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1. Estimation of Evaporation using Penman Open Water Evaporation Equation (Comparative study) | |||
Fathelrahman Ali Mohammed ,Adam Ishag Ibrahim ,Mohamed Abd Allah | |||
Hydraulic Engineering 07 April 2010 | |||
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Abstract:This paper estimate Evaporation ( E0) using the Penman Open Water Evaporation formula and comparing the result with the observed Evaporation for daily meteorological data from xianfeng basin , In this paper the excel program is used to calculate the penman open water evaporation and the daily meteorological weather data recorded for one year ( 2008) were used to obtain the result. The study detects that penman the penman open water evaporation is the best method to estimate (E0). | |||
TO cite this article:Fathelrahman Ali Mohammed ,Adam Ishag Ibrahim ,Mohamed Abd Allah . Estimation of Evaporation using Penman Open Water Evaporation Equation (Comparative study) [OL].[ 7 April 2010] http://en.paper.edu.cn/en_releasepaper/content/41618 |
2. Uncertainty Analysis of Xinanjiang Model using the Monte Carlo analysis toolbox | |||
Fathelrahman Ali Mohammed,Qinbo Chen ,Nabela Hamed | |||
Hydraulic Engineering 22 March 2010 | |||
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Abstract:The consideration of uncertainty in the modeling of hydrological and environmental systems are of increasing importance, and are sometimes even demanded by decision makers. At the same time, the growing complexity of models to represent real-world systems makes it more and more difficult to understand model behavior, sensitivities and uncertainties. The Monte Carlo Analysis Toolbox (MCAT) is a Matlab library of visual and numerical analysis tools for the evaluation of hydrological models. Input to the MCAT is the result of a Monte Carlo or population evolution based sampling of the parameter space of the model structure under investigation. The MCAT can be used off-line, i.e. it does not have to be connected to the evaluated model, and can thus be used for any model for which an appropriate sampling can be performed. The MCAT contains tools for the evaluation of performance, identifiability, sensitivity, predictive uncertainty and also allows for the testing of hypotheses with respect to the model structure used. And in this paper we used MACT to check and know which parameters is very sensitive in Xinanjiang model and six years of daily streamflow, precipitation, and potential evapotranspiration data from the Xingfeng Watershed located in south of china have been used | |||
TO cite this article:Fathelrahman Ali Mohammed,Qinbo Chen ,Nabela Hamed. Uncertainty Analysis of Xinanjiang Model using the Monte Carlo analysis toolbox[OL].[22 March 2010] http://en.paper.edu.cn/en_releasepaper/content/40971 |
3. THE COMPARISON BETWEEN WinBTOPMC AND XIN’ANJIANG MODEL | |||
Xin Penglei | |||
Hydraulic Engineering 10 January 2008 | |||
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Abstract:The Xin’anjiang model is used widely and perfected in China during the last thirty years, and WinBTOMC model is refers to the Blockwise application of TOPMODEL, which needs more high resolution hydrologic data and seems have a better performance. This study compared these two models on a same semi-arid basin, and the result is: the Xin’anjaing model performed much better than the WinBTOPMC model on yearly data while the WinBTOPMC model performs well on monthly metrological data. | |||
TO cite this article:Xin Penglei. THE COMPARISON BETWEEN WinBTOPMC AND XIN’ANJIANG MODEL [OL].[10 January 2008] http://en.paper.edu.cn/en_releasepaper/content/17954 |
4. Application of a distributed hydrologic model-BTOPMC in the Yellow River | |||
Li Qiaoling | |||
Hydraulic Engineering 16 May 2006 | |||
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Abstract:Nowadays, many researches focus on the distributed hydrologic process, for it is regarded as more physically and much closer to reality. Based on the digital elevation model, the flow direction and contributing area can be generated for the Lingkou Basin in the upper area of Luo River located in the Yellow River. The basin is divided into two blocks, BTOPMC Model has been performed on each block based on grids. The hydrometeorological data in special file format are taken as the input, the flow routing is done by Muskingham-Cunge method based on grids. The grid-by-grid spatial variability in soil and land cover properties is considered in calibrating parameters. The results show that the spatial properties can be described distinctly, which lays foundation for the further researches on distributed hydrologic process. | |||
TO cite this article:Li Qiaoling. Application of a distributed hydrologic model-BTOPMC in the Yellow River[OL].[16 May 2006] http://en.paper.edu.cn/en_releasepaper/content/6635 |
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