Application of neo-deterministic seismic hazard assessment to India
by Imtiyaz A.Parvez
Earthquakes constitute one of the most feared natural disasters that occur with no warning and can result in great destruction along with loss of lives, particularly the seismically earthquake-prone countries like India. One way to mitigate the destructive impact of such earthquakes is to conduct a seismic hazard and risk assessment and take remedial measures. This chapter aims at demonstrating significant contributions to the application of neo-deterministic seismic hazard assessment (NDSHA) in India and neighboring region. NDSHA has been built on a rigorous theoretical basis and exploits the currently available computational resources that permit to compute realistic synthetic seismograms. Parvez et al. (2003) published the first-ever neo-deterministic seismic hazard map of India by computing synthetic seismograms with input data set consisting of structural models, seismogenic zones, focal mechanisms, and earthquake catalogs. Later, using updated input data and advanced computational tools, Parvez et al. (2017) produced a revised neo-deterministic seismic hazard map of India. High-resolution NDSHA has also been applied at the regional and local scale in India, particularly in Gujarat state, Kolkata, and the capital city Delhi. This chapter also discusses how peak ground acceleration estimates alone are not sufficient for the adequate design of buildings and infrastructures, since displacements play a critical role and the dynamical analysis of the structure response requires scenario-based complete time series of ground motion. The applications discussed in this chapter can be used as a preventive definition of the seismic hazard without waiting for the great earthquakes and also help those earthquake and civil engineers to avail realistically estimated ground motion database for the safe design of buildings and other infrastructure in the country.
Annual and seasonal trends in actual evapotranspiration over different meteorological sub-divisions in India using satellite-based data
by Raghavendra Prasad K, Kantha Rao Bhimala, G. K. Patra, Himesh S & Sheshakumar Goroshi
The present study analyzed the actual evapotranspiration (ETa) and its components [transpiration (Et), bare soil evaporation (Eb), interception loss (Ei), and open water evaporation (Eo)] data to study the long-term (1980–2018) trends over different meteorological sub-divisions in India. Quantitatively, all India average (µ) annual ETa is 573 mm (standard deviation (σ) = 29 mm), where Et (µ = 456 mm; σ = 30 mm) plays a major role compared to other evaporation processes like Eb (µ = 56 mm; σ = 9 mm), Ei (µ = 34 mm; σ = 3 mm), and Eo (µ = 27 mm). The Mann–Kendall (MK) test reveals an increasing trend (1.33 mm/yr) in annual ETa due to the rising trend in Et (1.91 mm/yr) and Ei (0.16 mm/yr). The sub-division-wise analysis shows the increasing trend in ETa observed over irrigated regions located in the south, north-west, and foothills of the Himalayas during pre-monsoon (March–May) and monsoon season (June–September). The correlation analysis observed a complex relationship between ETa and climatic factors (rainfall (RF), soil moisture (SM), surface temperature (T), relative humidity (RH), surface net solar radiation (SSR), and wind speed (WS)) during monsoon season such that the water-limited areas have a positive correlation with SM, RH and RF, and negative correlation with WS, T, and SSR, whereas, in energy-limited areas (east India), the ETa showed a positive correlation with SSR and T and negative correlation with RF. The main climatic drivers for the increasing trend of ETa are SM and rainfall over dry regions and SSR and T over densely vegetated regions in India.
Analysis of spatio-temporal variability in observed rainfall over Karnataka using different data analytical techniques
by Adithya Samanth, V Rakesh, Smrati Purwar, S M Gavaskar, B Jagadeesha Pai & G N Mohapatra
Karnataka, a state in south India with nearly 80% of the cultivated land under rainfed farming, is very much dependent on rainfall for agricultural productivity. The spatio-temporal variability in observed rainfall over Karnataka is investigated using various data analytical techniques such as parametric and non-parametric methods, rotated empirical orthogonal function (REOF), clustering and spectral analysis. The observed data used for studying rainfall variability is the daily taluk-wise telemetric rain gauge data for a period of 1960–2016. A similar pattern in trend is observed in annual and south-west monsoon (SWM) rainfall over Karnataka such that taluks in the western and northern parts showed a decreasing trend, whereas the south interior part showed an increasing trend. A significant increasing trend in rainfall was found during pre-monsoon seasons whereas the northeast monsoon (NEM) rainfall showed a decreasing trend. The REOF analysis also indicated an upward (downward) trend in SWM and annual over the northern (southern) Karnataka and a weakening trend in the NEM rainfall. Using the hierarchical clustering method, six homogeneous rainfall clusters were identified over Karnataka based on distribution and variability of rainfall. The spectral analysis over different clusters showed significant oscillations in the annual and SWM rainfall in the 1970s and recent decades except the Western Ghat region where oscillations were much weaker during recent decades. The pre-monsoon and NEM rainfall also showed strong variability with a periodicity of 2–4 years in recent decades. The findings of this study can have implications while designing water resource management strategies across various sectors in Karnataka.
Source: https://link.springer.com/article/10.1007/s12040-022-01810-7
Analysis of heat wave over different physiographical regions in India
by Rani Devi, Krushna Chandra Gouda and Smrutishree Lenka
Heat waves (HW) in the tropical and subtropical region are the deadliest throughout the world. This study represents the HW characteristics over the tropical country India mainly divided in three different landmasses, i.e. hilly, plains and coastal. This work presents the HW characteristic quantification based on the physiography of the regions in India assessed over a period of 70 years (1951–2020) using the Indian Meteorological Department (IMD) observed data. Mostly, the earlier studies are more focused on HW in the plains and coastal regions. HW in hilly region has been excluded by using single threshold for the whole Indian region, so based on the topographical features, three thresholds of daily maximum temperature (DMT), i.e. DMT > 40 °C (plains), DMT > 37 °C (coastal) and DMT > 30 °C (hilly), are being applied. The spatio-temporal analysis of HW shows its occurrence in hilly regions (J&K, Manipur, Mizoram and Tripura) since 1972 and maximum 10-day HW in the northern region. The coupled model intercomparison project phase (CMIP6) model output for 7 models has been assessed to quantify the performance in capturing the HW parameters compared to IMD observations. The ensemble mean of 2 CMIP6 models, i.e. EC Earth3 and MPI LR, has been used to project future changes in HW properties over India under the different emission scenarios, i.e. SSP126 and SSP 585. The key finding of this study shows that for year 2050 onwards, a sharp increase in HW days, HW events and HW duration (average and maximum) will increase in hilly, coastal and plain region. Under SSP 585, the southern part will likely get more new hotspots of HW in India, and there will be significantly more longer, intense and frequent HW occurrence as compared to SSP 126. The results show the need of improvement in understanding of HW at regional scale and especially in hilly region.
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