The objective of this paper is to simulate flow frequency distribution curves for Amazon catchments with the aim of scaling power generation from small hydroelectric power plants. Thus, a simple nonlinear rainfall-runoff model was developed with sigmoid-variable gain factor due to the moisture status of the catchment, which depends on infiltration, and is considered a factor responsible for the nonlinearity of the rainfall-runoff process. Data for a catchment in the Amazon was used to calibrate and validate the model. The performance criteria adopted were the Nash-Sutcliffe coefficient (R²), the RMS, the Q95% frequency flow percentage error, and the mean percentage errors ranging from Q5% to Q95%.. Calibration and validation showed that the model satisfactorily simulates the flow frequency distribution curves. In order to find the shortest period of rainfall-runoff data, which is required for applying the model, a sensitivity analysis was performed whereby rainfall and runoff data was successively reduced by 1 year until a 1.5-year model application minimum period was found. This corresponds to one hydrological year plus the 6-month long ''memory''. This analysis evaluates field work in the ungauged sites of the region. and Cieľom tohto príspevku je simulácia čiar rozdelenia prietokov pre povodia rieky Amazonka pre potreby hodnotenia premeny energie v malých hydroelektrárňach. Preto bol vyvinutý jednoduchý nelineárny zrážko-odtokový model so sigmoidálne sa meniacim zdrojovým faktorom v závislosti od obsahu vody v povodí, ktorý závisí od infiltrácie a je považovaný za faktor, spôsobujúci nelinearitu zrážkoodtokových procesov. Pre kalibráciu a validizáciu modelu boli použité údaje z povodí rieky Amazonka. Použili sme tieto hodnotiace kritériá: Nashov-Sutcliffov koeficient (R²), RMS, Q95%, chyba určenia odtoku v percentách, a priemerná percentuálna chyba v rozsahu od Q5% do Q95%. Kalibrácia a validizácia ukázala, že model simuluje čiary rozdelenia prietokov uspokojivo. Aby bolo možné nájsť najkratšie obdobie pre nájdenia závislosti zrážky - odtok, ktorá je potrebná pre aplikáciu v modeli, použili sme citlivostnú analýzu tak, že údaje zrážky - odtok boli postupne redukované o jeden rok, až kým nebolo nájdené minimálne obdobie pre aplikáciu vzťahu zrážky - odtok 1,5 roka. Toto obdobie zodpovedá jednému hydrologickému roku, plus 6 mesiacov dlhá ''pamäť''. Touto analýzou boli vyhodnotené výsledky terénnych meraní v oblastiach, kde neboli k dispozícii merania odtoku.
The hydrological modeling can be considered as one of major possibilities for the quantification and qualification of changes in hydrological processes. For the application the WetSpa (Water and Energy Transfer between Soil, Plant and Atmosphere) model calibrated for the Hornad River Basin have been chosen. WetSpa simulates the most important hydrological processes in a river basin, such as runoff, actual evapotranspiration, groundwater recharge, and hydrographs at selected locations in the stream network, etc. The application have been done in the frame of the scientific objectives of the Tisza River Project - Reallife scale integrated catchment modelling for supporting water-related environmental management decisions (5th Framework Programme EU on Research and Technology Development). The Department of Hydrology and Hydraulic Engineering, the research unit of the Free University of Brussels (VUB) in cooperation with Slovak Hydrometeorological Institute (SHMÚ) and Water Research Institute in Bratislava (VÚVH) were responsible for calibration, validation and application of the WetSpa model in the Hornad River basin. and Pri hodnotení vplyvu využívania krajiny na priebeh povodní v povodí Hornádu sa aplikoval model WetSpa. Fyzikálne založený model bol vyvinutý na simuláciu a predpoveď prenosu vody a energie medzi pôdou, rastlinstvom a atmosférou (Water and Energy Transfer between Soil, Plants and Atmosphere- WetSpa). Modelové riešenie sa použilo v úlohe 5. rámcového programu EÚ ''Projekt rieky Tisa - integrované modelovanie povodia na podporu rozhodovacieho procesu v oblasti vody a prostredia od nej závislého''. Zodpovedným pracoviskom pre vytvorenie a aplikovanie modelu bolo Oddelenie hydrológie a hydrotechniky Univerzity Vrije v Bruseli. Úlohou spolupracujúcich organizácií zo SR (Slovenský hydrometeorologický ústav a Výskumný ústav vodného hospodárstva) bolo zabezpečiť a poskytnúť vstupné údaje a konzultácie pri kalibrácii modelu a jeho aplikácii.
