Showing 5 results for Vaziri
J. Niazi, H. R. Fooladmand, S. H. Ahmadi, J. Vaziri,
Volume 9, Issue 1 (spring 2005)
Abstract
A research was conducted in Fars province Agricultural Research Center in Zarghan area from 1999 to 2002 to determine the water requirement and crop coefficient of wheat, applying lysimeter.
The results indicated that the water requirements of wheat were 720, 712 and 674 mm in the years of 1999-2000, 2000-2001 and 2001-2002, respectively. Using Penman-Monteith method for estimating reference crop potential evapotranspiration, the crop coefficients for wheat at a four-stage crop growth were 0.37, 0.64, 1.10 and 0.51, respectively. Due to the inaccessibility of the whole weather data, we tried to figure out a solution to determine wheat water requirement to schedule irrigation planning for future. In this respect, we made use of a ten-day class A pan mean evaporation and crop coefficient.
S. F. Mousavi, H. R. Vaziri, H. Karami, O. Hadiani,
Volume 22, Issue 1 (Spring 2018)
Abstract
Exploitation of dam reservoirs is one of the major problems in the management of water resources. In this research, Crow Search Algorithm (CSA) was used for the first time to manage the operation of reservoirs. Also, the results related to the exploitation of the single-reservoir system of Shahid-Rajaei dam, located in Mazandaran province, northern Iran, which meets the downstream water demands, were compared to those obtained by applying the Particle Swarm and Genetic algorithms. Time reliability, volume reliability, vulnerability and reversibility indices, and a multi-criteria decision-making model were used to select the best algorithm. The results showed that the CSA obtained results close to the problem’s absolute optimal response, such that the average responses in the Crow, Particle Swarm and Genetic Algorithms were 99, 75 and 61 percent of the absolute optimal response, respectively. Besides, except for the time reliability index, the CSA had a better performance in the rest of the indices, as compared to Particle Swarm and Genetic Algorithms. The coefficient of variation of the obtained responses by CSA was 14 and 16 times smaller than the Genetic and Particle Swarm Algorithms, respectively. The multi-criteria decision-making model revealed that the CSA was ranked first, as compared to the other two algorithms, in the Shahid-Rajaei Reservoir's operation problem.
K. Ghaderi, B. Motamedvaziri, M. Vafakhah, A.a. Dehghani,
Volume 25, Issue 4 (Winiter 2022)
Abstract
Proper flood discharge forecasting is significant for the design of hydraulic structures, reducing the risk of failure, and minimizing downstream environmental damage. The objective of this study was to investigate the application of machine learning methods in Regional Flood Frequency Analysis (RFFA). To achieve this goal, 18 physiographic, climatic, lithological, and land use parameters were considered for the upstream basins of the hydrometric stations located in Karkheh and Karun watersheds (46 stations with a statistical length of 21 years). The best Probability Distribution Function (pdf) was then determined using the Kolmogorov-Smirnov test at each station to estimate the flood discharge with a return period of 50-year using maximum likelihood methods and L-moments. Finally, RFFA was performed using a decision tree, Bayesian network, and artificial neural network. The results showed that the log Pearson type 3 distribution in the maximum likelihood method and the generalized normal distribution in the L moment method are the best possible regional pdfs. Based on the gamma test, the parameters of the perimeter, basin length, shape factor, and mainstream length were selected as the best input structure. The results of regional flood frequency analysis showed that the Bayesian model with the L moment method (R2 = 0.7) has the best estimate compared to other methods. Decision tree and artificial neural network were in the following ranks.
M.a. Mohammadi, H. Ebrahimnezhadian, M. Asgarkhan Maskan, V. Vaziri,
Volume 26, Issue 2 (ُSummer 2022)
Abstract
The study of annual damage statistics due to floods in Iran and the world shows the extent of flood damage to natural and human resources in different regions. Determining the flood zone of rivers in order to protect national resources and reduce flood damage provides the possibility of protecting the river from encroachment and the construction of any unauthorized facilities in it. Therefore, in the present study, the capability of numerical models in simulating the flood zone of rivers was evaluated in the range of Azarshahr Qushqura river and the two-dimensional hydraulic model HEC-RAS 5.0.7 and one-dimensional HEC-RAS model were compared. Changes in the hydraulic characteristics of the flood flow including depth and velocity of the flow at different cross sections of the models were evaluated. The results showed that the water surface level (flow depth) of the two-dimensional model HEC-RAS compared to the one-dimensional model had the lowest error as compared to other hydraulic parameters of flood flow. The two-dimensional HEC-RAS model showed the highest error rate in the flow velocity parameter in comparison to the one-dimensional model. The results indicated that two-dimensional HEC-RAS model V5.0.7 determined the surface of the flood zone 12.46 % more than the one-dimensional HEC-RAS model. The confirmation of the resulting zones on the current state of the river and comparison with the river aerial photo of 1346 indicated the higher accuracy of the two-dimensional HEC-RAS model in estimating the flood zone of the river.
H. Nazaripour, M. Hamidianpour, M. Khosravi, M. Vazirimehr,
Volume 26, Issue 4 (Winiter 2023)
Abstract
In this study, the decade variability of frequency and severity of drought in Iran has been investigated. The one-month scale data from the standardized precipitation-evapotranspiration index (SPEI 01) in the period 1956 - 2015 have been used. Based on the common numerical thresholds, the characteristics of the frequency and severity of drought for each pixel have been calculated and they are the basis for the analysis of the drought situation. Then, the frequency of drought severity classes was calculated and its trend was investigated using the non-parametric Mann-Kendall test. The findings indicated the spatio-temporal variability of drought frequency and intensity patterns in Iran. The frequency of mild droughts has decreased from south to north and from east to west; while the frequency of more severe droughts has increased from north to south and from west to east. The frequency of mild droughts in the southeast, northwest, and northeast has increased by 5 to 40 percent. While the frequency of more severe droughts in most parts of Iran has increased between 10 and 20 percent. Variability in the frequency of more severe droughts is more pronounced in the Central Plateau catchment area as well as in the Persian Gulf-Oman Sea. The trend of drought intensity is decreasing (drought intensification) at the same time as the prevailing rainfall regime in Iran. A significant increase in drought intensity (wet season intensification) is observed only in southeastern Iran at the same time as the monsoon regime. However, extra-arid and arid regions of southeastern Iran are affected by the frequency and severity of drought and have a high degree of vulnerability.
