ali mohammad akhondali

Drought is a natural disaster which could be repeated, and cause damages in all climates. In Iran, drought has occurred frequently and caused water shortages in different sectors. Fars province geographical location is in the western sought of Iran. Due to the increases cities, villages, industrial and agricultural centers in this province, drought assessment is an urgent need. In this research Z score, Percentage of Normal Precipitation Index (PNPI), Decades of Precipitation Index (DPI), Rainfall Anomaly Index (RAI) and standard precipitation Index (SPI) were evaluated and and compared. Statistical analysis of precipitation showed a stable condition in Doroudzan Dam station and unstable conditions in Lar, Lamerd and Abadeh. Precipitation had a wide variation except in Shiraz, Zarghan and Doroudzan Dam stations, which verifies dominant drought climates in Fars. In order to determine the best index, minimum of rainfall and indicies correlation were used in this study. Results showed that PNPI-Z ,PNPI-SPI SPI-RAI, SPI-Z RAI-Z and PNPI-RAI indices are the most correlated ones, and DPI-SPI , DPI-RAI ,DPI-Z ,DPI-PNPI indices have week correlation. 1 and 12 months average indices showed the most correlation. The results showed that the PNPI, SPI and Z coincided with the date of minimal rainfall, and reported a severe drought in the study stations, therefore they are more efficient than the other indices to determine meteorological drought.

It is necessary to forecast the volume of inflow to reservoir operation in flood conditions, which is of double importance in mountainous basins with a rain-snow regime. The main purpose of the present study was to evaluate the accuracy of GEFSv12 reforecast data as an input to the HEC-HMS precipitation-runoff conceptual model in forecasting and warning issuance for floods entering the Dez dam resrvoir, southwest Iran. For this purpose, after deriving precipitation and temperature parameters (including control values and ensemble members) up to 10-days lead time, the flood ensemble forecast was produced. In the study, in case of exceeding the threshold discharge (1620 and 2640 m3/sec with return period of 2 and 5 years, respectively) by a relative majority of forecasting members, the flood warning was issued. Although, flood forecast in basins with the rain-snow regime is very complicated, the results of evaluation indexes showed that a considerable improvement of forecast accuracy might be expected 5 days ahead (5-days lead time). Then again, there was no direct relationship between the reduction of forecast lead time and the enhancement of forecast accuracy. The results of the probabilistic study of the members’ agreement percent in exceeding the threshold discharge of 2640 m3/sec indicated warning issuance within the forecast lead time of 4-7 days ahead.

Reservoir dams are important structures for surface water harvesting and flood control. Before construction, various studies are carried out in multiple phases to calculate the input to their reservoirs and the volume of stored water. The non-optimal operation of a reservoir dam occurs when the volume of the inflow during operation does not match the volume of the calculated inflow. The water intake systems of dams and their volumes can be measured with different criteria and options. Using the opinions of expert experts and the realism of different technical, economic, and social conditions with different multi-criteria decision-making models in identifying factors affecting the correct inflow forecasting of water harvesting by dams is a common method in water resources management research. In this study, using different multi-criteria decision-making methods including ElectreIII, Entropy, Topsis, SAW, VIKOR, PROMETEE and Fuzzy TOPSIS, the inflow to the reservoirs of 17 dams in Kermanshah province has been investigated. This research is the first research work in the field of evaluating the inflow forecasting to the reservoirs of the dams of Kermanshah province, which, with a comprehensive approach, expresses and examines the most important factors influencing the failure to estimate the optimal inflows to the dam. According to the findings of the research, the option that has more frequency than other options is the proportionality of water allocation in each dam reservoir, in fact, the inadequacy of the amount of water allocation with the objectives of the dam reservoir studies, the time-consuming studies and implementation of the dam cause deviation from the right path. Water harvesting is done in reservoir dams, and the trustees inevitably change the goals of the plan by making interim decisions and even during implementation. Such a process without economic analysis leads to a loss of opportunities and a waste of investments.

