پایش مکانی فرسایش‌ تونلی با استفاده از تصاویر هوایی پهپاد در اراضی باد‌رفت استان گلستان

نوع مقاله : پژوهشی

نویسندگان

1 گروه آبخیزداری و مدیریت مناطق بیابانی، دانشگاه علوم کشاورزی و منابع طبیعی گرگان، گرگان، ایران

2 استادیار گروه آبخیزداری و مدیریت مناطق بیابانی، دانشگاه علوم کشاورزی و منابع طبیعی گرگان، گرگان، ایران

3 دانشیار بخش مهندسی منابع طبیعی و محیط زیست دانشکده کشاورزی دانشگاه شیراز، شیراز، ایران

چکیده

فرسایش تونلی از جمله شکل‌های برجسته فرسایش آبی تشدید شونده است که دارای اندرکنشی بسیار شدید با یکدیگر در اراضی باد‌رفتی شرق استان گلستان است. در این پژوهش سعی بر آن است تا به استفاده از داده هایی با دقت بالا از طریق برداشت‌های میدانی و تصاویر پهپاد تأکید ویژه شده، و پس از آن، به بررسی آستانه‌ای عامل‌های تأثیرگذار بر فرسایش تونلی اقدام گردد.پژوهش حاضر با استفاده از تصاویر هوایی پهپاد در محدوده‌ای به وسعت تقریبی 2700 هکتار در اراضی باد‌رفت شرق استان گلستان انجام گرفت، و مناطق تحت تأثیر فرسایش تونلی شناسایی شدند. با توجه به بازدیدهای انجام گشته، موقعیت 833 تونلی با دستگاه موقعیت‌یاب جهانی و تصاویر تهیه گردیده به‌وسیله‌ی پهپاد ثبت شد. در این تحقیق عامل های پستی‌وبلندی، آب‌شناسی و زیستی به عنوان متغیرهای مستقل و فرسایش تونلی به عنوان متغیر‌های وابسته تجزیه‌و‌تحلیل آماری شدند. تجزیه‌و‌تحلیل عامل‌های پستی‌وبلندی نشان داد که حداکثر تراکم تونلی‌ها در ارتفاع بین 350–300 متر، دامنه‌های شرقی با شیب بیش از 30%، طول شیب کمتر از 5 متر و در نیمرخ طولی و عرضی مقعر به وقوع پیوسته است. در ارتباط با عامل های آب‌شناسی می‌توان اظهار داشت که حداکثر تراکم تونلی‌ها، در حداکثر مقدار عددی شاخص رطوبت پستی‌وبلندی (بیشتر از 12) و در نزدیک‌ترین فاصله نسبت به آبراهه (کمتر از 100 متر) به وقوع پیوسته است. عامل‌های زیستی نیز نشان دادند که حداکثر تراکم تونلی‌ها، در کاربری مرتع، و در مکان‌هایی یافت می‌شوند که این رخساره‌‌ی فرسایشی به جاده­ها نزدیک‌تر است. بنابراین، می­توان پیشنهاد داد که شناسایی رخساره­ی فرسایشی تونلی از طریق مشاهده‌ها و داده‌های با دقت بالا صورت گیرد تا منجر به درک بهتر عامل های مؤثر بر رخداد آنها گردد.

کلیدواژه‌ها


عنوان مقاله [English]

A Review of Spatial Monitoring of Piping Collapse Using Unmanned Aerial Vehicle in Loess-Derived Soils in the Golestan Province

نویسندگان [English]

  • Narges Kariminejad 1
  • Mohsen Hosseinalizadeh 2
  • Hamid Reza Pourghasemi 3
1 Dept. of Watershed & Arid Zone Management, Gorgan University of Agricultural Sciences & Natural Resources, Gorgan, Iran
2 Assistant Professor, Dept. of Watershed & Arid Zone Management, Gorgan University of Agricultural Sciences & Natural Resources, Gorgan, Iran
3 Associate Professor, Department of Natural Resources and Environmental Engineering, College of Agriculture, Shiraz University, Shiraz, Iran
چکیده [English]

Piping erosion is an influential landform of intensified water erosion that interact with each other in the loess-derived soilsof the Province of Golestan (NE Iran). This study attempts to emphasize the use of high-precision data through field surveys and UAV images, and then to establish a threshold to study the factors that affect piping erosion. The present study was carried out using photogrammetric drones in an area of ​​approximately 2700 hectares in the loess lands in the east of the Province of Golestan and identified areas affected by piping erosion. A total of 833 pipes were recorded using the GPS and the orthophoto images from the UAV. Topographic, hydrological, and biological factors were treated as independent variables and piping erosion as dependent variables through statistical analyzes. The topographic factors indicated that the maximum density of piping occurred at altitudes of between 300–350 m, at maximum slope of more than 30%, at slope length less than 5m, and in concave tracts and profile curvatures. Regarding the hydrological factors, the maximum piping density occurred at the maximum numerical value of the topographic wetness index (more than 12), and at the closest distance to waterways (less than 100m). Biological factors indicated that the maximum density of pipes is in the rangelands and where this erosional facies is closest to the roads. Therefore, it can be suggested that an accurate identification of the piping erosion is facilated through ground observations aided by high-precision areal photography and understanding causative factors developing them.

