| 11. |
- Huss, M., et al.
(författare)
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Toward mountains without permanent snow and ice
- 2017
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Ingår i: Earth's Future. - 2328-4277. ; 5:5, s. 418-435
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Forskningsöversikt (refereegranskat)abstract
- The cryosphere in mountain regions is rapidly declining, a trend that is expected to accelerate over the next several decades due to anthropogenic climate change. A cascade of effects will result, extending from mountains to lowlands with associated impacts on human livelihood, economy, and ecosystems. With rising air temperatures and increased radiative forcing, glaciers will become smaller and, in some cases, disappear, the area of frozen ground will diminish, the ratio of snow to rainfall will decrease, and the timing and magnitude of both maximum and minimum streamflow will change. These changes will affect erosion rates, sediment, and nutrient flux, and the biogeochemistry of rivers and proglacial lakes, all of which influence water quality, aquatic habitat, and biotic communities. Changes in the length of the growing season will allow low-elevation plants and animals to expand their ranges upward. Slope failures due to thawing alpine permafrost, and outburst floods from glacier-and moraine-dammed lakes will threaten downstream populations.Societies even well beyond the mountains depend on meltwater from glaciers and snow for drinking water supplies, irrigation, mining, hydropower, agriculture, and recreation. Here, we review and, where possible, quantify the impacts of anticipated climate change on the alpine cryosphere, hydrosphere, and biosphere, and consider the implications for adaptation to a future of mountains without permanent snow and ice.
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| 12. |
- Clague, JJ, et al.
(författare)
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Late Holocene environmental change at treeline in the Northern Coast Mountains, British Columbia, Canada
- 2004
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Ingår i: Quaternary Science Reviews. - : Elsevier BV. - 0277-3791. ; 23:23-24, s. 2413-2431
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Tidskriftsartikel (refereegranskat)abstract
- An integrated stratigraphic, paleoecological, and geochronological study of lake and fen sediments just beyond the terminus of Berendon Glacier provides insights into late Holocene climate, vegetation, and glacier change in the northern Coast Mountains of British Columbia. Cores collected from two small lakes in the foreland of Berendon Glacier and pits dug in a nearby fen record Little lee Age and older glacier advances. The first Little Ice Age advance in this area began more than 500 years ago and peaked in the early 17th century. An earlier Neoglacial advance began about 2800-3000 cal yr ago and may have lasted for hundreds of years. There is also evidence for an intervening advance of even smaller magnitude around 1200-1300 cal yr ago. The advances are broadly synchronous with those in other parts of western North America, indicating that they were caused by regional, possibly global, changes in climate. Plant communities within the study area did not change dramatically during the late Holocene. The ranges of some plants, however, likely retracted or extended near treeline in response to changes in mean temperatures of perhaps 1-2degreesC, as A well as changes in summer snow cover. The greatest changes in vegetation occurred within and just beyond the forefields of Berendon, Frank Mackie, and other nearby glaciers. The largest climate shifts of the last 3000 years took place during the late Little Ice Age and the last century. Climate warmed about 1-2degreesC during the 20th century, accompanied by a rise in treeline, an increase in coniferous tree cover in the subalpine zone, and an increase in the temperature and biological productivity of ponds. These trends are likely to continue if climate, as expected, continues to warm. (C) 2004 Elsevier Ltd. All rights reserved.
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| 13. |
- Margold, Martin, et al.
(författare)
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Retreat pattern of the Cordilleran Ice Sheet in central British Columbia at the end of the last glaciation reconstructed from glacial meltwater landforms
- 2013
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Ingår i: Boreas. - : Wiley. - 0300-9483 .- 1502-3885. ; 42:4, s. 830-847
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Tidskriftsartikel (refereegranskat)abstract
- The Cordilleran Ice Sheet (CIS) covered much of the mountainous northwestern part of North America at least several times during the Pleistocene. The pattern and timing of its growth and decay are, however, poorly understood. Here, we present a reconstruction of the pattern of ice-sheet retreat in central British Columbia at the end of the last glaciation based on a palaeoglaciological interpretation of ice-marginal meltwater channels, eskers and deltas mapped from satellite imagery and digital elevation models. A consistent spatial pattern of high-elevation (1600-2400m a.s.l.), ice-marginal meltwater channels is evident across central British Columbia. These landforms indicate the presence of ice domes over the Skeena Mountains and the central Coast Mountains early during deglaciation. Ice sourced in the Coast Mountains remained dominant over the southern and east-central parts of the Interior Plateau during deglaciation. Our reconstruction shows a successive westward retreat of the ice margin from the western foot of the Rocky Mountains, accompanied by the formation and rapid evolution of a glacial lake in the upper Fraser River basin. The final stage of deglaciation is characterized by the frontal retreat of ice lobes through the valleys of the Skeena and Omineca Mountains and by the formation of large esker systems in the most prominent topographic lows of the Interior Plateau. We conclude that the CIS underwent a large-scale reconfiguration early during deglaciation and was subsequently diminished by thinning and complex frontal retreat towards the Coast Mountains.
