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Showing 30 results for Eslamian

R. Malekian, J. Abedi-Koupai, S. S. Eslamian, M. Afyuni,
Volume 17, Issue 63 (Spring 2013)
Abstract

Nitrogen (N) loss from irrigated cropland, particularly sandy soils, significantly contributes to nitrate contamination in surface and groundwater and increases N applications to crops. This is because negatively charged nitrate normally does not have much affinity to soil particles. To retard the movement of nitrate, materials should have high affinity for anions, which most naturally occurring minerals do not have. The cation-exchange properties of natural zeolites can be exploited to modify their surface chemistries so that other classes of compounds, particularly anions and non-polar organics are retained. In this study, the ability to remove nitrate from aqueous solutions with different Cl- concentrations using Iranian zeolite (Semnan) modified by hexadecyltrimethylammonium bromide in millimeter and nanometer particle sizes was determined and the equilibrium isotherms were characterized. The nitrate release as affected by time and ionic strength was also evaluated. It was demonstrated that SMZ is capable of adsorbing more than 60 mmol kg-1 and 80 mmol kg-1 nitrate in millimeter and nanometer sizes, respectively, and adsorbed nitrate can be easily released under different ionic strengths. The millimeter and nanometer-sized SMZ showed 26.7% to 82.3% and 37.8% to 85.5% nitrate removal efficiency, respectively. The average of nitrate released by millimeter-sized SMZ was 6.92 mmol kg-1 in deionized water while it was 14.68, 22.71, and 34.91 mmol kg-1 in releasing solutions with ionic strengths of 0.03, 0.1, and 0.3 M, respectively
Bita Moravejalahkami, Behrouz Mostafazadeh-Fard, Manouchehr Heidarpour, Saeed Eslamian, Jaber Roohi,
Volume 17, Issue 64 (summer 2013)
Abstract

Most furrow irrigation systems have low performance due to deep percolation at the upstream end and tailwater runoff at the downstream end of the field. To eliminate this problem improving furrow irrigation performance is necessary. Since the inflow discharge has high effect on infiltration along the furrow which consequently affects the application efficiency and water distribution uniformity, it would be important to apply different furrow inflow hydrograph shapes based on the field data such as field slope, soil texture and furrow length to save water. To produce different furrow inflow hydrograph shapes, an automatic valve which was connected to a stepper motor was designed to change the inflow discharge with time according to the desired inflow hydrograph shape. The experimental field was located at Isfahan University of Technology. A constant head water delivery system to the furrows including the automatic valve was installed in the experimental field and the tests were conducted for different inflow hydrograph shapes. The comparison of the measured furrow inflow discharges with the simulated furrow inflow discharges produced by the automatic valve showed that the automatic valve can produce different furrow inflow hydrograph shapes with high accuracy.
J. Abedi Koupai, M. Salehi-Sirzar, S. S. Eslamian, J. Khajeali, Y. Hosseini,
Volume 18, Issue 68 (summer 2014)
Abstract

In order to investigate the effect of pest and water stresses on different growing stages of cowpea (Vigna sinensis) and pest occurrence, an experiment was conducted in Khazaneh Research station of Isfahan University of Technology. The experiment was carried out in a factorial complete randomized block design, in two different farms, with and without insecticide application. The treatments included severe water stress (50% water requirement), moderate water stress (75% water requirement) in four stages of cowpea growth, the first stage (from seed germination until flower in, second stage (from flowering until pod-filling), third stage (from pod-filling until harvesting) and the whole period of cowpea growth, in three replications. There was a control treatment in each farm with no stress in the whole period of cowpea growth, in three replications. The results showed that water stress had no significant effect on percentage of protein and mineral material. Result also showed that water stress had a significant effect (P≤ 0.01) on population of insects. Water stress significantly (P≤ 0.01) reduced the population of nymphs and adults of Empoasca decipiens Paoli and leaf minor damages, but water stress increased population of Thrips tabaci Lind. Considering the duration of first stage of growth (63 days), it is concluded that this stage had less sensitivity to water stress than the other stages. In regions, where farmers encounter water shortage for cowpea planting, the best performance can be obtained when moderate water stress (75% water requirement) is applied at the first stage of growth.
R. Malekian, J. Abedi-Koupai, S. S. Eslamian,
Volume 18, Issue 68 (summer 2014)
Abstract

