1. Irrigation project design
2. Irrigation project operation
3. Drainage projects
4. Rice cultivation
5. The effect of groundwater
6. Effective rainfall in unirrigated and low rainfall, areas
Knowledge of effective rainfall is vital for efficient utilization of water in irrigated agriculture. Application of information on effective rainfall is shown in the subsequent pages with sample calculations and illustrations for design of irrigation projects, operation of irrigation projects, design and operation of drainage systems, leaching of salts, rice cultivation, planning of irrigation systems using groundwater, and for rainfed agriculture.
Monthly, seasonal and annual rainfall varies from year to year, so does the effective rainfall, and consequently irrigation requirements. The Water supply cannot be planned on the minimum value of effective rainfall since this would result for most years in a highly uneconomic and wasteful project. Nor can it be based on the average amount of effective rainfall since this would provide an adequate and assured water supply for approximately only half the time. Therefore, the value of effective rainfall is computed on a probability basis. The percent chance of its occurrence is selected on a number of considerations, including yield predictions, cost of the system and financial returns; for instance, for a high value crop like vegetables, a water supply may be based on effective rainfall occurring nine years out of ten but for a low value crop, five out of ten years may be adequate.
The water supply to be developed is to be based on the percent chance of occurrence chosen which exceeds the gross irrigation requirement of the crop during the chosen period. If this is 10 percent, for example, the water supply for that period would be adequate in 9 years out of 10. The 90 percent chance effective rainfall will need to be determined.
Data items needed are rainfall data for several years, weekly; consumptive use data, mean monthly; available water storage capacity of soils in the scheme area, mean data for different soil types or classification units; irrigation efficiency, percentage or fraction; type of crops and acreages, their sowing and harvesting times, critical stages in crop growth, and special water needs if any; economic factors from which chance of occurrence of rainfall can be selected,
A procedure to develop gross irrigation requirements is given below.
Rainfall data can normally be obtained from available records. The rainfall values are arranged in order of magnitude and their cumulative frequency is worked out. In drawing cumulative frequency distribution of rainfall on a log-normal probability paper the following steps are required:
Step 1s obtain rainfall data for as many years as possible (columns 1 and 2);
Step 2: arrange them in order of magnitude, with the largest number first (columns 3 and 4);
Step 3: calculate the plotting position (Fa) by using the Hazen equation (USDA, SCS, 1967):
Fa = [100 (2n - 1)] / 2 y
Fa = the plotting position in percent
n = the rank number
y = the number of years of record keeping
Step 4: prepare the vertical scale of the log-normal probability paper and plot the rainfall on the vertical logarithmic scale against the Fa positions on the percent chance scale (Fig 8).
Step 5: drew the best fitting line through the plotted points as shown in Fig 8. For instance, at the 80 percent chance level, the rainfall is about 350 mm.
Years |
Annual rainfall (Ra) mm |
n |
Ra |
Fa |
(1) |
(2) |
(3) |
(4) |
(5) |
1934 |
380 |
2 |
960 |
3.8 |
1935 |
720 |
3 |
900 |
6.3 |
1936 |
1000 |
4 |
880 |
8.8 |
1937 |
900 |
5 |
860 |
11.3 |
1938 |
800 |
6 |
840 |
13-8 |
1939 |
520 |
7 |
800. |
16.3 |
1940 |
380 |
8 |
780 |
18.8 |
1941 |
260 |
9 |
760 |
21.3 |
1942 |
300 |
10 |
720 |
23.8 |
1943 |
620 |
11 |
700 |
26.3 |
1944 |
840 |
12 |
700 |
28.8 |
1945 |
300 |
13 |
560 |
31.3 |
1946 |
340 |
14 |
620 |
33.8 |
1947 |
660 |
15 |
600 |
36.3 |
1948 |
960 |
16 |
600 |
38.8 |
1949 |
240 |
17 |
580 |
41.3 |
1950 |
280 |
18 |
560 |
43.8 |
1951 |
400 |
19 |
540 |
46.2 |
1952 |
600 |
20 |
520 |
48.8 |
1953 |
880 |
21 |
500 |
51.2 |
1954 |
860 |
22 |
500 |
53.8 |
1955 |
780 |
23 |
480 |
56.2 |
1956 |
760 |
24 |
480 |
58.7 |
1957 |
360 |
25 |
460 |
61.2 |
1958 |
420 |
26 |
440 |
63.7 |
1959 |
540 |
27 |
420 |
66.2 |
I960 |
700 |
28 |
400 |
68.7 |
1961 |
360 |
29 |
400 |
71.2 |
196?. |
400 |
30 |
380 |
73.7 |
1963 |
440 |
31 |
380 |
76,2 |
1964 |
460 |
32 |
360 |
78.7 |
1965 |
480 |
33 |
360 |
81.2 |
1966 |
480 |
34 |
340 |
83.7 |
1967 |
500 |
35 |
320 |
86.2 |
1968 |
700 |
36 |
300 |
88.7 |
1969 |
500 |
37 |
300 |
91.2 |
1970 |
560 |
38 |
280 |
93.7 |
1971 |
580 |
39 |
260 |
96.2 |
1972 |
600 |
40 |
240 |
98.7 |
Fig 8: FREQUENCY DISTRIBUTION 0F RAINFALL
A sample calculation of irrigation water requirements is given in Table 10. In Table 10, from the above data, the 50 and 75 percent (or any other) chance rainfall can be determined, which is here 500 and 374 mm respectively. The ratio 374/500 = 0.75 is used here to determine the rainfall at 75 percent chance of occurrence for each month, assuming that the frequency distribution of yearly or seasonal rainfall is the same as the frequency distribution of each month. From data on mean monthly water needs and 50 or 75 percent chance monthly rainfall, the 50 and 75 percent chance effective rainfall is obtained from Table 8. Gross irrigation requirements can be calculated from crop water need and carryover soil moisture data and selected irrigation application efficiency for 50 and 75 percent chance effective rainfall or, in the example in Table 10, 404 and 513 respectively.
Rainfall patterns will differ from month to month. Rather than using a constant ratio derived from seasonal or yearly data, the 75 percent chance or any other percent chance monthly rainfall should preferably be determined from a rainfall frequency distribution analysis prepared for each month using the step method described above. This would also allow a selection of percent chance of rainfall occurrence for each month, with possibly a higher percentage when water is needed most, such as during the flowering stage of most crops. The calculations will be similar to those given in Table 10, except for column 9.
