Application of analytical hierarchy process (AHP) for flood risk assessment: a case study in Malda district of West Bengal,India

A field experiment was conducted from 2 May 2010 to 1 May 2012 in the Gurbantunggut Desert, the second largest desert in China, to investigate saltation activity and its threshold velocity, and their relations with atmospheric and soil conditions. The results showed that saltation activity occurred more frequently during 08:00–20:00 Local Standard Time in spring and summer, with air temperatures between 20.0 and 29.0 °C, water vapor pressures between 0.6 and 0.9 kPa, soil temperatures between 25.0 and 30.0 °C, and a soil moisture lower than 0.04 m³/m³. At 2 m height, the saltation threshold velocity varied between 11.1 and 13.9 m/s, with a mean of 12.5 m/s. Threshold velocity showed clear seasonal variations in the following sequence: spring (11.7 m/s) < autumn (12.7 m/s) < summer (13.6 m/s). Affected by soil conditions, aeolian sand transport was weak, with an average annual aeolian sand that transported across a section (1.0 m × 2.0 m) of less than 6.0 kg.     

Seasonal characteristics and sources of carbonaceous components and elements of PM10 (2010–2019) in Delhi,India

In this study we present the seasonal chemical characteristics and potential sources of PM₁₀ at an urban location of Delhi, India during 2010?2019. The concentrations of carbonaceous aerosols [organic carbon (OC), elemental carbon (EC), water soluble organic carbon (WSOC) and water insoluble organic carbon (WIOC)] and elements (Al, Fe, Ti, Cu, Zn, Mn, Pb, Cr, F, Cl, Br, P, S, K, As, Na, Mg, Ca, B, Ni, Mo, V, Sr, Zr and Rb) in PM₁₀ were estimated to explore their possible sources. The annual average concentration (2010–2019) of PM₁₀ was computed as 227?±?97 µg m^?3 with a range of 34?734 µg m^?3. The total carbonaceous aerosols in PM₁₀ was accounted for 22.5% of PM₁₀ mass concentration, whereas elements contribution to PM₁₀ was estimated to be 17% of PM₁₀. The statistical analysis of OC vs. EC and OC vs. WSOC of PM₁₀ reveals their common sources (biomass burning and/or fossil fuel combustion) during all the seasons. Enrichment factors (EFs) of the elements and the relationship of Al with other crustal metals (Fe, Ca, Mg and Ti) of PM₁₀ indicates the abundance of mineral dust over Delhi. Principal component analysis (PCA) extracted the five major sources [industrial emission (IE), biomass burning?+?fossil fuel combustion (BB?+?FFC), soil dust, vehicular emissions (VE) and sodium and magnesium salts (SMS)] of PM₁₀ in Delhi, India. Back trajectory and cluster analysis of airmass parcel indicate that the pollutants approaching to Delhi are mainly from Pakistan, IGP region, Arabian Sea and Bay of Bengal.

     

Estimation of air-overpressure produced by blasting operation through a neuro-genetic technique

Blasting operations usually produce significant environmental problems which may cause severe damage to the nearby areas. Air-overpressure (AOp) is one of the most important environmental impacts of blasting operations which needs to be predicted and subsequently controlled to minimize the potential risk of damage. In order to solve AOp problem in Hulu Langat granite quarry site, Malaysia, three non-linear methods namely empirical, artificial neural network (ANN) and a hybrid model of genetic algorithm (GA)–ANN were developed in this study. To do this, 76 blasting operations were investigated and relevant blasting parameters were measured in the site. The most influential parameters on AOp namely maximum charge per delay and the distance from the blast-face were considered as model inputs or predictors. Using the five randomly selected datasets and considering the modeling procedure of each method, 15 models were constructed for all predictive techniques. Several performance indices including coefficient of determination (R ²), root mean square error and variance account for were utilized to check the performance capacity of the predictive methods. Considering these performance indices and using simple ranking method, the best models for AOp prediction were selected. It was found that the GA–ANN technique can provide higher performance capacity in predicting AOp compared to other predictive methods. This is due to the fact that the GA–ANN model can optimize the weights and biases of the network connection for training by ANN. In this study, GA–ANN is introduced as superior model for solving AOp problem in Hulu Langat site.     

