Monsoon Season Research Articles

ASSESSING RAINFALL PATTERNS AND TREND DISTRIBUTION IN THE KELANTAN RIVER BASIN, MALAYSIA AND KLANG RIVER BASIN, MALAYSIA

This study examined rainfall patterns and trends in the Kelantan and Klang River Basin in Malaysia over a ten-year period from 2010 to 2020. The analysis revealed that the Kelantan River Basin experienced an upward trend in rainfall during the Southwest Monsoon season, indicating a gradual increase in precipitation levels over the years. On the other hand, the Klang River Basin showed a relatively stable rainfall pattern without a significant trend observed. The study employed an independent t-test to compare the mean yearly rainfall between the two basins, with the findings showing no significant difference in overall precipitation levels (t(22) = -0.8, p = 0.07). However, the timing and duration of rainy seasons varied between the two basins. The Kelantan River Basin experienced a rainfall pattern that is aligned with the regular monsoon season. In contrast, the Klang River Basin displayed a notable gap in rainfall during a later month in the monsoon season. Moreover, the analysis considered the spatial variability of precipitation patterns within each basin. Specific stations in the Kelantan River Basin showed a positive trend in rainfall during the monsoon seasons (March, p = 0.013), whereas stations along the Klang River exhibited a declining trend (August, p = 0.119). These findings emphasize the influence of geographical locations, local climate conditions, and topographical features on rainfall distribution within the same country. In conclusion, this research highlights the need for further investigation into the factors driving these patterns, emphasizing the importance of effective water resource management and climate adaptation strategies in these basins to mitigate the impact of climate change.

Characterization of Begomovirus Isolates Causing YMD in soybean and Analyzing the Relation with Early Reported Strains of Begomovirus from New Delhi Region

This work was focused on the exact characterization of begomovirus correlated with yellow mosaic disease (YMD) in soybean during the monsoon season. This information helped to understand the time-bound status of the viral group. Augmented design and was carried out at the research field. Starting material source for pure viral DNA Initial source material consisted of soybean plants (JS335) with a prominent yellow mosaic symptom that were grown in sick plots under controlled conditions in order to obtain a DNA samples that also contained the genomes of begomovirus. The experiment used an augmented design and was carried out at the research field in New Delhi during the 2018 kharif season. In each replication, the susceptible cultivar (JS335) genotypes were planted for the establishment of a sick soybean plot for YMD development purposes. A limited number of MYMIV DNA-A sequences was used to create the phylogenetic tree. Cluster W was used to align the sequences, with the default gap penalty values of gap opening 10 and extension 0.2. A neighbor-joining tree was built using MEGA 11.0, a p-distance model, and pairwise gap deletion. The viral genome was amplified and sequenced. The sequence analysis revealed that the viral genome is 2747 nucleotides long, similar to monopartite begomoviruses, and has seven conserved ORFs. Further nucleotide (nts) sequence comparisons revealed that the genome had the maximum sequence identity of 99%, which is identical to the previously reported sequence. The DNA-A of MYMIV (GenBank accession number: OQ473638) was made from 2747 nucleotides that were 99% the same as the sequence that had already been reported. Previously, that Mungbean yellow mosaic virus (MYMV) and Mungbean yellow mosaic India virus (MYMIV) are the primary begomoviruses causing yellow mosaic disease (YMD) in soybeans in India. This study also demonstrated that our isolate of MYMIV was more similar to the one that was already recognized to be Mu2 New Delhi isolate. This information would be useful in more detailed screening processes under controlled condition and evaluation of soybean genotypes as part of variety development for sustainable cultivation of soybean.

