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Arjen Ysbert Hoekstra - One of the best experts on this subject based on the ideXlab platform.
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Water Footprint of Tunisia from an economic perspective
2020Co-Authors: Hatem Chouchane, Martinus S. Krol, Arjen Ysbert Hoekstra, Mesfin MekonnenAbstract:This paper quantifies and analyses the Water Footprint of Tunisia at national and sub-national level, assessing green, Blue and grey Water Footprints for the period 1996–2005. It also assesses economic Water and land productivities related to crop production for irrigated and rain-fed agriculture, and Water scarcity. The Water Footprint of crop production gave the largest contribution (87%) to the total national Water Footprint. At national level, tomatoes and potatoes were the main crops with relatively high economic Water productivity, while olives and barley were the main crops with relatively low productivity. In terms of economic land productivity, oranges had the highest productivity and barley the lowest. South Tunisia had the lowest economic Water and land productivities. Economic land productivity was found to explain more of the current production patterns than economic Water productivity, which may imply opportunities for Water saving. The total Blue Water Footprint of crop production represented 31% of the total renewable Blue Water resources, which means that Tunisia as a whole experienced significant Water scarcity. The Blue Water Footprint on groundWater represented 62% of the total renewable groundWater resources, which means that the country faced severe Water scarcity related to groundWater.
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Water Footprint assessment in North Eastern region of Romania: A case study for Iasi County, Romania
Journal of Environmental Protection and Ecology, 2020Co-Authors: Arjen Ysbert Hoekstra, Mesfin Mekonnen, C. TeodosiuAbstract:Many factors affect the Water consumption pattern such as growing world population, climate changes, industrial and agricultural practices, etc. The present study provides for the first time a year-to-year analysis of Water use for agricultural production, domestic Water supply and industrial production from a hydrological, economical and ecological perspective in the NE region of Romania. Such an assessment can provide information to facilitate an efficient allocation of Water resources to different economic and environmental demands. This assessment is also considering the general economic and social context of the Iasi county as an important area within north-east- ern region of Romania. In the Iasi county, the green component takes the largest share in the total Water Footprint of crops because of the irrigation underdeveloped infrastructure, which makes the agricultural sector vulnerable to dry periods and floods as well. A monthly comparison between the Blue Water Footprint and Blue Water availability shows that Water scarcity varies greatly within the year, but also between years.
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The Water Footprint of Switzerland
2020Co-Authors: A.e. Ercin, Mesfin Mekonnen, Arjen Ysbert HoekstraAbstract:Usually, countries do not consider the external Water Footprint of national consumption, which is related to imported Water-intensive commodities, in their national Water policies. In order to support a broader sort of analysis and better inform decision-making, the traditional production perspective in national Water policy should be supplemented with a consumption perspective. Because many consumer goods are imported, a responsible and fair national Water policy should include an international dimension. This report focusses on Switzerland. The background of the study is the recognition that there is a relation between the import of Water-intensive goods to Switzerland and their impacts on Water systems elsewhere in the world. Many of the goods consumed in Switzerland are not produced domestically, but abroad. Some goods, most in particular agriculture-based products, require a lot of Water during production. These Water-intensive production processes are often accompanied by impacts on the Water systems at the various locations where the production processes take place. The impacts vary from reduced river Water flows, declined lake levels and groundWater tables and increased salt intrusion in coastal areas to pollution of freshWater bodies. The objective of this study is to carry out a Water Footprint assessment for Switzerland from a consumption perspective. The assessment focuses on the analysis of the external Water Footprint of Swiss consumption, to get a complete picture of how national consumption translates to Water use, not only in Switzerland, but also abroad, and to assess Swiss dependency on external Water resources and the sustainability of imports. The study quantifies and maps the external Water Footprint of Switzerland, differentiating between agricultural and industrial commodities, and shows how the Blue Water Footprint of Swiss consumption contributes to Blue Water scarcity in specific river basins and which products are responsible herein. The total Water Footprint of national consumption of Switzerland is an average 11 billion m3 per year for the period 1996-2005, which is 1528 m3 per year or approximately 4120 litre per day per Swiss citizen. About 68% of this total is ‘green’, 25% ‘grey’ and 7% ‘Blue’. Consumption of agricultural commodities makes up the bulk of Switzerland’s Water Footprint, accounting for 81% of the total. Industrial commodities account for 17%; the remaining 2% relates to domestic Water supply. Most of the Water Footprint of Swiss consumption (82%) lies outside Switzerland. About 34% of the Blue Water Footprint of Swiss consumption is in river basins that experience moderate to severe Water scarcity during at least one month in a year. The priority basins are located in France (Garonne, Loire, Escaut and Seine), Italy (Po), Central Asia (Aral Sea basin), the USA (Mississippi), India (Ganges, Krishna, Godavari, Tapti, Mahi, Cauvery and Penner), Pakistan (Indus), Spain (Guadalquivir, Guadiana, and Tejo), Middle East (Tigris and Euphrates), China (Huang He, Yongding He, Mekong, Huai He and Tarim), West Africa (Nile, Tana) and Cote d'Ivoire (Sassandra). Cotton, rice, sugar cane, grape, sorghum, maize, soybean, sunflower, citrus and coffee are identified as priority products, giving significant contributions to the Blue Water scarcity in the selected priority basins. Especially cotton, rice and sugar cane give an important contribution to the Blue Water Footprint in many of these basins.
