Quantifying consumptive water footprints of soybean in rainfed and irrigated systems under climate change scenarios

Remote sensing-based green and blue agricultural water footprint estimation at the river basin scale

基于水足迹理论的煤制油产业布局评价

Water footprint (WF), a comprehensive indicator of water resources appropriation, has evolved as an efficient tool to improve the management and sustainability of water resources. This study quantifies the blue and green WF of major cereals crops in India using high resolution soil and climatic datasets. A comprehensive modelling framework, consisting of Evapotranspiration based Irrigation Requirement (ETIR) tool, was developed for WF assessment. For assessing climate change impact on WF, multi-model ensemble climate change scenarios were generated using the hybrid-delta ensemble method for RCP4.5 and RCP6.0 and future period of 2030s and 2050s. The total WF of the cereal crops are projected to change in the range of − 3.2 to 6.3% under different RCPs in future periods. Although, the national level green and blue WF is projected to change marginally, distinct trends were observed for Kharif (rainy season—June to September) and rabi (winter season—October to February) crops. The blue WF of paddy is likely to decrease by 9.6%, while for wheat it may increase by 4.4% under RCP4.5 during 2050s. The green WF of rabi crops viz. wheat and maize is likely to increase in the range of 20.0 to 24.1% and 9.9 to 16.2%, respectively. This study provides insights into the influences of climate change on future water footprints of crop production and puts forth regional strategies for future water resource management. In view of future variability in the WFs, a water footprint-based optimization for relocation of crop cultivation areas with the aim of minimising the blue water use would be possible management alternative.

<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>

Agriculture accounts for ~90% of India's fresh water use, and there are concerns that future food production will be threatened by insufficient water supply of adequate quality. This study aimed to quantify the water required in the production of diets in India using the water footprint (WF) assessment method. The socio-demographic associations of dietary WFs were explored using mixed effects regression models with a particular focus on blue (irrigation) WF given the importance for Indian agriculture. Dietary data from ~7000 adults living in India were matched to India-specific WF data for food groups to quantify the blue and green (rainfall) WF of typical diets. The mean blue and green WF of diets was 737l/capita/day and 2531l/capita/day, respectively. Vegetables had the lowest WFs per unit mass of product, while roots/tubers had the lowest WFs per unit dietary energy. Poultry products had the greatest blue WFs. Wheat and rice contributed 31% and 19% of the dietary blue WF respectively. Vegetable oils were the highest contributor to dietary green WF. Regional variation in dietary choices meant large differences in dietary blue WFs, whereby northern diets had nearly 1.5 times greater blue WFs than southern diets. Urban diets had a higher blue WF than rural diets, and a higher standard of living was associated with larger dietary blue WFs. This study provides a novel perspective on the WF of diets in India using individual-level dietary data, and demonstrates important variability in WFs due to different food consumption patterns and socio-demographic characteristics. Future dietary shifts towards patterns currently consumed by individuals in higher income groups, would likely increase irrigation requirements putting substantial pressure on India's water resources.

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 improves upon earlier research by taking a high-resolution approach, estimating the water footprint of 126 crops at a 5 by 5 arc minute 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 the 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).