Table 10: SAMPLE CALCULATION OF IRRIGATION WATER REQUIREMENTS AT 50% AND 75% CHANCE OF OCCURRENCE OF RAINFALL (mm)
Month |
Mean monthly water need |
Monthly rainfall at 50% chance of occurrence |
Monthly effective rainfall at 50% chance of occurrence |
Carry over soil moisture |
Total available soil moisture |
Net irrigation requirement (Column 2 minus 6 plus 5 of the next month) at 50% chance |
Gross irrigation requirement at 75% irrigation efficiency |
Monthly rainfall at 75% chance of occurrence (Column 3 x R*) |
Monthly effective rainfall at 75% chance (Table 8) |
Carry over soil moisture |
Total available soil moisture |
Net irrigation requirement (Column 2 minus 12 plus 11 of the next month) at 75% chance |
Gross irrigation requirement at 75% irrigation efficiency |
1 |
2 |
3 |
4 |
5 |
6 |
7 |
8 |
9 |
10 |
11 |
12 |
13 |
14 |
May |
25 |
50 |
25 |
50 |
75 |
0 |
0 |
37 |
22 |
50 |
72 |
0 |
0 |
June |
75 |
100' |
64 |
50 |
114 |
0 |
0 |
75 |
50 |
47 |
97 |
3 |
4 |
July |
200 |
150 |
120 |
39 |
159 |
66 |
88 |
112 |
93 |
25 |
118 |
107 |
142 |
Aug. |
200 |
125 |
102 |
25 |
127 |
98 |
130 |
94 |
78 |
25 |
103 |
122 |
162 |
Sept. |
175 |
75 |
60 |
25 |
85 |
115 |
153 |
56 |
45 |
25 |
80 |
129 |
172 |
Oct. |
50 |
0 |
0 |
25 |
25 |
25 |
33 |
0 |
0 |
0 |
0 |
25 |
33 |
Total |
725 |
500 |
371 |
|
|
304 |
404 |
374 |
288 |
|
|
386 |
513 |
*R = [75% chance of total rainfall (374 mm)] / [50% chance of total rainfall (500 mm)] = 0.75
An alternative method for determining first estimates on effective rainfall that will exceed a given percent chance of occurrence is suggested by USDA, SCS (1967). Data needed are average annual rainfall and average effective rainfall; factors with which the average effective rainfall needs to be multiplied to obtain its value for any given percent chance of occurrence are given in Table 11. This method should be used only when no high degree of accuracy is required.
For example, if average annual rainfall is 1 250 mm, and mean effective rainfall is 1 000 mm, the 80 percent chance factor is 0.85 and effective rainfall at 80 percent chance of occurrence is 1 000 x 0.85 = 850 mm.
In a given irrigation project, certain crops may be provided with a water supply at 90 percent level of certainty while the others may be provided with one at 50 percent depending upon their economic value and availability of water. Normally, fruits and vegetables, oilseeds and industrial crops, spices and condiments require an assured supply to obtain high production levels while this may, for a given condition, be a less stringent requirement for cereals, pulses, pastures, and some millets. Irrigation projects should not be based on economic considerations alone; many other aspects, including humanitarian, are also involved in deciding on the level of water to be supplied.
Table 11: FACTORS APPLICABLE TO EFFECTIVE RAINFALL
Mean annual rainfall nun |
Percent chance of occurrence | ||||
|
50 |
60 |
70 |
50 |
90 |
75 |
0.80 |
0.68 |
0.56 |
0.45 |
0.33 |
100 |
.84 |
.72 |
.61 |
.50 |
.38 |
125 |
.87 |
.76 |
.65 |
.54 |
.42 |
150 |
.88 |
.78 |
.68 |
.57 |
.45 |
175 |
.89 |
.79 |
.69 |
.60 |
.48 |
200 |
.90 |
.81 |
.71 |
.62 |
.51 |
225 |
.91 |
.82 |
.73 |
.63 |
.53 |
250 |
.92 |
.83 |
.75 |
.65 |
.55 |
300 |
.93 |
.85 |
.78 |
.69 |
.58 |
350 |
.94 |
.86 |
.79 |
.71 |
.61 |
400 |
.95 |
.88 |
.81 |
.73 |
.63 |
450 |
.95 |
.89 |
.82 |
.74 |
.65 |
500 |
.96 |
.90 |
.83 |
.75 |
.67 |
550 |
.96 |
.90 |
.84 |
.77 |
.69 |
600 |
.97 |
.91 |
.84 |
.78 |
.70 |
650 |
.97 |
.92 |
.85 |
.79 |
.71 |
700 |
.97 |
.92 |
.86 |
.80 |
.72 |
750 |
.97 |
.93 |
.87 |
.81 |
.73 |
875 |
.98 |
.93 |
.88 |
.82 |
.75 |
1000 |
.98 |
.94 |
.89 |
.83 |
.77 |
1125 |
.98 |
.94 |
.90 |
.84 |
.78 |
1250 |
.98 |
.95 |
.91 |
.85 |
.79 |
1375 |
.99 |
.95 |
.91 |
.86 |
.80 |
1500 |
.99 |
.915 |
.91 |
.87 |
.81 |
1750 |
.99 |
.95 |
.92 |
.88 |
.83 |
2000 |
.99 |
.95 |
.92 |
.89 |
.85 |
2250 |
.99 |
.96 |
.93 |
.90 |
.86 |
2500 |
.99 |
.96 |
.93 |
.91 |
.87 |
Rainfall will affect the day to day operation of an irrigation project. Timing and the amount of water applied to the field will affect irrigation efficiency. Irrigation intervals may vary from 4 to 15 days depending mainly on the soil type and crop grown. Scheduling of irrigation should account for the rainfall received and hence precise knowledge about effective rainfall within 24 to 48 hours of its receipt is required for planning the next irrigation application. The operation schedules of the canal system can be subsequently adjusted This will result in a better utilization of available water resources and improved crop production.
The following data are needed: daily rainfall (duration, intensity and amount); mean value of soil water storage capacity in the root zone in the area commanded by an irrigation outlet} ETa data of crops at different stages of growth; thorough knowledge of local agricultural and irrigation practices, including special water needs if any.
A sample of a working sheet for irrigation programming follows. The example applies to conditions where the soil water storage capacity is 120 mm and irrigation is applied when 50% of the total available water has been used. All data are given in mm.
