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Urmia lake water has impressively decreased recently and seriously endangered the lives of the inhabitants. In this paper, the effects of various factors on the reduction of the lake water are investigated and appropriate scenarios are proposed for future improvement. Due to the significant impact of agricultural issues on this crisis, this paper has focused specifically on agriculture. So, this paper aims to forecast and improve the lake water level.

In this paper, a system dynamics (SD) model, which is capable to consider various parameters and variables affecting the lake water level within nonlinear and dynamic relations, is developed.

To show the effectiveness of SD model, real data are used to run the model and the results show that the actual behavior of the lake water is reproduced with high validation (around 98.28 per cent). Also, five different scenarios are proposed to increase lake water volume. The hybrid Scenario 5 (which combines three other scenarios including increasing irrigation efficiency in the agricultural sector, changing cultivation pattern of agricultural products and returning some dams’ water that are consumed in the agricultural sector into the lake) is chosen as the most effective scenario for increasing lake volume about 15 billion m³.

The main contributions of this paper are systemic view to the whole problem, paying attention to the agriculture subject as one of the most important issues, considering many critical variables (e.g. evaporation, salinity and precipitation) and providing improvement policies along with assessing the effects of them.

This paper aims to build a theoretical model of the impact of farmers’ adoption behavior of soil and water conservation measures on the agricultural output to analyze the impact of farmers’ adoption behavior of soil and water conservation measures on agricultural output.

Based on the field survey data of 808 farmers households in three provinces (regions) of the Loess Plateau, this paper using the endogenous switching regression model to analyze the effect of farmers’ adoption behavior of soil and water conservation measures on agricultural output.

Soil erosion has a significant negative impact on agricultural output, and soil erosion has a significant positive impact on farmers’ adoption of soil and water conservation measures. Farmers adopt soil and water conservation measures such as engineering measures, biological measures and tillage measures to cope with soil erosion, which can increase agricultural output. Based on the counterfactual hypothesis, if farmers who adopt soil and water conservation measures do not adopt the corresponding soil and water conservation measures, their average output per ha output will decrease by 2.01%. Then, if farmers who do not adopt soil and water conservation measures adopt the corresponding soil and water conservation measures, their average output per ha output will increase by 12.12%. Government support and cultivated land area have a significant positive impact on farmers’ adoption behavior of soil and water conservation measures.

The research limitation is the lack of panel data.

Soil erosion has a significant negative impact on agricultural output, and soil erosion has a significant positive impact on farmers’ adoption of soil and water conservation measures. Farmers adopt soil and water conservation measures such as engineering measures, biological measures and tillage measures to cope with soil erosion, which can increase agricultural output.

The conclusion provides a reliable empirical basis for the government to formulate and implement relevant policies.

The contributions of this paper are as follows: the adoption behavior of soil and water conservation measures and agricultural output are included into the same analytical framework for empirical analysis, revealing the influencing factors of farmers’ adoption behavior of soil and water conservation measures and their output effects, enriching existing research. Using endogenous switching regression model and introducing instrumental variables to overcome the endogenous problem between the adoption behavior of soil and water conservation measures and agricultural output, and to analyze the influencing factors of farmers’ adoption behavior of soil and water conservation measures and its impact on agricultural output. Using the counter-factual idea to ensure that the two matched individuals have the same or similar attributes, to evaluate the average treatment effect of the behavior of soil and water conservation measures, to estimate the real impact of adaptation measures on agricultural output as accurately as possible and to avoid misleading policy recommendations.

This paper aims to assess the economic effects of climate change on the Mediterranean’s irrigated agriculture and how the adoption of alternative crop varieties adapted to the expected length of the growing season can be an effective adaptation measure.

A case study of two irrigation areas in Southern Portugal is used to assess the response to climate change impacts on crop yields and irrigation requirements, and an agricultural supply model is calibrated using a positive mathematical programming (PMP) approach was developed.

Climate change reduces crop yields and causes a slight decrease in irrigation requirements, which could allow an increase in the irrigated area. However, positive impacts on rural areas regarding employment and investment are not expected. The adoption of adaptation measures based on alternative crop varieties, which could maintain crop yields at current levels, increases dramatically the economic value of water and mitigates losses in farm income.

The impacts on output and input market prices, as well as other biophysical impacts (for instance, CO₂ and water availability), are important in understanding the effects of climate change on irrigated agriculture, but they were not considered in this study. While this may be a limitation, it can also be a stimulus for further research.

This is an empirical paper, whose results contribute to improving knowledge about the effects of climate change on irrigated agriculture in Mediterranean areas, namely, its economic impacts on returns and the use of agricultural resources (land, water, labour and capital). Other practical implications of the paper are associated with the methodological approach, which provides a framework able to deal with the complexity and multidimensional effects of climate change.