In this study, the effect of clinoptilolite zeolite, as a soil amendment, on the parameters related to water and nitrogen movement in soil was investigated. Parameter and uncertainty estimation in the unamended (control) and amended soil (Z), was performed using the sequential uncertainty fitting algorithm (SUFI-2) which is linked to LEACHN (in the LEACHN-CUP software). The goodness of prediction uncertainty was judged on the basis of P-factor and R-factor. P factor, R-factor, and Nash-Sutcliffe coefficient (NS) was obtained 0.71, 0.76, and 0.92, respectively, in the prediction of the accumulated drainage from control. The results in prediction of the accumulated drainage from Z treatment using hydraulic parameters obtained in control were satisfactory (P-factor = 0.87, R-factor = 0.78, and NS = 0.87). P-factor, R factor, and NS were 0.87, 1.36, and 0.91, respectively, in the prediction of NO3-N leaching at control. According to the P-factor and R-factor values (P-factor = 1, R-factor = 2.46), application of the control parameter ranges in the prediction of NO3-N leaching at Z treatment produced a large uncertainty. By adjusting the parameters in control for zeolite amended soil, the estimated values for denitrification rate, distribution coefficient, and soil/solution NO3-N nitrification rate were greater in zeolite-amended soil compared to control.
J. Abedi Koupai, S. S. Eslamian, S. Y. Hasheminejad, R. Mirmohammad-Sadeghi,
Volume 18, Issue 69 (fall 2014)
Abstract

Phytoremediation models are important to understand the processes governing phytoremediation and the management of contaminated soils. Little effort has been made for evaluating the potential of the phytoremediation of metals based on the mathematical models. Therefore, the purpose of this study was modeling the phytoremediation of the nickel-contaminated soils. For this purpose, a model was recommended for estimating the rate of the phytoremediation of nickel from the soil by means of relative transpiration reduction and concentration of nickel in the plant functions. To evaluate the model, soil was contaminated with different levels of nickel by nickel nitrate. Then, the pots were filled with contaminated soil and Basil (ocimum tenuiflirum L.) seeds were planted. To avoid the dry tension, the pots were weighed and irrigated to the point of field capacity (FC) at short time intervals (48 hours). The plants were harvested in four times. At each harvesting stage, the relative transpiration values and nickel concentration in the soil and plant samples were measured. The performance of the model was evaluated by statistical methods such as Maximum Error, Root Mean Square Error, Coefficient of Determination, Efficiency of Model and Coefficient of Residual Mass. Results demonstrated that in the case of nickel contamination in soil, changes in the relative transpiration of Basil can be measured by the two proposed models and the linear model (R2=0.94) has a better performance compared to the nonlinear one (R2=0.84). Also the model obtained from the combination of linear function and nickel's concentration in soil has a relatively good (R=0.7) fit with the measured values of the remediation rate of nickel in soil.


S. S. Okhravi, S. S. Eslamian, N. Fathianpour, M. Heidarpour,
Volume 19, Issue 74 (Winter 2016)
Abstract

In addition to kinematic description of biological reaction, flow pattern plays an important role in designing constructed wetlands. This study investigates the effects of flow distribution on constructed sub-surface horizontal flow wetland with a length of 26 m, width of 4 m and 1% bed slope in order to understand internal hydraulic functioning patterns. Inlet configuration is selected as a variable parameter. Three different cases of inlet and outlet configurations were 1) midpoint, 2) corner, and 3) uniform. Outlet has been fixed in all configurations. Uranine tracer was used to determine the influences of flow distribution by drawing hydraulic retention time curve in different cases. Results showed that mean residence times for each configuration were equal to 4.53, 3.24 and 4.65 days, respectively.  Retention time distribution curve provided conditions, not only for showing dispersion patterns throughout system but also for interpreting hydraulic parameters like hydraulic efficiency and effective volume. According to the retention time curve, effective volume was 87.5% in configurations 1 and 3, and 62.1% in configuration 2 following numerous short-circuiting ratios. Finally, the best configuration of inlet-outlet layout to improve the performance of effluent treatment and use the geometry effectively was found to be the uniform-midpoint based on physical experiments followed by midpoint–midpoint as the second best.