Diversity and abundance of butterflies in urban areas of Bankura district, Bankura, West Bengal, India

ObjectiveDuring the present study, the biodiversity profile of butterflies was assessed on the Bankura Christian College campus, a large area with a huge amount of trees, bushes, rain forest, and undisturbed areas within the urban areas of Bankura district of West Bengal, India.MethodologyPresent study was carried out in Bankura Christian College campus, a relatively undisturbed area in Bankura town, of West Bengal, India. The findings presented here were based on seasonal diversity of Butterflies in the college campus. The species dominance of Butterflies was numerically measured on the basis of density, relative density, abundance, relative abundance, frequency, and relative frequency. To analyze the result, single factor ANOVA was performed in between five different seasons. Seasonal variation was analysed using individual rarefaction analysis. The Jaccard similarity index was also used to conduct hierarchical classical clustering.ResultA total of 47 genera and 59 species of butterflies that belongs to five families were recorded. The findings of the present study indicated a high abundance of the butterflies that belongs to Nymphalidae family comprising 13 Genera and 22 species.ConclusionIn the Monsoon season, the highest number of butterflies were recorded in comparison to other seasons. Different types of ecological indices were also calculated from observed species diversity of butterflies. Individual rarefaction analysis revealed that the probability of finding the greatest specimen was in monsoon season. Hierarchical cluster analysis among seasons based on the Jaccard Similarity index using Paired group (UPGMA) shows higher similarity of butterflies in between monsoon and Fall season.

Spatiotemporal discrepancies and risk assessment of toxic heavy metals in surface water of Shitalakhya River around Narayanganj port in Bangladesh

The urban rivers of developing countries like Bangladesh have been severely affected by toxic heavy metal pollution, posing serious ecological and human health risks. This study aimed to investigate the concentrations, spatiotemporal discrepancies, and associated risks of five alarming toxic metals (Pb, Cd, Cr, Cu and Mn) in the surface water of urban Shitalakhya River around Narayanganj port, one of the biggest and most important river ports in Bangladesh. Water samples were collected for three prevailing seasons i.e., pre-monsoon, monsoon, and post-monsoon from five selected sites. Physicochemical properties (color, odor, temperature, DO, pH, EC and TDS) of river water were also assessed, while heavy metal pollution index (HPI), heavy metal evaluation index (HEI) and degree of contamination (CD) were calculated to evaluate the risks associated with toxic metal pollution in river water. The findings revealed that several physicochemical parameters, especially DO, EC and TDS, were not within the standards. The hierarchy of mean heavy metal concentrations in Shitalakhya River water was found as Mn>Cr>Cu>Cd>Pb during pre-monsoon, Mn>Cu>Cr>Cd>Pb during monsoon, and Mn>Cr>Cu>Pb>Cd during post-monsoon season. The metal concentrations were found to be higher in pre-monsoon and post-monsoon seasons, whereas the concentrations of all the heavy metals excluding Mn were within the standards recommended for domestic use, surface water, fisheries and irrigation purposes. The comparative analysis exhibited that the water quality of Shitalakhya River is deteriorating day by day at an alarming rate. HPI showed a critical pollution index value (drinking) for all three seasons, whereas HEI revealed low heavy metal contamination for all sampling stations. The values of CD indicated a high level of contamination in pre-monsoon and post-monsoon but monsoon season. The results confirmed the spatiotemporal discrepancies in toxic metal concentrations and associated ecological and human health risks, possibly resulting from the hydrological and anthropogenic interventions not only associated with port activities. Hence, urgent collective effort and proper monitoring are of utmost importance to safeguard the public health and this urban riverine ecosystem. Int. J. Agril. Res. Innov. Tech. 14(2): 74-84, December 2024

Fluoride and nitrate contamination in groundwater of Naini Industrial Area, Uttar Pradesh: assessing non-carcinogenic human health risk