Date |
Initial soil moisture contents |
Irrigation |
Total rainfall |
Eta |
Net change in soil moisture |
Soil moisture balance |
Ineffective rain (surplus) |
Decision |
Date of next irrigation |
Actual irrigation date |
1 |
2 |
3 |
4 |
5 |
6 |
7 |
8 |
9 |
10 |
11 |
1 |
60 |
60 |
0 |
8 |
-52 |
112 |
0 |
Next irrigation not before 7 days |
8 |
0 |
2 |
112 |
0 |
0 |
8 |
- 8 |
104 |
0 |
|
8 |
0 |
3 |
104 |
0 |
20 |
7 |
13 |
117 |
0 |
Irri. postponed by 2 days |
10 |
0 |
4 |
117 |
0 |
30 |
7 |
23 |
120 |
20 |
Storage capacity limited to 60 mm. Irrigation postponed by 1 day |
11 |
0 |
5 |
120 |
0 |
0 |
9 |
- 9 |
111 |
0 |
|
11 |
0 |
6 |
111 |
0 |
0 |
10 |
-10 |
101 |
0 |
|
11 |
0 |
7 |
101 |
0 |
0 |
10 |
-10 |
91 |
0 |
|
11 |
0 |
8 |
91 |
0 |
0 |
10 |
-10 |
81 |
0 |
|
11 |
0 |
9 |
81 |
0 |
0 |
10 |
-10 |
71 |
0 |
Keep ready for irrigation on 11th |
11 |
0 |
10 |
71 |
0 |
10 |
9 |
+ 1 |
72 |
0 |
Irrigation postponed by 1 day |
12 |
0 |
11 |
72 |
0 |
0 |
9 |
- 9 |
63 |
0 |
Irrigate on 12th |
12 |
0 |
12 |
63 |
57 |
50 |
4 |
57 |
120 |
46 |
Rains received in the evening Hence became ineffective |
20 |
12 |
13 |
120 |
0 |
0 |
8 |
- 8 |
112 |
0 |
|
20 |
0 |
14 |
112 |
0 |
0 |
8 |
- 8 |
104 |
0 |
|
20 |
0 |
15 |
104 |
0 |
0 |
8 |
- 8 |
96 |
0 |
|
20 |
0 |
16 |
96 |
0 |
0 |
8 |
- 8 |
88 |
0 |
|
20 |
|
17 |
88 |
0 |
0 |
8 |
- 8 |
80 |
0 |
|
20 |
|
18 |
80 |
0 |
0 |
9 |
- 9 |
71 |
0 |
Keep ready for irrigation on 20th |
20 |
|
19 |
71 |
0 |
0 |
8 |
- 8 |
63 |
0 |
Irrigate on 20th |
20 |
- |
20 |
63 |
57 |
0 |
8 |
+49 |
112 |
0 |
Next irrigation not before 27th |
27 |
20 |
21 |
112 |
|
0 |
8 |
- 8 |
104 |
0 |
|
27 |
|
22 |
104 |
0 |
0 |
8 |
- 8 |
96 |
0 |
|
27 |
|
23 |
96 |
0 |
0 |
7 |
- 7 |
89 |
0 |
|
27 |
|
24 |
89 |
0 |
0 |
7 |
- 7 |
82 |
0 |
|
27 |
|
25 |
82 |
0 |
0 |
8 |
- 8 |
74 |
0 |
|
27 |
|
26 |
74 |
0 |
80 |
3 |
46 |
120 |
31 |
Irrigation postponed by 8 days. Not before 4th of next month |
4 |
|
27 |
120 |
0 |
0 |
7 |
- 7 |
113 |
0 |
|
4 |
|
28 |
113 |
0 |
0 |
8 |
- 8 |
105 |
0 |
|
4 |
|
29 |
105 |
0 |
0 |
8 |
- 8 |
97 |
0 |
|
4 |
|
30 |
97 |
0 |
0 |
8 |
- 8 |
89 |
0 |
|
4 |
|
1 |
89 |
0 |
0 |
9 |
- 9 |
80 |
0 |
Transfer to the next monthly sheet |
4 |
|
Monthly Summary
Total irrigations applied during June = 3 times = 174 mm ETa = 238 mm
Total rainfall = 190 mm Mean ETa per day = 8.0 mm
Ineffective rainfall = 97 mm
Effective rainfall = (ETa - irrigations) + (Final balance - Initial balance) = (238 - 174) + (89 - 60) = 93 mm
To increase the amount of effective rainfall and water economy personal judgment is often needed in scheduling water deliveries. As in the example given, on the 12th day irrigation water was applied in the morning and rain fell in the evening; however, if the sky was cloudy and there was a likelihood of rain, it would have been worth while to take the risk of postponing irrigation by a day.
Based on effective rainfall, swift changes in the scheduling programme can be made from time to time, depending on practicability and flexibility allowed in the operation of the water distribution network.
3.1 Drainage of Excess Water
3.2 Drainage for Leaching of Salts
Land drainage is essential for crop production in areas experiencing heavy rainfall. It is an inseparable part of irrigation systems to control salinity in arid and semi-arid regions for permanent and sustained agriculture. The drains may not necessarily flow throughout the year; the need may exist for just one or two months of the year, as is the case in many parts of the monsoon areas of Asia. Nevertheless, to save the crops from water-logging drainage becomes inevitable.
Depth and frequency of rain and the peak drainage discharge are closely related. The rate at which excess water must be removed from the soil is termed 'drainage co-efficient', which is expressed in mm per day or in m³ /sec/ha. This value is based on rainfall characteristics and on the excess water tolerance of the crop.
For a given situation consideration may need to be given to surface run-off, deep percolation losses from rainfall, seepage of irrigation canals and underground flows from adjacent areas. The absolute as well as relative contributions from the different sources vary in time as well as in quantity. Often they are also interdependent. Only the rainfall component in drainage flows is considered in the following section.
In simple terms, the sum of the daily rainfall minus consumptive use rate plus or minus the soil storage change, is the drainage need. In humid regions, the amount of precipitation will have a direct relationship to the quantity of water to be drained. In arid and semi-arid regions, the annual surface run-off from rain may range from about 0 to 200 mm while the seepage, percolation and leaching in irrigation schemes may range from 200 to 2 000 mm. Losses from irrigation systems may be of great significance. Precipitation is of little consequence and can most often be ignored in computing drainage discharges.
The ineffective rainfall for crop production, less the soil moisture left at harvest, amounts to effective rainfall in drainage, except in cases such as rice, leaching of salts, and. periods outside the growing season. Hence the methodology employed for assessing effective rainfall in crop production can also be used to assess it from the drainage point of view. Daily values of surplus rain water can be worked out for the whole year by the soil moisture balance sheet method. Deep percolation losses can be measured with lysimeters. In case of high groundwater the fluctuation in groundwater tables should be measured. Drainage practices then, can be based on crop tolerance to high groundwater tables taking into account soil and topography and the natural drainage characteristics of the area.
Several semi-empirical methods for estimating run-off for drainage design have been developed; they are given in most standard handbooks on hydrology. A simple method is described below; the method is rather empirical and only provides first estimates on surface run-off for general planning purposes.
The USDA, SCS (1969) has developed a procedure using charts and tables for estimating volume and peak rates of run-off. Apart from rainfall characteristics, important factors influencing rainfall run-off are the run-off potentiality of the area; the antecedent moisture condition; the degree of vegetal cover; conservation practices followed. The peak flow rates are also strongly dependent on slope of the land and area of the watershed. The method includes the following steps:
Processing of rainfall data: by processing records of the daily values of total rainfall, probability values at any frequency, for any given period, are obtained for the project concerned;
Run-off potentiality: the soils are to be grouped into one of the four hydrological classes on the basis of their run-off potentiality which is closely scheduled to their infiltration rates.
