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Forecasting of load is essential for operating power systems. India recently witnessed one of the worst power crisis with the highest ever power demand of 207 GW on April 29, 2022. The demand in the month of May and June 2022 was estimated to reach 215 GW. The peak demand this year 2023, according to the electricity ministry, is predicted to be around 230 GW from April to June. The inability to meet certain fundamental issues as power can take a toll on any country's economy. Proper prediction helps in proper decision making and planning. The main objective of this paper is to predict day ahead electrical load demand for Assam. Statistical and Machine Learning Algorithms has been studied. The study has been carried out using real-time data for the years 2016, 2017 and 2018. The paper presents a detailed analysis of the different hyper parameters of the deep learning models and their effect is seen on the learning efficiency. A novel stacked forecasting model is proposed using neural networks as base learners and CatBoost as the meta-learner. The performance of the proposed model has been evaluated and compared with individual models in terms of training time and accuracy using different error metrics namely MAE, MSE, RMSE, MAPE and R2 score. A comparison of the proposed prediction model with the prediction models available in literature has been presented. The conclusion states that both the statistical and machine learning algorithms used in this study act as useful tools for daily load forecasting with considerable accuracy; yet machine learning algorithm outperforms the statistical methods. The entire work has been done in Google Colaboratory using Python as the programming language. [ABSTRACT FROM AUTHOR]

Clean and sustainable energy holds preeminent importance from a socio-environmental standpoint and can be achieved through the implementation of a hybrid renewable energy system (HRES). As well as ensuring the stable and reliable operation of power systems amidst the increasing integration of renewable energy sources, precise source forecasting becomes indispensable. Thus, this paper presents a pioneering HRES design incorporating photovoltaic (PV), wind turbine (WT), and biogas generator (Bio) technologies, wherein animal manure is utilized as biomass for the sustainable valorization of animal waste. The preliminary objective of this study is to address the prevailing gaps to attain sustainable energy production that is both cost-optimal and technically efficient. Consequently, this paper investigates source forecasting through time series modeling, and assesses the techno-environmental and economic viability of HRES (both off-grid and on-grid) within the northeastern state of India, specifically focusing on the case study of the Cachar district in Assam state. Moreover, real data analysis is conducted to model and optimize the hybrid system. The findings reveal promising outcomes in terms of cost, emissions, and electrical energy potential, in which the optimal configuration PV/Bio with grid results in a net present cost (NPC) of 0.659 M$, cost of energy (COE) of 0.00684 $/kWh, and CO2\documentclass[12pt]{minimal}\usepackage{amsmath}\usepackage{wasysym}\usepackage{amsfonts}\usepackage{amssymb}\usepackage{amsbsy}\usepackage{mathrsfs}\usepackage{upgreek}\setlength{\oddsidemargin}{-69pt}\begin{document}$$_2$$\end{document} emission of 2368 kg/yr. For the off-grid, the optimal configuration PV/Bio/Battery obtained with NPC of 2.49 M$, COE of 0.218 $/kWh, and CO2\documentclass[12pt]{minimal}\usepackage{amsmath}\usepackage{wasysym}\usepackage{amsfonts}\usepackage{amssymb}\usepackage{amsbsy}\usepackage{mathrsfs}\usepackage{upgreek}\setlength{\oddsidemargin}{-69pt}\begin{document}$$_2$$\end{document} emission of 346 kg/yr. The analyzed results of the off-grid case are compared and validated with existing literature on different energy economics with optimum configurations. The obtained optimum system is more cost-effective than the existing systems in the literature. Furthermore, a sensitivity analysis is performed to assess the system’s robustness. Finally, this study endeavors to project a future power system for one of the prominent regions in Assam, an Indian state. [ABSTRACT FROM AUTHOR]

