Assessment of shallow seated landslide size and magnitude characteristics: An example from Northeastern Turkey

2020 ◽  
Author(s):  
Kübra Tezel ◽  
Aykut Akgün ◽  
Ehsan Alizadeh
Keyword(s):  
Image Interpretation ◽  
Google Earth ◽  
Slope Gradient ◽  
Stream Power ◽  
Field Surveys ◽  
Clastic Rocks ◽  
Multiple Image ◽  
Investigation Area ◽  
Prone Area ◽  
Stream Power Index

<p>Landslides occurred in the Northeastern part of Turkey are generally classified to be shallow seated landslides or earthflow type based on Varnes (1984) classification. These landslides are occasionally seen in the weathered  Eocene or Upper Crateceous aged volcanic and volcano-clastic rocks. Although there are considerable studies both directly on these landslides in point of mapping and hazard assessment, there is no any studies concerning size and magnitude characteristics of them. By considering this point, an assessment of size and magnitude characteristics of shallow seated type landslides at an area where is one of most landslide prone area of Turkey was carried out.</p><p>The investigation area is totaly covered by Eocene aged volcano-clastic lithology, and the weathering is widespread due to the climatical conditions in the area. The extend of the area is 140 square kilometers. In the area, 120 landslides were mapped by a multiple image interpretation that is from the years of 2000 to 2019. To do this, Google Earth images were used. In the area, the area (A<sub>L</sub>) of the landslide mapped differs from 53.28 m<sup>2</sup> to 902,809 m<sup>2</sup>. The length and width of these landslide were also determined and these characteristics were taken into account for an assessment of relationship between the size and topographical features such as slope gradient, curvature, topographical wetness index and stream power index. The approximate volumes of these landslides were calculated by considering direct depth observations in the field surveys, and then assessed by different relations proposed by different studies. Magnitude (M) of these landslides were also assessed by taken into account of the area (A<sub>L</sub>) and volume (V<sub>L</sub>) values.</p>

scholarly journals Automated Classification of Agricultural Lands Using GIS and NES

2018 ◽  
Vol 7 (4.38) ◽  
pp. 1146
Author(s):  
V. K. Kalichkin ◽  
A. I. Pavlova ◽  
A. F. Petrov ◽  
V. A. Smolyakov
Keyword(s):  
Land Use ◽  
Information System ◽  
Geographic Information System ◽  
Interpolation Method ◽  
Ground Surface ◽  
Geographic Information ◽  
Automated Classification ◽  
Stream Power ◽  
Stream Power Index

The article proposes the methodology for the automated classification of uplands using Geographic Information System (GIS) and Neural Expert System (NES). Quantitative indicators of topography are used as the basis of the proposed classification. A database consisting of topographic, soil, and land use maps was created using ArcGIS 10 geographic information system. A topologically correct digital elevation model (DEM) was created by the ANUDEM interpolation method. The DEM contains the following maps: hypsometric, steepness and slopes exposure, plan, profile, common curvature of the ground surface, and cumulative runoff maps. The boundaries of elementary surfaces (ES), which are homogeneous morphological formations, are established. Parameters characterizing the Stream Power Index (SPI) are taken into account. The essence of the proposed classification consists in attributing of ES to a certain group of lands based on aggregate of features. To do this, partial scales were created, containing indicators of topography, soil cover, land drainage conditions, as well as the degree of erosion development. The authors formed knowledge base for traning the NES using GIS database and partial scales of estimates. Teaching of neural network was carried out. The classification and topology of land was carried out by means of the NES. The uplands are distributed in flat and slightly convex areas. They are characterized by the following indicators: the curvature of the ground surface: plan curvature (0 – 0.03), profile curvature (0 – 0.15), common curvature (0 – 0.22); slope angles (less than 1.5о); horizontal dissection in elevation (less than 0.5 km/km2), vertical dissection (less than 5 m); and SPI (from -13.80 to -6.47). Electronic map of uplands of LLC «Salair» land-use area was created in the ArcGIS 10 environment.  

scholarly journals Effect of hydraulic parameters on sediment transport capacity in overland flow over erodible beds