‘Surface Drag in the Arctic Marginal Sea-ice Zone: A Comparison of Different Parameterisation Concepts’

Two parameterisation schemes for the turbulent surface fluxes and drag coefficients over the Arctic marginal sea-ice zone (MIZ) are (further) developed, and their results are compared with each other. Although the schemes are based on different principles (flux averaging and parameter averaging), the resulting drag coefficients differ only slightly in the case of neutral and stable stratification. For unstable stratification and sea-ice conditions being typical for the north-eastern Fram Strait, the drag coefficients resulting from the parameter-averaging concept are 5–10% larger than those of the flux-averaging concept. At a sea-ice concentration of 45%, the parameter-averaging method overestimates the heat fluxes by a factor of 1.2. An inclusion in the schemes of form drag caused by floe edges and ridges has a much larger effect on the drag coefficient, and on the momentum fluxes, than the choice between the parameter-averaging or flux-averaging methods. Based on sensitivity studies with the flux-averaging scheme, a simple formula for the effective drag coefficient above the Arctic MIZ is derived. It reduces the computational costs of the more complex parameterisations and could also be used in larger scale models. With this simple formula, the effective drag coefficient can be calculated as a function of the sea-ice concentration and skin drag coefficients for water and ice floes. The results obtained with this parameterisation differ only slightly from those using the more complex schemes. Finally, it is shown that in the MIZ, drag coefficients for sea-ice models may differ significantly from the effective drag coefficients used in atmospheric models.     

Chlorophyll modulation of mixed layer thermodynamics in a mixed-layer isopycnal General Circulation Model — An example from Arabian Sea and equatorial Pacific

Western tropical Indian Ocean, Arabian Sea, and the equatorial Pacific are known as regions of intense bio-chemical-physical interactions: the Arabian Sea has the largest phytoplankton bloom with seasonal signal, while the equatorial Pacific bloom is perennial with quasi-permanent upwelling. Here, we studied three dimensional ocean thermodynamics comparing recent ocean observation with ocean general circulation model (OPYC) experiment combined with remotely sensed chlorophyll pigment concentrations from the Coastal Zone Color Scanner (CZCS). Using solar radiation parameterization representing observations that a higher abundance of chlorophyll increases absorption of solar irradiance and heating rate in the upper ocean, we showed that the mixed layer thickness decreases more than they would be under clear water conditions. These changes in the model mixed layer were consistent with Joint Global Ocean Flux Study (JGOFS) observations during the 1994-1995 Arabian Sea experiment and epi-fluorescence microscopy (EFM) on samples collected during Equatorial Pacific Ocean Climate Study (EPOCS) in November, 1988. In the Arabian Sea, as the chlorophyll concentrations peak in October (3 mg/m³) after the summer plankton bloom induced by coastal upwelling, the chlorophyll induced biological heating enhanced the sea surface temperature (SST) by as much as 0.6‡C and sub-layer temperature decreases and sub-layer thickness increases. In the equatorial Pacific, modest concentrations of chlorophyll less than 0.3 mg/m³ is enough to introduce a meridional differential heating, which results in reducing the equatorial mixed layer thickness to more than 20 m. The anomalous meridional tilting of the mixed layer bottom enhances off equatorial westward geostrophic currents. Consequently, the equatorial undercurrent transports more water from west to east. We proposed that these numerical model experiments with use of satellite andin situ ocean observations are consistent under three dimensional ocean circulation theory combined with solar radiation transfer process.     

IR calibrations for water determination in olivine,r-GeO<Subscript>2</Subscript>, and SiO<Subscript>2</Subscript> polymorphs

Mineral-specific IR absorption coefficients were calculated for natural and synthetic olivine, SiO₂ polymorphs, and GeO₂ with specific isolated OH point defects using quantitative data from independent techniques such as proton–proton scattering, confocal Raman spectroscopy, and secondary ion mass spectrometry. Moreover, we present a routine to detect OH traces in anisotropic minerals using Raman spectroscopy combined with the “Comparator Technique”. In case of olivine and the SiO₂ system, it turns out that the magnitude of ε for one structure is independent of the type of OH point defect and therewith the peak position (quartz ε = 89,000 ± 15,000  \textl \textmol_{\textH2\textO}^-1 \textcm^-2\text{l}\,\text{mol}_{{\text{H}_2}\text{O}}^{-1}\,\text{cm}^{-2}), but it varies as a function of structure (coesite ε = 214,000 ± 14,000  \textl \textmol_{\textH2\textO}^-1 \textcm^-2\text{l}\,\text{mol}_{{\text{H}_2}\text{O}}^{-1}\,\text{cm}^{-2}; stishovite ε = 485,000 ± 109,000  \textl \textmol_{\textH2\textO}^-1 \textcm^-2\text{l}\,\text{mol}_{{\text{H}_2}\text{O}}^{-1}\,\text{cm}^{-2}). Evaluation of data from this study confirms that not using mineral-specific IR calibrations for the OH quantification in nominally anhydrous minerals leads to inaccurate estimations of OH concentrations, which constitute the basis for modeling the Earth’s deep water cycle.     

