Economic analysis of water footprint for water management of rain-fed and irrigated almonds in Iran

Bazrafshan, Ommolbanin; Vafaei, K.; Etedali, Hadi Ramezani; Zamani, Hossein; Hashemi, Masoumeh

doi:10.1007/s00271-023-00861-y

Cited by 6 publications

(3 citation statements)

References 53 publications

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“…Determining the blue water footprint can be considered an important indicator in agricultural water management [34]. This indicator has been used to better manage agricultural water resources in various studies in arid regions [35,36]. In this study, instead of using the evapotranspiration parameter that has been used to calculate the water footprint [37], the Gross Irrigation Water Requirement (GIWR) parameter was used.…”

Section: • Blue Water Footprintmentioning

confidence: 99%

A Framework for Assessing Food Baskets Based on Water and Carbon Footprints

Mohammadi,

Javadi,

Yousefi

et al. 2024

Water

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The composition of food baskets can significantly influence the water consumption rate and society’s environmental impact. This study evaluates the sustainability of Iran’s food and nutrition security by evaluating five food baskets using water and carbon-footprint indices. These food baskets are the common Iranian food basket (CIFB), the vegetarian food basket (VFB), the Ministry of Health desired food basket (MHDFB), the Swiss Society for Nutrition food basket (SSNFB), and the Mediterranean food basket (MFB). This study also examines the role of Iran’s agricultural sector under the Paris Climate Change Agreement (COP21). The TOPSIS multi-criteria decision-making method was used to identify the most desirable food basket. The results of this study show that the VFB could be the most desirable alternative to the CIFB. Replacing the CIFB with the VFB causes a 10% and 21% lower water and carbon footprint, respectively. From a 30-year perspective (around 2050), choosing the VFB would reduce the blue water footprint by 19.7 BCM and the gray water footprint by 3.6 BCM compared to the CIFB. According to the provisions of COP21 regarding Iran’s voluntary program to reduce greenhouse gas emissions, the agricultural sector will be one of the sources of greenhouse gas emissions that will face an upward trend. Hence, to adhere to this voluntary commitment, these emissions should be reduced by changing the CIFB to the VFB or reducing emissions in other sectors, such as industry. Choosing the VFB can reduce 10.7 million tons of CO2 emissions, which can be a significant step for the agricultural sector in Iran in reducing greenhouse gas emissions. Overall, considering the characteristics of farm products (water and carbon footprints) in Iran, a country located in a semi-arid climate, the VFB is recommended.

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Section: • Blue Water Footprintmentioning

confidence: 99%

A Framework for Assessing Food Baskets Based on Water and Carbon Footprints

Mohammadi,

Javadi,

Yousefi

et al. 2024

Water

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“…Sun et al [21] accounted for the spring wheat production water footprint in China's irrigation areas and distinguished the water footprint of irrigated agriculture and rain-fed agriculture. Bazrafshan et al [22] investigated almond cultivation in Iran and compared the water footprint of rain-fed and irrigated almond cultivation. Zhang et al [23] calculated the agricultural water footprint and constructed a regional water use evaluation index system in a typical arid zone to indicate the water stress.…”

Section: Introductionmentioning

confidence: 99%

Water Footprint Assessment of Agricultural Crop Productions in the Dry Farming Region, Shanxi Province, Northern China