Groundwater is the main source of drinking water globally; however, its quality has been deteriorated due to various geogenic and anthropogenic activities. The groundwater quality of Naini Industrial Area, Prayagraj was studied seasonally to evaluate the fluoride and nitrate contamination pertaining to human health risk assessment. The samples were collected from 60 locations in the pre- monsoon, monsoon, and post-monsoon season. The fluoride and nitrate were assessed with the help of Ion chromatography. The NO3– concentration exceeded the Indian drinking water quality standards in 27% of the groundwater samples. The NO₃⁻ contamination is predominantly associated with agricultural practices, while F⁻ can be linked to natural geological sources. The non-carcinogenic human health risk assessment was quantified by calculating the Hazard Quotient (HQ) and Hazard Index (HI) were calculated as per USEPA methodology for male, female and child population. The findings indicate that the child population is particularly susceptible to health risks associated with the ingestion of F– and NO₃⁻ through the drinking water pathway. Across all the sampled sites, the Hazard Index (HI) values varied from 0.10 to 12.3 for males, 0.09 to 10.6 for females, and 0.16 to 19.7 for children suggesting substantial risk to the local populace at more than half of the locations which is largely related to nitrate contamination. Thus, the study suggests that groundwater at many locations is unsuitable for drinking without treatment pertaining to the probable health risk they pose to consumers advocating upgraded water management plan for the residents.

Limited degradability of dissolved organic carbon, nitrogen, and phosphorus during contrasting seasons in a tropical coastal environment

AbstractThe biogeochemistry of dissolved organic matter (DOM) is poorly understood in tropical coastal waters. Here, we quantified the biological and photochemical lability of dissolved organic carbon, nitrogen, and phosphorus, in the tropical coastal waters of Singapore. We conducted experiments during the inter‐monsoon, the mid‐southwest monsoon, and the late southwest monsoon seasons, which span the greatest range of biogeochemical conditions found in the area. The DOM lability was quantified as concentration changes during 90‐d biodegradation and 7‐d photoreactor incubations. Overall, DOM showed low lability, even though dissolved organic nitrogen and dissolved organic phosphorus accounted for most of the dissolved nitrogen and phosphorus. In the biodegradation experiments, only 5–15% of dissolved organic carbon, 0–7% of dissolved organic nitrogen, and 8–21% of dissolved organic phosphorus were degraded. The addition of labile dissolved organic carbon, intended to test priming effects and to ensure the microbes were not carbon‐limited, had no measurable impact on the results. During our photochemical experiments only 2–10% of the dissolved organic carbon were degraded, while neither dissolved organic nitrogen nor dissolved organic phosphorus showed consistent photochemical losses. The DOM optical properties (absorbance and fluorescence spectra) showed limited or no changes during the biodegradation experiments but larger declines in the photochemical experiments. Overall, the biodegradation of DOM was highest during the inter‐monsoon, when autochthonous DOM was most dominant, while photolability was greater during the terrestrial DOM‐rich southwest monsoon. Our results illustrate that in some tropical coastal environments, DOM can be fairly resistant to biological and photochemical degradation, and thus does not represent a large stock of potentially available nutrients.

An investigation into the influence of climate extreme on groundwater regimes and human health in the Periyar Basin: a fast growing urban centre in India

ABSTRACT A total of 212 groundwater samples were collected during North East Monsoon (NEM), South West Monsoon (SWM), Pre-Monsoon (PREM), and Post-Monsoon (POM) seasons of 2020–2021 from the Periyar River Basin, draining the south western flanks of Western Ghats. The analytical results revealed the order of abundance of cations as Ca2+ > Na+ > Mg2+ > K+ and anions in the order of HCO3− > Cl− > SO42− > NO3− for all seasons. The major hydrochemical facies identified were CaHCO3 and mixed Ca–Mg–Cl in all the seasons with rock–water interaction as the key process regulating water chemistry. Ionic ratios of Ca2+ + Mg2+/Na+ + K+ and Ca2+/Mg2+ suggested significant effect of silicate minerals and other sources. The Water Quality Index (WQI) shows that the majority of the samples, namely, 98% in NEM, 86% in POM, 82% in PREM, and 95% in MON, fall in the categories ranging from excellent to good for drinking purposes. Furthermore, the health risk assessment based on carcinogenic and non-carcinogenic risk of the United States Environmental Protection Agency (US EPA) during monsoon and non-monsoon seasons for adults and children revealed the potential risk posed by Pb via oral exposure in the study area suggesting children are more susceptible to the damaging effects than adults.

