Journal of Water and Soil Conservation
Journal of Water and Soil Conservation (JWSC) is published quarterly by Gorgan University of Agricultural Sciences and Natural Resources. It has been regularly published since 2009. Journal of Water and Soil Conservation (JWSC) is one of the prestigious Iranian journals in water and soil sciences.
https://jwsc.gau.ac.ir/?lang=en
https://jwsc.gau.ac.ir/?lang=en
less
Uploads
Papers
Materials and methods: In this study, which was conducted to investigate the trend of vegetation changes in the study area during the period 2001-2018, 16-day combined time series data of MODIS-NDVI called MOD13Q1 with a spatial resolution of 250 meters was used. In this study in order to investigate the significance trend of vegetation cover, the non-parametric Mann-Kendall method was taken. Also the relationship between vegetation changes and altitude was investigated.
Results: Of the total area of the study area, 52% of the area had a decreasing trend of vegetation and the rest showed an increasing trend of vegetation, although a significant decrease in vegetation at the level of 5 and 1% occurred in 36% and 32% of the area, respectively. Also, 31 and 26 percent of the study area had a significant increase in vegetation at the level of 5 and 1 percent. In the study of the relationship between Z-Kendall statistic and height, the results showed that with increasing the height of Z-Kendall statistic increases and the correlation coefficient of height with Z-statistic is about 0.62. It seems that significant positive trends in vegetation occur at higher altitudes and significant negative trends in vegetation occur at lower altitudes. 99% and altitudes of 670 and 840 were obtained for the negative trend of 95 and 99%. In other words, at altitudes above 2030 and 1860, the trend of vegetation changes is positive and at altitudes below 670 and 840 meters, the trend of vegetation changes is significantly decreasing.
Conclusion: The results of this study showed a significant trend of greening at altitudes of more than 2030 meters in the region. It seems that with the increase of temperature due to climate change at elevated area, suitable temperature conditions and increasing of growing season length is provided for crop growth at altitudes. This increase in vegetation was further observed in the east and northeast of the study area. Also, the significant decrease in vegetation in low altitude areas less than 670 meters can be due to increased water requirement of low altitude plants and the occurrence of temperature stresses in these areas, which are mostly in the eastern, southern and low altitudes of the study area. However, it seems that the area between these two altitudes have not had a significant trend in vegetation changes.
Materials and methods: Based on a preliminary experiment, rice husk biochar (pH=5.64) and pine cone biochar (pH=6.56) produced at 300°C were selected for this study. The experiment was performed in a completely randomized factorial design with three replications. Treatments included two types of biochar (pine cone and rice husk) mixed with soil at one, three and six percent (g/g), two types of soil (a sandy loam, Tiran and a clay loam, Lavark), and two incubation periods of one and six months, with 4 controls and a total of 28 pots. The treated soils were kept in an incubator at 25°C and 60% of field (pot) capacity. At the end of the incubation periods, the soil moisture contents at field capacity and the permanent wilting point were measured respectively using sand-kaolin box and pressure plate devices and then soil available water contents was calculated.
Results: The results showed that the addition of biochars improved some physical properties of soils. The treatment of the soils with 3% and 6% of biochars caused significant increases in the available water (AW) in the sandy loam soils compared to the control. The physical quality index of Dexter (SDexter) fitted by van Genuchten–Mualem was significantly increased in the sandy loam soil amended with 6% of the biochars and in the clay loam soil amended with 3% and 6% of the biochars. The use of biochars also improved the physical quality of the soil, described by the Dexter index, from poor to very good.
Conclusion: The results of this study showed that addition of 6% rice husk biochar to the clay loam soil and at the 30 days incubation period, could improve soil properties. Therefore, according to these findings, the biochars produced from pine cones and rice husk can be suggested as a suitable conditioner for improving physical properties of the regional calcareous soils.
Materials and methods: Machine learning methods due to their high accuracy in predicting various issues have been noted in recent years . Therefore, in the present study, two methods of classical artificial neural network (ANN) and deep learning of long short-term memory (LSTM), which is a kind of artificial neural network with layers and amplification algorithms to improve network performance; have been used to predict the bed load of 19 gravel-bed rivers. To define suitable models for networks, the results of 10 experimental formulas in bed load prediction have been evaluated and the parameters of superior formulas have been used as the input of intelligent networks.
Results: The results showed that all experimental formulas had very poor results; As most formulas have predicted the bed load with a Discrepancy index of r greater than 100. However, machine methods with input parameters obtained from experimental formulas have acceptable accuracy in predicting bed load. and in comparison with machine methods, LSTM method has provided more accurate results than ANN method. Finally, the model related to the parameters of Begnold formula in LSTM method with DC= 0.900 and RMSE= 0.024 for the test data is the best model obtained from this research and The average diameter of sediment particles (D50), which is a common parameter of the top three models, has been selected as the most effective parameter in predicting bed load.
Conclusion: Despite the very poor performance of experimental formulas in predicting sediment transport, intelligent networks with input parameters derived from experimental formulas have had good results. Also, LSTM network is more efficient than artificial neural network (ANN) in predicting bed load transfer, which indicates that Maintaining training memory during the training process and adding reinforcement layers to the network improves network performance and increases network accuracy in subsequent training.
Materials and Methods: In this research ERA5 re-analysis and Terra satellite data used for the August 23-26, 2010 event in Hirmand. Products and satellite data used including true color images and AOD and re-analysis data including Surface latent heat flux (SLHF), Surface Sensible Heat Flux (SSHF), Surface net Solar Radiation (SSR), Surface net Thermal Radiation (STR) and Balance Radiation (Rn). Dust particles were routed using the HYSPLIT model and wind speed in the study area was also assessed using the analysis data. Also, for validation of satellite data and re-analysis, visibility and air temperature data, at height of 2 meters, at Zabol Meteorological Station, closest station to the study area, were analyzed.
Results: According to the HYSPLIT model output, most of the dust particles were collected from the deserts of Turkmenistan and then the dry areas around Lake Hamun and parts of northern Pakistan. AOD values showed that from August 21, the value of this index gradually increased so that on the 25th day, the maximum AOD value reached 1.25. Examination of the values of radiation and heat flux indices showed a significant decrease in SSHF, SSR, STR and Rn indices and their values reached the lowest value on the 26th day and the SLHF index with a slight difference on the 25th day reached its lowest value of 58 w/m2. Correlation study showed that SSR and Rn indices with -0.370 and -0.359 respectively had the highest and SLHF index with -0.153 showed the lowest correlation with AOD index.
Conclusion: The results of this study showed that the western parts of Hirmand Basin, Lavar or North wind has emitted dust particles into atmosphere, and the region and rotational currents has caused the distribution of these particles in the study area. The results of satellite data and their re-analysis and matching with real images showed that the study event increased the optical depth of dust particles, which resulted in tangible and surface heat fluxes, solar and thermal radiation, as well as balance. Radiation was greatly reduced. Evaluation of horizontal visibility and air temperature data at a height of 2 meters at Zabol station also confirmed the results of satellite images and re-analysis data.
Materials and Methods: The case study is located in Bushehr province, north of the Persian Gulf and southwest of Iran. To investigate the effect of drought on the amount of dust, data of 7 meteorological stations of Bushehr province with a statistical period of 30 years (1989-2018) was used on an annual scale including: hourly and daily amount of dust, monthly rainfall, temperature, humidity-relative and evapotranspiration. The estimation of drought with standard precipitation, dust occurrence based on phenomenon with codes 07 and 06 and their trend were analyzed by linear regression parametric test. Also, drought zoning of Bushehr province was done in Arc GIS software by IDW method. To investigate the climatic relationship with dust storms, stations with SPEI index and also dust storms that had a significant trend with variable frequency were analyzed using linear regression.
Results: The results showed that in the 30-year period, 79.06% of the frequency was mild drought, 18.96% was moderate drought and 2% was severe drought. Approximately 6.25% of droughts occurred in the first decade, 50% in the second decade and 43.75% in the third decade. The spatial distribution map of drought also showed that the main focus of this phenomenon is in the southern, central and northeastern regions compared to other parts of the province. The Saudi Arabian desert air currents towards the central regions of the province, the lack of proper vegetation, soil erosion and the presence of sand and salt zones in these parts have confirmed this issue. Also, the comparison of the incidence of droughts in the 30-year period shows the probability and frequency of mild droughts compared to moderate droughts, and the probability of occurrence of moderate droughts compared to severe droughts. The value of DSI index for Bushehr province has decreased over time.
