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Irrigation is an important adaptation strategy to cope with climate change which reduces vulnerability to water stress and improves crop productivity to feed millions. There is evidence of crop yield stagnation in many developing countries, and irrigation efficiency is claimed to increase crop productivity. Therefore, this paper uses data envelopment analysis to evaluate the farmer’s productivity through technical efficiency (TE), i.e., the relationship between resource inputs and outputs of 513 paddy farmers in Eastern India. The results show that the farms are, on average operating at 14% TE, leaving a considerable scope to improve up to 86% to reach the optimal level. A significant difference is observed between irrigated and rain-fed paddy farmers, such that10% of the irrigated farms achieved efficiency scores over 40% and only 2% of rain-fed farms achieved the same. The tobit and beta fit regression models are estimated to find out the factors that influence the TE. Both surface water and groundwater sources of irrigation are used as predictors, along with other socio-demographic factors. Access to surface water irrigation is identified to be a significant determinant of farm efficiency, however, surface water irrigation, such as canal irrigation, is accessible only to farmers living on plain land. Farmers living on highlands need to explore other sources of irrigation practices, such as drip and sprinkler, that can increase TE and farm productivity. Therefore, this paper calls for government intervention to provide extensive training and facilities for these micro-irrigation practices.

Irrigation is an important adaptation strategy to cope with climate change which reduces vulnerability to water stress and improves crop productivity to feed millions. There is evidence of crop yield stagnation in many developing countries, and irrigation efficiency is claimed to increase crop productivity. Therefore, this paper uses data envelopment analysis to evaluate the farmer's productivity through technical efficiency (TE), i.e., the relationship between resource inputs and outputs of 513 paddy farmers in Eastern India. The results show that the farms are, on average operating at 14% TE, leaving a considerable scope to improve up to 86% to reach the optimal level. A significant difference is observed between irrigated and rain-fed paddy farmers, such that10% of the irrigated farms achieved efficiency scores over 40% and only 2% of rain-fed farms achieved the same. The tobit and beta fit regression models are estimated to find out the factors that influence the TE. Both surface water and groundwater sources of irrigation are used as predictors, along with other socio-demographic factors. Access to surface water irrigation is identified to be a significant determinant of farm efficiency, however, surface water irrigation, such as canal irrigation, is accessible only to farmers living on plain land. Farmers living on highlands need to explore other sources of irrigation practices, such as drip and sprinkler, that can increase TE and farm productivity. Therefore, this paper calls for government intervention to provide extensive training and facilities for these micro-irrigation practices. • Data Envelopment analysis was estimated to derive the paddy efficiency among the tribal villages of eastern India. • The DEA estimates show that average Technical efficiency in the study region is much below the national average. • Irrigated farmers are more efficient than the rain-fed farmers. Surface irrigation is the dominate factor. • Rain-fed paddy cultivators' farm efficiency would improve by 6.5%, if they had irrigated. • Semi-mountainous regions with little access to surface irrigation must explore micro-irrigation practices such as drips and sprinklers. [ABSTRACT FROM AUTHOR]

Water scarcity threatens food security and leads to various economic, social, and environmental challenges, particularly in arid and semi-arid regions. As the agricultural sector consumes the most significant amount of water, conserving water resources in this sector is particularly important. Cultivation of low-water-demand (LWD) crops with high value-added is one of the effective measures to reduce agricultural water demand and improve farmers' livelihoods. However, changing water-intensive crops to LWD crops (e.g., medicinal plants) is voluntary pro-environmental behavior. Considering the role of psychological theories in understanding and explaining human behaviors, the main purpose of the current paper is to explore the socio-psychological determinants underlying farmers' intention to adopt an LWD cropping pattern using the Health Belief Model (HBM). In this regard, data were collected using face-to-face interviews with 184 farmers living in Zanjan province, Iran to examine their intention to cultivate LWD medicinal plants. Using structural equation modeling for data analysis, the HBM explained 49% of the variance in farmers' behavioral intentions. The structural equation modeling outcomes also revealed that self-efficacy, perceived barriers, cues to action, and perceived benefits are significantly related to farmers' intention to choose medicinal plants. Overall, the findings indicated the effectiveness and applicability of the HBM in illustrating farmers' intention to change their cropping pattern. Applying some strategies such as providing the necessary facilities and training programs for farmers, as well as, advertisements aimed at promoting the cultivation of medicinal plants can significantly contribute to conserving water resources in the study area. • Evaluating farmers' intention to medicinal crops using the Health Belief Model. • The HBM accounted for 49% of the variance of the farmers' behavioral intentions. • Self-efficacy, perceived expectations, and cues to action affect farmers intentions. • Self-efficacy was identified as the main predictor of farmers behavioral intentions. • Cultivating medicinal crops help conserving water resources in the study area. [ABSTRACT FROM AUTHOR]

Climate change has led to extreme weather events and food security issues, which have become urgent global problems. Crop models and hydrological models play important roles in analyzing these issues, but crop models have limitations in large-scale simulations, and hydrological models have shortcomings in depicting underlying surface details. Jointly using the two models to complement each other's shortcomings is becoming an important method, playing an important role in improving the quantitative characterization ability of different facets of agricultural production and is crucial to improving the efficiency of water resources utilization. This paper reviews the development process of crop and hydrological models and summarizes the widely used models at present, providing reference for researchers to select crop and hydrological models; secondly, it summarizes the types, methods, and examples of joint use of models, and analyzes possible problems in model combination; finally, some suggestions are put forward for the joint use of crop and hydrological models, providing a reference for researchers to combine models. • Retrospect on the development process of crop and hydrological models. • Summarized case studies on the combination of crop and hydrological models. • Provide an overview of cases where crop and hydrological models are used in conjunction. • General considerations and suggestions for future development. [ABSTRACT FROM AUTHOR]

Water scarcity threatens food security and leads to various economic, social, and environmental challenges, particularly in arid and semi-arid regions. As the agricultural sector consumes the most significant amount of water, conserving water resources in this sector is particularly important. Cultivation of low-water-demand (LWD) crops with high value-added is one of the effective measures to reduce agricultural water demand and improve farmers' livelihoods. However, changing water-intensive crops to LWD crops (e.g., medicinal plants) is voluntary pro-environmental behavior. Considering the role of psychological theories in understanding and explaining human behaviors, the main purpose of the current paper is to explore the socio-psychological determinants underlying farmers' intention to adopt an LWD cropping pattern using the Health Belief Model (HBM). In this regard, data were collected using face-to-face interviews with 184 farmers living in Zanjan province, Iran to examine their intention to cultivate LWD medicinal plants. Using structural equation modeling for data analysis, the HBM explained 49% of the variance in farmers' behavioral intentions. The structural equation modeling outcomes also revealed that self-efficacy, perceived barriers, cues to action, and perceived benefits are significantly related to farmers' intention to choose medicinal plants. Overall, the findings indicated the effectiveness and applicability of the HBM in illustrating farmers’ intention to change their cropping pattern. Applying some strategies such as providing the necessary facilities and training programs for farmers, as well as, advertisements aimed at promoting the cultivation of medicinal plants can significantly contribute to conserving water resources in the study area.