نشریه تخریب و احیاء اراضی طبیعی
پیاپی 1 (بهار و تابستان 1399)

Aim of this research was study effect of flood on soil carbon and nitrogen sequestration the soil of the habitat of three plant species Tamarix sp., Halostachys belangeriana and Suaeda  fruticosa Sistan region. To do this research first by survey satellite images, the areas were found that watering and no watering (control treatments) from Afghanistan floods. Then select the introductory treatments, 48 soil samples with five repetitions were collected randomly at 0-30 centimeter soil depth and analyzed Organic carbon, nitrogen, sequestered soil carbon and sequestered soil nitrogen from the three flood and control sites. In order to the compare carbon sequestration and nitrogen between treatments and control treatment using the one-way analysis of variance. Data shows that there were significant difference between soil organic carbon percentage and nitrogen in 0.05 levels. The Pearson correlation coefficient between data shows that the maximum amount of correlation of organic carbon and nitrogen was with organic matter (96%) which was significant at the 99% probability level. The result also shows that the above parameter has 99% negative correlation with soil apparent specific weight. Average comparison mean of carbon sequestration and nitrogen of soil shows that the maximum carbon sequestration and nitrogen were in Tamarix forest with 21.89 and 2.43 ton/ha, respectively. This is equivalent to 80.33 and 8.01 ton of carbon dioxide and air nitrogen dioxide in soil which 2.2 and 2.5 times of carbon sequestration and nitrogen of control treatment (9.76 and 0.97 ton/ha). Environmental economic value of carbon sequestration and nitrogen in floodplain is equivalent $ 300 and 85 billion per hectare, respectively. It is recommended to prevent further effects of climate change on the dry and sensitive ecosystem of Sistan region, increase vegetation through the flow of incoming floods from Afghanistan to eroded areas and seedlings should also be planted in these areas.

Electronic and electrical wastes are special types of wastes that have toxicity, pathogenicity and reliability in the surrounding environment and even in the body of living beings, corrosion of facilities and equipment and the like. The purpose of this study is to investigate and determine the factors influencing the release of nickel element in the environment. To investigate this effect, the effect of various factors such as temperature, pH, humic compounds (secondary herbal products) and time on the release of nickel element from such wastes to water and soil environments were studied. For this purpose, the selected parts were first milled and after preparation, the samples were tested and analyzed separately in water and soil environment and under acidic, neutral and game conditions. The results showed that in the aquatic environment, the rate of penetration of the nickel element is inversely related to the increase in pH and directly to the increase in temperature. The effect of hamic compounds on release is also greater in the play area. Also, the effect of the contact time parameter varies according to the pH changes. In the soil environment, increasing the humidity, acidifying the environment and increasing the humic compounds increase the release of Nickel.

Flood is one of the most devastating natural disasters that annually causes financial and life losses. Therefore, developing a susceptibility map for flood management and reducing its harmful effects is essential. The present study was conducted to prepare a flood susceptibility map using data mining models including Random Forest (RF) and Gradient Boosting Machine (GBM). At first, 275 flooding locations flood and 275 non-flood locations were identified in the Komijan watershed of Markazi province. Spatial locations were randomly divided to 70% (190 location) and 30% (82 location) for modeling and validation, respectively. Then, 12 factors affecting the occurrence of flood including slope, aspect, altitude, rainfall, land use, distance from river, drainage density, plan curvature, profile curvature, lithology, soil and stream power index were determined. The ROC curve was used to evaluate the models used. The results showed that in the validation stage, the under curve for RF and GBM models was 0.83 and 0.75%, respectively, which indicates that the RF model is more accurate in producing a flood susceptibility map. The most important factors affecting the flood are rainfall, distance from river and altitude.