Conclusion: This study showed that the DSI index decreased with increasing drought intensity during the study period and its correlation with drought during the 30-year period was not significant. Also, the combination of drought distribution map and DSI index did not show the same pattern. This indicates that human factors have played a more important role in creating a heterogeneous pattern of drought distribution and DSI index in Bushehr province. Certainly, it should be noted that the state of the province's winds is also important in the amount of dust production and droughts. Finally, the relationship between drought and the DSI index has always fluctuated based on droughts and wetlands.
Materials and Methods: All studies and research on the application of amendments in soil and water conservation in different conditions on various components of soil erosion and conservation in Iran were documented in databases and extracted from journal articles, conferences, executive reports, and related research, and theses and dissertations were investigated. The relevant 75 documents were then chronologically evaluated, analyzed, and summarized in order to assess the usage of various amendments in many areas, including the kind of amendments, the scope of use, the experimental setting, and the research variables. The necessary conclusions were ultimately drawn qualitatively.
Results: The use of soil stabilizers and amendments such as organic, inorganic, and biological elements to enhance the erodibility threshold and prevent soil water erosion has been widely documented based on the findings of this study. According to research findings, the performance of amendments varied depending on the kind, manner of application, scale, and soil type. In addition, the findings on the usage of amendments revealed that various additions are used and work well in soil and water conservation. However, adopting any of the customary changes has been noted as a considerable difficulty due to economic, environmental, health, administrative, functional, and technical restrictions. The use of biologically and ecologically friendly alternatives to boost the efficiency of the conditions for balancing and stabilizing the soil environment has been stressed due to the aforementioned constraints for the use of amendments.
Conclusion: Because of the widespread use of amendments, the feasibility of using environmentally friendly amendments, and emphasizing waste management in the primary industry through additional studies and research, there is a need for proper and appropriate measures that are naturally environmentally friendly in the long term. Nevertheless, additional research on the application of various amendments resulting from the direct or modified use of significant industrial wastes with respect to various aspects of environmental, economic, ecological, and even aesthetic and at different scales is necessary to summarize and develop appropriate executive instructions.
Materials and methods: This study was carried out in soil columns with a height of 15 and 30 cm and in a period of 12, 23, 56 and 112 days and including different levels of 1.5 and 3 WP% (Weight percent) of wheat biochar and control treatment as a completely randomized factorial design. The concentration of deltamethrin used was 300 cc per thousand liters per hectare. To determine the residual concentration, the pesticide was sprayed on the surface only once with the recommended dose and according to the considered irrigation periods, the changes of the pesticide over time and at different depths of the soil columns were studied. In this study, Brigham's analytical method was used to obtain the dispersion coefficient. Analysis of variance and comparison of means in the studied treatments was performed using LSD statistical test and SAS 9.4 software.
Results: The results showed that the residual concentrations of pesticides in 1.5 and 3% of biochar treatments compared to the control were decreased 26 and 43%, at depths of 0 -15 cm and 37 and 17% at depths of 15-30 cm respectively. Based on the results, pesticide uptake and stabilization in 3% biochar treatment was more than other treatments. In the control treatment, with increasing soil depth, it was observed that the dispersion coefficient decreased, in the modified treatment with biochar 1.5%, the dispersion increased while in the biochar 3% treatment, the dispersion coefficient decreased significantly by increasing the sample length. Deltamethrin dispersion coefficient in 15 cm columns for control, biochar 1.5 and 3% treatments were 5.37, 1, 3.59 cm and in 30 cm columns 3.91, 1.27, 0.92 cm was obtained, respectively.
Conclusion: Biochar production is very convenient and cost-effective and is successful in restricting the movement and stabilization of pesticides in the soil and by increasing its weight percentage in the soil, due to the surface area of biochar can control the movement of pesticides.
Materials and methods: The used soil was collected from the depth of 0 to 20 cm and was transferred to the laboratory. The study was performed on scale of splash cups and laboratory conditions using the rainfall simulator at rainfall intensity of 80 mm h-1. Also changes of time periods evaluated for durations of 24 h, two, four, eight, 16 and 32 week. Splash erosion measured by collecting the splash particles during each rainfall and then drying at temperature of 105° C. Physical and chemical characteristics of soil determined using current methods of laboratory. Data of splash erosion analyzed using SPSS software, Duncan test and GLM.
Results: The experiments showed that the application of the combination of compost and zeolite on changing the soil splash was the more than their separation effects. The results showed that the combination of compost and zeolite of total splash was with rates of 68.93, 15.53, 49.51, 38.83, 38.83 and 77.66%, respectively, and net splash of 67.27, 10.9, 56.36, 32.72, 47.27 and 72.72% at time periods of 24 h, two, four, eight, 16 and 32 week, respectively. Also, the changes percent of splash changes for the composition of compost and zeolite at the upstream of splash cup observed with amounts of 70.83, 20.83, 83.66, 45.41, 29.16 and 83.33%, respectively, and downstream was amounts of 68.35, 13.92, 51.89, 36.70, 41.77 and 75.94% , respectively. The effect study of time periods showed that the time periods of 32 and eight week had the more reduce at the amount of splash erosion. The statistical results showed that the effect of time period and treatment and their interaction on reducing the total splash and net splash was significant at the level of 99%. Also, the effect of time period and the interaction effect of time period and treatment on reducing the upstream and downstream splash was significant at level of 99%.
Conclusion: Adding these conditioners to the soil cause the reducing the soil splash erosion. The time effect also caused the more effect of the conditioners for reducing the amount of slash erosion. Among the used conditioners, the effect of compost conditioner was more than two other conditioners on reducing splash erosion, because this conditioner by increasing the stability and porosity of soil can bind the soil particles and thus the resistance of soil particles increase against the rainfall energy. Finally, it can be stated that the conditioners application separately and combination can be have the positive effects on decreasing soil splash that will lead to reducing soil loss at the long term.
Materials and methods: The Liqvan watershed with an area of 185 kilometers is located in the northwest of the country and East Azerbaijan province. In this study, for extraction of the depth of snows from 4 radar images of Sentinel 1 related to the time interval of December until March 1398 and a radar image associated with September 1398 in SLC format to implement radar interferometry in SARSCAPE software Used. To increase accuracy part of the work was used from the Google Earth Engine system. For this purpose, to extract the surface of the snow cover and its area of the NDSI daily product of the Modis sensor and the monthly NDSI- DEPTH product was used for extraction of the average depth of snow of each snow month in the Google Earth Engine Cloud System. Also, the Daily Product of Mod11A1 Modis Sensor was used to prepare a temperature map to examine the relationship between temperature and snow characteristics.
Results: Investigating the map of snow surfaces in the area of all months of the study period in the region showed the highest concentration of snow surfaces in high regions. Due to the outputs of the Google Earth Engine system, the highest and lowest snow cover level is calculated by January with 180 kilometers and December with a value of 83 km. The average and the lowest amount of the depth of snow is related to the February and December months, which utilizes the radar interferometry technique of 32 and 9 centimeters and uses the Snow depth- Inst product in the Google Earth Engine system 24 and 4 centimeters Has shown. The values for regression analysis were obtained between the time series of the surface temperature and the surface of the snow cover, respectively, 0/003 and -3/020 for the parameters of Sig and Z. The R2 variable was also obtained 0/47 about the correlation of the depth of snow and lst.
Conclusion: The results of this study indicate the ability of both radar interferometry technique and coding in the Google Earth Engine in calculating the depth of snow.
Maps and measures of the depth of snow can be an appropriate tool for managing water resources in the region for various uses. Also, the results of regression coefficients showed a significant relationship between the LST variable and the depth of snow and snow cover. So that the inverse relationship between the two components of LST and the snow cover (SC) and LST, and the depth of snow, as well as the direct relationship between reduced temperature and LST, showed.
Material and Methods: To determine the homogeneous regions for each year, the optimal number of clusters was initially obtained. After data clustering in Matlab software, the results of clustering were evaluated qualitatively with Schuler and Wilcox diagrams. For better representation of homogeneous regions, classification maps for the study area were presented.
Result and discussion: The results showed that the optimum numbers of clusters in 2006, 2011, and 2016 were 6, 5, and 6, respectively. Analysis of groundwater quality classification maps showed that in 2006, cluster no. 6, including 2.7% of the studied wells located within the city of Kalaleh, is poor in terms of drinking and farming groundwater quality. Also, based on the results, it can be seen that 36.8% of the wells across the province were in good condition in terms of quality of drinking and agricultural parameters in 2011. Likewise, 33.33% of the wells are in a moderate condition in terms of drinking quality, and the status of their groundwater has improved in terms of quality since 2006. Also, the results of NSGA- FCM in 2016 showed that most of the parameters (5.55% of the wells in the province) in the cluster 3 have a moderate quality.
