Generating Regional Models for Estimating the Peak Flows and Environmental Flows Magnitude for the Bulgarian-Greek Rhodope Mountain Range Torrential Watersheds

Abstract

The flood magnitudes with 25, 50, and 100 years return periods and the environmental flows (Qenv) are of outmost importance in the context of hydraulic and hydrologic design. In this study, 25 watershed characteristics were linked with the aforementioned recurrence intervals, peak discharge values, as well as Qenv for 15 pristine torrential watersheds with more than 10 years of streamflow records in the Rhodopi mountain range with a view to generating regional relationships for the assessment of discharge annual peaks and environmental flows regarding the ungauged torrential watersheds in the region. The Log-Pearson Type III probability distribution was fitted in the discharge annual peaks time series, so as to predict Q25, Q50, and Q100, whereas the Tennant method was utilised so as to estimate the environmental flows magnitude. Similarly, the Kolmogorov–Smirnov and the Anderson–Darling tests were performed to verify the distribution fitting. The Principal Components Analysis method reduced the explanatory variables number to 14, whilst the stepwise multiple regression analysis indicated that the exponential model is suitable for predicting the Q25, the power model best forecasted the Q50 and Q100, whereas the linear model is appropriate for Qenv prognosis. In addition, the reliability of the obtained regression models was evaluated by employing the R2, the Nash–Sutcliffe efficiency, and the Index of Agreement Statistical Criteria, which were found to range from 0.91–0.96, 0.88–0.95 and 0.97–0.99, respectively, thereby denoting very strong and accurate forecasts by the generated equations. Thus, the developed equations could successfully predict the peak discharge values and environmental flows within the region’s ungauged watersheds with the drainage size not exceeding 330 km2.

A Geographical Information Approach for Forest Maintenance Operations with Emphasis on the Drainage Infrastructure and Culverts

“…In a watershed where no instruments are installed, the estimation of the maximum water-carrying capacity of the torrent can be calculated indirectly if the cross-sectional area of the channel and the average flow velocity of the effluent water are known, based on the following equation [33,34]:…”

Modeling the Soil Erosion Regulation Ecosystem Services of the Landscape in Polish Catchments

“…A step-by-step regression model was applied in order to model the relationship between soil erosion as dependent variable and intrinsic variables of the soil, geomorphological variables and land use/land covers as independent variables. Four linear, power, logarithmic and exponential structures [33] were examined to determine which of these model structures could best explain the relationship between soil erosion and three explanatory factors: the intrinsic variables of the soil, the geomorphological variables, and land use/land covers.…”

Comparison of Three-Parameter Distributions in Controlled Catchments for a Stationary and Non-Stationary Data Series

“…In several studies [2,6,7], an appropriate estimation of flow values for various probabilities of occurrence or various return periods is required. Examples include the design of hydrotechnical structures and water management [4,[8][9][10][11][12][13][14]. Numerous methods are available for flood analysis using historical data [4,5].…”

“…Otherwise, the non-stationary FFA approach is recommended [10,[16][17][18]. The relationship between the flow and the probabilities of occurrence is unique for every gauging station [14,[18][19][20]. The maximum flow peak value occurring in a water year at a given cross-section of a stream collected for the longest possible period of observation allows one to get more realistic results of the FFA [1,13,21].…”