The Oeschinensee rock avalanche,Bernese Alps,Switzerland: a co-seismic failure 2300 years ago?

Landslide deposits dam Lake Oeschinen (Oeschinensee), located above Kandersteg, Switzerland. However, past confusion differentiating deposits of multiple landslide events has confounded efforts to quantify the volume, age, and failure dynamics of the Oeschinensee rock avalanche. Here we combine field and remote mapping, topographic reconstruction, cosmogenic surface exposure dating, and numerical runout modeling to quantify salient parameters of the event. Differences in boulder lithology and deposit morphology reveal that the landslide body damming Oeschinensee consists of debris from both an older rock avalanche, possibly Kandertal, as well as the Oeschinensee rock avalanche. We distinguish a source volume for the Oeschinensee event of 37 Mm³, resulting in an estimated deposit volume of 46 Mm³, smaller than previous estimates that included portions of the Kandertal mass. Runout modeling revealed peak and average rock avalanche velocities of 65 and 45 m/s, respectively, and support a single-event failure scenario. ³⁶Cl surface exposure dating of deposited boulders indicates a mean age for the rock avalanche of 2.3 ± 0.2 kyr. This age coincides with the timing of a paleo-seismic event identified from lacustrine sediments in Swiss lakes, suggesting an earthquake trigger. Our results help clarify the hazard and geomorphic effects of rare, large rock avalanches in alpine settings.     

STUDY OF RURAL TOURISM IN TURPAN, CHINA

~~STUDY OF RURAL TOURISM IN TURPAN ,CHINA@KEYIM Parhad$Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, P. R. China; The Graduate School of Chinese Academy of Sciences, Beijing 100039, P. R. ChinaBRAMWELL B, LANE B,…     

Statistical landslide susceptibility assessment in a dynamic environment: A case study for Lanzhou City,Gansu Province,NW China

This study presents a statistical landslide susceptibility assessment (LSA) in a dynamic environment. The study area is located in the eastern part of Lanzhou, NW China. The Lanzhou area has exhibited rapid urbanization rates over the past decade associated with greening, continuous land use change, and geomorphic reshaping activities. To consider the dynamics of the environment in the LSA, multitemporal data for landslide inventories and the corresponding causal factors were collected. The weights of evidence (WofE) method was used to perform the LSA. Three time stamps, i.e., 2000, 2012, and 2016, were selected to assess the state of landslide susceptibility over time. The results show a clear evolution of the landslide susceptibility patterns that was mainly governed by anthropogenic activities directed toward generating safer building grounds for civil infrastructure. The low and very low susceptibility areas increased by approximately 10% between 2000 and 2016. At the same time, areas of medium, high and very high susceptibility zones decreased proportionally. Based on the results, an approach to design the statistical LSA under dynamic conditions is proposed, the issues and limitations of this approach are also discussed. The study shows that under dynamic conditions, the requirements for data quantity and quality increase significantly. A dynamic environment requires greater effort to estimate the causal relations between the landslides and controlling factors as well as for model validation.     

Recharge source and hydrogeochemical evolution of shallow groundwater in a complex alluvial fan system,southwest of North China Plain

Many cities around the world are developed at alluvial fans. With economic and industrial development and increase in population, quality and quantity of groundwater are often damaged by over-exploitation in these areas. In order to realistically assess these groundwater resources and their sustainability, it is vital to understand the recharge sources and hydrogeochemical evolution of groundwater in alluvial fans. In March 2006, groundwater and surface water were sampled for major element analysis and stable isotope (oxygen-18 and deuterium) compositions in Xinxiang, which is located at a complex alluvial fan system composed of a mountainous area, Taihang Mt. alluvial fan and Yellow River alluvial fan. In the Taihang mountainous area, the groundwater was recharged by precipitation and was characterized by Ca–HCO₃ type water with depleted δ¹⁸O and δD (mean value of −8.8‰ δ¹⁸O). Along the flow path from the mountainous area to Taihang Mt. alluvial fan, the groundwater became geochemically complex (Ca–Na–Mg–HCO₃–Cl–SO₄ type), and heavier δ¹⁸O and δD were observed (around −8‰ δ¹⁸O). Before the surface water with mean δ¹⁸O of −8.7‰ recharged to groundwater, it underwent isotopic enrichment in Taihang Mt. alluvial fan. Chemical mixture and ion exchange are expected to be responsible for the chemical evolution of groundwater in Yellow River alluvial fan. Transferred water from the Yellow River is the main source of the groundwater in the Yellow River alluvial fan in the south of the study area, and stable isotopic compositions of the groundwater (mean value of −8.8‰ δ¹⁸O) were similar to those of transferred water (−8.9‰), increasing from the southern boundary of the study area to the distal end of the fan. The groundwater underwent chemical evolution from Ca–HCO₃, Na–HCO₃, to Na–SO₄. A conceptual model, integrating stiff diagrams, is used to describe the spatial variation of recharge sources, chemical evolution, and groundwater flow paths in the complex alluvial fan aquifer system.     

