scholarly journals Prediction of Blue Water Footprint Accounting for Water Treatment Plants in Kuantan River Basin

2018 ◽  
Vol 7 (4.35) ◽  
pp. 286 ◽  
Author(s):  
Syazwan N. Moni ◽  
Edriyana A. Aziz ◽  
M. A. Malek ◽  
Nadiah Mokhtar ◽  
Amirul A. Borhan
Keyword(s):  
Water Treatment ◽  
River Basin ◽  
Water Consumption ◽  
Historical Data ◽  
Water Footprint ◽  
Water Source ◽  
Blue Water ◽  
Water Treatment Plants ◽  
The Future ◽  
Backpropagation Method

Water treatment plants (WTPs) in Kuantan river basin abstracts water from the blue water source, which is the Kuantan river. Therefore, by accounting the blue water footprint (WFb), the overall water consumption for all five WTPs  namely; Sungai Lembing, Bukit Sagu, Panching, Semambu, and Bukit Ubi can be obtained. In order to predict the value, Backpropagation method is the best method to be used due to the historical data obtained from the WFb accounting for all five WTPs above. The objective of this study is to predict the overall blue water consumption for water treatment plants located along Kuantan river basin using Backpropagation method in artificial neural network. In this study, WFb has been accounted throughout all water treatment plants by using reference from water footprint manual. Then, the WFb will undergo a series of testing using application in MATLAB software in order to predict the future value based on historical data from 2015 until 2016. As a result, the total WFb accounting obtained was 190,543,378.2 m3/day, while the total maximum capacity of the WTPs was 189,654,000 m3/day. Hence, the prediction value that kept increasing will not be able to cater the future demand due to unstoppable urbanization.

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 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 Water Footprint Assessment and Water-Energy-Food Nexus for Domestic and Institutional Sectors in Klang Valley, Malaysia: a Review

2018 ◽  
Vol 7 (4.35) ◽  
pp. 244
Author(s):  
Nurul Azmah Safie ◽  
M.A. Malek ◽  
Z. Z. Noor
Keyword(s):  
Water Consumption ◽  
Water Availability ◽  
Water Footprint ◽  
Green Water ◽  
World Population ◽  
Blue Water ◽  
Water Production ◽  
Kuala Lumpur ◽  
Reliable Technique ◽  
Klang Valley

Change in climate, increasing world population and industrialization have placed considerable stress on water availability at certain places. Water Footprint accounting is a reliable technique that can be used for a better water management. This study focuses on establishing a doable methodology on water footprint accounting and assessment for direct water consumption from domestic and institutional sectors located in an urbanized environment such as Klang Valley, Kuala Lumpur. It includes investigation of Water Footprint at domestic household, schools, colleges, terminals and offices in Klang Valley. The value of water consumption, water production and water pollution will be determined using Hoekstra’s approach for green water, blue water and grey water. In addition, findings from this study will be linked to two other elements namely energy and food. This link is named as Water-Energy-Food Nexus. This study will establish the quantity and criteria of Water-Energy-Food Nexus specifically tailored to domestic and institutional sectors in Klang Valley.

scholarly journals Sensitivity and uncertainty in crop water footprint accounting: a case study for the Yellow River Basin

2014 ◽  
Vol 11 (1) ◽  
pp. 135-167 ◽  
Author(s):  
L. Zhuo ◽  
M. M. Mekonnen ◽  
A. Y. Hoekstra
Keyword(s):  
River Basin ◽  
Water Footprint ◽  
Yellow River ◽  
Yellow River Basin ◽  
The Yellow River ◽  
Blue Water ◽  
Total Water ◽  
Crop Water ◽  
Input Variables ◽  
The Yellow River Basin

Abstract. Water Footprint Assessment is a quickly growing field of research, but as yet little attention has been paid to the uncertainties involved. This study investigates the sensitivity of water footprint estimates to changes in important input variables and quantifies the size of uncertainty in water footprint estimates. The study focuses on the green (from rainfall) and blue (from irrigation) water footprint of producing maize, soybean, rice, and wheat in the Yellow River Basin in the period 1996–2005. A grid-based daily water balance model at a 5 by 5 arcmin resolution was applied to compute green and blue water footprints of the four crops in the Yellow River Basin in the period considered. The sensitivity and uncertainty analysis focused on the effects on water footprint estimates at basin level (in m3 t−1) of four key input variables: precipitation (PR), reference evapotranspiration (ET0), crop coefficient (Kc), and crop calendar. The one-at-a-time method was carried out to analyse the sensitivity of the water footprint of crops to fractional changes of individual input variables. Uncertainties in crop water footprint estimates were quantified through Monte Carlo simulations. The results show that the water footprint of crops is most sensitive to ET0 and Kc, followed by crop calendar and PR. Blue water footprints were more sensitive to input variability than green water footprints. The smaller the annual blue water footprint, the higher its sensitivity to changes in PR, ET0, and Kc. The uncertainties in the total water footprint of a crop due to combined uncertainties in climatic inputs (PR and ET0) were about ±20% (at 95% confidence interval). The effect of uncertainties in ET0 was dominant compared to that of precipitation. The uncertainties in the total water footprint of a crop as a result of combined key input uncertainties were on average ±26% (at 95% confidence level). The sensitivities and uncertainties differ across crop types, with highest sensitivities and uncertainties for soybean.

