TITLE:
Rating Curve Estimation of Surface Water Quality Data Using LOADEST
AUTHORS:
Bhasker Jha, Manoj Kumar Jha
KEYWORDS:
LOADEST; Rating Curve; Nutrient Load; Water Quality
JOURNAL NAME:
Journal of Environmental Protection,
Vol.4 No.8,
August
9,
2013
ABSTRACT: Measurement
of the nutrient concentrations in the stream is usually done on weekly,
biweekly or monthly basis due to limited resources. There is need to estimate
concentration and loads during the period when no data is available. The
objectives of this study were to test the performance of a suite of regression
models in predicting continuous water quality loading data and to determine
systematic biases in the prediction. This study used the LOADEST model which
includes several predefined regression models that specify the model form and
complexity. Water quality data primarily nitrogen and phosphorus from five
monitoring stations in the Neuse River Basin in North Carolina, USA were used
in the development and analyses of rating curves. We found that LOADEST performed generally well in
predicting loads and observation trends with general tendency/bias towards
overestimation. Estimated Total Nitrogen (TN) varied from observation (“true”
load) by -1% to 9%, but for the Total Phosphorus (TP) it ranged from -2% to
27%. Statistical evaluation using R2, Nash-Sutcliff Efficiency (NSE)
and Partial Load Factor (PLF) showed a strong correlation in prediction.