2012 ◽  
Vol 16 (2) ◽  
pp. 591-601 ◽  
Author(s):  
M. Ali ◽  
G. Sterk ◽  
M. Seeger ◽  
M. Boersema ◽  
P. Peters
Keyword(s):  
Shear Stress ◽  
Sediment Transport ◽  
Hydraulic Parameters ◽  
Transport Capacity ◽  
Slope Gradient ◽  
Mean Flow ◽  
Stream Power ◽  
Unit Discharge ◽  
Sediment Transport Capacity ◽  
Mean Flow Velocity

Abstract. Sediment transport is an important component of the soil erosion process, which depends on several hydraulic parameters like unit discharge, mean flow velocity, and slope gradient. In most of the previous studies, the impact of these hydraulic parameters on transport capacity was studied for non-erodible bed conditions. Hence, this study aimed to examine the influence of unit discharge, mean flow velocity and slope gradient on sediment transport capacity for erodible beds and also to investigate the relationship between transport capacity and composite force predictors, i.e. shear stress, stream power, unit stream power and effective stream power. In order to accomplish the objectives, experiments were carried out in a 3.0 m long and 0.5 m wide flume using four well sorted sands (0.230, 0.536, 0.719, 1.022 mm). Unit discharges ranging from 0.07 to 2.07 × 10−3 m2 s−1 were simulated inside the flume at four slopes (5.2, 8.7, 13.2 and 17.6%) to analyze their impact on sediment transport rate. The sediment transport rate measured at the bottom end of the flume by taking water and sediment samples was considered equal to sediment transport capacity, because the selected flume length of 3.0 m was found sufficient to reach the transport capacity. The experimental result reveals that the slope gradient has a stronger impact on transport capacity than unit discharge and mean flow velocity due to the fact that the tangential component of gravity force increases with slope gradient. Our results show that unit stream power is an optimal composite force predictor for estimating transport capacity. Stream power and effective stream power can also be successfully related to the transport capacity, however the relations are strongly dependent on grain size. Shear stress showed poor performance, because part of shear stress is dissipated by bed irregularities, bed form evolution and sediment detachment. An empirical transport capacity equation was derived, which illustrates that transport capacity can be predicted from median grain size, total discharge and slope gradient.

scholarly journals Harris Hawks Optimization: A Novel Swarm Intelligence Technique for Spatial Assessment of Landslide Susceptibility

Sensors ◽  
2019 ◽  
Vol 19 (16) ◽  
pp. 3590 ◽  
Author(s):  
Bui ◽  
Moayedi ◽  
Kalantar ◽  
Osouli ◽  
Gör ◽  
...  
Keyword(s):  
Landslide Susceptibility ◽  
Characteristic Curve ◽  
Absolute Error ◽  
Slope Aspect ◽  
Stream Power ◽  
Topographic Wetness Index ◽  
Conditioning Factors ◽  
Performance Error ◽  
Stream Power Index ◽  
Artificial Neural Network Ann

In this research, the novel metaheuristic algorithm Harris hawks optimization (HHO) is applied to landslide susceptibility analysis in Western Iran. To this end, the HHO is synthesized with an artificial neural network (ANN) to optimize its performance. A spatial database comprising 208 historical landslides, as well as 14 landslide conditioning factors—elevation, slope aspect, plan curvature, profile curvature, soil type, lithology, distance to the river, distance to the road, distance to the fault, land cover, slope degree, stream power index (SPI), topographic wetness index (TWI), and rainfall—is prepared to develop the ANN and HHO–ANN predictive tools. Mean square error and mean absolute error criteria are defined to measure the performance error of the models, and area under the receiving operating characteristic curve (AUROC) is used to evaluate the accuracy of the generated susceptibility maps. The findings showed that the HHO algorithm effectively improved the performance of ANN in both recognizing (AUROCANN = 0.731 and AUROCHHO–ANN = 0.777) and predicting (AUROCANN = 0.720 and AUROCHHO–ANN = 0.773) the landslide pattern.

scholarly journals Hydraulic characteristics and sediment generation on slope erosion in the Three Gorges Reservoir Area, China

