Applying Weibull distribution and Low Flow Frequency Curves for minimum flow prediction in an ungagged stream in Connecticut, New England

Abstract

The necessity to conduct hydrological studies for water resources management, infrastructure design and, ecosystems protection can help mitigate flood and drought hazards. Prediction of low flows remains an important task for water management and ecosystems protection that can affect streams during low-flow periods. There have been many approaches to low flow prediction applying either statistical or deterministic methods, but there has not been any successful approach to link low flows between similar watersheds yet. The Fenton, Natchaug and Mount Hope Rivers watersheds are neighbors and are the major streams that discharge into the Mansfield Hollow Lake that belongs to the Thames River watershed, located in Northeast of the State of Connecticut in USA. A study to determine whether and how water withdrawals from the University’s Fenton River water supply wells affect the fisheries habitat of the Fenton River adjacent to the well field was conducted for four years at the beginning of 2002. The Mount Hope River was the only river with a long record of daily discharges available since the year 1940, meanwhile the Fenton and Natchaug River remained ungagged until the year 2006. This research developed and tested two mathematical models for the prediction of minimum discharges in the Fenton and Natchaug Rivers with the discharges available from the Mount Hope River. Yearly Low Flow Duration Curves (LFFC) and Weibull distribution methods were applied to the three rivers to predict the low flows in the Fenton and Natchaug Rivers taking as input the minimum flows and dates in the Mount Hope River. The results found that the Weibull distribution model showed a much better accuracy than the Low Flow Duration Curve method for the prediction of low flows discharges in the Fenton and Natchaug Rivers.

Modeling Alex Hurricane: flood map simulation applying Multisensor grid precipitation, Monterrey, Mexico

“…The closer the simulated NS is to 1, the more accurate the model is. If NS < 0, it means that the observed data mean is a better predictor than the simulated values (Stella, 2021).…”

Mapping Floods of Fenton River, an Ungauged Stream in Connecticut

“…( ) ( ) that the observed data mean is a better predictor than the model [17]. Table 2 summarizes the correlation coefficients r-squared between daily discharges and annual maximum discharges between the Fenton River and the Mount Hope Rivers.…”