Twenty-seven farmers (from a total of 127 farmers in the region) were selected using the accidental sampling method and then interviewed. This figure represents 20% of the farmers in the irrigated district. Farms owned by the sampled farmers cover a total of 385 ha (20% of the total area of the irrigated district of Cherfech). Statistical methods such as Pearson correlation, Mann–Whitney U test, and the X2
test were used for the data analysis. The Pearson correlation was used to analyze the correlation between the farmers’ profiling variables. The Mann–Whitney test was used to analyze the influence of the farmers’ profiling variables on the acceptance of the IAS. The X2
test was used to check the statistical significance between the price selection of the service and the farmers’ profiling variables. These statistical tests are commonly used in farmers’ profiling and studies that deal with farmers’ perceptions towards agricultural services, practices, adaptation, or impacts [34
3.1. Farmer Profiling
From the data analysis of the survey conducted on 27 farmers, six typifying variables were considered regarding the farmer’s features, the farm characteristics, the agricultural cropping pattern, and the irrigation systems (Table 1
The results of the study show a certain heterogeneity of the sample interviewed, which is representative of the irrigation district. The age of interviewed farmers ranged from 29 to 75 years old, with about 33% of those questioned aged between 50 and 60. Older farmers (>60 years) represented 37% of the sampled group, with 18.5% aged between 60 and 70 years and 18.5% of farmers older than 70 years. Finally, younger farmers (<50 years old) represented 30% of the interviewed sample.
Education. Five levels of education were identified among participants: illiterate, quranic, primary, secondary, and university. Illiterate farmers represented 15% of the sample, while 4% went to quranic school and 37% of farmers had received primary school education. Twenty-two percent of the farmers had been to high school and twenty-two percent held a university degree. In 2000, [39
] found out 80% of farmers from the one irrigated district only had a primary education, meaning our results show an evolution of farmers’ education levels over the last decade. This may be explained by the fact that farmers’ sons are taking over the farm responsibilities and receive longer educations.
Farm size. The majority of interviewed farmers (78%) possessed a farm size lower than 15 ha: About 33% of farms were 10–15 ha in size, while 29% were 5–10 ha, and 16% were less than 5 ha. Farms larger than 15 ha represented 22 % of the sample and were distributed between farms sized between 15 and 20 ha (8%) and between 20 and 25 ha (3%). Only 11% of farms had a total area higher than 25 ha.
Plots. For the 2019/2020 growing season, the survey identified the number of plots per farm. The results were then divided into six groups, depending on the number of plots. A total of 7.4% of farms had a single plot, 11% had two plots, and 18.5% had three plots. A total of four plots was the highest number among farmers and represented 30% of those interviewed. Finally, 14.8% of the farmers had five plots and 18.5% had more than this amount. Similar numbers were recorded by [7
] during the 2010–2011 growing season.
Irrigation systems. Farmers were divided into two groups: those using pressurized irrigation systems (PI) and those using surface irrigation systems (SI). Interview results revealed that 63% of the farmers use pressurized irrigations systems, such as sprinkler and drip irrigation, while 37% still use surface irrigation systems, such as furrow and basin irrigation. Compared to [40
], we noted an increase of the adoption of pressurized systems in the same area (51% in 2011 against 63% in 2013).
Cropping patterns. Ten groups of cropping patterns were identified as being conducted by farmers. Around 18.5% of interviewed farmers have a single cropping pattern, with 3.7% cultivating cereals (C), 3.7% cultivating forage crops (F), 7.4% cultivating vegetables (V), and 3.7% cultivating fruit trees (T). The remaining 81.5% cultivate more than one crop, with a combination of: cereals and forages (CF = 29.6%); cereals and vegetables (CV = 7.4%); cereals, forages, and vegetables (CFV = 29.7%); cereals, forages, and fruit trees (CFT = 7.4%); cereals, vegetables, and fruit trees (CVT = 3.7%); and crop, cereals, forages, vegetables, and fruit trees (CFVT = 3.7%). The fact that the main cropping patterns used are the CF and CVT confirms findings from studies conducted by [7
], which shows that the dominant crop rotation is the triennial type (CFV). The same studies showed that around 20% of farmers applied a biennial crop rotation (CF or CV).
Following the farmers’ profiling assessment, a correlation analysis was conducted, including six demographic and technical (irrigation-related) variables. The results are presented in Table 2
shows a significant correlation, at the level of 5%, between farmers’ age and education level (−0.472), demonstrating that the older the farmer, the lower his level of education. A significant correlation at the level of 5% is found between the age of farmers and the cropping pattern (0.456). The older the farmer, the more likely they are to diversify their crops. A significant correlation, again at the level of 5%, was also found between education and the number of plots (−0.442), indicating that the more educated the farmer, the more likely they are to reduce their number of plots. Table 1
also shows that the older the farmer, the more likely they are to have a higher number of plots (significant correlation at the 1% level and a value of 0.502). A significant correlation at a level of 1% is also found between the cropping pattern and the number of plots (0.637). The more complex the cropping pattern, the higher the number of plots per farm.
