Combining AHP and genetic algorithms approaches to modify DRASTIC model to assess groundwater vulnerability: a case study from Jianghan Plain,China

Accurate identification of vulnerability areas is critical for groundwater resources protection and management. The present study employed the modified DRASTIC model to assess the groundwater vulnerability of Jianghan Plain, a major farming area in central China. DRASTICL model was developed by incorporating the land use factor to the original model. The ratings and weightings of the selected parameters were optimized by analytic hierarchy process (AHP) method and genetic algorithms (GAs) method, respectively. A combined AHP–GAs method was proposed to further develop this methodology. The unity-based normalization process was employed to categorize the vulnerability maps into four types, such as very high (>0.75), high (0.5–0.75), low (0.25–0.5), and very low (<0.25). The accuracy of vulnerability mapping was validated by Pearson’s correlation coefficient between vulnerability index and the nitrate concentration in groundwater and analysis of variance F statistic. The results revealed that the modified DRASTIC model had a large improvement over the conventional model. The correlation coefficient increased significantly from 41.07 to 75.31% after modification. Sensitivity analysis indicated that the depth to groundwater with 39.28% of mean effective weight was the most critical factor affecting the groundwater vulnerability. The developed vulnerability model proposed in this study could provide important objective information for groundwater and environmental management at local level and innovation for international researchers.     

The extreme, red afterglow of GRB 060923A: distance or dust?

Gamma-ray bursts (GRBs) are powerful probes of the early Universe, but locating and identifying very distant GRBs remain challenging. We report here the discovery of the K -band afterglow of Swift GRB 060923A, imaged within the first hour post-burst, and the faintest so far found. It was not detected in any bluer bands to deep limits, making it a candidate very high- z burst  ( z ≳ 11)  . However, our later-time optical imaging and spectroscopy reveal a faint galaxy coincident with the GRB position which, if it is the host, implies a more moderate redshift (most likely   z ≲ 2.8  ) and therefore that dust is the likely cause of the very red-afterglow colour. This being the case, it is one of the few instances so far found of a GRB afterglow with high-dust extinction.     

Solar transients disturbing the terrestrial magnetic environment at higher latitudes

Geomagnetic field variations during five major Solar Energetic Particle (SEP) events of solar cycle 23 have been investigated in the present study. The SEP events of 1 October 2001, 4 November 2001, 22 November 2001, 21 April 2002 and 14 May 2005 have been selected to study the geomagnetic field variations at two high-latitude stations, Thule (77.5^° N, 69.2^° W) and Resolute Bay (74.4^° E, 94.5^° W) of the northern polar cap. We have used the GOES proton flux in seven different energy channels (0.8–4 MeV, 4–9 MeV, 9–15 MeV, 15–40 MeV, 40–80 MeV, 80–165 MeV, 165–500 MeV). All the proton events were associated with geoeffective or Earth directed CMEs that caused intense geomagnetic storms in response to geospace. We have taken high-latitude indices, AE and PC, under consideration and found fairly good correlation of these with the ground magnetic field records during the five proton events. The departures of the H component during the events were calculated from the quietest day of the month for each event and have been represented as ΔH _THL and ΔH _RES for Thule and Resolute Bay, respectively. The correspondence of spectral index, inferred from event integrated spectra, with ground magnetic signatures ΔH _THL and ΔH _RES along with Dst and PC indices have been brought out. From the correlation analysis we found a very strong correlation to exist between the geomagnetic field variation (ΔHs) and high-latitude indices AE and PC. To find the association of geomagnetic storm intensity with proton flux characteristics we derived the correspondence between the spectral indices and geomagnetic field variations (ΔHs) along with the Dst and AE index. We found a strong correlation (0.88) to exist between the spectral indices and ΔHs and also between spectral indices and AE and PC.     

The unusual X-ray light curve of GRB 080307: the onset of the afterglow?

Swift -detected GRB 080307 showed an unusual smooth rise in its X-ray light curve around 100 s after the burst, at the start of which the emission briefly softened. This 'hump' has a longer duration than is normal for a flare at early times and does not demonstrate a typical flare profile. Using a two-component power-law-to-exponential model, the rising emission can be modelled as the onset of the afterglow, something which is very rarely seen in Swift -X-ray light curves. We cannot, however, rule out that the hump is a particularly slow early-time flare, or that it is caused by upscattered reverse shock electrons.     

User expectations for multibeam echo sounders backscatter strength data-looking back into the future

With the ability of multibeam echo sounders (MBES) to measure backscatter strength (BS) as a function of true angle of insonification across the seafloor, came a new recognition of the potential of backscatter measurements to remotely characterize the properties of the seafloor. Advances in transducer design, digital electronics, signal processing capabilities, navigation, and graphic display devices, have improved the resolution and particularly the dynamic range available to sonar and processing software manufacturers. Alongside these improvements the expectations of what the data can deliver has also grown. In this paper, we identify these user-expectations and explore how MBES backscatter is utilized by different communities involved in marine seabed research at present, and the aspirations that these communities have for the data in the future. The results presented here are based on a user survey conducted by the GeoHab (Marine Geological and Biological Habitat Mapping) association. This paper summarises the different processing procedures employed to extract useful information from MBES backscatter data and the various intentions for which the user community collect the data. We show how a range of backscatter output products are generated from the different processing procedures, and how these results are taken up by different scientific disciplines, and also identify common constraints in handling MBES BS data. Finally, we outline our expectations for the future of this unique and important data source for seafloor mapping and characterisation.     

