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

MODELING THE SOIL.W ATER-PLANT
RELATlONSRIP8, CASE STUDY IN UTAB

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Before it is concluded that modifications which
reduce salinity leaching are really a valuable
management tool, it is necessary to explore the actual
response of crop, soil, and water factors to irrigation
practices and the cost effectiveness of proposed
irrigation practices. Specifically stated, this portion of
the study involved tbe development of a physical
model to predict the response of soil, water, and crop
factors to irrigation and the development of an
economic model which, using the physical model for
bssic data, predicted the cost effectiveness of
irrigation management as related to return flow
salinity (Appendix 6). Tbese models were originally
developed to determine optimal cropping. and irriga'
tion strategies subject to certain constraints for a
one.year period. A multi.year analysis was subse.
quently developed by using the final conditions of a
given year for the initial soil aalinity conditions of the
following year subject to the assumptiona of the
physical model. The physical and economic models are
discussed separately for purposes of organization and
convenience to the reader.

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The Physleal Model

The model used in this study is concerned with
the soil water flow in response to varying irrigation
management inputs. Tbe general equation for water
flow is given as:

~ = ~ (KaH) +a(z)....... .......(1)
at az \ az

in which '0 is the water content, t is time, K is tbe
hydraulic conductivity, H is the matrix potential, z is
depth, and a(z) is the root extraction term.

The salt flow portion of the model is given as
follows:

aco = ~ (D ac) . d(Cq) . . . . . .........(2)
at a z I; a z dz

in which C is the salt concentration, D includes the
combined diffusion and dispersion coefficients, and q is
the mass flux of water.

To determine the influence of salinity on the
crop yield, another component must be added to tbe
model. This is done by assuming the relative yield was
related to relative transpiration as follows:

I = ..!.............................(3)
Yp Tp

in which Y is the dry matter yield of a given crop for
the season, T is the transpiration for the same crop for

the same aeason, Y p is the potential yield for the same
crop and season where soil water or salinity did not
reduce yields, and T p is tbe potential transpiration for
the same crop and season where soil water or salinity
did not reduce yields. The ratio of actual yield to
potential yield under uideal" conditions is aD important
component of the model and because of the stated
assumptions may be represented also as the ratio
T/Tp. The ratio is shown to vary considerably among
various irrigation management practices and initial
soil salinity levels. Since variation in the ratio reflects
varistion in agricultural productivity, it will be of
interest to agricultural water users and policy makers.

The procedure followed was to compute various
consequences of a given irrigation management
sequence for a typical season ss a. function of soil and
crop conditions for that season. Three important
factors were varied and the outputs predicted which
resulted from the varistion. The three factors were
irrigation, initial soil salt concentration, and cropping
varisbles. Irrigation wss applied in the simulations
according to the frequency used on the experimental
farm in tbe Colorado River Basin during 1971. The
amount of water applied was varied from zero to
sufficient to cause considerable drainage. The initial
salt concentration in tbe soil was assumed to be
uniform at the beginning of the season at 20, 50, or 200
millequivalents per liter. The 20 meq/I concentration
represents present conditions on tbe experimental
farm. The 50 meq/I and 200 meq/I are used to simulate
salt buildup that would occur over several years if
proper draiDllge, or insufficient leaching were not
achieved.

Three crops were simulsted: alfalfa, corn, and
oats. The varistion of the crop component amounted to
varying the root zone dimensions and tbe ratio of
actual transpjration to potential transpiration. The
only situations deemed relevant for this pre80ntstion
are those in which the depth of alfalfa roots is assumed
to be greater than the depth of corn roots. Crop
management varisbles are to be introduced in the
discussion of the economic model.

Table 28 shows the results of varying tbe water
application rate and initial soil salt concentration level
in the cultivation of com, alfalfa, and oats. Table 28
data show tbat the TIT p ratio for corn and alfalfa'
increased in value as the irrigation level increased
until it .reached 1.0 between the 40.8 and 56.4
centimeter levels. TIT did not reach 1.0 for oats.
However, the pattern gf increase through the water
application levels was similar to that of corn and
alfalfa. The smaller values of T /Tp for oats are due
chiefly to a more shallow root depto. The data show a
more significant decrease in TIT for alfalfa than for
corn in the lower irrigation rails. This ia due to a
longer season of active water use by alfalfa and for a
much greater proportion of transpiration to evapo-
transpiration for alfalfa than for corn.

There was relatively little difference between the
T ITp values of the two lower initial salt concentration

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