The growing population and, consequently, the need to produce crops on the one hand and the limitation of water resources as an important factor in agricultural production have led to the intensification of the problem of dehydration in many parts of the world, including Iran. Therefore, a balance between water resource constraints and agricultural development is essential. In this regard, the International Water Management Organization (IMO) has estimated in its comprehensive assessment that water management in agriculture in rainforests could lead to a 75% increase in global food products (Di Dono, 2009). Therefore, agricultural development through the development of dry land areas can be considered as a logical solution in the context of the water crisis (Akhavan et al. 2013).

In this study, to investigate the effects of land use changes on hydrological components of the Doroudzan Dam basin for the three periods of 1979 to 1990, from 1987 to 1999, and from 1997 to 2006, three land use maps for the years 1986, 1996 and 2005 were prepared. Then, using the semi-distributed SWAT model, the basin hydrology processes were simulated. After calibration to validate the model, validation was performed for each period. The Nash-Sutcliffe coefficient in calibration and validation of the first period was 0.74 and 0.52, in the second period was 0.88 and 0.61, and in the third period was 0.83 and 0.8, respectively. Also, three scenarios were defined to determine the effect of each land use management application in the study time step (1979 to 2006). All the scenarios were simulated under the same conditions for rainfall and temperature and  different land use maps. The impact of land use change under these scenarios is well observed, with the latter having a 27.7% decrease in surface runoff compared to the control scenario, as rangeland, forest, agricultural cover increased, wasteland decreased. Has found. In the third scenario, surface runoff decreased by 13.5% compared to the control scenario, but increased compared to the second scenario, as rangeland cover decreased and wasteland increased.

Today, reducing the vulnerability of urban land uses to reduce the amount of damage is one of the most important objectives that city planners and managers are trying to achieve, which is important by using new approaches to crisis management such as passive defense. It is achievable and can be effective in creating a safe environment in cities. Urban flood risk mapping is a new tool that can be used to identify development sites to reduce public risk and damage to land uses. These maps show the condition of residential areas and other uses in relation to floods and state that flood control operations and flood warning systems should be considered in areas that are highly vulnerable. In this research, flood prone areas in the return period of 2, 5, 25, 50, 100, 200 and 500 years in an interval of 5.8 km from the Dez River bed in the central area of ​​Dezful city using HEC-RAS model and ArcGIS software was prepared, for this purpose digital maps with 10 meters accuracy, discharge statistics of Dezful regulatory dam hydrometric station and river morphology features were used in the study area. Since the Dez river basin is a flood zone with a return period of 25 years, the results showed that the maximum depth and speed of water during the flood with a return period of 25 years are 19.47 m and 7.43 m/s, respectively. For the return period of 2, 5, 25, 50, 100, 200 and 500 years, 65.6, 106.3, 1.154, 1.168, 180.6, 192.4 and 208 hectares under flood cover, respectively. It is decided that due to the existence of residential areas and resort uses on the banks of the river, it is necessary to carry out flood control operations and flood warning systems in the parts where more vulnerability is predicted, and in order to Necessary measures should be taken to remove the illegal possessions that have taken place in the bed and privacy of the Dez river.

In any country, the management of water resources in watersheds is very important, and managers try to protect these resources by providing management packages. One of the basins that have been considered by managers in the recent years is the catchment area of Lake Urmia located in the northwestern of Iran. In this study, considering the complexity of the rainfall, temperature, evaporation, discharge of hydrometric stations, water volume of the Lake, the contribution of each factor on the rate of decreasing water volume of Urmia Lake was determined. To evaluate the changes in complexity, Wavelet-Entropy combination method was used. To calculate the value of complexity, 41 years seasonal time series were used (period of 1977-2018) for the selected hydrological units of the south and west of Urmia lake. Then, the time series were divided into three equal parts, and the complexity changes were calculated in these intervals based on the wavelet-entropy criterion (SWS). The results showed that SWS of lake water volume, rivers discharge flow and precipitation were reduced in entire time, however, the SWS of temperature and evaporation increased. Generally, it seems that the rivers discharge flow was the main cause of reducing the volume of lake water, and precipitation, temperature, and evaporation parameters were in the next ranks.

