en |
Sensitivity Analysis of Stream Water Quality and Land Cover Linkage Models Using Monte Carlo Method
Nakane, K. & Haidary, A.
Abstract
Sensitivity analysis might be considered as one of inevitable steps in modelling since
it would help to determine the behaviour of model, which was developed for further application.
Sensitivity analysis was not paid much attention in studies that have been conducted for modelling
the relationship between stream water quality and land cover except machine learning techniques
such as artificial neural networks was applied for specifying the possible relationship between
alteration in area (%) of land cover types and changes in water quality variable. Two linkage models
for predicating stream water total nitrogen (r2= 0.70, p<0.01) and total phosphorus (r2=0.47, p<0.01)
concentrations were developed using multiple regression approach in twenty-one river basins in
the Chugoku district of west Japan. Application of Monte Carlo method-based sensitivity analysis
indicated that TN regression model would be able to predict stream water concentration between
0.4-3.2 mg/L without any possibility for generation of negative value. For the TP regression model,
predicting capacity would vary between 0.04, 0.32 mg/L. The results revealed that the Monte Carlo
method-based sensitivity analysis would provide reliable information for determining output space
in which the model would accurately respond.
Keywords
Sensitivity analysis, Stream, Water, Quality, Nitrogen, Phosphorus
|