Snowmelt runoff assessment and prediction under variable climate and glacier cover scenarios in Astore River Basin,Western Himalayas

Climate change is expected to have a significant impact on the Himalayan region, which may ultimately affect the water security and agriculture productivity in the region. Investigations of hydrologic regimes and their linkage to climatic trends are therefore gaining importance to reduce vulnerability of growing implications in the region. In the present study, the eWater source software implementation of GR4JSG snow melt model was used for snow melt runoff modeling of the Astore river basin, western Himalayas. The model calibration and validation indicated a close agreement between the simulated and observed discharge data. The scenario of 0.9 °C increase in temperature indicated 33% rise in the river discharge, while an increase of 10% in precipitation may exaggerate the river flows by 15%. The scenario of 100% increase in glaciated area showed 41% increase in the Astore river discharge. On the other hand, reduction of 50% glacier cover may result in 34% decline in the river discharge, while 0% glacier coverage may reduce the river discharges by 49% from that of the base year 2014. It is essential to develop a long-term water resource monitoring process and adapt water management systems taking into account the socio-economic and ecological complexities of the region.     

GIS-based DRASTIC model for groundwater vulnerability and pollution risk assessment in the Peshawar District,Pakistan

Groundwater is the most economic natural source of drinking in urban and rural areas which are degraded due to high population growth and increased industrial development. We applied a GIS-based DRASTIC model in a populated urban area of Pakistan (Peshawar) to assess groundwater vulnerability to pollution. Six input parameters—depth to phreatic/groundwater level, groundwater recharge, aquifer material, soil type, slope, and hydraulic conductivity—were used in the model to generate the groundwater vulnerable zones. Each parameter was divided into different ranges or media types, and ratings R?=?1?–?10 were assigned to each factor where 1 represented the very low impact on pollution potential and 10 represented very high impact. Weight multipliers W?=?1?–?5 were also used to balance and enhance the importance of each factor. The DRASTIC model scores obtained varied from 47 to 147, which were divided into three different zones: low, moderate, and high vulnerability to pollution. The final results indicate that about 31.22, 39.50, and 29.27% of the total area are under low, moderate, and high vulnerable zones, respectively. Our method presents a very simple and robust way to assess groundwater vulnerability to pollution and helps the decision-makers to select appropriate landfill sites for waste disposals, and manage groundwater pollution problems efficiently.     

Volume,gravitational potential energy reduction,and regional centroid position change in the wake of landslides triggered by the 14 April 2010 Yushu earthquake of China

In recent years, earthquake-triggered landslides have attracted much attention in the scientific community as a main form of seismic ground response. However, little work has been performed concerning the volume and gravitational potential energy reduction of earthquake-triggered landslides and their severe effect on landscape change. This paper presents a quantitative study on the volume, gravitational potential energy reduction, and change in landscape related to landslides triggered by the 14 April 2010 Yushu earthquake. At least 2,036 landslides were triggered by the earthquake. A total landslide scar area of 1.194 km² was delineated from the visual interpretation of aerial photographs and satellite images and was supported by selected field checking. In this paper, we focus on possible answers to the following five questions: (1) What is the total volume of the 2,036 landslides triggered by the earthquake, and what is the average landslide erosion thickness in the earthquake-stricken area? (2) What are the elevations of all landslide materials in relation to pre- and post-landsliding? (3) How much was the gravitational potential energy reduced due to the sliding of these landslide materials? (4) What is the average elevation change caused by these landslides in the study area? (5) What is the vertical change of the regional centroid position above sea level, as induced by these landslides? It is concluded that the total volume of the 2,036 landslides is 2.9399?×?10⁶ m³. The landslide erosion thickness throughout the study area is 2.02 mm. The materials of these landslides moved from an elevation of 4,145.243 to 4,104.697 m, resulting in a decreased distance of 40.546 m. The gravitational potential energy reduction related to the landslides triggered by the earthquake was 2.9213?×?10¹² J. The average regional elevation of the study area is 4,427.160 m, a value consistent with the assumption that the accumulated materials were remained in situ. This value changes from 4,427.160 to 4,427.158 m with all landslide materials moved out of the study area, resulting in a reduction in elevation of 2 mm. Based on the assumption that all landslide materials moved out of the study area, the elevations of the centroid of the study area’s crust changed from 2,222.45967 to 2,222.45867 m, which means the centroid value decreased by 1 mm. This value is 0.001 mm when assuming that the materials were remained in situ, which is almost negligible, compared with the situation of “all landslide materials moved out of the study area.”     