Pressurized irrigation methods can be a suitable solution for optimal use of water resources, provided that the selection, design, implementation and operation of irrigation systems are done with sufficient care and according to the principles. In decision-making and implementation of pressurized irrigation systems at the sub-regional and regional scale, several factors such as water, soil and climate along with socio-economic factors are of particular importance. Dez Plain (including Lor, Dimcheh, West Dez, East Dez and Sabili plains) is the largest plain and one of the most important agricultural hubs in Khuzestan Province. In this study, using AHP in GIS software, the suitability of various areas for implementing different irrigation systems (localized, solid set, wheel move, centre pivot, linear, Gun, low-pressure, and surface) was investigated in Dez Plain. For this purpose, effective criteria including socio-economic and field physical conditions were considered for implementation of each irrigation method. Socio-economic criteria included four sub-criteria, namely, operation and maintenance, costs, laborers skills, and local culture, and physical conditions included water, climate, soil, and topography. The final location map was prepared in GIS software. According to the results, Dez Plain areas with high suitability for each methods were as follows: 62.77% for all sprinkler systems, 14.6% for localized irrigation, 14.3% for low-pressure irrigation, and 8.3% for surface irrigation. Among all irrigation methods, the solid-set sprinkler obtained the highest score in all parts of the study area and, in total, 15.04% of the whole plain is highly suitable for this system.

Estimation of sediment transported by the streamflow is important for planning and storing water resources of dam reservoirs and river bed changes, watershed management, coastal protection and the environment. Sediment transport in the river is an inherently uncertain and complex phenomenon. Incomplete knowledge of processes and data create uncertainty in estimating sediment transport. Parameters uncertainty is one of the main sources of uncertainty in estimating the suspended and bed sediment load. In this paper, the Monte Carlo (MC) simulation method is used to estimate the uncertainty of suspended and bed sediment load due to uncertainty in the parameters of the support vector machine (SVM) model in the Karaj Dam Basin. The partial mutual information (PMI) algorithm was used to select the efficient input variables in the SVM model to estimate the suspended and bed sediment load. The results of using PMI algorithm show that the only efficient variable in estimating the suspended and bed sediment loads is the current stream discharge. The results show that the uncertainty in estimating the suspended sediment load with SVM model for training, test and total data is equal to 12.8%, 17% and 13.5%, respectively. Also, the uncertainty in estimating the bed sediment load with SVM model for training, test and total data is equal to 23.5%, 36.8% and 27.2%, respectively. Therefore, the uncertainty in estimating the bed sediment load with SVM model is more than the one in estimating the suspended sediment load. Therefore, the use of optimization methods can be useful for accurate estimation of parameter values and reducing uncertainty in estimating the suspended and bed sediment load.

This study presents a novel approach for real-time flood control by optimizing operation of a reservoir during the flood. However, the fundamental operational challenge of using this method is to determine optimized decisions of the reservoir management before the occurrence of flood, and optimal use of the pre-release to reduce the flood damages. In addition to this optimization challenge, since the timely forecasts are derived by employing the probabilistic methods, they would always associate with uncertainty. As a result, quantifying and considering these uncertainties in the flood control would result in reducing the risk of flood damage that can be evaluated by minimizing the expected value of the damage. Timely and continuous forecasting of inflow and reservoir operation management will be implemented before the occurrence of flood until it ends. In order to address the above challenges, a novel simulation-optimization methodology, by taking into account uncertainty, is developed; and illustrated on a case study of Dez reservoir, as a highly important reservoir system in south-west of Iran, to optimize the performance of this reservoir, during the floods. Accordingly, a new water resource management has been proposed and tested. The results derived from the proposed method, indicate a significant reduction in the peak release from the reservoir and the improved operation of the Dez reservoir in controlling the flood at real-time, which will reduce damages in the downstream area.