Retrieving of Land Surface Temperature Using Thermal Remote Sensing and GIS Techniques in Kandaihimmat Watershed,Hoshangabad, Madhya Pradesh

Remotely sensed thermal infrared (TIR) data have been widely used to retrieve land surface temperature (LST). LST is an important parameter in the studies of urban thermal environment and dynamics. In the study, an attempt has been made using LANDSAT 8 thermal imagery to compute LST and the associated land cover parameters viz; land surface emissivity (LSE), normalized difference vegetation index (NDVI), normalized difference built-up index (NDBI) and normalized difference water index (NDWI). Landsat 8 TIRS band 10 & 11 (thermal bands) during 21 Oct. 2016, 22 Nov.2016, 24 Dec. 2016 and 09 Jan. 2017 were processed for LST analysis. However, band 5 & band 4 of the imagery was processed for NDVI, band 6 & band 5 for NDBI and band 2 & band 5 for NDWI analysis. LST has been derived from both the bands 10 &11 and validated by in-situ observations on the date and time of satellite overpass from the study area. Band 10 derived LST have shown much temperature difference while comparing with the in-situ observations. However, LST derived from band 11 found similar & close to the in-situ measurements. Relationship between band 11 results and in-situ observed measurements were developed, which has showing a strong correlation with (r² = 0.991). Land surface emissivity were also evaluated which shows variation in different land cover surfaces like vegetation, settlement, forest cover and water body. The study has proven that land surface temperature derived from satellite band 11 is the actual surface temperature of the study area.     

Corruption in cyclone preparedness and relief efforts in coastal Bangladesh: Lessons for climate adaptation?

This article seeks to draw possible lessons for adaptation programmes in Bangladesh by examining whether cyclone preparedness and relief interventions are subject to corrupt practices. Based on a random sample survey of 278 households, three focus-group discussions and seven key-informant interviews, the article investigates the nature and extent of corruption in pre- and post-disaster interventions in Khulna before and after Cyclone Aila in May 2009. Ninety nine percent of households reported losses from corrupt practices. Post-disaster interventions (such as food aid and public works schemes) suffered from greater levels, and worse types, of corruption than pre-disaster interventions (such as cyclone warning systems and disaster-preparedness training). Using an asset index created using principal component analysis, the article assesses how corruption affected wealth quartiles. Ultra-poor households were affected more by corruption in pre-disaster interventions, the wealthiest quartile more in certain post-disaster interventions, in particular public works and non-governmental interventions. These findings may hold lessons for attempts to increase resilience as current adaptation measures mirror some cyclone preparedness and relief efforts.     

Chaos in streaming MHD flows

Taking into account the effect of external driving, Kelvin-Helmholtz instability in hydromagnetics is studied to determine a local criterion for the existence of chaotic motion with the use of Melnikov function. Also obtained is the most chaotic frequency.     

Downscaling and projection of precipitation from general circulation model predictors in an equatorial climate region by the automated regression-based statistical method

The authors have applied an automated regression-based statistical method, namely, the automated statistical downscaling (ASD) model, to downscale and project the precipitation climatology in an equatorial climate region (Peninsular Malaysia). Five precipitation indices are, principally, downscaled and projected: mean monthly values of precipitation (Mean), standard deviation (STD), 90th percentile of rain day amount, percentage of wet days (Wet-day), and maximum number of consecutive dry days (CDD). The predictors, National Centers for Environmental Prediction (NCEP) products, are taken from the daily series reanalysis data, while the global climate model (GCM) outputs are from the Hadley Centre Coupled Model, version 3 (HadCM3) in A2/B2 emission scenarios and Third-Generation Coupled Global Climate Model (CGCM3) in A2 emission scenario. Meanwhile, the predictand data are taken from the arithmetically averaged rain gauge information and used as a baseline data for the evaluation. The results reveal, from the calibration and validation periods spanning a period of 40 years (1961–2000), the ASD model is capable to downscale the precipitation with reasonable accuracy. Overall, during the validation period, the model simulations with the NCEP predictors produce mean monthly precipitation of 6.18–6.20 mm/day (root mean squared error 0.78 and 0.82 mm/day), interpolated, respectively, on HadCM3 and CGCM3 grids, in contrast to 6.00 mm/day as observation. Nevertheless, the model suffers to perform reasonably well at the time of extreme precipitation and summer time, more specifically to generate the CDD and STD indices. The future projections of precipitation (2011–2099) exhibit that there would be an increase in the precipitation amount and frequency in most of the months. Taking the 1961–2000 timeline as the base period, overall, the annual mean precipitation would indicate a surplus projection by nearly 14~18 % under both GCM output cases (HadCM3 A2/B2 scenarios and CGCM3 A2 scenario). According to the model simulation, the September–November periods might be the more significant months projecting the increment of the precipitation amount around over 50 %, while the precipitation deficit would be seen in March–May periods.