Local Climatic Conditions Research Articles

The effect of local climatic conditions on household consumption: a case study of South Africa

The article explores the causal effect of local climate conditions on household consumption in South Africa. The climatic conditions are represented by monthly average temperature and precipitation. The study utilises the nationally representative 2017 National Income Dynamics Study (NIDS), wave 5 data and 2017 Climate Research Unit (CRU) climate data. The parsimonious quantile regression shows that climatic conditions (precipitation, temperature, wet days, and cloud cover) impact household per capita consumption. The quadratic quantile regression model analysis shows that household per capita consumption is convex in precipitation. Below the turning point, increased precipitation is associated with decreased household per capita consumption. Above the turning point, increased precipitation is related to increased household per capita consumption. Regions that receive very low precipitation or experience extreme temperatures (very cold or very hot) require tailor-made interventions to alleviate consumption. When we control for household characteristics, the impact of climatic conditions on household per capita consumption is weak. Providing inclusive development policies and programmes can mitigate the impact of climatic conditions on household per capita consumption.

Central Asia's desertification challenge: Recent trends and drives explored with google earth engine

Achieving land degradation neutrality (LDN) is considered critical to achieving sustainable development goals. However, further research and an improved large-scale desertification assessment framework are needed. We constructed a comprehensive land desertification status index (LDSI) to assess desertification and its driving mechanisms in Central Asia from 2001 to 2020. Our spatial distance models and principal component analysis were verified by combined field data. The results indicate that desertification levels in Central Asia fluctuated, decreasing from south to north and increasing from west to east. The extent of increased desertification (45.75%) and recovery (45.65%) were nearly equivalent. According to optimal parameters-based geographical detectors, climate factors are the main contributors to desertification, the most significant being reference evapotranspiration. We also found regional differences in the driving mechanisms of desertification. Based on Theil–Sen, Mann–Kendall, and Hurst tests, future desertification intensification of 9.69% is possible, with hotspots mainly in northwestern Central Asia, while 9.73% restoration may occur in other areas. The findings have relevance for achieving LDN. Policymakers should monitor the impact of global climate change and develop recovery measures based on comprehensive consideration of local climate, soil, and terrain conditions.

ORGANIC FARMING: DEVELOPMENT PROSPECTS IN RUSSIA, TAKING INTO ACCOUNT THE INTERNATIONAL MARKET

The production of organic agriculture products has become one of the most growing areas of economic activity, with projected annual growth of 10-12%. At the same time, the demand for organic products significantly exceeds the supply, which is largely due to the lack of land that can be allocated for this production. Russia, which has significant areas of virtually unused land on which mineral fertilizers and pesticides have not been used for a long time, reaching 19.7 million. ha, has a significant potential for development in this direction. At the same time, considering that a significant part of unused territories is located within the zone of risky agriculture, and also has soils with a low level of natural fertility, degraded, arid, waterlogged, etc., the actual amount of land resources that can be involved in organic agriculture is significantly less. For the most complete introduction into circulation of unused agricultural lands, it is necessary to increase the knowledge intensity and manufacturability of organic agriculture, for which research work in the following areas is highly relevant: 1) optimization of the balance of humus and nutrients in soils, 2) breeding and seed production of crops for organic agriculture, 3) development of biological products for disease and pest control, 4) development of optimal farming systems taking into account local soil and climatic conditions, 5) optimization of agricultural landscapes based on increasing the diversity of agricultural land use. Along with the involvement of unused lands in the organic production system, the development of the industry largely depends on the system of training qualified personnel in this area, which should take into account the specifics of the technologies used, which differ significantly from traditional farming systems. To do this, it is necessary to update existing professional standards, which should include generalized labor functions related to the development and implementation of organic farming technologies, as well as knowledge and skills in organizing organic production. On the basis of updated professional standards, universities should form new professional competencies and a corresponding set of academic disciplines. The personnel training system for the industry should include various levels of training: agricultural classes, higher education, additional professional education.