In the present study, the effect of elevation on the performance of PERSIANN and PERSIANN-CDR satellite precipitation algorithms in Helleh basin has been investigated. Satellite precipitation data with spatial resolution of 0.25⁰ in longitude and latitude, compared with 114 rain gauge stations data during a fourteen year period (2003- 2016). Also, with the use of errors zoning in the basin area, the effect of elevation on the performance of the satellite precipitation algorithms was investigated. The results showed that the PERSIANN algorithm is underestimate on different temporal and spatial scales and it had a little accuracy. In contrast, the PERSIANN-CDR algorithm was more accurate. However, the performance of the adjusted algorithm is unacceptable at daily scale. The determination coefficient of the adjusted algorithm was 0.7588 and 0.9446, monthly and annual at the cell scale respectively. Intensity-Duration-Frequency of curves The three types of data sources show that both algorithms unserestimate rainfall values at different times during different Frequency and at different times than observational values. The spatial distribution of errors of satellite precipitation algorithms relative to basin elevation showed that in both algorithms, the RMSE value increases from low to high elevation. It is recommended to be more cautious in the use of satellite precipitation algorithms for estimating precipitation in high altitudes, and in addition to applying cloud properties to satellite imagery, a correction for altitude classes should also be considered. It is recommended to be more cautious in the use of satellite precipitation algorithms for estimating precipitation in high altitudes,

The reliability and validity of extreme floods, especially the probable maximum flood (PMF), requires to consider uncertainty sources in flood estimation. Parameters uncertainty of rainfall-runoff models are the main sources of uncertainty in flood estimation. In this paper, the Monte Carlo method has been used to estimate the PMF hydrograph uncertainty due to uncertainty in the calibration parameters of the rainfall-runoff model in Bakhtiary Basin in southwestern of Iran. The HEC-HMS hydrologic model was used to estimate the PMF hydrograph resulted by the probable maximum precipitation (PMP). The SCS curve number, Clark's unit hydrograph and Muskingum methods were used to model losses, rainfall-runoff transform and river flood routing, respectively. The results show that the uncertainty in peak discharge and volume of PMF hydrograph due to the uncertainty of all parameters are 17.13 and 6.79%, respectively. The results showed that the uncertainty in peak discharge and PMF hydrograph volume due to uncertainty of all parameters are 17.13 and 6.79 percent respectively. The uncertainty in peak discharge of PMF hydrograph due to curve number, initial losses, concentration time, Clark's storage coefficient, Muskingum K and Muskingum X parameters are 5.05, 0.4, 3.78, 3.85, 4.05 and 0.01 percent respectively. Also, the uncertainty in the PMF hydrograph volume due to the uncertainty of the curve number, initial losses, concentration time, Clark's storage coefficient, Muskingum K and Muskingum X parameters were 4.46, 0.332, 0.328, 1.6, 0.08 and 0.0002 percent respectively. Therefore, in order to reduce the uncertainty in estimating PMF hydrograph, it is necessary to be more precise in estimating the parameters of curve number, Muskingum K, Clark's storage coefficient and concentration time, respectively.

Nowadays, monitoring of river quality information is one of the most important issues in water resources engineering because of the direct relationship of water quality with environmental health and quality of life. Today, traditional methods of river monitoring are receiving less attention due to the fact that they are costly and time-consuming for the researcher. Instead, the recent, low-cost methods are favorable to many researchers in this filed. Different methods have always been considered for river monitoring, but the application of spectral indicators and remote sensing technologies to control and monitor the water quality of rivers and reservoirs is very cost-effective and could be a good alternative to traditional methods. Since it is time-saving and less costly, it would be a good indicator for the whole region and a good alternative to manual methods (Bonansea et al., 2015). Although satellite imagery has been widely used in estimating water quality indices (Onderka and Pekárová, 2008), the complexity of hydrological systems and the presence of noise in images can increase the calculation error. Wavelet transform and intelligent models are among the most efficient methods that can significantly increase computation accuracy by filtering and noise reduction. Good research has been done on the use of wavelet transform in image processing (Graps, 1995) and fuzzy inference system to estimate water quality parameters (Solgi et al., 2017). In this study, using wavelet transform, Landsat 8 images were processed, then the processed images were considered as inputs of ANFIS model.

