فهرست مطالب فهیمه رضی

Examining and quantifying the degree of uncertainty in the prediction results of the models is the most important step before using the results of the models in water resources decisions making. In this research, the Markov chain technique was used to predict the hydrological status of the basin according to the amount of precipitation in the previous time step. The present study aims to determine the degree of uncertainty of prediction using the confidence interval of the probability of occurrence of events in different meteorological and hydrological conditions. To assess the uncertainty of the predictions by the 2D Markov chain transfer probability matrix, 20 periods with similar characteristics to historical conditions were simulated by the Monte Carlo method. To determine the uncertainty in estimating the hydroclimatology transfer matrix components, the nonparametric method of ratios for large samples and the exact method based on the sign test for the median of the predicted matrix components were used. The results of the long-term hydroclimatology matrix showed that the hydrological conditions tended to remain normal. The results of uncertainty analysis also indicated that the sign test, as a non-parametric method, in assessing the uncertainty of the Markov Chain acts better, and because the range of probabilities of transfer from different meteorological states to hydrological states is almost the same for all stations, the study basin is considered meteorologically and hydrologically homogeneous.

There is a deficiency in the number and depth of researches regarding the significant association between meteorological and hydrological droughts, and investigating the effects of uncertainties in the lag time between the two phases of the droughts. In this study, the lag time between the two phases of meteorological and hydrological droughts was investigated based on the available observations, using frequency-counting methods for the Anzali wetland basin with 9 meteorological and 20 hydrometric stations having recorded data from 1985 to 2015. Due to the fact that in the 30-year observation period, the possibility of severe droughts is low, to generate unobserved meteorological drought conditions of varying magnitude, continuity, and intensity, using the Monte Carlo method artificial rainfall was simulated. The SWAT water balance model was employed to generate the hydrological drought situations for different meteorological drought scenarios. The effect of the persistence and severity of meteorological drought on the lag time was investigated using the statistical technique of cross-correlation matrices. The results showed that an increase in meteorological drought duration increases the hydrological drought duration while an increase in the drought intensity reduces the lag time between the two phases of the droughts. The confidence interval of the lag time between meteorological and hydrological droughts showed that there is a chance of 70% to have a lag time of one month or less between the two phases of the droughts.

Despite the need to predict the flow regime in rivers, especially in hydrological drought conditions, little progress has been made in this area, and practically time series of discharge or non-dimentional indices are used instead. In this study, the prediction of hydrological conditions in rivers based on the basin condition in terms of rainfall is done using Markov chain concepts for the case study of Anzali Wetland catchment with 9 meteorological stations and 20 hydrometric stations over the years. The data from 1985 to 2015 have been used. Two-dimensional Markov probability matrix was used to predict the hydrological status of the rivers by observing the meteorological condition of the basin. The two-dimensional transition probability matrix is different from what has been customary so far, using two different phases of moisture flow in hydrometeorological processes in a matrix so that its columns represent the meteorological state and its rows represent the hydrological conditions. Evaluation of Anzali catchment conditions showed that meteorological and hydrological conditions are the same in each month by the probability of higher than 50%. Based on the results of the 2D matrix of the probability of transfer, the probability of being in normal, wet and dry hydrologic conditions, if these conditions occur in a step ahead in the meteorological phase, is 80, 50 and 40%, respectively. Based on the achieved results, with the expected value of the pertinent discharges in the forecasted hydrological condition concerning the former step climatological state, the probable discharge in the river is predicted.

