A new approach to the allocation of the blue water footprint of reservoirs using fuzzy AHP model

2019 ◽  
Vol 6 (2) ◽  
pp. 793-797 ◽  
Author(s):  
Mohammad Reza Golabi ◽  
Feridon Radmanesh
Keyword(s):  
Water Footprint ◽  
Fuzzy Ahp ◽  
Blue Water ◽  
New Approach ◽  
Ahp Model

Assessment of Water Footprint in Selected Crops: A State Level Appraisal

2017 ◽  
Vol 1 (1) ◽  
pp. 11-25
Author(s):  
Mohammad Suhail
Keyword(s):  
Water Use ◽  
Water Footprint ◽  
Large Fraction ◽  
State Level ◽  
Soil Survey ◽  
National Bureau ◽  
Blue Water ◽  
Total Water Consumption ◽  
Balanced Approach ◽  
Green Component

Every commodity or goods has intake of water i.e. either in processing or furnished stage. Thus, the present study propensities macro-level (states-level) water footprint (WFP) assessment of selected eight crops namely, Wheat, Barley, Maize, Millets, Rice, Sorghum, Soybeans and Tea. The aim of present research is to assess water use in selected crops at field level. In addition, the spatial evaluation at state level also considered as one of the significant objective to understand regional disparity and/or similarly. Methodology and approach of assessment was adopted from Water Footprint Assessment Manual (2011). Data was collected from state Agricultural Directorate, National Bureau of Soil Survey and landuse, published reports and online database such as FAOSTAT, WMO, WFN, and agriculture census. Results show that green component of WFP contributes large fraction as about 72 percent, while blue and grey component amounted of about 19 and 9 percent of the total water consumption, respectively. Moreover, spatial variability of blue, green and grey among the states assimilated by soil regime and climate barriers. Supply of blue water is high where the region imparted to semi-arid or arid land. Consequently, a balanced approach between green and blue water use has been recommended in the present study to address increasing water demand in the future.

scholarly journals Agro-economic and socio-environmental assessments of food and virtual water trades of Iran

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Fatemeh Karandish ◽  
Hamideh Nouri ◽  
Marcela Brugnach
Keyword(s):  
Food Security ◽  
Water Consumption ◽  
Crop Production ◽  
Water Footprint ◽  
Virtual Water ◽  
Environmental Indicators ◽  
Blue Water ◽  
Water Crisis ◽  
Food Trade ◽  
Water Limitations

AbstractEnding hunger and ensuring food security are among targets of 2030’s SDGs. While food trade and the embedded (virtual) water (VW) may improve food availability and accessibility for more people all year round, the sustainability and efficiency of food and VW trade needs to be revisited. In this research, we assess the sustainability and efficiency of food and VW trades under two food security scenarios for Iran, a country suffering from an escalating water crisis. These scenarios are (1) Individual Crop Food Security (ICFS), which restricts calorie fulfillment from individual crops and (2) Crop Category Food Security (CCFS), which promotes “eating local” by suggesting food substitution within the crop category. To this end, we simulate the water footprint and VW trades of 27 major crops, within 8 crop categories, in 30 provinces of Iran (2005–2015). We investigate the impacts of these two scenarios on (a) provincial food security (FSp) and exports; (b) sustainable and efficient blue water consumption, and (c) blue VW export. We then test the correlation between agro-economic and socio-environmental indicators and provincial food security. Our results show that most provinces were threatened by unsustainable and inefficient blue water consumption for crop production, particularly in the summertime. This water mismanagement results in 14.41 and 8.45 billion m3 y−1 unsustainable and inefficient blue VW exports under ICFS. “Eating local” improves the FSp value by up to 210% which lessens the unsustainable and inefficient blue VW export from hotspots. As illustrated in the graphical abstract, the FSp value strongly correlates with different agro-economic and socio-environmental indicators, but in different ways. Our findings promote “eating local” besides improving agro-economic and socio-environmental conditions to take transformative steps toward eradicating food insecurity not only in Iran but also in other countries facing water limitations.

