Daily rainfall forecasting in Assam, northeast India, remains challenging due to strong monsoon variability and complex terrain. This study compares Multiple Linear Regression (baseline), XGBoost, and LightGBM for daily precipitation prediction across five hydro-climatic regions of Assam using a 24-year meteorological dataset (2001–2024) from IMD (India Meteorological Department) and NASA POWER. Models were trained on 2001–2023 and evaluated on an independent 2024 test year. Both gradient boosting models substantially improved prediction accuracy relative to linear regression, achieving R² (Coefficient of Determination) values of 0.775–0.974 and reducing mean absolute error by up to 85%. Event-detection skill was also strong, with CSI (Critical Success Index) values of 0.852–0.958 at the 5 mm/day rainfall threshold and consistent detection of heavy rainfall events at 25 mm/day, where linear regression showed very limited skill. Seasonal analysis indicated higher uncertainty during the peak monsoon season, particularly in the orographically complex Upper Assam region where LightGBM monsoon R² declined to 0.687. The analysis is limited by the use of single representative grid points per region and evaluation on a single test year, which may not fully capture inter-annual variability. Nevertheless, the results suggest that gradient boosting models with temporal feature engineering and strict train–test separation provide a promising framework for operational rainfall forecasting in monsoon-dominated regions such as Assam.

This study examines the morphometric characteristics and drainage anomalies of the Kanchi River Basin, which is a tributary of the Subarnarekha River located in Jharkhand, India. SRTM DEM data alongside ArcGIS 10.3.1 were utilized to outline the drainage system and conduct morphometric evaluations. The recorded drainage density stands at 1.13 km/km², the stream frequency at 0.97 streams/km², and the relative relief at 276.66 m. The anomalies in DD range from –1.23 to –2.35 km/km², while the anomalies in stream frequency range from –1.21 to –4.77stream/km². The basin is elongated, moderately dissection, and is influenced by the underlying structure. Tectonic activity and variations in lithology have a significant impact on how drainage anomalies are spatially distributed. The combination of DEM and GIS has proven effective for geomorphological studies, assisting in watershed management and planning for land use.

This study presents a novel hybrid approach integrating hydrodynamic cavitation (HC) with advanced oxidation processes (AOPs) like hydrogen peroxide (H2O2) and ozone (O3) to enhance the biodegradability of real dairy industry wastewater. The research focuses on optimizing HC with other oxidants and exploring the synergistic effects of oxidants on pretreatment efficacy. Experimental investigations were conducted using an orifice plate HC reactor at 2 bar inlet pressure, treating actual dairy effluent with high chemical oxygen demand (COD) and low initial biodegradability index (BI = 0.35). HC treatment alone improved the BI to 0.66, while combining HC with H2O2 (9 g/L) and combining with O3 (200 mg/h) further increased the BI to 0.74 and 0.81, respectively. Most notably, the ternary combination of HC + H2O2 + O3 achieved a substantial increase in BI to 0.89, demonstrating a strong synergistic effect. This enhancement is attributed to the intensified generation of reactive hydroxyl radicals (.OH) through cavitational and oxidative reactions, leading to effective degradation of complex organic pollutants and improved downstream biological treatment potential. These results underscore the viability of HC-AOPs hybrids as cost-effective and sustainable pretreatment strategies for dairy wastewater management.

Oaks of the Himalayan region are at risk due to relentless anthropogenic pressure and climate change. This study was undertaken to assess regeneration status of Quercus lanata (Q. lanuginosa) dominated forests in the Kumaun region of Indian Himalaya. Q. lanata has restricted distribution and forms small patches of a few hectares between 1800 and 2400 m elevation. The study was conducted across two forest sites, located in Nainital and Pithoragarh districts, between the elevation ranging 1950 and 2200 m. Present research attempts to evaluate regeneration status of Q. lanata at selected sites in Kumaun Himalaya. Across both sites, total tree density varied between 665 and 1115 ind ha-1, and density of Q. lanata ranged between 525 and 560 ind ha-1, and total basal area was between 36.96 and 40.52 m²ha-1. Seedling density of Q. lanata varied between 80 and 455 ind ha-1 across both sites. Across the study sites, the sapling density was low. The results indicate that Q. lanata showed fair recruitment of seedling however the conversion of seedling into saplings is poor. This study emphasizes the requirement for targeted conservation efforts to sustain the biodiversity and ecological balance of the Q. lanata. Forests.

Water crisis restricts availability to safe water, due to unsustainable practices leading to excessive aquifer consumption. In this study, the Grey water was collected from household kitchen sink and was treated by Electro-coagulation (EC) (60 A/m2) method using aluminium (Al), copper (Cu), stainless steel (SS) electrodes along with banana bract activated through three different agents (H3PO4, CaCo3, KOH) as adsorbent by varying the operating parameters (time, electrode and activation agent). Initial characteristics of Grey water were determined using experimental methods. The surface response design is based on Box-Behnken which has been used to optimize parameters by quadratic model, with independent variables assessed by analysis of variance (ANOVA). Cu-Cu electrode with CaCo3 adsorbent (0.5g dosage) at 60 minutes of contact time exhibited higher efficiency of 82% achieved under optimum parametric conditions. With Response Surface Methodology (RSM) the wastage of water to find the suitable adsorbent and contact time has been reduced with minimal runs. This study shows that the EC process along with RSM is an effective tool to improve characteristics of Grey water under different operating parameters.