R. Mollaei, J. Abedi Koupai, S. S. Eslamian,
Volume 20, Issue 75 (Spring 2016)
Abstract

Water scarcity forced farmers to use wastewater as water source, without considering its effects on environment and resultant contamination of soils and plants especially with heavy metals. The objectives of this study are to evaluate the application effects of zeolite as soil amendments on the uptake of Cd by spinach (Spinach Oleares L.) irrigated with wastewater (containing 10 ppm Cd). Different levels amounts of zeoilte (0, 1% and 5% w/w) were added to the soil and the experiment was conducted as a completely randomized design in a green house with 3 replications. The results indicated that, the addition of zeolite 1% (w/w) in soil treated with wastewater reduced cadmium concentration in plant, and consequently the percentage of extractable Cd using DTPA was decreased. However, application of zeolite 5% (w/w) increased the soil salinity, and as a result increased Cd concentration in the plant but this increase was not statistically significant, comparing with control. Spinach biomass did not differ significantly under irrigation with wastewater, but the Cd available in wastewater caused a decrease in Spinach biomass yield.


M. J. Zareian, S. S. Eslamian, H. R. Safavi,
Volume 20, Issue 75 (Spring 2016)
Abstract

This study investigated the effects of climate change on the evapotranspiration amount and water balance in the Zayandeh-Rud river basin. Two important weather stations; Isfahan and Chelgerd stations, located in the East and West of the basin respectively, were selected for investigation in this study. The combination of 15 GCM models were created based on the weighting method and three patterns of climate change including the ideal, medium and critical were defined. Using the proposed patterns, the effects of climate change on temperature and evapotranspiration in Isfahan station and precipitation in Chelgerd station were estimated under the A2 and B1 emissions scenarios. Two indices were considered to determine the sustainability of agricultural water consumption in the study area. Ratio of evapotranspiration in the East part of the basin to precipitation in the West part was defined as EPR index (Evapotranspiration-Precipitation Ratio), and the ratio of maximum agricultural water deficit to the amount of agriculture water need, was considered as maximum deficit index (MD). Results showed that the annual temperature would increase between 0.63-1.13°C in the eastern part of the basin. The west precipitation in the basin would reduce between 6.5-30% in the ideal to critical patterns. Summer season, showed the most amount of increase in the temperature, and winter season, showed the most amount of decrease in precipitation. The A2 emission scenario showed more temperature increase and more precipitation decrease in comparison with the B1 emission scenario and also indicated that the potential evapotranspiration would increase by 3.1 to 4.8% in the basin. The EPR index will increase between 13-52% and MD index will increase between 9-35% in Zayandeh-Rud river basin under different climate change patterns. The results revealed the imbalance between agricultural water use in eastern part and the precipitation in the western part of the basin. In other words, in these conditions, appropriate management strategies and planning should be implemented to ensure the sustainability of water resources in Zayandeh-Rud River Basin.


Sh. Kouhestani, S, Eslamian, A. Besalatpour,
Volume 21, Issue 1 (Spring 2017)
Abstract