Conclusion: The findings of this study showed that the groundwater quality in the province in 2016 is lower than in 2011, so appropriate management plans should be adopted. Moreover, it was observed that the fuzzy clustering method is a suitable method for assessing and identification of critical region of the quality of groundwater resources, since it considers the uncertainty conditions in the classes of the classification system.
Materials and Methods:In accord with supplementary data layers(geology,pedology,landuse,etc.) and stratified randomized sampling method, eventually, 128 samples from 20cm of soil surface of Mazandaran province (scattered parts), were gathered. First of all, sample-set subdivided into two subsets: calibration and validation. Afterwards, using the hyperspectral analyses, multivariate regression analysis-PLSR method with the leave-one-out-cross-validation technique and some preprocessing algorithms such as: spectral averaging,smoothing and 1stderivative(Savitzky-Golay-derivation algorithm), the definitive calibration model with two&four latent vectors according to indices such as R,R2,RMSE,RPD and RPIQ were made.
Results&Discussion:During the present research based on the sand hyperspectral modeling in the calibration subset containing 96 samples as well as the validation subset composing of 32 standalone samples, it has been showed the first two and four LVs out of the seven LVs can provide the best estimate of the soils of the study province. Consequently, the calibration process of sand hyperspectral model was done based on the first four LVs and the full LOOCV procedure. Because these number of LVs are able to concentrate the info-variance of sand variable more than 60% and likewise, the info-variance of spectral variables more than of 98%. The best calibrated hyperspectral model predicting sand components resulted with these specs: Rc=0.76,R2C=0.57,RMSEc= 9.77 and SEc of about 9.82. The correlation coefficients(R) of sand contents with the effective spectral domains were calculated as: UV-390nm=0.46, Vis-510to540nm about 0.53, 680to690 about 0.55, NIR- 950to970 about 0.67 and 1100nm=0.70, SWIR-1410 nm=0.76, 1860to1900 about 0.76, 2180to2220 about 0.77; which the specified spectral bands(spectral ranges) with the maximum of R contents indicating their highly impact and influence as the independent predictors on the sand parameter hyperspectral modeling processes at the studied soils of Mazandaran province. Furthermore, the most influential spectral domains involved in the modeling process of sand particles were determined as follows: UV-390nm,Vis-440-540nm,NIR-740-990nm,SWIR-1430-1890,1930,2190-2240,2330-2440nm, which these results were in agreement with others. The quality of calibrated sand hyperspectral model via assays such as Hotelling, adjusted leverage and residual variances was also confirmed. The accuracy assessment specs were as: Rp=0.83,R2p=0.68,RMSEp=8.68,SEp=8.72 and bias=-1.26.
Conclusion:Results indicate the apt hyperspectral analyses to estimate the sand based on LV=2: RPDc=1.51,RPIQc=2.44,RPDp=1.78 and RPIQp=2.45, additionally for LV=4:RPDc=1.54,RPIQc=2.48,RPDp=1.75 and RPIQp=2.41 have been gained. On the basis of the RPIQ values which were more than 2, it can be concluded the models are able to estimate the sand contents of Mazandaran soils satisfactorily and showing the acceptable quality of the predicting models utilizing the hyperspectral data. Our results can be the starting point to accurate mapping of sand constituents of soil texture using the RS platforms. It is noteworthy, the characterization of key wavelengths in the hyperspectral modeling of sand components, the upscaling operation as well as constructing the new airborne/satellite hyperspectral sensors can be bettered using the principle wavebands affecting the hyperspectral process so that providing the more precise hyperspectral studying of soil texture constituents using the aerial or space platforms.
Materials and Methods After measuring acidity, electrical conductivity, organic carbon, soil texture, lead, and cadmium concentrations, the relationship between the distribution of biocrusts with soil properties and cadmium and lead concentrations was investigated by principal component analysis. Then, using one-way ANOVA, the most important effective features are identified. Based on Duncan's test, the mean values of soil properties measured in five villages located in Sejzi plain were compared with each other at 95% probability level, and finally, the soil of points of Sejzi plain with higher cadmium and lead concentrations were determined.
Results: According In all studied sites, the average absorbable lead was more than 80 mg/kg (permissible level). The amounts of cadmium were measured at Fasaran and Sejzi at 2.8±0.6 and 2.38±0.18 mg/kg, respectively, that had been exceeded it's permissible level (2 mg/kg). Also, the results of the principal component analysis showed that in the first component, which is 67.4% of the total variance of the data, the correlation between the percentage of silt was 0.438 and the percentage of sand was measured -0.451. In the second component, which is justified about 48.6% of the total variance of the data, the correlation coefficient of the values of cadmium and lead were estimated 0.388 and -0.438, respectively. The comparison of soil properties in different places showed that the average values of soil salinity, organic matter, silt percentage, cadmium and lead are different in those places.
Conclusion: The high concentration of lead and cadmium levels in areas without biocrusts, including Sajzi and Fesaran, were mainly due to human mismanagement and construction of factories, mines, and roads. Also, some intrinsic properties of soil, such as soil texture were effective in the distribution and establishment of biological crusts.
Materials and methods: At first, numerical modeling of Birjand aquifer was performed. MODFLOW numerical simulation of Birjand aquifer area was performed in two permanent and non-permanent modes in 2011. Then the hydraulic conductivity calibration was performed on the mentioned date and validated for two years 1391 and 1392. Then, the necessary scenarios for the project, considering different points for wastewater discharge and artificial feeding, were defined. Finally, the effects of reduction, increase and decrease of 20% harvest on pollutant movement were investigated using MODPATH.
Results: The calibration results show that the observed and calculated mid-level error (RMSE) is 1.071 meters, which is desirable. Also, the level calculated by the model indicates the movement of groundwater in the direction of the dominant slope of the region, ie from east and northeast to west and southwest. Also, the way particles move corresponds to the groundwater gradient and in the general direction from east to west. The length of motion of the particle at a given time in the eastern part of the aquifer is less than the western part.
Conclusion:According to the applied scenarios, it can be concluded that increasing and decreasing the withdrawal of Birjand groundwater by 20% does not make a significant difference in the direction and route of pollutant transfer during 10,000 days, but the artificial feeding scheme has a significant effect on the transfer Leaves pollutant particles. Therefore, due to the problems in the groundwater of Birjand, the implementation of artificial nutrition plan for this city is necessary.
Materials and methods: For this, the research region's precipitation, temperature, and precipitation type data from 1985 to 2018 were used. For the three scenarios RCP2.6, RCP4.5, and RCP8.5, the National Center for Environmental Protection's (NCEP) atmospheric reanalysis data and the CanESM2 model were used to forecast future climate change. Furthermore, the downscaling was done using the SDSM5.3 model. To find data patterns, the classic and modified Mann-Kendall tests were performed. Fixed temperature approaches, the UBC watershed model, the USCE model, and Kienzel's suggested method were utilized to separate the precipitation phase.
Results: To separate the precipitation phase throughout the fundamental period, observational reports were examined, and the approaches Kienzle and USCE gave satisfactory results. Climate change will also produce major changes in the precipitation temperature distribution in the examined mountain region in the future, according to the findings of this study. Also, a significant portion of the influence of climate change on the snow and rain phases. The modifications are done in such a way that rainfall will rise at higher temperatures and decrease at lower temperatures in the prediction period (2026-2060) compared to the observation period (1985-2018). The greatest total rainfall recorded at Shahrekord station during the observation period was 5.7 ° C, which has fallen to 0 ° C in the projected period. The temperature range of precipitation at this station was -10 to +18 degrees Celsius during the observation period, and will climb to an average of -10 to +24 degrees Celsius for all three scenarios over the forecast period. The range of precipitation in the future and measurements at Koohrang station is essentially the same, but climate change has produced a rapid shift in the amount of precipitation in this temperature range. Over example, during the 34-year observation period, the greatest rainfall that occurred at a temperature of 1.6 ° C was a total of 5700 mm, which was reduced to -1.6 ° C and a value of 3700 mm owing to climate change for the next 34 years.
The highest limit of the precipitation range at Boroojen station has increased from +18 ° C in the historical era to +24 °C in the anticipated period as a result of the modifications.
Conclusion: The results of the trend test on the predicted data demonstrate that it is present in the monthly rainfall in the study stations in a substantial way. The temperature distribution of precipitation varies as a result of these changes, which are caused by the impacts of climate change on the study region.