scholarly journals A spatially detailed blue water footprint of the United States economy

2018 ◽  
Vol 22 (5) ◽  
pp. 3007-3032 ◽  
Author(s):  
Richard R. Rushforth ◽  
Benjamin L. Ruddell
Keyword(s):  
United States ◽  
Water Use ◽  
Water Footprint ◽  
Virtual Water ◽  
The United States ◽  
Energy Information Administration ◽  
Blue Water ◽  
Consumptive Use ◽  
The Us ◽  
Per Capita

Abstract. This paper quantifies and maps a spatially detailed and economically complete blue water footprint for the United States, utilizing the National Water Economy Database version 1.1 (NWED). NWED utilizes multiple mesoscale (county-level) federal data resources from the United States Geological Survey (USGS), the United States Department of Agriculture (USDA), the US Energy Information Administration (EIA), the US Department of Transportation (USDOT), the US Department of Energy (USDOE), and the US Bureau of Labor Statistics (BLS) to quantify water use, economic trade, and commodity flows to construct this water footprint. Results corroborate previous studies in both the magnitude of the US water footprint (F) and in the observed pattern of virtual water flows. Four virtual water accounting scenarios were developed with minimum (Min), median (Med), and maximum (Max) consumptive use scenarios and a withdrawal-based scenario. The median water footprint (FCUMed) of the US is 181 966 Mm3 (FWithdrawal: 400 844 Mm3; FCUMax: 222 144 Mm3; FCUMin: 61 117 Mm3) and the median per capita water footprint (FCUMed′) of the US is 589 m3 per capita (FWithdrawal′: 1298 m3 per capita; FCUMax′: 720 m3 per capita; FCUMin′: 198 m3 per capita). The US hydroeconomic network is centered on cities. Approximately 58 % of US water consumption is for direct and indirect use by cities. Further, the water footprint of agriculture and livestock is 93 % of the total US blue water footprint, and is dominated by irrigated agriculture in the western US. The water footprint of the industrial, domestic, and power economic sectors is centered on population centers, while the water footprint of the mining sector is highly dependent on the location of mineral resources. Owing to uncertainty in consumptive use coefficients alone, the mesoscale blue water footprint uncertainty ranges from 63 to over 99 % depending on location. Harmonized region-specific, economic-sector-specific consumption coefficients are necessary to reduce water footprint uncertainties and to better understand the human economy's water use impact on the hydrosphere.

scholarly journals The green, blue and grey water footprint of crops and derived crop products

2011 ◽  
Vol 8 (1) ◽  
pp. 763-809 ◽  
Author(s):  
M. M. Mekonnen ◽  
A. Y. Hoekstra
Keyword(s):  
Water Balance ◽  
River Basin ◽  
Crop Production ◽  
Water Footprint ◽  
Grid Cell ◽  
Blue Water ◽  
Total Water ◽  
Grey Water ◽  
Global Average ◽  
Average Water