Class A (low run-off potential): deep sandy soils;
B: shallow sandy soils and medium texture soils with above average infiltration rates;
C: shallow soils of medium to heavy texture with below average infiltration rates;
D: (high run-off potential) clay and shallow soils with hardpan, high groundwater table, etc.
Antecedent moisture condition: the moisture condition is selected from precipitation during the 5 days (or more) preceding the day in question; there are 3 classes, as follows:
Precipitation during 5 days before the day in question (mm) |
Condition |
|
Growing season |
Dormant season |
|
Less than 35 |
Less than 12.5 |
Dry - I |
35.0 to 52.5 |
12.5 to 27.5 |
Average - II |
Greater than 52.5 |
Greater than 27.5 |
Wet -III |
Run - off equation:
the equation used for surface run-off is:
Q = run-off over the drainage area (mm)
P = precipitation over the drainage area (mm)
S = potential water retention by the soil over the drainage area at time of start of rainfall (mm)
S values are expressed in the relation CN = 1 000/(10 + S).
CN values for the different hydrological classes, A, B, C and D, the vegetal covers and the conservation treatment are shown in Table 12 for antecedent moisture condition II. Corrected values for moisture conditions I (dry) and III (wet) are shown in Table 13. Run-off values (Q) for different values of CN and rainfall rates can be obtained from Table 14.
For example, if a row crop of maize is grown on 40 ha of loamy soil belonging to hydrological class D, without any conservation treatment and having a moderate slope ranging from 3 to 8 percent, the antecedent moisture condition is dry, and the rainfall is 150 nun during 24 hours, evenly distributed, it follows that CN will amount to 91 for medium moisture condition as per Table 12 and 80 for dry condition as per Table 13. The depth of surface run-off flow will be 94.50 mm as per Table 14.
Table 12: CN VALUES FOR WATERSHED CONDITION II FOR DIFFERENT TYPES OF LAND USE
Land use or cover |
Treatment or practice |
State |
Hydrological soil class |
|||
A |
B |
C |
D |
|||
Fallow |
Straight row |
Poor |
77 |
86 |
91 |
94 |
Row crops |
Straight row |
Poor |
72 |
81 |
88 |
91 |
|
Straight row |
Good |
67 |
78 |
85 |
89 |
|
Contoured |
Poor |
70 |
79 |
84 |
88 |
|
Contoured |
Good |
65 |
75 |
82 |
86 |
|
Contoured and terraced |
Poor |
66 |
74 |
80 |
82 |
|
Contoured and terraced |
Good |
62 |
71 |
78 |
81 |
Small grain |
Straight row |
Poor |
65 |
76 |
84 |
88 |
|
Straight row |
Good |
63 |
75 |
83 |
87 |
|
Contoured |
Poor |
63 |
74 |
82 |
85 |
|
Contoured |
Good |
61 |
73 |
81 |
84 |
|
Contoured and terraced |
Poor |
61 |
72 |
79 |
82 |
|
Contoured and terraced |
Good |
59 |
70 |
78 |
81 |
Closed-seeded legumes or rotation meadow |
Straight row |
Poor |
66 |
77 |
85 |
89 |
|
Straight row |
Good |
58 |
72 |
81 |
85 |
|
Contoured |
Poor |
64 |
75 |
83 |
85 |
|
Contoured |
Good |
55 |
69 |
78 |
83 |
|
Contoured and terraced |
Poor |
63 |
73 |
80 |
83 |
|
Contoured and terraced |
Good |
51 |
67 |
76 |
80 |
Pasture or |
|
Poor |
68 |
79 |
86 |
89 |
range |
|
Pair |
49 |
69 |
79 |
84 |
|
|
Good |
39 |
61 |
74 |
80 |
|
Contoured |
Poor |
47 |
67 |
81 |
88 |
|
Contoured |
Pair |
25 |
59 |
75 |
83 |
|
Contoured |
Good |
6 |
35 |
70 |
79 |
Meadow |
|
Good |
30 |
58 |
71 |
78 |
(permanent) |
|
Poor |
45 |
66 |
77 |
83 |
Woodlands |
|
Pair |
36 |
60 |
73 |
79 |
(farm woodlots) |
|
Good |
25 |
55 |
70 |
77 |
Table 13: CN NUMBERS FOR DIFFERENT MOISTURE CONDITIONS AND S VALUES
CN for condition II |
CN |
S-values mm |
CN for |
CN |
S-values mm |
||
I |
III |
condition II |
I |
III |
|||
100 |
100 |
100 |
0.0 |
58 |
38 |
76 |
181.0 |
98 |
94 |
99 |
5.1 |
56 |
36 |
75 |
196.5 |
96 |
89 |
99 |
10.4 |
54 |
34 |
73 |
213.0 |
94 |
85 |
98 |
15.9 |
52 |
32 |
71 |
230.7 |
92 |
81 |
97 |
21.7 |
50 |
31 |
70 |
250,0 |
90 |
78 |
96 |
27.7 |
48 |
29 |
68 |
270.0 |
88 |
75 |
95 |
34.0 |
46 |
27 |
66 |
292.5 |
86 |
72 |
94 |
40.7 |
44 |
25 |
64 |
317.5 |
84 |
68 |
93 |
47.5 |
42 |
24 |
62 |
345.0 |
82 |
66 |
92 |
55.0 |
40 |
22 |
60 |
375.0 |
80 |
63 . |
91 |
62.5 |
38 |
21 |
58 |
407.5 |
78 |
60 |
90 |
70.5 |
36 |
19 |
56 |
445.0 |
76 |
58 |
89 |
79.0 |
34 |
18 |
54 |
485.0 |
74 |
55 |
88 |
87.7 |
32 |
16 |
52 |
530.0 |
72 |
53 |
86 |
97.2 |
30 |
15 |
50 |
582.5 |
Table 13 continued
CN for condition II |
cm |
S-values mm |
CN for condition II |
CN |
S-values mm |
||
I |
III |
I |
III |
||||
70 |
51 |
85 |
107.0 |
25 |
12 |
43 |
750.0 |
68 |
48 |
84 |
117.5 |
20 |
9 |
37 |
1000.0 |
66 |
46 |
82 |
128.7 |
15 |
6 |
30 |
1417.5 |
64 |
44 |
81 |
140.5 |
10 |
4 |
22 |
2250.0 |
62 |
42 |
79 |
153.2 |
5 |
2 |
13 |
4750.0 |
60 |
40 |
78 |
166.7 |
0 |
0 |
0 |
Infinity |
Table 14: RUN-OFF UNDER DIFFERENT CN VALUES AND RATES OF RAINFALL IN mm
Rainfall mm |
CN values |
||||||
70 |
65 |
70 |
75 |
80 |
85 |
90 |
|
25.0 |
0 |
0 |
0 |
0.75 |
2.0 |
4.25 |
8.0 |
30.0 |
0 |
0 |
0.75 |
1.75 |
3.75 |
7.0 |
11.5 |
35.0 |
0 |
0.50 |
1.50 |
3.25 |
6.0 |
9.75 |
15.2 |
40.0 |
0.25 |
1.25 |
2.75 |
5.0 |
8.50 |
13.0 |
19.0 |
45.0 |
0.75 |
2.25 |
4.25 |
7.25 |
11.0 |
16.2 |
23.2 |
50.0 |
1.50 |
3.50 |
6.0 |
9.50 |
14.0 |
20.0 |
27.2 |
62.5 |
4.25 |
7.50 |
11.5 |
16.2 |
22.2 |
29.5 |
38.2 |
75.0 |
8.25 |
12.7 |
18.0 |
24.0 |
31.2 |
39.7 |
49.5 |
100.0 |
19.0 |
25.7 |
33.2 |
41.7 |
51.0 |
61.5 |
73.0 |
125.0 |
32.5 |
41.2 |
51.0 |
61.2 |
72.2 |
84.2 |
97.0 |
150.0 |
48.0 |
58.7 |
70.0 |
82.0 |
94.5 |
107.7 |
121.2 |
175.0 |
65.0 |
77.5 |
90.5 |
103.7 |
117.2 |
131.5 |
145.5 |
200.0 |
83.2 |
97.5 |
111.7 |
126.0 |
140.5 |
155.5 |
170.2 |
225.0 |
102.5 |
118.0 |
133.5 |
148.7 |
164.2 |
179.7 |
194.7 |
250.0 |
122.5 |
139.2 |
155.7 |
172.0 |
188.0 |
204.0 |
219.5 |
275.0 |
143.0 |
161.0 |
178.2 |
195.5 |
212.0 |
228.5 |
244.2 |
300.0 |
164.0 |
183.0 |
201.2 |
219.0 |
236.2 |
253.0 |
269.0 |
Application of data