An environmental geographical study involves the relief aspects of the geographical unit. Relief analysis of a geographical unit includes relative relief, slope gradient, steepness, and drainage characteristics. The study area selected for the study is a part of the upper Jiadhal drainage basin consisting of 370.63 sq. km of area. It is a young river system (6th order) with lots of sediment carrying capacity and intensive flood frequencies. In this study, the relief morphology of the upper Jiadhal basin is undertaken observing its unique characteristic of large sediment supply causing flood problems in lower basin areas. Open source Landsat: L5135041_041200901113_MTL, TA6RFR_A012986-20,190,901 data from Bhuvan (ISRO) was accessed by ArcGIS tools. It focused that the upper catchment is more influential by environmental problems rather than human except deforestation activities, as there is very less settlement due to no communication route to the interior catchments of the basin. The mainstream of Sido occupies forth (4th) order stream, Sika and Siri are of fifth (5th) order and Jia of sixth (6th) order stream contained to drain the lower basin. The results revel that, the landscape is prone to erosion mainly due to physical and climatic factors and prominently dominated by human intervention due to agro-forestry and could be mitigated with certain specific measures on a location basis including structural engineering measures and watershed management techniques in the degraded areas for the sustainability of the basin. The early studies in this region include the lower basin of the river system, due to inaccessibility. The area is newly demarcated to a different administrative district of Arunachal Pradesh (Lower Siang) and thus in near future more anthropogenic activities would active in the upper catchment, which may influence the environment stability. So the upper catchment management would be a prime concern for the environmentalist in near future. [ABSTRACT FROM AUTHOR]

Background: Operational large-scale flood monitoring using publicly available satellite data is possible with the advent of Sentinel-1 microwave data, which enables near-real-time (at 6-day intervals) flood mapping day and night, even in cloudy monsoon seasons. Automated flood inundation area identification in near-real-time involves advanced geospatial data processing platforms, such as Google Earth Engine and robust methodology (Otsu's algorithm). Objectives: The current study employs Sentinel-1 microwave data for flood extent mapping using machine learning (ML) algorithms in Assam State, India. We generated a flood hazard and soil erosion susceptibility map by combining multi-source data on weather conditions and soil and terrain characteristics. Random Forest (RF), Classification and Regression Tool (CART), and Support Vector Machine (SVM) ML algorithms were applied to generate the flood hazard map. Furthermore, we employed the multicriteria evaluation (MCE) analytical hierarchical process (AHP) for soil erosion susceptibility mapping. Summary: The highest prediction accuracy was observed for the RF model (overall accuracy [OA] > 82%), followed by the SVM (OA > 82%) and CART (OA > 81%). Over 26% of the study area indicated high flood hazard-prone areas, and approximately 60% showed high and severe potential for soil erosion due to flooding. The automated flood mapping platform is an essential resource for emergency responders and decision-makers, as it helps to guide relief activities by identifying suitable regions and appropriate logistic route planning and improving the accuracy and timeliness of emergency response efforts. Periodic flood inundation maps will help in long-term planning and policymaking, flood management, soil and biodiversity conservation, land degradation, planning sustainable agriculture interventions, crop insurance, and climate resilience studies. [ABSTRACT FROM AUTHOR]

Preservatives are used to increase the shelf life of any product for a very long time, yet they are extremely detrimental to human health when used in food. The use of preservatives like formaldehyde by fishermen and fish merchants for prolonged preservation of fish during sales and transportation has recently become problematic and threat to human health. Therefore, the goal of the current investigation was to determine the presence of formaldehyde in the fish sold at fish markets in Nagaon, Assam. The present investigation indicates the contamination of fish with formaldehyde in the local fish markets of Nagaon district. The fish that show the presence of formaldehyde are imported (challani) and out of the whole fish sample collection (challani/imported), Labeo rohita, Catla catla indicates the highest positive result, with 35.96% and 48.44% respectively from the 114 Labeo rohita to 64 Catla catla samples. Additionally, the results for Ompok pabda, Pangasius pangasius, Hilsa ilisha, and Piaractus brachypomus are all positive, with Hilsa ilisha showing a positive result of 100% from their whole sample collection. However, the local fish like Labeo gonius, Cirrhinus reba, Ctenopharyngodon idella, Cirrhinus mrigala, and Hypophthalmicthys nobilis fish species have shown 100% negative results for formalin detection, indicating that their samples are formalin-free. Since formaldehyde is harmful to human health, better methods and techniques should be adopted for the preservation of fish for commerce and storage. Strict regulations should be put in place to limit the use of these hazardous chemical substances. [ABSTRACT FROM AUTHOR]

