فهرست مطالب alireza zamani nouri

One of the biggest challenges of the rainfall-runoff model is to accurately determine the rate of water infiltration into the soil as one of the parameters that determine the size and shape of the hydrographs of historical floods. The studies conducted in different climates that show different morphometry of the earth indicate the weakness of widely used methods such as SCS-CN in determining the rate of water infiltration into the soil. For the SCS-CN method, as the soil storage index approaches infinity, the soil moisture ratio approaches 1, and this is due to the limitation of the SCS-CN method. In this research, focusing on this weakness in the basic relationships of loss calculations, and an integrated approach in determining the infiltration of water into the soil, the magnitude of the historical floods in the watershed was analyzed. The importance of this analysis can be in verifying the magnitude of floods, which is the criterion for determining structures or crisis control programs.

Considering that in order to solve the problem of infiltration calculations at the basin scale, and based on the new equations to determine flow losses, a homogeneous but raster criterion is needed, in this research, based on the sensitivity of the produced flow to the amount of losses in the probabilistic investigation of the index humidity and flow ratio, a depth-infiltration model was prepared from the two-dimensional comprehensive model in the range. In this study, based on the new relationships of losses determination, numerical calculations were done in the software and script environment sequentially and based on the outputs of the hydrological model. First, the HEC-HMS rainfall-runoff model structure was generated with Arc Hydro and HEC_GeoHMS extensions in Shadegan catchment. Then, infiltration parameters were determined by SMA method in the analysis of remote sensing images from the basin. In the next stage, the development of the primary continuous model, calibration and validation was done focusing on soil moisture information. After determining the soil moisture relationship based on the results of the soil wetting model, the artificial unit occurrence hydrograph was determined by determining the flood volume based on the SCS-CN and VIC combined method. 

The general results of the implementation of the hydraulic model of the flood plain showed that the maximum inflow was equal to 3023 cubic meters per second at the 90th hour of the event, and the maximum outflow flood was at the 93rd hour with a figure of 2137 cubic meters per second. The discharge value is assumed to be 0 at the beginning of the calculations. The flow volume at the end of the calculations was equal to 141.03 million cubic meters, which is the remaining volume of 918.36 million cubic meters in the whole event. The difference between the inlet and outlet discharge was calculated as a deficiency of about 6.14%. Also, the layer of flow depth changes shows that the water level in the plain is trying to be at a possible and reasonable level by filling the lower points. So that a large part of the volume of water from the southern strip of the borders of Trava for the active area of modeling will eventually flow into the sea. However, the direction of water movement has even been estimated to be perpendicular to the direct path towards the sea in some cases. These results indicate a maximum depth of 16.4 units in some areas, with a minimum depth of 5.3 units. The important point is that in the plains, according to the cell size, definitely in some cases much lower depths can be calculated. The average depth in active cells is 11.9 meter calculated locally. These figures can change according to different rainfall events.

The results showed that it is possible to verify the infiltration based on the new base distribution equations with a probabilistic condition in the estimation of the basin shape parameter. The amount of hydrograph calibration in response to water infiltration in soil is dependent on the correct estimation of initial soil moisture. Flow losses in large-scale watersheds are obtained more suitably based on SCS-based distribution equations. Numerical and hydrological models such as HEC-HMS or modelers such as HEC_GeoHMS are completely dependent on the DEM raw layer introduced for the purpose of upstream demarcation. Changes in land cover in flat areas can actually produce a closed border of the watershed compared to the reality of the land in different simulation models. According to the basic assumptions such as calibration coefficients, the single hydrograph method can be a good substitute for areas without rainfall-runoff statistics. The TUFLOW software model gave the best response to one-dimensional to two-dimensional flow for Shadgan plain according to the type of boundary conditions.

Due to the sharp decline of the underground water in the country's plains due to their indiscriminate extraction for agricultural purposes, managers are looking for solutions to manage and restore underground water tables. One of the solutions to compensate for the drop in the underground water level, which is one of the most effective factors in destroying the discharge capacity and increasing the quality in the underground water area, scenarios of reducing withdrawal of farming wells and prepare prohibition plans with the least uncertainty based on the regional sensitivity to pollution. The purpose of this research is to predict the flow and pollution conditions of the area based on numerical models, so that the level network and the direction of the underground water flow of the plain using MODFLOW software in a long-term period and the development of the prediction model using Calibration and validation operations should be performed on the base period of the studies in order to be able to implement the forecast scenarios by applying restrictions and reducing harvesting on aquifer exploitation resources, and specifically agricultural wells, until the stage of stable hydrograph extraction of the plain.

This research was carried out with the aim of estimating and predicting the state of pollution in the urban pollution site, using MODFLOW and MODPATH computer programs in GMS software. To achieve this goal, in the first step, the numerical model of the aquifer flow was prepared and calibrated by the MODFLOW code. Then, the MODPATH code was used to track the contaminated particles in the steady-state progressive method. In the second stage, the impact of the scenario of increasing and decreasing the pumping from the exploitation wells on the travel time, the length of the path and the catchment area of the leachate particles leading to them was predicted and evaluated by the regressive method. In the third step, the tracking of particles leading to qualitative sampling wells in the plain was predicted and evaluated by regressive method in steady state.