This study aims to investigate the changes of minimum and maximum temperature variables under the impact of climate change for time period of 2015-2100 in the Zayandeh-Rud River Basin. The outputs of 14 Global Climate Models (GCMs) under three green-house emission scenarios (RCP2.6, RCP4.5, and RCP8.5) are employed from the Fifth Assessment Report (CMIP5) of Intergovernmental Panel on Climate Change (IPCC). A novel statistical downscaling method using a Bayesian Relevance Vector Machine (RVM) is used to project the impact of climate change on the temperature variables at regional scale. The results of the weighting average of the GCMs show that the various models have different accuracy in the projecting the minimum and maximum temperatures in the study area. The results demonstrate that the MIROC5 and CCSM4 are the most reliable models in projecting the maximum and minimum temperatures, respectively. The highest increase for both maximum and minimum temperatures was obtained in winter.
    On the annual basis, the maximum temperature will increase by 0.18-0.76 °C and 0.25-1.67 °C, respectively, in the near and long-term future periods under different emission scenarios. The annual minimum temperature will increase by 0.28 to 0.82 °C and 0.24-1.56 °C, respectively, in the near and long-term future periods. In a general view, changes in maximum temperature will be slightly higher than minimum temperature changes in the future.
 


Z. Dehghan, S. S. Eslamian, R. Modarres,
Volume 22, Issue 4 (Winter 2019)
Abstract

Regionalization is one of the useful tools for carrying out effective analyses in regions lacking data or with having only incomplete data. One of the regionalization methods widely used in the hydrological studies is the clustering approach. Moreover, another effective factor on clustering is the degree of importance and participation level for each of these attributes. In this study, it was tried to use a broad range of attributes to compare their performance in regionalization. Then, according to the importance and role of each attribute in regionalization, the appropriate weight for each of the attributes in each category was determined using the principal component analysis (PCA) method, and the effect of this weighting in forming the homogenous regions was investigated by the Ward's clustering method. In this regard, the maximum 24-hour rainfall data of 63 meteorological stations located in Urmia Lake Basin (ULB) was used in this study during a time period of 30 years (1979-2008). Furthermore, seven categories of attributes were defined in order to regionalize the rainfall. The results showed that by considering different attributes and combining them with each other, a different clustering is obtained in each category in terms of the number of clusters and stations. Among seven categories of attributes, it was found that the geographical and climatic-geographical categories of attributes showed a more appropriate clustering over the ULB. Additionally, the weighting of attributes could have more effect on improving homogeneity and forming the independent clusters in most cases in terms of the scattering of station and how to locate over the basin.

E. Shrifi Garmdareh, M. Vafakhah, S. Eslamian,
Volume 23, Issue 1 (Spring 2019)
Abstract

Flood discharge estimation with different return periods is one of important factors for water structures design and installation. On the other hand, a lot of rivers existing in Iran watersheds have no complete and accurate hydrometric data. In these cases, one of the suitable solutions to estimate peak discharges with different return periods is the regional flood analysis. In this research, 55 hydrometric stations were used. For this purpose, at first, peak discharges in different return periods were estimated using the EasyFit software. Then, the effective variables on the peak discharges were collected and the input variables of the models were selected by using gamma test with the help of the WinGamma software. Finally, data modeling was performed using the support vector machine, artificial neural networks and nonlinear multivariate regression techniques. Quantitative and qualitative assessment of the results using various indices including Nash-Sutcliffe Efficiency Coefficient (NSC) showed that SVM modeling method had the most accuracy in comparison to the other two modeling methods to predict the peak discharges in the Namak Lake Watershed.

M. A. Amini, G. Torkan, S. S. Eslamian, M. J. Zareian, A. A. Besalatpour,
Volume 23, Issue 1 (Spring 2019)
Abstract

In the present study, we used 27 precipitation average monthly data from synoptic, climatologic, rain-guage and evaporative stations located in Zayandeh-Rud river basin for the period of 1970-2014. Before interpolating, the missing data in the time series of each station was reconstructed by the normal ratio method. Also, for the data quality control, the Dickey-Fuller and Shapiro-Wilk tests were used to check the data stationarity and normality. Then, these data were interpolated by six interpolation methods including   Inverse Distance Weighting, Natural Neighbor, Tension Spline, Regularized Spline, Ordinary Kriging and Universal Kriging; then each method was evaluated using the cross-validation technique with MAE, MBE and RMSE indices. The results showed that among the spatial interpolation methods, Natural Neighbor method with MAE of 0.24 had the best performance for interpolating precipitation among all of the methods. Also, among Ordinary Kriging, Universal Kriging, Spline and Inverse Distance Weighting methods, respectively, Exponential Kriging with MAE 0.54, Quadratic Drift Kriging with MAE of 0.5, Tension Spline with the MAE of 0.54 and Inverse Distance Weighting with the power of 4 with MAE of 0.57 had the least error compared to other IDW methods.

