مجله مهندسی و مدیریت آبخیز
سال سیزدهم شماره 1 (بهار 1400)

Drought is a natural phenomenon that occurs in almost all parts of the world. The effects of this crawling phenomenon are more pronounced in arid and semi-arid areas due to their annual rainfall. In contrast to traditional methods based on meteorological stations observations that focus more on weather drought, the use of remote sensing and satellite imagery as a useful tool for monitoring agricultural drought has been considered. In the present study, the aim of comparing and assessing agricultural drought monitoring in Urmia Lake basin using VCI, VHI, TCI vegetation cover indices during the years 2000 to 2011 is using Madison. For this purpose, the NDVI index was first calculated from the images of Madis during June, July, August and September. Then, by comparing the mean of this index during these months, Shahrivar was selected with the maximum value as the month of the indicator. With regard to the minimum and maximum NDVI index in the months of September 2003 and 2008, VCI, VHI, TCI dash mapping maps were prepared. In order to evaluate the performance of agricultural drought indices, correlation coefficients were calculated for VCI, VHI and TCI profiles with SPI Meteorological Index. The results showed that the remote sensing index had a good accuracy in estimating the spatial and temporal dispersion of agricultural drought, so that the correlation coefficient between the VHI and SPI index was 0.86, which indicates that the index is consistent with the SPI meteorological index.

The method employed in this study was based on experimental research and field study. In this method, the stored radiocesium of the forest region which was supposed to be converted into Poplar plantation has been compared with the stored radiocesium of the reference region. 11 core samples were taken from reference region and then 7 core samples were selected from the transect which was a part of Poplar plantation that were taken by topographic characteristics in a depth of 25 centimeters, Having prepared the core samples according to the IAEA, they were packaged into the special Gama spectrometer containers. After that the amount of radiocesium of all samples has been measured by Bq kg-1 scale. The findings revealed that the amount of radiocesium in reference region was computed as 5894.1. Bq m-2 y-1. In the present study, soil loss rate during transect was estimated using proportional conversion models and mass balance I and II of 18.70, 22.72 and 18.64 ton / ha, respectively. These values were obtained for slope of 10-20%, canopy cover of 25% and clay loam soil under 1000 mm precipitation. This study recommended mass balance model II for estimation of erosion in changed land use areas and concluded that forest land use change to plantation due to reduction of long soil cover and plantation management by removing other seedlings and herbaceous cover increased the rate of soil erosion occurs. This process for many years has caused the erosion rate to exceed and has caused the loss of 0.1 cm of soil per year.

Due to the flow regime and consequently the sediment regime are not constantly in the watersheds, the prediction of sediment discharge is a great help in estimating and managing the sediment input to hydraulic structures. Measurement of sediment in the usual way is not justified in nowadays and may also lead to human error. Therefore, in this study, three meta-heuristic optimization algorithms, including imperialist competitive algorithm (ICA), grey wolf optimizer algorithm (GWO) and election algorithm (EA), were used to predict the suspended sediment load of the Zarrineh river. In order to calculate the sediment discharge by the models, firstly, the necessary statistics and data were collected from the studied station in the period 1993-2015. After processing the data, 210 corresponding discharge and sediment data were selected. The corresponding discharge-sediment data from the study station were randomly separated into two parts, 70% for training and 30% for testing. In order to evaluate the performance of the algorithms, four statistics consist of R2, RMSE, MAE and the NSE were used. The results showed that GWO algorithm with values of statistical criteria R2=0.96, RMSE=228.86 ton/day, NSE=0.74 and MAE=67.32 ton/day, has a very high accuracy compared to other algorithms used which this would lead to comprehensive planning for the design and construction of hydraulic structures.

Evaluation of watershed management projects today is one of the most fundamental issues being addressed in countries for future planning in the field of natural resource management projects. The results of evaluating watershed projects by presenting a strategy and strategy should reduce future problems and costs. In this study, hierarchical analysis method and SWOT analytical model were used to evaluate and present the strategy. In this study 4 main criteria (reduction of erosion, flood reduction, increase of vegetation covers and increase of sewage discharge) and 8 sub-criteria were used. Then the final weight of each criterion and sub-criteria were determined using Expert choice software. The results showed that erosion reduction criterion with relative importance of 0.482 had the most impact on watershed projects. SWOT model results in the region indicated that the region's conditions were in the fourth quarter, WT or defensive strategy. To this end, strategies for mitigating threats and addressing regional weaknesses were presented using the region's potentials and opportunities, and prioritized using expert opinions. 8 strategies were identified and evaluated based on the potential of the area and the evaluation of implemented projects. The best management strategies to build coastal walls around the gardens in collaboration with locals with a final score of 0.28 were the first priority and a strategy to improve and increase the height of the dam overflow. Constructed with 0.02 points was the last priority.

