共查询到10条相似文献，搜索用时 125 毫秒
1.
Alireza Arabameri Khalil Rezaei Hamid Reza Pourghasemi Saro Lee Mojtaba Yamani 《Environmental Earth Sciences》2018,77(17):628
Toroud Watershed in Semnan Province, Iran is a prone area to gully erosion that causes to soil loss and land degradation. To consider the gully erosion, a comprehensive map of gully erosion susceptibility is required as useful tool for decreasing losses of soil. The purpose of this research is to generate a reliable gully erosion susceptibility map (GESM) using GIS-based models including frequency ratio (FR), weights-of-evidence (WofE), index of entropy (IOE), and their comparison to an expert knowledge-based technique, namely, Analytic Hierarchy Process (AHP). At first, 80 gully locations were identified by extensive field surveys and Google Earth images. Then, 56 (70%) gully locations were randomly selected for modeling process, and the remaining 26 (30%) gully locations were used for validation of four models. For considering geo-environmental factors, VIF and tolerance indices are used and among 18 factors, 13 factors including elevation, slope degree, slope aspect, plan curvature, distance from river, drainage density, distance from road, lithology, land use/land cover, topography wetness index (TWI), stream power index (SPI), normalized difference vegetation index (NDVI), and slope–length (LS) were selected for modeling aims. After preparing GESMs through the mentioned models, final maps divided into five classes including very low, low, moderate, high, and very high susceptibility. The receiver operating characteristic (ROC) curve and the seed cell area index (SCAI) as two validation techniques applied for assessment of the built models. The results showed that the AUC (area under the curve) in training data are 0.973 (97.3%), 0.912 (91.2%), 0.939 (93.9%), and 0.926 (92.6%) for AHP, FR, IOE, and WofE models, respectively. In contrast, the prediction rates (validating data) were 0.954 (95.4%), 0.917 (91.7), 0.925 (92.5%), and 0.921 (92.1%) for above models, respectively. Results of AUC indicated that four model have excellent accuracy in prediction of prone areas to gully erosion. In addition, the SCAI values showed that the produced maps are generally reasonable, because the high and very high susceptibility classes had very low SCAI values. The results of this research can be used in soil conservation plans in the study area. 相似文献
2.
为探明细沟形成条件下不同土壤坡面水沙变化特性,利用室内模拟降雨试验,分析了塿土和黄绵土在细沟发育及已有细沟条件下的水沙过程变化规律。结果表明,塿土产流快,易形成细沟,细沟发育有明显的规律性,在坡面上呈平行状分布,细沟密度与坡度密切相关,细沟存在会延长产流时间;黄绵土产流慢,较难形成细沟,细沟发育随机性大。细沟发育对产流过程没有明显影响,土壤入渗快慢是两种土壤产流过程存在差异的主要原因。细沟发育程度加剧,会使塿土含沙量的增加速度加快,达到稳定含沙量的时间提前,坡面已有细沟只对稳定含沙量有明显影响,细沟密度增加会使稳定含沙量提高;黄绵土含沙量的变化主要取决于细沟发育过程中的随机性,当细沟侵蚀以崩塌作用为主时,含沙量会出现急剧增加,即使雨强较小,也会产生严重的土壤侵蚀。 相似文献
3.
次降雨条件下坡面侵蚀形态的演变过程和细沟的发生发展过程是土壤侵蚀规律研究中的重点和难点。利用REE示踪法,采取沿坡面垂直分层布设的新的试验方法,通过室内模拟降雨试验,对坡面侵蚀演变过程进行了探索性研究。结果表明:降雨初期坡面侵蚀以面蚀为主,细沟出现后,坡面侵蚀加剧;随着降雨时间的延续,累积面蚀量和细沟侵蚀量逐渐增加,但后者的增加速率大于前者,面蚀占总侵蚀量的比率随降雨时间呈曲线形式逐渐递减,细沟侵蚀则逐渐增加;试验结束时细沟侵蚀量为面蚀量的2～4倍。本研究为定量区分和研究坡面侵蚀过程中面蚀和细沟侵蚀量,面蚀向细沟侵蚀的转变以及细沟侵蚀发生、发育提供了新的思路和解决途径。 相似文献
4.
