Relationship between water quality and macro-scale parameters(land use, erosion, geology, and population density )
To date, few studies have investigated the simultaneous effects of macro-scale parameters (MSPs) such as land use, population density, geology, and erosion layers on micro-scale water quality variables (MSWQVs). This research focused on an evaluation of the relationship between MSPs and MSWQVs in the Siminehrood River Basin, Iran. In addition, we investigated the importance of water particle travel time (hydrological distance) on this relationship. The MSWQVs included 13 physicochemical and biochemical parameters observed at 15 stations during three seasons. Primary screening was performed by utilizing three multivariate statistical analyses (Pearson's correlation, cluster and discriminant analyses) in seven series of observed data. These series included three separate seasonal data, three two-season data, and aggregated three-season data for investigation of relationships between MSPs and MSWQVs. Coupled data (pairs ofMSWQVs and MSPs) repeated in at least twoout of three statistical analyses were selected for final screening. The primary screening results demonstrated significant relationships between land use and phosphorus, total solids and turbidity, erosion levels and electrical conductivity, and erosion and total solids. Furthermore, water particle travel time effects were considered through three geographical pattern definitions of distance for each MSP by using two weighting methods To find effectiveMSP factors onMSWQVs, amultivariate linear regression analysiswasemployed. Then preliminary equations that estimated MSWQVswere developed. The preliminary equationswere modified to adaptive equations to obtain the finalmodels. The final models indicated that a newmetric, referred to as hydrological distance provided better MSWQV estimation and water quality prediction compared to the National Sanitation Foundation Water Quality Index
study case : in the Siminehrood River Basin
:keywords
Macro-scale parameters
Micro-scale water quality variables
Multivariate linear regression analysis
Erosion
گروه: مقالات