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1
Content available remote TRANSCAT DSS architecture and modelling services
100%
EN
The main goal of the TRANSCAT project is to create an operational and integrated comprehensive Decision Support System (DSS) for optimal water management of catchments in borderland regions. The analysis of system requirements was followed by the analysis of possible architecture of the complex system and its appropriate design. The core of the proposed system (ETRA GIS) contains gis-Toolkit, web server, DBS, database interface, web services application interface and remote components. The system utilises selected software tools of hvdrological and hvdrogeological modelling (HEC-HMS, ModFlow, GRASS GIS modules). The special wrappers for each of the model were developed, enabling communication among models. Decision-making is supported by integrated decision applications (mDSS, Mediator, ProDec, BarTend, ArgWar) facilitating mainly the process of evaluation of a wide spectrum of indicators and the process of decision-making. The core of the system utilises a database with special design. The object part of the database represents a data warehouse with multidimensional structure. Implementation of TDSS was undertaken in Bela/Biala Glucholaska (CZ/PL), Pasvik (NO/RUS), Sumava (CZ/D), Mesta/Nestos (BG/GR) and Guadiana (P/ESP) pilot areas, where also respective models were calibrated.
EN
This study aimed to develop a hydrologic model for the central region (central catchments) located between Dokan and Al-Dibis dams in the Lesser Zab River (LZR) watershed, in Iraq. The hydrologic structure of the study area was prepared based on the DEM layer with 12.5 m spatial resolution by using the GIS environment, and then the HEC-HMS software was used for simulating the main hydrological processes like the infiltration losses, transformation, channel routing, and the baseflow contribution by using the SCS-CN, SCS-UH, Muskingum, and the Recession methods respectively. The corrections of the CN parameter due to the effects of the slope and initial abstraction were used and the resulting CN values for the entire LZR watershed were ranging from 56 to 100. This study concluded the effectivity of using the GIS environment and HEC-HMS software in the continuous rainfall-runoff modelling and achieved very good performance with R2 and NSE criteria of 0.9115 and 0.9 under the calibration phase, while 0.925 and 0.91 values were achieved for the same criteria under the validation phase respectively, also the CN was the most sensitive parameter in the proposed hydrologic model.
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2018
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tom no. 36
37--43
EN
Surface runoff is a major problem in urban catchments; its generation is always related to the amount of effective rainfall dropped over the surface, however in urban catchments the process is considerably altered by the emergence of impervious areas. In this study the Soil Consevation Service – curve number (SCS-CN) and the Green–Ampt loss methods were used in rainfall-runoff modelling in the Zaafrania urban catchment which is located in Annaba city in the north east of Algeria. The two loss methods were carried out within Hydrologic Engineering Center – Hydrologic Modelling System (HEC-HMS), the choice of the appropriate method for simulating runoff hydrographs in the study area was made by comparing the simulated hydrographs versus observed data using visual inspection and statistical analysis. The results indicate that SCS-CN loss method fit better in the case of 100 years return period NSE (0.462) than in 10 years NSE (0.346) and the results of calibration of Green– Ampt loss method for the 100 years return period NSE (0.417) provide best fit than the case of 10 years NSE (0.381). Furthermore, the results of both return periods (10 and 100 years) of SCS-CN loss method provide best fit than the results of return periods (10 and 100 years) of Green–Ampt loss method. It could be concluded that SCS-CN method is preferred to the Green–Ampt method for event based rainfall-runoff modelling.
PL
Spływ powierzchniowy jest głównym problemem w miejskich zlewniach. Spływ jest zawsze uzależniony od opadu, jednak w miejskich zlewniach proces ulega znaczącej modyfikacji z powodu obecności powierzchni nieprzepuszczalnych. W badaniach prezentowanych w niniejszej pracy zastosowano dwie metody – SCS-CN (ang. Soil Coservation Service – curve number) i Green–Ampt do modelowania relacji opad–odpływ w miejskiej zlewni Zaafrania na terenie miasta Annaba na północnym wschodzie Algierii. Obie metody realizowano w ramach modelu HEC-HMS. Odpowiednią metodę symulowania hydrogramu odpływu dobrano na podstawie wizualnej oceny i analizy statystycznej. Wyniki dowodzą, że metoda SCS-CN dawała lepsze dopasowanie w przypadku stuletniego okresu powtarzalności (NSE = 0,462) niż w przypadku okresu dziesięcioletniego (NSE = 0,346). Wyniki kalibracji metodą Green–Ampt zapewniały lepsze dopasowanie dla stuletniego niż dla dziesięcioletniego okresu powtarzalności (NSE odpowiednio 0,417 i 0,381). Ponadto wyniki metody SCS-CN dla obu okresów (10 i 100 lat) wykazywały lepsze dopasowanie niż wyniki uzyskane za pomocą metody Green– Ampt dla tych okresów. Można wnioskować, że metoda SCS-CN ma przewagę nad metodą Green–Ampt w modelowaniu relacji opad–odpływ w odniesieniu do poszczególnych zdarzeń.
4
67%
EN
This paper presents an approach to estimating the probability distribution of annual discharges Q based on rainfall-runoff modelling using multiple rainfall events. The approach is based on the prior knowledge about the probability distribution of annual maximum daily totals of rainfall P in a natural catchment, random disaggregation of the totals into hourly values, and rainfall-runoff modelling. The presented Multi-Event Simulation of Extreme Flood method (MESEF) combines design event method based on single-rainfall event modelling, and continuous simulation method used for estimating the maximum discharges of a given exceedance probability using rainfall-runoff models. In the paper, the flood quantiles were estimated using the MESEF method, and then compared to the flood quantiles estimated using classical statistical method based on observed data.
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