This study examines the presence of heavy metal pollution in 111 vegetable samples that were collected in the winter from industrial regions in Haryana, India. The samples mean heavy metal concentrations (mg/kg-1 dry weight) were determined to be as follows Al, Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb, and Zn, was 158.01, 0.23, 0.04, 3.70, 7.82, 297.87, 39.81, 1.78, 0.52, and 32.21 respectively. Two main metal clusters (Al-Fe-Pb and Zn-Cu) were identified by statistical analysis, indicating shared contamination sources. The FAO/WHO-established acceptable limits for heavy metals were surpassed by the majority of vegetables, presenting serious health hazards. For every species of vegetable, the total target hazard quotient (TTHQ) was higher than 1, suggesting a possible non-carcinogenic health risk to consumers. The highest metal pollution index (MPI) was found in leafy vegetables, indicating a higher propensity for metal accumulation. The results highlight how urgently monitoring and mitigating measures are needed to lower the exposure to heavy metals from eating vegetables in industrial areas.

Seasonal pools and ephemeral wetlands are ecologically significant habitats that support diverse flora and fauna. This study, conducted during the 2022–23 monsoon at Nediyenga, Sreekandapuram, Kannur District, Kerala, explores herbaceous plant diversity, soil and water characteristics, and climate trends. A total of 53 vascular plant species from 34 families were documented, with angiosperms accounting for 96% and dicots being dominant. Endemic and threatened species such as Rotala malabarica and Utricularia cecilii highlight the site's conservation value. Climate data from 2019 to 2023 reveal increasing summer temperatures, warmer winter nights, and erratic monsoon rainfall, indicating shifting ecological conditions. Soil analysis showed slightly acidic pH, with high nutrient variability and elevated iron and manganese levels suggestive of anthropogenic influence. Water analysis revealed low TDS(79-89ppm), acidic pH (5.7-5.8), and slightly improved quality in 2023. These findings emphasize the biodiversity, the endemic plant diversity, ecological sensitivity, and vulnerability to climate change and anthropogenic pressures, calling for urgent, adaptive conservation strategies.

The role of air pollutants in the climate alterations of the North Central region of Maharashtra was analysed with a focus on predicting the Air Quality Index, a crucial tool for managing air quality in both residential and industrial areas. A two-year study assessed air quality by analysing gaseous pollutants such as Sulfur Dioxide(SO2), Nitrogen Dioxide(NO2), and particulate matter(PM10&PM2.5).Pollutant concentration were estimated using satellite data from Sentinel-5P and OMI/Aura, supplemented by ground based measurement. These efforts highlight the importance of continuous monitoring and prediction to combat the growing threat of air pollution in diverse environments. Spatial and temporal variations in pollutant levels, with higher concentrations were consistently observed in industrial zones as compared to residential areas. Statistical correlation analysis was conducted to establish correlations between satellite and in-situ measurements, validating the manoeuvre of remote sensing technologies for air quality monitoring. The findings emphasize the importance of a multifaceted approach, integrating satellite observations with ground-based data, for enhanced air quality monitoring and management strategies.

Soil and water contamination by heavy metals, such as chromium, poses a significant food safety concern. Scientists are suggesting various remedial strategies to address this burning problem worldwide. Chromium-VI causes detrimental morphological, physiological and metabolic impacts on plant system. In this research, we examined how citric acid influences the reduction of stress caused by Cr-VI stress in mung bean (Vigna radiata) seedlings. Results showed that Cr exposure led to diminished plant growth, decrease in the photosynthetic pigment levels and antioxidant enzyme activity. Addition of citric acid with chromium improved shoot and root length, total chlorophyll, chlorophyll a, chlorophyll b, carotenoids, anthocyanin, total sugar and reducing contents, phenol and flavonoid levels in plants. Furthermore citric acid supplementation increases ROS scavenging enzyme activities while proline, MDA and H2O2 levels declined. These results concluded that citric acid boosted the antioxidant system of test seedlings to diminish the toxicity of Chromium-VI. Hence, application of exogenous citric acid might be a useful strategy for alleviating Cr-VI toxicity in mung bean seedlings in Cr contaminated field.

The transfer of residents from rural areas to cities, the resulting decline in rural populations, and the ways in which communities adapt to these changes are taken into consideration of urbanization. Surface water quality and quantity are also impacted by increasing urbanization. The biological, physical, and chemical characteristics of water are commonly used to assess its quality. The major objective of this study is to ascertain how urbanization impacted the surface water's physicochemical properties in Mangalore—the Gurupura and Netravati rivers—which are used for drinking. To determine whether the surface water characteristics of the Netravati and Gurupura rivers in the Dakshina Kannada District, Karnataka, are suitable for household and drinking use in the city of Mangalore, a thorough monitoring program was conducted. The monitoring took place in before-monsoon, after the-monsoon, monsoon seasons of 2018 and 2019. Eighty-four surface water samples from the Gurupura and Netravati rivers were analyzed for a number of physicochemical factors. Majority of the metrics are within the WHO and BIS allowed ranges after the monsoon season, because of the increase in fresh rainwater during and after the monsoon. The Weighted Arithmetic Index (WAI) method was applied to categorize the quality of surface water. According to this method, Five categories are utilized to classify surface water quality, Such as: Excellent (0 to 25), Good (26 to 50), Bad (51 to 75), Very Poor (76 to 100), and Unfit for Consumption (more than 100). Considering the outcomes of the Weighted Arithmetic Index (WAI) method, samples of surface water collected during the monsoon season are of good quality.