Benchmark levels for the consumptive water footprint of crop production for different environmental conditions: a case study for winter wheat in China

Abstract

Abstract. Meeting growing food demands while simultaneously shrinking the water footprint (WF) of agricultural production is one of the greatest societal challenges. Benchmarks for the WF of crop production can serve as a reference and be helpful in setting WF reduction targets. The consumptive WF of crops, the consumption of rainwater stored in the soil (green WF), and the consumption of irrigation water (blue WF) over the crop growing period varies spatially and temporally depending on environmental factors like climate and soil. The study explores which environmental factors should be distinguished when determining benchmark levels for the consumptive WF of crops. Hereto we determine benchmark levels for the consumptive WF of winter wheat production in China for all separate years in the period 1961-2008, for rain-fed vs. irrigated croplands, for wet vs. dry years, for warm vs. cold years, for four different soil classes, and for two different climate zones. We simulate consumptive WFs of winter wheat production with the crop water productivity model AquaCrop at a 5 by 5 arcmin resolution, accounting for water stress only. The results show that (i) benchmark levels determined for individual years for the country as a whole remain within a range of ±20 % around long-term mean levels over 1961-2008, (ii) the WF benchmarks for irrigated winter wheat are 8-10 % larger than those for rain-fed winter wheat, (iii) WF benchmarks for wet years are 1-3 % smaller than for dry years, (iv) WF benchmarks for warm years are 7-8 % smaller than for cold years, (v) WF benchmarks differ by about 10-12 % across different soil texture classes, and (vi) WF benchmarks for the humid zone are 26-31 % smaller than for the arid zone, which has relatively higher reference evapotranspiration in general and lower yields in rain-fed fields. We conclude that when determining benchmark levels for the consumptive WF of a crop, it is useful to primarily distinguish between different climate zones. If actual consumptive WFs of winter wheat throughout China were reduced to the benchmark levels set by the best 25 % of Chinese winter wheat production (1224 m 3 t −1 for arid areas and 841 m 3 t −1 for humid areas), the water saving in an average year would be 53 % of the current water consumption at winter wheat fields in China. The majority of the yield increase and associated improvement in water productivity can be achieved in southern China.

Water Footprints and ‘Pozas’: Conversations about Practices and Knowledges of Water Efficiency

“…In recent years, WF studies have emphasized the role of place and time in determining water footprints, arguing that basin caps and water footprint benchmarks are context-specific [13,44]. With growing databases, improved special resolution, and advanced computer models, attempts are made to capture local natural conditions, such as climate variability and soil characteristics, in global assessments [39].…”

Water Footprint Assessment: Evolvement of a New Research Field

“…Besides, a WF benchmark for a certain type of production provides governments with a reference with respect to what is a reasonable WF permit to be issued to specific users. Questions still to be addressed are to which extent benchmarks for water consumption in crop production will need to differentiate between different climate and soil conditions, because a certain best practice may yield a larger WF per tonne of crop on sandy soil in a hot semi-arid climate than in other conditions (Zhuo et al 2016b). Besides, we may need to have benchmarks for different technologies and practices (Chukalla et al 2015).…”

“…Some of the early-day criticisms on the concepts of WF and VWT still arise at regular interval -as will be discussed in this paper -but in the meantime the field of WF and VWT assessment has matured, yielding in-depth studies and examples of practical use. Advances include the development of the full WFA methodology , the quantification of WFs at high spatial and temporal resolution , the study of inter-annual variability and trends in WFs and VWT (Zhuo et al 2016a), the development of WF benchmarks for crops (Mekonnen and Hoekstra 2014;Zhuo et al 2016b), the assessment of monthly blue water scarcity at a high spatial resolution based on patterns of blue WFs versus patterns of water availability , the computation of water pollution levels in river basins based on grey WFs versus assimilation capacity (Liu et al 2012), the exploration of the use of remote sensing (Romaguera et al 2010) and the development of future WF and VWT scenarios (Ercin and Hoekstra 2014). WFA applications vary widely, from product assessments, sector studies, diet assessments and catchment, municipal and national studies to global assessments.…”

Advancing Water Footprint Assessment Research: Challenges in Monitoring Progress towards Sustainable Development Goal 6

“…The blue WF can be expressed in terms of a water volume consumed per unit of a specific process or product. Given available technologies and practices, we can establish a benchmark for each process or product, which can be function of local conditions like soil or climate as well [13]. In agriculture, the first step is to develop benchmarks for the total consumptive WF, per crop, given local environmental conditions and best management practices.…”