Landslide Susceptibility and Soil Loss Estimates for Drift Creek Watershed, Lincoln County, Oregon

2020 ◽  
Vol 26 (2) ◽  
pp. 167-184
Author(s):  
David M. Korte ◽  
Abdul Shakoor
Keyword(s):  
Water Quality ◽  
Landslide Susceptibility ◽  
Soil Loss ◽  
Sedimentary Rock ◽  
Engineering Properties ◽  
Susceptibility Map ◽  
Rock Formations ◽  
Creek Watershed ◽  
Lincoln County ◽  
The Impact

ABSTRACT Drift Creek watershed, Lincoln County, Oregon, is a source of drinking water as well as a reproductive habitat for endangered salmon and trout species. Landslides, exacerbated by logging, are suspected as a cause of water quality deterioration in the watershed. To investigate the impact of landslides on water quality, we mapped landslide distribution and susceptibility, determined engineering properties of landslide-prone soil and rock, and estimated soil loss resulting from landslide-derived sediment within 30 m of Strahler third-order-or-higher streams in the watershed. We mapped 570 landslides using LiDAR imaging, orthophotographs, and field observations. We used logistic regression to determine the most significant variables contributing to landslide occurrence and to create a watershed-scale landslide susceptibility map. Siletz River Volcanics and the sedimentary Tyee Formation make up 85 percent of the watershed, with the sedimentary Yamhill and Nestucca formations making up the majority of the rest. Sedimentary rocks dominate in the Upper Drift Creek watershed, and volcanic dominate in the lower portion. The largest landslide deposits and the highest susceptibility occur in the sedimentary rock formations. The Siletz River Volcanics has a larger abundance of landslides than the sedimentary rock formations, but they are smaller in size with lower susceptibility of occurrence. The soil loss model indicates that the average annual soil loss from landslide deposits in the Upper Drift Creek watershed is 65 tons/acre/yr compared to 29 tons/acre/yr in the Lower Drift Creek watershed. The model also indicates that soil loss from areas along roads in the watershed is high.

scholarly journals Assessing the Impact of Site-Specific BMPs Using a Spatially Explicit, Field-Scale SWAT Model with Edge-of-Field and Tile Hydrology and Water-Quality Data in the Eagle Creek Watershed, Ohio

Water ◽  
2018 ◽  
Vol 10 (10) ◽  
pp. 1299 ◽  
Author(s):  
Katherine Merriman ◽  
Prasad Daggupati ◽  
Raghavan Srinivasan ◽  
Chad Toussant ◽  
Amy Russell ◽  
...  
Keyword(s):  
Water Quality ◽  
Cover Crops ◽  
Best Management Practices ◽  
Swat Model ◽  
Monitoring Data ◽  
Quality Data ◽  
Field Scale ◽  
Water Quality Data ◽  
Creek Watershed ◽  
The Impact

The Eagle Creek watershed, a small subbasin (125 km2) within the Maumee River Basin, Ohio, was selected as a part of the Great Lakes Restoration Initiative (GLRI) “Priority Watersheds” program to evaluate the effectiveness of agricultural Best Management Practices (BMPs) funded through GLRI at the field and watershed scales. The location and quantity of BMPs were obtained from the U.S. Department of Agriculture-Natural Resources Conservation Service National Conservation Planning (NCP) database. A Soil and Water Assessment Tool (SWAT) model was built and calibrated for this predominantly agricultural Eagle Creek watershed, incorporating NCP BMPs and monitoring data at the watershed outlet, an edge-of-field (EOF), and tile monitoring sites. Input air temperature modifications were required to induce simulated tile flow to match monitoring data. Calibration heavily incorporated tile monitoring data to correctly proportion surface and subsurface flow, but calibration statistics were unsatisfactory at the EOF and tile monitoring sites. At the watershed outlet, satisfactory to very good calibration statistics were achieved over a 2-year calibration period, and satisfactory statistics were found in the 2-year validation period. SWAT fixes parameters controlling nutrients primarily at the watershed level; a refinement of these parameters at a smaller-scale could improve field-level calibration. Field-scale modeling results indicate that filter strips (FS) are the most effective single BMPs at reducing dissolved reactive phosphorus, and FS typically decreased sediment and nutrient yields when added to any other BMP or BMP combination. Cover crops were the most effective single, in-field practice by reducing nutrient loads over winter months. Watershed-scale results indicate BMPs can reduce sediment and nutrients, but reductions due to NCP BMPs in the Eagle Creek watershed for all water-quality constituents were less than 10%. Hypothetical scenarios simulated with increased BMP acreages indicate larger investments of the appropriate BMP or BMP combination can decrease watershed level loads.

scholarly journals Evaluating the impact of road construction on landslide susceptibility- A case study of Mandi district, Himachal Pradesh, India.