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the Blue Water Footprint of urban green spaces an example for adelaide australia
Landscape and Urban Planning, 2019Co-Authors: Arjen Ysbert Hoekstra, Hamideh Nouri, Sattar Chavoshi BorujeniAbstract:Abstract The development of ‘greening’ cities introduces an uneasy tension between more green spaces and the increased use of scarce Blue Water resources to maintain this greenness, particularly in dry regions. This paper presents the first estimate of the Blue Water Footprint (WF) of urban greenery. We estimated total Water consumption of a 10-hectare parkland in Adelaide, South Australia. Evapotranspiration of the urban vegetation was estimated by monitoring soil Water inflows, outflows, and storage changes at an experimental site representing different species, microclimates, and plant densities, the most critical parameters affecting Water use. The total WF was estimated at 11,140 m3/ha per year, 59% from Blue Water (irrigation), and 41% from green Water (rainWater), with the highest Water consumption in summer. The dependency on Blue Water resources for maintaining the greenery varied from 49% in October to 67% in March. Even in the wet period of the year, there was a significant Blue WF. Given the lack of Blue Water resources to allocate for further greening the city in an arid environment, we suggest an integrated adaptive management strategy to maintain available greenery and expand green spaces with a minimum of extra pressure on Blue Water resources.
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monthly Blue Water Footprint caps in a river basin to achieve sustainable Water consumption the role of reservoirs
Science of The Total Environment, 2019Co-Authors: Arjen Ysbert Hoekstra, La Zhuo, Pute Wu, Xining ZhaoAbstract:Abstract The Blue Water Footprint (WF) measures the consumption of runoff in a river basin. In order to ensure sustainable Water consumption, setting a monthly Blue WF cap, that is an upper-limit to the Blue WF in a river basin each month, can be a suitable policy instrument. The Blue WF cap in a river basin depends on the precipitation that becomes runoff and the need to maintain a minimum flow for sustaining ecosystems and livelihoods. Reservoirs along the river generally smooth runoff variability and thus raise the WF cap and reduce Blue Water scarcity during the dry season. Previous Water scarcity studies, considering the ratio of actual Blue WF to the Blue WF cap under natural background conditions, have not studied this effect of reservoir storages. Here we assess how Water reservoirs influence Blue WF caps over time and how they affect the variability of Blue Water scarcity in a river basin. We take the Yellow River Basin over the period January 2002–July 2006 as case study and consider data on observed storage changes in five large reservoirs along the main stream. Results indicate that reservoirs redistribute the Blue WF cap and Blue Water scarcity levels over time. Monthly Blue WF caps were generally lowered by reservoir storage during the flood season (July–October) and raised by reservoir releases over the period of highest crop demand (March–June). However, with Water storage exceeding 20% of natural runoff in most rainy months, reservoirs contribute to “scarcity in the wet months”, which is to be understood as a situation in which environmental flow requirements related to the occurrence of natural peak flows are no longer met.
Mesfin Mekonnen - One of the best experts on this subject based on the ideXlab platform.
