Combining Fuzzy, Multicriteria and Mapping Techniques to Assess Soil Fertility for Agricultural Development: A Case Study of Firozabad District, Uttar Pradesh, India

Anuj Saraswat, Shri Ram, Mohamed A. E. AbdelRahman, Md Basit Raza (), Debasis Golui (), Hombegowda Hc, Pramod Lawate, Sonal Sharma, Amit Kumar Dash, Antonio Scopa and Mohammad Mahmudur Rahman
Additional contact information
Anuj Saraswat: Department of Soil Science, G.B. Pant University of Agriculture and Technology, Pantnagar 263145, India
Shri Ram: Department of Soil Science, G.B. Pant University of Agriculture and Technology, Pantnagar 263145, India
Mohamed A. E. AbdelRahman: Division of Environmental Studies and Land Use, National Authority for Remote Sensing and Space Sciences (NARSS), Cairo 1564, Egypt
Md Basit Raza: ICAR—Indian Institute of Soil and Water Conservation, RC, Koraput 763002, India
Debasis Golui: Department of Civil, Construction and Environmental Engineering, North Dakota State University, Fargo, ND 58102, USA
Hombegowda Hc: ICAR—Indian Institute of Soil and Water Conservation, RC, Koraput 763002, India
Pramod Lawate: ICAR—Indian Institute of Soil and Water Conservation, Dehradun 248195, India
Sonal Sharma: Department of Soil Science, Maharana Pratap University of Agriculture and Technology, Udaipur 313001, India
Amit Kumar Dash: ICAR—National Bureau of Soil Survey & Land Use Planning, Nagpur 440033, India
Antonio Scopa: Scuola di Scienze Agrarie, Forestali, Alimentari ed Ambientali (SAFE), University of Basilicata, Viale dell’Ateneo Lucano, 10-85100 Potenza, Italy
Mohammad Mahmudur Rahman: Global Centre for Environmental Remediation (GCER), College of Engineering, Science and Environment, The University of Newcastle, Callaghan, NSW 2308, Australia

Land, 2023, vol. 12, issue 4, 1-18

Abstract: Soil fertility (SF) assessment is an important strategy for identifying agriculturally productive lands, particularly in areas that are vulnerable to climate change. This research focuses on detecting SF zones in Firozabad district, Uttar Pradesh, India, for agricultural purposes, so that they can be prioritized for future management using the fuzzy technique in the Arc GIS model-builder. The model computing technique was also deployed to determine the different fertility zones, considering 17 soil parameters. The derived fuzzy technique outperformed the traditional method of dividing the sampling sites into clusters to correlate soil fertility classes with the studied soil samples. The prioritization of the soil factors and a spatial analysis of the fertility areas were carried out using the Analytic Hierarchy Process (AHP) and GIS tools, respectively. The AHP analysis outcome indicated that hydraulic properties had the highest weighted value, followed by physical and chemical properties, regarding their influence on SF. The spatial distribution map of physico-chemical properties also clearly depicts the standard classification. A fuzzy priority map was implemented based on all the classes parameters to identify the five fertility classes of the soil, namely very high (0.05%); high (16.59%); medium (60.94%); low (22.34%); and very low (0.07% of total area). This study will be of significant value to planners and policymakers in the future planning and development of activities and schemes that aim to solve similar problems across the country.

Keywords: fuzzy model; geographical information system (GIS); spatial interpolation; soil fertility mapping (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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