Spatio‐temporal shift in body size and plumage coloration is associated with the magnitude of climate change in a cosmopolitan owl

AbstractAimClimatic gradients shape geographic variation in phenotypic traits that are involved in animal thermoregulation. Therefore, increasing temperatures under global warming are expected to cause change over time in traits that show predictable spatial patterns according to environmental clines (body and appendage size, tegument coloration), as well exemplified by biogeographic rules and shown by increasing literature at a local scale. However, whether temporal shifts in phenotypic traits vary spatially according to the magnitude of the change in local climatic conditions is still unknown.LocationWorld.TaxonBarn owl species complex (Tyto alba group).MethodsBy using thousands of museum specimens collected across the globe from 1901 to 2018, we calculated within‐population change over time in wing length, bill length and melanin‐based plumage coloration and examined whether these trends differed across geographic regions, latitudes and gradients of climate changes.ResultsWe showed that populations exposed to an increasing warmer climate were subjected to a more marked decrease in body size, as gauged by wing length, and also absolute bill length that displayed a similar, although less steep, pattern of shrinking over time. In addition, phaeomelanin‐based ventral plumage colour has become paler in regions where the climate changed into warmer and drier, and darker where both temperature and precipitation increased.Main ConclusionsThese trends are generally coherent with the predictions based on Bergmann's and Gloger's rules, but not Allen's rule, and suggest that temporal shifts in body size and tegument colour depend on the magnitude of the alteration in climatic conditions, with populations living in regions where the climate has changed the most that are subjected to more marked phenotypic changes. Spatio‐temporal variation in climate has driven within‐species phenotypic clines, and it is expected to increase differences among populations according to the predicted further climate change.

Evaluation of energy performance and ecological benefit of free-cooling system for data centers in worldwide climates

Water-side economizer (WSE) is an effective free-cooling solution aiming to enhance the natural cooling duration and in turn reduce the cooling-energy consumption of data centers. However, the system's performance is constrained by the limited understanding of its control mechanisms and the influence of local climatic conditions on its free-cooling capabilities. To overcome these limitations, a thermodynamic model of the WSE system with control strategies is provided and its adaptability performance in diverse worldwide locations is systematically evaluated. Modelica-based models of chiller plants and control strategies are firstly developed, and then the energy consumption and ecological benefit of the WSE system are investigated via large-scale simulations in worldwide climates. The performance indicators and application potential of the system are demonstrated through visualization maps. The analysis reveals significant energy savings potential of the WSE system, with the capacity to reduce annual cooling energy consumption of data centers by 4.4–33.7 % in hot to marine zones, and even by a remarkable 62.6 % in plateaus and cold zones. Furthermore, it is observed that every 1 °C increase in outdoor air temperature can reduce energy efficiency ratio by 1.3–8.7 % while simultaneously increase PUE by 0.3–1.0 %. The ecological benefit results revealed that the WSE system can effectively harness larger quantities of stable free-cooling resources in mixed and cool climate zones, exceeding its capabilities in hot and warm regions. These results offer valuable insights for the impact of climate on the energy and ecological benefits of WSE system for data center, which can be helpful to guide the design or retrofit of such cooling systems in specific locations, presenting an immense opportunity to maximize cooling-energy savings.

Drosophila suzukii (Diptera: Drosophilidae): An exotic pest of small fruits in Cabernet Sauvignon vineyards of Santa Catarina State, Brazil

To characterize the annual Drosophila suzukii population dynamics in vineyards in Santa Catarina, Brazil, and to relate it to the local climatic conditions, we conducted a weekly monitoring survey in four commercial vineyards of Cabernet Sauvignon, between November 2018 and October 2020. The D. suzukii population was monitored both inside the vineyards and the surrounding forest border and correlated with climate variables. To capture the insects, plastic pot traps baited with the attractive Droskidrink were used. The traps were inspected weekly throughout two years, and the captured insects were counted and identified. The relationship between population fluctuations and climate variables was analyzed with multiple regression models. The numbers of D. suzukii captured in the forest borders were typically much higher than those into the vineyards, but in certain periods of the year, D. suzukii adults was indeed detected inside all vineyards. The number of captures varied between the years of monitoring, where the first year had higher numbers of adults captured for all monitored sites. The D. suzukii population numbers in all monitored vineyards were positively correlated with high relative humidity. The results show that there is indeed a significant risk of crop damage due to D. suzukii infestations in vineyards, but only during a distinct period during the ripening of the grapes. We recommend that farmers specifically perform D. suzukii management in their vineyards during this relatively short period of the year.

Optimization of Domestic Rainwater Harvesting Systems in Guangxi and Guangdong Provinces, Southern China

The optimization of domestic rainwater harvesting systems (RWHS) in the rural areas of Guangxi and Guangdong provinces, Southern China, offers a viable solution to address water scarcity and enhance water security. This research focuses on designing, implementing, and evaluating RWHS tailored to local climatic, topographical, and social conditions. By capturing and storing rainwater, these systems reduce reliance on groundwater, improve local water management, and provide a sustainable water source for domestic and agricultural use. Key components of an effective RWHS include rooftop catchments, gutters, downpipes, storage tanks, and filtration units. The study also involves community engagement, training, and capacity-building to ensure the long-term sustainability and effectiveness of the systems. Performance monitoring and data collection on water usage patterns and system reliability are essential to optimize the RWHS. The economic and social impacts, as well as the environmental benefits, are assessed to provide comprehensive insights into the benefits and challenges of RWHS implementation. Policy recommendations and support mechanisms are proposed to promote the widespread adoption of RWHS in rural communities, enhancing water security and sustainability.