River flow prediction is one of the key issues in the management and planning of water resources, in particular the adoption of proper decisions in the event of floods and droughts. To predict the flow rate of rivers, various approaches have been introduced in hydrology, the most important of which are the intelligent models. In this study, a hybrid, model wavelet- support vector machine, was applied to estimate the discharge of Dez river basin based on the daily discharge statistics provided by the hydrometric stations located at the upstream of the dam during the statistical period (2008-2018) and its performance was compared with the support vector machine model. The correlation coefficients, root mean square error, and mean absolute error was used for evaluation and a comparison of the performance of models. The results showed that the hybrid structures presented acceptable outcomes in the modeling of river discharge. A comparison of models also showed that the hybrid model of wavelet -support vector machine has a better performance in forecasting the flow. In conclusion, the use of the WSVM model could be effective in estimating flood peak discharge.

Geographical location and proximity to countries such as Saudi Arabia, Pakistan and Afghanistan as well as desert conditions and poor vegetation cover, weather instability and high winds have caused dust storms in different parts of Hormozgan province. This phenomenon is nowadays recognized as one of the environmental challenges in southern Iran. In order to study the dust phenomena in Hormozgan province, were first analyzed the dust data of twelve synoptic stations in the region between 2000 and 2018 Ackerman’s model, Normalized Difference Dust Index (NDDI), Thermal-infrared Dust Index (TDI) and Thermal Infrared Integrated Dust Index (TIIDI) were four Algorithm methods for dust source and plume identification using MODIS data MODIS Level 1B and MODIS Level 2 aerosol data to delineate and compares. Results showed that Qeshm station with 2762 days had the most and Minab station with 356 days had the least frequency of dust occurrence in the province. Also, 2007, 2008 and 2003 have the highest occurrence among the studied years. According to the survey data from 35716 days associated with dust phenomenon, 84% of dust events in the stations were locally originated (code 07) and 16% were of external source (06). The results also showed that the most occurrence of dust occurred in May, April and July, and the least occurrence of dust occurred in November, December and October. The results are shows all of the techniques except NDDI were successful in detecting dust plumes, but the most effective algorithm for plumes identification varied from event to event. In addition, TDI is the best algorithm comparing 3 evidence and eastern regions of Hormozgan, Jazmoorian area, Sistan and Baluchestan, and the western part of Afghanistan and Pakistan and south of Saudi Arabia are most important for dust source in Hormozgan Province.

One of the most important challenges of researchers in rainfall-runoff modelling is the estimation losses and extracting excess rainfall, which can affect on accuracy of the model and hydrograph characteristics. In the present study, at first the infiltration index of was estimated based on the depth of runoff and rainfall and also effective rainfall time. Then, instantaneous unit hydrograph was computed through Russo Method and the dimensions of direct runoff hydrograph were determined for 20 rainfall- runoff events. Then in order to increase the precision in estimating the dimensions of obtained hydrograph, the value of penetration index was estimated based on bivariate distribution resulted from infiltration index and one of rainfall characteristics which obtained from Copula function. For this purpose, at first the correlation between infiltration index of , characteristics of rainfall hyetograph and runoff hydrograph was calculated, then the best- fitted marginal distribution on each variable was specified. Finally, Galambos function was chosen as the best copula function for creating bivariate distribution for pairs of infiltration index of and rainfall height, infiltration index of and maximum velocity, infiltration index of and average flow and also infiltration index of and velocity. Therefore, the hydrograph dimensions were obtained for each event. Comparing the various dimensions of computed and observed hydrograph by copula function in Russo method showed that the infiltration index of can be estimated more accurately by using the copula function.

Resilience is one of the strategies to reduce the vulnerability of communities in dealing with natural hazards. Among environmental hazards, drought is the most costly natural hazard due to the decrease in production and severity of suffering for villagers and farmers. Assessment of the effects of recent drought in the country, Indicators of low resilience of societies against this natural hazard are therefore indispensable for resilience of societies against drought. This is an applied research and has been done by descriptive-analytical method with the aim of measuring and evaluating the level of rural resilience in facing drought risk. To conduct research, using library resources, indicators and factors affecting rural resilience were identified and defined operationally. Then, using the field method and the questionnaire, the required information was gathered and the information collected using SPSS software Processed. The statistical population of the rural farmers is Hablehrood. For this purpose, 9 villages from different areas of the province with different levels of drought and development were selected and based on the Cochran formula, 271 farmers were selected as sample size. The tests used in this research are single sample T, Friedman test and Pearson correlation coefficient. The results showed that the level of field fluctuation was at an undesirable level and lower than the average level, and the rural areas of Hablehrood watershed were at risk of drought occurrence in the vulnerability to resilience.

This study focuses on simulation and management the various hydrological responses to climatic changes. The semi-distributed hydrologic model SWAT (soil and water assessment tool) was used to evaluate runoff and water balance due to climate changes in Siminehroud and Zarrinehroud watersheds. The simulation period was selected between 1990 and 2014. The assessment results in the calibration and validation periods using the NS and R2 obtained 0.75, on average. Using statistical multisite downscaling of LARS-WG climatic models MIROC-ESM-CHEM، GFDL-ESM2M and NorESM1-M the future climatic condition entered to the model using two optimistic RCP2.6 and pessimistic RCP8.5 scenarios. The largest changes in runoff in the upcoming period, May, reduced by 2.4 m3 s-1 and in April, increased by 1.49 m3 s-1 in the optimistic scenario. In RCP8.5 pessimistic scenario in May and June, also the highest runoff was observed. The rate of actual monthly evaporation will increase in the optimistic scenario up to 3 mm and in the pessimistic scenario up to 8 mm increase will have a negative impact on the available water resources in the watershed. With estimation the climate changes and its effect on the stream flow discharge is possible performing a suitable management in Siminehroud and Zarrinehroud watersheds.