Data collected over several years on quantity and peak rate of surface run-off are needed on which to base the value of the drainage co-efficient for the design of a drainage project. The value is determined taking into account level of probability and degree of protection to crops. Higher values will be needed for crops sensitive to water logging such as truck and most fruit crops, and generally lower values for field crops, pastures, meadows, native ranges and forests.
The mean rate of run-off for more than 24 hours for a two to five year frequency is generally a good guide in selecting a value of drainage co-efficient. Values may range from 8 to 25 and from 12 to 40 nun per day for general field crow and special high value crops respectively. The values will be about 1.5 times higher for organic or peat soils.
Peak flow rates
Peak flow rates can be determined by using the unit hydrograph method, Cook's method, or the rational formula. The last is very simple and hence popular, but also very empirical and should be used for first estimates only.
The relationship is
Q = C I A/360
Q = peak rate of flow in m³/sec for a given frequency of rainfall
C = a constant ranging from 0 to 1, according to watershed conditions
I = maximum rainfall intensity in mm/hr
A = drainage area in ha
The values of C under different conditions are as follows.
Soil type |
Cultivated lands |
Pastures |
Sand |
0.20 |
0.15 |
Loam |
0.40 |
0.35 |
Clay |
0.50 |
0.45 |
The maximum rainfall intensity, i, relates to a rainfall duration equal to the concentration time, Tc, of the basin. To determine the maximum intensity, empirical formulas have been developed expressing precipitation for various durations as a function of frequency and which are of the form i = aTb/tc where T is the return period, t the duration in minutes and a, b, and c are regional constants. Values for the US show for rainfall of less than 60 mins a = 7 to 11, b = 0.17 to 0.23 and C = 0.38 to 0.47. Tc can be obtained from the empirical formula Tc = 0.00195 (L/)0.77 where Tc is in mins, L is the length of the mainstream and S = H/L where H is the difference in height between the highest and the lowest point in the field or basin. For example, if H is 9.5 m, L = 3070 m then Tc = 1 hr 27 mins. With precipitation intensity for various durations known, the value of i can then be determined. Such data can normally be obtained from the national meteorological service.
To short cut the necessary calculations graphs are given to determine peak discharge in cusecs for given water shed conditions and typical types of storm rainfall distribution (USDA, SCS, 1969). An example is given in Fig 9. The selection of the . correct graph for a given situation is somewhat problematic.
Soils may contain large amounts of salts when they weather and decompose. Irrigation water may also carry salts in appreciable amounts; even the best quality is never as pure as rainfall. The electrical conductivity of rain water is some 30 to 50 micromhos/cm while the best quality irrigation water is never lees than 100 micromhos/cm, but frequently much higher. Irrigation water evaporates, leaving the salts behind. With the lapse of time, these salts accumulate in the root zone. The salt content is usually expressed in electrical conductivity (EC) in millimho/cm or in parts per million on a weight basis (ppm). . EC in millimhos/cm is roughly 1/640 x ppm. The presence of salts in the root zone beyond a certain concentration hampers crop growth. Therefore, it is necessary to provide additional water (Dd) to leach them. Part of the rain received during the non-growing season is also useful in removing salts from the root zone. The extent of effective rainfall may thus be lower in salt affected areas than in non-saline areas.
On an annual basis, the net quantity of irrigation water (Di) needed to meet the consumptive use by the crop (Do) amounts to total water need (CD) less the annual effective rainfall (Dr).
Di = Do = CU - Dr (1)
When there is a salt problem, additional water is required (Dd) for leaching the salts and hence the relation becomes:
Di = Dc + Dd (2)
Fig 9: PEAK RATES OF DISCHARGE FOR SMALL WATERSHEDS TYPE II STORM DISTRIBUTION SLOPE-MODERATE / CURVE NUMBER 75 (USDA, SCS, 1969)
The leaching requirement (LR) is the fraction of the total amount of irrigation water that must be passed through the soil in excess of crop water needs, to control salinity at a specified level. Different crops differ in salt tolerance. The salt content of drainage water should normally not exceed the tolerance level of a crop. Leaching requirement (LR) can be expressed in terms of ratio of the depth of drainage water (Dd) to that of irrigation water (Di) or in terms of a ratio of the salt content of the irrigation water (ECi) to that of drainage water (ECd), or
(3)
In case of rainfall, it is necessary to take into account its amount and the electrical conductivity also and to work out its weighted average.
(Di) adjusted = Di + Dr (4)and (ECi) adjusted = (5)
When electrical conductivity of rain water is assumed to be zero for ill practical purposes, the equation 5 resolves to:
(ECi) adjusted = (6)
In case of rainfall, therefore, the equation 3 of leaching requirements resolves to:
(7)
From equations 2 and 7 above, the quantity of irrigation water (Di) can be expressed in terms of EC values, annual leaching requirement (Dd) and consumptive water requirement as under.
and (8)
Also from equation 3:
It follows that: (9)
The amount of rain water entering the soil from the annual rainfall (Ra) is obtained by deducting from the latter the annual run-off (Sa) and evaporation from the soil surface in the non-growing season (En). Sa and En are not useful in the leaching process and hence their values must be subtracted from the total, or
Dr = Ra - (Sa + En) (10)
The values of evaporation from land surfaces can be determined locally. If these are not available, however, the broad monthly values can be read from a chart prepared by the USDA, SCS (1967), shown in Pig 10. The chart has been prepared from relationships between rates of rainfall, mean monthly temperature and evaporation.