The far-reaching impact of climate change on water resources, particularly its intensification of scarcity, poses a substantial threat to the sustainable management of water in agriculture. To enhance cross-sectoral decision-making at various scales, it is vital to quantify both current and future water consumption, employing methodologies that assess the agricultural water footprint (WF). This study employs the Site-sPecific Agricultural water Requirement and footprint Estimator (SPARE:WATER) to evaluate the susceptibility of green and blue agricultural WF at various scales across Colombia. The assessment is conducted under two CORDEX (Coordinated Regional Climate Downscaling Experiment)-driven climate scenarios, RCP2.6 and RCP8.5. High-resolution (0.22°) CORDEX climate model projections are used to drive the SPARE:WATER model, while historical weather data from fifteen stations (1977-2005) are employed to bias-correct the model's gridded data using the Equal Quantile Matching (EQM) method. This corrected data was spatialized using IDW interpolation. Ten major crops are selected based on their national production significance, based on the National Agricultural Survey. Crop characteristics such as harvested area, yield, and crop coefficients are obtained from local and FAO sources. The analysis focuses on both green and blue WF for the near future (2060) and far future (2099), compared to the present (2020). Preliminary findings underscore a national WF of 45 km3/yr, with important variations at the departmental level. The spatial variability of WF is influenced by both wet and dry years.  Cocoa, coffee, and palm oil emerge as crops with the most substantial WF, showcasing respective water requirements of 30 k m3/t, 18 k m3/t, and 8 k m3/t nationally. Regional variations reveal the significance of crops such as plantain and banana in the agricultural WF landscape. Under the RCP2.6 scenario, the green and blue WF projections for 2060 and 2099 exhibit marginal changes relative to 2020. Conversely, under the RCP8.5 scenario, a discernible increase, particularly in blue WF, is evident, with a surge of 96% by 2099. This trajectory underscores the heightened water requirements anticipated for pivotal crops like cocoa and coffee in the future agricultural landscape. These findings underscore the urgent need for informed water management strategies in the future of Colombian agriculture, particularly in the face of a high-emission scenario. The results of this study can inform policy and decision-making aimed at ensuring sustainable water resources management and food security under the evolving climate landscape.

In the face of increasing water scarcity, reducing the consumptive and degradative water use of crop production is important to produce more food and/or for the environment. The thesis explores the potential for reducing the green, blue and grey water footprint (WF) of irrigated crop production by model-based assessment of different (combinations of) field management practices. First, the effect of management practices on ET and/or nitrogen(N) load to freshwater, and on crop yield are simulated (using AquaCrop or APEX models). The ET is partitioned into its green and blue part by applying a shadow water-balance method, which is developed in the thesis. Then green, blue and grey WF of crop production resulting from different management practices are calculated using the global WF accounting standard. The field management practices considered in this thesis are: four irrigation techniques, four irrigation strategies, three mulching practices, different N-application rates, two forms of nitrogen, and two tillage practices. We analyse various cases, including three crops, four different environments, different hydrologic years (dry to wet), and different soil types. The results show that compared to the reference (furrow and full irrigation without mulching), the maximum reduction in the blue and consumptive WF of crop production can be achieved by practicing drip/subsurface drip with deficit irrigation and synthetic mulching. Reducing the N-application rate will generally result in a higher reduction of the grey WF per tonne than changing the form of N applied, the tillage practice or the irrigation strategy. For reducing both consumptive WF and grey WF per tonne, one can best apply manure-N instead of inorganic-N, and deficit instead of full irrigation. Trade-offs between crop yield, blue and grey WF are likely: increasing the N-application rate to increase the crop yield to its maximum, decreases the blue WF per tonne, and increases the grey WF per tonne. Aiming at cost-effective consumptive WF reduction, application of marginal cost curves shows that, one can best improve the irrigation strategy first, next the mulching practice can best be changed from no mulching to organic mulching, and finally the irrigation technique from furrow or sprinkler to drip irrigation.

Overestimation of water pressure by traditional water footprint: Method revision and application

