Gangetic West Bengal Research Articles

A detrended fluctuation analysis to examine the pollutant pattern over Gangetic West Bengal of India

A detrended fluctuation analysis to examine the pollutant pattern over Gangetic West Bengal of India

On the identification of seasonal trends, dependency and driving forces of precipitation and vertically integrated vapour transport over Northeast India

AbstractThe vertically integrated horizontal vapour transport (IVT) accompanied by westerlies and southwesterlies mainly contributes as a distant source of moisture to the seasonal precipitation (PR). The moisture transport and PR patterns across the eastern Himalayas (Sikkim, northern Sub‐Himalayan West Bengal and Arunachal Pradesh) are strongly modulated by the orographic setup, local land‐atmospheric factors and teleconnection with climate indices of the Indian and Pacific oceans. This study elaborates on the changing patterns of PR and IVT, changes in IVT contribution to the seasonal PR under the nonstationary framework and evaluates the nonlinear dependency on local and distant drivers with piecewise regression model. Asymmetries in significant seasonal trends are conspicuous due to multi‐altitude interactions. Strong declining trend over Assam and Arunachal Pradesh is evident for PR with concurrent rising trend over the Meghalaya plateau. The IVT signals show a significant decline in post‐monsoon (October and November) and winter (December to February) across Assam Plain. The increase in mean IVT contributes significantly to seasonal PR. Significant decline in the contribution of heavy IVT to winter PR is observed over Manipur, Mizoram, Tripura and part of Assam. Surface 2 m temperature and net thermal radiation exhibit contrasting influence on seasonal PR. IVT shows mainly positive association with surface 2 m dew point temperature and latent heat flux across the eastern Himalayas. NINO3.4 index exhibits strong negative influence on post‐monsoon PR. The Pacific Decadal Oscillation is strongly associated with summer (March to May) PR. Monsoon (June to September) IVT is negatively influenced by the Pacific Decadal Oscillation over the Sub‐Himalayan West Bengal, Gangetic West Bengal, Bihar and Jharkhand. The Southern Oscillation Index is negatively linked with summer IVT. The combination of local driving forces mainly controls the seasonal PR and IVT across all seasons. Besides, distant drivers are prominent in monsoon and post‐monsoon. This study reveals insights into recent changes of PR and IVT, their contribution to seasonal water resources in the eastern Himalayas and the controlling strength of local land‐atmosphere feedback mechanism and distant land‐ocean coupling drivers under nonstationary climate.

Assessment of the Suitability of Extractants for Predicting Plant Available Arsenic in Some Tropical Rice Growing Inceptisols of Eastern India

ABSTRACT The complex behavior of arsenic (As) in soil in conjunction to crop mediated transfer through the food chain necessitates a thorough evaluation of its phyto-availability. In this pretext, the present experiment has been conducted to determine the best chemical extractant for plant available As under the As-prone, rice-dominant agro-ecosystems of Gangetic West Bengal, India. Based on the tube-well arsenic data (JPOA, UNICEF), surface soil samples from high, medium, low and uncontaminated As sites have been collected. A pot study with rice cv. IR-36, exposed to varying levels of As (0, 0.1, 0.2, 0.3 and 0.4 mg L−1) was conducted. Ten chemical extractants were used in this study. The As extraction pattern followed the pattern of (HCl+H2SO4)>; (NH4-oxalate+Ascorbic acid)>; (Malic+Citric)> NaOH> KH2PO4> NaHCO3>; (H2O2+HNO3)> NH4F> NH4Cl> NH4OAc. On the 85th day after sowing, the rice plants were harvested keeping in mind that the maximum uptakes of heavy metals like As occurs during the peak vegetative growth (panicle initiation) stage. The soil As correlated with rice dry matter As accumulation as: NH4-oxalate+ascorbic acid (r = 0.729**)> NH4Cl (r = 0.698**)> H2O2+HNO3 (r = 0.697**)> NH4F (r = 0.693**)>Malic+Citric (r = 0.666**)> KH2PO4 (r = 0.615**)> HCl+H2SO4 (r = 0.608**)> NaOH (r = 0.589**)> NaHCO3 (r = 0.571**)> NH4OAc (r = 0.533*). Statistical analyses through correlation sum and stepwise multiple regression modeling revealed that NH4-oxalate+ascorbic acid had the best relationship with all other extractants, As fractions and soil physicochemical characters and therefore emerged as the best suited extractant of As for the wide-scale experimental locations under rice cultivation system.