Assessing the success of tree plantations created by executive agencies can be a valuable guide to draw a future path for restoration of forest lands. In order to evaluate the success and impact of pistachio and almond reforestation in the rehabilitation of forest lands in the south of Yazd province, a 157 -hectare area was selected and divided into sections based on planting method. In each section, survival and seedling dimensions were measured. The results of direct sowing and inverted potting methods as well as continuous irrigation and first year irrigation methods were compared by independent t-test. Direct sowing, inverted potting and seedling planting methods were also compared by analysis of variance. Transect method was used to study the richness of herbaceous plants. The results showed that in the first year irrigation section, the total survival rate was 77% and the inverted potting method was more successful than direct sowing. In the continuous irrigation section, the survival rate of pistachio by inverted potting method was 38.8%, direct sowing of almonds was 69.9%, inverse potting was 84.5% and seedling planting was 86.9%. There were a total of 35 plant species in the planting sector and 14 species in the grazing sector. Grass cover density in the planting area was 1.68 seedling.m-2 and cover was 32% vs 0.49 seedling.m-2 and the coverage was 3.91% in the area under grazing. According to the results, the rainfall of the region alone is sufficient for success in almond reforestation. Of course, almond seedling planting with irrigation has also had a significant survival. In general, for almond, seedling planting and inverted potting method are considered suitable but direct sowing has less viability. Also, pistachio reforestation without pioneer species is not recommended and preferably must be done after rehabilitation of nurse trees. Restoration of rangeland cover and the presence of natural regeneration of pioneer species between rows show a positive trend of land reclamation in the area.

Over the past decade, the trend of declining water levels as well as declining groundwater quality along with quantity is a major issue in water resources management. In this study frequency ratio, statistical index, weight of evidence, classification and regression tree (CART) algorithms and random forest methods were used for groundwater salinity hazard mapping in the southern part of Bakhtegan watershed. After considering the salinity threshold for groundwater (EC<1000 µSiemens/cm), As groundwater salinity map, thematic layers of 21 groundwater salinity conditioning factors including altitude, distance to anticlines, distance to synclines, distance to salt plans, distance to saltwater lakes, distance to dams. Soil salinity index, topographic wetness index, curvature, plan curvature, plan curvature, flow accumulation, flow direction, slope, aspect, land use, soil type, climate, land cover, groundwater drop, groundwater level were prepared. EC data were divided into two categories of training and validation and by comparing the salinity map of groundwater with 21 independent factors; the weighting of two-variable methods and the parameters of multivariate methods were estimated. According to the selected factors in the southern plains of Bakhtegan watershed, the results of this study stated that altitude factors, distance to salt plans, distance to synclines and anticlines and distance to saltwater lakes are more important in the occurrence of groundwater salinity in this region. The results of validation of bivariate models estimated the amount of area under the curve (ROC) for frequency ratio methods (0.923), statistical index (0.905) and weight of evidence (0.908), which indicates better performance of frequency ratio method compared to two other methods. Also, the results of multivariate methods showed better performance of random forest method with matching coefficient values (0.91) and correlation coefficient (0.85) than CART with matching coefficient (0.89) and correlation coefficient (0.82). Finaly, in any research, the efficiency of the models depends on the appropriate selection of the effective factor in the occurrence of the phenomenon under study, the quality of the collected data and the quality of the maps used.

Change of rangeland land use is one of the most important threats to rangeland ecosystems that this degradation and change can affect the components of ecosystems. The purpose of this study was to investigate the effect of land use change and compare plant composition and diversity in abandoned rangelands and drylands of three areas of Kilk, Salavat Abad and Sarab Qamish, Sanandaj. For this purpose, in each use, 3 transects with a length of 100 meters were randomly placed in the area and 10 plots of one square meter with a distance of 10 meters were selected on each transect, which a total of 180 plots were harvested. In each plot, the percentage of coverage related to any measurement was recorded and recorded. Indices related to richness, diversity and uniformity were calculated using PAST software. In order to statistically compare each of the parameters, one-way analysis of variance and Duncan's test were used in SPSS software. The results showed that out of 116 identified species, 61 species were common in the two uses and 37 species were found only in rangelands and 18 species were found only in converted lands. The palatable and perennial species Festuca ovina and Stachys inflata were the index of rangeland lands, and the annual and invasive species Heteranthelium piliferum and Taeniatherum crinitum were the index of abandoned drylands. The results showed that there was a significant difference between the indices of richness and diversity in the two uses, but this difference was not significant in the uniformity index. In general, the results showed that changing the use of pastures to agricultural lands has reduced the richness and diversity of species in these lands and agricultural activities on rangeland ecosystems can change the composition of species, the invasion of annual grasses and reduce valuable rangeland plants and forage in the wake of have.

