Estimating Water Footprints of Vegetable Crops: Influence of Growing Season, Solar Radiation Data and Functional Unit

Abstract

Abstract:Water footprint (WF) accounting as proposed by the Water Footprint Network (WFN) can potentially provide important information for water resource management, especially in water scarce countries relying on irrigation to help meet their food requirements. However, calculating accurate WFs of short-season vegetable crops such as carrots, cabbage, beetroot, broccoli and lettuce presented some challenges. Planting dates and inter-annual weather conditions impact WF results. Joining weather datasets of just rainfall, minimum and maximum temperature with ones that include solar radiation and wind-speed affected crop model estimates and WF results. The functional unit selected can also have a major impact on results. For example, WFs according to the WFN approach do not account for crop residues used for other purposes, like composting and animal feed. Using yields in dry matter rather than fresh mass also impacts WF metrics, making comparisons difficult. To overcome this, using the nutritional value of crops as a functional unit can connect water use more directly to potential benefits derived from different crops and allow more straightforward comparisons. Grey WFs based on nitrogen only disregards water pollution caused by phosphates, pesticides and salinization. Poor understanding of the fate of nitrogen complicates estimation of nitrogen loads into the aquifer.

Assessment of nutritional water productivity and improvement strategies for traditional vegetables in South Africa

“…In addition, we converted the water footprint values of selected alien vegetables to water productivity values (Table 2A.2); at a glance, these values are higher compared to the values of this study. Probably the water footprint values from Le Roux et al (2016) and Mekonnen and Hoekstra (2011) were calculated on a fresh mass basis. Therefore, alien vegetables might have high water footprint if a fresh mass was used, but if a dry mass was used, water footprints of these vegetables could be relatively low (Le Roux et al, 2016).…”

“…Probably the water footprint values from Le Roux et al (2016) and Mekonnen and Hoekstra (2011) were calculated on a fresh mass basis. Therefore, alien vegetables might have high water footprint if a fresh mass was used, but if a dry mass was used, water footprints of these vegetables could be relatively low (Le Roux et al, 2016). Le Roux et al (2016) found that the water footprints of maize and wheat were higher than those of vegetables if expressed in terms of fresh mass; however, when expressed in terms of dry mass, the water footprints of maize and wheat were similar to those of vegetables.…”

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

“…Thirteen of the fourteen papers in this special issue consider green and blue WFs [14][15][16][17][18][19][20][21][22][23][24][25][26], while eight papers include grey WF estimation. All papers that include the grey WF specifically focus on pollution through nitrogen [14,15,17,19,21,22,25,27].…”

“…All papers that include the grey WF specifically focus on pollution through nitrogen [14,15,17,19,21,22,25,27]. The only paper that exclusively focuses on the grey WF is the one by Brueck and Lammel [27].…”

“…Their study reveals that the uncertainty of crop yield prediction, arising from the use of different models, contributes more to the uncertainty in the assessment of water-use efficiency and water footprints than the estimation of evapotranspiration. Another paper that aims to better understand the intricacies involved in estimating WFs is the study by Le Roux et al [17], who do so in a case study for vegetables grown on a water-stressed aquifer in South Africa. They analyze how WF outcomes are influenced by several factors, like natural variations in weather conditions between growing seasons and between different years, and uncertainties related to model parameterization and input data used.…”