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Water Footprint of Tunisia from an economic perspective
2020Co-Authors: Hatem Chouchane, Martinus S. Krol, Arjen Ysbert Hoekstra, Mesfin MekonnenAbstract:This paper quantifies and analyses the Water Footprint of Tunisia at national and sub-national level, assessing green, Blue and grey Water Footprints for the period 1996–2005. It also assesses economic Water and land productivities related to crop production for irrigated and rain-fed agriculture, and Water scarcity. The Water Footprint of crop production gave the largest contribution (87%) to the total national Water Footprint. At national level, tomatoes and potatoes were the main crops with relatively high economic Water productivity, while olives and barley were the main crops with relatively low productivity. In terms of economic land productivity, oranges had the highest productivity and barley the lowest. South Tunisia had the lowest economic Water and land productivities. Economic land productivity was found to explain more of the current production patterns than economic Water productivity, which may imply opportunities for Water saving. The total Blue Water Footprint of crop production represented 31% of the total renewable Blue Water resources, which means that Tunisia as a whole experienced significant Water scarcity. The Blue Water Footprint on groundWater represented 62% of the total renewable groundWater resources, which means that the country faced severe Water scarcity related to groundWater.
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The Water Footprint of Switzerland
2020Co-Authors: A.e. Ercin, Mesfin Mekonnen, Arjen Ysbert HoekstraAbstract:Usually, countries do not consider the external Water Footprint of national consumption, which is related to imported Water-intensive commodities, in their national Water policies. In order to support a broader sort of analysis and better inform decision-making, the traditional production perspective in national Water policy should be supplemented with a consumption perspective. Because many consumer goods are imported, a responsible and fair national Water policy should include an international dimension. This report focusses on Switzerland. The background of the study is the recognition that there is a relation between the import of Water-intensive goods to Switzerland and their impacts on Water systems elsewhere in the world. Many of the goods consumed in Switzerland are not produced domestically, but abroad. Some goods, most in particular agriculture-based products, require a lot of Water during production. These Water-intensive production processes are often accompanied by impacts on the Water systems at the various locations where the production processes take place. The impacts vary from reduced river Water flows, declined lake levels and groundWater tables and increased salt intrusion in coastal areas to pollution of freshWater bodies. The objective of this study is to carry out a Water Footprint assessment for Switzerland from a consumption perspective. The assessment focuses on the analysis of the external Water Footprint of Swiss consumption, to get a complete picture of how national consumption translates to Water use, not only in Switzerland, but also abroad, and to assess Swiss dependency on external Water resources and the sustainability of imports. The study quantifies and maps the external Water Footprint of Switzerland, differentiating between agricultural and industrial commodities, and shows how the Blue Water Footprint of Swiss consumption contributes to Blue Water scarcity in specific river basins and which products are responsible herein. The total Water Footprint of national consumption of Switzerland is an average 11 billion m3 per year for the period 1996-2005, which is 1528 m3 per year or approximately 4120 litre per day per Swiss citizen. About 68% of this total is ‘green’, 25% ‘grey’ and 7% ‘Blue’. Consumption of agricultural commodities makes up the bulk of Switzerland’s Water Footprint, accounting for 81% of the total. Industrial commodities account for 17%; the remaining 2% relates to domestic Water supply. Most of the Water Footprint of Swiss consumption (82%) lies outside Switzerland. About 34% of the Blue Water Footprint of Swiss consumption is in river basins that experience moderate to severe Water scarcity during at least one month in a year. The priority basins are located in France (Garonne, Loire, Escaut and Seine), Italy (Po), Central Asia (Aral Sea basin), the USA (Mississippi), India (Ganges, Krishna, Godavari, Tapti, Mahi, Cauvery and Penner), Pakistan (Indus), Spain (Guadalquivir, Guadiana, and Tejo), Middle East (Tigris and Euphrates), China (Huang He, Yongding He, Mekong, Huai He and Tarim), West Africa (Nile, Tana) and Cote d'Ivoire (Sassandra). Cotton, rice, sugar cane, grape, sorghum, maize, soybean, sunflower, citrus and coffee are identified as priority products, giving significant contributions to the Blue Water scarcity in the selected priority basins. Especially cotton, rice and sugar cane give an important contribution to the Blue Water Footprint in many of these basins.
