Spatiotemporal drought analysis in Bangladesh using the standardized precipitation index (SPI) and standardized precipitation evapotranspiration index (SPEI)

Abstract Countries depending on small-scale agriculture, such as Bangladesh, are susceptible to climate change and variability. Changes in the frequency and intensity of drought are a crucial aspect of this issue and the focus of this research. The goal of this work is to use SPI (standardized precipitation index) and SPEI (standardized precipitation evapotranspiration index) to investigate the differences in drought characteristics across different physiognomy types in Bangladesh and to highlight how drought characteristics change over time and spatial scales when considering different geomorphologies. This study used monthly precipitation and temperature data from 29 metrological stations for 39 years (1980–2018) for calculating SPI and SPEI values. To determine the significance of drought characteristic trends over different temporal and spatial scales, the modified Mann–Kendall trend test and multivariable linear regression (MLR) techniques were used. The results are as follows: (1) Overall, decreasing dry trend was found in Eastern hill regions, whereas an increasing drought trends were found in the in the rest of the regions in all time scaless (range is from − 0.08 decade−1 to − 0.15 decade−1 for 3-month time scale). However, except for the one-month time scale, the statistically significant trend was identified mostly in the north-central and northeast regions, indicating that drought patterns migrate from the northwest to the center region. (2) SPEI is anticipated to be better at capturing dry/wet cycles in more complex regions than SPI. (3) According to the MLR, longitude and maximum temperature can both influence precipitation. (4) Drought intensity increased gradually from the southern to the northern regions (1.26–1.56), and drought events occurred predominantly in the northwestern regions (27–30 times), indicating that drought meteorological hotspots were primarily concentrated in the Barind Tract and Tista River basin over time. Findings can be used to improve drought evaluation, hazard management, and application policymaking in Bangladesh. This has implications for agricultural catastrophe prevention and mitigation

Assessing the critical success factors for implementing industry 4.0 in the pharmaceutical industry: Implications for supply chain sustainability in emerging economies.

The emerging technologies of Industry 4.0 (I4.0) are crucial to incorporating agility, sustainability, smartness, and competitiveness in the business model, enabling long-term sustainability practices in the pharmaceutical supply chain (PSC). By leveraging the latest technologies of I4.0, pharmaceutical companies can gain real-time visibility into their supply chain (SC) operations, allowing them to make data-driven decisions that improve SC performance, efficiency, resilience, and sustainability. However, to date, no research has examined the critical success factors (CSFs) that enable the pharmaceutical industry to adopt I4.0 successfully to enhance overall SC sustainability. This study, therefore, analyzed the potential CSFs for adopting I4.0 to increase all facets of sustainability in the PSC, especially from the perspective of an emerging economy like Bangladesh. Initially, sixteen CSFs were identified through a comprehensive literature review and expert validation. Later, the finalized CSFs were clustered into three relevant groups and analyzed using a Bayesian best-worst method (BWM)-based multi-criteria decision-making (MCDM) framework. The study findings revealed that "sufficient investment for technological advancement", "digitalized product monitoring and traceability", and "dedicated and robust research and development (R&D) team" are the top three CSFs to adopt I4.0 in the PSC. The study's findings can aid industrial practitioners, managers, and policymakers in creating effective action plans for efficiently adopting I4.0 in PSC to avail of its competitive benefits and ensure a sustainable future for the pharmaceutical industry

Predicting long term regional drought pattern in Northeast India using advanced statistical technique and wavelet-machine learning approach