Unraveling the dynamics of climate: empirical evidence from the Indian state of West Bengal

Abstract Understanding climate variability and trends is crucial for managing a host of sectors. Everything from water availability to agricultural productivity is affected by variability and trends in temperature, rainfall, evapotranspiration, and solar radiation. Nevertheless, their dynamics have seldom been explored together, especially in India. To address this gap, the present study investigates the variability, trend, and magnitude of those parameters individually and concurrently using fractal dimension and non-parametric statistics over the Indian state of West Bengal from 1951 to 2020. The results show a south–north gradient in overall climate variability. The Gangetic West Bengal (GWB) is experiencing higher variability, along with a rising minimum temperature (≥0.008 °C year−1) and declining rainfall (≥− 1 mm year−1). Though the Sub-Himalayan West Bengal as a whole shows less variability, its foothills reveal modest variation coupled with increasing maximum temperature (≥0.005 °C year−1), reference evapotranspiration (≥0.4 mm year−1), and decreasing rainfall in the post-monsoon and winter seasons. Based on the results, we identified the western GWB, the Sundarbans, and the sub-Himalayan foothills as the most vulnerable areas and recommended proactive crop and water management strategies. Finally, we underline the need to analyze climate dynamics holistically to manage climate-sensitive sectors efficiently and sustainably.

Five new Indian species of the genus Dasyhelea Kieffer (Diptera, Ceratopogonidae) with a key to the adult males

Five new species of biting midges, Dasyhelea (Dasyhelea) incisurasp. nov., D. (D.) quasifulcillatasp. nov., D. (D.) trigonasp. nov., D. (Sebessia) falxasp. nov. and D. (S.) foliasp. nov. are described and illustrated based on adult males. The new species are compared and contrasted to their congeners; important morphological characters are displayed. All specimens were collected from the Deltaic Proper of Gangetic West Bengal, India. An illustrated key to the adult males of the subgenera Dasyhelea s.str. and Sebessia from India is presented. Short accounts on ecological notes of the midges are also provided.

Future changes in monsoon extreme climate indices over the Sikkim Himalayas and West Bengal

Utilizing an ensemble of regional climate models (RCMs) from Coordinated Regional Climate Downscaling Experiment (CORDEX) South Asia, projected changes in mean and extreme climate indices are analysed for future period (SCEN; 2021–2060). The parametric transformation bias correction technique is applied to enhance the model agreement in calibration period (1961–2005) and to produce reliable results for evaluation period. The observed pattern of temperature and precipitation indices is illustrated for control period (CTRL; 1961–2005), which exhibits high spatial variability with the altitudinal differences, especially over the Himalayas. Strong meridional moisture flow from the Bay of Bengal contributes higher, heavier and more intense precipitation events over the Sikkim Himalayas and northern Sub-Himalayan West Bengal (SWB). Despite spatial difference in the occurrences of return value for 5-, 10- and 50-year levels, some indices show close similarity between the Sikkim Himalayas and Gangetic West Bengal (GWB). The projected uncertainties under the RCPs remain very high for extreme temperatures over the Himalayas. Change in minimum temperature is largely significant. Conversely, maximum temperature shows insignificant change. Diurnal temperature range shows an expected decline for projected scenarios. Lower atmospheric easterlies towards east-central India enhance future moisture transport, which don’t eventually bring positive change for precipitation amount. Instead, the Sikkim Himalayas and the Eastern Ghats exhibit expected rise in higher, heavier and intense precipitation events. Consecutive dry days exhibit significant future rise over the plain and lower plateaus, which show significant decline over the mountains. The topographic forcings to the convective mechanism as well as model sensitivity evidently control the spatial pattern and occurrences of extreme events. Future rise in moisture level is more conspicuous under RCP8.5 along with the significant changes in extreme climate indices.

Impact of prevailing atmospheric conditions on diurnal variability of the pre-monsoon rainfall over a tropical location, Kolkata

The annual rainfall amount over Gangetic West Bengal is predominantly determined by monsoon (June to September) and pre-monsoon (March to May) rain events. Consequently, such seasonal precipitation is directly linked to the socio-economic advancement of the area. In this paper, some characteristics of pre-monsoon rainfall over a tropical urban location, Kolkata have been explored utilizing ground-based observations. Pre-monsoon rainfall over Kolkata is characterized by convective rain events and thunderstorms, mostly occurring from afternoon to night (15:30 IST − 21:30 IST) span. Emphasis has been given to the set-in time of pre-monsoon rain events, based upon which they are classified as expected (14:30 IST − 18:30 IST) and delayed (after 18:30 IST). Efforts have been made to assess the sustaining atmospheric conditions (in terms of temperature, water vapour, liquid water content and instability parameter) associated with such rain events prevailing over two non-overlapping time spans of pre-monsoon season. The mean diurnal variations of integrated water vapour (IWV), liquid water path (LWP), and instability parameter, namely, convective available potential energy (CAPE) during the expected and delayed rain event dates show distinct intensity in the increasing trends prior to the respective rainfall peaks. It has been observed that for the delayed events, the temperature difference between ground and 2000 m altitude begins to fall at a later part of the evening in comparison with the expected ones. Overall the investigated parameters exhibited distinguishable nature of variations for the two classes of rain events over the study location.

