Fine-tuning inflow prediction models: integrating optimization algorithms and TRMM data for enhanced accuracy.

This research explores machine learning algorithms for reservoir inflow prediction, including long short-term memory (LSTM), random forest (RF), and metaheuristic-optimized models. The impact of feature engineering techniques such as discrete wavelet transform (DWT) and XGBoost feature selection is investigated. LSTM shows promise, with LSTM-XGBoost exhibiting strong generalization from 179.

WITHDRAWN: Trace metals translocation from soil to plants: Health risk assessment via consumption of vegetables in the urban sprawl of a developing country.

This article has been withdrawn at the request of the author(s) and/or editor. The Publisher apologizes for any inconvenience this may cause. The full Elsevier Policy on Article Withdrawal can be found at https://www.

Fuzzy logic, geostatistics, and multiple linear models to evaluate irrigation metrics and their influencing factors in a drought-prone agricultural region.

The quality of water used for irrigation is one of the major threats to maintaining the long-term sustainability of agricultural practices. Although some studies have addressed the suitability of irrigation water in different parts of Bangladesh, the irrigation water quality in the drought-prone region has yet to be thoroughly studied using integrated novel approaches. This study aims to assess the suitability of irrigation water in the drought-prone agricultural region of Bangladesh using traditional irrigation metrics such as sodium percentage (NA%), magnesium adsorption ratio (MAR), Kelley's ratio (KR), sodium adsorption ratio (SAR), total hardness (TH), permeability index (PI), and soluble sodium percentage (SSP), along with novel irrigation indices such as irrigation water quality index (IWQI) and fuzzy irrigation water quality index (FIWQI).

Perception and legacy of soil chromium and lead contamination in an operational small-scale coal mining community.

Operational small-scale coal mining (OSCM) is one of the most significant sources of chromium (Cr) and lead (Pb) pollution in Bangladesh. Attempts to minimize or lessen the use of Cr and Pb in OSCM have shown unsatisfactory results, mainly because they need to address the sociotechnical complexity of pollution concerns in OSCM. This research adopts a multidisciplinary, sociotechnical approach to addressing Cr and Pb problems, coupling soil sampling for Cr and Pb with questionnaires of miners' and inhabitants' perceptions of pollution and its distribution.

Pollution trends and ecological risks of heavy metal(loid)s in coastal zones of Bangladesh: A chemometric review.

Heavy metal(loid)s inputs contribute to human and environmental stresses in the coastal zones of Bangladesh. Several studies have been conducted on metal(loid)s pollution in sediment, soil, and water in the coastal zones. However, they are sporadic, and no attempt has been made in coastal zones from the standpoint of chemometric review.

Corrigendum to "Development of a fabricated first-flush rainwater harvested technology to meet up the freshwater scarcity in a South Asian megacity, Dhaka, Bangladesh" [Heliyon 9 (1) (January 2023) Article e13027].

[This corrects the article DOI: 10.1016/j.heliyon.

Identifying factors affecting irrigation metrics in the Haor basin using integrated Shannon's entropy, fuzzy logic and automatic linear model.

The sustainability of agricultural practices is seriously threatened by the quality of water used for irrigation. This paper aims to evaluate the suitability of irrigation water and identify the region suitable for agricultural use in the Haor basin of Bangladesh using conventional irrigation indices such as sodium adsorption ratio (SAR), percent sodium (Na%), magnesium hazard ratio (MHR), permeability index (PI), and Kelly's ratio (KR), as well as novel irrigation indices such as, Shannon's entropy index for irrigation water quality (EWQ) and fuzzy logic index for irrigation water quality (FIWQI). The main influences of groundwater and surface water parameters on irrigation indices were predicted using automatic linear modeling (ALM).

A critical review and prospect of NO and SO pollution over Asia: Hotspots, trends, and sources.

Nitrogen dioxide (NO) and sulfur dioxide (SO) are two major atmospheric pollutants that significantly threaten human health, the environment, and ecosystems worldwide. Despite this, only some studies have investigated the spatiotemporal hotspots of NO and SO, their trends, production, and sources in Asia. Our study presents a literature review covering the production, trends, and sources of NO and SO across Asian countries (e.

Development of a fabricated first-flush rainwater harvested technology to meet up the freshwater scarcity in a South Asian megacity, Dhaka, Bangladesh.

The scarcity of freshwater in most of the megacities in the world is an important concern. In this regard, scientifically harvested rainwater could provide an effective measure to this crisis. In this attempt, we developed a cost-effective sensor-based automated first-flush rainwater harvesting system (RHS) to improve the freshwater scarcity and economic development of megacities like Dhaka, Bangladesh.

Distribution, sources, and pollution levels of toxic metal(loid)s in an urban river (Ichamati), Bangladesh using SOM and PMF modeling with GIS tool.

Indexical assessment coupled with a self-organizing map (SOM) and positive matrix factorization (PMF) modeling of toxic metal(loid)s in sediment and water of the aquatic environment provides valuable information from the environmental management perspective. However, in northwest Bangladesh, indexical and modeling assessments of toxic metal(loid)s in surface water and sediment are still rare. Toxic metal(loid)s were measured in sediment and surface water from an urban polluted river (Ichamati) in northwest Bangladesh using an atomic absorption spectrophotometer to assess distribution, pollution levels, sources, and potential environmental risks to the aquatic environment.

Effects of COVID-19 era on a subtropical river basin in Bangladesh: Heavy metal(loid)s distribution, sources and probable human health risks.

The COVID-19 era has profoundly affected everyday human life, the environment, and freshwater ecosystems worldwide. Despite the numerous influences, a strict COVID-19 lockdown might improve the surface water quality and thus provide an unprecedented opportunity to restore the degraded freshwater resource. Therefore, we intend to investigate the spatiotemporal water quality, sources, and preliminary health risks of heavy metal(loid)s in the Karatoya River basin (KRB), a tropical urban river in Bangladesh.