The reliability and validity of extreme floods, especially the Probability Maximum Flood (PMF), cannot be ensured without considering the uncertainties in flood estimation. Input variables in rainfall-runoff models include precipitation, air temperature, and initial Snow Water Equivalent (SWE) are sources of uncertainty in flood forecasting and estimation. In this paper, the fuzzy set theory method is used to propagate uncertainty of PMP, air temperature and initial SWE for estimating PMF in Bakhtiari Dam Basin in southwestern Iran. The results show that the uncertainty of PMF hydrograph peak discharge due to uncertainty of PMP is more than the uncertainty of PMF hydrograph volume. The uncertainty of the PMF hydrograph volume due to the uncertainty of air temperature and initial SWE is more than the uncertainty of the PMF hydrograph peak discharge. So that the uncertainty of PMF hydrograph peak discharge due to uncertainty in PMP, air temperature and initial SWE equal to 10% were ±10.2%, ±7.6% and ±0.18% respectively. Also the uncertainty of PMF hydrograph volume due to uncertainty in PMP, air temperature and initial SWE equal to 10% were ±8.0%, ±9.8% and ±0.35% respectively. Therefore, in order to reduce the uncertainty in estimating PMF, it is necessary to be more careful in estimating PMP, air temperature and initial SWE values respectively.

Recent advances in numerical weather and seasonal forecasts ,make the water resources manager and operators very interested to involve the forecasts in real operation.Generally in the studies, the skill assessment of the forecasts would be done by comparing the forecasts with station gauge or gridded data which maight not reflect the real skill of the forecasts in basin scale. In this paper , the forecasts generated by the Noaa climate forecast system version 2( CFSv2) were evaluated in the Dez dam basin. A combination of rain gauge data with satelite base precipitation estimates( Persiann-CDR) were used as the basis of evaluation. Result showed monthly precipitation forecasts with lead 1 has the best performance based on R and ROCauc although the underestimation is higher than other leads. Evaluation of the forecasts in 3 different percentile including below normal, normal and above normal, showed well performance in percentiles above 0.6 and below 0.4, also best monthly forecast performance with lead1 was 0.88 for Nov, 0.66 for Dec and 0.8 for Mar respectively for percentile of category 1 to 3 based on ROCauc. Winter precipitation evaluation based on the SPI with 5 category, suggested that 50 to 60 percent of the times, the exact category was truly predicted while with on category difference the accuracy imrove up to 80 percent of the times.

Reservoirs of hydropower plants have a significant impact on water shortages as large amounts of water evaporate from the surface of the reservoirs and become out of reach. This is a major issue in hydrology and water resources, which results in the availability of water resources. In this regard, the concept of water footprint was used to calculate the water consumed in the process of generating electricity from these plants. In this study, to calculate the water footprint in electricity produced in hydropower plants of the country, data on the annual evaporation volume (m3) and annual electricity generation (m3/TJe) from 17 hydropower plants in Iran for the period of 2010 to 2017. The results showed that on average, the largest water footprint in electricity produced by Droudzan power plant was 287649 (m3 / TJe) and the lowest was related to Masjed Soleyman power plant and equal to 405 m3 / TJe. The average water footprint in electricity production from Iranian hydropower plants was estimated at 6132 (m3 / TJe).

The present study aims to determine the annual water footprint trend of wheat production in Esfahan province during the period 1982-2016. In order to investigate the trend of water footprint time series of wheat production, Mann-Kendall Trend test and Sen's slope estimator were used. After ranking the cities from the point of view of the water footprint and water footprint trend, using the Social Choice Rules (SCR), the best city for wheat cultivation was identified in Esfahan province. The results showed that the average total water footprint of wheat production in Esfahan province was 4122.73 m3/ton and according to Mann-Kendall statistics, there is a decreasing and increasing trend and this trend was significant for the Fereidan, Fereydun Shahr and Isfahan cities at a level of 90%. The results also indicate that the low amount of water footprint indicator or the decreasing trend of this indicator in producing a product in a region is not an acceptable criterion for choosing that area for cultivating that product and by using bargaining simulations such as social choice rules, it is possible to identify the best region for cultivating each product and to change the pattern of cultivation in its policy of work to preserve water resources and increase productivity. In this study, from the point of view of the water footprint, Fereydun Shahr was selected as the best city for wheat cultivation in Esfahan province

