مجله مدیریت بیابان
پیاپی 18 (تابستان 1400)

Sand dunes are one of the most dynamic geomorphic features of the earth's surface. Accordingly, identifying the factors affecting the mobility of sands and predicting their future status is essential to control dust. The study area was selected due to the location of Sabzevar city in the busiest railway line of the country, and the condition of sand dunes around this city. For this purpose, after calculating the percentage of erosive winds and drought index, the Lancaster index based on the average annual rainfall ratio and annual potential evapotranspiration for the period of 1990-2016 was calculated for analysis of sand dunes' mobility status. To predict the effect of climate change on the mobility of sand dunes, a sensitivity analysis test was carried out. The results show that the values ​​of the Lancaster index in this station did not show the inactive status in this span time period. The results of the analysis of the relationship between drought index and mobility of sand dunes show a significant effect of drought on the mobility and activity of sand dunes. Finally, the results of sensitivity analysis showed that if the frequency of erosive winds and evapotranspiration potential increases by 30%, the activity of sand dunes in the Sabzevar station will increase by 38%. Also, due to the potential of solid particles in creating dust, the location of sand dunes, and the study of local dust at Sabzevar station, the priority is to stabilize the hills located in the east of the study area.

The purpose of this study is to investigate the effect of floodwater spreading on the vegetation of Abdalan plain after 24 years since the implementation of the project. For this purpose, the changes in vegetation density and diversity and soil characteristics of the floodwater spreading were considered as the basis for the effectiveness of various floods. To determine the characteristics of density and percentage of vegetation, percentage of rocks, gravels, litter, and bare soil as well as Physico-chemical characteristics of soil in each area of floodwater spreading and control, 3 transects with a length of 100 meters were deployed. Measuring and sampling were performed on one square meter plots. The results of field studies led to the identification of 36 plant species and 33 genera belonging to 14 plant families. The most important plant families in the region are Asteraceae, Poaceae, and Fabaceae. The results showed that there are 34 plant species in the floodwater spreading area and 25 plant species in the control area. Of these, 12 plant species were observed only in the floodwater spreading area and 2 plant species were observed only in the control area, and 23 plant species were common in both areas. According to the results, the percentage of cover and density of plants in the floodwater spreading area has increased compared to the control area by 32.8% and 4.4%, respectively. The percentage of clay, silt, and sand has increased compared to the control in the field of floodwater spreading. Sufficient moisture and suitable fine-grained sediments to maintain the required moisture for a longer time as well as the seeds in the sediments have caused the growth and increase of density and canopy cover of plants in the field of floodwater spreading. These operations on the Abdalan plain have caused the revitalization of the region by changing the physical characteristics of the surface soil and improving vegetation conditions.

In recent decades, the increase in temperature has caused widespread climate change all over the world, especially in arid and semi-arid regions of Iran and Yazd province. The purpose of this study is to project climate change in Yazd province using the CanESM2 model and new emission scenarios (RCP) during 2021-2050 (near future) and 2051-2080 (distant future) and to study the trend of changes in the baseline period using the Mann-Kendall test. The statistical indices of R2, RMSE, and NSE were used to evaluate the performance of the CanESM2 model. According to the results, the model had an appropriate performance for projecting precipitation and temperature in the future period and was classified into good and very good classes in terms of capability. Investigating the trend of the annual change of temperature and precipitation in the baseline period showed that the temperature had an increasing trend under most scenarios and stations, while the trend of the change of precipitation was no significant. The results of temperature changes in Yazd province indicated an increase of 2.2, 1.2, and 2.5 °C during 2021-2050 and 2.28, 3.19, and 4.77°C during 2051-2080 under RCP2, RCP4.5, and RCP8.5 scenarios, respectively. Changes in precipitation in Yazad province during the winter season showed a decrease in precipitation by 32, 26, and 34% during 2021-2050 and by 32, 32, and 5% during 2051-2080 under RCP2.6, RCP4.5, and RCP8.5 scenarios, respectively.