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Water Footprint assessment in North Eastern region of Romania: A case study for Iasi County, Romania
Journal of Environmental Protection and Ecology, 2020Co-Authors: Arjen Ysbert Hoekstra, Mesfin Mekonnen, C. TeodosiuAbstract:Many factors affect the Water consumption pattern such as growing world population, climate changes, industrial and agricultural practices, etc. The present study provides for the first time a year-to-year analysis of Water use for agricultural production, domestic Water supply and industrial production from a hydrological, economical and ecological perspective in the NE region of Romania. Such an assessment can provide information to facilitate an efficient allocation of Water resources to different economic and environmental demands. This assessment is also considering the general economic and social context of the Iasi county as an important area within north-east- ern region of Romania. In the Iasi county, the green component takes the largest share in the total Water Footprint of crops because of the irrigation underdeveloped infrastructure, which makes the agricultural sector vulnerable to dry periods and floods as well. A monthly comparison between the Blue Water Footprint and Blue Water availability shows that Water scarcity varies greatly within the year, but also between years.
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The Water Footprint of Tunisia from an economic perspective
Ecological Indicators, 2015Co-Authors: Hatem Chouchane, Martinus S. Krol, Arjen Ysbert Hoekstra, Mesfin MekonnenAbstract:This paper quantifies and analyses the Water Footprint of Tunisia at national and sub-national level, assessing green, Blue and grey Water Footprints for the period 1996–2005. It also assesses economic Water and land productivities related to crop production for irrigated and rain-fed agriculture, and Water scarcity. The Water Footprint of crop production gave the largest contribution (87%) to the total national Water Footprint. At national level, tomatoes and potatoes were the main crops with relatively high economic Water productivity, while olives and barley were the main crops with relatively low productivity. In terms of economic land productivity, oranges had the highest productivity and barley the lowest. South Tunisia had the lowest economic Water and land productivities. Economic land productivity was found to explain more of the current production patterns than economic Water productivity, which may imply opportunities for Water saving. The total Blue Water Footprint of crop production represented 31% of the total renewable Blue Water resources, which means that Tunisia as a whole experienced significant Water scarcity. The Blue Water Footprint on groundWater represented 62% of the total renewable groundWater resources, which means that the country faced severe Water scarcity related to groundWater.
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Sensitivity and uncertainty in crop Water Footprint accounting: A case study for the Yellow River Basin
Hydrology and Earth System Sciences, 2014Co-Authors: La Zhuo, Mesfin Mekonnen, Arjen Ysbert HoekstraAbstract: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 and Blue 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 arc minute 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/ton) from 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 changes in the 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.
A. D. Chukalla - One of the best experts on this subject based on the ideXlab platform.
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trade off between Blue and grey Water Footprint of crop production at different nitrogen application rates under various field management practices
Science of The Total Environment, 2018Co-Authors: A. D. Chukalla, Martinus S. Krol, Arjen Ysbert HoekstraAbstract:Abstract In irrigated crop production, nitrogen (N) is often applied at high rates in order to maximize crop yield. With such high rates, the Blue Water Footprint (WF) per unit of crop is low, but the N-related grey WF per unit of crop yield is relatively high. This study explores the trade-off between Blue and grey WF at different N-application rates (from 25 to 300 kg N ha−1 y−1) under various field management practices. We first analyse this trade-off under a reference management package (applying inorganic-N, conventional tillage, full irrigation). Next, we estimate the economically optimal N-application rate when putting a price to pollution. Finally, we consider the Blue-grey WF trade-off for other management packages, a combination of inorganic-N or organic-N with conventional tillage or no-tillage, and full or deficit irrigation. We use the APEX model to simulate soil Water and N balances and crop growth. As a case study, we consider irrigated maize on loam soil for the period 1998–2012 in a semi-arid environment in Spain. The results for the reference package show that increasing N application from 50 to 200 kg N ha−1, with crop yield growing by a factor 3, involves a trade-off, whereby the Blue WF per tonne declines by 60% but the N-related grey WF increases by 210%. Increasing N application from 25 to 50 kg N ha−1, with yield increasing by a factor 2, is a no-regret move, because Blue and grey WFs per tonne are reduced by 40% and 8%, respectively. Decreasing N application from 300 to 200 kg N ha−1 is a no-regret move as well. The minimum Blue WF per tonne is found at N application of 200 kg N ha−1, with a price of 8 $ kg−1 of N load to Water pollution the economically optimal N-application rate is 150 kg N ha−1.