کلیدواژه‌ها [English]

  • Golestan province
  • Loess-derived soils
  • Piping
  • Unmanned aerial vehicle
Bernatek-Jakiel A, Kacprzak A, Stolarczyk M. 2016. Impact of soil characteristics on piping activity in a mountainous area under a temperate climate (Bieszczady Mts., Eastern Carpathians). Catena. 141 (0341–8162): 117–129.
Bernatek-Jakiel A, Wrońska-Wałach D. 2018. Impact of piping on gully development in mid-altitude mountains under a temperate climate: A dendrogeomorphological approach. Catena. 165 (0341–8162): 320–332.
Castillo C, Taguas EV, Zarco‐Tejada P, James MR, Gómez JA. 2014. The normalized topographic method: an automated procedure for gully mapping using GIS. Earth Surface Processes and Landforms. 39(15): 2002–2015.
Colomina I, Molina P. 2014. Unmanned aerial systems for photogrammetry and remote sensing: A review. ISPRS Journal of Photogrammetry and Remote Sensing. 92 (0924–2716): 79–97.
Cucchiaro S, Cavalli M, Vericat D, Crema S, Llena M, Beinat A, Marchi L, Cazorzi F. 2018. Monitoring topographic changes through 4D-structure-from-motion photogrammetry: Application to a debris-flow channel. Environmental Earth Sciences. 77(18): 632–652.
Faulkner H. 2013. Badlands in marl lithologies: A field guide to soil dispersion, subsurface erosion and piping-origin gullies. Catena. 106 (0341–8162): 42–53.
Frankl A, Poesen J, Deckers J, Haile M, Nyssen J. 2013. Gully head retreat rates in the semi-arid highlands of Northern Ethiopia. Geomorphology. 173 (0169–555X): 185–195.
Hosseinalizadeh M, Kariminejad N, Campetella G, Jalalifard A, Alinejad M. 2018 a. Spatial point pattern analysis of piping erosion in loess-derived soils in Golestan Province, Iran. Geoderma. 328 (0016–7061): 20–29.
Hosseinalizadeh M, Kariminejad N, Alinejad M. 2018b. An application of different summary statistics for modelling piping collapses and gully headcuts to evaluate their geomorphological interactions in Golestan Province, Iran. Catena. 171 (0341–8162): 613–621.
Hosseinalizadeh M, Kariminejad N, Rahmati O, Keesstra S, Alinejad M, Mohammadian Behbahani A. 2019. How can statistical and artificial intelligence approaches predict piping erosion susceptibility?. Science of the Total Environment. 646 (0048–9697): 1554–1566.
Jalalifard A, Hosseinalizadeh M, Komaki ChB, Azim Mohseni M. 2018. Modeling of piping erosion in loess lands. Journal of Environmental Erosion Research. 4(32): 1–18. (In Persian).
Jones JAA. 2010. Soil piping and catchment response. Hydrological processes. 24(12): 1548–1566.
Kariminejad N, Hosseinalizadeh M, Pourghasemi HR, Bernatek-Jakiel A, Campetella G, Ownegh M. 2019a. Evaluation of factors affecting gully headcut location using summary statistics and the maximum entropy model: Golestan Province, NE Iran. Science of the Total Environment. 677 (0048–9697): 281–298.
Kariminejad N, Hosseinalizadeh M, Pourghasemi HR, Bernatek‐Jakiel A, Alinejad M. 2019b. GIS‐based susceptibility assessment of the occurrence of gully headcuts and pipe collapses in a semi‐arid environment: Golestan Province, NE Iran. Land Degradation & Development. 30 (18): 2163–2380.
Knapen A, Poesen J. 2010. Soil erosion resistance effects on rill and gully initiation points and dimensions. Earth Surface Processes Landform. 35 (2): 217–228.
Lozano-Garcia B, Parras-Alcantara L, Brevik EC. 2016. Impact of topographic aspect and vegetation (native and reforested areas) on soil organic carbon and nitrogen budgets in Mediterranean natural areas. Science of the Total Environment. 544 (0048–9697): 963–970.
Maleki S, Khormali F, Bodaghabadi MB, Mohammadi J, Hoffmeister D, Kehl M.  2018. Role of geomorphic surface on the above-ground biomass and soil organic carbon storage in a semi-arid region of Iranian loess plateau. Quaternary International. 134 (3–4): 178–189.
