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Identifying Suitable Watersheds across Nigeria Using Biophysical Parameters and Machine Learning Algorithms for Agri–Planning

OAR@ICRISAT

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Relation http://oar.icrisat.org/12133/
https://www.mdpi.com/2220-9964/11/8/416
https://doi.org/10.3390/ijgi11080416
 
Title Identifying Suitable Watersheds across Nigeria Using Biophysical Parameters and Machine Learning Algorithms for Agri–Planning
 
Creator Panjala, P
Gumma, M K
Ajeigbe, H A
Badamasi, M M
Deevi, K C
Tabo, R
 
Subject Agriculture
Nigeria
Water Resources
Drylands
 
Description Identifying suitable watersheds is a prerequisite to operationalizing planning interventions for agricultural development. With the help of geospatial tools, this paper identified suitable watersheds across Nigeria using biophysical parameters to aid agricultural planning. Our study included various critical thematic layers such as precipitation, temperature, slope, land-use/land-cover
(LULC), soil texture, soil depth, and length of growing period, prepared and modeled on the Google Earth Engine (GEE) platform. Using expert knowledge, scores were assigned to these thematic layers, and a priority map was prepared based on the combined weighted average score. We also validated priority watersheds. For this, the study area was classified into three priority zones ranging from ‘high’ to ‘low’. Of the 277 watersheds identified, 57 fell in the high priority category, implying that they are highly favorable for interventions. This would be useful for regional-scale water resource planning for agricultural landscape development.
 
Publisher MDPI
 
Date 2022-07-22
 
Type Article
PeerReviewed
 
Format application/pdf
 
Language en
 
Rights cc_attribution
 
Identifier http://oar.icrisat.org/12133/1/International%20Journal%20of%20Geo-Information_11_01-17_2022.pdf
Panjala, P and Gumma, M K and Ajeigbe, H A and Badamasi, M M and Deevi, K C and Tabo, R (2022) Identifying Suitable Watersheds across Nigeria Using Biophysical Parameters and Machine Learning Algorithms for Agri–Planning. International Journal o f Geo-Information, 11. 01-17. ISSN 2220-9964