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| 14. |
- Margold, Martin, et al.
(författare)
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Timing of terminal Pleistocene deglaciation at high elevations in southern and central British Columbia constrained by Be-10 exposure dating
- 2014
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Ingår i: Quaternary Science Reviews. - : Elsevier BV. - 0277-3791 .- 1873-457X. ; 99, s. 193-202
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Tidskriftsartikel (refereegranskat)abstract
- The Cordilleran Ice Sheet (CIS) covered most of British Columbia and southern Yukon Territory at the local Last Glacial Maximum (ILGM) during Marine Oxygen Isotope Stage 2. However, its subsequent demise is not well understood, particularly at high elevations east of its ocean-terminating margin. We present Be-10 exposure ages from two high-elevation sites in southern and central British Columbia that help constrain the time of initial deglaciation at these sites. We sampled granodiorite erratics at elevations of 2126-2230 m a.s.l. in the Marble Range and 1608-1785 m a.s.l. in the Telkwa Range at the western margin of the Interior Plateau. The erratics at both sites are near ice-marginal meltwater channels that delineate the local ice surface slope and thus the configuration of the ice sheet during deglaciation. The locations of the erratics and their relations to meltwater channels ensure that the resulting Be-10 ages date CIS deglaciation and not the retreat of local montane glaciers. Our sample sites emerged above the surface of the CIS as its divide migrated westward from the Interior Plateau to the axis of the Coast Mountains. Two of the four samples from the summit area of the Marble Range yielded apparent exposure ages of 14.0 +/- 0.7 and 15.2 +/- 0.8 ka. These ages are 1.8-3.0 ka younger than the well-established ILGM age of ca 17 ka for the Puget lobe of the CIS in Washington State; they are 1.7 ka younger than the ILGM age for the Puget lobe if a snow-shielding correction to their uncertainty-weighted mean age is applied. The other two samples yielded much older apparent exposure ages (20.6 +/- 1.4 and 33.0 +/- 1.5 ka), indicating the presence of inherited isotopes. Four samples collected from the summit area of the Telkwa Range in the Hazelton Mountains yielded well clustered apparent exposure ages of 10.1 +/- 0.6, 10.2 +/- 0.7, 10.4 +/- 0.5, and 11.5 +/- 1.1 ka. Significant present-day snow cover introduces a large uncertainty in the apparent exposure ages from this site. A snow-shielding correction based on present-day snow cover data increases the uncertainty-weighted mean exposure age of the Telkwa Range erratics to 12.4 +/- 0.7 ka, consistent with deglacial C-14 ages from areas near sea level to the west. Our exposure ages show a thinning of the southern portion of the CIS shortly after the ILGM and persistence of a remnant mountain ice cap in the central Coast Mountains into the Younger Dryas Chronozone. Our data also show that the summit area of the Marble Range was ice-covered during the ILGM. The presence of an ice body of considerable dimension in north-central British Columbia until, or possibly even after, the Younger Dryas highlights the need for geomorphological and geochronological studies of the ice dispersal centre over the Skeena Mountains in northwest British Columbia and the need for better understanding of the response of the CIS to Lateglacial climate fluctuations.
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| 15. |
- Nhu, Viet-Ha, et al.
(författare)
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Landslide Susceptibility Mapping Using Machine Learning Algorithms and Remote Sensing Data in a Tropical Environment
- 2020
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Ingår i: International Journal of Environmental Research and Public Health. - Switzerland : MDPI. - 1661-7827 .- 1660-4601. ; 17:14
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Tidskriftsartikel (refereegranskat)abstract
- We used AdaBoost (AB), alternating decision tree (ADTree), and their combination as an ensemble model (AB-ADTree) to spatially predict landslides in the Cameron Highlands, Malaysia. The models were trained with a database of 152 landslides compiled using Synthetic Aperture Radar Interferometry, Google Earth images, and field surveys, and 17 conditioning factors (slope, aspect, elevation, distance to road, distance to river, proximity to fault, road density, river density, normalized difference vegetation index, rainfall, land cover, lithology, soil types, curvature, profile curvature, stream power index, and topographic wetness index). We carried out the validation process using the area under the receiver operating characteristic curve (AUC) and several parametric and non-parametric performance metrics, including positive predictive value, negative predictive value, sensitivity, specificity, accuracy, root mean square error, and the Friedman and Wilcoxon sign rank tests. The AB model (AUC = 0.96) performed better than the ensemble AB-ADTree model (AUC = 0.94) and successfully outperformed the ADTree model (AUC = 0.59) in predicting landslide susceptibility. Our findings provide insights into the development of more efficient and accurate landslide predictive models that can be used by decision makers and land-use managers to mitigate landslide hazards.