Indicators on the sustainability of productive human sectors help boosting societal awareness and provide remarkable information for political decision-making and resources management. Prominent examples of relevant environmental indicators currently available are those that form the footprint family. In agriculture, the water footprint approach provides indicators that integrate direct and indirect freshwater usage. While a considerable number of studies developed so far used tabulated values for crop parametrization, the less explored application of dense remote sensing time series provides huge benefits.This paper aims to present the spatiotemporal estimation of the green and blue Remote Sensing-based Agriculture Water Footprint (RS-AWAF) at the Pinios River Basin (11,000 km2) in Greece (year 2017), combining two globally accepted and operational methodologies: the Soil Water Balance published by the Food and Agriculture Organization in its irrigation and drainage paper 56 for water accounting purposes, and the standardized methodology for Agricultural Water Footprint estimation of growing a crop or tree published by the Water Footprint Network. Initially, the RS-AWAF applies dense temporal series of the Normalized Difference Vegetation Index produced by Sentinel-2 data at 10m spatial resolution to monitor the crops provided by local authorities through the Land Parcel Information System and derive the biophysical parameters along its development, such as the basal crop coefficient and the fraction of soil surface covered by vegetation. Those are then integrated into a validated and operational Remote Sensing-based Soil Water Balance that day after day and within a pixel spatial scale, estimates among other components of the balance, the adjusted crop evapotranspiration (ETcadj) and the net irrigation requirements (NIR). In a second step, both previous components are combined to estimate the blue crop water use (CWUblue), related to the NIR, and the green crop water use (CWUgreen), related to the fraction of the ETcadj that comes from other freshwater sources different than irrigation, the precipitation. Finally, crop yield values collected from official statistics per crop or crop group are used to estimate the blue water footprint (WFblue) and the green water footprint (WFgreen).Once the green and blue RS-AWAF is estimated, a collection of thematic maps over the Pinios River Basin is ready for use by local stakeholders at their desired working scale. In that sense, monthly and annual thematic maps of ETcadj, NIR, CWUgreen and CWUblue are available, as well as annual thematic maps of WFblue and WFgreen. In parallel, tabulated values are created from these parameters using zonal statistics through GIS at the spatial scale appropriate to the final user (i.e. water user associations).These results are part of the EU Horizon 2020 project REXUS (Managing Resilient Nexus Systems Through Participatory Systems Dynamics Modelling), in which stakeholders from water user associations to river basin water managers are evaluating the information. At this stage, our final goal is to provide spatiotemporal distributed accounting of agricultural freshwater resources over large areas that enhance regional knowledge and increases efficiency in water management and subsequently contributing to energy-saving, since the major agricultural water volume is abstracted from deep groundwater wells.

Increasing water scarcity places considerable importance on precise quantification of water consumption. The concepts of virtual water content (VWC) and water footprint (WF) are increasingly being used to analyse the water consumption and to support optimal crop and water management practices at different spatial scales. In the present study, the blue, green and grey VWC of crops and WF of crop production within the Gomti river basin (GRB) in India were assessed for irrigated and rainfed conditions. Total WF is the sum of blue, green and grey WFs within the basin. Blue WF is the amount of surface or groundwater used in crop evapotranspiration (ETc), green WF refers to amount of rain water use in ETc, and the grey water use is the volume of freshwater that is required to assimilate the agricultural pollutant load to acceptable levels. On the basis of variability in ETc, the GRB was divided into four spatial resolution units (SRUs). A linear programming model was developed to optimize the area under each crop in different SRUs with the objective function of minimizing the blue WF within the GRB. The findings show that annual WF of crop production within the GRB was 12,196 Mm3, of which 89% was from irrigated agriculture. Wheat, paddy and sugarcane shared 94% of the total WF of crop production within the basin. Share of blue and green WFs in total WF of the basin was 48 and 46%, respectively. There was considerable variation in VWC of crops in different SRUs. The VWC-based optimal allocation of crops would result in savings of 196 Mm3 in blue WF per year. Considering the large WF of crop production, optimizing the crop planting pattern is the key to achieve more sustainable water use within the basin. The approach suggested in this study will be useful in devising informed policy decisions related to crop choices and their cultivation areas so as to ensure efficient use of water resources.