2021 ◽  
Author(s):  
Amol Sharma ◽  
Chander Prakash
Keyword(s):  
Statistical Models ◽  
Landslide Susceptibility ◽  
Road Construction ◽  
Himachal Pradesh ◽  
Susceptibility Mapping ◽  
Landslide Susceptibility Mapping ◽  
Susceptibility Map ◽  
Landslide Susceptibility Map ◽  
The Impact ◽  
Very High

Landslide susceptibility mapping has proved to be crucial tool for effective disaster management and planning strategies in mountainous regions. The present study is perused to investigate the changes in the landslide susceptibility of the Mandi district of Himachal Pradesh due to road construction. For this purpose, an inventory of 1723 landslides was generated from various sources. Out of these, 1199 (70%) landslides were taken in the training dataset to be used for modelling and prediction purposes, while 524 (30%) landslides were taken in the testing dataset to be used for validation purposes. Eleven landslide causative factors were selected from numerous hydrological, geological and topographical factors and were analyzed for landslide susceptibility mapping using three bivariate statistical models, namely; Frequency Ratio (FR), Certainty Factor (CF) and Shanon Entropy (SE). Two sets of LSM maps i.e. landslide susceptibility map natural (LSMN) and landslide susceptibility map road (LSMR), were generated using the above mentioned bivariate models and were divided into five landslide susceptibility classes namely; very low, low, medium, high and very high. These maps were analyzed for accuracy of prediction and validation using receiver operating characteristic (ROC) curves and area under curve (AUC) technique which indicated that all three bivariate statistical models performed satisfactorily with the SE model had the highest prediction and validation accuracy of 83-86%. Further analysis LSM maps confirmed that the percentage area in high and very high classes of land-slide susceptibility increased by 2.67-4.17% due to road construction activities in the study area.

scholarly journals Weights of Evidence Modeling for Landslide Susceptibility Mapping of Kabi-Gebro Locality, Gundomeskel area, Central Ethiopia

2020 ◽  
Author(s):  
Nega Getachew ◽  
Matebie Meten
Keyword(s):  
Landslide Susceptibility ◽  
Agricultural Land ◽  
Google Earth ◽  
Weights Of Evidence ◽  
Susceptibility Map ◽  
Landslide Susceptibility Map ◽  
Data Set ◽  
Causative Factors ◽  
Central Highland ◽  
The Impact

Abstract Kabi-Gebro area is located within the Abay Basin at Dera District of North Shewa Zone near Gundomeskel town in the Central highland of Ethiopia and it is about 320 Km from Addis Ababa. This is characterized by undulating topography, intense rainfall, active erosion and highly cultivated area. Geologically characterized by weathered sedimentary and volcanic rocks. Currently, landslides are creating serious challenges in road construction, farming practices and affecting people in this area. Active landslides in this area damaged the gravel road, houses and agricultural land. The main objective of this research is to prepare the landslide susceptibility map. To overcome the landslide problem in this area, landslide susceptibility map was prepared using GIS- based Weights of Evidence model. Based on detailed field assessment and Google Earth image interpretation, 514 landslide locations were identified and classified randomly as training landslide (80%) and validation landslide (20%). The training landslide data set include nine landslide causative factors such as lithology, slope angle, aspect, curvature, land use/land cover, distance to stream, distance to lineament, distance to spring and rainfall inorder to prepare landslide susceptibility map in this study. The landslide susceptibility maps were prepared by adding the weights of contrast values of the nine causative factors using rater calculator in the spatial analyst tool of ArcGIS. The final landslide susceptibility map was reclassified as very low, low, moderate, high and very high landslide susceptiblity classes. This susceptibility map was validated using landslide density index and Area Under the Curve (AUC). The result from this validation showed a success rate and avalidaton rate accuracies of 82.4% and 83.4% respectively for this model. Finally, this study recommends application of appropriate mitigation or corrective measures in order to lessen the impact of landslide in the area.