Materials and Methods: In this study, the maximum entropy of three replications was applied to Maxent software to investigate landslide susceptibility in the southern areas of the Fars Province, Iran. Thirteen factors were used to prepare the landslide susceptibility map: lithological units (Lu), land use/land cover (LULC), slope percentage (SP), slope aspect (SA), altitude, plan curvature (Plan-C), topographic wetness index (TWI), distance to river (DTR), distance to roads (DTRS), distance to fault (DTF), drainage density (DD), normalized difference vegetation index (NDVI), and annual mean rainfall (AMR). In this study, the lack of multicollinearity among the effective factors was proven using tolerance (TOL) and variance inflation factor (VIF) indicators. In addition, the weights of these 13 factors were determined using the analytic hierarchy process (AHP) model.
Results: The results of the AHP method show that, in descending order, lithological units, land use-cover, and slope percentage are the most important factors influencing the occurrence of landslides in the study area. Thirty percent of the landslide points were randomly selected, removed from the modeling data, and used for the evaluation using the ROC/AUC indicator. In addition, the final map of the landslide susceptibility was presented in three scenarios using data replication. The preparation of three different outputs had good accuracy, but the third iteration, with an AUC value of 0.778 (ROC= 77.8%), had the highest accuracy in preparing the landslide susceptibility map. The evaluation of landslide susceptibility maps using the second and third iterations, with AUC values of 0.77 (ROC= 77 %) and 0.640 (ROC= 64%), respectively, had good and moderate accuracy with the highest efficiency in predicting landslide sensitivity. Finally, the highest percentage of landslide susceptibility area according to the first, second, and third repetitions were, respectively, in the moderate sensitivity class (0.03-0.1) with the value of 26.14%, in the moderate sensitivity class (0.04-0.4) with a value of 25.91%, and in the moderate sensitivity class (0.04-0.1) with a value of 25.71%, which was the highest percentage of the landslide area.
Conclusion: In general, landslides, due to their dangerous nature, suddenly disrupt the morphology of an area and cause major damage that can be measured in the lithological units of the study area, land-use change, and slope percentage. Therefore, landslides are a complex process that has a devastating effect on the environment and human life and requires more investigation and preventive measures.
Material and Methods: Navrood watershed located in the west part of Gilan province is chosen for the study area in this research. Required data is collected from Kharjgil (1368-1398) and Kholian (1375-1397), including monthly river flow, rainfall, and temperature from Gilan regional water company. The amount of runoff is predicted in two approaches by the received data in monthly and seasonal time steps sing three models of multivariable linear regression, time series, and M5 decision tree. In the first approach, input variables to the model were river flow, rainfall, and temperature with three steps delay. In the second approach, the only variable was river flow with three steps delay. The model evaluation criteria in this research are the mean bias error (MBE), Nash-Sutcliffe efficiency (NSE), and coefficient of determination (R^2).
Results: In the first approach and in monthly timestep, M5 decision tree is selected model with MBE-NSE equal to -0.04,0.80 (train) and 0.01,0.72 (test) in Kharjgil station, and -0.01,0.79 (train) and 0.00,0.86 (test) in Kholian station. In the seasonal time step, the criteria for the M5 decision tree in Kholian station are equal to 0.02,0.78 (train), -0.02,0.86 (test), and in Kholian station are -0.01,0.79 (train), 0.00,0.86 (test). This model was the best in this study for the first approach in the seasonal time step. The second approach has led to different findings considering both monthly and seasonal time steps. In the second approach, the criteria in monthly time step for time series model during train and test in Kharjgil station are respectively -0.05,0.47 and 0.10,0.52 and in Kholian are -0.02,0.63 and 0.2,0.49. The selected model criteria for seasonal time step considering train and test are -0.42,0.58 and 0.06,0.83 in Kharjgil station, and 0.09,0.40 and -0.10,0.62 in Kholian station. The time series model is selected in the second approach in the seasonal time step.
Conclusion: The findings of this research have shown that in both stations and time steps, the M5 decision tree model has shown a higher accuracy in prediction than the two other models in the first approach. Meanwhile, the decision tree model does not show accurate results in the second approach. Alternatively, compared to two other models in both stations and both time steps, the time series model had a higher accuracy. Findings of this research have emphatically shown that specific approaches in choosing the model's inputs can effectively influence the selected model and the accuracy of modeling.
Materials and methods: In this study, the area of Chehel Chay River located at Araz Kooseh was studied. The LISFLOOD-FP two-dimensional hydraulic model outputs were used to calculate the risks associated with flooding, including the risks of water flooding, its severity, and the depth of water flooding that affects people or the environment. After collecting the data and using a series of equations, the risk was calculated and the data were graphically represented as hazard maps. The calculated risk included flood risk to people, buildings, infrastructure, and a building damage map.
Results: In this study, for floods with a return period of 500 years, the highest probability of mortality was 10.08% and the highest probability of bodily injury was 34.81% and the highest amount of damage to buildings was estimated at 8300 million Rials.
Conclusion: Based on theoretical experiences, one of the appropriate methods for flood management is to determine the extent of flood progress and its height relative to the ground and also to determine the characteristics of floods. These characteristics include the speed and direction of flood progress in different return periods, which are called hazard maps. Determining these criteria can lead to a reduction in flood damage in different areas. All four hazard maps including Risk of fatality, Risk of injury to people and Physical Risk Assessment for buildings as well as Economic flood risk to buildings maps showed that the northeast side of the river is the most vulnerable part of the study area. Due to high density construction in those areas, weakness in the strength of buildings and the antiquity of some buildings, awareness of the people and municipalities about the severity of flood risk and understanding the hydraulic behavior of the river is important.
Materials and Methods: This research was conducted using HEC-RAS, GIS software and HEC-GeoRAS add-on. In order to investigate the effect of the ring road and railway line on the flood rate of AqQala city, this effect in three scenarios (absence of ring road and railway line, existence of ring road and railway line with coils installed in the route and existence of ring road and railway line It was discussed along with the embedded culverts and the cracks created in the path during the flood) was discussed.
Results: Examining the three scenarios discussed in this study, it was found that in the first scenario, we see flooding of a large area of the city of AqQala, so that 1.38 square kilometers of the city has been flooded. The second scenario shows an increase in flooding and intensification of floods in the city compared to the first scenario, which causes flooding of 2.53 square kilometers of residential land, and the third scenario shows the positive effect of cracks created during floods to reduce flooding in the city Which has reduced the amount of flooding to 1.98 square kilometers.
Conclusion: Although the low level of ground level in some areas of AqQala city such as Eidgah, Moallemabad and Hakimabad, the flooding of these areas is obvious, a comparison of the first and second scenarios showed that the location of the ring road and rail line Railway in the direction of flood movement has increased the extent of flooding and submergence of some other areas and neighborhoods and the persistence of flood flow in the city of AqQala. On the other hand, by comparing the second and third scenarios, it can be concluded that the lack of procrastination and rapid decision-making regarding the gap on the ring road and railway line, could have reduced the relative flooding of the city and the persistence of floods and submerged some Avoid areas.
Materials and Methods: In this research, the Deciles Index (DI) was used to determine meteorological drought conditions. Firstly the monthly rainfall statistics were collected and tested for accuracy, precision and homogeneity of data from 27 selected meteorological and rain gauge stations during the period from 1990 to 2015. Accordingly, the factor of percentage of droughts occurrence and were determined with yearly time scale for each station, and then the Drought Hazard Index (DHI) was extracted for each of the different intensities. Then, the drought hazard index was extracted by assigning weights and degrees to each drought class based on drought severity. Meteorological drought vulnerability was also calculated using physical and socio-economic indicators. Subsequently, vulnerable areas of drought were identified. Finally, drought Risk quantification was calculated based on two factors:
potential drought hazards and vulnerability rate, and then drought risk areas were specified.
Results: The results of research on drought conditions showed that the most severe droughts occurred in the region in 1990, 1995, 2001 and 2008. Based on the drought hazard index, the results showed that the south western area and part of the northeast of the region, equal to 41.13% of the province, is a region that is prone to severe droughts. The largest of area (64.36% of the area) that located in the eastern part of the province has had severe drought vulnerability. Generally, about 85 percent of the total area of North Khorasan province has been affected by severe to moderate drought vulnerability. Also, about 75 percent of the entire area of the province has a moderate to severe drought risk.