In applying the above method to determine annual gross leaching needs the following data should be available:
- monthly and annual rainfall values (Rm and Ra);- rainfall during growing season (Rg);
- growing season effective rainfall (Re);
- concumptive use of water by crop (CU);
- salt content or electrical conductivity of irrigation water (ECi);
- salt content (parts per million) or electrical conductivity of drainage water (ECd) or salt tolerance limit of crop;
- annual surface run - off (Sa);
- irrigation efficiency (Ef);
- evaporation in non-growing season (En).
A sample calculation for determining the effective rainfall and annual leaching needs of a crop of berseem is given below; in this example annual consumptive use (CU) is 750 mm, annual rainfall (Ra) is 400 mm, annual run-off (Sa) is 40 mm, evaporation in non-growing season (E) is 160 mm, effective rainfall during growing season (ER) is 150 mm, irrigation efficiency (Ef) is 70%, salt content of irrigation water (ECi) is 1 920 ppm, and salt tolerance limit of the crop (ECd) is 9.0 mmhos/cm.
Using equation (1), DC = CU - ER = 750 - 150 = 600 mm; and mmhos/cm, by equation (10), Dr = Ra - (Sa + En) = 400 - (40 + 160) = 200 mm.
Assume first that no irrigation water is to be added.
By using equations 7 and 8:
and
If this quantity of 200 mm is substituted in the above equations, then
The higher value of 221.75 mm is obtained meaning thereby that more than 200 mm of water will be required for leaching purposes. Next assume that 250 - of water are to be added. In this case:
Since 227.4 is lower than 250, the quantity of irrigation water to be added for leaching is lees than 227.4 mm. The required value lies between 221.75 mm and 227.4 mm.
By interpolation:
Dd = 224.60
After substituting this value of 224.6 mm in the above equations:
Since the irrigation efficiency is 70%, the annual gross leaching need will be 224.60/0.70 - 320.8 mm.
Another approach to estimating annual leaching needs was developed by Van der Molen and Boumans (1963). The relationship between different parameters was derived as follows:
= year total of indicated quantities in dmP = deep percolation below the root zone required to maintain soil salinity at the selected average level
ET = Evapotranspiration in din/month
N = Precipitation less interception and surface run-off in din/month
k = leaching co-efficient
ECe = electrical conductivity of saturation extract in mmhos/cm or tolerated average salt level
ECi = electrical conductivity of the irrigation water in mmhos/cm
A calculation example of the average annual drainage needs according to the equation given above is presented below.
Soil Type |
Sand |
Loam |
Clay |
Leaching Co-efficient (k) |
0.8 |
0.6 |
0.3 |
Evapotranspiration (ET) dm |
9 |
9 |
9 |
Precipitation (N) dm |
3 |
3 |
3 |
Tolerated average salt level (ECe) |
4 |
4 |
4 |
Conductivity irrigation water (ECi) |
2 |
2 |
2 |
Required leaching (£P) |
2.5 |
3.3 |
6.6 |
Required irrigation G[i3?) |
8.5 |
9.3 |
12.6 |
Natural drainage (+) or seepage supply (-) |
0 |
+2 |
-3 |
Total drainage dm |
2.5 |
3.3 |
6.6 |
Artificial drainage dm |
2.5 |
1.3 |
9.6 |
The average annual requirement is, however, inadequate as a design criterion. Information on peak drainage needs can be obtained by studying irrigation - Bait - drainage relationships for each monthly period. To derive the necessary monthly data, reference is made to Chapter 11 edited by Tan den Berg in FAO/UNESCO International Sourcebook on Irrigation Drainage and Salinity (1973).
To assess the effective rainfall in rice culture, the water balance should preferably be calculated from daily data. The use of the drum culture technique described earlier permits the measurement of actual evapotranspiration (ETa), deep percolation (Dp) and effective rainfall (ER).
If this degree of accuracy is not needed, however, the effective rainfall can be measured using values of estimated ETp, deep percolation and permissible water depth for land submergence to obtain a daily account value, X
X = (Water stock on hand - Water losses) - (Permissible water depth) (for land submergence)
If the value of X is positive, it indicates the amount of water surplus or rainfall is ineffective.
If the value of X is 0, it means that all the rainfall received on that day has been effective and the field has attained its maximum allowable flooding capacity. There is no room to store any more water. Also, there is no water surplus on that day.
If the value of X is negative, it means that all the rainfall received on that day is effective and some more (equivalent to X value) can be accommodated in the field without it being ineffective. ',"'
As already stated, stock on hand includes the previous day's balance plus any addition due to rain or irrigation. Losses are those due to evapotranspiration and deep percolation, The permissible water depth for land submergence depends on the stage of crop growth and field bund height, whichever is lower of the two. The illustration of three cases is given below, and daily water balance can thus be maintained to derive the monthly values.
Parameters |
Case A |
Case B |
Case C |
Previous 'balance (ram depth) |
30 |
30 |
30 |
Rainfall received (mm) |
40 |
45 |
50 |
Irrigation (mm) |
0 |
0 |
0 |
Evapotranspiration (mm) |
8 |
8 |
8 |
Deep percolation (mm) |
7 |
7 |
7 |
Crop stage allowance (mm) |
60 |
60 |
60 |
Field, bund height allowance (mm) |
125 |
125 |
125 |
X value (mm) |
- 5 |
0 |
5 |
Balance to be carried forward |
55 |
60 |
60 |
Conclusion , |
All rain effective Space for additional 5 mm |
All effective No space for storing more rain |
5 mm ineffective |
Data requirements for this method are: total rainfall from rain gauge (daily value); evapotranspiration from open pan (daily value); percolation, mean value for the field (daily value); crop stage allowance (weekly value); field bund allowance from direct measurement of bund height (seasonal value).
A summary table can be used as given for the following example, where at a given period the crop stage allowance is 75 mm and the field bund allowance is 150 mm. All data are in mm.