The results of the paper provide important information for scientists, politicians and other stakeholders about the design of more effective adaptation measures able to mitigate the effects of climate change.

Crop yields and irrigation requirements were previously calculated based on data generated by the regional climate models. This is the first time that an application is developed for Portugal. Two distinct profiles of irrigation areas were studied and a large set of crops was considered, which is not common in the existing studies. To specify the PMP approach used to calibrate the agricultural supply model, exogenous crop-specific supply elasticities were estimated through a least square model, which is not common in previous studies.

This paper aims to propose, for the very first time in Burkina Faso, a “no regret” reference tool to improve policies and processes which could strengthen agricultural water resilience under climate risks and change for sustained food security. Such a framework consists of five pillars derived from the agricultural water vulnerability analysis.

The method combined a new designed tool “ClimProspect”, adapted to the Sahelian climatic context, participatory and analogue approaches.

Innovative “no regret” framework to overcome current and future climate risks on agricultural water requirements has been built.

The paper proposes a new way to assess vulnerability and build resilience for a given system and brings climate and disaster risks together. In fact, in the country, disaster and climate risks are closely associated.

The proposed measures will reinforce water security under climate variability and change and disaster risks, boost the farmers’ participation in water governance and secure the adaptation investment for the long term.

Implementing the proposed measures should provide farmers with agricultural water needs at any time over the year, having access to social protection and sustainably increase their food security.

Method used explicitly allows for paying attention, at the same time, to climate variability and change, disaster risks and social issues. The “no regret” framework is a practical secured tool for policy makers and planners, and it gives them a new way to secure sustainable water requirements.

A core challenge of assessing regional agricultural drought vulnerability (RADV) is to reveal what vulnerability factors, under which kinds of synergistic combinations and at what strengths, will lead to higher vulnerability: namely, the influence patterns of RADV.

A two-phased grey rough combined model is proposed to identify influence patterns of RADV from a new perspective of learning and mining historical cases. The grey entropy weight clustering with double base points is proposed to assess degrees of RADV. The simplest decision rules that reflect the complex synergistic relationships between RADV and its influencing factors are extracted using the rough set approach.

The results exemplified by China's Henan Province in the years 2008–2016 show higher degrees of RADV in the north and west regions of the province, in comparison with the south and east. In the patterns with higher RADV, the higher proportion of agricultural population appears in all decision rules as a core feature. A smaller quantity of water resources per unit of cultivated land area and a lower adaptive capacity, involving levels of irrigation technology and economic development, present a significant synergistic influence relationship that distinguishes the features of higher vulnerability from those of the lower.

The proposed grey rough combined model not only evaluates temporal dynamics and spatial differences of RADV but also extracts the decision rules between RADV and its influencing factors. The identified influence patterns inspire managerial implications for preventing and reducing agricultural drought through its historical evolution and formation mechanism.

Intensive agricultural production in the countries of the Aral Sea Basin has resulted in undesirable ecological and social consequences, including the drying of the Aral Sea. Water has become scarce due to a score of internal and external factors including the growing demand for water resources by the upstream countries, expansion of the irrigated areas to ease food insecurity, and the poor condition of irrigation and drainage networks. To cope with environmental consequences and regional water challenges, it is vital to look for pathways of improved integrated water resource management, higher water use efficiencies, and reducing overall water use.

A combination of value chain and water footprint analyses of the dominant crop, cotton, was applied to assess water use in different sectors of the Uzbekistan economy and to seek water saving and improved water management and efficiency options.

The findings show that reduction in water use could be achieved by diversifying the economy and moving from water intensive agricultural production to less water consuming industrial sectors by introducing water saving irrigation technologies and by raising awareness of the population about the real value of water.

The combined findings of the economic based value chain analysis and ecologically oriented water footprint analysis gave an added value for better informed decision-making to reach land, water, and ecosystem sustainability and to contribute to the Millennium Development Goals of eradicating poverty and hunger and achieving food and water security.

Agriculture is under pressure to produce more food under increasingly variable climate conditions. Consequently, producers need management innovations that lead to improved physical and financial productivity. Currently, farm accounting technologies lack the sophistication to allow producers to analyse productivity of water. Furthermore water-related agricultural technology (“agtech”) systems do not readily link to accounting innovations. This study aims to establish a conceptual and practical framework for linking temporal, biophysical and management decision-making to accounting by develop a soil moisture and climate monitoring tool.