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| 16. |
- Nhu, Viet-Ha, et al.
(författare)
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Shallow Landslide Susceptibility Mapping : A Comparison between Logistic Model Tree, Logistic Regression, Naïve Bayes Tree, Artificial Neural Network, and Support Vector Machine Algorithms
- 2020
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Ingår i: International Journal of Environmental Research and Public Health. - Switzerland : MDPI. - 1661-7827 .- 1660-4601. ; 17:8, s. 1-30
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Tidskriftsartikel (refereegranskat)abstract
- Shallow landslides damage buildings and other infrastructure, disrupt agriculture practices, and can cause social upheaval and loss of life. As a result, many scientists study the phenomenon, and some of them have focused on producing landslide susceptibility maps that can be used by land-use managers to reduce injury and damage. This paper contributes to this effort by comparing the power and effectiveness of five machine learning, benchmark algorithms—Logistic Model Tree, Logistic Regression, Naïve Bayes Tree, Artificial Neural Network, and Support Vector Machine—in creating a reliable shallow landslide susceptibility map for Bijar City in Kurdistan province, Iran. Twenty conditioning factors were applied to 111 shallow landslides and tested using the One-R attribute evaluation (ORAE) technique for modeling and validation processes. The performance of the models was assessed by statistical-based indexes including sensitivity, specificity, accuracy, mean absolute error (MAE), root mean square error (RMSE), and area under the receiver operatic characteristic curve (AUC). Results indicate that all the five machine learning models performed well for shallow landslide susceptibility assessment, but the Logistic Model Tree model (AUC = 0.932) had the highest goodness-of-fit and prediction accuracy, followed by the Logistic Regression (AUC = 0.932), Naïve Bayes Tree (AUC = 0.864), ANN (AUC = 0.860), and Support Vector Machine (AUC = 0.834) models. Therefore, we recommend the use of the Logistic Model Tree model in shallow landslide mapping programs in semi-arid regions to help decision makers, planners, land-use managers, and government agencies mitigate the hazard and risk.
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| 17. |
- Salvati, Aryan, et al.
(författare)
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Flood susceptibility mapping using support vector regression and hyper-parameter optimization
- 2023
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Ingår i: Journal of Flood Risk Management. - : John Wiley and Sons Inc. - 1753-318X. ; 16:4
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Tidskriftsartikel (refereegranskat)abstract
- Floods are both complex and destructive, and in most parts of the world cause injury, death, loss of agricultural land, and social disruption. Flood susceptibility (FS) maps are used by land-use managers and land owners to identify areas that are at risk from flooding and to plan accordingly. This study uses machine learning ensembles to produce objective and reliable FS maps for the Haraz watershed in northern Iran. Specifically, we test the ability of the support vector regression (SVR), together with linear kernel (LK), base classifier (BC), and hyper-parameter optimization (HPO), to identify flood-prone areas in this watershed. We prepared a map of 201 past floods to predict future floods. Of the 201 flood events, 151 (75%) were used for modeling and 50 (25%) were used for validation. Based on the relevant literature and our field survey of the study area, 10 effective factors were selected and prepared for flood zoning. The results show that three of the 10 factors are most important for predicting flood-sensitive areas, specifically and in order of importance, slope, distance to the river and river. Additionally, the SVR-HPO model, with area under the curve values of 0.986 and 0.951 for the training and testing phases, outperformed the other two tested models.
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| 18. |
- Shahabi, Himan, et al.