Application of a distributed erosion model for the assessment of spatial erosion patterns in the Lushi catchment,China 总被引：2，自引：2，他引：0
Guoqiang Wang Jingshan Yu S. Shrestha H. Ishidaira K. Takeuchi 《Environmental Earth Sciences》2010,61(4):787-797
A grid-based erosion model is developed by integrating the distributed hydrological model, BTOPMC, with the modified USLE
to estimate soil erosion and sediment outflow during single storms. The possible sheet, rill, channel erosion types, and sediment
transport processes are considered within each grid under the model structure. Instead of representing the sheet erosion and
rill erosion separately, the classic USLE method is modified to simulate the lumped sheet–rill erosion during storms. In the
modification, the runoff ratio and a relevant correction coefficient are brought into the R-factor which improves the model’s applicability in predicting erosion during single storms. Instead of representing a grid
with a unique erosion type, a channel component is assumed to exist in each grid, and its width varies with the upstream contributing
area of the grid. This assumption avoids the problems that are caused by the difference between the channel widths in the
upstream area and the downstream area if the grid is simply recognized as a channel grid. It also enables the model to be
applicable in simulating soil erosion and sediment outflow from a large catchment. Through a case study in the Lushi catchment,
China, the results show an overall satisfactory accuracy for the selected events. Moreover, by analyzing the spatial distribution
of soil erosion or deposition, the erosion-prone areas are identified for the prioritization purpose. 相似文献
5.
6.
An assessment of soil erosion probability and erosion rate in a tropical mountainous watershed using remote sensing and GIS 总被引：1，自引：1，他引：0
H. Vijith M. Suma V. B. Rekha C. Shiju P. G. Rejith 《Arabian Journal of Geosciences》2012,5(4):797-805
Remote sensing data and Geographical Information System (GIS) has been integrated with the weighted index overlay (WIO) method and E 30 model for the identification and delineation of soil erosion susceptibility zones and the assessment of rate of soil erosion in the mountainous sub-watershed of River Manimala in Kerala (India). Soil erosion is identified as the one of the most serious environmental problems in the human altered mountainous environment. The reliability of estimated soil erosion susceptibility and soil loss is based on how accurately the different factors were estimated or prepared. In the present analysis, factors that are considered to be influence the soil erosion are: land use/land cover, NDVI, landform, drainage density, drainage frequency, lineament frequency, slope, and relative relief. By the WIO analysis, the area is divided into zones representing low (33.30%), moderate (33.70%), and high (33%) erosion proneness. The annual soil erosion rate of the area under investigation was calculated by carefully determining its various parameters and erosion for each of the pixels were estimated individually. The spatial pattern thus created for the area indicates that the average annual rate of soil erosion in the area was ranging from 0.04 mm yr−1 to 61.80 mm yr−1. The high soil erosion probability and maximum erosion rate was observed in areas with high terrain alteration, high relief and slopes with the intensity and duration of heavy precipitation during the monsoons. 相似文献
7.
人工掏挖是黄土高原地区夏闲地翻耕时广为应用的耕作方式,为探明其坡面侵蚀过程,利用三维激光扫描仪及ArcGIS软件,阐明其在人工模拟间歇降雨下坡面微地貌、侵蚀产沙及水力学参数演变规律。结果表明:①坡面侵蚀历经溅蚀-片蚀、断续细沟、连续细沟3个阶段;降雨截止时细沟平面密度、平均沟深、最大沟长和最大沟深分别增至初始的1.42倍、2.24倍、15.5倍和2.43倍。②地表糙度随降雨历时推移从1.706呈近似线性趋势减小至1.488;累积降雨量达80 mm之前,径流量、含沙量随地表糙度的减小增加缓慢,但之后随地表糙度减小增加剧烈。③降雨过程中流速呈现波动增加趋势,水流由层流快速过渡至紊流,但始终保持为缓流,水流阻力呈波动下降,且形态阻力一直居于主导地位。人工掏挖耕作坡面在雨强1.5 mm/min、降雨量80 mm以内可起到蓄水保土作用,但在连续强降雨下也更易引起细沟侵蚀。 相似文献
8.
