Finding pathways for enhancing irrigated farming systems in Lebanon

Abstract : The economy of the Middle East relies heavily on agriculture as a source of food and income. These countries have initiated agricultural policies that advocate the intensification of their production systems. These policies encourage greater use of subsidized inputs and the purchase of famers’ production at subsidized prices compared to international market prices. The methodology of this work was to start with comprehensive farms survey followed by a cluster analysis to help identify and assess the farming systems diversity in the area and their performances. Then to propose scenarios of variations in water availability and prices, market prices of agricultural produce, and premiums given to farmers for the purpose of testing the vulnerability of the current cropping systems to shocks. And finally to construct a bio-economic model to help capturing the resilience indicators of the farming systems in the area. Baalbek-Hermel, in the northern part of the Bekka Valley in Lebanon, was selected to be representative for Lebanon as well as the MENA region due to the facts that it is the most desertification prone area in country and one of its poorest agricultural areas. It has diverse /mosaic biophysical conditions, with high fluctuation in rainfall. Agricultural intensification in the area started deliberately in 1970. Survey at the farm level was conducted by first selecting representative farms: a sample of 97 farmers out of 486 were selected and given a quantitative questionnaire containing closed questions covering the farmer’s socio-economic profile, farming practices, production, costs incurred, and marketing access strategies. Estimation of amount of irrigation water per crop followed since irrigation water is distributed to farms on a per hour or per area basis, and not based on the volume of water applied. To estimate the amount of irrigation water applied per crop, and subsequently its cost, which is initially expressed as area or time, two calculation steps were defined: mapping the spatial water distribution systems in the study area, and estimation of water flow for each source of irrigation water. To classify the different farms in the study area according to their cropping patterns, a principal component analysis (PCA), followed by Hierarchical Ascendant Classification (HAC) was performed. The farm typology was then followed by a sensitivity analysis to investigate the extent to which farm incomes, in the study region, were sensitive to prices and subsidy variabilities. This includes sensitivity to allocated premiums or/and product price, and irrigation water prices, taking into consideration farming system diversity in the region. The analysis carried out was intended to assess, for each farm type, income loss, but also productivity loss in response to the suppression of subsidies for each crop (wheat tobacco, grape, and potato), or to the increase in irrigation water prices in order to reduce its consumption. Finally, scenarios for vulnerability were defined, which were composed of mainly four components: time horizon, spatial scale, external driving forces, and indicators/intermediate variables. The dynamic recursive bio-economic model was developed to assess the scenarios and calculate the resilience indicators. Our results showed that intensification pathways led to five different types of farming systems, except for conventional extensive cereal farms. Although these farming types follow different trajectories, they still achieve similar incomes with different potential environmental impacts. Beyond the results obtained at study zone level, this study shows that the intensification of agriculture has allowed farmers to increase their incomes, but often at the cost of environmental degradation. However, this improvement remains very dependent on direct or indirect support levels granted to farmers.
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Mohamad El Khansa. Finding pathways for enhancing irrigated farming systems in Lebanon. Agricultural sciences. Université Montpellier, 2017. English. ⟨NNT : 2017MONTT104⟩. ⟨tel-01697620⟩

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