(författare)
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Flood Detection and Susceptibility Mapping Using Sentinel-1 Remote Sensing Data and a Machine Learning Approach : Hybrid Intelligence of Bagging Ensemble Based on K-Nearest Neighbor Classifier
- 2020
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Ingår i: Remote Sensing. - Switzerland : MDPI. - 2072-4292. ; 12:2, s. 1-30
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Tidskriftsartikel (refereegranskat)abstract
- Mapping flood-prone areas is a key activity in flood disaster management. In this paper, we propose a new flood susceptibility mapping technique. We employ new ensemble models based on bagging as a meta-classifier and K-Nearest Neighbor (KNN) coarse, cosine, cubic, and weighted base classifiers to spatially forecast flooding in the Haraz watershed in northern Iran. We identified flood-prone areas using data from Sentinel-1 sensor. We then selected 10 conditioning factors to spatially predict floods and assess their predictive power using the Relief Attribute Evaluation (RFAE) method. Model validation was performed using two statistical error indices and the area under the curve (AUC). Our results show that the Bagging–Cubic–KNN ensemble model outperformed other ensemble models. It decreased the overfitting and variance problems in the training dataset and enhanced the prediction accuracy of the Cubic–KNN model (AUC=0.660). We therefore recommend that the Bagging–Cubic–KNN model be more widely applied for the sustainable management of flood-prone areas.
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| 19. |
- Sharifipour, Behzad, et al.
(författare)
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Rangeland species potential mapping using machine learning algorithms
- 2023
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Ingår i: Ecological Engineering. - : Elsevier. - 0925-8574 .- 1872-6992. ; 189
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Tidskriftsartikel (refereegranskat)abstract
- Documenting habitats of rangeland plant species is required to properly manage rangelands and to understand ecosystem processes. A reliable rangeland species potential map can help managers and policy makers design a sustainable grazing system on rangelands. The aim of this study is to map the plant species in the Qurveh City rangelands, Kurdistan Province, Iran, using state-of-the-art machine learning algorithms, including Support Vector Machine (SVM), Artificial Neural Network (ANN), Naïve Bayes (NB), Bayes Net (BN) and Classification and Regression Tree (CART). A total of 185 rangeland species were used in the study, together with 20 conditioning factors, to build and validate models. The One-R feature section technique and multicollinearity test were used, respectively, to determine the most important factors and correlations between them. Model validation was performed using sensitivity, specificity, accuracy, F1-measure, Matthews correlation coefficient (MCC), Kappa, root mean square error (RMSE), and area under the receiver operating characteristic curve (AUC). Results showed that topographic wetness index (TWI), slope angle, elevation, soil phosphorus and soil potassium were the five most important factors to increase the rangeland plants habitat suitability. The Naïve Bayes algorithm (AUC = 0.782) had the highest performance and prediction accuracy and best consistency across the species in the investigated rangeland, followed by the SVM (AUC = 0.763), ANN (AUC = 0.762), CART (AUC = 0.627), and BN (AUC = 0.617) models.
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| 20. |
- Stroeven, Arjen, 1963-, et al.
(författare)
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Investigating the glacial history of the northern sector of the Cordilleran Ice Sheet with cosmogenic 10Be concentrations in quartz
- 2010
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Ingår i: Quaternary Science Reviews. - : Elsevier BV. - 0277-3791 .- 1873-457X. ; 29:25-26, s. 3630-3643
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Tidskriftsartikel (refereegranskat)abstract
- Exposure durations of glacial landforms in widely separated areas of central Yukon Territory affected bythe northern sector of the Cordilleran Ice Sheet (CIS) and alpine glaciers have been determined usingcosmogenic 10Be in quartz. The aim of our research is to test previous reconstructions of glacial historyand to begin to address the paucity of chronological control for the lateral and vertical extent of thenorthern CIS. Chronological evidence for CIS expansion predating the Last Glacial Maximum comes fromminimum surface exposure durations of c 100 ka for two bedrock samples within the Reid glacial limit,indicating a possible marine Oxygen Isotope Stage (OIS) 6 age for this event, and from minimumexposure durations of about 40 ka for boulders on moraines constructed by alpine glaciers on a nunatakwithin the McConnell glacial limit (OIS 2), indicating a possible OIS 4 age. High elevation minimumsurface exposure durations within the McConnell limit indicate that some areas formerly mapped asnunataks were covered by cold-based ice prior to 30 ka. Montane glaciation in the Mackenzie Mountains,outside the McConnell glacial limit, was contemporaneous with nearby CIS advance at 17 ka, with CISretreat by 15 ka. Deglaciation of the Tintina Trench, a major ice discharge route, was completed by 12 ka.At this time ice in an adjacent discharge route to the south was still entering higher-elevation valleys inthe Pelly Mountains. A Lateglacial readvance may have peaked at ca 10 ka in the Ogilvie Mountains.Considerable variation in ages from individual landforms, and possible complex histories, requireadditional cosmogenic nuclide measurements to confirm interpretations.
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