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green and Blue Water Footprint reduction in irrigated agriculture effect of irrigation techniques irrigation strategies and mulching
Hydrology and Earth System Sciences, 2015Co-Authors: A. D. Chukalla, Martinus S. Krol, Arjen Ysbert HoekstraAbstract:Consumptive Water Footprint (WF) reduction in irrigated crop production is essential given the increasing competition for freshWater. This study explores the effect of three management practices on the soil Water balance and plant growth, specifically on evapotranspiration (ET) and yield (Y) and thus the consumptive WF of crops (ET / Y). The management practices are four irrigation techniques (furrow, sprinkler, drip and subsurface drip (SSD)), four irrigation strategies (full (FI), deficit (DI), supplementary (SI) and no irrigation), and three mulching practices (no mulching, organic (OML) and synthetic (SML) mulching). Various cases were considered: arid, semi-arid, sub-humid and humid environments in Israel, Spain, Italy and the UK, respectively; wet, normal and dry years; three soil types (sand, sandy loam and silty clay loam); and three crops (maize, potato and tomato). The AquaCrop model and the global WF accounting standard were used to relate the management practices to effects on ET, Y and WF. For each management practice, the associated green, Blue and total consumptive WF were compared to the reference case (furrow irrigation, full irrigation, no mulching). The average reduction in the consumptive WF is 8–10 % if we change from the reference to drip or SSD, 13 % when changing to OML, 17–18 % when moving to drip or SSD in combination with OML, and 28 % for drip or SSD in combination with SML. All before-mentioned reductions increase by one or a few per cent when moving from full to deficit irrigation. Reduction in overall consumptive WF always goes together with an increasing ratio of green to Blue WF. The WF of growing a crop for a particular environment is smallest under DI, followed by FI, SI and rain-fed. Growing crops with sprinkler irrigation has the largest consumptive WF, followed by furrow, drip and SSD. Furrow irrigation has a smaller consumptive WF compared with sprinkler, even though the classical measure of "irrigation efficiency" for furrow is lower.
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Green and Blue Water Footprint reduction in irrigated agriculture: Effect of irrigation techniques, irrigation strategies and mulching
Hydrology and Earth System Sciences, 2015Co-Authors: A. D. Chukalla, Martinus S. Krol, Arjen Ysbert HoekstraAbstract:Consumptive Water Footprint (WF) reduction in irrigated crop production is essential given the increasing competition for fresh Water. This study explores the effect of three management practices on the soil Water balance and plant growth, specifically on evapotranspiration (ET) and yield (Y) and thus the consumptive WF of crops (ET/Y). The management practices are: four irrigation techniques (furrow, sprinkler, drip and subsurface drip (SSD)); four irrigation strategies (full (FI), deficit (DI), supplementary (SI) and no irrigation); and three mulching practices (no mulching, organic (OML) and synthetic (SML) mulching). Various cases were considered: arid, semi-arid, sub-humid and humid environments; wet, normal and dry years; three soil types; and three crops. The AquaCrop model and the global WF accounting standard were used to relate the management practices to effects on ET, Y and WF. For each management practice, the associated green, Blue and total consumptive WF were compared to the reference case (furrow irrigation, full irrigation, no mulching). The average reduction in the consumptive WF is: 8–10 % if we change from the reference to drip or SSD; 13 % when changing to OML; 17–18 % when moving to drip or SSD in combination with OML; and 28 % for drip or SSD in combination with SML. All before-mentioned reductions increase by one or a few per cent when moving from full to deficit irrigation. Reduction in overall consumptive WF always goes together with an increasing ratio of green to Blue WF. The WF of growing a crop for a particular environment is smallest under DI, followed by FI, SI and rain-fed. Growing crops with sprinkler irrigation has the largest consumptive WF, followed by furrow, drip and SSD. Furrow irrigation has a smaller consumptive WF compared with sprinkler, even though the classical measure of "irrigation efficiency" for furrow is lower.
