The consequences of COVID-19 on the economy and agriculture have raised many concerns about global food security, especially in developing countries. Given that food security is a critical component that is affected by global crises, beside the limited studies carried out on the macro-impacts of COVID-19 on food security in Iran, this paper is an attempt to address the dynamic impacts of COVID-19 on food security along with economic and environmental challenges in Iran. For this purpose, a survey was conducted with the hypothesis that COVID-19 has not affected food security in Iran. To address this fundamental hypothesis, we applied the systematic review method to obtain the evidence. Various evidences, including indices and statistics, were collected from national databases, scientific reports, field observations, and interviews. Preliminary results revealed that COVID-19 exerts its effects on the economy, agriculture, and food security of Iran through six major mechanisms, corresponding to a 30% decrease in the purchasing power parity in 2020 beside a significant increase in food prices compared to 2019. On the other hand, the expanding environmental constraints in Iran reduce the capacity of the agricultural sector to play a crucial role in the economy and ensure food security, and in this regard, COVID-19 forces the national programs and budget to combat rising ecological limitations. Accordingly, our study rejects the hypothesis that COVID-19 has not affected food security in Iran.

No abstract

No abstract

No abstract

In recent years, climate change in Iran has led to frequent droughts and reduction of available water resources. Iranian farmers are extremely vulnerable to unexpected drought. Despite the undesirable impacts of climate change on their vulnerability, farmers have not sufficiently used adaptive strategies; accordingly, we investigated factors affecting farmers’ choice of adaptive strategies to lessen the consequences of climate change in Iran. We propose a framework that covers household, farm, socio-economic, social-capital, and psychological characteristics. Farmers (n = 366) in Fars province, Iran, were selected using a multistage, stratified random sampling method, and data were collected through questionnaires during 2018-2019. Considering the adaptive strategies of changing crop varieties, crop patterns, and irrigation technologies, a multinomial logit model was used. The results showed that off-farm income and access to credit had a significant positive effect on adopting costly and efficient strategies, including changing crop varieties and irrigation technologies. Moreover, our results indicated that when farmers actively participate in social groups, their beliefs and risk perception of climate change become stronger, providing greater incentives to employ adaptive strategies. This study revealed the effective role of social-capital and psychological characteristics in the adaptive behavior of farmers in Iran.

Regarding the rapid socio-economic development, increasing food demand and decreasing available resources, this challenge has become a major problem in the agricultural sector, causing the change consumption from surface water to groundwater resources and reduction of farmers' income. Therefore, optimal programming of the cropping pattern is necessary to handle such challenges. To accomplish the mentioned aim, a model of irrigation water allocation was developed based on the cropping pattern using multistage stochastic programming in accordance with the surface water supply fluctuations. In this model, different stochastic states are considered for all irrigation seasons in the irrigation network of Jiroft plain in Kerman province, which faces a severe shortage of surface water resources and the tendency of farmers to overuse groundwater resources. By solving multistage stochastic model, it can be observed that by utilizing an appropriate programming of the cropping pattern, more benefits for the farmers could be realized in the conditions of available surface water fluctuations. The results also indicated that if the surface water released into the canals increased in the spring, the share of profitable with high water consumption crops in pattern will increase, which will strengthen farmers' profits and pressure on groundwater resources. However, it could not expect to receive a significant reduction of groundwater resource consumption and a significant increase of cropping intensity. According to the results obtained, surface water resources cannot meet the water needs of the region, even by using optimal cropping patterns, and this has led to overuse of groundwater resources in this area. Finally, such planning can help adoption of desired policies for irrigation water management through the proper release of these resources.

Integrated management of water supply and demand has been considered by many policymakers and due to its complexity, the decision makers have faced many challenges. In this study, we proposed an efficient framework for managing water supply and demand in line with the economic and environmental objectives of the basin. To design this framework, a combination of ANFIS and multi-objective augmented ε-constraint programming models and TOPSIS were used. First, using hydrological data from 2001 to 2017, the rate of water release from the dam reservoir was estimated with the ANFIS model; afterwards, its allocation to agricultural areas was performed by combining multi-objective augmented ε-constraint models and TOPSIS. To prove the reliability of the proposed model, the southern Karkheh basin in Khuzestan province, Iran, was considered as a case study. The results showed that this model is able to reduce irrigation water consumption and improve its economic productivity in the basin.

No abstract