Innovative lake pollution profiling: unveiling pollutant sources through advanced multivariate clustering techniques.

In many developed and developing nations, lakes are the primary source of drinking water. In the current scenario, due to rapid mobilization in anthropogenic activities, lakes are becoming increasingly contaminated. Such practices not only destroy lake ecosystems but also jeopardize human health through water-borne diseases.

Agricultural watershed conservation and optimization using a participatory hydrological approach.

Maximizing the impact of agricultural wastewater conservation practices (CP) to achieve total maximum daily load (TMDL) scenarios in agricultural watersheds is a challenge for the practitioners. The complex modeling requirements of sophisticated hydrologic models make their use and interpretation difficult, preventing the inclusion of local watershed stakeholders' knowledge in the development of optimal TMDL scenarios. The present study develops a seamless modeling approach to transform the complex modeling outcomes of Hydrologic Simulation Program Fortran (HSPF) into a simplified participatory framework for developing optimized management scenarios.

Bio-chelate assisted leaching for enhanced heavy metal remediation in municipal solid waste compost.

Municipal solid waste compost, the circular economy's closed-loop product often contains excessive amounts of toxic heavy metals, leading to market rejection and disposal as waste material. To address this issue, the study develops a novel approach based on: (i) utilizing plant-based biodegradable chelating agent, L-glutamic acid, N,N-diacetic acid (GLDA) to remediate heavy metals from contaminated MSW compost, (ii) comparative assessment of GLDA removal efficiency at optimal conditions with conventional nonbiodegradable chelator EDTA, and (iii) enhanced pre- and post-leaching to evaluate the mobility, toxicity, and bioavailability of heavy metals. The impact of treatment variables, such as GLDA concentration, pH, and retention time, on the removal of heavy metals was investigated.

Effect of varying hydrologic regime on seasonal total maximum daily loads (TDML) in an agricultural watershed.

Rising hypoxia due to the eutrophication of riverine ecosystems is primarily caused by the transport of nutrients. The majority of existing TMDL models cannot be efficienty applied to represent nutrient concentrations in riverine ecosystems having varying flow regimes due to seasonal differences. Accurate TMDL assessment requires nutrient loads and suspended matter estimation under varying flow regimes with minimal uncertainty.

An innovative approach for predicting pandemic hotspots in complex wastewater networks using graph theory coupled with fuzzy logic.

Unlabelled: Early prediction of COVID-19 infected communities (potential hotspots) is essential to limit the spread of virus. Diagnostic testing has limitations in big populations because it cannot deliver information at a fast enough rate to stop the spread in its early phases. Wastewater based epidemiology (WBE) experiments showed promising results for brisk detection of 'SARS CoV-2' RNA in urban wastewater.

Wetland functional assessment and uncertainty analysis using fuzzy α-cut-based modified hydrogeomorphic approach.

Wetlands are significant ecosystems which perform several functions such as ground water recharge, flood control, carbon sequestration, and pollution reduction. Accurate evaluation of wetland functions is challenging, due to uncertainty associated with variables such as vegetation, soil, hydrology, land use, and landscape. Uncertainty is due to the factors such as the cost of evaluating quality parameters, measurement, and human errors.

Heavy metal remediation using chelator-enhanced washing of municipal solid waste compost based on spectroscopic characterization.

Due to high metal toxicity, mixed municipal solid waste (MSW) compost is difficult to use. This study detected the presence of heavy metals (Cd, Cu, Pb, Ni, and Zn) in MSW compost through mineralogical analysis using X-ray diffraction (XRD) and performed topographical imaging and elemental mapping using a scanning electron microscope and energy dispersive X-ray analysis (SEM-EDX). Ethylenediaminetetraacetic acid (EDTA), a typical chelator, is tested to remove heavy metals from Indian MSW compost (New Delhi and Mumbai).

Managing nitrate-nitrogen in the intensively drained upper Mississippi River Basin, USA under uncertainty: a perennial path forward.

The upper Mississippi River basin has been identified as the most significant contributor of excessive nutrients to the hypoxic zone in the Gulf of Mexico. The land-use changes from an internally drained prairie-wetland complex to an intensively managed corn-soybean production system drained by subsurface tile drainage system in the north-central Iowa and south-central Minnesota are the primary cause of nutrient loads into the Mississippi River and many other environmental stresses. The present study summarizes the water-quality degradation from land-use change and offers a fuzzy logic-based decision support for assessing degree of suitability of the four recommended perennial plant options for managing water and nitrate-nitrogen export.

Hydro-conditioning: Advanced approaches for cost-effective water quality management in agricultural watersheds.

Accurate simulation of landscape hydrological connectivity is pivotal for planning practices required for treating agricultural farm pollution. This study assesses the role of an advanced geospatial approach, namely, 'hydro-conditioning' employed for modifying Digital Elevation Models, termed hDEMs to replicate landscape hydrology by simulating continuous downslope flow through drainage structures such as bridges and culverts. The capabilities of manual and automated hDEMs in delineating optimal locations and water treatment potential of Best Management Practices (BMPs) in a typical agricultural watershed were evaluated.

Cloud-based neuro-fuzzy hydro-climatic model for water quality assessment under uncertainty and sensitivity.

River water quality is a function of various bio-physicochemical parameters which can be aggregated for calculating the Water Quality Index (WQI). However, it is challenging to model the nonlinearity and uncertain behavior of these parameters. When data is deficient and noisy, it creates missing and conflicting parameters within their complex inter-relationships.

Detecting SARS-CoV-2 RNA prone clusters in a municipal wastewater network using fuzzy-Bayesian optimization model to facilitate wastewater-based epidemiology.

The current pandemic disease coronavirus (COVID-19) has not only become a worldwide health emergency, but also devoured the global economy. Despite appreciable research, identification of targeted populations for testing and tracking the spread of COVID-19 at a larger scale is an intimidating challenge. There is a need to quickly identify the infected individual or community to check the spread.

An integrated fuzzy-based advanced eutrophication simulation model to develop the best management scenarios for a river basin.

Assessment of water quality status of a river with respect to its discharge has become prerequisite to sustainable river basin management. The present paper develops an integrated model for simulating and evaluating strategies for water quality management in a river basin management by controlling point source pollutant loadings and operations of multi-purpose projects. Water Quality Analysis and Simulation Program (WASP version 8.