A GIS-index integration approach to groundwater suitability zoning for irrigation purposes

In recent decades, the high population growth has increased the demand for agricultural lands and products. Groundwater offers reliability and flexibility in access to water for irrigation purposes, especially in arid and semi-arid areas, such as Amol-Babol Plain, Iran. However, the quality and quantity of groundwater may not be suitable for irrigation purposes in all areas due to urbanizations, and intensive agricultural and industrial activities. Groundwater suitability zoning for irrigation purposes could be useful to improve water resources and land use planning, mostly in areas with water scarcity. Therefore, a GIS-based indices method is proposed to assess suitable zones for agricultural activities, integrating the irrigation water quality (IWQ) index and hydrogeological factors. IWQ index was utilized to assess groundwater quality based on salinity hazard, infiltration hazard, specific ions, and trace elements hazards, and miscellaneous effects such as pH, bicarbonate, and nitrate. The potential of the aquifer for irrigation water abstraction was investigated using hydrogeological surveys such as slope angle of the plain, hydraulic conductivity, and aquifer thickness. The groundwater suitability index classified most of the study area (more than 90 %) as “excellent” or “good” suitability zones for irrigation purposes. A limited area of around 5.6 % of the total area has moderate suitability for irrigation purposes due to the Caspian Seawater intrusion and the presence of fossil saline water. The proposed methodology provides useful information in order to allow irrigation management to prevent water and soil deterioration.     

Adsorption of antimony(V) on kaolinite as a function of pH,ionic strength and humic acid

The present work investigated the adsorption and mobility (desorption) of Sb(V) on kaolinite using batch experiments. The adsorption of Sb(V) on kaolinite was studied as a function of contact time, pH, ionic strength, humic acid (HA), initial Sb(V) concentration and temperature. Kinetic studies suggest that the equilibrium is achieved within 24 h. The adsorption of Sb(V) was strongly affected by changes in I at low ionic strength and unaffected at high ionic strength. The adsorption is weakly dependent on the presence of humic acid, but is strongly dependent on pH. Within the range tested, the optimal pH for Sb(V) adsorption is 3.6, and close to 75% removal can be achieved. Desorption is dependent on the original suspension pH. The addition sequence of Sb(V)/HA do not influence the adsorption of Sb(V) on kaolinite. The adsorption data fit both the Freundlich and Langmuir isotherm. The thermodynamic parameters (ΔH ⁰, ΔS ⁰ and ΔG ⁰) were calculated from the temperature dependence, and the results suggest the endothermic and spontaneous nature of the process.     

Dimensionality Reduction and Classification of Hyperspectral Images Using Object-Based Image Analysis

Object-based image analysis (OBIA) has attained great importance for the delineation of landscape features, particularly with the accessibility to satellite images with high spatial resolution acquired by recent sensors. Statistical parametric classifiers have become ineffective mainly due to their assumption of normal distribution, vast increase in the dimensions of the data and availability of limited ground sample data. Despite pixel-based approaches, OBIA takes semantic information of extracted image objects into consideration, and thus provides more comprehensive image analysis. In this study, Indian Pines hyperspectral data set, which was recorded by the AVIRIS hyperspectral sensor, was used to analyse the effects of high dimensional data with limited ground reference data. To avoid the dimensionality curse, principal component analysis (PCA) and feature selection based on Jeffries–Matusita (JM) distance were utilized. First 19 principal components representing 98.5% of the image were selected using the PCA technique whilst 30 spectral bands of the image were determined using JM distance. Nearest neighbour (NN) and random forest (RF) classifiers were employed to test the performances of pixel- and object-based classification using conventional accuracy metrics. It was found that object-based approach outperformed the traditional pixel-based approach for all cases (up to 18% improvement). Also, the RF classifier produced significantly more accurate results (up to 10%) than the NN classifier.     

Impacts of Cumulus Convective Parameterization Schemes on Summer Monsoon Precipitation Simulation over China

By using the Betts-Miller-Janjic, Grell-Devenyi, and Kain-Fritsch cumulus convective parameterization schemes in theWeather Research and Forecasting (WRF) model, long time simulations from 2000 to 2009 are conducted to investigate the impacts of different cumulus convective parameterization schemes on summer monsoon precipitation simulation over China. The results show that all the schemes have the capability to reasonably reproduce the spatial and temporal distributions of summer monsoon precipitation and the corresponding background circulation. The observed north-south shift of monsoon rain belt is also well simulated by the three schemes. Detailed comparison indicates that the Grell-Devenyi scheme gives a better performance than the others. Deficiency in simulated water vapor transport is one possible reason for the precipitation simulation bias.     

Statistical estimation of high-resolution surface air temperature from MODIS over the Yangtze River Delta,China

High-resolution surface air temperature data are critical to regional climate modeling in terms of energy balance, urban climate change, and so on. This study demonstrates the feasibility of using Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) to estimate air temperature at a high resolution over the Yangtze River Delta region, China. It is found that daytime LST is highly correlated with maximum air temperature, and the linear regression coefficients vary with the type of land surface. The air temperature at a resolution of 1 km is estimated from the MODIS LST with linear regression models. The estimated air temperature shows a clear spatial structure of urban heat islands. Spatial patterns of LST and air temperature differences are detected, indicating maximum differences over urban and forest regions during summer. Validations are performed with independent data samples, demonstrating that the mean absolute error of the estimated air temperature is approximately 2.5°C, and the uncertainty is about 3.1°C, if using all valid LST data. The error is reduced by 0.4°C (15%) if using best-quality LST with errors of less than 1 K. The estimated high-resolution air temperature data have great potential to be used in validating high-resolution climate models and other regional applications.