2016 ◽  
Vol 64 (3) ◽  
pp. 237-245 ◽  
Author(s):  
Feng Qian ◽  
Dongbin Cheng ◽  
Wenfeng Ding ◽  
Jiesheng Huang ◽  
Jingjun Liu
Keyword(s):  
Soil Erosion ◽  
Sediment Yield ◽  
Rainfall Intensity ◽  
Purple Soil ◽  
Three Gorges ◽  
Slope Gradient ◽  
Stream Power ◽  
Yield Rate ◽  
The Three Gorges ◽  
Subsurface Runoff

Abstract Hydrological processes play important roles in soil erosion processes of the hillslopes. This study was conducted to investigate the hydrological processes and the associated erosional responses on the purple soil slope. Based on a comprehensive survey of the Wangjiaqiao watershed in the Three Gorges Reservoir, four typical slope gradients (5°, 10°, 15°and 20°) were applied to five rainfall intensities (0.6, 1.1, 1.61, 2.12 and 2.54 mm·min-1). The results showed that both surface and subsurface runoff varied greatly depending on the rainfall intensity and slope gradient. Surface runoff volume was 48.1 to 280.1 times of that for subsurface runoff. The critical slope gradient was about 10°. The sediment yield rate increased with increases in both rainfall intensity and slope gradient, while the effect of rainfall intensity on the sediment yield rate was greater than slope gradient. There was a good linear relationship between sediment yield rate and Reynolds numbers, flow velocity and stream power, while Froude numbers, Darcy-Weisbach and Manning friction coefficients were not good hydraulic indicators of the sediment yield rate of purple soil erosion. Among the three good indicators (Re, v and w), stream power was the best predictor of sediment yield rate (R2 = 0.884). Finally, based on the power regression relationship between sediment yield rate, runoff rate, slope gradient and rainfall intensity, an erosion model was proposed to predict the purple soil erosion (R2 = 0.897). The results can help us to understand the relationship between flow hydraulics and sediment generation of slope erosion and offer useful data for the building of erosion model in purple soil.

scholarly journals SISTEMATIZAÇÃO DE UMA EXPERIÊNCIA AGROECOLÓGICA NO CERRADO BRASILEIRO: SUBSÍDIOS PARA O PLANEJAMENTO DE UNIDADES PRODUTIVAS DE BASES ECOLÓGICAS

Nativa ◽  
2021 ◽  
Vol 9 (5) ◽  
pp. 573-581
Author(s):  
Isabel Corrêa Fontes Chagas de Oliveira ◽  
Renato Linhares De Assis ◽  
Adriana Maria de Aquino
Keyword(s):  
Satellite Images ◽  
Social Economic ◽  
Google Earth ◽  
Aerial Photographs ◽  
Construction Process ◽  
Brazilian Cerrado ◽  
Way Of Life ◽  
Complex Dynamic ◽  
Field Surveys ◽  
Midwest Region

Este estudo consiste na sistematização de uma experiência agroecológica a partir do ordenamento e síntese dos processos do seu uso e ocupação. A experiência iniciou em 1984, em unidade agroecológica pioneira, com características neorurais, na região Centro-oeste do Brasil. A pesquisa contou com entrevistas não estruturadas, levantamento de campo, pesquisa bibliográfica e documental (fotografias, revistas, jornais, imagens de satélite e fotografias aéreas). Utilizou-se a ferramenta Google Earth para avaliar o mosaico de agroecossistemas resultante da ação agroecológica no espaço e tempo. Os resultados apontaram uma dinâmica complexa do processo de construção de agroecossistemas e redes sociais, configurando-se num desenho agroecológico que ultrapassa as fronteiras físicas da propriedade. O processo de síntese e análise relatado, além de empoderar os protagonistas, traz a luz do conhecimento científico aprendizados de uma experiência empírica de um modo de vida integrado à natureza, com riqueza em variedade, diversidade e possibilidades nos processos biológicos, sociais, econômicos, éticos, morais e culturais, que pode inspirar e subsidiar outras iniciativas de base agroecológica. Palavras-chave: neoruralidade; gerenciamento agroecológico; redesenho da paisagem; agroecossistemas.   Systematization of an agroecological experience in the Brazilian Cerrado: subsidies for the planning of productive units of ecological bases   ABSTRACT: This study consists of the systematization of an agroecological experience from the ordering and synthesis of the processes of its use and occupation. The experience began in 1984, in a pioneering agroecological unit, with neorural characteristics, in the Midwest region of Brazil. The research included unstructured interviews, field surveys, bibliographic and documentary research (photographs, magazines, newspapers, satellite images, and aerial photographs). The Google Earth tool was used to evaluate the mosaic of agroecosystems resulting from agroecological action in space and time. The results pointed toward a complex dynamic of the construction process of agroecosystems and social networks, configuring itself in an agroecological design that goes beyond the physical boundaries of the property. The reported process of synthesis and analysis, in addition to empowering the protagonists, brings to light scientific knowledge learning from an empirical experience of a way of life integrated with nature, with a wealth of variety, diversity, and possibilities in biological, social, economic, ethical, moral and cultural processes, which can inspire and subsidize other agroecological initiatives. Keywords: neorurality; agroecological management; landscape redesign; agroecosystems.