Understanding drought and its multifaceted challenges is crucial for safeguarding food security, promoting environmental sustainability, and fostering socio-economic well-being across the globe. As a consequence of climate change and anthropogenic factors, the occurrence and severity of drought has risen globally. In India, droughts are regular phenomenon affecting about 16% area of country each year which leads to a loss of about 0.5–1% of country’s annual GDP. Hence, the study aims to analyse and predict the meteorological drought in northeast India during 1901 to 2015 using standardised precipitation index (SPI) and analytical techniques such as Mann–Kendall test (MK), innovative trend analysis (ITA), and wavelet approach. In addition, the periodicity of the drought was estimated using Morlet wavelet technique, while discrete wavelet transform (DWT) was applied for decomposing the time series SPI-6 & SPI-12. Study shows that the northeast India experienced moderate drought conditions (SPI-6) in short term and two significant severe droughts (SPI-12) in long term between 1901 and 2015. The trend analysis shows a significant increase in SPI-6 & SPI-12 (p-value 0.01). Further, the combination of parameters i.e. approximation and levels result in the best drought prediction model with higher correlation coefficient and lower error. By using PSO-REPTtree, this study pioneers the use of decomposed parameters to detect trends and develop a drought prediction model. The study is the first step towards establishing drought early warning system that will help decision-makers and farmers to mitigate the impact of drought at the regional level

Assessment of As, Cr, Cd, and Pb in urban surface water from a subtropical river: contamination, sources, and human health risk

This work aimed to determine the level of some toxic elements (As, Cr, Cd, and Pb) in the water of the Rupsha River, Bangladesh, concerning their potential dangers to human exposure. The elemental concentrations (mg/L) were determined using Atomic Absorption Spectrometer and found to decrease in the order of Cr (0.041) > Pb (0.029) > As (0.004) > Cd (0.002). The level of elements in this river water surpasses various international limits, making it unfit for human consumption. Furthermore, the metal pollution index and contamination index indicated that the water was also unsuitable for this purpose. The elements chosen were persuasive to discern the hazard quotient of non-carcinogenic risk. Moreover, total targeted hazard quotient (TTHQ) values were found for adults and children within acceptable limits (TTHQ −6 to 10−4) of the threshold limit. Due to their high-water consumption per unit of body-weight and physiological development, children were found to be more sensitive than adults. Multivariate analyses demonstrated that human activities were the primary origin of toxic elements in river water. According to the findings, urban and industrial effluents should be treated before being released into rivers. Development along the river bank must be carefully controlled to safeguard the river environment. In the end, this will improve the quality of the water and lower the chance that people will be exposed to metals.</p

Spatiotemporal distribution of drought and its possible associations with ENSO indices in Bangladesh

Droughts and related water stress are the major constraints of the sustainable socioeconomic development of Bangladesh. Large-scale atmospheric oscillations are the major drivers of climate fluctuation and droughts in Bangladesh, like many other regions of Asia including the Indian subcontinent, the largest entity in the world, with over 1.7 billion people. Therefore, it is crucial to insight into the spatiotemporal distribution of drought and its linkage to large-scale atmospheric indices to provide early warning and alleviate drought impacts. However, regional droughts and their linkages to large-scale oscillation indices like El-Nino Southern Oscillation (ENSO) are not explored adequately in Bangladesh. This study intends to evaluate the spatiotemporal distribution of droughts in Bangladesh using the standardized precipitation evapotranspiration index (SPEI) and the standardized precipitation index (SPI) for multiple timescales,?-?3,?-?6,?-?12, and 24-months, and to investigate the relationship of drought characteristics with ENSO. The monthly rainfall and temperature records from twenty locations for 38 years from the period 1980 to 2017 were used for this purpose. The results revealed that the droughts are region-specific and are in agreement with the warming trends observed in the different regions of Bangladesh. The droughts, particularly short-term droughts, are increasing significantly in the North-western region, indicating the worsening drought conditions in the drought-prone region. The SPI and SPEI showed a significant (p?<?0.05) positive association with the percentage of precipitation anomaly (Pa). However, the association of drought indices with ENSO and potential evapotranspiration (PET) were not significant. The polynomial regression model demonstrated that Indian Ocean Dipole (IOD) could explain SPEI-3 (4.7%) variations better than SPI-3 (4.2%)