Evaluation of spatio-temporal water quality status of Jeera river, Odisha, India

Jeera River of Bargarh District, Odisha faces serious deterioration due to massive human intervention. It is particularly susceptible to degradation because it receives industrial and waste water emissions from surrounding organizations and municipal bodies. The river was formerly a flourishing tributary of the massive Mahanadi River that possessed excellent navigability, an array of aquatic ecosystems, and a well-established basin with an expanding agricultural sector. The current condition of the Jeera River is deplorable, leaving behind only minimal economic and ecological values. The study emphasizes analyzing the seasonal variation of the water quality rating of Jeera River in terms of the Water Quality Index (WQI). WAWQI (Weighed Arithmetic Water Quality Index) values show that almost all sampling sites have poor or unsuitable quality. During the monsoon season, the water quality deteriorated the most, with an average WQI score of 516.430 compared to pre- and post-monsoon with average WQI values of 154.558 and 276.014 respectively. CCMEWQI (Canadian Council of Ministers of Environment Water Quality Index) values indicate that water quality ranges from marginal, and poor to fair. This study concludes that out of the eight sampling sites, station 5 (Dumerpali) is observed to be the most polluted site. Many water quality parameters including iron, turbidity, nitrate, phosphate, E. coli, and Total coliform are found to exceed the permissible limits prescribed by WHO and BIS. Reducing sewage outflow, blocking direct stormwater discharge, and avoiding continuous solid garbage disposal by neighbouring populations are ways to improve river water quality.Graphical abstract

Changes in physical characteristics of extreme rainfall events during the Indian summer monsoon based on downscaled and bias-corrected CMIP6 models

We identified a set of bias-corrected and downscaled Coupled Model Intercomparison Project 6 (CMIP6) models capable of accurately simulating the observed mean Indian summer monsoon rainfall, extreme rain events (EREs) and their respective interannual variability. The future changes in EREs projected by these models for four climate change scenarios—Shared Socioeconomic Pathways (SSPs), 1–2.6, 2–4.5, 3–7.0 and 5–8.5 were estimated using percentile thresholds. Under the highest emission scenario, SSP5-8.5, at the end of the century, summer monsoon season total rainfall exhibits a 1.1-fold increase, while extreme rainfall intensity demonstrates a more substantial rise of 1.3-fold. The spatial variability of seasonal total rainfall increases by 1.2-fold compared to the baseline period, with an even more pronounced 2.1-fold increase in the spatial variability of extreme rainfall (R99p). These findings underscore the significant amplification of rainfall variability and intensity under the most extreme climate scenario. The intensity and frequency of very extreme rainfall events (vEREs) were also found to increase, though with a substantial inter-model spread. Under SSP5-8.5, extreme rainfall intensity scales with temperature at 1.5 to 2 times the Clausius-Clapeyron (CC) rate. While mid-century scenarios show minimal variations in extreme rainfall intensity from the historical period, end-century projections reveal significant shifts; an increase in north India and a decrease in south India due to cloud-induced cooling effects.

Seasonal trends and sources of dicarboxylic acids in fine aerosol over the Brahmaputra valley, North-East India.

