WSP06476

• File Number: 8271.300
• Description: Colorado River Basin Salinity Control Program - General Information and Publications-Reports
• Basin: Colorado Mainstem
• Water Division: 5
• Date: 6/1/1978
• Title: Salinity Management Options for the Colorado River -- Part 1 of 2 -- Title Page - Page 168
• Water Supply Pro - Doc Type: Report/Study

."

Table 29. Comparison of drainage and salt outflow to groundwater for corn, alfaJla, and oats at various levels of
water application and initial salt concentration.

~
"'-l
. ,
, ~
~

Irrigation Drainage in Centimeters
and Rain
em Corn Alfalfa Oats
5.6 .14.2 .9.7 .3.8
5.6 .14.2 -9.4 .3.8
5.6 .11.6 .7.8 .3.6
10.3 .14.1 .9.5 .3.8
10.3 .14.0 .9.3 .3.8
10.3 .11.4 .7.7 -3.5
15.0 .14.0 .9.3 .3.8
15.0 .13.9 .9.2 .3.8
15.0 .11.4 -7.6 .3.5
22.0 .13.6 .9.4 .3.8
22.0 .13.5 -9.2 .3.8
22.0 .11.3 .7.5 .3.3
40.8 -8.7 .7.4 .2.5
40.8 .7.1 -6.7 .2.4
40.8 -6.2 .5.6 .1.2
56.4 0.9 0.0 1.3
56.4 1.0 0.4 1.3
56.4 1.1 0.3 2.5
66.7 10.5 8.8 10.0
66.7 10.6 9.3 10.0
66.7 10.8 9.4 9.9

return data for the farm. The beginning point is to
assume tbat any amount of salt can be allowed to leave
tbe farm. The model is set to maximize net income
under this assumption, then it is successively'
constrained to allow smaller and smaller amounts of
salt outflow. Of primary concern is the reduction of
income which accompanies this constraint on resource
use. Also of concern are the cropping and irrigation
management alternatives as they affect income and
salt outflow.

As the salt outflow and income incrementally
change, the model develops as a by-product the
marginal relationship between salt outflow and
income. From this relationship a shadow price is
derived whicb reflects the value of an additional ton of
salt outflow in terms of net income, or the amount of
the income loss that occurs as salt outflow is
incrementally reduced. This value can be compared
witb alternative ways of reducing salinity in the river
or compensating the damages that accrue to down.
stream users.

The linear programming model used in this study
is a profit maximizing model which has the algebraic
form:

Maximize Z = ex
Subject to AX ~ B
X;;>O

in which Z is net income or profit, C is the row vector
of net revenue per unit of activity, X is the set of

Salt Flow to Groundwater in
Millequivalents

Initial Salt
Concentration
Meq/Liter

20
50
200

20
50
200

20
50
200

20
50
200

20
50
200

20
50
200

20
50
200

Alfalfa

Oats

Corn

.195
-472
.1561

.189
-466
.1860

.154
-458
-1840

.148
-461
.1840

-148
.370
.1340

o
22
61

178
467
1882

.74
.191
-718

-76
.190
.700

-76
.189
.700

.76
.190
-660

.50
.120
-240

26
66
490

198
495
1975

.284
-710
.2320

.282
.700
-2280

.280
-695
.2280

.272
-675
.2260

.174
.355
.1240

19
49
214

210
532
2160

activities or production processes, A is the matrix of
technical coefficients or production relationships, and
B is the column vector of constraints on resource
availability.

Linear programming and tbe economic concepts
involved were applied to the present study as follows:

1. The optimal combination of crops to be
produced is selected subject to constraints on
certain fixed inputs such as land.
2. Many of the inputs are not fixed, therefore, the
optimal combination of these inputs can be
selected by considering their relative producti.
vity and cost.
3. The optimal level of output per acre is defined
and selected at the point where the value of the
incremental unit of production or output equals
the cost of the incremental unit of input.

Using the multi.year calculation of soil salinity
during a given year where the initial soil salinity level
depends on the final salinity of the previous year, a
simple recursive program was adopted to calculate
and maximize net income over a 6~year period. Instead
of using stochastic processes to estimate supply
relationships by the prices of commodities and their
major competitors, we began with the technical
structure of the decision-making process and derived
~m it the relationships connecting production to
pnces, costs, acreage controls, and technological
changes. This technique was adapted to maximize net
revenue subject to salinity constraints over a 6.year
period.

29