Remote sensing (RS) has long been a useful tool in global and regional applications. The Water Footprint (WF) of a crop is defined as the volume of water consumed for its production, where green and blue WF stand for rain and irrigation water usage. RS provides new tools for global WF assessment and represents an innovative approach to regional and global irrigation mapping, enabling the estimation of green and blue water use. This paper presents an overview of the EU COST Action ES 1106 Assessment of European agriculture water use and trade under climate change (EURO-AGRIWAT), regarding the evaluation of the potential of remote sensing to improve the WF and Virtual Water Trade (VWT) assessment. The main objective is the analysis of the role of satellite data in the suitable models and indices concerned with the analysis of WF and VWT. The main tasks include: an inventory of the existing and near future satellite data records for several European regions that could be used for the WF and VWT assessment; the study of satellite data resolution requirements, in time and space; the analysis of the assimilation of satellite data into models for the determination of green and blue water use; conclusions and recommendations concerning the possibility to integrate remote sensing into WF and VWT accounting. The combination of RS data to assess the volume of irrigation applied, and the green and blue WF faces several limitations with respect to discrepancies in spatial and temporal resolution and data availability, which will be studied.

Abstract. Grey water footprint (WF) reduction is essential given the increasing water pollution associated with food production and the limited assimilation capacity of fresh water. Fertilizer application can contribute significantly to the grey WF as a result of nutrient leaching to groundwater and runoff to streams. The objective of this study is to explore the effect of the nitrogen application rate (from 25 to 300 kg N ha−1), nitrogen form (inorganic N or manure N), tillage practice (conventional or no-tillage) and irrigation strategy (full or deficit irrigation) on the nitrogen load to groundwater and surface water, crop yield and the N-related grey water footprint of crop production by a systematic model-based assessment. As a case study, we consider irrigated maize grown in Spain on loam soil in a semi-arid environment, whereby we simulate the 20-year period 1993–2012. The water and nitrogen balances of the soil and plant growth at the field scale were simulated with the Agricultural Policy Environmental eXtender (APEX) model. As a reference management package, we assume the use of inorganic N (nitrate), conventional tillage and full irrigation. For this reference, the grey WF at a usual N application rate of 300 kg N ha−1 (with crop yield of 11.1 t ha−1) is 1100 m3 t−1, which can be reduced by 91 % towards 95 m3 t−1 when the N application rate is reduced to 50 kg N ha−1 (with a yield of 3.7 t ha−1). The grey WF can be further reduced to 75 m3 t−1 by shifting the management package to manure N and deficit irrigation (with crop yield of 3.5 t ha−1). Although water pollution can thus be reduced dramatically, this comes together with a great yield reduction, and a much lower water productivity (larger green plus blue WF) as well. The overall (green, blue and grey) WF per tonne is found to be minimal at an N application rate of 150 kg N ha−1, with manure, no-tillage and deficit irrigation (with crop yield of 9.3 t ha−1). The paper shows that there is a trade-off between grey WF and crop yield, as well as a trade-off between reducing water pollution (grey WF) and water consumption (green and blue WF). Applying manure instead of inorganic N and deficit instead of full irrigation are measures that reduce both water pollution and water consumption with a 16 % loss in yield.

Mutual impact of salinity and climate change on crop production water footprint in a semi-arid agricultural watershed: Application of SWAT-MODFLOW-Salt

Climate change has an impact on the world of water availability. Water use efficiency important to do especially in the agricultural sector which is one of the largest sectors in water use. Potato cultivation in Pangalengan which continues to grow along with the pricing policies of potatoes as a source of diversification of West Java has the potential to deplete the availability of water in these locations. Amount of consumptive water during the cultivation process needs to be known in order to determine the water management policy. Amount of agricultural consumptive water can be influenced by cultivation methods applied. Approach blue and green water footprint was used to determine the amount of consumptive water usage in the cultivation. Purpose of this study was to calculate the amount of blue and green water footprint of potato on two different methods of cultivation they were semiorganic and conventional methods. The calculation of green water footprint in this study used rainfall water evapotranspiration, whereas value of blue water footprint from irrigation water evapotranspiration. Value of green and blue water footprint of conventional potatoes each was 126 m3 /ton and 24.4 m3 /ton. While the value of green and blue water footprint semi-organic potatoes each were 103.3 m3 /ton and 2.5 m3 /ton. Water used in semi-organic method was more efficient than the conventional method. Semi-organic methods can reduce water consumption directly (blue water) up to 89.75%.