The atmospheric dicarboxylic acids (DCAs) have a significant impact on the climate and indirectly affect human health, making them important organic substances. PM2.5 bound DCAs were analysed for Jorhat, India, 2019. In addition to the temporal variability, seasonal variation throughout the year and the impact of varying meteorological factors on DCAs concentration have also been studied. It has been noted that precipitation and ambient air temperature considerably impact DCA concentrations, which affect the type of source contribution of DCAs. The average concentration of all DCAs was 107.04 ± 97.54ng/m3, with a higher prevalence of high molecular weight DCAs than low molecular weight DCAs. Correlation analysis, water-soluble inorganic species, EC-OC ratio and diagnostic ratios of DCAs were employed to determine whether DCAs originate from direct emission and/or from photochemical oxidation of biogenic or anthropogenic precursors. DCAs concentration varied seasonally in decreasing order, with the maximum in the monsoon (144.24 ± 101.62ng/m3) followed by winter (138.36 ± 95.11ng/m3), post-monsoon (80.72 ± 37.27ng/m3), and summer (36.64 ± 34.52ng/m3). Air mass back trajectory and concentration-weighted trajectory (CWT) were used to show both short and long-range air mass transport with moderate to high DCAs contribution regions. Photochemical oxidation of diacids precursors predominates during the monsoon season, whereas in winter, direct anthropogenic emissions account for the majority of DCAs.

Decadal Trend Assessment and Future Projections of Artificial Light Pollution in Ahmedabad, Surat, and Vadodara City of Gujarat, India

The study focuses on a detailed assessment of artificial light pollution in three major cities of Gujarat: Ahmedabad, Surat, and Vadodara for year 2014 to 2023. Night light pollution, resulting from the excessive directed use of artificial lighting, is a pressing environmental issue with far-reaching implications. The findings of this study are expected to offer valuable insights into the extent and nature of light pollution in these cities. The research includes the calculation of average night light radiation for urban areas. By employing the Mann Kendall and Sen’s Slope, this research also aims to identify trends and patterns in night light pollution over the study period. Moreover, by employing the ARIMA and SARIMA model, this research also aims to identify trends and patterns as well as forecasting in night light pollution for 2024. Vadodara, Ahmedabad, and Surat exhibit distinct seasonal patterns in night light radiance, characterized by peaks during winter and troughs during the monsoon season, influenced by local environmental and climatic factors. From 2014 to 2023, all three cities show a consistent upward trend in radiance, with significant seasonal fluctuations observed from July to September due to monsoonal cloud cover. Surat, in particular, maintains relatively stable radiance levels but experiences reduced trends in July and September. These findings underscore the interplay between seasonal variability and long-term growth, highlighting the severity of light pollution in urban areas and emphasizing the need for data-driven interventions to inform urban planning and resource management strategies.

Understanding the Impact of Heavy Metals on the Environment and Human Life in a Non-Perennial River Basin South India – A Multi-Index Geochemical Analysis

In western Tamil Nadu, the Noyyal River basin is the primary water source for agriculture, industry, and consumption. The present research aims to evaluate the quality of surface water and the implications of heavy metal contamination on the surface waters within the Noyyal River basin. The major chemistry of the surface water exhibits the CaMgHCO3 type with dominant silicate weathering. The sodium absorption ratio and sodium percentage show the acceptability of water for irrigation purposes. On the other hand, water quality is unsuitable for human consumption during both seasons. The heavy metal pollution index revealed that 32% of monsoons and 40% of summer locations have a higher index (>100). Hazard index and Probability cancer risk show a higher risk of metal pollution, especially chromium in children than in adults and newborns. Principal component and cluster analysis shows that metals entering the river system mainly through industrial wastewater discharge during summer and monsoon seasons experience significant weathering through rainfall runoff. In essence, the study shows industrial activity plays a major role in increased surface water pollution in the study region with metals causing a major impact on the environment and human health, especially on children compared to adults.

Possible Mechanisms behind Dominant Modes of Seasonal Cycle of Rainfall over India