Evaluation of the interactions between surface water and groundwater in order to efficiently manage water resources is essential. Having Dezful-Andimeshk plain as the largest and the most important agricultural plain in Khuzestan province and also experiencing increasing demand in surface water and groundwater resources in the agricultural use, affirm that the assessment of the relationship between aquifers and rivers for the proper management of water resources is of great importance. In this study Cluster analysis has been performed to determine the interactions between groundwater resources and surface waters in the designated plain. In this paper, the qualitative parameters of 37 groundwater wells and 3 hydrometric stations related to Shavour, Dez and Karkheh rivers were investigated in normal, dry and wet periods. The parameters are: EC (Electrical conductivity), main cations (Ca2 +, Mg2 +, Na+, K+) and major anions (Cl-, HCO3-, SO42-). Then, through using cluster analysis, the similarity between stations was determined, the dendrogram indicated three distinct groups, the first group demonstrated the similarity between the Shavour river, Dez river and the right-hand seafront aquifer, the second group of the qualitative repository wells the southern plain and the third group reflected the similarity of the Karkhe River with the wells around the river. Results have shown that discharging the Dez River directly affects the quality of the aquifer in the plain, and it seems that the Karkheh River has the least similarity to the surface water and groundwater resources in the plain.

Drought risk management requires a strategy. Choosing a spatial scale is one of the strategic aspects. In the present study, drought monitoring was carried out at sub-basin scale and for dry lands products. For this purpose, using the SWAT simulator, the Khorramabad basin with a total area of 2480 km2 was divided into 31 sub-basins based on homogeneity of soil texture, land use and elevation. The RDI Drought Detection Index was calculated on a 9-month time scale for assessing agricultural drought during the period of 1348-1396, in accordance with the crop year. Using Thiessen method and the use of meteorological stations in the studied area, rainfall and temperature of each sub-basin, the estimation and relative reduction of yield of dryland products were calculated for each of the different drought intensities. The present study was able to compare the different areas of the basin with respect to the drought risk in different products. So that the risk of product production varies from 14 to 30 percent in each sub-basin. The average risk of producing dryland products including wheat, barley, peas and lentils was 21.2%, 18.8%, 17.4% and 18%, respectively. The results also showed that the effect of drought severity on the yield of each product is different. So, in the middle drought, 54-60, 47-55, 46-54, 47-57%, severe drought, 63-70, 58-64, 49-60, 51-62% and very severe drought, 75-82, 69-74, 59-68, 67-74%, reduced potential yield of each product, respectively, wheat, barley, peas and lentils respectively.

Estimating air temperature plays an important role in many water and energy balance calculations, hydrological modeling, meteorological and agricultural studies. Changes in air temperature influence on plant growth and many other components at the interface between earth surface and atmosphere. The most common sources for air temperature time series are meteorological stations. However, meteorological networks are sparse in complex terrains, such as mountains. This is mainly due to difficulties with the installation and maintenance of the stations. The air temperature can also be calculated using climate model and reanalysis datasets. The purpose of this study was to introduce two meteorological reanalysis databases: the European Center for Medium-Range Weather Forecasts (ECMWF) and Modern-Era Retrospective Analysis for Research and Applications (MERRA), and evaluation of their performance in estimating daily maximum, minimum and average air temperature. In this regard, maximum, minimum and average air temperature data at daily scale for a period of 14 years from 2003 to 2016 (5114 days) were obtained from 12 temperature measurement stations in Helleh river basin area in south of Iran and the Persian Gulf coasts. The elevation correction and downscaling temperature based on modeled lapse rate are used for correcting two meteorological reanalysis datasets. The correlation coefficient (CC), mean error (ME) and squared mean of errors (RMSE) were used to evaluate the presented datasets. The results showed that the compliance rate of reanalysis datasets in all parameters of maximum, minimum, and average air temperature are appropriate, but the ECMWF-ERA-Interim version dataset is much better than the MERRA version 2 dataset. The correlation coefficients for all parameters of maximum, minimum and average air temperature are more than 0.9. Also, the performance of both datasets in estimating the average air temperature at daily scale is better than the maximum and minimum air temperature at daily scale. Both databases are also underestimated in estimating maximum temperature data and overestimated in estimating minimum data. The average air temperature at daily scale is estimated slightly warmer (0.4°C) from the ECMWF-ERA-Interim version dataset, while the MERRA dataset of version 2 estimates the mean of air temperature colder (-0.5°C). Finally, the use of daily air temperature parameters (maximum, minimum and average) of the ECMWF ERA-Interim dataset is more preferable than MERRA version 2 dataset. Considering the proper performance of reanalysis datasets and using their advantages, we suggest evaluating other meteorological parameters.