Pute Wu - One of the best experts on this subject based on the ideXlab platform.
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monthly Blue Water Footprint caps in a river basin to achieve sustainable Water consumption the role of reservoirs
Science of The Total Environment, 2019Co-Authors: Arjen Ysbert Hoekstra, La Zhuo, Pute Wu, Xining ZhaoAbstract:Abstract The Blue Water Footprint (WF) measures the consumption of runoff in a river basin. In order to ensure sustainable Water consumption, setting a monthly Blue WF cap, that is an upper-limit to the Blue WF in a river basin each month, can be a suitable policy instrument. The Blue WF cap in a river basin depends on the precipitation that becomes runoff and the need to maintain a minimum flow for sustaining ecosystems and livelihoods. Reservoirs along the river generally smooth runoff variability and thus raise the WF cap and reduce Blue Water scarcity during the dry season. Previous Water scarcity studies, considering the ratio of actual Blue WF to the Blue WF cap under natural background conditions, have not studied this effect of reservoir storages. Here we assess how Water reservoirs influence Blue WF caps over time and how they affect the variability of Blue Water scarcity in a river basin. We take the Yellow River Basin over the period January 2002–July 2006 as case study and consider data on observed storage changes in five large reservoirs along the main stream. Results indicate that reservoirs redistribute the Blue WF cap and Blue Water scarcity levels over time. Monthly Blue WF caps were generally lowered by reservoir storage during the flood season (July–October) and raised by reservoir releases over the period of highest crop demand (March–June). However, with Water storage exceeding 20% of natural runoff in most rainy months, reservoirs contribute to “scarcity in the wet months”, which is to be understood as a situation in which environmental flow requirements related to the occurrence of natural peak flows are no longer met.
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assessing Blue and green Water utilisation in wheat production of china from the perspectives of Water Footprint and total Water use
Hydrology and Earth System Sciences, 2014Co-Authors: Pute Wu, Yubao Wang, X N ZhaoAbstract:The aim of this study is to estimate the green and Blue Water Footprint (WF) and the total Water use (TWU) of wheat crop in China in both irrigated and rainfed productions. Crop evapotranspiration and Water evaporation loss are both considered when calculating the Water Footprint in irrigated fields. We compared the Water use for per-unit product between irrigated and rainfed crops and analyzed the relationship between promoting the yield and conserving Water resources. The national total and per-unit-product WF of wheat production in 2010 were approximately 111.5 Gm 3 (64.2% green and 35.8% Blue) and 0.968 m 3 kg −1 , respectively. There is a large difference in the Water Footprint of the per-kilogram wheat product (WFP) among different provinces: the WFP is low in the provinces in and around the Huang–Huai–Hai Plain, while it is relatively high in the provinces south of the Yangtze River and in northwestern China. The major portion of WF (80.9%) comes from irrigated farmland, and the remaining 19.1% is rainfed. Green Water dominates the area south of the Yangtze River, whereas low green Water proportions are found in the provinces located in northern China, especially northwestern China. The national TWU and total Water use of the per-kilogram wheat product (TWUP) are 142.5 Gm 3 and 1.237 m 3 kg −1 , respectively, containing approximately 21.7% Blue Water percolation (BW p ). The values of WFP for irrigated (WFP I ) and rainfed (WFP R ) crops are 0.911 and 1.202 m 3 kg −1 , respectively. Irrigation plays an important role in food production, promoting the wheat yield by 170% and reducing the WFP by 24% compared to those of rainfed wheat production. Due to the low irrigation efficiency, more Water is needed per kilogram in irrigated farmland in many arid regions, such as the Xinjiang, Ningxia and Gansu Provinces. We divided the 30 provinces of China into three categories according to the relationship between the TWUP I (TWU for per-unit product in irrigated farmland) and TWUP R (TWU for per-unit product in rainfed farmland): (I) TWUP I R , (II) TWUP I = TWUP R , and (III) TWUP I > TWUP R . Category II, which contains the major wheat-producing areas in the North China Plain, produces nearly 75% of the wheat of China. The double benefits of conserving Water and promoting production can be achieved by irrigating wheat in Category I provinces. Nevertheless, the provinces in this category produce only 1.1% of the national wheat yield.
