated to benefit only if SAR and one which did not. Total benefits were is a significant problem while the western estimated to be much higher when an SAR reaches benefit more if SAR is not a signifi- crop yield impact was included, while the cant problem than if it is. distribution of benefits was very sensitive to Results of this study emphasize that for an the SAR crop yield effect. Benefit estimates economic analysis of salinity control for irri- in both scenarios (with and without SAR gation it is essential that the SAR effect on effect) were calculated as the difference in crop yield be approximately quantified. In- present value of profit maximizing net re- clusion or noninclusion of SAR yield effects turns with and without the project. The num- dramatically impacts the size of the irrigation erical accuracy of these findings depends benefit estimate as well as the distribution of greatly on whether producers actually ap- benefits within a region. proximate profit-maximizing behavior and on 204 Laughlin and Lacewell Benefits of Salinity Control

the accuracy of the assumed parameters. Gerard, C. J. "The Influence of Soil Moisture, Soil Further, use of normalized crop prices in this Texture, Drying Conditions and Exchangeable Ca- case tended to underestimate current farm tions on Soil Strength." Soil Science Society of Ameri- ca Proceedings. prices, while costs represented current values. This affects project benefits as well as Gerard, C. J., B. W. Hipp, J. R. Runkles, and W. G. absolute profitability for a crop and relative McCulley. "Water Requirements", Chapter 3. Gross- profitability among crops. Lastly, the re- man & Keith/Consulting Engineers, 1979a. gional LP model does not consider unique Gerard, C. J., D. Bordovsky, W. G. McCulley, and resources of a farm firm and hence may not B. W. Hipp. "Effects of Water Quality on Saturated estimate the profit maximizing situation on a Hydraulic Conductivities of Different Soils in the Red farm basis. Furthermore, the overall regional River Valley," Chapter 4, Grossman & Keith/Consult- cropping pattern identified by this type of LP ing Engineers, 1979b. model may not be the same as the aggrega- Grossman & Keith/Consulting Engineers. Red River tion of all optimal farm planning solutions. Chloride Study, Analysis of Irrigated Agriculture. Nevertheless, this analysis has shown that Final contract report to the Tulsa District Army Corps substantial benefits from salinity control in of Engineers, 1979. the study area are possible and has pointed Lacewell, R. D. and G. D. Condra. out that the The Effect of size and distribution of benefits Changing Input and Product Prices on the Demand can vary greatly depending on which SAR for Irrigation Water in Texas. Texas Water Resources crop yield impact parameter is used. Institute Tech. Rep. 75, 1976.

Laughlin, David H., Ronald D. Lacewell and Donald S. Moore, The Agricultural Benefits of Salinity Control References On The Red River of Texas Oklahoma, Texas Water Resources Institute, Texas A&M University, Tech. Adams, B. M., R. D. Lacewell, and G. D. Condra. Eco- Rep. 112, December 1980. nomic Effect on Agricultural Production of Alterna- tive Energy Input Prices: Texas High Plains. Texas Longenecker, D. E. and P. J. Lyerly. Control of Soluble Water Resources Institute Tech. Rep. 73, 1976. Salts in Farming and Gardening. Texas Agricultural Experiment Station Bulletin B-876, June 1974. Anderson, Jay C. and Alan P. Kleinman. Salinity Man- agement Options for the Colorado River. Water Re- Mapp, H. P. and C. L. Dobbins. "Implications of Rising source Planning Series Report, P-78-003. Logan: Utah Energy Costs for irrigated Farms in the Oklahoma State University, 1978. Panhandle." American Journal of Agricultural Eco- nomics. 58(1976): 971-77. Ayers, R. S., and D. W. Westcot. "Water Quality for Agriculture," Irrigation and Drainage Paper No. 29, Mass, E. V. and G. J. Hoffman. "Crop Salt Tolerance 1976. Current Assessment." Journal of Irrigation and Drainage Div. ASCE, No. IR2, Proc. Paper 12993. Casey, E., L. L. Jones, and R. D. Lacewell. "Estimating 103(1978): 115-34. Regional Output Response to an Exhaustible Natural Resource." Western Journal of Agricultural Econom- McDanields, L. L. Consumptive Use of Water by Major ics, J. Agr. Econ. 1(1977): 269-71. Crops in Texas. Texas Board of Water Engineers Bulletin 6019, 1960. Condra, Gary D., R. D. Lacewell, Daniel C. Hardin, Kenneth Lindsey, and Robert E. Whitson. An Eco- McFarland, James W. "Groundwater Management and nomic Feasibility of Irrigated Crop Production in the Salinity Control: A Case Study in Northwest Mexico." Pecos Valley of Texas. Texas Water Resources Insti- American Journal of Agricultural Economics. tute Tech. Rep. 101, March 1979. 57(1975): 456-62.

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205 December 1981 Western Journal of Agricultural Economics

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