scholarly journals Landslide Susceptibility in Majalengka Regency, West Java Province

2021 ◽  
Vol 884 (1) ◽  
pp. 012053
Author(s):  
S Selaby ◽  
E Kusratmoko ◽  
A Rustanto
Keyword(s):  
Landslide Susceptibility ◽  
Public Works ◽  
Disaster Mitigation ◽  
Susceptibility Map ◽  
Landslide Susceptibility Map ◽  
Multi Criteria Evaluation ◽  
Susceptibility Maps ◽  
The Government ◽  
The Impact ◽  
Landslide Susceptibility Maps

Abstract Majalengka is one of districts in Indonesia which is susceptible to landslides. Landslides in Majalengka caused enormous losses such as damage to infrastructure, loss of property, and even human fatalities. Seeing of the impact, mitigation efforts are needed to reduce risks and losses by making landslide susceptibility maps. This study aims to map areas landslide susceptibility and as a reference for the government and related agencies to reduce losses. The method used overlay using Spatial Multi-Criteria Evaluation (SMCE), using weighting values from the Minister Public Works Regulation NO.22/PRT/M/2007, Puslittanak Bogor (2014) and Directorate Volcanology and Disaster Mitigation (DVMBG) (2004). Then comparison of these sources is carried out to determine weighting value with the highest accuracy. The variables are slope, rainfall, soil type, lithology, and land use. The results of this study indicate that landslide susceptibility areas are divided into non-susceptible, low, moderate, and high areas. Where areas Majalengka Regency is dominated by moderate susceptibility level. For the accuracy value of the landslide susceptibility map produced by the weighted value source from the Minister of Public Works Regulation NO.22/PRT/M/2007 has the highest accuracy value of 76%. For weighting from the Bogor Puslittanak is 73%, while weighting source from DVMBG is 68%.

scholarly journals ROCK FORMATION AND SITE CLASS IN BANDAR LAMPUNG

2020 ◽  
Vol 6 (3) ◽  
pp. 183-189
Author(s):  
Rustadi Rustadi ◽  
Eko Rananda
Keyword(s):  
Shear Wave ◽  
Wave Velocity ◽  
Shear Wave Velocity ◽  
Sedimentary Rock ◽  
Soil Characteristics ◽  
Shallow Depth ◽  
Site Class ◽  
Rock Formations ◽  
Class D ◽  
The Impact

Soil characteristics are important impact for the scale of damage caused by earthquake vibrations. The impact caused by an earthquake in a location depends on the shear wave velocity (Vs). The study examined the effect of sedimentary rock formations on shear wave velocity and site class based on SPT tests in two rock formations in Bandar Lampung. The value of Vs, Vs30 and site class is determined based on the N-SPT value. Older rock formations of Quaternary age, have produced compaction at a shallow depth of 2 m from the surface, with Vs30 360 m/s and site class C. While the formation is younger, compactions are formed at a depth of 20 m, Vs30 200 m/s and site class D.

Model of spring runoff quantity and quality for urban watersheds

1999 ◽  
Vol 39 (12) ◽  
pp. 249-256 ◽  
Author(s):  
Alena Bartošová ◽  
Vladimir Novotny
Keyword(s):  
Water Quality ◽  
Traffic Safety ◽  
Suspended Solids ◽  
Dissolved Metals ◽  
Chemical Application ◽  
Traffic Emission ◽  
Creek Watershed ◽  
Receiving Waters ◽  
The Impact

Use of deicing chemicals to provide traffic safety during winter causes water quality problems for urban receiving waters. High chloride content from deicing salt changes partitioning between adsorbed and dissolved metals, increasing the dissolved (toxic) metal fraction in snowmelt. Abrasives generate large loads of suspended solids. A model was developed to evaluate the impact of snow removal and road deicing practices on water quality of urban receiving waters. The model was calibrated using data from the Lincoln Creek watershed (Milwaukee, Wisconsin), and verified on 30th Ave. watershed (Edmonton, Alberta). The watersheds differ in winter weather pattern as well as in winter road maintenance. Road salt is used exclusively in Milwaukee to maintain road safety while sand-salt mixture is applied in Edmonton. The quantitative part of the model is based on heat balance theory and describes the processes of snowpack formation, snow melting, infiltration, and runoff formation. The qualitative part calculates the accumulation of pollutants (atmospheric deposition, traffic emission, and deicing chemical application) in snowpack and resulting quality of snowmelt runoff. The mobility of pollutant in the snowpack is determined by partitioning to particulates and ice crystals. The results of simulation for chlorides, suspended solids, and lead are presented.