M. Saeidipour, F. Radmanesh, S. Eslamian, M. R. Sharifi,
Volume 23, Issue 2 (Summer 2019)
Abstract

The current study was conducted to compute SPI and SPET drought indices due to their multi-scale concept and their ability to analyze different time-scales for selected meteorological stations in Karoon Basin. Regionalization of SPI and SPEI Drought indices based on clustering analysis was another aim of this study for hydrological homogenizing. Accordingly, to run test through data and determine similar statistical periods, 18 stations were selected. SPI and SPEI values were plotted in the sequence periods graphs and their relationships were analyzed using the correlation coefficient. The results were compared by Pearson correlation coefficient at the significance level of 0.01. The results showed that correlation coefficients (0.5-0.95) were positive and meaningful for all stations and the correlation coefficient between the two indices were increased by enhancing the time-scales. Also, time-scales enhancement decreased the frequency of dry and wet periods and increased their duration. Through regionalization of basin stations based on clustering analysis, the stations were classified into 7 classes. The results of SPEI regionalization showed that the frequency percentage of the normal class was more than those of dry and wet classes.

P. Shojaei, M. Gheysari, H. Nouri, H. Esmaeili, S. Eslamian,
Volume 23, Issue 3 (Fall 2019)
Abstract

Creation and conservation of urban parks is challenging in arid environments where daily thermal extremes, water scarcity, air pollution and shortage of natural green spaces are more conspicuous. Water scarcity in the arid regions of Iran is major challenge for water managers. Accurate estimation of urban landscape evapotranspiration is therefore critically important for cities located in naturally dry environments, to appropriately manage irrigation practices. This study investigated two factor-based approaches, Water Use Classifications of Landscape Species (WUCOLS) and Landscape Irrigation Management Program (LIMP), to measure the water demand in a botanic garden. The irrigation water volume applied was compared with the gross water demand for the period from 2011 to 2013. On average, WUCOLS estimated an average annual irrigation need of 1164 mm which is 15% less than the applied value of 1366 mm while the LIMP estimate of 1239 mm was 9% less than the applied value. Comparison of estimated and applied irrigation showed that a water saving of 9% can be made by the LIMP method. The outcomes of this research stressed the need to modify the irrigation requirements based on effective rainfall throughout the year, rather relying on long-term average data.

A. Alinezhad, A. Gohari, S. Eslamian, Z. Saberi,
Volume 23, Issue 4 (Special Issue of Flood and Soil Erosion, Winter 2019)
Abstract

The evaluation of climate change impact on hydrological cycle includes uncertainty. This study aimed to evaluate the uncertainty of climate change impact on the Zayandeh-Rud Reservoir inflow during the future period of 2020-2049. The outputs of 22 GCM models were used under the three emission scenarios including RCP2.6, RCP4.5 and RCP8.5. The Bayesian Model Averaging (BMA) was used as the uncertainty analysis for weighting the 22 GCM models based on their ability to simulate the baseline 1990-2005 period. Results showed that different GCM models had different abilities in estimating climatic and hydrological variables and the application of uncertainty analysis in climate change studies could be necessary. The monthly temperature in the upstream of Zayandeh-Rud reservoir could be raised by 0.85 to 1 ◦C; also, the precipitation might be increased by 2 to 3 percent. The high flow during winter season will increase under climate change, while the spring and autumn seasons’ low flows are expected to reduce. Additionally, the annual reservoir inflow may decrease by 1 to 8 percent, showing the necessity for change in Zayandeh-Rud reservoir’s rule curve and allocation of water resources.