According to the automatic calibration and validation approach, the underground water flow model produced the least statistical deviation on the optimization parameters. Also, the particle transfer quality model was correctly implemented on the groundwater flow prediction model. In the Babol aquifer, the waste disposal area outside the designated aquifer is saturated. It was observed that, by adjusting the parameters of the simulation of the transfer of residual pollution cloud particles, an estimate of the concentration was applied to the permeable boundaries and the channel network. This means that in the simulation of particle transport, here the source of pollution spread is the channel network and permeable boundaries, which will be directly affected by pollution during periods of rainfall and especially floods. The concentration limit was given to the model in the form of variable figures based on discharge and precipitation in the range and equal to the primary stable threshold of the research subject (landfill). Based on the cumulative diagram of the outlet concentration from the permeable boundary and flow channel in the southeast region, the trend of changes in the cloud pollution concentration diagram, in the qualitative modeling of the plain, shows that in the forecast period, the increase in concentration will increase linearly. Considering that the waste disposal location is outside the plain, the rate of increase in pollution was not very high until the end of the initial simulation. However, the reason for the increase in concentration accumulation volume can be related to the existence of permeable boundaries and severe drop of underground water in this area. In other words, when the underground water level drops too much in the saturation area of the plain, the direction of the flow will move the volume of polluted water towards the aquifer at a higher speed.

If the situation of groundwater withdrawals continues in the same way, in addition to the reduction of the groundwater storage of the plain, the quality of the remaining water storage will also decrease. This causes more serious problems in the agricultural situation of the region. The results of the implementation of quantitative and qualitative model in order to investigate the infiltration of polluted water from the landfill based on the concentration of pollution, showed that there is a high probability of the infiltration of polluted particles from the south wall side to the aquifer during periods of rainfall Event that current is run in the channels accidently. and then the expansion to the sea will actually occur due to the drop in the water level of the Caspian Sea. Water infiltration is more likely in the eastern regions than in the western regions. The reason for choosing the spread of pollution from the eastern waste disposal site in order to show the accumulation of polluted particles and the repulsion from the sea was the same. It is suggested that in the field of policy making, in order to control the plain's leachate crisis, appropriate bed construction and walling of the waste accumulation area should be applied based on the flow direction.

Drought is one of the most important and damaging natural disasters in the field of water resources that occurs in all climatic regimes of the country. Therefore, predicting and dealing with it is very important. In the present study, 79 synoptic stations in Iran were selected as the study. Three meta-heuristic optimization algorithms TLBO, IWO, PSO and the conventional Levenberg-Marquadt algorithm were used to train the multilayer artificial neural network to predict the SPEI12 drought index for the next one to three months. Due to the large number of synoptic stations, the stations were divided into five clusters C1 to C5 according to the time series of the drought using the K-means method. The results were compared with respect to the location of the stations in the clusters and the accuracy of the models was evaluated based on the RMSE and R2 indices of the test data. Showed that in all three prediction models, the accuracy of the models decreased with increasing prediction time. Comparison between the three optimization algorithms mentioned and Levenberg-Marquadt algorithm as a widely used algorithm in optimizing neural network weights, showed the better performance of meta-heuristic algorithms. The comparison between the three TLBO, IWO and PSO algorithms showed that the TLBO algorithm performed slightly better than the other algorithms and provided more accurate results. R2 was observed in cluster one (eastern regions, southern strip and southeastern regions of Iran) and the highest RMSE values and the lowest accuracy of the models were observed in cluster five (northern strip strip of the country).

Drought is one of the most important natural hazards and often affects the lives of many people and causes economic damage, environmental damage and social problems. This study was conducted to evaluate the drought trend, intensity and duration during 1988-2019 in relation to the existing climates in the southern Alborz region. To describe droughts in 3, 6, 12 and 24-month time scales, two drought indices, namely standardized precipitation index (SPI) and standardized precipitation evapotranspiration index (SPEI) were used. In the case of SPEI, evapotranspiration was an important factor in monitoring drought. Therefore, (HS) method was used to calculate evapotranspiration. Drought intensity and duration maps were presented for SPI and SPEI. The correlation between SPI and SPEI was also examined. In the present results, unlike humid climates, SPI does not have a good correlation with SPEI in extremely arid and arid climates and shows the importance of reference evapotranspiration (ET0) to identify drought in these areas and the index (SPEI) has more accurate monitoring results. Relative to the index (SPI). In addition, drought intensity maps for (SPI) and (SPEI) have shown that the region is experiencing very dry conditions and water resources are affected by intense drought in the short and medium term. Short-term drought in the east of the region (Zanjan) and long-term drought in the center and west of the region (Garmsar, Semnan, Karaj, Tehran) have been more.