4.1. Assessment of Irrigation Water Requirements
Indirectly, the amount of irrigable land depends on the crop's irrigation requirements. Crop evapotranspiration (ETc) and effective rainfall were computed using the CROPWAT 8.0 software, applying equations 2 and 4, respectively, which are used to calculate the irrigation water requirement of crops. Eq. 6 was used to determine the monthly gross irrigation water requirements for maize, cabbage, sugarcane, and onion over their whole growth cycles. Freshly harvested crops like cabbage need the same amount of water during the late-season stage as they did during the mid-season stage. The crops are harvested fresh and thus need water up to the last moment. During the late season, dry-harvested crops such as maize were allowed to dry out. Thus, their water needs during the late-season stage are minimal. Of course, no irrigation is given to these crops during the late-season stage.
4.1.1. Scheme irrigation need
The net irrigation requirement for the crops was calculated by adding the monthly irrigation requirements for every crop. Throughout the course of a year, the farmers could plant multiple types of crops simultaneously. For this reason, it is frequently required to determine the irrigation requirements for a multiple-cropping system. From the perspective of water-saving, drip irrigation system is more preferable than other systems for the study region, as indicated in Table 1. One of the most common ways to use water efficiently in areas with limited water supplies is to apply modern irrigation techniques, such as drip irrigation, to boost irrigation efficiency. Eq. 5 was utilized to calculate the monthly gross irrigation requirements by applying surface, sprinkler, and drip irrigation methods for the four selected crops in the area. The CROPWAT 8.0 software result depicted that sugarcane, cabbage, maize, and onion have seasonal crop water requirements of 640.66mm, 251.66mm, 260 mm, and 233.17mm, respectively.
Table 1
Estimated scheme irrigation needs of Crops (mm/month)
Month
|
Jan
|
Feb
|
Mar
|
Apr
|
May
|
Jun
|
Jul
|
Aug
|
Sep
|
Oct
|
Nov
|
Dec
|
Total
|
Sugarcane
|
175.67
|
136
|
0
|
12
|
15
|
31.17
|
75.7
|
24
|
15.33
|
4
|
73.3
|
105.67
|
640.66
|
Cabbage
|
70.33
|
80.5
|
100.8
|
0
|
0
|
|
|
|
|
|
|
|
251.66
|
Maize
|
130.33
|
128
|
0
|
|
|
|
|
|
|
|
1.67
|
0
|
260.00
|
Onion
|
81.167
|
68.8
|
83.17
|
0
|
0
|
0
|
|
|
|
|
|
|
233.17
|
Monthly total irrigation water requirement by using surface irrigation system
|
Total
|
457.49
|
413
|
184
|
12
|
15
|
31.17
|
75.7
|
24
|
15.33
|
4
|
75
|
105.67
|
1412.36
|
Monthly total irrigation water requirement by using sprinkler irrigation system
|
Total
|
366.0
|
330.4
|
147.2
|
9.6
|
12.0
|
24.9
|
60.6
|
19.2
|
12.3
|
3.2
|
60.0
|
84.5
|
1129.9
|
Monthly total irrigation water requirement by using drip irrigation system
|
Total
|
322.9
|
291.5
|
129.9
|
8.5
|
10.6
|
22.0
|
53.4
|
16.9
|
10.8
|
2.8
|
52.9
|
74.6
|
997.0
|
4.2. Assessment of Surface Water Availability for Irrigation and its Proximity
In addition to estimating crop water requirements for irrigation potential, surface water availability was assessed based on the low flow potential of the river. Using FDC 2.1 software tool analysis, the low flow discharge (90-percentile flow) of rivers was generated, and the result was used to compute the possibly irrigable land from rivers. Low flow frequency analysis is a valuable practice for assessing the possibility of water availability in streams during critical dry seasons, which can be beneficial for the implementation of irrigation. The FDC 2.1 software tools result revealed that, the overall long-term monthly minimum available stream flow of the Zenti River is 0.11 m3/s(110L/s) and average minimum flow was 6.175m3/s. If you look at 90% exceedance, m3/s, which is the lowest flow rate recorded 0.11, so by definition, the flow in the river is at this flow rate or more for 90% of the time, such that discharge exceeds 19 out of 21 years of flows through the year. Due to the dry and windy climatic conditions and high evapotranspiration that occur in the region, low monthly water availability was found in January, February, December, and March, which are dry-season months; whereas the highest flow was obtained in May, August, and September, which are rainy-season months. The information in Table 2 depicts the overall monthly 90 percentile (Q-90) exceedance probability and monthly average stream flow of the river using Eq. 6.
Table 2
Average monthly stream flow and FDC analysis using 90% probabilities
Months
|
Jan
|
Feb
|
Mar
|
Apr
|
May
|
Jun
|
Average monthly(m3/s)
|
0.583
|
0.57
|
0.748
|
1.5
|
1.906
|
1.277
|
90% flow(m3/s)
|
0.66
|
0.27
|
0.256
|
0.274
|
0.594
|
0.387
|
Months
|
Jul
|
Aug
|
Sep
|
Oct
|
Nov
|
Dec
|
Average monthly(m3/s)
|
1.543
|
2.5
|
2.38
|
2.525
|
1.635
|
0.554
|
90% flow(m3/s)
|
0.635
|
0.89
|
0.519
|
0.813
|
0.212
|
0.66
|
FDC long-term is used to generate the flow duration curves from completely imported time-series data, as indicated in Fig. 4.