Precipitation is a major component of the hydrological cycle, which has significant changes in location and time. The lack of suitable data for this parameter causes a problem in hydrological forecasts. Since satellite data provides a new solution for estimating rainfall with spatial and temporal variation, this study evaluate the accuracy of some of these data types, including high-resolution spatial data consist of ERA-Interim, CHIRPS and PERSIANN-CDR at the upstream of the Maroon Dam on daily, monthly and annual timescales. In order to evaluate gridded precipitation data and observational data from 2003 to 2014, it was considered. The results show that estimation of the annual rainfall data of the gridded precipitation models is underestimated and estimates the average annual precipitation less than the mean annual observational precipitation. In the estimation of monthly precipitation with regard to the Nash-Sutcliff coefficient at Dehno, Idenak and Margoon stations, the ERA-Interim model and at the Ghale-Raeesi station CHIRPS model indicate the best performance compared to other models. In the daily rainfall estimation, like the monthly rainfall, the best estimate at the Idenak station is the ERA-Interim model, which has a NSE of 0.63 and the best estimate of precipitation in all stations is by ERA-Interim. ERA-Interim has the best performance from the 3 gridded models in the correct detection of rainy days. The best performance of this model is in determining the correct rain days with POD = 0.53 at Idenak station.

Drought is one of the extreme events that can impact vast areas gradually over time. Also understanding the implications of climate change on drought is important for water resources management in order to manage the available water resources in the basin appropriately. Having better understanding of drought condition, drought indices were developed. Several drought indices are used for identifying and quantifying droughts that among them the standardized precipitation index (SPI) provides proper results. Based on each drought indices, drought characteristics can be calculated namely drought duration and drought severity. Drought characteristics are highly correlated to each other. Trusting on one of the drought characteristics for managing the water resources may lead to inappropriate understanding of drought condition. Therefore, it is important to notice all characteristics together by using a joint distribution function that among them copula function is prevalently used in hydrology studies. Several studies were examined the impact of climate change on the drought conditions by using different drought indices in many basins in the word and Iran (Bazrafshan et al., 2015, Kouchaki ei al. 2007, Mahsafar, 2011, Eghtedarnejad et al., 2016, Naserzadeh and Ahmadi, 2012, Hoffman et al., 2009, Kirono et al., 2011, Selvaraju and. Baas, 2007, Lee et al., 2013, Serinaldi et al., 2009, Mirabbasi et al., 2013). There have been many studies which using copula function in order to compute the return period of the drought (Abbasian et al., 2014, Golian, 2010, Serinaldi et al., 2009, Mirabbasi et al., 2016, Maddadgar and Moradkhani, 2011, Chen et al., 2011). Therefore, in this study drought condition was analyzed by using copula under climate change condition to have a better understanding of future drought situation and the return periods of drought events in the future. The SPI was used to extract the drought duration and drought severity in the ZayandehRoud River basin for a historical period (1979-2008), and the far future (2058-2099) by using 15 GCM models from the IPCC Fifth Assessment Report (AR5) scenarios. A significant past drought event in the basin was used as a benchmark with severity of -4.39 and duration of 6 months. The Archimedean and Elliptical families of copula functions were used to construct the joint distribution functions for evaluating the drought return periods in the basin. Results from historical analysis show that the return period of significant past drought is about 5 years and this period will increase to about 25 years in the future.