Impact Assessment of Cyclone Amphan on Agriculture Over Parts of West Bengal Using Remote Sensing

Super-cyclone Amphan caused a devastating impact on agriculture in West Bengal. The present study aims at identifying the agricultural areas affected due to cyclone Amphan led water inundation in twelve selected districts of Gangetic West Bengal. The Sentinel 1 data of both pre- and post-cyclonic periods were analyzed to obtain the inundation area. Subsequently, the multi-temporal Landsat 8 datasets of 2019 and 2020 from April to June were analyzed to assess the crop conditions existing during the pre-cyclonic period. Both the layers were intersected to estimate the district-wise inundated agricultural areas along with the crop conditions. The post-cyclone water inundation was highest (43408 ha.) in Purba Medinipur. Among the inundated agricultural area, the standing crop including both growing and mature was significantly higher than harvested crop area. The validation with the ground-based information shows that the proposed approach was able to detect the crop conditions existing during the pre-cyclonic period efficiently with more than 90% accuracy. Hence, the same methodology may be adopted for assessing the crop damages caused due to cyclone induced inundation.

Sustainable Management of Arsenic Translocation in the Paddy Plants (Oryza sativa L) Cultivated in the Alluvial Soil of Gangetic West Bengal, India.

Rice plants are known to be more susceptible to arsenic (As) contamination during the cultivation process. Arsenic is genotoxic and can be a big threat to the rice eating people at large. Studies on an effective mitigation mechanism are the need of the hour. This work was an approach using iron (Fe3+) to form Fe-plaque in the plant root that could trap As. The present research was designed with several experimental set ups for rice cultivation in pot culture using different Fe doses with fertilizer in the soil, and finally, the optimum dose was selected considering the translocation ability, plant health, and molecular and stress biomarkers. The study revealed that on an increase in Fe dose, translocation factor (TF) and stress marker (malondialdehyde content) of the plant decreased gradually and encountered minimum (0.12 and 0.03mg/kg, respectively) at the dose of 4.5gm/kg. In contrast, higher values of chlorophyll (2.5mg/kg) and carbohydrate (2.2mg/kg) and intact DNA content were recorded highlighting the rich health condition of the plant. Thus, the experiment supported well the fact that the dose of Fe as fortified fertilizer can be considered the most effective in reducing soil arsenic accumulation in the rice plants. This approach might save the rice eating people from harmful effects of As contamination in this region of India.

Application of Analytic Hierarchy Process and weighted sum techniques for green tourism potential mapping in the Gangetic West Bengal, India

Application of Analytic Hierarchy Process and weighted sum techniques for green tourism potential mapping in the Gangetic West Bengal, India

Intraseasonal variability and possible causes of large-scale and convective precipitations over the Gangetic plain of India

The occurrence of Indian summer monsoon rainfall (ISMR) during June to September, especially over the eastern Gangetic plain of India, is the lifeline for densely residing people. The intraseasonal and interannual variability in ISMR provokes drought and flood conditions and largely affects agriculture practices. Owing to its importance, several studies on the variability of ISMR over the meteorological subdivisions, namely West Bengal (WB), Jharkhand (JH), Bihar (BR), East Uttar Pradesh (EUP), and West Uttar Pradesh (WUP), respectively, have been conducted; however, the contribution of large-scale precipitation (LSP) and convective precipitation (CP) in ISMR needs to discuss. The LSP is precipitated out from the stratus or nimbostratus clouds, while CP occurs from the cumulus and cumulonimbus clouds, and both of them coexist in ISMR during summer monsoon months. The objective of this paper is to analyze and discuss the climatological characteristics and possible causes of occurrence of LSP and CP over the meteorological subdivisions. For this purpose, the data of LSP, CP, zonal, meridional (u and v components) wind, and relative humidity (rh) at the spatial resolution of 0.25° × 0.25° for the period of 1980–2019 are taken from the European Centre for Medium-Range Weather Forecasts (ECMWF). The outgoing longwave radiation (OLR) data at a surface resolution of 1° × 1° for the same periods are obtained from the National Centre for Environmental Information (of NOAA). The observed rainfall data of the India Meteorological Department at the same resolution and period is considered and compared with ECMWF Reanalysis (ERA5) data. The spatial and temporal distribution of both types of precipitation is analyzed, and their linkage with OLR, zonal winds, and rh at pressure levels of 1000 hPa, 850 hPa, and 700 hPa (in lower troposphere) is examined. The daily climatological values of CP (LSP) are relatively higher (lower) in each meteorological subdivision. The associated lower values of OLR are noticed over the Gangetic West Bengal, Jharkhand, and Bihar, while higher values of OLR are seen over the East and West UP. From the pressure levels of 1000 to 700 hPa, the change in the zonal wind, i.e., easterly to westerly and vice versa, and occurrence of a large amount of rh (>80%) may be possibly initiated moist convective activity for more precipitating out CP over the Gangetic West Bengal, Jharkhand, and Bihar in comparison to East and West Uttar Pradesh.