scholarly journals Landform classification using GIS techniques. The case of Kimi municipality area, Euboea Island, Greece.

2016 ◽  
Vol 47 (1) ◽  
pp. 264 ◽  
Author(s):  
I. Ilia ◽  
D. Rozos ◽  
I. Koumantakis
Keyword(s):  
Spatial Analysis ◽  
Power Index ◽  
Stream Power ◽  
Topographic Wetness Index ◽  
Wetness Index ◽  
Topographic Position Index ◽  
Landform Classification ◽  
Essential Parameter ◽  
Position Index ◽  
Stream Power Index

The main objective of this paper is to classify landforms in Kimi municipality area of Euboea Island, Greece using advanced spatial techniques. Landform categories were determined by conducting morphometric analysis through the use of advanced GIS functions. In particular, the process of classifying the landscape into landform categories was based on Topographic Position Index (TPI). The main topographic elements such as slope inclination, aspect, slope shape (curvature), topographic wetness index and stream power index were obtained from the DEM file of the study area. Landform classification was obtained using TPI grids and the classes were related with the geological pattern and the land cover by sophisticated spatial analysis function. The knowledge obtained from the present study could be useful in identifying areas prone to land degradation and instability problems in which landforms are identified as an essential parameter

scholarly journals Landslide Susceptibility Assessment Using Modified Frequency Ratio Model in Kaski District, Nepal

2021 ◽  
Vol 11 (1) ◽  
pp. 167-177
Author(s):  
Niraj Baral ◽  
Akhilesh Kumar Karna ◽  
Suraj Gautam
Keyword(s):  
Landslide Susceptibility ◽  
Frequency Ratio ◽  
Satellite Image ◽  
Image Interpretation ◽  
Google Earth ◽  
Slope Aspect ◽  
Susceptibility Map ◽  
Conditioning Factors ◽  
Prediction Rate ◽  
Using Data

Landslides are the most common natural hazards in Nepal especially in the mountainous terrain. The existing topographical scenario, complex geological settings followed by the heavy rainfall in monsoon has contributed to a large number of landslide events in the Kaski district. In this study, landslide susceptibility was modeled with the consideration of twelve conditioning factors to landslides like slope, aspect, elevation, Curvature, geology, land-use, soil type, precipitation, road proximity, drainage proximity, and thrust proximity. A Google-earth-based landslide inventory map of 637 landslide locations was prepared using data from Disinventar, reports, and satellite image interpretation and was randomly subdivided into a training set (70%) with 446 Points and a test set with 191 points (30%). The relationship among the landslides and the conditioning factors were statistically evaluated through the use of Modified Frequency ratio analysis. The results from the analysis gave the highest Prediction rate (PR) of 6.77 for elevation followed by PR of 66.45 for geology and PR of 6.38 for the landcover. The analysis was then validated by calculating the Area Under a Curve (AUC) and the prediction rate was found to be 68.87%. The developed landslide susceptibility map is helpful for the locals and authorities in planning and applying different intervention measures in the Kaski District.

scholarly journals A field investigation on rill development and flow hydrodynamics under different upslope inflow and slope gradient conditions