Predicting snow cover dynamics and relevant streamflow due to snowmelt is a challenging issue in mountainous basins. Spatio-temporal variations of snow extent can be analyzed using probabilistic snow cover maps derived from satellite images within a relatively long period. In this study, Probabilistic Snow Depletion Curves (P-SDCs) and Probabilistic Snow Lines (P-SLs) are acquired from Moderate Resolution Imaging Spectroradiometer (MODIS) cloud-filtered daily snow cover images. Analyses of P-SDCs show a strong correlation with average daily runoff (R2 = 0.90) and temperature (R2 = 0.96). On the other hand, the challenge lies in developing noteworthy methods to use P-SDCs in streamflow estimations. Therefore, the main objective is to explore the feasibility of producing probabilistic runoff forecasts with P-SDC forcing in a snow dominated basin.
Upper Euphrates Basin in Turkey has large snow extent and high snowmelt contribution during spring and summer periods. The melting characteristics are defined by P-SDCs using MODIS imagery for 2001–2012. The value of snow probability maps on ensemble runoff predictions is shown with Snowmelt Runoff Model (SRM) during 2013–2015 where the estimated runoff values indicate good consistency (NSE: 0.47–0.93) with forecasts based on the derived P-SDCs. Therefore, the probabilistic approach distinguishes the snow cover characteristics for a region and promotes a useful methodology on the application of probabilistic runoff predictions especially for snow dominated areas.
Presented study is aimed at using additional information to improve process represen-tativity of hydrological modelling. The study region is the Haute-Mentue catchment lo-cated in the western part of Switzerland, 20 km north of Lausanne. Previous research in this catchment allowed improving of the understanding of the runoff generation by combining point soil moisture measurements (TDR) and integrating measurements both at the hillslope scale (dye tracing) and at the catchment scale (environmental tracing). In this work, environmental tracing information will be integrated into a semi-distributed hydrological model, which is a modified version of TOPMODEL taking into account a rapid stormflow generation above a less permeable soil horizon. Additional information has been incorporated by using a version of simulated annealing adapted for multi-criteria optimisation. and Štúdia je venovaná využitiu dodatkových informácií pri reálnejšej simulácii hydrologických procesov v zrážkovo-odtokovom modeli. Študovanou oblasťou je povodie Haute-Mentue, ležiace v západnej časti Švajčiarska, 20 km od Lausanne. Predchádzajúci výskum v tomto povodí, založený na kombinácii bodových meraní (TDR) a integrovaných meraní v mierke svahu (farbiace skúšky) a povodia (prirodzené stopovače), zlepšil vedomosti o tvorbe odtoku. V tejto štúdii sú informácie získané prirodzenými stopovačmi použité pri posudzovaní výsledkov simulácie odtoku pomocou semidistribuovaného hydrologického modelu (modifikovaná verzia modelu TOPMODEL, ktorá uvažuje s mechanizmom tvorby odtoku nasýtením nad vrstvou pôdy s nižšou priepustnosťou). Ďalšou dodatkovou informáciou boli výsledky automatickej optimalizácie parametrov modelu pmocou metódy vychádzajúcej z analógie medzi optimalizáciou parametrov modelu a rozdelením častíc v tuhnúcej kvapaline (tzv. simulated annealing), adaptovanej na optimalizáciu podľa viacerých kritérií.