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Water Footprint of Grain Product in Irrigated Farmland of China
Water Resources Management, 2014Co-Authors: Pute Wu, Yubao Wang, Xining ZhaoAbstract:China faces the dual challenge of grain production pressure and Water scarcity. It is significant to reduce Water Footprint of grain product (WFGP, m 3 /t) in irrigated farmland. The focus of grain production and agricultural Water use, and the precondition is to determine the WFGP and its composition. This paper estimates the WFGP in irrigated farmland of 31 provinces (including municipalities, autonomous regions) a by collecting actual data of 443 typical irrigation districts in 1998, 2005 and 2010, and analyses its temporal and spatial variation in irrigated farmland of China. The result shows that the WFGP in each province decreases with time except in Jiangxi and Hunan, and the average value of all provinces reduced from 1494 m 3 /t in 1998 to 1243 m 3 /t in 2010. The WFGP decreases faster in more developed municipal cities and major grain production provinces. The annual average WFGP in irrigated farmland is 1339 m 3 /t and the Blue and green Water account for 63.5 % and 36.5 % of the total, respectively. The WFGP and its composition are significantly different between provinces. Generally, provinces distributed inside and beyond Huang-Huai-Hai Plain, have a higher Water productivity, lower WFGP and Blue Water Footprint of grain product, while most provinces located in northwest, northeast, southeast and south China have a higher WFGP and lower proportion of green Water in the WFGP as a whole. Portion of the Blue Water Footprint (BWFGP) is not consumed for crop evapotranspiration (BWFGP ET ) but conveyance loss (BWFGP cl ). The national averaged BWFGP cl decreases with time and but still remains up to 466 m 3 /t in 2010, making up 34.8 % of the WFGP. In order to safeguard grain security and ease the Water resource pressure, the Chinese government should increase investment and apply advanced technology for developing Water-saving agriculture, improve the efficiency of Water use and further reduce the WFGP. Considering also the contribution of grain output and the relatively high WFGP, the government should give priority to developing Water-saving agriculture in the Northeast of China. Copyright Springer Science+Business Media Dordrecht 2014
La Zhuo - One of the best experts on this subject based on the ideXlab platform.
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monthly Blue Water Footprint caps in a river basin to achieve sustainable Water consumption the role of reservoirs
Science of The Total Environment, 2019Co-Authors: Arjen Ysbert Hoekstra, La Zhuo, Pute Wu, Xining ZhaoAbstract:Abstract The Blue Water Footprint (WF) measures the consumption of runoff in a river basin. In order to ensure sustainable Water consumption, setting a monthly Blue WF cap, that is an upper-limit to the Blue WF in a river basin each month, can be a suitable policy instrument. The Blue WF cap in a river basin depends on the precipitation that becomes runoff and the need to maintain a minimum flow for sustaining ecosystems and livelihoods. Reservoirs along the river generally smooth runoff variability and thus raise the WF cap and reduce Blue Water scarcity during the dry season. Previous Water scarcity studies, considering the ratio of actual Blue WF to the Blue WF cap under natural background conditions, have not studied this effect of reservoir storages. Here we assess how Water reservoirs influence Blue WF caps over time and how they affect the variability of Blue Water scarcity in a river basin. We take the Yellow River Basin over the period January 2002–July 2006 as case study and consider data on observed storage changes in five large reservoirs along the main stream. Results indicate that reservoirs redistribute the Blue WF cap and Blue Water scarcity levels over time. Monthly Blue WF caps were generally lowered by reservoir storage during the flood season (July–October) and raised by reservoir releases over the period of highest crop demand (March–June). However, with Water storage exceeding 20% of natural runoff in most rainy months, reservoirs contribute to “scarcity in the wet months”, which is to be understood as a situation in which environmental flow requirements related to the occurrence of natural peak flows are no longer met.
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Sensitivity and uncertainty in crop Water Footprint accounting: A case study for the Yellow River Basin
Hydrology and Earth System Sciences, 2014Co-Authors: La Zhuo, Mesfin Mekonnen, Arjen Ysbert HoekstraAbstract: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 and Blue 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 arc minute 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/ton) from 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 changes in the 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.