Haoyuan Hong Aiding Kornejady Adel Soltani Seyed Vahid Razavi Termeh Junzhi Liu A-Xing Zhu Arastoo Yari hesar Baharin Bin Ahmad Yi Wang 《Earth Science Informatics》2018,11(4):605-622
The present study is aimed at producing landslide susceptibility map of a landslide-prone area (Anfu County, China) by using evidential belief function (EBF), frequency ratio (FR) and Mahalanobis distance (MD) models. To this aim, 302 landslides were mapped based on earlier reports and aerial photographs, as well as, carrying out several field surveys. The landslide inventory was randomly split into a training dataset (70%; 212landslides) for training the models and the remaining (30%; 90 landslides) was cast off for validation purpose. A total of sixteen geo-environmental conditioning factors were considered as inputs to the models: slope degree, slope aspect, plan curvature, profile curvature, the new topo-hydrological factor termed height above the nearest drainage (HAND), average annual rainfall, altitude, distance from rivers, distance from roads, distance from faults, lithology, normalized difference vegetation index (NDVI), sediment transport index (STI), stream power index (SPI), soil texture, and land use/cover. The validation of susceptibility maps was evaluated using the area under the receiver operating characteristic curve (AUROC). As a results, the FR outperformed other models with an AUROC of 84.98%, followed by EBF (78.63%) and MD (78.50%) models. The percentage of susceptibility classes for each model revealed that MD model managed to build a compendious map focused at highly susceptible areas (high and very high classes) with an overall area of approximately 17%, followed by FR (22.76%) and EBF (31%). The premier model (FR) attested that the five factors mostly influenced the landslide occurrence in the area: NDVI, soil texture, slope degree, altitude, and HAND. Interestingly, HAND could manifest clearer pattern with regard to landslide occurrence compared to other topo-hydrological factors such as SPI, STI, and distance to rivers. Lastly, it can be conceived that the susceptibility of the area to landsliding is more subjected to a complex environmental set of factors rather than anthropological ones (residential areas and distance to roads). This upshot can make a platform for further pragmatic measures regarding hazard-planning actions. 相似文献
9.
Haoyuan Hong Seyed Amir Naghibi Mostafa Moradi Dashtpagerdi Hamid Reza Pourghasemi Wei Chen 《Arabian Journal of Geosciences》2017,10(7):167
Forest fire is known as an important natural hazard in many countries which causes financial damages and human losses; thus, it is necessary to investigate different aspects of this phenomenon. In this study, performance of four models of linear and quadratic discriminant analysis (LDA and QDA), frequency ratio (FR), and weights-of-evidence (WofE) was investigated to model forest fire susceptibility in the Yihuang area, China. For this purpose, firstly, a forest fire locations map was prepared implementing MODIS satellite images and field surveys. Then, it was classified into two groups including training (70%) and validation (30%) by a random algorithm. In addition, 13 forest fire effective factors were prepared and used such as slope degree, slope aspect, altitude, Topographic Wetness Index (TWI), plan curvature, land use, Normalized Difference Vegetation Index (NDVI), annual rainfall, distance from roads and rivers, wind effect, annual temperature, and soil texture. Using the training dataset and effective factors, LDA, QDA, FR, and WofE models were applied and forest fire susceptibility maps were prepared. Finally, area under the curve (AUC) of receiver operating characteristics (ROC) was implemented for investigating the performance of the models. The results depicted that WofE had the best performance (AUC = 82.2%), followed by FR (AUC = 80.9%), QDA (AUC = 78.3%), and LDA (AUC = 78%), respectively. The results of this study showed the high contribution of altitude, slope degree, and temperature. On the other hand, it was seen that slope aspect and soil had the lowest importance in forest fire susceptibility mapping. From the AUC results, it can be concluded that FR, WofE, LDA, and QDA had acceptable performance and could be used for forest fire susceptibility mapping at the regional scale. 相似文献
10.
Gully erosion is an important environmental issue with severe impacts. This study aimed to characterize gully erosion susceptibility and assess the capability of information value (InfVal) and frequency ratio (FR) models for its spatial prediction in Ourika watershed of the High Atlas region of Morocco. These two bivariate statistical methods have been used for gully erosion susceptibility mapping by comparing each data layer of causative factor to the existing gully distribution. Weights to the gully causative factors are assigned based on gully density. Gullies have been mapped through field surveys and Google earth high-resolution images. Lithofacies, land use, slope gradient, length-slope, aspect, stream power index, topographical wetness index and plan curvature were considered predisposing factors to gullying. The digitized gullies were randomly split into two parts. Sixty-five percent (65%) of the mapped gullies were randomly selected as training set to build gully susceptibility models, while the remaining 35% cases were used as validation set for the models’ validation. The results showed that barren and sparse vegetation lands and slope gradient above 50% were very susceptible to gully erosion. The ROC curve was used for testing the accuracy of the mentioned models. The analysis confirms that the FR model (AUC 80.61%) shows a better accuracy than InfVal model (AUC 52.07%). The performance of the gully erosion susceptibility map constructed by FR model is greater than that of the map produced by InfVal model. The findings proved that GIS-based bivariate statistical methods such as frequency ratio model could be successfully applied in gully susceptibility mapping in Morocco mountainous regions and in other similar environments. The produced susceptibility map represents a useful tool for sustainable planning, conservation and protection of land from gully processes. 相似文献