The paper adopts an exploratory mixed-methods approach to understand supply of and demand for water accounting and water-related agtech; and bundling these innovations with farm accounting to generate a stable tool with the ability to improve agricultural practices over time. Three phases of data collection are the focus here: first, a desk-based review of water accounting and water technology – including benchmarking of key design characteristics of these methods and key actor interviews to verify and identify trends, allowing for conceptual model development; second, a producer survey to test demand for the “bundled” conceptual model; third and finally, a participant-based case study in potato-farming that links the data from direct monitoring and remote sensing to farm accounts.

Design characteristics of water accounting and agtech innovations are bundled into an overall irrigation decision-making conceptual model based on in-depth review of available innovations and verification by key actors. Producer surveys suggest enough demand to pursue practical bundling of these innovations undertaken by developing an integrated accounting, soil moisture and climate monitoring tool on-farm. Productivity trends over two seasons of case study data demonstrate the pivotal role of accounting in leading to better technical irrigation decisions and improving water productivity.

The model can assist practitioners to gauge strengths and weaknesses of contemporary water accounting fads and fashions and potential for innovation bundling for improved water productivity. The practical tool demonstrates how on-farm irrigation decision-making can be supported by linking farm accounting systems and smart technology

This paper aims to examine impediments to the adoption of sustainable water-efficient technological innovation in agriculture. Farming is the largest water consumer and food production expansion in response to global population growth, combined with increasing droughts from climate change, threatens water and food insecurity for many countries. Yet, climate smart agriculture (CSA) innovation adoption has been slow, and in this regard, governments and the agricultural sector are not fulfilling their social responsibility and sustainability obligations.

Barriers to water-efficient drip irrigation (DI) adoption in Australia were investigated via 46 depth interviews with agricultural stakeholders and a survey of 148 farmers.

While DI water efficiency is recognised, this is not the key determinant of farmers’ irrigation method selection. Complex interrelationships between internal and external barriers impede DI adoption are identified. These include costs, satisfaction with alternative irrigation methods, farmer characteristics that determine the suitability of the innovation and the extent it is incremental or radical, plus various multidimensional risks. Government support of alternative, less water-efficient irrigation methods is also a critical barrier.

A conceptual framework for understanding barriers to sustainability oriented innovation adoption is presented. Its insights should be applicable to researchers and practitioners concerned with understanding and improving the adoption of socially responsible and sustainable innovation in a wide range of contexts. Recommendations for overcoming such adoption barriers are discussed in relation to the research focus of water-efficient agriculture and encouraging uptake of DI.

The onset of climate change is expected to result in variations in weather patterns which can exacerbate water scarcity issues. This can potentially impact the economic productivity of nations as economic activities are highly dependent on water especially for agricultural countries. In response to this, the concepts of virtual water and water footprint have been introduced as metrics for measuring the water intensity of products, services and nations. Researchers have thus looked into virtual water trade flows as a potential strategy for alleviating water scarcity. The paper aims to discuss these issues.

Environmentally extended input-output models (IOMs) are often used to analyze interactions between economic and ecological systems. This work thus develops a multi-regional input-output model for optimizing virtual water trade between different geographic regions in consideration of local environmental resource constraints, product demands and economic productivity.

A case study on agriculture crop production and trade in different regions of the Philippines is utilized to demonstrate the capabilities of the model. The results show that the optimal strategy does not necessarily limit a water-scarce region to produce less water-intensive crops.

The model uses an input-output framework whose fixed coefficients reflect a fixed technological state. As such, the model is best used for short-term projections, or projections for mature technological state (i.e. where no major gains in efficiency or yield can be foreseen).

The proposed modeling framework can be used in any geographic region (provided relevant statistical data are available for calibration) to provide decision support for optimal use of limited water resources.

The model proposed in this work has general applicability to the optimal planning of agro-industrial systems under water footprint constraints. This modeling approach will be particularly valuable in the future, as climate change causes changes in precipitation patterns and water availability.

The purpose of this paper is to gain more insight into the relationship between off‐farm employment of rural households and water‐saving investments and irrigation water use in rural China.

Data from a survey held among 317 households in Minle County, Zhangye City, Gansu Province, covering the year 2007, are used for a probit analysis explaining investments in land leveling and for an ordinary least squares regression explaining irrigation water use per mu.

Off‐farm employment is not significantly related to investments in land leveling, but is negatively associated with water use per mu. In addition, the paper finds that the share of migrant students in a household is positively related to investments in land leveling. The results indicate the presence of major factor market imperfections in the research area, and confirm that the new economics of labor migration (NELM) approach is more relevant for analyzing off‐farm employment and agricultural production in China than neoclassical economic theory.

The paper expands the NELM approach towards the analysis of water‐saving investments and water use. In addition, it distinguishes migrant students as an important category that should be taken into account in analyzing farm household decisions making.