Data |
Rainfall |
Irrigation |
Percolation plus ET |
Change in water stored |
Depth of stored water |
Ineffective rain |
1 |
2 |
3 |
4 |
5 |
6 |
7 |
- |
0 |
0 |
0 |
0 |
75 |
0 |
1 |
20 |
0 |
15 |
5 |
75 |
5 |
2 |
40 |
0 |
18 |
22 |
75 |
22 |
3 |
100 |
0 |
15 |
85 |
75 |
85 |
4 |
15 |
0 |
15 |
0 |
75 |
0 |
5 |
0 |
0 |
18 |
-18 |
57 |
0 |
6 |
0 |
0 |
19 |
-19 |
38 |
0 |
7 |
20 |
0 |
17 |
3 |
41 |
0 |
8 |
60 |
0 |
16 |
44 |
75 |
10 |
9 |
70 |
0 |
15 |
-55 |
75 |
55 |
10 |
0 |
0 |
18 |
-18 |
57 |
0 |
11 |
0 |
0 |
18 |
-18 |
39 |
0 |
12 |
0 |
0 |
17 |
-17 |
22 |
0 |
13 |
0 |
0 |
15 |
-15 |
7 |
0 |
14 |
0 |
75 |
17 |
58 |
65 |
0 |
15 |
30 |
0 |
15 |
15 |
75 |
5 |
Total |
355 |
- |
- |
- |
- |
182 |
High groundwater tables may be due to ample rain at the site or in the surrounding area or due to seepage and percolation losses from irrigation canals. They may also be due to underground water flow from other areas. The contributions from different sources may vary from year to year.
With groundwater tables within 1-1.5m from the root zone, there is on most soil types some contribution by capillary movement of water towards the water needs of crops. When the water depth is beyond this limit, the contribution by capillary flow for most soils is negligible.
A distinct feature of irrigation systems based on pumped groundwater is that the command areas are frequently nearer the source of water, as compared to the canal systems where long distances may be involved. The area supplied by one well is small in size, easy to manage and has a high flexibility. The cultivation and irrigation practices can be adapted quickly to the available water supply.
Kith deep water table conditions, water is pumped and used for irrigation in a similar method to that used for canal irrigation systems. Effective rainfall can be calculated by the same method as that used in surface irrigation project designs or project operations. From the frequency distribution of effective rainfall and by selecting the proper percent chance of occurrence of total rainfall, and of effective rainfall, the net irrigation requirements can be calculated.
With shallow water table conditions, there can be a significant moisture recharge by capillary action to the root zone. Effective rainfall can decrease by an amount equal to the contribution from groundwater storage. There have been few studies on the relationship between depth of groundwater and effective rainfall. Hater will rise by capillary action above the water table, its height and rate depending on the type of soil and its hydraulic properties, the soil moisture content and consequently the type of crop and level of evaporative demand. Both distance and rate of water movement are important; for heavy textured soil the distance is great but the rate slow, whilst for sandy soils the distance is small but the rate is high. In the absence of impervious layers, the contribution of water to the root zone of less than 1 mm/day may be approximately taken when the upper soil layer is moist at 50 to 90 cm for coarse and heavy textured soils and some 120 to 200 cm for most medium textured soils.
The contribution from the groundwater table can be assessed with the methods reported by Doering (1963), Dastane (1972) and White and Troxell, quoted by Chow (1964). In the White and Troxell method, it is assumed that evapotranspiration is negligible between midnight and 4 a.m. and that the level of the water table during this interval approximates the daily mean using Fig 11.
Fig 11: DIURNAL FLUCTUATION OF A WATER TABLE AS A RESULT OF TRANSPIRATION (AFTER TROXELL)
If h is the hourly rise from midnight to 4 a.m. and S = net fall or rise of water table in one day, then the daily volume discharge = VET = Sy A (24 h ± S) , where Sy is specific yield and A is the area of vegetation. The specific yield is defined as the ratio of volume of water which, after the soil is saturated, will drain out by gravity to the total volume of the soil. It is non-capillary porosity of the soil. If the groundwater reservoir has a surface area of 10 km² n and an average specific yield is 7.5 percent, each 1 metre rise or fall in the water level over the area represents 75 hm of water. This method assumes that there is no but or in flow of water in the area under consideration and a change in the water table is a result of ET only.
Recently, Allison (1964) derived a formula for estimating capillary rise of water as follows:
Dgw = depth of ground water evaporated or removed
ECe = electrical conductivity of saturation extract in mmhos per dm at 25°C.
ds = soil density (gm/cc)
Ds = depth of soil, where salt accumulation takes place
Sp = saturation percentage of soil
dw == density of water (gm/cc)
ECgw = electrical conductivity of groundwater in mmhos/cm
The daily soil water budget method can also be used for determining the value of effective rainfall under shallow water table conditions; an additional column on ground-water contribution on the income side, similar to that of irrigation is needed.
If no information is available on the extent of groundwater contribution, the value of effective rainfall can be estimated by obtaining first the values of uncorrected effective rainfall under deep groundwater conditions from Table 8 and then correcting them by applying the multiplication factors as shown in Table 15. For example, if the total rainfall is 100 mm, the depth of water application is 50 mm and consumptive use is 150 mm, then the effective rainfall under the deep water table conditions is 2.97 x 0.93 x 25» 69 mm. Under the conditions of a shallow water table, say at 140 cm, the effective rainfall will be 69.05 x 0.6 = 41.5 mm
Table 15: MULTIPLICATION FACTORS TO BE APPLIED TO THE VALUES OF UNCORRECTED EFFECTIVE RAINFALL FROM TABLE 8 TO OBTAIN EFFECTIVE RAINFALL UNDER SHALLOW WATER TABLE CONDITIONS
Depth to water table from soil surface (cm) |
Soil Type | ||
|
Sand |
Loam |
Clay |
50 |
0 |
0 |
0 |
60 |
0.25 |
0 |
0 |
70 |
0.50 |
0.30 |
0 |
80 |
0.75 |
0.50 |
0.22 |
90 |
0.95 |
0.66 |
0.40 |
100 |
1.00 |
0.80 |
0.57 |
110 |
|
0.90 |
0.75 |
120 |
|
0.95 |
0.86 |
130 |
|
1.00 |
0.95 |
140 |
|
|
0.97 |
150 |
|
|
1.00 |
Over 150 |
1.00 |
1.00 |
1.00 |
In low rainfall, unirrigated areas, knowledge of the effective rainfall is most essential in planning crop production with the correct selection of crop species and agronomic practices.
Two situations can be distinguished; rainfall may be received, predominantly in the crop growing season, and rainfall may be received during the non-growing season. In the first situation, it is necessary to know the extent of rain which is or can be actually used and that which is utilizable but lost through surface run-off and deep percolation, and whether suitable measures can be adopted to reduce these losses. In the second case it is necessary to know the extent of rainwater which can be conserved economically and carried over to the next season for crop use. In other words, is it possible to conserve moisture and, if so, to what extent. These two situations are dealt with below and illustrations are given for the best utilization of the often limited water.
The essential data needed include:
layer-by-layer values of field capacity, wilting point, bulk density and depth of the soil in order to compute the moisture storage capacity and the moisture balance;
daily rainfall records for several years from available records;
data on the consumptive use of crops,
class A pan records or other ET data;
equipment needed includes soil augar, soil moisture boxes, weighing balance, drying oven, rain gauge.
