On the variability of a river water flow under seasonal conditions: Case study

Abstract

Precipitation regime and anthropogenic activities are the main factors that influence the river flow along the time. To assure the flow regulation and the flood mitigation some structural measures must be implemented. Building dams represents one of these measures. Their impact on the stream flow and climate change must be studied for avoiding negative effects on the environment. Therefore, our study focuses on the variability of the Buzau River (in Romania) water flow and its seasonal variation. The analysis is done for the period before and after the moment when the Siriu Dam (Romania) was built. The stationarity and the trend existence are analysed and the results are compared by statistical methods.

Study of the River Discharge Alteration

“…Compared to the results obtained in [38] by utilizing the IHA methodology, the present article provides new insights into the series variability by building IMFs. The output of this study is in concordance with the finding of [39], indicating the significant alteration in the river flow after building the dam, emphasized by the differences between the IMFs' amplitudes and frequencies corresponding to S1 and S2. Meanwhile, in [38], it was shown that a decrease of 12.6% in the maximum monthly discharge was noticed after 1984 with respect to 1955-1983, and in the same period, the minimum and the maximum of the 90-day maximum flow decreased from 28.6 to 16.4 m 3 /s, and from 92.6 to 69.8 m 3 /s, respectively, but no chart of the time series components is provided.…”

“…The current analysis provides a comprehensive and nuanced view of the dam's impact on Buzău discharge dynamics, validating and complementing the findings from the articles [38,39]. While the research conducted in [39] only tested for the existence of a trend in the annual and quarterly flow series and built an AR(5) model to forecast the mean quarterly series, the present study has a larger scope. With a higher-resolution data series, it can detect monthly seasonality factors.…”

“…Within this complex realm, our research combines different approaches to crossvalidate the results of the hydrological alteration in the Buzău River flow after operating the Siriu dam, Romania's second biggest accumulation lake. Very few articles [38][39][40] have approached the impact of building the Siriu dam on the river flow, one of them using IHA [38] and the other [39] using statistical methods to test the existence of specific trends in seasonal series (winter, spring, summer, and autumn) before and after the dam's inception. Another attempt was made by modeling the daily mean flow series using general regression neural networks (GRNNs) [40].…”

“…Another attempt was made by modeling the daily mean flow series using general regression neural networks (GRNNs) [40]. None of these studies have provided a complete analysis given that (1) assessing the tendency by the Mann-Kendall test followed by utilizing Sen's slope (which computes a linear trend) [39] cannot capture the complex behavior of the data series (such as seasonality), (2) the linear parametric regression [38,40] was not satisfactory from the viewpoint of the extracted information, and (3) the GRNN model [40] was not accurate enough. In the GRNN, the correlation between the actual and predicted values on the test set was not very high, and the time taken to run the algorithm was very long (a few hours).…”

Comparative Analysis of Convolutional Neural Network-Long Short-Term Memory, Sparrow Search Algorithm-Backpropagation Neural Network, and Particle Swarm Optimization-Extreme Learning Machine Models for the Water Discharge of the Buzău River, Romania

“…Our research aims to answer whether the Buzău River discharge is altered after putting the Siriu Dam, one of Romania's most important accumulation lakes in the country, into operation. Two articles [36,37] attempted to answer this question by testing different statistical hypotheses and using indicators of hydrologic alterations (IHA). Two models (regression and generalized regression neural network) [37,38] for the daily river discharge have also been proposed, but neither of them was satisfactory from an accuracy viewpoint.…”