Conclusion: The results of this study indicate that the hazards and vulnerabilities caused by meteorological drought seriously threaten North Khorasan province. The meteorological drought risk maps can be a helpful alert tool at risk reduction plans for all policy makers, managers and stakeholders in the research area. This issue is of particular importance in the planning of agricultural activities, the optimal use of water resources and green water management, especially in this province, where the livelihood of its agricultural also depends on rain-fed agriculture.
Materials and methods: In this study, which was conducted to investigate the trend of vegetation changes in the study area during the period 2001-2018, 16-day combined time series data of MODIS-NDVI called MOD13Q1 with a spatial resolution of 250 meters was used. In this study in order to investigate the significance trend of vegetation cover, the non-parametric Mann-Kendall method was taken. Also the relationship between vegetation changes and altitude was investigated.
Results: Of the total area of the study area, 52% of the area had a decreasing trend of vegetation and the rest showed an increasing trend of vegetation, although a significant decrease in vegetation at the level of 5 and 1% occurred in 36% and 32% of the area, respectively. Also, 31 and 26 percent of the study area had a significant increase in vegetation at the level of 5 and 1 percent. In the study of the relationship between Z-Kendall statistic and height, the results showed that with increasing the height of Z-Kendall statistic increases and the correlation coefficient of height with Z-statistic is about 0.62. It seems that significant positive trends in vegetation occur at higher altitudes and significant negative trends in vegetation occur at lower altitudes. 99% and altitudes of 670 and 840 were obtained for the negative trend of 95 and 99%. In other words, at altitudes above 2030 and 1860, the trend of vegetation changes is positive and at altitudes below 670 and 840 meters, the trend of vegetation changes is significantly decreasing.
Conclusion: The results of this study showed a significant trend of greening at altitudes of more than 2030 meters in the region. It seems that with the increase of temperature due to climate change at elevated area, suitable temperature conditions and increasing of growing season length is provided for crop growth at altitudes. This increase in vegetation was further observed in the east and northeast of the study area. Also, the significant decrease in vegetation in low altitude areas less than 670 meters can be due to increased water requirement of low altitude plants and the occurrence of temperature stresses in these areas, which are mostly in the eastern, southern and low altitudes of the study area. However, it seems that the area between these two altitudes have not had a significant trend in vegetation changes.
Materials and methods: Based on a preliminary experiment, rice husk biochar (pH=5.64) and pine cone biochar (pH=6.56) produced at 300°C were selected for this study. The experiment was performed in a completely randomized factorial design with three replications. Treatments included two types of biochar (pine cone and rice husk) mixed with soil at one, three and six percent (g/g), two types of soil (a sandy loam, Tiran and a clay loam, Lavark), and two incubation periods of one and six months, with 4 controls and a total of 28 pots. The treated soils were kept in an incubator at 25°C and 60% of field (pot) capacity. At the end of the incubation periods, the soil moisture contents at field capacity and the permanent wilting point were measured respectively using sand-kaolin box and pressure plate devices and then soil available water contents was calculated.
Results: The results showed that the addition of biochars improved some physical properties of soils. The treatment of the soils with 3% and 6% of biochars caused significant increases in the available water (AW) in the sandy loam soils compared to the control. The physical quality index of Dexter (SDexter) fitted by van Genuchten–Mualem was significantly increased in the sandy loam soil amended with 6% of the biochars and in the clay loam soil amended with 3% and 6% of the biochars. The use of biochars also improved the physical quality of the soil, described by the Dexter index, from poor to very good.
Conclusion: The results of this study showed that addition of 6% rice husk biochar to the clay loam soil and at the 30 days incubation period, could improve soil properties. Therefore, according to these findings, the biochars produced from pine cones and rice husk can be suggested as a suitable conditioner for improving physical properties of the regional calcareous soils.
Materials and methods: Machine learning methods due to their high accuracy in predicting various issues have been noted in recent years . Therefore, in the present study, two methods of classical artificial neural network (ANN) and deep learning of long short-term memory (LSTM), which is a kind of artificial neural network with layers and amplification algorithms to improve network performance; have been used to predict the bed load of 19 gravel-bed rivers. To define suitable models for networks, the results of 10 experimental formulas in bed load prediction have been evaluated and the parameters of superior formulas have been used as the input of intelligent networks.
Results: The results showed that all experimental formulas had very poor results; As most formulas have predicted the bed load with a Discrepancy index of r greater than 100. However, machine methods with input parameters obtained from experimental formulas have acceptable accuracy in predicting bed load. and in comparison with machine methods, LSTM method has provided more accurate results than ANN method. Finally, the model related to the parameters of Begnold formula in LSTM method with DC= 0.900 and RMSE= 0.024 for the test data is the best model obtained from this research and The average diameter of sediment particles (D50), which is a common parameter of the top three models, has been selected as the most effective parameter in predicting bed load.
Conclusion: Despite the very poor performance of experimental formulas in predicting sediment transport, intelligent networks with input parameters derived from experimental formulas have had good results. Also, LSTM network is more efficient than artificial neural network (ANN) in predicting bed load transfer, which indicates that Maintaining training memory during the training process and adding reinforcement layers to the network improves network performance and increases network accuracy in subsequent training.
Materials and Methods: In this research ERA5 re-analysis and Terra satellite data used for the August 23-26, 2010 event in Hirmand. Products and satellite data used including true color images and AOD and re-analysis data including Surface latent heat flux (SLHF), Surface Sensible Heat Flux (SSHF), Surface net Solar Radiation (SSR), Surface net Thermal Radiation (STR) and Balance Radiation (Rn). Dust particles were routed using the HYSPLIT model and wind speed in the study area was also assessed using the analysis data. Also, for validation of satellite data and re-analysis, visibility and air temperature data, at height of 2 meters, at Zabol Meteorological Station, closest station to the study area, were analyzed.
Results: According to the HYSPLIT model output, most of the dust particles were collected from the deserts of Turkmenistan and then the dry areas around Lake Hamun and parts of northern Pakistan. AOD values showed that from August 21, the value of this index gradually increased so that on the 25th day, the maximum AOD value reached 1.25. Examination of the values of radiation and heat flux indices showed a significant decrease in SSHF, SSR, STR and Rn indices and their values reached the lowest value on the 26th day and the SLHF index with a slight difference on the 25th day reached its lowest value of 58 w/m2. Correlation study showed that SSR and Rn indices with -0.370 and -0.359 respectively had the highest and SLHF index with -0.153 showed the lowest correlation with AOD index.
Conclusion: The results of this study showed that the western parts of Hirmand Basin, Lavar or North wind has emitted dust particles into atmosphere, and the region and rotational currents has caused the distribution of these particles in the study area. The results of satellite data and their re-analysis and matching with real images showed that the study event increased the optical depth of dust particles, which resulted in tangible and surface heat fluxes, solar and thermal radiation, as well as balance. Radiation was greatly reduced. Evaluation of horizontal visibility and air temperature data at a height of 2 meters at Zabol station also confirmed the results of satellite images and re-analysis data.
Materials and Methods: The case study is located in Bushehr province, north of the Persian Gulf and southwest of Iran. To investigate the effect of drought on the amount of dust, data of 7 meteorological stations of Bushehr province with a statistical period of 30 years (1989-2018) was used on an annual scale including: hourly and daily amount of dust, monthly rainfall, temperature, humidity-relative and evapotranspiration. The estimation of drought with standard precipitation, dust occurrence based on phenomenon with codes 07 and 06 and their trend were analyzed by linear regression parametric test. Also, drought zoning of Bushehr province was done in Arc GIS software by IDW method. To investigate the climatic relationship with dust storms, stations with SPEI index and also dust storms that had a significant trend with variable frequency were analyzed using linear regression.
Results: The results showed that in the 30-year period, 79.06% of the frequency was mild drought, 18.96% was moderate drought and 2% was severe drought. Approximately 6.25% of droughts occurred in the first decade, 50% in the second decade and 43.75% in the third decade. The spatial distribution map of drought also showed that the main focus of this phenomenon is in the southern, central and northeastern regions compared to other parts of the province. The Saudi Arabian desert air currents towards the central regions of the province, the lack of proper vegetation, soil erosion and the presence of sand and salt zones in these parts have confirmed this issue. Also, the comparison of the incidence of droughts in the 30-year period shows the probability and frequency of mild droughts compared to moderate droughts, and the probability of occurrence of moderate droughts compared to severe droughts. The value of DSI index for Bushehr province has decreased over time.
Conclusion: This study showed that the DSI index decreased with increasing drought intensity during the study period and its correlation with drought during the 30-year period was not significant. Also, the combination of drought distribution map and DSI index did not show the same pattern. This indicates that human factors have played a more important role in creating a heterogeneous pattern of drought distribution and DSI index in Bushehr province. Certainly, it should be noted that the state of the province's winds is also important in the amount of dust production and droughts. Finally, the relationship between drought and the DSI index has always fluctuated based on droughts and wetlands.