Abstract The South Asian summer monsoon that occurs over four months from near summer solstice (June) to near Autumnal equinox (September) evolves within the season due to interaction with other climate components. Since most climate patterns are seasonally phase-locked, their interaction and feedback with monsoon should also be season-dependent. Here, using rain-gauge-based precipitation over India for seventy-four years, we show that the onset phase of the monsoon (June) is uncorrelated with rest of the season (July to September). Propagation of Madden Julian Oscillation (MJO) over the Indian Ocean triggers northward-propagation of precipitable water that plays a key role during the onset phase. MJO appears over the Western equatorial Indian Ocean both during the early and late Central Indian onset years. Normal and slow MJO phase propagation during early and late onset years respectively give rise to interannual variations in June rainfall. After onset, till the end of the monsoon season, interannual variability of the dominant seasonal mode of precipitation is regulated by the phase of the El Nino Southern Oscillation (ENSO) through anomalous moisture convergence. We show that, in June, ENSO doesn’t play key role because of the opposing impact on wind and moisture. However, from July to September, ENSO perturbs wind and moisture in a way that gives rise to positive feedback between monsoon, ENSO, and large-scale circulation. Such feedback of monsoon with ENSO results in a coherent impact of ENSO on monsoon precipitation in July-September. Our results suggest that dominant mechanisms for interannual variations of Indian monsoon rainfall in June and the rest of the season are different.

Deciphering the Relationship Between Moisture Flux and Monsoon Extreme Rainfall Over the West Coast of India

ABSTRACTThe west coast of India has recently been experiencing torrential monsoon rains, a trend that studies indicate is likely to continue under future warming scenarios. This study investigates the link between moisture flux and extreme rainfall over the west coast, using observational and reanalysis datasets for the monsoon seasons (June to September) from 1990 to 2023. The analysis shows that, over the Indian subcontinent, rainfall along the west coast is primarily influenced by large‐scale moisture flux from the Arabian Sea. By decomposing the vertically integrated moisture flux into dynamic and thermodynamic components, this study observes that the thermodynamic component of moisture flux exhibits an increasing trend over the southwest coast, while this increasing trend is more prominent for the dynamic component over the northwest coast. Extreme rainfall over the southwest coast is increasing at a rate of 0.23 mm per season, attributed primarily to the increase in the thermodynamic component of moisture flux. It is observed that the rate of sea surface temperature (SST) increase over the Arabian Sea is faster than over the Bay of Bengal, with the average SST over the southeast Arabian Sea exceeding 28°C in recent years. Observations indicate that warming over the southeast Arabian Sea is strongly coupled with moisture accumulation observed over the southwest coast. This study provides strong evidence of a link between moisture transport, extreme rainfall and SST, identifying the southwest coast as a region vulnerable to climate change. Over the northwest coast, the incidence of extreme rainfall is associated with the strengthening of dynamic processes, and the mean monsoon rainfall in this region is increasing in alignment with the rising dynamic component of moisture flux.

Assessment of geochemistry and irrigation suitability of the River Ganga, Varanasi, India: PCA reduction for water quality index and health risk evaluation.

Surface water chemistry of the River Ganga at Varanasi was analyzed at 10 locations over 3years (2019-2021) across pre-monsoon, monsoon, and post-monsoon seasons. The study aimed to assess water parameters using principal component analysis (PCA), calculate the water quality index (WQI), determine processes governing water chemistry, evaluate irrigation suitability, and estimate non-carcinogenic health risks. The physical parameters measured included pH (8.12 ± 0.37, 8.17 ± 0.30, 7.80 ± 0.30), electrical conductivity (EC) (857.58 ± 163.17, 667.17 ± 162.15, 754.46 ± 179.32 µS/cm), total dissolved solid (TDS) (428.98 ± 81.74, 334.99 ± 80.75, 376.14 ± 88.91mg/L), and total coliform (6201.96 ± 6914.17, 4363.76 ± 3379.98, 6176.53 ± 7080.62 MPN/100mL) for pre-monsoon, monsoon, and post-monsoon seasons, respectively. WQI, based on 9 major parameters via PCA reduction, indicated poor water quality (53-74) across sites and seasons, except for S1, which was rated as good during the monsoon. The major ion concentrations in the samples followed the trend: (bicarbonate) HCO3⁻ (360.20mg/L) > (chloride) Cl⁻ (59.80mg/L) > (sodium) Na⁺ (53.10mg/L) > (calcium) Ca2⁺ (44.61mg/L) > (sulphate) SO₄2⁻ (43.81mg/L) > (magnesium) Mg2⁺ (24.50mg/L) > (potassium) K⁺ (5.20mg/L) > (phosphate) PO₄3⁻ (2.41mg/L) > (fluoride) F⁻ (0.52mg/L), indicating alkaline water. The Piper diagram is dominated by Ca-Mg-HCO3 and mixed SO4-Cl hydrochemical facies, while the Gibbs plot suggested rock-water interaction as the key driver of ion chemistry. Irrigation indices [sodium percentage (Na%); sodium absorption ratio (SAR); Kelly index (Ki); permeability index (PI); magnesium hazard (MH)] indicated suitability for irrigation. Non-carcinogenic risk assessment showed children were more sensitive to fluoride and chloride ingestion, while teenagers were more affected through dermal exposure.

