New Regression Model for Estimating Irrigation Water Quality Index

Autor:	Aysar Tuama Al-Awadi, Abdul Khider Aziz Mutasher, Riyadh Jasim Mohammed Al-Saadi
Rok vydání:	2021
Předmět:	Index (economics) media_common.quotation_subject Statistics General Engineering Environmental science Regression analysis Quality (business) General Agricultural and Biological Sciences Irrigation water General Environmental Science media_common
Zdroj:	International Journal of Design & Nature and Ecodynamics. 16:127-134
ISSN:	1755-7445 1755-7437
DOI:	10.18280/ijdne.160202
Popis:	The common tool to evaluate the groundwater quality is so-called the Irrigation Water Quality Index (IWQI). In the present study, the IWQI model developed by Meireles is used to assess the quality of groundwater in Karbala - Najaf plateau, Iraq. The quality parameters that collected from groundwater tests of 78 wells in the study area are; EC, Na+1, Mg+2, Ca+2, Cl-1, and HCO3-1. The SPSS software program is employed to develop a non-linear regression model of the IWQI for the study area. The results show that the IWQI values for 90% of groundwater wells fall within the Severe Restriction (SR) category, which means that it’s only suitable for irrigation of high salt tolerance crops. While its remaining 10% of the wells are in the High Restriction (HR) category, and this means it is suitable for irrigation of moderate to high salt tolerance crops. The calibration and validation for the developed model presented that this model has a good estimation of the IWQI values. Due to flexible and unbiased, the current study recommends to use the proposed model to estimate the IWQI.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::669b093fe3ae22cfa26c6475833cd795 https://doi.org/10.18280/ijdne.160202 Zobrazit plný text záznamu