Wang,

Yan,

Zhang

et al. 2024

Agronomy

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Exploring the crop production water footprint and their driving factors is of significant importance for management of agricultural water resources. However, how do we effectively assess the total agricultural water consumption and explore the significance of their driving factors, i.e., population, economy, and agricultural production conditions, using a backpropagation neural network (BPNN)? It is still ambiguous. Water consumption for crops during the growing season is explicitly explored by way of water footprint indicators (green water footprint, WFPg, and blue water footprint, WFPb). This study provides new insights into the factors driving the changes in crop production water footprint in Taiyuan City over the period of 2005–2021. Simulations of crop evapotranspiration using the CROPWAT model were quantified. The results showed that Taiyuan City has a low crop yield level below the average level of China, with the highest crop yield in maize. The crop production water footprint in Taiyuan City showed a non-linearly decreasing trend over time. The average annual crop production water footprint was 187.09 × 103 m3/kg in Taiyuan City, with the blue water footprint and green water footprint accounting for 63.32% and 36.68%, respectively. The crop production water footprint in the west and north of Taiyuan City was significantly higher than those in other areas, accounting for 42.92% of the total crop production water footprint. Oilseed crops contributed most to the total crop production water footprint, accounting for 47.11%. The GDP and total sown area of crops were more important for the changes in WFPb. Agricultural machinery power and agriculture-to-non-agriculture ratio were more important for the changes in WFPg. Agricultural machinery power and GDP were more important for the changes in IWFP. In-depth analysis of the factors driving the changes in crop production water footprint is dramatically important for agricultural decision makers to mitigate water resource pressure in Taiyuan City.

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“…Rainfall has great significance as a hydrologic parameter, is a vital feature of climate change, and significantly affects food production, harvesting, human resources, and the natural environment 6 . Relevant and essential rainfall information, such as daily, weekly, and monthly assessments, are required to maintain an adequate water management system 7 , 8 . The historical rainfall trend analysis can make predictions 9 .…”

Section: Introductionmentioning

confidence: 99%

Spatiotemporal analysis and predicting rainfall trends in a tropical monsoon-dominated country using MAKESENS and machine learning techniques

Monir,

Rokonuzzaman,

Sarker

et al. 2023

Sci Rep

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Spatiotemporal rainfall trend analysis as an indicator of climatic change provides critical information for improved water resource planning. However, the spatiotemporal changing behavior of rainfall is much less understood in a tropical monsoon-dominated country like Bangladesh. To this end, this research aims to analyze spatiotemporal variations in rainfall for the period 1980–2020 over Bangladesh at seasonal and monthly scales using MAKESENS, the Pettitt test, and innovative trend analysis. Multilayer Perception (MLP) neural network was used to predict the next 8 years' rainfall changes nationally in Bangladesh. To investigate the spatial pattern of rainfall trends, the inverse distance weighting model was adopted within the ArcGIS environment. Results show that mean annual rainfall is 2432.6 mm, of which 57.6% was recorded from July to August. The Mann–Kendall trend test reveals that 77% of stations are declining, and 23% have a rising trend in the monthly rainfall. More than 80% of stations face a declining trend from November to March and August. There is a declining trend for seasonal rainfall at 82% of stations during the pre-monsoon, 75% during the monsoon, and 100% during the post-monsoon. A significant decline trend was identified in the north-center during the pre-monsoon, the northern part during the monsoon, and the southern and northwestern portions during the post-monsoon season. Predicted rainfall by MLP till 2030 suggests that there will be little rain from November to February, and the maximum fluctuating rainfall will occur in 2025 and 2027–2029. The ECMWF ERA5 reanalysis data findings suggested that changing rainfall patterns in Bangladesh may have been driven by rising or reducing convective precipitation rates, low cloud cover, and inadequate vertically integrated moisture divergence. Given the shortage of water resources and the anticipated rise in water demand, the study's findings have some implications for managing water resources in Bangladesh.

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Economic analysis of water footprint for water management of rain-fed and irrigated almonds in Iran

Cited by 6 publications

References 53 publications

A Framework for Assessing Food Baskets Based on Water and Carbon Footprints

A Framework for Assessing Food Baskets Based on Water and Carbon Footprints

Water Footprint Assessment of Agricultural Crop Productions in the Dry Farming Region, Shanxi Province, Northern China

Spatiotemporal analysis and predicting rainfall trends in a tropical monsoon-dominated country using MAKESENS and machine learning techniques

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