AN OVERVIEW OF THUNDERSTORMS OVER BANGLADESH

An attempt has been made to find out the monthly, seasonal and annual variability, and trend of thunderstorms (TSs) over Bangladesh, specialty the pre-monsoon TSs which are locally known as Nor’westers or Kal-baishakhis. TSs data for the period of 1981-2020, collected from Bangladesh Meteorological Department (BMD), have been analyzed and found that during this period average annual TS days were 66 having maximum in May and minimum in December. Seasonal distribution of TSs shows that highest and lowest number of TSs occurred in the monsoon season and winter season respectively but the pre-monsoon TSs are severe in nature. From the seasonal time series of TSs, it is seen that all the three seasons have increasing trend and the winter season shows decreasing trend. Station-wise distribution of annual average TS days reveals that Sylhet and Srimangal experience the highest number of TS days (136.28 and 116.92 days respectively), while Teknaf experiences the lowest number of TS days (26.15 days) during the study period (1981-2020). Spatial distribution of average annual and seasonal TS days shows that, the North-eastern part of the country is the most TS prone area, followed by northern, mid-western and north-western parts of the country. South-eastern part of the country experienced comparatively lower number of annual average TSs days. Most of the Nor’westers directed from north-west and occurred between 1400- 1600 U.T.C. and least number of Nor’westers occurred between 0400-0600 U.T.C. As the number of observatories of Bangladesh Meteorological Department (BMD) is less considering its area, there is possibilities of unnoticed thunderstorms over Bangladesh. Bangladesh Journal of Physics, Vol. 29, Issue 1, pp. 1 – 11, June 2022

A preliminary checklist of butterflies (Lepidoptera: Rhopalocera) of Dhorpatan Valley, Dhorpatan Hunting Reserve, Nepal

Butterfly species were studied in the Dhorpatan Valley, situated in the western region of Nepal, during the pre-monsoon and monsoon seasons of 2021 and 2022. This preliminary study documented forty-three species of butterflies from five families Lycaenidae, Pieridae, Nymphalidae, Papilionidae, and Hesperiidae. A purposive sampling method was applied to locate various butterfly species across elevations ranging 2,846–4,000 m. This study recorded Polyommatus nepalensis, an endemic species and Polyommatus stoliczkanus, a rare species. No reports have been made of this endemic butterfly from eastern region of Nepal.

Bacterial accumulation in edible bivalve, Villorita cyprinoides of Ashtamudi estuarine wetland, a Ramsar site in Kerala State, India

The Ashtamudi Lake in Kerala, recognized under the Ramsar Convention, showcases rich biodiversity but faces pollution threats from human activities. Of particular concern is the potential bacterial contamination of inland fishery resources due to these anthropogenic influences. The present study, seasonally analysed the total heterotrophic bacteria (THB) and E. coli in water, sediment and Villorita cyprinoides respectively using pour plate and MPN methods. Water temperature, pH, salinity, DO and BOD of water samples were also estimated. The results showed the presence of THB in water was more in monsoon season and in sediments and the organism in premonsoon season. However, E. coli counts were more in all the media in monsoon season. The E. coli count slightly exceeded the standards set by European Union for Class A waters. In general, THB and MPN E. coli values were the highest in the oyster. Pearson’s correlation showed highly significant positive correlation between THB and E. coli in all the phases. pH and salinity showed highly significant positive correlation with BAF and highly significant negative correlation with DO and rainfall. Conversely, rainfall and BOD showed significant negative correlation with BAF. The present study indicates that the density of E. coli in shellfish at some locations exceeds the standard limit set by Indian Standards.

