@article { author = {Javadi, Mohammad Reza and Zehtabian, Gholamreza and Ahmadi, Hassan and Ayoubi, shamsollah and Jafari, Mohammad}, title = {Investigation of spatial variability of soil erosion factor using some geostatistical methods (case study: Nomehrood watershed)}, journal = {Researches in Earth Sciences}, volume = {13}, number = {2}, pages = {42-57}, year = {2022}, publisher = {Shahid Beheshti University}, issn = {2008-8299}, eissn = {2588-5898}, doi = {10.48308/esrj.2022.101780}, abstract = {IntroductionDue to the interaction of effective factors in soil formation, changes in soil properties from one place to another and even for one type of soil will be obvious. Iran is one of the countries that has many problems in terms of soil erosion, so that every year millions of tons of rich and fertile soil is eroded from its original location due to mismanagement and unprincipled and becomes inaccessible. Continuation of this trend in recent years has led to the creation of acute environmental problems that should be adopted principled and logical solutions to not intensify and continue this trend.materials and methodsNomehrud watershed is limited to Noor city from the north and the Caspian Sea from the east to Vazrud watershed from the west to Noorrud watershed and from the south to Haraz watershed. Its area is about 50 square kilometers. The study area is located between the northern latitudes approximately 4014000 to 4027100 and the eastern longitudes approximately 590300 to 597000 (in the utm system). The average annual rainfall is 613 mm. At first, the whole area was divided into one kilometer square networks (1000 meters * 1000 meters) and within each network, according to the conditions of access to different parts of the region and homogeneity in other characteristics (topography, lithology, land use and soil science) two Three soil samples were taken randomly from a depth of 0 to 30 cm. Soil structure was determined directly in the desert. Parameters, percentage of coarse sand (by sieving method), silt + very sandy (by sieving method), organic matter (by walkie-block method), soil structure (in the desert) and soil permeability (using the relationship between soil texture and group Hydrological) was determined and finally the amount of soil erodibility factor was obtained for each sampling site. Finally, the soil erodibility factor was zoned using some interpolation methods.Results and DiscussionDue to the existence of land types in the control area, we have a wide range between the minimum and maximum values ​​of the studied parameters and are involved in the soil erodibility factor. The soil structure in the area is mainly spongy grains. Soil permeability is often in the middle to low category, the amount of organic matter between 0.3 to 5.4, silt in the area 4 to 62%, clay 2 to 51%, sand 14 to 72% and erosion factor values ​​between Is set to 0.05 to 0.6. Gaussian model was selected from the fitted models. Considering the accreditation accuracy indicators, it was found that the kriging method has a higher accuracy than other methods. According to the zoning map, soil erodibility factor shows that except for the central parts of the region, which have dense and semi-dense forest lands, other parts of the region are more sensitive to soil erosion, which is mainly due to the reduction. Soil permeability, higher amounts of silt, lower amounts of clay and sand and the presence of formations more susceptible to erosion, etc., which is accompanied by the effect of destructive factors such as overgrazing in pastures (village and upstream lands), destruction of forest areas (Thin) due to the entry and grazing of livestock in these areas and also the unprincipled use of these lands for recreational activities and wood smuggling on the one hand and lack of access to barren and mountainous forest areas on the other(central areas)Be.ConclusionConsidering the conditions and situation of degradation in the areas of natural resources of the country, estimating and determining the soil erodibility factor and subsequently using it in different models of soil erosion is an important and necessary matter. In general, it can be said that among the various interpolation methods, the kriging method has a special place. According to some researchers, this method works as the best method of interpolation and estimation in non-statistical points in homogeneous regions. This method requires prior calculation and determination of the spatial correlation of field data, which can be done by drawing a toxic experimental variogram and selecting an appropriate mathematical model that can fit its points. One of the advantages of production plans is the quantification of the obtained results, which leads to the ability to reproduce and update the obtained information.}, keywords = {Nomehroud watershed,Soil physical properties,Interpolation Methods,Erodibility Factor}, title_fa = {بررسی تغییرپذیری مکانی عامل فرسایش‌پذیری خاک با استفاده از برخی روش‌های زمین‌آماری(مطالعه موردی: حوزه آبخیز نومه رود)}, abstract_fa = {تغییرات مکانی در خصوصیات خاک به دلیل تغییر در فاکتورهای زمین­شناسی و خاک­شناسی دخیل در تشکیل خاک جزء ذاتی آن به شمار می­رود. هدف از این مطالعه بررسی تغییرپذیری مکانی عامل فرسایش­پذیری خاک در حوزه آبخیز نومه رود واقع در شهر نور استان مازندران می­باشد. بدین منظور ابتدا منطقه مورد نظر به شبکه­های یک کیلومتر مربعی (1000متر*1000متر) تقسیم­بندی شد و در هر شبکه از عمق 0 تا 30 سانتی متری به تعداد 2 الی 3 نمونه خاک و جمعا 135 نمونه خاک از کل منطقه اخذ گردید. سپس پارامتر ساختمان خاک، درصد مواد آلی، نفوذپذیری، درصد شن درشت، درصد شن خیلی­ریز + سیلت اندازه­گیری شدند و فاکتور فرسایش­پذیری خاک تعیین گردید. پس از بررسی و آزمون نرمال بودن داده­ها، تغییرپذیری مکانی فرسایش­پذیری خاک با استفاده از تغییرنما و نسبت اثر واریانس اثر قطعه­ای به واریانس کل مورد بررسی قرار گرفت. سپس مناسب­ترین مدل تئوری به داده­های تجربی برازش داده شد. جهت انتخاب مدل درون­یابی مناسب از تخمینگرهای کریجینگ و روش­های معین (IDW و RBF) در محیط نرم افزاری GS+ استفاده به عمل آمد. انتخاب بهترین روش و مدل براساس کم­ترین خطای MAE  و RMSE صورت پذیرفت. نتایج نشان داد که از بین روش­های مورد بررسی، روش کریجینگ (0320/RMSE=0 ) به عنوان مناسبترین روش درون­یابی و الگوی گوسی نیز به عنوان بهترین مدل برازش داده شده برای داده­های فاکتور فرسایش­پذیری خاک در منطقه شناخته شده است. دامنه وابستگی مکانی برای این متغیر نیز براساس بهترین روش حدود 3500 متر به دست آمده است.}, keywords_fa = {حوزه آبخیز نومه رود,خصوصیات فیزیکی خاک,روش‌های درون یابی,عامل فرسایش‌پذیری}, url = {https://esrj.sbu.ac.ir/article_101780.html}, eprint = {https://esrj.sbu.ac.ir/article_101780_8224afbd4203feea4e121e40b0252596.pdf} }