This study aimed to identify the epicenter and co-occurrence factors of dust storm waves in Kermanshah from 16 to 18 June 2016. To investigate the synoptic conditions of the causes of this phenomenon, data set with a resolution of 0.125º arcs from the European Center for Medium-Term Atmospheric Prediction (ESMWF), including geopotential height at 500 hPa, omega at 700 hPa, sea level pressure, orbital components and meridian at 300 hPa level, specific moisture at 700 hPa level, soil moisture up to 10 cm depth and dust optical depth were used. To route, the origin of dust particles, the Lagrangian method of the HYSPLIT model was used 48 hours before the occurrence of dust phenomenon in Kermanshah at three altitude levels of 200, 1000, and 1500 m. The dust storm was also simulated using WRF-chem numerical weather forecasting model. Finally, through the processing of MODIS satellite images, its scope was determined. Examination of HYSPLIT tracking maps showed that the central and western deserts of Iraq and the Syrian are the main sources of dust for the study area. In synoptic conditions, simultaneously with the occurrence of rising dust, cyclonic systems play a significant role in the transmission of this phenomenon. Significant strengthening of the Iraqi low-pressure system along with the formation of traffic in the Zagros mountains has caused the creation and transfer of dust in the warm period of the year to the study area. The spatial distribution of the dust interpreted by the MODIS images is consistent with the spatial distribution of the dust concentration simulated by the WRF-chem model.

groundwater. In the present study, the 3-year drought and wet periods were determined using 23-year rainfall data of four meteorological stations and the SIAP index. To investigate the physicochemical properties of groundwater, after considering the data of observation wells in the Eastern part of Gorgan plain, 14 deep and semi-deep wells were selected. Then, three criteria of EC, SAR, and Na were used to assess the water in the agricultural sector and the Schoeller diagram was used to assess the water in the drinking sector. To estimate the significant differences between the physicochemical properties of groundwater in the three periods of the wet period, drought, and long-term, an F-test at the probability level of 0.05 was used. The results revealed that the water quality of semi-deep wells is better than for deep wells in agriculture and drinking water sections. Based on the Piper diagram, the chemical facies of semi-deep wells are less diverse than deep wells. The results of both deep and semi-deep wells showed that chemical facies in the dry season show a greater tendency to achieve seawater composition. The results of the F test showed that there is a significant difference with 95% probability between groundwater quality parameters in semi-deep aquifers in wet and dry periods. In contrast, the occurrence of wet and dry periods in the study area had little effect on the physicochemical properties of deep aquifers.

Land use and land cover (LULC) is one of the most important factors that affect the desertification risk in this study, the desertification sensitivity of the Mokhtaran basin in South Khorasan province was estimated by integrating LU/LC scenarios with the MEDALUS environmentally sensitive areas (ESAs) model to predict the desertification risk. The four main MEDALUS criteria including soil, climate, vegetation, and management were examined to assess the sensitive areas to the desertification. Land use maps were categorized using the Landsat satellite imageries of TM, ETM+, and OLI sensors for 1987, 1998, 2003 as a past scenario, and 2015 as a current scenario. Land use maps for 2025 and 2035 were produced as the future scenario based on the simulation of CA-Markov models. The validation results confirmed the model accuracy by calculating the kappa coefficient of 0.95. The land use map was predicted for the years 2025 and 2035 based on the transition rules and a transition area matrix. The results showed that the rainfed area was reduced by 68.29 km2 and the agricultural land was increased by 25.35 km2 during theperiod. In the protection area of playa-bare lands, the changes showed this area was increased by 26.86 km2. The rangeland has also experienced positive changes with an increase of 18.83 km2. Compared to the current scenario, the desertification trend in the future scenario was positively predicted by increasing the area of critical areas from 30.9% to 48.7% over 20 years. The most susceptible lands to desertification were known as playa-bare lands.

Drought forecasting is of particular importance in water resources management. Drought forecasting allows planners to schedule for reducing the negative impacts of drought as well as to adapt to it. Drought prediction is more important in arid regions. Because these areas are inherently water scares and the consequences of drought in these areas are more severe. Due to the high variabilities of the temporal and spatial distribution of precipitation in these areas, the frequency of drought is higher and results in more difficulty to model and predict drought. In this study, since drought time series is nonlinear and cyclic, nonlinear autoregressive neural networks (NARs) were used to predict short-term and long-term drought in Yazd synoptic station from 2006 to 2018. Reconnaissance Drought Index (RDI) which in addition to precipitation, considers potential evapotranspiration to monitor droughts, for one, three, and six months timescales was calculated. Potential evapotranspiration was calculated using the FAO-Penman-Monteith method. The results of short-term (one month) drought prediction presented that the model provides high performance in predicting three and six months RDI values. The results of long-term (13-years) drought forecasting (without access to real drought data from 2006 to 2018) indicated that RDI values in dry months show best fit to real values ​​ in ​​ three months’ timescale. To improve the efficiency of the model in the long-term drought forecasting, long-term precipitation and potential evapotranspiration (without model access to real data from 2006 to 2018) were predicted. RDI values ​​were then calculated based on the predicted precipitation and potential evapotranspiration data. The results showed that the prediction accuracy increased in one and three months scales. Also, on six months’ timescale, RDI data were more accurately predicted in dry months.