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Food-Energy-Water Nexus Resilience and Sustainable Development pp 57–73Cite as

A Decision Support Tool for the Assessment of Water–Energy–Food Nexus in Saudi Arabia

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Abstract

The sustainable management of natural resources is a fundamental component that drives the economic growth of most countries. Economic crisis, poverty, and hunger have been escalating in different parts of the world due to unsustainable use of natural resources. Thus, the goals of economic and sustainable development should be defined in terms of sustainability of resources: water, energy, and food. Identifying factors affecting these resources, and explaining the interconnectedness between them, is the first step towards sustainable management of natural resources.

Several frameworks and models have been designed to help policymakers understand the complexity of the interlinkages between natural resources and assist with planning and regulating these resources. This paper describes a spatial-temporal decision support tool that analyzes energy requirements in the food sector. The tool provides policymakers with essential information to assess which energy inputs in food production are the largest and which factors might influence the increase in energy use over space and time.

The tool was developed using a web-based Geographical Information System (GIS) application in a way that allows the user to navigate over different spatial locations, select a point of interest to grow a certain quantity of a specific crop, and calculate water, land, and energy requirements accordingly. This application provides a web-mapping platform and helps users determine when and where they can grow crops based on water and energy requirements objective functions. This application is very helpful for areas with limited information on natural resources. It utilizes satellite imagery to identify major environmental features that are important for analysis. It also allows comparison between different scenarios of food production, promotes natural resources usage efficiency, and encourages greater policy coherence.

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Author information

Authors and Affiliations

  1. Texas A&M University, College Station, TX, USA

    Sa’d Shannak

  2. University of New Haven, Henry C. Lee College of Criminal Justice and Forensic Sciences, West Haven, CT, USA

    Michele Vittorio

Authors
  1. Sa’d Shannak
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  2. Michele Vittorio
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Corresponding author

Correspondence to Sa’d Shannak .

Editor information

Editors and Affiliations

  1. Department of Architectural Engineering, Pennsylvania State University, University Park, PA, USA

    Somayeh Asadi

  2. Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, Iran

    Behnam Mohammadi-Ivatloo

Appendix: Land Suitability Analysis

Appendix: Land Suitability Analysis

  • Hundred Landsat 8 satellite scenes covering all of Saudi Arabia for the month of June and July 2015 have been downloaded from USGS and processed in ArcGIS 10.3 environment.

  • Satellite imagery was georeferenced. Color enhancement was done in such a way to be able to digitize various sections and features of the land layer.

  • The Normalized Difference Vegetation Index (NDVI) procedures were applied to assess whether the target being observed contains live green vegetation or not.

  • The next step was to classify the imagery into two main classes; vegetated and not- vegetated. This was followed by vectorization, which involves the conversion of raster data to vector by digitization.

  • Street and residential layers were placed on the top of the analyzed imagery layer. Points of intersections were exported to exclude potential future agriculture activities where residential and paved streets took place.

  • DEM layer was generated and slopes were calculated all over the topography to determine hilly and flat areas.

  • Potential new agricultural areas were determined based on closeness to water sources, distance from the road network, soil cover, soil type, and land productivity.

Example: monthly crop water requirements for different cities in Saudi Arabia (Fig. 3.8).

Fig. 3.8
figure 8

The spatial distributions of monthly ET0 values

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Shannak, S., Vittorio, M. (2020). A Decision Support Tool for the Assessment of Water–Energy–Food Nexus in Saudi Arabia. In: Asadi, S., Mohammadi-Ivatloo, B. (eds) Food-Energy-Water Nexus Resilience and Sustainable Development. Springer, Cham. https://doi.org/10.1007/978-3-030-40052-1_3

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  • DOI: https://doi.org/10.1007/978-3-030-40052-1_3

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-40051-4

  • Online ISBN: 978-3-030-40052-1

  • eBook Packages: EnergyEnergy (R0)

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