Prospects of aquaculture of West Bengal, India under Changing climate

Climate variability refers to the variability observed in the climate record in periods when the state of the climate system is not showing changes. If the climate state changes, usually characterized by a shift in means, then the frequency of formerly rare events on the side to which the mean has shifted might occur more frequently with increasing climate variability. Natural variability is a characteristic of the global climate and occurs on both long and short-time scales. Aquaculture practices involve the breeding, rearing, and harvesting of aquatic organisms in freshwater, brackish water, or marine environments. Aquaculture is a rapidly growing sector of nutrition security in Gangetic West Bengal. A study was conducted on West Bengal in India, one of the eastern states of India. West Bengal state has different types of agroclimatic zones. Aquaculture in West Bengal has tremendous potential to grow as an industry. Residents of West Bengal must understand the value of local wetlands and the importance of the conservation of wet lands. Government institutes should collectively work with different educational hubs, scientists, and NGOs on beneficial issues of the state so that aquaculture conservation and development and appropriate adaptation strategies can be adopted.

Assessing the suitability of groundwater for irrigation in the light of natural forcing and anthropogenic influx: a study in the Gangetic West Bengal, India

Assessing the suitability of groundwater for irrigation in the light of natural forcing and anthropogenic influx: a study in the Gangetic West Bengal, India

Evaluation of LARS-WG model for generating climate data over lower Gangetic West Bengal

Evaluation of LARS-WG model for generating climate data over lower Gangetic West Bengal

Assessing pre-monsoon and monsoon rainfall change signal with future projection over Gangetic West Bengal

Monsoon rainfall is the dominant factor that determines the success or failure of agriculture in general. Gangetic West Bengal is not any exception. Monsoon rainfall has immense importance for growing kharif rice in this region. Whereas pre-monsoon rainfall helps farmers for proper crop planning like choosing variety etc. So assessing a long (1901-2005) and short (1961-2005 and 1991-2005) period rainfall data, its comparison with different models and construction of future scenario have utmost importance. For this purpose, rainfall data from nine selected station of India Meteorological Department were collected and subjected to trend analysis. Model outputs were compared with the observed station data. Results showed an overall negative trend of pre-monsoon rainfall during 1901-2005. However, increasing trend in monsoon rainfall was noticed during the same period. In future scenario, monsoon rainfall indicates a nominal increase (~6%) whereas pre-monsoon rainfall increases in moderate amount (~11%). So, from the study it may be said that in near future farmers and crop planner should give more importance in pre-monsoon rainfall for better crop planning and other stake holder activities.

Eastern and North Eastern sub-divisions of India : An analysis of trend and chaotic behaviour of rainfall in different seasons

The aim of the study is to understand trend or non-linearity along with a chaotic behaviour, if any, of Eastern and North Eastern sub-divisional rainfall, namely Orissa, Gangetic West Bengal, Sub Himalayan West Bengal, Assam and Meghalaya and also Nagaland, Manipur, Mizoram and Tripura based on rainfall data of 143 years (1871-2013). The analysis is performed for examining behaviour of rainfall in each of the seasons, namely, Pre monsoon, South West monsoon, North East monsoon and also Annual rainfall extracted from the monthly data. For that purpose, a trend analysis with Hurst Exponent and non-linearity analysis with Lyapunov Exponent are employed. The analysis revealed that rainfall of Orissa is persistent for all the seasons whilst the rainfall is persistent in Gangetic West Bengal in Pre monsoon and North East monsoon and Assam and Meghalaya along with Nagaland, Manipur, Mizoram and Tripura exhibit persistent behaviour in South West Monsoon and annually. Sub Himalayan West Bengal exhibit persistence in annual rainfall only. Chaotic tendency in low magnitude is located in many cases whilst non-chaotic situation has occurred when the persistence is found, mainly in pre-monsoon season. Moreover, the analysis of Hurst and Lyapunov Exponent revealed to identify two groups of sub-divisions with exactly similar region of every respect. Those two groups contain (i) sub-divisions Orissa and Assam and Meghalaya and also (ii) sub-divisions Sub Himalayan West Bengal and Nagaland, Mizoram, Manipur and Tripura although those are at distances of hundreds of kilometers away. The behaviour of those subdivisions in a group has similar behaviour in all respects.