Materials and Methods: All studies and research on the application of amendments in soil and water conservation in different conditions on various components of soil erosion and conservation in Iran were documented in databases and extracted from journal articles, conferences, executive reports, and related research, and theses and dissertations were investigated. The relevant 75 documents were then chronologically evaluated, analyzed, and summarized in order to assess the usage of various amendments in many areas, including the kind of amendments, the scope of use, the experimental setting, and the research variables. The necessary conclusions were ultimately drawn qualitatively.
Results: The use of soil stabilizers and amendments such as organic, inorganic, and biological elements to enhance the erodibility threshold and prevent soil water erosion has been widely documented based on the findings of this study. According to research findings, the performance of amendments varied depending on the kind, manner of application, scale, and soil type. In addition, the findings on the usage of amendments revealed that various additions are used and work well in soil and water conservation. However, adopting any of the customary changes has been noted as a considerable difficulty due to economic, environmental, health, administrative, functional, and technical restrictions. The use of biologically and ecologically friendly alternatives to boost the efficiency of the conditions for balancing and stabilizing the soil environment has been stressed due to the aforementioned constraints for the use of amendments.
Conclusion: Because of the widespread use of amendments, the feasibility of using environmentally friendly amendments, and emphasizing waste management in the primary industry through additional studies and research, there is a need for proper and appropriate measures that are naturally environmentally friendly in the long term. Nevertheless, additional research on the application of various amendments resulting from the direct or modified use of significant industrial wastes with respect to various aspects of environmental, economic, ecological, and even aesthetic and at different scales is necessary to summarize and develop appropriate executive instructions.
Materials and methods: This study was carried out in soil columns with a height of 15 and 30 cm and in a period of 12, 23, 56 and 112 days and including different levels of 1.5 and 3 WP% (Weight percent) of wheat biochar and control treatment as a completely randomized factorial design. The concentration of deltamethrin used was 300 cc per thousand liters per hectare. To determine the residual concentration, the pesticide was sprayed on the surface only once with the recommended dose and according to the considered irrigation periods, the changes of the pesticide over time and at different depths of the soil columns were studied. In this study, Brigham's analytical method was used to obtain the dispersion coefficient. Analysis of variance and comparison of means in the studied treatments was performed using LSD statistical test and SAS 9.4 software.
Results: The results showed that the residual concentrations of pesticides in 1.5 and 3% of biochar treatments compared to the control were decreased 26 and 43%, at depths of 0 -15 cm and 37 and 17% at depths of 15-30 cm respectively. Based on the results, pesticide uptake and stabilization in 3% biochar treatment was more than other treatments. In the control treatment, with increasing soil depth, it was observed that the dispersion coefficient decreased, in the modified treatment with biochar 1.5%, the dispersion increased while in the biochar 3% treatment, the dispersion coefficient decreased significantly by increasing the sample length. Deltamethrin dispersion coefficient in 15 cm columns for control, biochar 1.5 and 3% treatments were 5.37, 1, 3.59 cm and in 30 cm columns 3.91, 1.27, 0.92 cm was obtained, respectively.
Conclusion: Biochar production is very convenient and cost-effective and is successful in restricting the movement and stabilization of pesticides in the soil and by increasing its weight percentage in the soil, due to the surface area of biochar can control the movement of pesticides.
Materials and methods: The used soil was collected from the depth of 0 to 20 cm and was transferred to the laboratory. The study was performed on scale of splash cups and laboratory conditions using the rainfall simulator at rainfall intensity of 80 mm h-1. Also changes of time periods evaluated for durations of 24 h, two, four, eight, 16 and 32 week. Splash erosion measured by collecting the splash particles during each rainfall and then drying at temperature of 105° C. Physical and chemical characteristics of soil determined using current methods of laboratory. Data of splash erosion analyzed using SPSS software, Duncan test and GLM.
Results: The experiments showed that the application of the combination of compost and zeolite on changing the soil splash was the more than their separation effects. The results showed that the combination of compost and zeolite of total splash was with rates of 68.93, 15.53, 49.51, 38.83, 38.83 and 77.66%, respectively, and net splash of 67.27, 10.9, 56.36, 32.72, 47.27 and 72.72% at time periods of 24 h, two, four, eight, 16 and 32 week, respectively. Also, the changes percent of splash changes for the composition of compost and zeolite at the upstream of splash cup observed with amounts of 70.83, 20.83, 83.66, 45.41, 29.16 and 83.33%, respectively, and downstream was amounts of 68.35, 13.92, 51.89, 36.70, 41.77 and 75.94% , respectively. The effect study of time periods showed that the time periods of 32 and eight week had the more reduce at the amount of splash erosion. The statistical results showed that the effect of time period and treatment and their interaction on reducing the total splash and net splash was significant at the level of 99%. Also, the effect of time period and the interaction effect of time period and treatment on reducing the upstream and downstream splash was significant at level of 99%.
Conclusion: Adding these conditioners to the soil cause the reducing the soil splash erosion. The time effect also caused the more effect of the conditioners for reducing the amount of slash erosion. Among the used conditioners, the effect of compost conditioner was more than two other conditioners on reducing splash erosion, because this conditioner by increasing the stability and porosity of soil can bind the soil particles and thus the resistance of soil particles increase against the rainfall energy. Finally, it can be stated that the conditioners application separately and combination can be have the positive effects on decreasing soil splash that will lead to reducing soil loss at the long term.
Materials and methods: The Liqvan watershed with an area of 185 kilometers is located in the northwest of the country and East Azerbaijan province. In this study, for extraction of the depth of snows from 4 radar images of Sentinel 1 related to the time interval of December until March 1398 and a radar image associated with September 1398 in SLC format to implement radar interferometry in SARSCAPE software Used. To increase accuracy part of the work was used from the Google Earth Engine system. For this purpose, to extract the surface of the snow cover and its area of the NDSI daily product of the Modis sensor and the monthly NDSI- DEPTH product was used for extraction of the average depth of snow of each snow month in the Google Earth Engine Cloud System. Also, the Daily Product of Mod11A1 Modis Sensor was used to prepare a temperature map to examine the relationship between temperature and snow characteristics.
Results: Investigating the map of snow surfaces in the area of all months of the study period in the region showed the highest concentration of snow surfaces in high regions. Due to the outputs of the Google Earth Engine system, the highest and lowest snow cover level is calculated by January with 180 kilometers and December with a value of 83 km. The average and the lowest amount of the depth of snow is related to the February and December months, which utilizes the radar interferometry technique of 32 and 9 centimeters and uses the Snow depth- Inst product in the Google Earth Engine system 24 and 4 centimeters Has shown. The values for regression analysis were obtained between the time series of the surface temperature and the surface of the snow cover, respectively, 0/003 and -3/020 for the parameters of Sig and Z. The R2 variable was also obtained 0/47 about the correlation of the depth of snow and lst.
Conclusion: The results of this study indicate the ability of both radar interferometry technique and coding in the Google Earth Engine in calculating the depth of snow.
Maps and measures of the depth of snow can be an appropriate tool for managing water resources in the region for various uses. Also, the results of regression coefficients showed a significant relationship between the LST variable and the depth of snow and snow cover. So that the inverse relationship between the two components of LST and the snow cover (SC) and LST, and the depth of snow, as well as the direct relationship between reduced temperature and LST, showed.
Material and Methods: To determine the homogeneous regions for each year, the optimal number of clusters was initially obtained. After data clustering in Matlab software, the results of clustering were evaluated qualitatively with Schuler and Wilcox diagrams. For better representation of homogeneous regions, classification maps for the study area were presented.
Result and discussion: The results showed that the optimum numbers of clusters in 2006, 2011, and 2016 were 6, 5, and 6, respectively. Analysis of groundwater quality classification maps showed that in 2006, cluster no. 6, including 2.7% of the studied wells located within the city of Kalaleh, is poor in terms of drinking and farming groundwater quality. Also, based on the results, it can be seen that 36.8% of the wells across the province were in good condition in terms of quality of drinking and agricultural parameters in 2011. Likewise, 33.33% of the wells are in a moderate condition in terms of drinking quality, and the status of their groundwater has improved in terms of quality since 2006. Also, the results of NSGA- FCM in 2016 showed that most of the parameters (5.55% of the wells in the province) in the cluster 3 have a moderate quality.
