Abstract
This study aims to detect non-stationarity of the maximum and minimum streamflow regime in Tamsui River basin, northern Taiwan. Seven streamflow gauge stations, with at least 27-year daily records, are used to characterize annual maximum 1- and 2-day flows and annual minimum 1-, 7-, and 30-day flows. The generalized additive models for location, scale, and shape (GAMLSS) are used to dynamically detect evolution of probability distributions of the maximum and minimum flow indices with time. Results of time-covariate models indicate that stationarity is only noted in the 4 maximum flow indices out of 35 indices. This phenomenon indicates that the minimum flow indices are vulnerable to changing environments. A 16-category distributional-change scheme is employed to classify distributional changes of flow indices. A probabilistic distribution with complex variations of mean and variance is prevalent in the Tamsui River basin since approximate one third of flow indices (34.3%) belong to this category. To evaluate impacts of dams on streamflow regime, a dimensionless index called the reservoir index (RI) serves as an alternative covariate to model nonstationary probability distribution. Results of RI-covariate models indicate that 7 out of 15 flow indices are independent of RI and 80% of the best-fitted RI-covariate models are generally worse than the time-covariate models. This fact reveals that the dam is not the only factor in altering the streamflow regime in the Tamsui River, which is a significant alteration, especially the minimum flow indices. The obtained distributional changes of flow indices clearly indicate changes in probability distributions with time. Non-stationarity in the Tamsui River is induced by climate change and complex anthropogenic interferences.
Highlights
Probabilistic theories have played an essential role in hydraulic facilities planning and design due to the inherent uncertainties involved in hydro-climatic series
An important assumption in such frequency analysis-based approaches is stationarity; that is, the probability distribution used to fit the variable of interest is time invariant
The main aim of this work is to detect the presence of non-stationarity in the streamflow regime, characterized by the maximum and minimum flow indices at various time scales, of the Tamsui River located in northern Taiwan
Summary
Probabilistic theories have played an essential role in hydraulic facilities planning and design due to the inherent uncertainties involved in hydro-climatic series. It has become a standard practice to employ frequency analysis of extreme hydro-climatic variables in the risk evaluation of hydraulic facilities [1,2]. Climate change and/or anthropogenic interference-induced changing environments may lead to alterations in statistical characteristics of hydro-climatic variables, and result in non-stationarity. Non-stationarity in hydro-climate series renders estimates of return period and risk used for hydraulic facilities planning and design ambiguous and questionable [3,4,5,6,7]. Impacts of climate change and anthropogenic activities on streamflow regime have drawn considerable attention recently [18,19,20,21,22,23]. Most studies focus on extreme streamflow such as flood or low flow, while few studies have investigated them simultaneously
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