Kharif rice yield prediction over Gangetic West Bengal using IITM-IMD extended range forecast products

Kharif rice yield prediction over Gangetic West Bengal using IITM-IMD extended range forecast products

Incorporation of Surface Observations in the Land Data Assimilation System and Application to Mesoscale Simulation of Pre-monsoon Thunderstorms

In the present study, local insitu observations are utilized in the Land Data Assimilation System (LDAS) to generate high-resolution (4 km and hourly) soil moisture (SM) and soil temperature (ST) data over India. Further, the impact of the LDAS-derived SM and ST initialization on simulation of pre-monsoon (March–May) thunderstorms over the Gangetic West Bengal region are assessed. The high-resolution (4 km and hourly) land surface conditions such as SM and ST data are prepared for the period from 2010 to 2013 using the LDAS forced with various insitu observations from Automatic Weather Stations (AWS), Meteorological Aviation Reports (METAR), and micro-meteorological tower observations over India. Four thunderstorm (TS) events during the pre-monsoon season of 2010 are considered for the numerical experiments using climatological SM and ST at coarser resolution (CNTR) and LDAS-generated high-resolution SM and ST (WLDAS) for initializing the Weather Research and Forecasting (WRF) Model. The efficacy of the LDAS-generated SM and ST data are verified against micro-meteorological tower observations at Kharagpur, West Bengal, and the results indicate the magnitude and variation in the data product are close to observations. The initialization of high-resolution LDAS-generated SM and ST in the WRF improves the simulation of near-surface air temperature, humidity, and pressure at Kharagapur. Most importantly, the location and timing of the storm are relatively better simulated in the WLDAS than CNTR over the Kolkata region. The study encourages the use of more local observations in the generation of high-resolution SM and ST data for application in the simulation of pre-monsoon TSs.

Impact of soil addendum on arsenic uptake by rice plant in the alluvial soil of gangetic West Bengal, India

Impact of soil addendum on arsenic uptake by rice plant in the alluvial soil of gangetic West Bengal, India

Bayesian Network based modeling of regional rainfall from multiple local meteorological drivers

This study aims to establish the conditional independence structure between regional monthly rainfall and several local meteorological drivers (probable predictors) to develop a parsimonious prediction model in the framework of Bayesian Networks (BN). The chosen study area is the Gangetic West Bengal (GWB) region, India and the chosen meteorological drivers at the surface and different pressure levels are the 12 probable predictors, viz. air temperature, total precipitable water, relative humidity, geo-potential height, zonal wind, meridional wind, omega and soil moisture, each up to a lead time of 6 months, making a total of 72 inputs. Within the BN architecture, two heuristic algorithms namely Hill-Climb (HC) and Max-Min Hill Climb (MMHC) were used to establish that a large part (89% for HC and 97% for MMHC) of the input information was redundant, given the potential predictors that are selected via these algorithms. The potential predictors revealed via these algorithms include geo-potential height at a pressure of 850 mb, total precipitable water, and soil moisture, each at a lead time of 2 months. The selected predictors were further used to develop a prediction model that results in good agreement with the observations. Additionally, two widely used machine learning techniques namely, Artificial Neural Networks (ANN) and Support Vector Regression (SVR) were also used to develop standalone models wherein all the 72 probable predictors are used for prediction, and also in conjunction with BN (i.e., BN-ANN and BN-SVR), wherein only the drivers selected via BN are used as predictors. The results indicate that the parsimonious models perform better or equally well as the higher dimensional models, with refined Index of agreement values: MDBN = 0.824, MDBN-ANN = 0.835 and MDBN-SVR = 0.841, MDANN = 0.813, MDSVR = 0.823, and Normalized Mean Square Error values: NMSEBN = 0.242, NMSEBN-ANN = 0.226 and NMSEBN-SVR = 0.234, NMSEANN = 0.226, NMSESVR = 0.238 for validation period (averaged values across three folds). The model predictions are further used to categorize monthly rainfall into dry/ intermediate/ wet in terms of Standardized Precipitation Anomaly Index (SPAI). All the approaches show consistent performance, with the ‘dry’ cases being captured slightly better than ‘wet’ cases.