Environmental and Economic Evaluation of Cow-Calf Wintering Site Runoff Control as a Beneficial Management Practice to Improve Surface Water Quality

2007 ◽  
Vol 42 (4) ◽  
pp. 240-251
Author(s):  
James J. Wuite ◽  
David S. Chanasyk ◽  
Muhammad A. Akbar
Keyword(s):  
Water Quality ◽  
Management Practice ◽  
Surface Water Quality ◽  
Economic Cost ◽  
Creek Watershed ◽  
Runoff Control ◽  
Surrogate Measure ◽  
The Impact ◽  
Kjeldahl Nitrogen

Abstract A runoff diversion-collection system was evaluated as a beneficial management practice (BMP) for minimizing the impact of wintering site runoff on the water quality of an adjacent reach in the headwaters sub-basin of the Haynes Creek Watershed in central Alberta. Significant (α = 0.05) post-BMP mean annual load reductions of 13, 47, and 17% for dissolved, particulate, and total phosphorus, respectively, were realized. Mean annual loads of nitrate nitrogen and total Kjeldahl nitrogen were also reduced by 83 and 22%, respectively. The sum of total loads of Kjeldahl nitrogen and nitrate-plus-nitrite nitrogen, a surrogate measure of total nitrogen, also showed a reduction of 29%. However, mean annual load of total residue increased by 15%. Despite significance at the wintering site, these water quality changes were not statistically detected at the outlet of the subbasin. In spite of the measureable improvement in downstream water quality, adoption of the studied BMP represented a net economic cost to the producer under the current management conditions at the site. Furthermore, there appeared a need for concurrent implementation of BMPs in the headwaters sub-basin to be able to register any detectable changes in water quality at its outlet.

scholarly journals Weights of evidence modeling for landslide susceptibility mapping of Kabi-Gebro locality, Gundomeskel area, Central Ethiopia

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Nega Getachew ◽  
Matebie Meten
Keyword(s):  
Landslide Susceptibility ◽  
Google Earth ◽  
Weights Of Evidence ◽  
Slope Aspect ◽  
Susceptibility Map ◽  
Landslide Susceptibility Map ◽  
Causative Factors ◽  
Central Highland ◽  
Slide Debris ◽  
The Impact

AbstractKabi-Gebro locality of Gundomeskel area is located within the Abay Basin at Dera District of North Shewa Zone in the Central highland of Ethiopia and it is about 320Km from Addis Ababa. This is characterized by undulating topography, intense rainfall, active erosion and highly cultivated area. Geologically, it comprises weathered sedimentary and volcanic rocks. Active landslides damaged the gravel road, houses and agricultural land. The main objective of this research is to prepare the landslide susceptibility map using GIS-based Weights of Evidence model. Based on detailed field assessment and Google Earth image interpretation, 514 landslides were identified and classified randomly into training landslides (80%) and validation landslides (20%). The most common types of landslides in the study area include earth slide (rotational and translational slide), debris slide, debris flow, rock fall, topple, rock slide, creep and complex. Nine landslide causative factors such as lithology, slope, aspect, curvature, land use/land cover, distance to stream, distance to lineament, distance to spring and rainfall were used to prepare a landslide susceptibility map of the study area by adding the weights of contrast values of these causative factors using a rater calculator of the spatial analyst tool in ArcGIS. The final landslide susceptibility map was reclassified as very low, low, moderate, high and very high susceptibility classes. This susceptibility map was validated using landslide density index and area under the curve (AUC). The result from this model validation showed a success rate and a validation rate accuracy of 82.4% and 83.4% respectively. Finally, implementing afforestation strategies on bare land, constructing surface drainage channels & ditches, providing engineering reinforcements such as gabion walls, retaining walls, anchors and bolts whenever necessary and prohibiting hazardous zones can be recommended in order to lessen the impact of landslides in this area.

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