The following steps are required:
- determine the moisture storage capacity of the soil;- maintain daily records of gains due to rains and losses due to evapotranspiration; if records are available, they must be tabulated;
- prepare a daily soil moisture balance sheet, as shown for the Thornthwaite's method, using rainfall and consumptive use values. If data on actual consumptive use values are not available, these may be computed by using any of the formulae, their selection depending on the climatological data available. To obtain the first approximate value of evaporation from the soil surface, Fig 9, showing broadly the relationship between temperature, rainfall and evaporation, may be used;
- check the balance sheet value against that determined by periodic soil moisture sampling and oven drying. Samples should be taken immediately after rains, as early as possible. Moisture lost during the period from the cessation of rainfall until the soil is sampled should be estimated by multiplying the class A pan evaporation value for the corresponding period by 0.4 to 0.8, depending on the siting of the pan. (see FAO Irrigation and Drainage paper No. 24);
- determine the total and effective rainfall for each week, month and season, and the year;
- plot a frequency distribution diagram of effective rainfall during the growing season using available records;
- select the value of the effective rainfall at the desired percent chance of occurence for planning purposes;
- interpret the data from the economic and crop production points of view.
A sample calculation is given below which uses data from moisture studies after a rain shower to find the moisture storage capacity, effective rainfall and soil moisture balance when total rainfall is 200 mm; class A pan evaporation value for the three days after cessation of rains until the soil is sampled is 8, 10 and 12 mm. The soil moisture data on oven - dry weight basis are as follows:
Soil Layer |
Field Capacity % |
Wilting point % |
Moisture % |
Bulk Density (gm/co) |
|
Before rains |
After rains |
||||
0-30 |
24.0 |
12.0 |
14.0 |
22.0 |
1.40 |
30-60 |
26.0 |
13.0 |
15.0 |
24.0 |
1.45 |
60-00 |
28.0 |
14.0 |
16.0 |
25.0 |
1.50 |
90-120 |
30.0 |
15.0 |
22.0 |
22.0 |
1.50 |
Available moisture storage capacity of soil on a volume basis:
or
Total = 23.7 cm
Similarly, the initial available soil moisture on a volume basis:
or
Total =5.8 cm
The final available soil moisture balance on a volume basis
Total =17.1 cm
The evapotranspiration during the interval between the cessation of rains and soil moisture sampling is:
The effective rainfall is equal to the increase in soil moisture plus that evapotranspired during the interval between the cessation of the rain and the soil moisture sampling, or (17.1 - 5.8) + 2.4 = 13.7 cm.
Thus of 200 mm of rainfall only 137 mm was effective. The rest, or 63 mm, was lost by surface run-off. The moisture did not reach the fourth layer because it had too little time for infiltration. Suitable measures should therefore be taken to avoid this run-off and to store the moisture for use by the crop, such as ploughing, mulching or terracing.
A sample calculation is also given on moisture studies during the crop growing season. Weekly data on rainfall and consumptive use are given in columns 2 and 3 in the water balance sheet. The available soil water storage capacity is assumed to be 75 mm.
Period week |
Rainfall mm |
Actual evapotranspiration ETa |
Water storage change in soil |
Water storage balance in soil |
Water surplus |
1 |
150 |
10 |
140 |
75 |
65 |
2 |
40 |
15 |
25 |
75 |
25 |
3 |
50 |
20 |
30 |
75 |
30 |
4 |
130 |
25 |
105 |
75 |
105 |
5 |
0 |
30 |
-30 |
45 |
0 |
6 |
0 |
30 |
-30 |
15 |
0 |
7 |
0 |
15 |
-15 |
0 |
0 |
8 |
10 |
10 |
0 |
0 |
0 |
9 |
5 |
5 |
0 |
0 |
0 |
10 |
10 |
10 |
0 |
0 |
0 |
11 |
100 |
35 |
65 |
65 |
0 |
12 |
60 |
35 |
25 |
75 |
15 |
13 |
70 |
30 |
40 |
75 |
40 |
14 |
0 |
20 |
-20 |
55 |
0 |
15 |
20 |
10 |
10 |
65 |
0 |
16 |
0 |
5 |
- 5 |
60 |
0 |
Total |
645 |
305 |
- |
60 |
280 |
In the latter example, during the first six weeks, the rainfall exceeds the consumptive use and moisture storage capacity of the soil, and so there will be substantial losses amounting to 225 mm by surface run-off and deep percolation. After six weeks, the crop will suffer through lack of moisture until the end of the tenth week. From the eleventh week onwards, there will again be adequate moisture until the crop matures. The water surplus is 55 mm, whilst considerable moisture (60 mm) is left at the end of the growing period.
A rainfall frequency distribution on a weekly basis should be prepared from available rainfall records. If this shows a trend like that shown above, measures for more efficient use of the soil moisture through judicious crop planning should be taken. The possibility of conserving surplus water during the first four weeks by the construction of ponds should be investigated, and whether the water stored can be used to irrigate the crop during the seventh to the tenth week. Also, a crop with a longer growing period may be selected since considerable moisture is left unused at the end of the crop season. In rainfed agriculture it is advisable to choose different types of crop, with the length of growing seasons varying. Mixed cropping is a frequently applied method of using the available soil moisture efficiently and reducing the risk of total crop failure.
Studies on the efficiency of fallowing should be made where applicable. Moisture conservation through fallowing the land has been an ancient practice in many parts of the world. Quantitative and comprehensive studies on soil moisture have been conducted and have been reported by Kanitkar (1944), Jenkins (1951), Evans and Lemon (1957), Duley and Coyle (1955). Literature shows that the efficiency of fallowing depends upon the water holding properties of the soil, the rainfall pattern during the fallowing period, the evaporative demand during the fallowing period, the length of the fallowing period and the management practices. The efficiency of summer fallowing may range from 15 to 30 percent and that of winter fallowing from 25 to 60 percent.
The value of effective rainfall cannot exceed the moisture storage capacity of the soil and hence moisture storage or fallowing efficiency should be regarded as 100% if the soil water is wetted to its maximum capacity. Dastane and Joshi (1961) suggested the following formula for the evaluation of moisture conservation efficiency during the fallowing period. Soil moisture available at sowing time for use by the crop amounts to the effective rainfall in the proceeding seasons.
E = efficiency of moisture conservation in percentage
M1 = available moisture at the beginning of the fallowing period
M2 = available moisture at the end of the period
R = rainfall received
Sc = available moisture storage capacity of the soil
If the available moisture in the root zone before and after fallowing is 50 and 150 mm respectively, the rainfall during the fallowing period is 250 mm and the available water storage capacity of the soil is 200 mm, then the efficiency of fallowing will be 75 percent. The effective rainfall is 150 mm only out of the total received.
Due to the enormous variations in soil conditions, it is emphasised that, in determining the soil moisture properties, it is necessary to provide an adequate number of replications of soil samples in time and space. With all care taken, errors may still be in the order to 5 to 20 percent, or larger. Reference is made to the monograph by Black et al (1965) for a detailed discussion on the errors involved in the determination of soil moisture properties.