S. Banihashemi , S. S. Eslamian, B. Nazari,
Volume 25, Issue 2 (Summer 2021)
Abstract

The upcoming climate change has become a serious concern for the human society. These changes, caused and aggravated by the industrial activities of the international community and the increase in the concentration of greenhouse gases in the atmosphere, are seen as a threat to the food security and environment. Temperature change and precipitation are studied in the form of different probabilistic scenarios in order to have an outlook for the future. The present study was conducted to address the effects of climate changes on temperature and precipitation in Qazvin plain in the form of five AOGCMs including Hadcm3, CSIRO-MK3, GFDL, CGCM3 and MICROC3.2, and 3 greenhouse gas emission scenarios of A1B, A2 and B1, based on different possible scenario combinations in the next 30 years, 2021-2050 and 2051-2080 (near and far future). On basis of the study results, all 4 target stations, on average, will have experienced a change between two ratios of 0.5 and 1.4 of  the observed precipitation period  by the end of 2050, and the mean temperature will have had a change  between -0.1 to 1.6 °C, relative to the observed period.  By the end of 2080,  the  precipitation will also have fluctuated between the two proportions of 0.5 and 1.7 times of the observed precipitation period and the mean temperature will touch an increase between 0.6 and 2.6 °C. Both SPI and SPEI indices suggest the increment in the number of dry periods in the near and far future. However, the total number of negative sequences differed considering the 3, 12 and 24-month intervals at the stations level. Given the SPEI index, as compared to the base period, the total negative sequences of drought and number of dry periods will increase at 3 stations of Avaj, Bagh-Kowsar and Shahid-rajaei-powerhouse and decrease at Qazvin station in the future; however, SPI gives different results, such that  for Bagh-Kowsar, there will be an increase in both total negative sequences of drought and number of dry periods, as  compared to the baseline period; three other stations will have more dry periods, specifically, but less total negative sequences. The results reported that the drought events would become severe, and the wet events would become extreme in the future.

Prof. J. Abedi-Koupai, S. Rahimi, S. Eslamian,
Volume 25, Issue 3 (Fall 2021)
Abstract

Changing the date of the first fall frost and the last spring frost is an important phenomenon in agriculture that can be one of the consequences of global warming. Using general circulation models (GCMs) is a way to study future climate. In this study, observations of temperature and precipitation were weighted by using Mean Observed Temperature-Precipitation (MOTP) method. This method considers the ability of each model in simulating the difference between the mean simulated temperature and mean precipitation in each month in the baseline period and the corresponding observed values. The model that had more weight, selected as the optimum model because it is expected that the model will be valid for the future. But, these models are not indicative of stationary climate change due to their low spatial resolution. Therefore, in this research, the outputs of GCM models are based on the three emission scenarios A2 and B1 and A1B, downscaled by LARS-WG for Isfahan station. The data were analyzed by SPSS software at a 95% confidence level (P<0.05). The results indicated that in the Isfahan in the future period 2020-2049 based on the three scenarios, as compared with baseline period 1971-2000, the first fall frost will occur later and the last spring frost will occur earlier. The first fall frost will occur later for 2 days (based on the A1B emission scenario) to 5 days (based on the A2 emission scenario) and the last spring frost will occur earlier for 2 days (based on the and B1 emission scenario) to 4 days (based on the A2 emission scenario). Finally, the best distribution functions for the first fall frost and the last spring frost for the baseline period and under climate change were selected and compared using the EasyFit software.