Recently, the use of copula functions as a practical and flexible tool for constructing joint probability distribution of multivariate hydrologic phenomena, such as flood, has attracted great attention of hydrologists. The main objective of this study is to extract and analysis of the joint and conditional return periods of some dependent characteristics of runoff hydrograph, including runoff volume, peak discharge, base time and time to peak discharge. These characteristics extracted from 60 flood events recorded in Valikbon hydrometric station, located in outlet of Kasiliyan reference watershed during 1975-2007. Three copulas, including Clyton, Ali-Mikhail-Haq and Frank were considered for constructing the joint distribution of the paired hydrograph characteristics. The Frank copula was selected as the best copula for constructing the joint distribution from paired characteristics of runoff volume and peak discharge of hydrograph and also runoff volume and base time of hydrograph. While the Clyton copula was recognized as the best copula for other two dependent characteristics, namely time of peak discharge and base time of hydrograph. After constructing joint distributions, several valuable information such as joint probability, joint and conditional return periods were calculated and plotted.

Recently, copula functions have attracted great attention of hydrologists as a practical tool for multivariate frequency analysis of climatological phenomena. In this study, we focus on the joint frequency analysis of two dependent characteristics of rainfall, including depth (mm) and duration (hr) using copulas for 522 events recorded in Sangdeh rain gauge station located in Kasiliyan watershed. To join the marginal distributions and constructing the joint distribution, seven copulas including Clyton, Ali-Mikhail-Haq, Farlie-Gumbel-Morgenstern, Frank, Galambos, Gumbel-Hougaard and Placket were used and evaluated. By comparing the mentioned parametric copulas with an empirical copula, we found that the Placket is the the best fitted copula on the considered variables. Finally, the joint probabilities, joint return periods and conditional joint return periods were calculated and plotted. For example, joint probability values for two events with duration of 12 and 24 (hr) given rainfall depth that exceeds 15 (mm) were calculated as 0.2663 and 0.7693, respectively. Also, conditional return period was calculated equal to 9.19 year for an event with depth of 30 (mm), given rainfall duration that exceeds 24 (hr) and equal to 14.94 year for an event with duration of 24 (hr), given rainfall depth that exceeds 30 (mm).

draining the flood of enormous dams and transmitting the procedure to the downstream is one of the important issues regarding hydraulic structures. Plunge pools are the main structures to dissipate the high rate of energy. The amount of energy at an outlet jet depends on various parameters such as the dropping height, the thickness of the jet, and other environmental conditions. Local erosion in plunge pools with alluvial beds is a complex phenomenon and determining the geometric features of the scour hole is really difficult. The outlet flow mixes with the turbulence factor and hits the bed of the plunge pools with a semi-perpendicular condition. Therefore, the present study was conducted to determine the scour which was caused by inlet air along the middle water jet on the bottom of the plunge pools. Xu et al. (2004) tested the aeration effects on the scouring caused by the falling jet and obtained a small relationship between the percentage of air jet density and the relative scour depth. The results informed that aeration affects the shape of the scour hole and essentially reduces the scour depth. Manso et al. (2004) investigated the interaction of the geometric shape of the submerged pond with rocky bedding on the rate of diffusion of the falling jet. They tested various diameters of jets,5.5, 11 and 16.5 times the diameter of falling jet, on the smooth and rough beds to investigate the dynamic pressures with frequencies between 1 to 2 KHZ. Their findings showed that the geometric shape of the pond has a direct impact on the jet diffusion rate. Duarte et al. (2015) studied the effects of air inlet to jet on the dynamical pressure on the floor of the submerged pond. They increased the jet's velocity to 22 m/s. The final results showed that the air inlet to the jet led to a decline in the total pressure on the floor of the pond.