3.1.1. Farmer’s Irrigation Decision Criteria and Knowledge and Use of Irrigation Decision Tools
In order to better understand farmers’ irrigation decision making processes, two questions were asked: “How do you know when to irrigate?” and “How do you determine the amount of water to apply?”
Forty-one percent of farmers answered that they rely on the soil and crop condition to decide when to irrigate, while eleven percent base their decision on a combination of the climate, the soil, and the crop. Meanwhile, 15% stated they base their frequency of irrigation on a fixed CWR calendar. Finally, 7% of farmers declared relying on established practices: Irrigation frequency is fixed depending on the crop type. For example, during spring, alfalfa should be irrigated once every two weeks, while artichokes should be irrigated every two to three days in August.
When deciding how much water to apply, results show that 30% of farmers irrigate until the soil saturation is reached. Meanwhile, 15% of farmers use information about the amount of water required by the crop, 11% irrigate according to water availability at the farm level, and 19% stated the amount of water applied depends on water availability and the soil water content. Finally, 7% declared the amount of water they apply aligns with a fixed crop calendar, and 18% relied on previous knowledge and experience.
When asked if they were aware of technologies that assist with irrigation decision making, only 22% responded yes, compared to 78% who did not know about the existence of such technologies. None of the interviewed farmers declared using technologies, such as sensors or real time irrigation scheduling, although 15% revealed they use fixed irrigation scheduling.
3.1.2. Perception of the WUA among Farmers
A question was asked to gauge farmers’ perceptions around the role of WUAs. Fifty-nine percent of farmers answered that the role of the WUA is water distribution and the billing process, while only fifteen percent knew that WUAs are responsible for the distribution, billing, and maintenance of the network. Meanwhile, 11% believed that the role of WUAs is the distribution of water among farmers. Regarding perceptions of WUA work, 54% of farmers feel the WUA is doing a good job and are satisfied by their work, but 34% were unsatisfied. A total of 4% judged the work as ‘passable’, expressing that with the means available to WUAs, farmers cannot expect better. The remaining 8% did not provide an opinion on the subject.
3.2. Acceptance of an IAS at WUA Level
The interview results show that 77% of farmers responded positively to the idea of implementing an IAS at the WUA level. Despite 54% of farmers being satisfied with the WUA’s current work, they support the idea that the WUA would provide—in addition to the existing service of providing, billing, and maintenance of the network—an advisory service for irrigation scheduling.
To study the acceptance of an implementation of an IAS, a Mann–Whitney U test was conducted to examine the relation between the acceptance of the service and the different parameters of the farmers’ profiles. The Mann–Whitney test was conducted to determine whether farmers’ variables were statistically significant in the acceptance of the IAS. Table 3
shows no significance between the farmers’ variables and acceptance of the IAS.
The acceptance of the service does not depend on the farmers’ variables. As such, the farmers’ profiles cannot be considered as significant parameters in explaining the acceptance among them for the suggested IAS.
3.2.1. Choice between Proposed Services and Interactions with the Prices
In order to ascertain the effect of price differentials on the farmers, they were asked to select the same four services at two stages: first, before they knew of the cost, and again once they had been informed of prices (Table 4
It should be noted that, after the disclosure of prices, 7.4% of the farmers decided not to select any of the suggested services. Before prices were revealed, 15.8% of the farmers selected the first service, 47.4% selected the third service, and 36.8% selected the fourth service. No farmers selected the second service. After the disclosure of the prices, the number of farmers who selected the fourth service dropped to 11.8%. The first service received 27.2 % of votes and the third service was selected by more than half of the farmers (54.4 %). Even after the disclosure of prices, the second service was not selected. This can be explained by the fact that this service provides an estimation for irrigation based on a specific agricultural practice (fixed date of cropping, fixed soil characteristics, fixed date of cutting, etc.), but the farmers want a level of specificity and independence towards the date of crop installation and the practice of the irrigation.