Understanding the atmospheric dynamics over high-altitude glaciated regions in the central Himalaya using high-resolution numerical simulations

Abstract The atmospheric dynamics over the higher Himalaya play a crucial role in controlling glacier variability and ultimately regulating downstream water availability. However, the paucity of station observations makes exploring these atmospheric dynamics challenging. To address these issues, we employed a high-resolution configuration of the Weather Research and Forecasting (WRF) model with a 2-km convection-permitting grid scale to simulate atmospheric variables over the central Himalaya. We analyze the atmospheric variables over three high-altitude glaciated regions, namely the Langtang, Rolwaling, and Everest regions, in the central Himalaya. The model reproduces precipitation and temperature seasonality well, with the model precipitation displaying better agreement with the station data and outperforming the satellite observations. Furthermore, we investigate the spatial variability of precipitation during the monsoon and winter seasons and explore the associated dynamics by computing the vertically integrated moisture transport (VIMT) and vertically integrated moisture flux divergence (VIMFD). The VIMT and VIMFD analysis reveal that the valleys that meridionally dissect the Himalaya transport the moisture from the Indo-Gangetic plains to the higher Himalaya, and the sharp rise in elevation results in moisture convergence and precipitation, with the results that the ridges and windward slopes accumulate more precipitation than the leeward slopes and valleys. The orographic effect on moisture convergence, cloud formation, and precipitation consequently controls the glacier energy balance. During the monsoon season, the enhancement of net radiation by thick monsoon cloud cover, coupled with added latent heat and reduced albedo from the dominant liquid precipitation below 5,000 m amsl, increases the melt energy, promoting glacier melt.

Evaluation of Rainfall Variability Over Major River Basins of India Using Multi Temporal Satellite Data Products

ABSTRACTHigh resolution remotely sensed rainfall data is indispensable to accurately monitor rainfall variability at a river basin scale under climate change. The aim of the study is to assess the change in rainfall climatology and determine the performance of three GPM rainfall products (IMERG Final_Run, GSMaP_Gauge and recently developed GSMaP_ISRO) against in situ observation over major Indian River basins for the monsoon season rainfall during 2000–2020. The analysis provides valuable insights into the issues in the rainfall products and their performance under varying rainfall intensity (low, moderate and heavy) and orography. Results indicate that mean monsoon rainfall is better represented in GSMaP_ISRO than IMERG Final_Run and GSMaP_Gauge estimates. GSMaP_ISRO outperformed IMERG Final_Run and GSMaP_Gauge with smaller root‐mean‐square error and higher correlation coefficient. It was observed that the performance of GPM rainfall is influenced by rainfall intensity and terrain height of basins. In particular, for high rainfall occurrence, the Brahmaputra and Barak basins in northeast India exhibited large uncertainties in IMERG Final_Run and GSMaP_Gauge products. The statistical evaluation of different rainfall scores (POD, FAR and CSI) suggested that the GSMaP_ISRO rainfall has significant skill over Indian river basins. A significant improvement is observed over Brahmaputra (RMSD = 34.46, CC = 0.92, FAR = 0.26), Barak and others (RMSD = 65.75, CC = 0.95, FAR = 0.29) and Cauvery basin (RMSD = 23.1, CC = 0.8, FAR = 0.15) for GSMaP_ISRO estimates. These findings provide valuable information on the accuracy of GPM rainfall necessary for hydro‐meteorological applications.