Conclusion: The findings of this study showed that the groundwater quality in the province in 2016 is lower than in 2011, so appropriate management plans should be adopted. Moreover, it was observed that the fuzzy clustering method is a suitable method for assessing and identification of critical region of the quality of groundwater resources, since it considers the uncertainty conditions in the classes of the classification system.
Materials and Methods:In accord with supplementary data layers(geology,pedology,landuse,etc.) and stratified randomized sampling method, eventually, 128 samples from 20cm of soil surface of Mazandaran province (scattered parts), were gathered. First of all, sample-set subdivided into two subsets: calibration and validation. Afterwards, using the hyperspectral analyses, multivariate regression analysis-PLSR method with the leave-one-out-cross-validation technique and some preprocessing algorithms such as: spectral averaging,smoothing and 1stderivative(Savitzky-Golay-derivation algorithm), the definitive calibration model with two&four latent vectors according to indices such as R,R2,RMSE,RPD and RPIQ were made.
Results&Discussion:During the present research based on the sand hyperspectral modeling in the calibration subset containing 96 samples as well as the validation subset composing of 32 standalone samples, it has been showed the first two and four LVs out of the seven LVs can provide the best estimate of the soils of the study province. Consequently, the calibration process of sand hyperspectral model was done based on the first four LVs and the full LOOCV procedure. Because these number of LVs are able to concentrate the info-variance of sand variable more than 60% and likewise, the info-variance of spectral variables more than of 98%. The best calibrated hyperspectral model predicting sand components resulted with these specs: Rc=0.76,R2C=0.57,RMSEc= 9.77 and SEc of about 9.82. The correlation coefficients(R) of sand contents with the effective spectral domains were calculated as: UV-390nm=0.46, Vis-510to540nm about 0.53, 680to690 about 0.55, NIR- 950to970 about 0.67 and 1100nm=0.70, SWIR-1410 nm=0.76, 1860to1900 about 0.76, 2180to2220 about 0.77; which the specified spectral bands(spectral ranges) with the maximum of R contents indicating their highly impact and influence as the independent predictors on the sand parameter hyperspectral modeling processes at the studied soils of Mazandaran province. Furthermore, the most influential spectral domains involved in the modeling process of sand particles were determined as follows: UV-390nm,Vis-440-540nm,NIR-740-990nm,SWIR-1430-1890,1930,2190-2240,2330-2440nm, which these results were in agreement with others. The quality of calibrated sand hyperspectral model via assays such as Hotelling, adjusted leverage and residual variances was also confirmed. The accuracy assessment specs were as: Rp=0.83,R2p=0.68,RMSEp=8.68,SEp=8.72 and bias=-1.26.
Conclusion:Results indicate the apt hyperspectral analyses to estimate the sand based on LV=2: RPDc=1.51,RPIQc=2.44,RPDp=1.78 and RPIQp=2.45, additionally for LV=4:RPDc=1.54,RPIQc=2.48,RPDp=1.75 and RPIQp=2.41 have been gained. On the basis of the RPIQ values which were more than 2, it can be concluded the models are able to estimate the sand contents of Mazandaran soils satisfactorily and showing the acceptable quality of the predicting models utilizing the hyperspectral data. Our results can be the starting point to accurate mapping of sand constituents of soil texture using the RS platforms. It is noteworthy, the characterization of key wavelengths in the hyperspectral modeling of sand components, the upscaling operation as well as constructing the new airborne/satellite hyperspectral sensors can be bettered using the principle wavebands affecting the hyperspectral process so that providing the more precise hyperspectral studying of soil texture constituents using the aerial or space platforms.
Materials and Methods After measuring acidity, electrical conductivity, organic carbon, soil texture, lead, and cadmium concentrations, the relationship between the distribution of biocrusts with soil properties and cadmium and lead concentrations was investigated by principal component analysis. Then, using one-way ANOVA, the most important effective features are identified. Based on Duncan's test, the mean values of soil properties measured in five villages located in Sejzi plain were compared with each other at 95% probability level, and finally, the soil of points of Sejzi plain with higher cadmium and lead concentrations were determined.
Results: According In all studied sites, the average absorbable lead was more than 80 mg/kg (permissible level). The amounts of cadmium were measured at Fasaran and Sejzi at 2.8±0.6 and 2.38±0.18 mg/kg, respectively, that had been exceeded it's permissible level (2 mg/kg). Also, the results of the principal component analysis showed that in the first component, which is 67.4% of the total variance of the data, the correlation between the percentage of silt was 0.438 and the percentage of sand was measured -0.451. In the second component, which is justified about 48.6% of the total variance of the data, the correlation coefficient of the values of cadmium and lead were estimated 0.388 and -0.438, respectively. The comparison of soil properties in different places showed that the average values of soil salinity, organic matter, silt percentage, cadmium and lead are different in those places.
Conclusion: The high concentration of lead and cadmium levels in areas without biocrusts, including Sajzi and Fesaran, were mainly due to human mismanagement and construction of factories, mines, and roads. Also, some intrinsic properties of soil, such as soil texture were effective in the distribution and establishment of biological crusts.
Materials and methods: At first, numerical modeling of Birjand aquifer was performed. MODFLOW numerical simulation of Birjand aquifer area was performed in two permanent and non-permanent modes in 2011. Then the hydraulic conductivity calibration was performed on the mentioned date and validated for two years 1391 and 1392. Then, the necessary scenarios for the project, considering different points for wastewater discharge and artificial feeding, were defined. Finally, the effects of reduction, increase and decrease of 20% harvest on pollutant movement were investigated using MODPATH.
Results: The calibration results show that the observed and calculated mid-level error (RMSE) is 1.071 meters, which is desirable. Also, the level calculated by the model indicates the movement of groundwater in the direction of the dominant slope of the region, ie from east and northeast to west and southwest. Also, the way particles move corresponds to the groundwater gradient and in the general direction from east to west. The length of motion of the particle at a given time in the eastern part of the aquifer is less than the western part.
Conclusion:According to the applied scenarios, it can be concluded that increasing and decreasing the withdrawal of Birjand groundwater by 20% does not make a significant difference in the direction and route of pollutant transfer during 10,000 days, but the artificial feeding scheme has a significant effect on the transfer Leaves pollutant particles. Therefore, due to the problems in the groundwater of Birjand, the implementation of artificial nutrition plan for this city is necessary.
Materials and methods: For this, the research region's precipitation, temperature, and precipitation type data from 1985 to 2018 were used. For the three scenarios RCP2.6, RCP4.5, and RCP8.5, the National Center for Environmental Protection's (NCEP) atmospheric reanalysis data and the CanESM2 model were used to forecast future climate change. Furthermore, the downscaling was done using the SDSM5.3 model. To find data patterns, the classic and modified Mann-Kendall tests were performed. Fixed temperature approaches, the UBC watershed model, the USCE model, and Kienzel's suggested method were utilized to separate the precipitation phase.
Results: To separate the precipitation phase throughout the fundamental period, observational reports were examined, and the approaches Kienzle and USCE gave satisfactory results. Climate change will also produce major changes in the precipitation temperature distribution in the examined mountain region in the future, according to the findings of this study. Also, a significant portion of the influence of climate change on the snow and rain phases. The modifications are done in such a way that rainfall will rise at higher temperatures and decrease at lower temperatures in the prediction period (2026-2060) compared to the observation period (1985-2018). The greatest total rainfall recorded at Shahrekord station during the observation period was 5.7 ° C, which has fallen to 0 ° C in the projected period. The temperature range of precipitation at this station was -10 to +18 degrees Celsius during the observation period, and will climb to an average of -10 to +24 degrees Celsius for all three scenarios over the forecast period. The range of precipitation in the future and measurements at Koohrang station is essentially the same, but climate change has produced a rapid shift in the amount of precipitation in this temperature range. Over example, during the 34-year observation period, the greatest rainfall that occurred at a temperature of 1.6 ° C was a total of 5700 mm, which was reduced to -1.6 ° C and a value of 3700 mm owing to climate change for the next 34 years.
The highest limit of the precipitation range at Boroojen station has increased from +18 ° C in the historical era to +24 °C in the anticipated period as a result of the modifications.
Conclusion: The results of the trend test on the predicted data demonstrate that it is present in the monthly rainfall in the study stations in a substantial way. The temperature distribution of precipitation varies as a result of these changes, which are caused by the impacts of climate change on the study region.