Soil salinity is one of the main desertification factors that have mostly affected the soils in arid and semi-arid regions. Traditional methods of data collection in soil studies have many problems that can be solved by remote sensing techniques. Therefore, this study was conducted to investigate the possibility of preparing soil salinity map using Landsat digital data in Dashli-borun area. In this study, 47 soil surface samples were randomly collected and after preparing the samples in the laboratory, the electrical conductivity of the saturated extract of soil samples was measured. After determining the appropriate bands to participate in the model, the preliminary results showed that there is a significant relationship between the values of surface electrical conductivity with the main band B5 and the combined bands SI1, SI2 and SI3 at the level of 1%. Regression models were used to model soil salinity.Accordingly, the data were divided into educational (80%) and evaluation (20%). The results of evaluating the models based on indices the square root of error and mean error showed that multivariate regression models have higher accuracy than SI3 regression model in predicting soil salinity. The results showed kappa coefficient and overall accuracy obtained from the two models that the multivariate regression model with the percentage of kappa coefficient (71) and overall accuracy (73) had a higher agreement with the salinity of the region. The results showed that the highest soil salinity is in the northern and eastern regions. This study showed that in the Dashli-Borun area, the use of TM digital data and its derivatives can be effective in zoning salinity changes. By completing, expanding and expanding the findings of this study, it is possible to zoning the lands using satellite images and minimizing the need for sampling.

Soil salinization is one of the most important soil degradation phenomena in arid and semi-arid regions. In recent years, indirect methods have been used to estimate soil salinity. For this purpose, 100 samples were taken from a depth of 0-30 cm around Lake Urmia and tested, and soil salinity was estimated using Landsat 8 satellite image indicators and digital elevation model. In order to model soil salinity, decision tree models and artificial neural network were used. Accordingly, the data were divided into educational duality (80%) and evaluation (20%). The results of evaluating the models based on the square root indices of error, mean error and coefficient of explanation showed that the decision tree model has the highest accuracy in predicting soil properties. The results of kappa coefficient and overall accuracy obtained from the two models showed that the decision tree model with having kappa coefficient percentage (56.56) and overall accuracy (73.46) had a greater agreement with the soil salinity of the region. In general, based on the obtained results, it was shown that CRSI and NDSI indices are the most important parameters for predicting soil salinity class and have the highest correlation with terrestrial data. Therefore, in the future studies, it is suggested to use tree models and CRSI and NDSI indices to prepare a digital soil salinity map.

Soil salinity is one of the most important characteristics of the soil. Salinity accumulation is strong in arid areas and it has become a serious environmental problem. Identification and mapping of saline soils often due to temporal and spatial variability and the need for sampling and laboratory work is difficult. In recent decades using geostatistic and remote sensing have been developed for mapping salinity and sodicy of surface soil and monitoring it heir changes. The objective of this research was soil salinity zonation and comparing the capability of geostatistic and remote sensing for mapping soil salinity- in Segzi plain, Esfehan province. For this purpose, 29 soil samples from the study area were randomly sampled and measured the electrical conductivity. TM LandSat 7 images from August 1997 at the same time field sampling were applies to prepare for mapping soil salinity. Then Image processing like image enhancement and PCA were applied on the data. The results indicated that the ordinary kriging (OK) with exponential semivariogram the best method for modeling and interpolating soil salinity. With a significance level analysis and measure study between ground data and output of models, best salinity method selected and extraction soil salinity map. The results showed that the PCA234 method has the highest correlation with the sampling point.  With the results of two periods of 1997 and 2018, it was found that the salinity levels of medium and high classes were reduced in 1997, then in 2018, respectively. Added to the Very high and extreme salinity classes in 2018.