2020 ◽  
Vol 51 (5) ◽  
pp. 1201-1220
Author(s):  
Pei Tian ◽  
Chengzhong Pan ◽  
Xinyi Xu ◽  
Tieniu Wu ◽  
Tiantian Yang ◽  
...  
Keyword(s):  
Soil Loss ◽  
Field Investigation ◽  
Rill Erosion ◽  
Slope Gradient ◽  
Power Functions ◽  
Stream Power ◽  
Erosion Processes ◽  
Initial Stage ◽  
Quantitative Impact ◽  
Inflow Discharge

Abstract Few studies focus on the quantitative impact of upslope inflow rate and slope gradient on rill development and erosion processes. Field plot experiments under varying inflow rates (6–36 L min−1m−1) and slope gradients (26, 42 and 57%) were conducted to address this issue. The results showed soil loss rates significantly demonstrated temporal variability in relevance to the rill developing process. Rill erosion and its contribution to soil loss increased with increasing inflow rates and slope gradients by power functions. There was a threshold inflow discharge (12–24 L min−1m−1), under which, rill erosion became the dominant erosion pattern. At the initial stage, downcutting of rill bottom and headward erosion were obvious, whereas rill broadening was significant at the actively rill developing period. Rill density increased with slope gradient increasing from 26% to 42%, and then decreased. For the 57% slope under high inflow rates (24–36 L min−1m−1), gravity caused an increase in the collapse of rills. Mean rill width increased with increasing inflow rates but decreased as slope gradients increased, while mean rill depth increased with increasing inflow rates and slope gradients. Stream power and rill flow velocity were the best hydrodynamic parameter to simulate rill erosion and rill morphology, respectively.

Effects of Glacial Isostatic Adjustment on Surface Topography, Flow Accumulation,  Stream Power & Sediment Transport Indexes in the Canadian Prairies

2021 ◽  
Author(s):  
Patrick Wu ◽  
Tanghua Li ◽  
Holger Steffen
Keyword(s):  
Sediment Transport ◽  
North America ◽  
Surface Topography ◽  
Water Flow ◽  
Stream Power ◽  
Land Uplift ◽  
Flow Accumulation ◽  
Isostatic Adjustment ◽  
Stream Power Index ◽  
Differential Uplift

<p>Glacial Isostatic Adjustment (GIA) induced by the melting of the Pleistocene Ice Sheets causes differential land uplift, relative sea level and geoid changes. Thus, GIA in North America may affect water flow-accumulation and the rate of sedimentation and erosion in the South Saskatchewan River Basin (SSRB), but so far this has not been well investigated.</p><p> </p><p>Our aim here is to use surface topography in the SSRB and simple models of surface water flow to compute flow-accumulation, wetness index, stream power index and sediment transport index - the latter two affect the rates of erosion and sedimentation. Since the river basin became virtually ice-free around 8 ka BP, we shall study the effects of GIA induced differential land uplift during the last 8 ka on these indexes.</p><p> </p><p>Using the present-day surface topography ETOPO1 model, we see that the stream power index and sediment transport index in the SSRB may not be high enough to alter the surface topography significantly today and probably during the last 8 ka except for places around the Rocky Mountains. The effect of using 1 and 3 arc minute grid resolution of the ETOPO1 model does not significantly alter the value of these indexes. However, we note that using 1 arc minute grid is much more computationally intensive, so only a smaller area of the SSRB can be included in the computation.</p><p> </p><p>Next, we assume that sedimentation and erosion did not occur in the SSRB during the last 8 ka BP, and the change in surface topography is only due to GIA induced differential uplift. We use land uplift predicted by a large number of GIA models to study the changes in stream power & sediment transport indexes in the last 8 ka BP. Our base GIA model is ICE6G_C(VM5a). Then we investigate the effects of using uplift predicted by other GIA models that can still fit the observed relative sea level (RSL), uplift rate and gravity-rate-of-change data in North America reasonably well. These alternate GIA models have lateral heterogeneity in the mantle and lithosphere included – in particular we test those that give the largest differential uplift in the SSRB. We found that the effect of these other GIA earth models is not large on the stream power & sediment transport indexes. Finally, we investigate the sensitivity of these indexes on the ice models that are consistent with GIA observations. The results of this study will be useful to our understanding of water flow accumulation, sedimentation and erosion in the past, present and future and for water resource management in North America.</p>

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