In the last fifteen years, tsunami science has progressed at a rapid pace. Three major tsunamis: The Indian Ocean in 2004, the 2011 Tohoku tsunami, and the 2018 Palu tsunami were significant landmarks in the history of tsunami science. All the three tsunamis, as mentioned, suffered from either no warning or poor reception of the alerts issued. Various lessons learned, consequent numerical models proposed, post-2004 tsunami damage findings manifested into solutions. However, the misperceived solutions led to a disastrous impact of the 2011 Tohoku event. In the following years, numerous improvements in warning systems and community preparedness frameworks were proposed and implemented. The contributions and new findings have added multi-fold advancements to tsunami science progress. Later, the 2018 Palu tsunami happened and again led to a massive loss of life and property. The warning systems and community seemed un-prepared for this non-seismic tsunami. A significant change is to take place in tsunami science practices and solutions. The 2018 tsunami is one of the most discussed and researched events concerning the palaeotsunami records, damage assessment, and source findings. In the new era, using machine learning and deep learning prevails in all the fields related to tsunami science. This article presents a complete 15-year bibliometric analysis of tsunami research from Scopus and Web of Science (WoS). The review of majorly cited documents in the form of a progressing storyline has highlighted the need for multidisciplinary research to design and propose practical solutions.
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Geochemical characterization of groundwater from northeastern part of Nagpur urban,Central India 总被引：2，自引：1，他引：1
Hydrogeochemical investigations are carried out in the northeastern part of Nagpur urban to assess the quality of groundwater
for its suitability for drinking and irrigation purposes. Groundwater samples are collected from both shallow and deep aquifers
to monitor the hydrochemistry of various ions. The groundwater quality of the area is adversely affected by urbanization as
indicated by distribution of EC and nitrate. In the groundwater of study area, Ca2+ is the most dominant cation and Cl− and HCO3
− are the dominant anions. Majority of the samples have total dissolved solids values above desirable limit and most of them
belong to very hard type. As compared to deep aquifers, shallow aquifer groundwaters are more polluted and have high concentration
of NO3
−. The analytical results reveal that most of the samples containing high nitrate also have high chloride. Major hydrochemical
facies were identified using Piper trilinear diagram. Alkaline earth exceeds alkalis and weak acids exceed strong acids. Shoeller
index values reveal that base-exchange reaction exists all over the area. Based on US salinity diagram most of samples belong
to high salinity-low sodium type. A comparison of groundwater quality in relation to drinking water standards showed that
most of the water samples are not suitable for drinking purpose. 相似文献
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Tsunami in the last 15 years: a bibliometric analysis with a detailed overview and future directions
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N. Subba Rao Deepali Marghade A. Dinakar I. Chandana B. Sunitha B. Ravindra T. Balaji 《Environmental Earth Sciences》2017,76(21):747
A survey on quality of groundwater was carried out for assessing the geochemical characteristics and controlling factors of chemical composition of groundwater in a part of Guntur district, Andhra Pradesh, India, where the area is underlain by Peninsular Gneissic Complex. The results of the groundwater chemistry show a variation in pH, EC, TDS, Ca2+, Mg2+, Na+, K+, HCO3 ?, Cl?, SO4 2?, NO3 ? and F?. The chemical composition of groundwater is mainly characterized by Na+?HCO3 ? facies. Hydrogeochemical type transits from Na+–Cl?–HCO3 ? to Na+–HCO3 ?–Cl? along the flow path. Graphical and binary diagrams, correlation coefficients and saturation indices clearly explain that the chemical composition of groundwater is mainly controlled by geogenic processes (rock weathering, mineral dissolution, ion exchange and evaporation) and anthropogenic sources (irrigation return flow, wastewater, agrochemicals and constructional activities). The principal component (PC) analysis transforms the chemical variables into four PCs, which account for 87% of the total variance of the groundwater chemistry. The PC I has high positive loadings of pH, HCO3 ?, NO3 ?, K+, Mg2+ and F?, attributing to mineral weathering and dissolution, and agrochemicals (nitrogen, phosphate and potash fertilizers). The PC II loadings are highly positive for Na+, TDS, Cl? and F?, representing the rock weathering, mineral dissolution, ion exchange, evaporation, irrigation return flow and phosphate fertilizers. The PC III shows high loading of Ca2+, which is caused by mineral weathering and dissolution, and constructional activities. The PC IV has high positive loading of Mg2+ and SO4 2?, measuring the mineral weathering and dissolution, and soil amendments. The spatial distribution of PC scores explains that the geogenic processes are the primary contributors and man-made activities are the secondary factors responsible for modifications of groundwater chemistry. Further, geochemical modeling of groundwater also clearly confirms the water–rock interactions with respect to the phases of calcite, dolomite, fluorite, halite, gypsum, K-feldspar, albite and CO2, which are the prime factors controlling the chemistry of groundwater, while the rate of reaction and intensity are influenced by climate and anthropogenic activities. The study helps as baseline information to assess the sources of factors controlling the chemical composition of groundwater and also in enhancing the groundwater quality management. 相似文献
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