چکیده مقاله
Water Quality Index WQI is one of the most popular mathematical approaches for assessing the quality of water resources, which converts several physical, chemical, and biological characteristics of water into a single number representing the condition of water quality Given the fact that designing optimal treatment strategies and the protection of water quality requires confidence in WQI evaluation, a comprehensive uncertainty analysis will ensure that the uncertainty is reflected in the estimation of WQI, thereby providing reliable assessments Among various sources, input data uncertainty is a considerable and unavoidable source of uncertainty in WQI, which has been infrequently accounted for in previous studies Factors such as measurement errors or the use of model based data both have the potential to produce this type of uncertainty and bias in estimations In this study, we present a new multivariate framework for uncertainty analysis that is based on uncertainty aware principal component analysis UPCA and hierarchical clustering HC We applied our framework to uncertainty analysis of WQI for the South Florida watershed over seven years 2015 2021 and 19 stations Furthermore, we used a global sensitivity analysis approach to identify water quality parameters that mostly contribute to the uncertainty in WQI Overall, results reveal how data uncertainty significantly affects traditional, widely used principal component analysis outcomes Also, we found that the cluster with the highest level of uncertainty is created with the most significant influences from total phosphate, total hardness and pH Moreover, alkalinity and nitrogen have the lowest effect Results indicated the effectiveness of the proposed framework for input data uncertainty analysis that could be replicated for other watersheds
کلیدواژهها
نویسندگان
Farshad Jahangiri
M Sc Student, Department of Civil Engineering, Sharif University of Technology
Razi Sheikholeslami
Assistant Professor, Department of Civil Engineering, Sharif University of Technology
شیوه ارجاع
Jahangiri, Farshad and Sheikholeslami, Razi,1402,A Multivariate Approach to Accounting for Input Data Uncertainty in Water Quality Assessment,13th International Congress on Civil Engineering,Tehran
ارائهشده در
مجموعه مقالات سیزدهمین کنگره بین المللی مهندسی عمران25 مهر 1402 · تهران