Climate Change Data Portal
| DOI | 10.1007/s11069-021-04690-0 |
| Morphometry of AFs in upstream and downstream of floods in Gribayegan, Iran | |
| Mokarram M.; Pourghasemi H.R.; Tiefenbacher J.P. | |
| 发表日期 | 2021 |
| ISSN | 0921030X |
| 起始页码 | 425 |
| 结束页码 | 450 |
| 卷号 | 108期号:1 |
| 英文摘要 | This study aims to determine the effect of a flood-spreading system on the morphometric characteristics of alluvial fans (AFs) in Gribayegan Fasa, Iran, and its relationship with erosion, age, texture, and type of formations. After determining the AFs using the semiautomatic method and determining their recharged watersheds, 25 morphometric characteristics were investigated. The most important morphometric characteristics were identified using principal component analysis (PCA). The group method of data handling (GMDH) neural network is used to predict erosion, soil texture, age, and formation material based on the morphometric characteristics of the fan. The results demonstrate that the semiautomatic method can effectively extract AF from the landscape. The results of AF morphometry before and after flood spreading show that the fan area, drainage basin circularity (Cirb), fan perimeter, relief ratio of the fan, fan length, minimum fan height, and maximum fan height were higher before flood spreading, and basin shape, St (soil texture), upper fan slope, fan volume, and sweep angle had higher values after the flood. In addition, the results of PCA show that fan area, fan perimeter, fan length, fan radius, fan volume, basin area, basin perimeter, main channel length, basin length, and drainage density are important factors. The results of the GMDH algorithm reveal that this method can accurately predict the formation, age, soil texture, and erosion rate using morphometric characteristics. Therefore, the R2 is 0.92 for the formation age and R2 is 0.86 for the erosion rates, formation types, and soil texture, respectively. Therefore, the most important morphometric parameters can be determined using PCA, and the conditions and processes in the basin, such as formation material, age, soil texture, and erosion rate, can be predicted with high accuracy using the GMDH algorithm. © 2021, The Author(s), under exclusive licence to Springer Nature B.V. |
| 关键词 | Alluvial fan (AF)Flood spreadingGMDH algorithmGribayegan plainMorphometric characteristicsPCA method |
| 语种 | 英语 |
| 来源期刊 | Natural Hazards
 |
| 文献类型 | 期刊论文 |
| 条目标识符 | http://gcip.llas.ac.cn/handle/2XKMVOVA/206438 |
| 作者单位 | Department of Range and Watershed Management, College of Agriculture and Natural Resources of Darab, Shiraz University, Shiraz, Iran; Department of Natural Resources and Environmental Engineering, College of Agriculture, Shiraz University, Shiraz, Iran; Department of Geography, Texas State University, San Marcos, TX, United States |
| 推荐引用方式 GB/T 7714 | Mokarram M.,Pourghasemi H.R.,Tiefenbacher J.P.. Morphometry of AFs in upstream and downstream of floods in Gribayegan, Iran[J],2021,108(1). |
| APA | Mokarram M.,Pourghasemi H.R.,&Tiefenbacher J.P..(2021).Morphometry of AFs in upstream and downstream of floods in Gribayegan, Iran.Natural Hazards,108(1). |
| MLA | Mokarram M.,et al."Morphometry of AFs in upstream and downstream of floods in Gribayegan, Iran".Natural Hazards 108.1(2021). |
| 条目包含的文件 | 条目无相关文件。 | |||||
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。