Abstract. This study quantifies the green, blue and grey water footprint of global crop production in a spatially-explicit way for the period 1996–2005. The assessment is global and improves upon earlier research by taking a high-resolution approach, estimating the water footprint of 126 crops at a 5 by 5 arc min grid. We have used a grid-based dynamic water balance model to calculate crop water use over time, with a time step of one day. The model takes into account the daily soil water balance and climatic conditions for each grid cell. In addition, the water pollution associated with the use of nitrogen fertilizer in crop production is estimated for each grid cell. The crop evapotranspiration of additional 20 minor crops is calculated with the CROPWAT model. In addition, we have calculated the water footprint of more than two hundred derived crop products, including various flours, beverages, fibres and biofuels. We have used the water footprint assessment framework as in the guideline of the water footprint network. Considering the water footprints of primary crops, we see that global average water footprint per ton of crop increases from sugar crops (roughly 200 m3 ton−1), vegetables (300 m3 ton−1), roots and tubers (400 m3 ton−1), fruits (1000 m3 ton−1), cereals} (1600 m3 ton−1), oil crops (2400 m3 ton−1) to pulses (4000 m3 ton−1). The water footprint varies, however, across different crops per crop category and per production region as well. Besides, if one considers the water footprint per kcal, the picture changes as well. When considered per ton of product, commodities with relatively large water footprints are: coffee, tea, cocoa, tobacco, spices, nuts, rubber and fibres. The analysis of water footprints of different biofuels shows that bio-ethanol has a lower water footprint (in m3 GJ−1) than biodiesel, which supports earlier analyses. The crop used matters significantly as well: the global average water footprint of bio-ethanol based on sugar beet amounts to 51 m3 GJ−1, while this is 121 m3 GJ−1 for maize. The global water footprint related to crop production in the period 1996–2005 was 7404 billion cubic meters per year (78% green, 12% blue, 10% grey). A large total water footprint was calculated for wheat (1087 Gm3 yr−1), rice (992 Gm3 yr−1) and maize (770 Gm3 yr−1). Wheat and rice have the largest blue water footprints, together accounting for 45% of the global blue water footprint. At country level, the total water footprint was largest for India (1047 Gm3 yr−1), China (967 Gm3 yr−1) and the USA (826 Gm3 yr−1). A relatively large total blue water footprint as a result of crop production is observed in the Indus River Basin (117 Gm3 yr−1) and the Ganges River Basin (108 Gm3 yr−1). The two basins together account for 25% of the blue water footprint related to global crop production. Globally, rain-fed agriculture has a water footprint of 5173 Gm3 yr−1 (91% green, 9% grey); irrigated agriculture has a water footprint of 2230 Gm3 yr−1 (48% green, 40% blue, 12% grey).

scholarly journals Landfill Site Selection Using Geographic Information System and Fuzzy-AHP Model: A Case Study of Ilam Township, Iran

2020 ◽  
Author(s):  
Mehdi Ahmadi ◽  
Mehdi Nikseresht ◽  
Esmaeil Najafi ◽  
Behzad Morshedi
Keyword(s):  
Information System ◽  
Geographic Information System ◽  
Waste Disposal ◽  
Fuzzy Ahp ◽  
Geographic Information ◽  
Municipal Waste ◽  
Environmental Stability ◽  
Landfill Site Selection ◽  
Municipal Solid Wastes ◽  
Ahp Model

Introduction: Landfill siting is a difficult, complex, and protracted process, which requires evaluating different criteria. A suitable site should be located to dispose the municipal solid wastes hygienically (sanitary landfill), which is one of the fundamental subjects related to the environmental stability of the human settlements. The aim was to select a suitable waste disposal area using fuzzy-Analytic Hierarchy Process (AHP) models. Materials and Methods: To conduct this study, the information about elevation, slope, soil, drainage, vegetation, land use, population, and roads were produced and corrected in layers called shape files using the Geographic Information System (GIS) software. Finally, weights were applied in expert choice software by combining and overlapping information layers in GIS.  Results: Based on the fuzzy-AHP model, 6 sites were identified as suitable areas for municipal waste disposal. Among the selected sites, one site was highly suitable, two were suitable, and three sites were moderately suitable. These areas with an area of 83.8 km2 are located along the west part of the city adjacent to the Iraqi border. The unsuitable sites for municipal waste disposal were located in the eastern and northeastern areas. Conclusion: However, applying fuzzy-AHP model provides the necessary conditions for assessing effective relationships among discrete criteria. In the end, combining these models and their findings represented advantages of this kind of modeling and improved scoring in all of these pixels.

Affecting Factors of Knowledge-Based Companies Using Fuzzy AHP Model, Case Study Tehran University Enterprise Park

2018 ◽  
Vol 11 (2) ◽  
pp. 574-592 ◽  
Author(s):  
Elham Amini ◽  
Mohammad Baniasadi ◽  
Hossein Vahidi ◽  
Hossein Nematollahi ◽  
Mehrdad Khatami ◽  
...  
Keyword(s):  
Fuzzy Ahp ◽  
Affecting Factors ◽  
Model Case ◽  
Ahp Model ◽  
Knowledge Based
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