Strategies to mitigate aliasing of loading signals while estimating GPS frame parameters

Although GNSS techniques are theoretically sensitive to the Earth center of mass, it is often preferable to remove intrinsic origin and scale information from the estimated station positions since they are known to be affected by systematic errors. This is usually done by estimating the parameters of a linearized similarity transformation which relates the quasi-instantaneous frames to a long-term frame such as the International Terrestrial Reference Frame (ITRF). It is well known that non-linear station motions can partially alias into these parameters. We discuss in this paper some procedures that may allow reducing these aliasing effects in the case of the GPS techniques. The options include the use of well-distributed sub-networks for the frame transformation estimation, the use of site loading corrections, a modification of the stochastic model by downweighting heights, or the joint estimation of the low degrees of the deformation field. We confirm that the standard approach consisting of estimating the transformation over the whole network is particularly harmful for the loading signals if the network is not well distributed. Downweighting the height component, using a uniform sub-network, or estimating the deformation field perform similarly in drastically reducing the amplitude of the aliasing effect. The application of these methods to reprocessed GPS terrestrial frames permits an assessment of the level of agreement between GPS and our loading model, which is found to be about 1.5 mm WRMS in height and 0.8 mm WRMS in the horizontal at the annual frequency. Aliased loading signals are not the main source of discrepancies between loading displacement models and GPS position time series.     

Implications of climate change on streamflow of a snow-fed river system of the Northwest Himalaya

Air temperature and snow cover variability are sensitive indicators of climate change. This study was undertaken to forecast and quantify the potential streamflow response to climate change in the Jhelum River basin. The implications of air temperature trends (+0.11°C/decade) reported for the entire north-west Himalaya for past century and the regional warming (+0.7°C/decade) trends of three observatories analyzed between last two decades were used for future projection of snow cover depletion and stream flow. The streamflow was simulated and validated for the year 2007-2008 using snowmelt runoff model (SRM) based on in-situ temperature and precipitation with remotely sensed snow cover area. The simulation was repeated using higher values of temperature and modified snow cover depletion curves according to the assumed future climate. Early snow cover depletion was observed in the basin in response to warmer climate. The results show that with the increase in air temperature, streamflow pattern of Jhelum will be severely affected. Significant redistribution of streamflow was observed in both the scenarios. Higher discharge was observed during spring-summer months due to early snowmelt contribution with water deficit during monsoon months. Discharge increased by 5% 40% during the months of March to May in 2030 and 2050. The magnitude of impact of air temperature is higher in the scenario-2 based on regional warming. The inferences pertaining to change in future streamflow pattern can facilitate long term decisions and planning concerning hydro-power potential, waterresource management and flood hazard mapping in the region.     

Streamflow response to regional climate model output in the mountainous watershed: a case study from the Swiss Alps

Regional climate model (RCM) outputs are often used in hydrological modeling, in particular for streamflow forecasting. The heterogeneity of the meteorological variables such as precipitation, temperature, wind speed and solar radiation often limits the ability of the hydrological model performance. This paper assessed the sensitivity of RCM outputs from the PRUDENCE project and their performance in reproducing the streamflow. The soil and water assessment tool was used to simulate the streamflow of the Rhone River watershed located in the southwestern part of Switzerland, with the climate variables obtained from four RCMs. We analyzed the difference in magnitude of precipitation, maximum and minimum air temperature, and wind speed with respect to the observed values from the meteorological stations. In addition, we also focused on the impact of the grid resolution on model performance, by analyzing grids with resolutions of 50 × 50 and 25 × 25 km². The variability of the meteorological inputs from various RCMs is quite severe in the studied watershed. Among the four different RCMs, the Danish Meteorological Institute provided the best performance when simulating runoff. We found that temperature lapse rate is significantly important in the mountainous snow and glacier dominated watershed as compared to other variables like precipitation, and wind speed for hydrological performance. Therefore, emphasis should be given to minimum and maximum temperature in the bias correction studies for downscaling climatic data for impact modeling in the mountainous snow and glacier dominated complex watersheds.     

汶川M_S8.0地震对甘肃陇东地区的破坏影响与特征分析

在汶川MS8.0地震后甘肃陇东地区的详细灾害调查基础上,对该区地震破坏进行了分类研究,给出了各种建筑物及工程结构的破坏程度及破坏特征.结合该区独特的地质地理环境对产生地震破坏的原因进行了分析.认为该区地震破坏相对严重的原因除与建筑物本身质量及结构有关外,还与远震和地形影响的长周期效应及持时较长有关.