Materials and Methods: In this study, the maximum entropy of three replications was applied to Maxent software to investigate landslide susceptibility in the southern areas of the Fars Province, Iran. Thirteen factors were used to prepare the landslide susceptibility map: lithological units (Lu), land use/land cover (LULC), slope percentage (SP), slope aspect (SA), altitude, plan curvature (Plan-C), topographic wetness index (TWI), distance to river (DTR), distance to roads (DTRS), distance to fault (DTF), drainage density (DD), normalized difference vegetation index (NDVI), and annual mean rainfall (AMR). In this study, the lack of multicollinearity among the effective factors was proven using tolerance (TOL) and variance inflation factor (VIF) indicators. In addition, the weights of these 13 factors were determined using the analytic hierarchy process (AHP) model.
Results: The results of the AHP method show that, in descending order, lithological units, land use-cover, and slope percentage are the most important factors influencing the occurrence of landslides in the study area. Thirty percent of the landslide points were randomly selected, removed from the modeling data, and used for the evaluation using the ROC/AUC indicator. In addition, the final map of the landslide susceptibility was presented in three scenarios using data replication. The preparation of three different outputs had good accuracy, but the third iteration, with an AUC value of 0.778 (ROC= 77.8%), had the highest accuracy in preparing the landslide susceptibility map. The evaluation of landslide susceptibility maps using the second and third iterations, with AUC values of 0.77 (ROC= 77 %) and 0.640 (ROC= 64%), respectively, had good and moderate accuracy with the highest efficiency in predicting landslide sensitivity. Finally, the highest percentage of landslide susceptibility area according to the first, second, and third repetitions were, respectively, in the moderate sensitivity class (0.03-0.1) with the value of 26.14%, in the moderate sensitivity class (0.04-0.4) with a value of 25.91%, and in the moderate sensitivity class (0.04-0.1) with a value of 25.71%, which was the highest percentage of the landslide area.
Conclusion: In general, landslides, due to their dangerous nature, suddenly disrupt the morphology of an area and cause major damage that can be measured in the lithological units of the study area, land-use change, and slope percentage. Therefore, landslides are a complex process that has a devastating effect on the environment and human life and requires more investigation and preventive measures.
Material and Methods: Navrood watershed located in the west part of Gilan province is chosen for the study area in this research. Required data is collected from Kharjgil (1368-1398) and Kholian (1375-1397), including monthly river flow, rainfall, and temperature from Gilan regional water company. The amount of runoff is predicted in two approaches by the received data in monthly and seasonal time steps sing three models of multivariable linear regression, time series, and M5 decision tree. In the first approach, input variables to the model were river flow, rainfall, and temperature with three steps delay. In the second approach, the only variable was river flow with three steps delay. The model evaluation criteria in this research are the mean bias error (MBE), Nash-Sutcliffe efficiency (NSE), and coefficient of determination (R^2).
Results: In the first approach and in monthly timestep, M5 decision tree is selected model with MBE-NSE equal to -0.04,0.80 (train) and 0.01,0.72 (test) in Kharjgil station, and -0.01,0.79 (train) and 0.00,0.86 (test) in Kholian station. In the seasonal time step, the criteria for the M5 decision tree in Kholian station are equal to 0.02,0.78 (train), -0.02,0.86 (test), and in Kholian station are -0.01,0.79 (train), 0.00,0.86 (test). This model was the best in this study for the first approach in the seasonal time step. The second approach has led to different findings considering both monthly and seasonal time steps. In the second approach, the criteria in monthly time step for time series model during train and test in Kharjgil station are respectively -0.05,0.47 and 0.10,0.52 and in Kholian are -0.02,0.63 and 0.2,0.49. The selected model criteria for seasonal time step considering train and test are -0.42,0.58 and 0.06,0.83 in Kharjgil station, and 0.09,0.40 and -0.10,0.62 in Kholian station. The time series model is selected in the second approach in the seasonal time step.
Conclusion: The findings of this research have shown that in both stations and time steps, the M5 decision tree model has shown a higher accuracy in prediction than the two other models in the first approach. Meanwhile, the decision tree model does not show accurate results in the second approach. Alternatively, compared to two other models in both stations and both time steps, the time series model had a higher accuracy. Findings of this research have emphatically shown that specific approaches in choosing the model's inputs can effectively influence the selected model and the accuracy of modeling.
Materials and methods: In this study, the area of Chehel Chay River located at Araz Kooseh was studied. The LISFLOOD-FP two-dimensional hydraulic model outputs were used to calculate the risks associated with flooding, including the risks of water flooding, its severity, and the depth of water flooding that affects people or the environment. After collecting the data and using a series of equations, the risk was calculated and the data were graphically represented as hazard maps. The calculated risk included flood risk to people, buildings, infrastructure, and a building damage map.
Results: In this study, for floods with a return period of 500 years, the highest probability of mortality was 10.08% and the highest probability of bodily injury was 34.81% and the highest amount of damage to buildings was estimated at 8300 million Rials.
Conclusion: Based on theoretical experiences, one of the appropriate methods for flood management is to determine the extent of flood progress and its height relative to the ground and also to determine the characteristics of floods. These characteristics include the speed and direction of flood progress in different return periods, which are called hazard maps. Determining these criteria can lead to a reduction in flood damage in different areas. All four hazard maps including Risk of fatality, Risk of injury to people and Physical Risk Assessment for buildings as well as Economic flood risk to buildings maps showed that the northeast side of the river is the most vulnerable part of the study area. Due to high density construction in those areas, weakness in the strength of buildings and the antiquity of some buildings, awareness of the people and municipalities about the severity of flood risk and understanding the hydraulic behavior of the river is important.
Materials and Methods: This research was conducted using HEC-RAS, GIS software and HEC-GeoRAS add-on. In order to investigate the effect of the ring road and railway line on the flood rate of AqQala city, this effect in three scenarios (absence of ring road and railway line, existence of ring road and railway line with coils installed in the route and existence of ring road and railway line It was discussed along with the embedded culverts and the cracks created in the path during the flood) was discussed.
Results: Examining the three scenarios discussed in this study, it was found that in the first scenario, we see flooding of a large area of the city of AqQala, so that 1.38 square kilometers of the city has been flooded. The second scenario shows an increase in flooding and intensification of floods in the city compared to the first scenario, which causes flooding of 2.53 square kilometers of residential land, and the third scenario shows the positive effect of cracks created during floods to reduce flooding in the city Which has reduced the amount of flooding to 1.98 square kilometers.
Conclusion: Although the low level of ground level in some areas of AqQala city such as Eidgah, Moallemabad and Hakimabad, the flooding of these areas is obvious, a comparison of the first and second scenarios showed that the location of the ring road and rail line Railway in the direction of flood movement has increased the extent of flooding and submergence of some other areas and neighborhoods and the persistence of flood flow in the city of AqQala. On the other hand, by comparing the second and third scenarios, it can be concluded that the lack of procrastination and rapid decision-making regarding the gap on the ring road and railway line, could have reduced the relative flooding of the city and the persistence of floods and submerged some Avoid areas.
Materials and Methods: In this research, the Deciles Index (DI) was used to determine meteorological drought conditions. Firstly the monthly rainfall statistics were collected and tested for accuracy, precision and homogeneity of data from 27 selected meteorological and rain gauge stations during the period from 1990 to 2015. Accordingly, the factor of percentage of droughts occurrence and were determined with yearly time scale for each station, and then the Drought Hazard Index (DHI) was extracted for each of the different intensities. Then, the drought hazard index was extracted by assigning weights and degrees to each drought class based on drought severity. Meteorological drought vulnerability was also calculated using physical and socio-economic indicators. Subsequently, vulnerable areas of drought were identified. Finally, drought Risk quantification was calculated based on two factors:
potential drought hazards and vulnerability rate, and then drought risk areas were specified.
Results: The results of research on drought conditions showed that the most severe droughts occurred in the region in 1990, 1995, 2001 and 2008. Based on the drought hazard index, the results showed that the south western area and part of the northeast of the region, equal to 41.13% of the province, is a region that is prone to severe droughts. The largest of area (64.36% of the area) that located in the eastern part of the province has had severe drought vulnerability. Generally, about 85 percent of the total area of North Khorasan province has been affected by severe to moderate drought vulnerability. Also, about 75 percent of the entire area of the province has a moderate to severe drought risk.
Conclusion: The results of this study indicate that the hazards and vulnerabilities caused by meteorological drought seriously threaten North Khorasan province. The meteorological drought risk maps can be a helpful alert tool at risk reduction plans for all policy makers, managers and stakeholders in the research area. This issue is of particular importance in the planning of agricultural activities, the optimal use of water resources and green water management, especially in this province, where the livelihood of its agricultural also depends on rain-fed agriculture.