مقالههای B. Ghahraman
توجه: محتویات این صفحه به صورت خودکار پردازش شده و مقالههای نویسندگانی با تشابه اسمی، همگی در بخش یکسان نمایش داده میشوند.
اطلاعات انتشار: ششمین کنفرانس بین المللی مهندسی عمران، سال ۱۳۸۲
تعداد صفحات: ۸
A pseudo–distributed Gamma type geomorpho–climatic instantaneous unit hydrograph (GcIUH) method is presented as a physically based technique for modeling of basin runoff. The proposed approach is an out–growth of the research on geomorphological instantaneous unit hydrograph (GIUH), GcIUH and also the effect of path type on distributed runoff generation (Jin model). Velocity effects are virtually eliminated in the proposed approach, incorporating GcIUH and the Gamma function. Green–Ampt infiltration theory is used for a more proper treatment of soil physical behavior to separate excess rainfall values. A representative basin in northern I.R. Iran is selected for actual evaluation of the proposed methodology. The results of the proposed model along with the original GcIUH and both original and modified Jin model are compared with the observed hydrograph data. In all cases the proposed approach has provided peak discharge, time to peak, and volume of surface runoff with higher accuracy. For a number of sub–basins, multi–peaked outflow hydrographs are developed, indicating the effect of individual surface responses with different lag times. The proposed pseudo–distributed approach is a major departure from the lumped nature of the unit hydrograph towards a distributed one<\div>
اطلاعات انتشار: اولین کنفرانس بین المللی و سومین کنفرانس ملی سد و نیروگاههای برق آبی، سال ۱۳۹۰
تعداد صفحات: ۱۲
In this study a Fuzzy Based Model using a Non–Linear Programming to obtain optimal reservoir operation for irrigation of multiple crops is proposed. The reservoir level Fuzzy logic model can extract important features of the system from the inputoutput data set by Non–Linear Programming and represents features as general operating rules. The developed model can serve not only as efficient decision making tool in easy and understandable Fuzzy Inference Systems but also can provide operators with a limited number of the most meaningful operating rules usingClustering–Based approach. The model is set properly in a yearly base and monthlysteps. Results show that the changing trend of water releases in both models is the same with R2 = 0.97. Over the 12 months period, both trends had risen from October to May but since then they had fallen gradually. In general the amount of annual released water in Fuzzy model is almost less than NLP, especially in competitive months, May and June. The percentage of water deficit to the percentage of annual mean water deficit was respectively 0.57 and 0.81 in training and 0.93 and 1.145 in the test stage. The findings suggest that in the year with water deficit the amount of water release in competitive months to increase the Net Benefit should be more considered.<\div>
۳Effect of Short– and Long–term Memory on Trend Significancy of Mean Annual Flow by Mann–Kendall Test
نویسنده(ها): B. Ghahraman
اطلاعات انتشار: International Journal of Engineering، بيست و ششم،شماره۱۰، October ۲۰۱۳، سال ۰
تعداد صفحات: ۱۴
Climate variability and change is threatening water resources around the world. One hundred and fourteen (114) stations from Reference Hydrometric Basin Network (RHBN) around Canada with at least 30 years continuous data (up to 2011) were selected to study the trend in mean annual runoff for different periods of 30 to 100 years in step 10 years by non–parametric Mann–Kendall test. Effect of short term persistent (STP) and long term persistent (LTP) on this test were made through lag 1 serial correlation (r1 ) and Hurst exponent (H), respectively. r1 for about one third of the total cases considered was negative. H, based on “equivalent Normal deviate” (eNv), was slightly right–skewed with minimum and maximum values of 0.20 and 0.87, respectively. About half of the data sets were anti–persistent (H0.5). No regional pattern was found for r1 and H. Based on five stations with around 100 years data it was shown that r1 and H are unstable for record length, roughly, up to 50 years. r1 and H were highly correlated (r=0.86). H from eNd were smaller than H from original data by around 10% with high correlation (r=0.87). Under classic Mann–Kendall trend test, different time periods of different stations showed different trend direction and significancy, which admits for abrupt change in trend direction and significancy for different time periods. On overall, more than 60% of cases there were no significant trends (i.e. p–value>0.1). The number of positive and negative trend, were nearly the same, though fluctuating for different time spans. p–value after pre–whitening was highly correlated with those of before pre–whitening, for both negative and positive trends. There were about 16% of cases that pre–whitening decreased the p–values of the Mann–Kendall trend test, where nearly all of them were negatively trended. The effect of LTP on Mann–Kendall trend test was minor due to inconsistency of originally significant trend case and significant H of greater than 0.5. For recent 30 years length of record (1982–2011), British Columbia is experiencing positive trend in the west and negative trend in the east. Most parts of the New Brunswick are experiencing the positive trend, while negative trend is due to Southeast of Ontario. For the longer duration of 40 years, trend statistics and geographical pattern were changed. While the significant trends are decreased, more significant negative trends are governed over New Brunswick. There is no positive trend in British Colombia in the past 50 years (1962–2011) while there are both negative and positive trends in New Brunswick which negative trends are switched to positive trends in south east of Ontario. For long duration of > 70 years, there are only positive trends in Southeast of Canada (South New Brunswick and South East of Ontario) while central and east of Canada have experienced a negative trend.
۴Predicting Dryland Wheat Yield from Meteorological Data Using Expert System, Khorasan Province, Iran
اطلاعات انتشار: Journal of Agricultural Science and Technology، سيزدهم،شماره۴، Autumn ۲۰۱۱، سال ۰
تعداد صفحات: ۱۴
Khorasan Province is one of the most important provinces of Iran, especially as regards agricultural products. The prediction of crop yield with available data has important effects on socio–economic and political decisions at the regional scale. This study shows the ability of Artificial Neural Network (ANN) technology and Adaptive Neuro–Fuzzy Inference Systems (ANFIS) for the prediction of dryland wheat (Triticum aestivum) yield, based on the available daily weather and yearly agricultural data. The study area is located in Khorasan Province, north–east of Iran which has different climate zones. Evapotranspiration, temperature (max, min, and dew temperature), precipitation, net radiation, and daily average relative humidity for twenty–two years at nine synoptic stations were the weather data used. The potential of ANN and Multi–Layered Preceptron (MLP) methods were examined to predict wheat yield. ANFIS and MLP models were compared by statistical test indices. Based on these results, ANFIS model consistently produced more accurate statistical indices (R2= 0.67, RMSE= 151.9 kg ha–1, MAE= 130.7 kg ha–1), when temperature (max, min, and dew temperature) data were used as independent variables for prediction of dryland wheat yield.
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