scholarly journals Cumulative Environmental Effects of Hydropower Stations Based on the Water Footprint Method—Yalong River Basin, China

2019 ◽  
Vol 11 (21) ◽  
pp. 5958 ◽  
Author(s):  
Yu ◽  
Jia ◽  
Wu ◽  
Wu ◽  
Xu ◽  
...  
Keyword(s):  
River Basin ◽  
Environmental Effects ◽  
Water Scarcity ◽  
Water Footprint ◽  
Environmental Flow ◽  
Blue Water ◽  
Development And Utilization ◽  
Hydropower Stations ◽  
Yalong River ◽  
Yalong River Basin

The construction of hydropower stations is not without controversy as they have a certain degree of impact on the ecological environment. Moreover, the water footprint and its cumulative effects on the environment (The relationship between the degree of hydropower development and utilization in the basin and the environment) of the development and utilization of cascade hydropower stations are incompletely understood. In this paper, we calculate the evaporated water footprint (EWF, water evaporated from reservoirs) and the product water footprint of hydropower stations (PWF, water consumption per unit of electricity production), and the blue water scarcity (BWS, the ratio of the total blue water footprint to blue water availability) based on data from 19 selected hydropower stations in the Yalong River Basin, China. Results show that: (a) the EWFs in established, ongoing, proposed, and planning phases of 19 hydropower stations are 243, 123, 59, and 42 Mm3, respectively; (b) the PWF of 19 hydropower stations varies between 0.01 and 4.49 m3GJ−1, and the average PWF is 1.20 m3GJ−1. These values are quite small when compared with hydropower stations in other basins in the world, and the difference in PWF among different hydropower stations is mainly derived from energy efficiency factor; (c) all the BWS in the Yalong River Basin are below 100% (low blue water scarcity), in which the total blue water footprint is less than 20% of the natural flow, and environmental flow requirements are met. From the perspective of the water footprint method, the cumulative environmental effects of hydropower development and utilization in the Yalong River Basin will not affect the local environmental flow requirements.

Assessment of Water Footprint for Koshi River Basin (KRB), Nepal

2020 ◽  
Author(s):  
Raj Deva Singh ◽  
Kumar Ghimire ◽  
Ashish Pandey
Keyword(s):  
River Basin ◽  
Water Use ◽  
Crop Production ◽  
Agricultural Land ◽  
Water Footprint ◽  
Green Water ◽  
Blue Water ◽  
Total Water ◽  
Green And Blue Water ◽  
Koshi River Basin

<p>Nepal is an agrarian country and almost one-third of Gross Domestic Product (GDP) is dependent on agricultural sector. Koshi river basin is the largest basin in the country and serves large share on agricultural production. Like another country, Nepalese agriculture holds largest water use in agriculture. In this context, it is necessary to reduce water use pressure. In this study, water footprint of different crop (rice, maize, wheat, millet, sugarcane, potato and barley) have been estimated for the year 2005 -2014 to get the average water footprint of crop production during study period. CROPWAT model, developed by Food and Agriculture Organization (FAO 2010b).</p><p>For the computation of the green and blue water footprints, estimated values of ET (the output of CROPWAT model) and yield (derived from statistical data) are utilised. Blue and green water footprint are computed for different districts (16 districts within KRB) / for KRB in different years (10 years from 2005 to 2014) and crops (considered 7 local crops). The water footprint of crops production for any district or basin represents the average of WF production of seven crops in the respective district or basin.</p><p>The study provides a picture of green and blue water use in crop production in the field and reduction in the water footprint of crop production by selecting suitable crops at different places in the field. The Crop, that has lower water footprint, can be intensified at that location and the crops, having higher water footprint, can be discontinued for production or measure for water saving technique needs to be implemented reducing evapotranspiration. The water footprint of agriculture crop production can be reduced by increasing the yield of the crops. Some measures like use of an improved variety of seed, fertilizer, mechanized farming and soil moisture conservation technology may also be used to increase the crop yields.</p><p>The crop harvested areas include both rainfed as well as irrigated land. Agricultural land occupies 22% of the study area, out of which 94% areas are rainfed whereas remaining 6% areas are under irrigation. The study shows 98% of total water use in crop production is due to green water use (received from rainfall) and remaining 2 % is due to blue water use received from irrigation (surface and ground water as source). Potato has 22% blue water proportion and contributes 85% share to the total blue water use in the basin. Maize and rice together hold 77% share of total water use in crops production. The average annual water footprint of crop production in KRB is 1248 cubic meter/ton having the variation of 9% during the period of 2005-2014. Sunsari, Dhankuta districts have lower water footprint of crop production. The coefficient of variation of water footprint of millet crop production is lower as compared to those of other crops considered for study whereas sugarcane has a higher variation of water footprint for its production.</p>

