Dissolved oxygen concentrations in the lower reaches of the Tualatin River in northwest Oregon are the result of many processes. Temperature imposes a seasonal signal through the solubility of oxygen in water. Streamflow determines the travel time through the system and affects the amount of oxygen consumed via processes such as ammonia nitrification and the decomposition of organic material in...

This is our reply to the comment by Beven (2008) on our paper ‘‘Equifinality of formal (DREAM) and informal (GLUE) Bayesian approaches in hydrologic modeling?’’ recently published in Stochastic Environmental Research and Risk Assessment. There is strong disagreement in the hydrologic literature whether an appropriate framework for uncertainty estimation should have its roots within a proper sta...

Abstract This study investigates the capability of sequence-to-sequence machine learning (ML) architectures in an effort to develop streamflow forecasting tools for Canadian watersheds. Such are useful inform local and region-specific water management flood related activities. Two powerful deep-learning variants Recurrent Neural Network were investigated, namely standard attention-based encoder...

[1] Recognizing that the frequency distribution of annual maximum floods at a given location may change over time in response to interannual and longer climate fluctuations, we compare two approaches for the estimation of flood quantiles conditional on selected ‘‘climate indices’’ that carry the signal of structured low-frequency climate variation, and influence the atmospheric mechanisms that ...

This paper proposes the use of discrete wavelet transform (DWT) to remove the high-frequency components (details) of an original signal, because the noises generally present in time series (e.g. streamflow records) may influence the prediction quality. Cleaner signals could then be used as inputs to an artificial neural network (ANN) in order to improve the model performance of daily discharge ...

Lumped parameter hydrologic models are frequently used for operational streamflow forecasting in the United States. With the deployment of the Weather Surveillance Radar 1988 Doppler (WSR88D), many hydrologists will use radar-rainfall data as input to these models. WSR-88D precipitation products can be used in a variety of ways (Shedd and Fulton, 1993; Lindsey, 1993). In this paper, we examine ...