Abstract

The assessment of the water scarcity footprint of products emerged as an important step in supporting water management strategies. Among others, the AWARE methodology was published as a consensus-based indicator to perform such an assessment at a watershed level and monthly scale. The need to adopt such a detailed resolution, however, collides with the availability of data, so that general year and country-wide factors are commonly used. The objective of this study is to develop and verify the applicability of 26 crop-specific water scarcity characterization factors to help assess the water scarcity footprint when data and information availability is limited. To do so, a weighted average consumption approach was adopted, starting from local AWARE characterization factors and local crop-specific water consumption. The resulting factors, ranging from 0.19 m3/ton eq for “other perennial crop” in Brunei to 9997 m3/ton eq for “other annual crop” in Mauritania, illustrate the large variability of potential water scarcity impacts. Factors were applied to the water consumption of selected crops to assess their water scarcity footprint. The results of the study confirmed that the use of crop-specific factors is recommended as they are a better proxy of water scarcity in a region when compared to their national generic counterparts.

Highlights

  • In the framework of the Sustainable Development Goals [1], with the global population expected to be 9 billion people by 2050, agriculture is considered to play a fundamental role in human well-being and economic growth [2]

  • While the AWARE model uses the total water consumption for irrigation, the data obtained from Global Crop Water Model (GCWM) provide irrigation data for each of the 26 crops

  • The results of the quantification of the crop-specific characterization factors (CF) proved that there is a high variability among crops in selected countries, suggesting that the use of these CF is a better proxy of water scarcity in a region when compared to the national generic CF counterparts (Figure 5)

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Summary

Introduction

In the framework of the Sustainable Development Goals [1], with the global population expected to be 9 billion people by 2050, agriculture is considered to play a fundamental role in human well-being and economic growth [2]. With specific reference to water, agricultural products are responsible for the consumption of 1180 km yr−1 [5], representing about 70% of the total water consumption [6], granting this sector a leading role in order to guarantee the sustainable use of this resource. In this context, the need for tools and methods to adequately quantify and address undesired environmental impacts has clearly emerged [7]

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