The presence of heavy metals in agricultural soils has become a critical concern in the face of increased environmental scrutiny, highlighting the relationship between human and natural impacts on our land. This study focused on examining heavy metal contamination levels including Copper (Cu), Chromium (Cr), Cobalt (Co), Lead (Pb), Iron (Fe), Zinc (Zn), Nickel (Ni) and Manganese (Mn) conducting an ecological risk assessment in the Morigaon district's paddy fields, which are characterized by disturbed soils. Undisturbed playground soils of the Morigaon district were taken as control. Based on the averages of all locations and the corresponding contamination factor (Cf) for paddy field, it was found that the soil's Cr (0.56 to 0.84), Fe (0.11 to 0.13), Mn (0.38 to 0.78), and Zn (0.35 to 0.65) contamination is low, with Cf < 1 for all seasons. Observed levels of Cu, Ni, and Pb showed moderate contamination throughout seasons, with contamination factors (Cf) ranging from 1 to 3. Meanwhile, Co exhibited a greater amount of contamination in the disturbed soil, with Cf ranging from 3 to 6, indicating significant contamination. Higher degree of contamination (CD) of the sampling sites (10.71 to 14.72) might have been due to metal contamination, especially Co, Ni and Pb. Undisturbed soil showed a comparatively lesser degree of contamination because of an absence of physical or chemical disturbances. In particular, Ni contents of disturbed and undisturbed sites were excessively higher than the worldwide average. Significant variations from global averages were particularly noted for Co and Pb. Conversely, Cr, Mn, and Zn demonstrated minimal variations when compared to these averages. Additionally, metrics such as Enrichment Factors (EF), Potential Ecological Risk Index (PERI) and Ecological Risk Index (Er) were elevated in the disturbed soils relative to their undisturbed counterparts. The findings indicated that anthropogenic activities have significantly negatively influenced the Morigaon district paddy field's soil quality and agriculture. [ABSTRACT FROM AUTHOR]

The Assam lemon is a highly valued Citrus cultivar known for its unique aroma, flavor, and appearance. This study aimed to investigate the morphological, seeding pattern and biochemical variations within 132 populations of Assam lemon from across 22 districts of Assam along with the control samples, with the objective to offer comprehensive understanding that could facilitate the improvement of breeding programs and further improvement of this important cultivar. Clustering based on UPGMA algorithm for morphological and seeding pattern data were analysed at population level, revealed two major clusters, where all the populations of Upper Assam districts were in the same cluster with the original stock (control population). The populations from Tinsukia and Dhemaji districts displayed more close similarities with the control population in comparison to populations of Upper Assam districts. Another interesting observation was regarding flowering patterns, while populations from Upper Assam districts excluding Golaghat district displayed both bisexual and unisexual flowers with less concentration of unisexual flowers, other remaining districts had bisexual and unisexual flowers of almost equal concentration. Unisexual flowers contained only the male reproductive organs with 40 anthers, while bisexual flowers had 36 anthers. Seeding patterns were examined across the districts, and it was found that populations from Tinsukia, Dhemaji, Lakhimpur, Dibrugarh, Jorhat, and the control population exhibited seedless characteristic while populations from other selected districts displayed a combination of seedless and seeded traits. Interestingly, Golaghat district appears as the linking district and showed availability of both seeded and seedless Assam lemon fruit, connecting the regions of Barak valley, Central, Lower, North and Upper Assam. Biochemical analysis showed significant variations across districts, however, the populations from Dhemaji, Tinsukia, Lakhimpur, Dibrugarh, and Jorhat districts displayed similarity with the control population. The study also investigated variability in soil nutrient content revealing substantial variation among the populations studied. This comprehensive investigation provides valuable insights into the morphological, seeding pattern, and biochemical diversity within the Assam lemon cultivar. These findings can be instrumental in breeding programs to enhance the cultivar, particularly in producing high-quality seedless fruits to meet consumer demands. [ABSTRACT FROM AUTHOR]