Marzolff I, Ries JB, Poesen J. 2011. Short‐term versus medium‐term monitoring for detecting gully‐erosion variability in a Mediterranean environment. Earth Surface Processes and Landforms. 36(12): 1604–1623.
Mlambo R, Woodhouse I, Gerard F, Anderson K. 2017. Structure from motion (SfM) Photogrammetry with drone data: A low cost method for monitoring greenhouse gas emissions from forests in developing countries. Forests. 8 (3): 68–72.
Peter KD, d'Oleire-Oltmanns S, Ries JB, Marzolff I, Hssaine AA. 2014. Soil erosion in gully catchments affected by land-levelling measures in the Souss Basin, Morocco, analysed by rainfall simulation and UAV remote sensing data. Catena. 113 (0341–8162): 24–40.
Poesen J, Nachtergaele J, Verstraeten G, Valentin C. 2003. Gully erosion and environmental change: Importance and research needs. Catena. 50(2–4): 91–133.
Pourghasemi HR, Yousefi S, Kornejady A, Cerdà A. 2017. Performance assessment of individual and ensemble data-mining techniques for gully erosion modeling. Science of the Total Environment. 609 (0048–9697):764–775.
Seibert J, Stendahl J, Sorensen R. 2007. Topographical influences on soil properties in boreal forests. Geoderma. 141(1–2): 139–148.
Stöcker C, Eltner A, Karrasch P, 2015. Measuring gullies by synergetic application of UAV and close range photogrammetry—A case study from Andalusia, Spain. Catena. 132 (0341–8162): 1–11.
Teka K, Nyssen J, Teha N, Haile M, Deckers J. 2015. Soil, land use and landform relationship in the Precambrian lowlands of northern Ethiopia. Catena. 131(0341–8162): 84–91.
Torri D, Poesen J. 2014. A review of topographic threshold conditions for gully head development in different environments. Earth Science Reviwe. 130 (0012–8252): 73–85.
Trimble Business Center. 2008. T.B.C Release 2: Capability to Efficiently Edit, Process, and Adjust Geospatial Data. Trimble Business Center, Ohio, U.S.A. www.trimble.com.UNISDR. 2009. Terminology on Disaster Risk Reduction. United Nations International Strategy for Disaster Reduction (UNISDR): Geneva, Switzerland.
Tsui CC, Chen ZS, Hsieh CF. 2004. Relationships between soil properties and slope position in a lowland rain forest of southern Taiwan. Geoderma. 123(1–2): 131–142.
Tziavou O, Pytharouli S, Souter J. 2017. Unmanned Aerial Vehicle (UAV) based mapping in engineering geological surveys: Considerations for optimumresults. The address for the corresponding author was captured as affiliation for all authors. Engineering Geology. 232 (0013–7952): 12–21.
Vega F, Ramírez F, Siaz M, Rosua F. 2015. Multi-temporal imaging using an unmanned aerial vehicle for monitoring a sunflower crop. Biosystems Engineering. 132 (1537–5110): 19–27.
Verachtert E, Van Den Eeckhaut M, Poesen J, Deckers J. 2010 Factors controlling the spatial distribution of soil piping erosion on loess-derived soils: A case study from central Belgium. Geomorphology, 118 (0169–555X): 339–348.
Wang X, Wei H, Khormali F, Taheri M, Kehl M, Frechen M, Lauer M, Chen M. 2016. Grain-size distribution of Pleistocene loess deposits in northern Iran and its palaeoclimatic implications. Quaternary International. In Press. Quaternery international, 429 (1040–6182): 41–51.
Weiler M, McDonnell JJ. 2007. Conceptualizing lateral preferential flow and flow networks and simulating the effects on gauged and ungauged hillslopes. Water Resources Research. 43(3): 1–13.
Xu Q, Kou P, Wang C, Yunus AP, Xu J, Peng S, He C. 2019. Evaluation of gully head retreat and fill rates based on high-resolution satellite images in the loess region of China. Environmental Earth Sciences. 78(15): 465–480.
Zhang Y, Wua Y, Liu B. 2006. Characteristics and factors controlling the development of ephemeral gullies in cultivated catchments of black soil region, Northeast China. Soil & Tillage Research. 96 (0167–1987): 28–41.