The use of environmentally friendly mulch is one of the methods used to reduce wind erosion and stabilize the sand. To prepare the bed for the treatments in the laboratory, windy sand of the Kashan desert was used. For experiments, metal trays with dimensions of 2 × 30 × 100 cm and for spraying bentonite clay, zeolite, molasses, and lignocellulose treatments were used. Complete randomized examinations were performed. Finally, based on the experimental results and after creating a regression model between the mixed design variables and the response, the optimal value of each mulch in the Design of Expert software was obtained. According to the obtained results, the presence of zeolite, lignocellulose, and molasses as a combination in each mulch creates a significant difference in terms of compressive, shear, impact, abrasion and ridge formation characteristics with other mulches and control samples. The study performed in the maximum and medium state showed that the amount of bentonite and molasses are equal to each other (15 g) and differ in the amount of zeolite and lignocellulose, so that the amount of zeolite and lignocellulose in the maximum state is 5 and 15 g. And in the middle state are 15 and 0 grams. Each material alone shows different responses to different resistances, but what the results of this study show us that the combination of these materials together has improved soil stability indices. So that the amount of compressive strength is 3.2 kg/cm2, the shear strength is 7.9 N/cm2, the impact is 0.8, the wear is 45 and the thickness is 20 mm. Increased compared to the control sample.

Extensive changes in land use over the past few decades have posed a major challenge to the ability of ecosystems to provide services. Therefore, a better understanding of the impact of these changes on the ecosystem services is essential. For this purpose, in the present study, while extracting the land use map for the past and present, the land use map for the future was predicted and extracted using the Scenario Generator tool of InVEST software. Then, the effects of land use change on ecosystem services related to habitat quality in Normab Dam Basin of Golestan province were evaluated using the Habitat Quality tool of InVEST software. The results showed that due to severe changes in land use and conversion of natural lands, especially forest lands into agricultural and residential lands, the quality of habitats has decreased from 2000 to 2018 and land degradation has increased by the same amount. The forecast for 2036 also confirmed that if the current trend continues, the decline in habitat quality will be more severe and land degradation will increase. Based on the results, the average habitat quality for the years 2000, 2018, and 2036 is 0.8, 0.71, and 0.59, respectively, which indicates a sharp decline in habitat quality. Also, the average land degradation for the years 2000, 2018, and 2036 is 0.016, 0.020, and 0.025, respectively, which indicates an increase in degradation over time.

Human-induced land degradation often lead to desertification and then emerging new-born unstable ecosystems, such as dried-up lake and, or wetland beds. Therefore, accelerating the self-restoring time of new-born unstable ecosystems will lead to the achievement of sustainable development goals. Accordingly, this study planned to evaluate the possibility of using cyanobacterial inoculation technology to create biocrusts in the Lake Urmia dried beds, as a new-born and wind erosion-prone ecosystem. To this end, the bulk samples were taken from the Lake Urmia dried beds, and the samples poured into the erosion small-scale trays (with 50, 30, and 10 cm length, width, height). The existing cyanobacteria were selected, purified and proliferated from the soil origin soil, and then they inoculated (1.52 g l-1) on the trays. After 120 days, we measured the important indicators of the biocrust development including chlorophyll concentration, thickness and aggregate stability to assess the extent of biocrust creation. We found that the cyanobacteria inoculation improved the chlorophyll concentration and thickness of the soils by 57 -and 2.89-fold, respectively, as compared to the control. Assessing the scanning electron microscopy images from the soil surface also confirmed the ability of cyanobacteria in increasing the strong bindings between soil particles. By and large, in line with the objectives of soil conservation, our inoculation technique was an effective and rapid way to control land degradation and create biocrusts in the new-born unstable ecosystems.