Luigi Piemontese
This spatial dataset contains raster files for 6 spatial archetypes representing social-ecological regions — archetypes of water harvesting regions (AWHR) and the related potential for crop production increase.
It was constructed from 162 empirical case studies taken from the WOCAT (World Overview of Conservation Approaches and Technologies) database on local implementations of water harvesting across the globe. The 162 cases were clustered according to their social-ecological conditions, defined by a set of 12 social-ecological indicators: precipitation amount, seasonality, aridity, slope, soil organic carbon, farm size, agricultural labour, land tenure, remoteness, Human Development Index (HDI), access to credit and gender inequality. We used the HDI as an aggregate indicator which embraces the key aspects of education, income and life expectancy.
From six clusters of case studies, six global areas showing similar social-ecological conditions (archetypes) were mapped. Each of the six corresponding raster files in ASCII format represents one of the six social-ecological regions where the 162 case studies of increasing crop productivity with water harvesting can be replicated given the similar conditions. The dataset can be used to understand the social-ecological suitability of different agricultural development practices and guide the transferability of local successful solutions.
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Citation
Luigi Piemontese (2020) Global social-ecological regions with potential for crop production increase with water harvesting. Dataset version 1. Bolin Centre Database. https://doi.org/10.17043/piemontese-2020-regions-1
References
Piemontese L, Castelli G, Fetzer I, Barron J, Liniger H, Harari N, Bresci E, Jaramillo F (2020) Estimating the global potential of water harvesting from successful case studies. Glob. Environ. Change 63:102121. https://doi.org/10.1016/j.gloenvcha.2020.102121
Data description
The database contains 7 raster files in unprojected WGS84 geographic coordinates (latitude and longitude) with a resolution of 0.05°. The files are in ASCII format and can be open with any text editor or geographic information system program.
The 6 ASCII files with names starting with AWHR are the spatial archetypes of water harvesting region, each one representing areas with different social-ecological conditions for agriculture as below:
- Larger farms in arid remote areas
- Smallholder farms in dense rural areas
- Smallholder farms in arid developing areas
- Remote farms in tropical developing areas
- Larger farms in higher developed areas
- Slope farms in higher developed areas
The file "CROP_P_increase" is a global map of potential for crop production increase derived by the 6 AWHR.
The information in the raster files is shown on maps in Figure 4 of the article by Piemontese et al. (2020). For more information about this data set, we refer to the publication and its supplementary information.
Comments
We thank the WOCAT for providing free access to the documentation of field-tested sustainable land management practices.
The data creator, Luigi Piemontese, is a PhD student at the Stockholm Resilience Centre and part of the Bolin Centre for Climate Research.
GCMD science keywords
Earth science services > Data analysis and visualization > Geographic information systems
Project
This research was funded by the This database was developed within the PhD project funded by the Swedish Research Council for Environment, Agricultural Sciences and Spatial Planning FORMAS (942-2015-740).
Publisher
Bolin Centre Database
DOI
10.17043/piemontese-2020-regions-1
Published
2020-10-21 12:23:33