S. Toghiani Khorasgani, S. Eslamian, M.j Zareian,
Volume 25, Issue 4 (Winiter 2022)
Abstract

In recent decades, water scarcity has become a global problem due to the growth of the world's population as well as the increase in per capita water consumption. Therefore, planning and managing water resources to prevent potential risks such as floods and drought in the future is one of the important measures of water resources management. One of the important measures to avoid potential risks and predict the future is rainfall-runoff modeling. The objective of this study was to investigate the efficiency of the WetSpa hydrological model in estimating surface runoff in the Eskandari watershed, which is one of the important sub-basins of the Zayandehrood watershed. In this study, Daran and Fereydunshahr synoptic stations have been used to collect meteorological information in the Eskandari watershed. Also, to study the flow of the Plasjan river, daily data of Eskandari hydrometric station, located at the outlet of the basin, have been used. Climatic data along with digital maps of altitude, soil texture, and land use were entered as input to the WetSpa model. Finally, the ability of the WetSpa model was evaluated in estimating river surface runoff. The observed flow at the basin outlet in the hydrometric station was used to evaluate and calibrate the model. The model was calibrated for the statistical period (1992-2000) and its validation was performed for the statistical period (2001-2004). In the calibration period, the trial and error method were used to calibrate the model parameters. The simulation results showed a good correlation between the simulated flow and the measured flow. In the present study, the Nash Sutcliffe coefficient in the calibration and validation stages was equal to 0.73 and 0.75, respectively which shows the good and acceptable ability of the model in estimating the surface runoff of the study basin.

S. Parvizi, S. Eslamian, M. Gheysari, A.r. Gohari, S. Soltani Kopai, P. Mohit Esfahani,
Volume 26, Issue 3 (Fall 2022)
Abstract

Investigation of homogeneity regions using univariate characteristics is an important step in the regional frequency analysis method. However, some hydrological phenomena have multivariate characteristics that cannot be studied by univariate methods. Droughts are one of these phenomena their definition as univariate will not be effective for risk assessment, decision-making, and management. Therefore, in this study, the regional frequency analysis of drought was studied in multivariate methods using SEI (Standardized Evapotranspiration Index), SSI (Standardized Soil Moisture Index), and SRI (Standardized Runoff Index) indices in the Karkheh River basin from 1996 to 2019. The indices calculated probabilistic distribution between the variables of evapotranspiration, runoff, and soil moisture using multivariate L-moments method and Copula functions and considered meteorological, agricultural, and hydrological droughts simultaneously. The results of multivariate regional frequency analysis considering the Copula Gumbel as the regional Copula showed that the basin is homogeneous in terms of severity of SEI-SSI combined drought indices and is heterogeneous in terms of severity of SEI-SSI combined drought indices. However, after clustering the basin into four homogeneous areas in terms of characteristics of SPI (Standardized Precipitation Index), the basin is homogeneous in all areas in terms of univariate SEI, SSI, and SRI indices and is heterogeneous in the third and fourth clusters of SRI and SSI drought indices. Pearson Type (III), Pareto, normal, and general logistics distribution functions were found suitable to investigate the characteristics of SEI, SSI, and SRI drought indices in this case. Finally, large estimates of the types of combined droughts and their probability of occurrence showed that the northern and southern parts of the Karkheh River basin will experience short and consecutive droughts in the next years. Droughts in areas without meteorological data can be predicted in terms of joint probability using the multivariate regional frequency analysis method proposed in this study.

V. Rezaei, S. S. Eslamian, J. Abedi Koupai, A. R. Gohari,
Volume 28, Issue 2 (Summer 2024)
Abstract

The relationship between intensity-duration-frequency of rainfall is a significant tool for estimating flood discharge. According to the sparsely available rain gauge stations and the development of technology, it is possible to use satellite rainfall data with different temporal and spatial resolutions. PERSIANN rainfall data with a time resolution of 1 and 6 hours were used in this research. Also, the spatial resolution of these data is 0.04 x 0.04 degrees. Rainfall data from synoptic stations around the Kan basin were also used. Three common continuous probability distributions of Gamble, Pearson type 3, and Log Pearson type 3 with return periods of 2, 5, 10, 25, 50, and 100 years were investigated to calculate and check the IDF curve. In general, the precipitation intensity obtained from Gumble's method was more than Pearson Type 3's method. Log Pearson type 3 distribution did not provide acceptable results in this research. The two interpolation methods of inverse distance weighting and empirical Bayesian kriging were used to generalize the frequency intensity curves to the entire Kan basin. The results showed little difference between these two methods, except for Pearson type 3 probability distribution.


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