A Pearson chi-square test was also conducted for the selection of the service before and after the price disclosure, in relation to the six profiling farmers’ variables. The chi-square test showed that the choice of service and each of the variables were statistically independent (Table 5
3.2.2. Perception of the Service Prices
The price for each service (detailed in the Methodology section) was presented to the farmers, in order to understand whether they perceived it to be good value. The proposed monthly prices were 5 Tunisian dinar (TND) for service 1, 8 TND for service 2, 18 TND for service 3, and 40 TND for service 4, all as a monthly rate. For each price, the farmers had to choose between four possible answers: cheap, suitable, quite expensive, and very expensive. The price range for each service was then determined following farmers’ feedback. Figure 4
shows the different services, their prices, and perceptions of these among farmers. The highest service price (for service 4) was perceived by farmers as very expensive.
Regarding service 1, 60% of farmers found its price of 5 TND to be very cheap, while 30% considered it suitable. Five percent of farmers believed the price for service 1 was quite expensive, and the same amount felt it was very expensive. For service 2, 25% of the farmers said the service was cheap, while 35% found it suitable. Thirty percent of farmers said the price was quite expensive and ten percent said it was very expensive. Concerning service 3, only 20% of farmers considered the price to be cheap, while 40% found the price was suitable and 40% believed it was very expensive. Finally, for service 4, 85% of farmers stated the service was very expensive and only 15% said the price was suitable.
3.3. Financial Feasibility of Payment for an IAS
To analyze the viability of the (paid) IAS technology and to ascertain a price range for the different services the WUA would offer, a feasibility study was then created based on the results obtained from the survey taking into consideration the preferences of the farmers following the disclosure of prices. A sensitivity analysis (results in Section 3.3.4
) was then conducted to determine the resilience of the project by increasing the total costs (investment, operating, and labor costs) and applying a decrease to the price of the services.
3.3.1. Investment and Operating Costs
The investment costs of the IAS at the WUA level are represented in Table 6
. The total investment costs per year are 18,400 TND. The depreciation rate is fixed for four years, which represents a depreciation rate of 25% per year.
Concerning operating and labor costs, Table 7
shows the office operating costs, the mobile unit costs, and labor costs, totaling 17,220 TND annually. In order to operate the IAS, one laborer would be required to operate the service.
For the first year, the total number of customers (obtained from the survey) was projected to be 77% of the 127 farmers in the irrigated district (98 farmers). For the first service, the number of users was hypothesized as 29, the second service as 0, the third service as 58, and 12 for the fourth service.
During the second year, the number of customers projected is (once again) 98 farmers in the irrigated district and 15 farmers located around this area. The total numbers of users would then be 113: 33 for the first service, 0 for the second service, 66 for the third service, and 13 for the fourth service.
With regards to the third year, an increase of 10% (compared to the second year) in the number of the customers would be anticipated, representing a total of 125 farmers with 37 selecting the first service, 74 selecting the third service, and 15 selecting the fourth service. The number of the total customers would then stabilize for the following years of the project.
Concerning the prices of the different services, the survey shows that farmers judged them to be suitable and cheap. The farmers’ opinions were considered when building the price for each service.
During the first year, the total benefits would be 20,028 TND, 22,476 TND in the second year, and 25,404 TND in the third year.
3.3.3. Benefit/Cost Ratio and Internal Return Rate
The benefit/cost (B/C) ratio for a 15-year project duration was calculated by taking the value of benefits and dividing by the value of costs. The life span of 15 years was selected because beyond this period the obtained value of the cash flow is negligible. Moreover, based on an exhaustive review done by [41
], the life span of water saving irrigation technologies varied from 10 to 20 years. From this, the B/C ratio obtained was 1.018 and, since this exceeds the value of 1, the project can be considered feasible.
An internal rate return (IRR) was also calculated for 21 years. The IRR was 19%, which shows the feasibility of the project, and is above the opportunity costs of 12%, which means the project has the potential to be highly successful. The selected discount rate for the implementation of the IAS is in the range that has been considered to represent the overall average for the appropriate discount rate varying commonly from 6 to 15% in developing countries [42
]. As such, the WUA of the studied irrigated area can generate profit from this project and use the money to provide farmers with micro credits.
3.3.4. Sensitivity Analysis
To determine the resilience of the base project, a sensitivity analysis was applied. The first scenario of the sensitivity analysis saw total costs increased by 10%. Based on a discount rate of 12%, the results show that the B/C ratio obtained was 0.97. Concerning IRR, the value was 9%. The second scenario saw the price decreased by 10%, along with the total benefits. Concerning the B/C ratio, the value obtained was 0.96. Concerning IRR, the value found was 7%.
The sensitivity analysis shows that the project may not generate a lot of benefits, but would at least cover its investment costs. Since the IAS would play a significant social role in helping farmers in their irrigation decisions, the social and environmental sustainability of the project should also be considered as feasible.
The results show that implementing an IAS at the WUA level is a feasible project and can be economically sustainable.