Fuzzy logic, geostatistics, and multiple linear models to evaluate irrigation metrics and their influencing factors in a drought-prone agricultural region

S M Rabbi Al Zihad; Abu Reza Md Towfiqul Islam; Md Abu Bakar Siddique; Md Yousuf Mia; Md Saiful Islam; Md Aminul Islam; A B M Mainul Bari; Md Bodrud-Doza; Sobhy M Yakout; Venkatramanan Senapathi; Sumanta Chatterjee

doi:10.1016/j.envres.2023.116509

Fuzzy logic, geostatistics, and multiple linear models to evaluate irrigation metrics and their influencing factors in a drought-prone agricultural region

Environ Res. 2023 Oct 1:234:116509. doi: 10.1016/j.envres.2023.116509. Epub 2023 Jul 1.

Affiliations

¹ Department of Disaster Management, Begum Bekeya University, Rangpur, 5400, Bangladesh. Electronic address: razihad@gmail.com.
² Department of Disaster Management, Begum Bekeya University, Rangpur, 5400, Bangladesh; Department of Development Studies, Daffodil International University, Dhaka, 1216, Bangladesh. Electronic address: towfiq_dm@brur.ac.bd.
³ Institute of National Analytical Research and Service (INARS), Bangladesh Council of Scientific and Industrial Research (BCSIR), Dhanmondi, Dhaka 1205, Bangladesh. Electronic address: sagor.bcsir@gmail.com.
⁴ Department of Disaster Management, Begum Bekeya University, Rangpur, 5400, Bangladesh. Electronic address: ym.fahim.brur@gmail.com.
⁵ Department of Soil Science, Patuakhali Science and Technology University, Dumki, Patuakhali 8602, Bangladesh. Electronic address: msaifulpstu@yahoo.com.
⁶ Department of Disaster Management, Begum Bekeya University, Rangpur, 5400, Bangladesh. Electronic address: aminul.dm@brur.ac.bd.
⁷ Department of Industrial and Production Engineering, Bangladesh University of Engineering and Technology, Dhaka, 1000, Bangladesh. Electronic address: mainul.ipe@gmail.com.
⁸ Department of Geography, Environment & Geomatics, University of Guelph, ON | N1G 2W1, Canada. Electronic address: mbodrudd@uoguelph.ca.
⁹ Department of Biochemistry, College of Science, King Saud University, P.O. Box 2455, Riyadh 11451, Saudi Arabia. Electronic address: syakout@ksu.edu.sa.
¹⁰ Department of Disaster Management, Alagappa University, Karaikudi, Tamilnadu, India. Electronic address: venkatramanansenapathi@gmail.com.
¹¹ USDA-ARS Hydrology and Remote Sensing Laboratory, BARC-West, Beltsville, MD 20705, USA; ICAR-National Rice Research Institute, Cuttack, Odisha 753006, India. Electronic address: chatterjeesumanta65@gmail.com.

PMID: 37399988
DOI: 10.1016/j.envres.2023.116509

Abstract

The quality of water used for irrigation is one of the major threats to maintaining the long-term sustainability of agricultural practices. Although some studies have addressed the suitability of irrigation water in different parts of Bangladesh, the irrigation water quality in the drought-prone region has yet to be thoroughly studied using integrated novel approaches. This study aims to assess the suitability of irrigation water in the drought-prone agricultural region of Bangladesh using traditional irrigation metrics such as sodium percentage (NA%), magnesium adsorption ratio (MAR), Kelley's ratio (KR), sodium adsorption ratio (SAR), total hardness (TH), permeability index (PI), and soluble sodium percentage (SSP), along with novel irrigation indices such as irrigation water quality index (IWQI) and fuzzy irrigation water quality index (FIWQI). Thirty-eight water samples were taken from tube wells, river systems, streamlets, and canals in agricultural areas, then analyzed for cations and anions. The multiple linear regression model predicted that SAR (0.66), KR (0.74), and PI (0.84) were the primary important elements influencing electrical conductivity (EC). Based on the IWQI, all water samples fall into the "suitable" category for irrigation. The FIWQI suggests that 75% of the groundwater and 100% of the surface water samples are excellent for irrigation. The semivariogram model indicates that most irrigation metrics have moderate to low spatial dependence, suggesting strong agricultural and rural influence. Redundancy analysis shows that Na^+, Ca²⁺, Cl^-, K⁺, and HCO₃^- in water increase with decreasing temperature. Surface water and some groundwater in the southwestern and southeastern parts are suitable for irrigation. The northern and central parts are less suitable for agriculture because of elevated K⁺ and Mg²⁺ levels. This study determines irrigation metrics for regional water management and pinpoints suitable areas in the drought-prone region, which provides a comprehensive understanding of sustainable water management and actionable steps for stakeholders and decision-makers.

Keywords: Chemometric tool; Fuzzy logic; Geostatistical; Northern Bangladesh; RDA; Sustainable water management.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Agricultural Irrigation
Agriculture
Benchmarking
Droughts
Environmental Monitoring
Fuzzy Logic
Groundwater* / analysis
Linear Models
Sodium / analysis
Water Pollutants, Chemical* / analysis
Water Quality

Substances

Sodium
Water Pollutants, Chemical