Trend analysis of rainfall is often carried out in water resources management to understand its distribution over a given region. The cumulative seasonal and annual rainfall derived from monthly datasets spanning 102 years (1901–2002) for 11 districts of the semi-arid Karnataka, India, was used for the trend analysis. The two-step homogeneous test approach was carried out on all the time series. Then, lag-1 autocorrelation was conducted only on homogeneous time series. Only 78.18 % of the total time series data were detected as homogeneous, and 95.35% of time series data were found to have insignificant autocorrelation. Then, the Innovative Trend Analysis (ITA) method was applied to 43 homogeneous rainfall time series, as well as to 41 time series using the MK and SR tests, and to two time series using the mMK test. The MK and SR tests detected a significant trend in 14.63% of the time series, while the ITA method was able to detect a trend in 93.02% of the total time series data. The MK and SR tests revealed significant trends in winter and post-monsoon season precipitation for two districts, but only for one district in the case of summer and annual rainfall. No trend was identified for monsoon season precipitation. The mMK test showed a positive trend for the post-monsoon season in a district, while the ITA method revealed significant trends for all seasons in most districts. The sub-trend analysis revealed trends that traditional methods were unable to detect.
The synergistic effect of climatic factors on malaria transmission: a predictive approach for northeastern states of India
by Nikhila Yaladanda, Rajasekhar Mopuri, Hariprasad Vavilala, Kantha Rao Bhimala, Krushna Chandra Gouda, Madhusudhan Rao Kadiri, Suryanarayana Murty Upadhyayula & Srinivasa Rao Mutheneni
Abstract
The northeast region of India is highlighted as the most vulnerable region for malaria. This study attempts to explore the epidemiological profile and quantify the climate-induced influence on malaria cases in the context of tropical states, taking Meghalaya and Tripura as study areas. Monthly malaria cases and meteorological data from 2011 to 2018 and 2013 to 2019 were collected from the states of Meghalaya and Tripura, respectively. The nonlinear associations between individual and synergistic effect of meteorological factors and malaria cases were assessed, and climate-based malaria prediction models were developed using the generalized additive model (GAM) with Gaussian distribution. During the study period, a total of 216,943 and 125,926 cases were recorded in Meghalaya and Tripura, respectively, and majority of the cases occurred due to the infection of Plasmodium falciparum in both the states. The temperature and relative humidity in Meghalaya and temperature, rainfall, relative humidity, and soil moisture in Tripura showed a significant nonlinear effect on malaria; moreover, the synergistic effects of temperature and relative humidity (SI=2.37, RERI=0.58, AP=0.29) and temperature and rainfall (SI=6.09, RERI=2.25, AP=0.61) were found to be the key determinants of malaria transmission in Meghalaya and Tripura, respectively. The developed climate-based malaria prediction models are able to predict the malaria cases accurately in both Meghalaya (RMSE: 0.0889; R2: 0.944) and Tripura (RMSE: 0.0451; R2: 0.884). The study found that not only the individual climatic factors can significantly increase the risk of malaria transmission but also the synergistic effects of climatic factors can drive the malaria transmission multifold. This reminds the policymakers to pay attention to the control of malaria in situations with high temperature and relative humidity and high temperature and rainfall in Meghalaya and Tripura, respectively.
Source: https://doi.org/10.1007/s11356-023-26672-4
Trends of seasonal and annual rainfall of semi-arid districts of Karnataka, India: application of innovative trend analysis approach
by KK Chowdari, Surajit Deb Barma, Nagaraj Bhat, R Girisha, K.C. Gouda & Amai Mahesha
Abstract:
Relationship of height and intensity of low-level jet stream with Indian summer monsoon rainfall
by Smrati Purwar, V. Rakesh, Ajay Bankar & G. N. Mohapatra
A strong equatorial flow at lower troposphere exists over the Indian Ocean plays a crucial role in modulating the Indian Summer Monsoon Rainfall (ISMR) referred as monsoon low-level jet (MLLJ). The variation in strength and height of MLLJ can provide an important lead in predicting the variations in ISMR. The variability of MLLJ is examined using the fifth-generation ECMWF (European Centre for Medium-Range Weather Forecasts) reanalysis ERA-5; National Centers for Environmental Prediction-Climate Forecast System Reanalysis (NCEP-CFSR)/Climate Forecast System, version 2 (CFSv2); the Modern-Era Retrospective Analysis for Research and Application, version-2 (MERRA-2); and radiosonde data during 40-year period (1979–2018). The results suggest that there is an increasing trend in MLLJ strength during July and September, but a decreasing trend is observed during August. The MLLJ height showed an increasing trend in all the data sets. Significant interannual oscillations in MLLJ strength and height are observed with a prominent periodicity of 2–3 years. The ISMR over Western Ghats region and central India showed strong positive correlation with the MLLJ strength as well as height except during August. It is noted that the influence of the MLLJ on rainfall over the Indian landmass is stronger during the onset and withdrawal phases of monsoon. The increasing trend in MLLJ height indicated the possibility of increase in rainfall over many regions in India especially Western Ghat and Central India.
Source: https://doi.org/10.1007/s00704-022-04301-3
Seismic hazard potential of Kachchh paleo-rift basin of Indian craton from seismic and geodetic strain rates
by Sapna Ghavri, Rajeev Kumar Yadav and Sridevi Jade
The Kachchh paleo-rift basin of western India which recently experienced Mw 7.6, 26th January 2001 Bhuj earthquake, is one of the most active and vulnerable intra-cratonic zones in the world categorized as seismic zone V, i.e. having potential to produce earthquakes of intensity IX or higher. We analysed the geodetic and seismic principal strain rates to reveal the seismic hazard potential of the Kachchh paleo-rift basin. The geodetic strain rates are calculated from the reported surface motion in the region using a modified least-square inversion scheme that utilizes distance and spatial coverage dependent weight factor on the uncertainty in the plate motion to get a reliable estimate of principal strain rates and their orientations at regular grid nodes. An optimal weighting factor yields a mean rate of compression of ~ − 16 ± 6 nano strain/yr towards north-northeast in the region. The seismic strain rates are estimated based on fault plane solutions of the significant past earthquakes (Mw ≥ 2.5) of the region using the Kostrov formulations. The seismic strain rate and stress inversion estimate indicate that the region released elastic strain at an average rate of ~ − 85 nano strain/yr towards north-south in the past 350 years. A composite analysis of the geodetic and seismic strain rates indicates 900–3000 years of recurrence interval of major (Mw 7.8–8) earthquakes in the region. Our analysis indicates a high rate of strain build-up on the reactivated major faults in the region that have the potential to generate devastating (Mw ≥6) earthquakes.
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