Understanding the behavior of phenomena requires attention to all its dimensions, and one way to understand their complexities is modeling. Soil surface moisture is a key variable for describing drought, water, and energy exchanges between Korea and the air, as well as assessing crop conditions. Soil moisture is affected by both environmental variables and many environmental variables such as runoff, soil erosion, and crop production, but is highly variable due to unstable spatial and temporal conditions. The purpose of this paper is to investigate, extract and evaluate the spatial model of soil moisture dispersal after more than normal rainfall in 1979-98 in Kurdistan province. In this regard, after analyzing soil moisture dispersion as dependent variable and precipitation variables, snow water equivalent, topographic moisture index and vegetation index were selected as independent variables. Then, using a general regression model (OLS) and geographically weighted regression (GWR), spatial modeling was performed. Based on the evaluation criteria, the results showed that the GWR model with R2 = 0.74 has better explanatory power and better estimation than the general regression model with R2 = 0.68. According to the results of the GWR model, snow water equivalent variable in the northern mountainous regions had the highest effect on evapotranspiration and the least effect on soil moisture. The obtained spatial model can identify low or moist soil areas in order to identify environmental potentials and improve decision making, allocation and spatial distribution of agricultural services.

In this study, with using the data mining algorithm prediction, more efficient management of the aquifer of Tirvan and Karvan can be done. Seven different human and natural factors affecting aquifer depth changes were used in this manuscript. Initially, the predictions of three tree algorithms CART, CHAID and MP5 in aquifer changes were evaluated using statistical indices. The CAHID algorithm performed better than the CART and MP5 algorithms with respect to the regression coefficient of 0.82 and absolute error mean of 0.12. The highest aquifer rise in December, January, February and March, when the amount of precipitation was between 0.08 to 0.72 million cubic meters and the air humidity percentage was more than 72% and also the highest aquifer drawdown in month August and September, when air temperature more than 25 centigrade and the volume of water discharged from agricultural wells were more than 1.32 million cubic meters, were predicted by the CHAID algorithm tree diagram. From natural factors, air temperature and human factors, the volume of water harvested from agricultural wells had the greatest impact on aquifer depth changes in the plain. The two factors of air humidity percentage and precipitation volume were the only factors that had a direct relationship with the aquifer depth elevation. The most influential factors in predicting the depth changes of the aquifer of Tirvan and Karvan were air temperature, volume of water harvested from agricultural wells, and Precipitation volume and other parameters, respectively.

In recent decades, among natural disasters, the frequency of agricultural drought has been higher than other natural disasters. The best way to management of agricultural drought was to management drought-stricken society. The purpose of this study was to assess the vulnerability and spatial analysis of drought in Pishkuh watershed in Yazd province. the effective parameters in the vulnerability of agricultural drought in the region became information layers, and after weighting the layers in terms of the importance of agricultural drought vulnerability in the framework of multi-criteria decision making (MCDM) Agricultural drought in the study area was prepared. In order to control, monitoring and evaluation the final map, field studies of the study area were also used. The results showed that the highest weight of the effective parameters in drought vulnerability was related to the precipitation parameter, the value of which is equal to 0.31, and the lowest weight was related to the slope parameter with a value of 0.05. According to the obtained results, the most vulnerable agricultural droughts were related to Sanich, Darashir, Darasir, Eshkaft, Morok, etc. Geomorphologically, these areas were considered to be high and mountainous, more severe than plain areas due to the low depth of sediments, coarse-grained soil texture and aquatic resources (Qanats), mainly their vulnerability to drought, and In terms of time, they suffer more quickly, in other words, they suffer a lot of damage in the short term. While areas such as Islamia, Nasrabad, Mazrea Akhund, Hemmatabad , etc. were in a lower degree of agricultural drought damage. The results indicate that the degree of damage to agricultural drought estimated in the final map is in line with the findings of field studies. Therefore, the map of agricultural drought vulnerability has acceptable and desirable accuracy.

Aim of this research was Studying and Recognition of lithology and Erosion Rivers in Sistan region. To done this research distinct situation of rivers according of basin and collected inform about basin of Sistan and review different parts of them such as type of erosion in river banks by using available reports and filed works. We have used available scale of 1:50,000, 1:250,000, Geologic maps, field observation and global positioning system (GPS). We found erodible area of river banks according to scale of 1:250,000 erodible Geologic maps. The data show that’s the main factor of cause to erosion is effect geologic conditions. The main parts of the basin covered with sediment of quaternary which is very sensitive to water erosion. The sistan rivers classification shows that stone, alluvium and other are 20.7, 38.1 and 41.2 percentage of rivers length, respectively. 7.2 percentages of area rivers occur erosion that bed and banks erosion are 85.1 and 14.9%, respectively.