Using the local minimum method of base flow computation, the base flow index (BFI) values of the river range from 0.16 to 1 and are consistent with the findings of other research [20;21]. The majority of river flow data is greater than 0.52, indicating quite considerable water resource potential in the study. A high index value of base flow would imply that the catchment has a more stable flow regime and is thus able to sustain river flow during extensive dry periods. The results revealed that the maximal BFI is greater for dry seasons than rainy seasons. The result shows that the river is strongly influenced by base flow contribution. The results were calibrated manually by trial and error. The trail is stopped when the curve of the calculated base flow (red curve) is closely fitted to the observed discharge (blue area color) for dry periods. Figure 5 show base flow separation result in the form of a hydrograph.
After minimum river flow, availability was calculated using FDC 2.1, the straight-line (Euclidean) distance from the streams that is obtained from a 30m x 30m cell size DEM was calculated using a GIS tool. By reclassifying the river proximity map, suitable irrigable land that is near the water source (rivers) was identified. According to [22], the area closest to the stream was deemed to be the most suitable for irrigation development, and the area farther away was estimated to be marginally acceptable for irrigation purposes. The river proximity map depicted the riverbank land as highly suitable (S1), moderately suitable (S2), slightly suitable (S3), and currently not suitable (N). Figure 6 shows that land near rivers is highly suitable for irrigation up to a distance of 3km, moderately suitable up to a distance of 7km, marginally suitable up to a distance of 11km, and currently not suitable for a distance greater than 11km [17]. This is due to the cost of constructing a canal and the presence of more water loss as it is far from the irrigated area.
Regarding the preparation of the land for irrigation as well as the operation and efficiency of irrigation, the elevation of the field is a significant factor on irrigation suitability. According to the FAO land suitability classification, land feature(elevation) of the study area(Fig. 7) were classified into S1, S2, S3 and N from the surface irrigation suitability perspective, i.e., from 656-1207m as highly suitable (S1), 1207-1525m as moderately suitable (S2), 1525-1934m as slightly suitable (S3) and 1934-2922mas not suitable (N). According to the suitability results, 34% of the land was extremely suitable, 35% was moderately acceptable, 24% was only slightly suitable, and 7% was not suitable for irrigation development. The recommended low land areas have a slope that is essentially within the acceptable range of slope classifications (less than 8%) for surface irrigation. The Fig. 7 provides an overview of the suitability of elevation of the study area for irrigation purposes across the entire catchment area
4.3. Evaluation of Physically Suitable Irrigation Potential Area
According to FAO guideline criteria [13], physical surface irrigation potential was obtained by comparing irrigation water requirements on identified irrigable land with the minimum available stream flow on a monthly basis using the FDC 2.1 tool. A study found that the Zenti river has an average annual minimum surface water yield of 6.175m3/s and a total irrigation demand of 4.251m3/s. The average annual river flow is 17.72m3/s, indicating enough water to satisfy irrigation needs on an annual basis in the study area. However, it may not be adequate for daily, monthly, or seasonal requirements. Therefore, a small storage structure could help meet monthly irrigation demand during shortages. Low flow volume was divided by the net irrigation demand of crops dominantly grown in the research area (maize, onion, cabbage, and sugarcane) to obtain potentially irrigated land from rivers during the dry season. The minimum flow of any irrigation system should be sufficient to supply the area being irrigated with water at times of peak demand. From the total stream flow, 15% of the available stream flow in the catchment was released downstream for ecological purposes. The results of these analyses revealed that the monthly irrigation requirements are less than the available mean monthly flows of the Zenti River. The minimum available flow is 0.28m3/s in the month of February, whereas the water requirement in the month of February is 0.14m3/s/ha, giving a critical command area that can be reliably irrigated using the available flows in the Zenti River. In the study watershed, a total of 3016.75 hectares of physically irrigable land were identified while accounting for water availability using 90% of the FDC 2.1 analysis. However, the current irrigated area was found to be 1568.71ha of the land irrigated by surface water. The potential for surface irrigation might cover 52% of the arable land that constitutes the entire amount of irrigable land. Consequently, in times of scarcity, providing little storage building (dams, weir) might be able to supply the monthly irrigation need. Other strategic plans include encouraging the use of groundwater and water-saving irrigation technology, as drip irrigation may increase water supply. By doing this, it is possible to expand irrigation potential over the entire highly suitable region (i.e., 3016.75ha of irrigable land) present in the study area. Eq. 1 was used to determine the effective irrigable areas (ha) for each month, as indicated in Table 3, based on the gross irrigation demand and the 90% available minimum monthly flow of the Zenti river basin.
Table 3
Irrigation Demands, Minimum Available Flow and Irrigation Potential
Months
|
Available flow @90%(m3/s)
|
Irrigation Demands(m3/s/ha)
|
Irrigation potential(ha)
|
Jan
|
0.66
|
0.045
|
128.6
|
Feb
|
0.28
|
0.14
|
123.12
|
Mar
|
0.256
|
0.5
|
78
|
Apr
|
0.274
|
0.22
|
125.5
|
May
|
0.594
|
0.33
|
89
|
Jun
|
0.387
|
0.25
|
141
|
Jul
|
0.635
|
1.68
|
138
|
Aug
|
0.885
|
0.53
|
136
|
Sep
|
0.519
|
0.34
|
153.3
|
Oct
|
0.813
|
0.09
|
162
|
Nov
|
0.212
|
0.057
|
146.2
|
Dec
|
0.66
|
0.087
|
148
|
Total
|
6.175
|
4.251
|
1568.71
|
Possible diversion site required for irrigation area was assessed based drop in head along the river and elevation of irrigable land using hydro resource of the spatial analysis tool according to the approach followed by [23]. Identifying potential diversion locations could offer an opportunity for irrigation expansion in the future. However, these diversion sites also need to be evaluated in light of the socioeconomic, geological, and other constraints on diversion systems. Figure 8 depicts the physically possible irrigable area and diversion site of the study area.