Long meteorological drought can lead to the onset of hydrological drought. In this research, the lag time between the two types of drought was investigated for determining the hydrologic drought onset after realizing the climatological drought. This is a matter to provide managers with enough time for decision making before the occurrence of water shortage in the watershed. The SWAT water balance model was used to determine and predict the lag time between the two types of drought for Foomanat (Anzali wetland) watershed in Gilan province Due to the ability to simulate the long-term flow of representative rivers in the basin. The OAT method was employed for the sensitivity analysis of the water balance model. Among the parameters used in SWAT, three parameters including curve number, available water, and the evaporation compensation factor in the soil were recognized as the most effective parameters for the results of the model. Calibration and validation of SWAT were performed using SCH model. The calculated Nash-Sutcliff and correlation coefficient in estimating runoff as well as determining and predicting the lag time between the two types of drought by SWAT were acceptable. The Nash coefficient was obtained as 0.68 and 0.8 for calibration, and 0.65 and 0.79 for validation periods, respectively. Using the calibrated model, one can predict the water balance situation and the lag time between the onset of meteorological drought and the emerging hydrological drought in the watershed for any interested meteorological drought scenarios. Based on the results, the chance of having a one -month lag time, is more than 70 percent, while the chance of a 2-month lag time in the Foomanat watershed Anzali wetland) is more than 23 percent.

One important issue in drought studies is realizing the spatial pattern of drought events in a region through point estimation of the drought characteristics. In the first section of this research, in order to investigate the effect of probability distribution function transformation embedded in SPI, on the spatial distribution of drought, regional analysis was carried out using precipitation and SPI data, separately. The case study is the ​​Anzali wetland watershed in the north of Iran. The results in terms of the employed regional analysis method and time scale were different. The results showed that by decreasing the time scales to less than 1 year, while by the SPI index the region was completely homogeneous, the region was divided into different sub-regions using precipitation. The important conclusion drawn from this part of the research was the necessity of zoning the region via precipitation and then analyzing drought in the obtained regions. In the second part of the research, a comparison was made among three zoning methods including; L-moment, hierarchical and non-hierarchical clustering methods using precipitation and SPI, separately. Overall, L-moment was more successful than the other two clustering methods in detecting homogeneous regions in the study area. Finally, it was concluded that reducing events time scales sharpened the difference between the zoning methods; therefore, choosing an appropriate zoning method would be more important in monthly and seasonal time resolutions.

Drian installation depth is one of the most important challenges in drainage network design and construction. Deep drain installation leads to increase inflow volume to the drain and causes to decrease drain water quality. In the other hand, deep drains washes deeper soil profile and discharges traped salts in lower layers to final outlet. The objective of this study was to find the optimum drain installation depth to reduce drain volume and improve drain water quality. To do this, a laboratory investigation was carried out as well as numerical simulation. Drainage pipes were installed in 0.25, 0.5 and 0.85 m depth within a sand box filled with three silty clay soil layers with initial salinity of 12.7, 31.2 and 67.5 dS/m, respectively from top to bottom. Drain outflow volume and water quality from the sand tank were measured. The laboratory test was simulated using SEEP/W software and the results showed that a deeper soil profile has been leached by increasing drain installation depth, and streamlines flew to a deeper layer and then moved back to the drain pipes. In addition, drain outflow rate was computed using the software. The results showed that the outflow rate increases with drain depth. So, it could be concluded that reduction in drain depth leads to inprove drain water quality and decrease in drainage volume.

Iran is ranked fourth for saline-sodic soils in Asia following China, India and Pakistan. Therefore, if coupled with waterlogging, drainage would be an inevitable and indispensable activity agriculture in most irrigated parts of Iran. Drain installation depth is one of the main economic as well as environmental challenges in design and construction of drainage systems. Deep pipe drain installation cause the effective control waterlogging, but damage the drain water quality. Deeper drain installation leaching more of salts from partly a deeper soil profile, throughout the current study. Extracting salts from beneath root zone. A laboratory test was carried out in which a 2×1×0.5 m3 sand tank filled with three 30 cm layers of clay-loam being employed to investigate the influence of drain installation depth on the drained water quality. Drain pipes were installed at 0.25, 0.5 and 0.85 m depths. Initial electrical conductivity of soil extracts (ECe) was estimated as 12.7, 31.2 and 67.5 dS/m, for the three layers, respectively. The results indicated that the maximum drain water EC (ECdw) increased by depth, being recorded as 43.1, 55.6 and 131.8 dS/m for 0.25, 0.5 and 0.85 m depths, respectively. Drain water depths for the tests were recorded as 22.5, 25.5 and 27 mm. The results showed that decrease in drain installation depth improved drain water quality, decreasing the drain water volume and while leading to an improvement in the environmental impacts of drainage.