Probability Prediction Model for Landslide Occurrences in Xi’an,Shaanxi Province,China

Landslides are increasing since the 1980s in Xi’an, Shaanxi Province, China. This is due to the increase of the frequency and intensity of precipitation caused by complex geological structures, the presence of steep landforms, seasonal heavy rainfall, and the intensifcation of human activities. In this study, we propose a landslide prediction model based on the analysis of intraday rainfall （IR） and antecedent effective rainfall （AER）. Primarily, the number of days and degressive index of the antecedent effective rainfall which affected landslide occurrences in the areas around Qin Mountains, Li Mountains and Loess Tableland was established. Secondly, the antecedent effective rainfall and intraday rainfall were calculated from weather data which were used to construct critical thresholds for the 10%, 50% and 90% probabilities for future landslide occurrences in Qin Mountain, Li Mountain and Loess Tableland. Finally, the regions corresponding to different warning levels were identified based on the relationship between precipitation and the threshold, that is; “A” region is safe, “B” region is on watch alert, “C” region is on warning alert and “D” region is on severe warning alert. Using this model, a warning program is proposed which can predict rainfall-induced landslides by means of real-time rain gauge data and real-time geo-hazard alert and disaster response programs. Sixteen rain gauges were installed in the Xi’an region by keeping in accordance with the regional geology and landslide risks. Based on the data from gauges, this model accurately achieves the objectives of conducting real-time monitoring as well as providing early warnings of landslides in the Xi’an region.     

Biosorption of Cr(III) and Cr(VI) species from aqueous solution by Cabomba caroliniana: kinetic and equilibrium study

This study reports the potential ability of non-living biomass of Cabomba caroliniana for biosorption of Cr(III) and Cr(VI) from aqueous solutions. Effects of contact time, biosorbent dosage, pH of the medium, initial concentration of metal ion and protonation of the biosorbent on heavy metal–biosorbent interactions were studied through batch sorption experiments. Cr(III) was sorbed more rapidly than Cr(VI) and the pH of the medium significantly affected the extent of biosorption of the two metal species differently. Surface titrations showed that the surface of the biosorbent is positively charged at low pH while it is negatively charged at pH higher than 4.0. Protonation of the biosorbent increased its capacity for removal of Cr(III), while decreasing that of Cr(VI). FT-IR spectra of the biosorbent confirmed the involvement of –OH groups on the biosorbent surface in the chromium removal process. Kinetic and equilibrium data showed that the sorption process of each chromium species followed pseudo second-order kinetic model and both Langmuir and Freundlich isothermal models. A possible mechanism for the biosorption of chromium species by non-living C. caroliniana is suggested.     

Uncertainties in the regional climate models simulations of South-Asian summer monsoon and climate change

The uncertainties in the regional climate models (RCMs) are evaluated by analyzing the driving global data of ERA40 reanalysis and ECHAM5 general circulation models, and the downscaled data of two RCMs (RegCM4 and PRECIS) over South-Asia for the present day simulation (1971–2000) of South-Asian summer monsoon. The differences between the observational datasets over South-Asia are also analyzed. The spatial and the quantitative analysis over the selected climatic regions of South-Asia for the mean climate and the inter-annual variability of temperature, precipitation and circulation show that the RCMs have systematic biases which are independent from different driving datasets and seems to come from the physics parameterization of the RCMs. The spatial gradients and topographically-induced structure of climate are generally captured and simulated values are within a few degrees of the observed values. The biases in the RCMs are not consistent with the biases in the driving fields and the models show similar spatial patterns after downscaling different global datasets. The annual cycle of temperature and rainfall is well simulated by the RCMs, however the RCMs are not able to capture the inter-annual variability. ECHAM5 is also downscaled for the future (2071–2100) climate under A1B emission scenario. The climate change signal is consistent between ECHAM5 and RCMs. There is warming over all the regions of South-Asia associated with increasing greenhouse gas concentrations and the increase in summer mean surface air temperature by the end of the century ranges from 2.5 to 5 °C, with maximum warming over north western parts of the domain and 30 % increase in rainfall over north eastern India, Bangladesh and Myanmar.