Increasing water resources: a combined approach of water footprint and geographic information system for the sustainability challenge in the agricultural context

The agricultural sector is responsible for global freshwater consumption equal to 70% and generates the major impact on the shortage of water resources. Particularly, water pressure and scarcity affect the socioeconomic development of the countries (Li et al., 2022). Intending to address the need for food and water of a growing global population - that in 2050 it could reach 9.7 billion people, for the agricultural context is fundamental the estimation of the water footprint (WF), crop yield, and evapotranspiration for evaluating the pressure on water resources (Chanu & Oinam, 2023). For this reason, it is crucial to recommend some effective methods for decreasing irrigation water consumption considering several elements such as crop varieties with higher yields, regions, clusters of cultivation and growth potential. All these methods are necessary to potentially reduce WF (Garofalo et al., 2019; Mokarram et al., 2021; Zhuo et al., 2016). Among several environmental indicators studies applied to agricultural context in a combined approach with other tools, WF applications are very limited in the literature (Bilge Ozturk et al., 2022). Above all, the combined applications with other tools, such as life cycle assessment (LCA) or geographic information system (GIS), are very few. Most studies have been conducted to calculate WF focusing on the relationship between WF and other agricultural parameters, such as yield of products and type of cultivated plants (Mokarram et al., 2021). The past studies underlined that the integration of the WF methodology with high-resolution local data deriving from georeferencing through GIS supports agricultural processes with low environmental impact, reduction of water resource consumption, and increase in yield (Shtull-Trauring et al., 2016). Therefore, GIS tool is contemplated amongst the efficient IT-based technological tools for displaying complex information that include several geographical representation of the agricultural system. Besides, the integration of other programs (such as CROPWAT by FAO for the WF estimation) within GIS can improve the implementation and analysis of spatial data deriving from more solutions (Haji et al., 2020; Monika & Srinivasan, 2015). In the last 10 years, some authors have used GIS to extract and combine relevant information from climate, soil, and land use to develop a water balance model with high-resolution grids (Daccache et al., 2014) to build a model of input data with WF calculation. Accordingly, when multiple approaches are combined (e.g., WF and GIS), the output data are digitized and integrated, also according to computerized approaches, into a unified geoprocessing platform for enabling the visualization and further processing of risk factors (Haji et al., 2020). GIS, which is already very popular for the specific location of current and future uses of land for energy crops, has been applied to analyze the suitability of territory in the geographical context (Viccaro et al., 2022). Hence, a current and updated application can satisfy the data collection for building a dataset model of water consumption in the agricultural sector. Similarly, Feng et al. (2017) proposed a GIS-based model to evaluate the suitability of marginal lands for some plants as switchgrass, miscanthus, and hybrid poplar in the Upper Mississippi River Basin (United States) to produce biomass resources. Consequently, to date, after the first evaluation of the feasibility of the combinate application of GIS and WF tools, the authors proposed a systematic literature review (SLR) of the scientific interest for testing this combined application in the agricultural context, particularly in the cultivation of crops for food production and processing. The general research question of this chapter is the understanding of whether the WF indicator combined with the GIS tool has been applied in the past, particularly in the sector of agricultural production and crops cultivation for nutrition and regarding food-related human benefits, and can be used in the management of water resources too. In particular, the authors tested whether, within a GIS environment, the output of a vegetation model can be combined with other data sources to conduct a more comprehensive and spatially explicit analysis of water consumption for growing crops for human nutrition at certain geographic locations.