scholarly journals Estimating the Blue Water Footprint of In-Field Crop Losses: A Case Study of U.S. Potato Cultivation

2018 ◽  
Vol 10 (8) ◽  
pp. 2854 ◽  
Author(s):  
Edward Spang ◽  
Bret Stevens
Keyword(s):  
Water Consumption ◽  
Water Footprint ◽  
National Level ◽  
Potato Production ◽  
The United States ◽  
Data Sets ◽  
United States Department ◽  
Blue Water ◽  
Field Crop ◽  
Crop Losses

Given the high proportion of water consumption for agriculture, as well as the relatively common occurrence of crop losses in the field, we estimate the amount of water embedded in crops left on the farm. We are particularly interested in understanding losses associated with fruits and vegetables, having a higher level of harvesting selectivity and perishability (and thus, losses) than grain crops. We further refined the study to focus on potatoes, as they represent the largest acreage under cultivation of all fruit and vegetable crops in the U.S. We attempt to get the most complete understanding of pre-harvest and harvest loss data for potatoes by leveraging three centralized data sets collected and managed by the United States Department of Agriculture (USDA). By integrating these three distinct data sets for the five-year period 2012–2016, we are able to estimate water consumption for potato cultivation for total in-field losses by production stage and driver of loss for seven major potato-producing states (representing 77% of total U.S. potato production). Our results suggest that 3.6%–17.9% of potatoes are lost in the field with a total estimated blue water footprint of approximately 84.6 million cubic meters. We also find that the leading driver for crop loss for in-field potato production is harvest sorting and grading, accounting for 84% of total lost production at the farm. We conclude with a discussion of opportunities for improved national level data collection to provide a better understanding of in-field crop losses over time and the resource footprints of these losses.

scholarly journals Understanding the Spatial-Temporal Changes of Oasis Farmland in the Tarim River Basin from the Perspective of Agricultural Water Footprint

Water ◽  
2021 ◽  
Vol 13 (5) ◽  
pp. 696
Author(s):  
Aihua Long ◽  
Jiawen Yu ◽  
Xiaoya Deng ◽  
Xinlin He ◽  
Haifeng Gao ◽  
...  
Keyword(s):  
River Basin ◽  
Crop Production ◽  
Water Footprint ◽  
Tarim River ◽  
Tarim River Basin ◽  
Blue Water ◽  
Agricultural Water ◽  
The Tarim River ◽  
Production Water ◽  
The Tarim River Basin

The Tarim River Basin in China has predominantly assumed the task of commodity cotton and other high water-intensive crop production in recent years. The spatial matching status of agricultural water and land resources is a prerequisite for local economic development. This paper provides an insight into the spatiotemporal variation trends of agricultural production water footprint and oasis farmland in the Tarim River Basin. The degree of spatial mismatching between oasis farmland and crop production water footprints studied in this paper found how the crop water footprint affected the change in oasis farmland area by sensitivity analysis. Time series data covering the period of 1990–2015 were used for the study. The results showed that the annual variation of crop production water footprint and oasis farmland area have experienced upward trends in Tarim River Basin. The blue water makes the largest contribution to the components of the crop production water footprint in each district (all exceeded 77%). The crop production water footprint and oasis farmland area tend to aggregate towards the eastern region. The level of spatial mismatch between the blue water footprint and farmland area fluctuated during the study period, but it was gradually remedied after 2000, while the spatial mismatch between green water footprint and farmland area gradually worsened. The number of districts with mid and high sensitivity to changes in blue water footprint continuously increased during 1990–2005, which revealed that the change in blue water footprint has an increasing influence on oasis farmland. The results can provide operable recommendations for efficient use of water resources, maintaining oasis suitable farmland scale and agricultural sustainable development in the Tarim River Basin.

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