Effect of Integrated Nutrient Management (INM) on Growth, Yield and Quality of Okra (Abelmoschus esculentus L.) cv. ‘Arka Anamika’

The present investigation was carried out at Agricultural Research Farm, Department of Horticulture, S.G.V.U., Jaipur (Rajasthan) to study the effect of INM on growth, yield and quality of Okra (Abelmoschus esculentus L.) cv. ‘Arka Anamika’ during Rabi season of the year 2022-23. The experiment was laid down in RBD which consisted 9 treatment combinations viz; Control (T0), 100% RDF (T1), 100% RDF + Vermicompost @5t/ha (T2), 100% RDF + Poultry manure @2t/ha (T3), 100% RDF + Neem cake @2t/ha (T4), 50% RDF + Vermicompost @5t/ha (T5), 50% RDF + Poultry Manure @2t/ha (T6), 50% RDF + Neem cake @2t/ha (T7), 50% RDF + Vermicompost @5t/ha + Poultry Manure @2t/ha + Neem cake @2t/ha (T8) and treatments were replicated three times. Appraisal of the result indicated that the influence of organic and inorganic fertilizers on important parameters like vegetative growth, yield and quality of Okra were significantly influenced by INM under local agro climatic conditions. The treatment (T8) had a significant effect on various vegetative growth, yield and quality parameters, and the results revealed that the maximum plant height plant height at 30, 60 and 90 DAS, leaves per plant, days taken to 50% flowering, flowers per plant, fruit length, fruit diameter, fruit per plant, fruit yield, TSS, Ascorbic acid and Titrable Acidity (%) were recorded in T8. The minimum values of growth, yield and quality parameters were recorded in the control (T0). Results further indicated that the highest (3.06) benefit: cost ratio was observed in T8. Whereas, the lowest benefit: cost ratio (1.07) was recorded under control.

Investigating the Impact of Large Lakes on Local Precipitation: Case Study of Lake Urmia, Iran

Large lakes face considerable challenges due to human activities and climate change, impacting local weather conditions and ecosystem sustainability. Lake Urmia, Iran’s largest lake and the world’s second-largest saltwater lake, has undergone a substantial reduction in water levels, primarily due to drought, climate change, and excessive irrigation. This study focuses on the potential repercussions on local climate conditions, particularly investigating the impact of moisture sources, evaporation from lake surfaces, and evapotranspiration from agricultural activities, on local convection rainfall. The prevailing westerly winds in the basin suggest a hypothesis that this moisture is transported eastward within the basin, potentially leading to local precipitation as it ascends to higher altitudes near the eastern basin border. To validate this hypothesis, climate data from 1986 to 2017 from the Sarab meteorological station (east of the lake basin, influenced by local precipitation) and Saqez meteorological station (south of the basin, unaffected by local precipitation) were analyzed. The impact of lake water level reduction was assessed by categorizing data into periods of normal lake conditions (1986–1995) and water level reduction (1996–2017). Additionally, the MSWEP global precipitation product was used to examine the precipitation distribution in the entire basin over the entire period and sub-periods. The findings indicate Lake Urmia’s significant influence on convective rainfall in the eastern basin, especially during the summer. Despite decreasing lake levels from 1996 to 2017, convective rainfall in the eastern basin increased during the summer, suggesting intensified agricultural irrigation, particularly in hot seasons.

The role of environmental gradients and microclimates in structuring communities and functional groups of lizards in a rainforest-savanna transition area.

Environmental heterogeneity poses a significant influence on the functional characteristics of species and communities at local scales. Environmental transition zones, such as at the savanna-forest borders, can act as regions of ecological tension when subjected to sharp variations in the microclimate. For ectothermic organisms, such as lizards, environmental temperatures directly influence physiological capabilities, and some species use different thermoregulation strategies that produce varied responses to local climatic conditions, which in turn affect species occurrence and community dynamics. In the context of global warming, these various strategies confer different types of vulnerability as well as risks of extinction. To assess the vulnerability of a species and understand the relationships between environmental variations, thermal tolerance of a species and community structure, lizard communities in forest-savanna transition areas of two national parks in the southwestern Amazon were sampled and their thermal functional traits were characterized. Then, we investigated how community structure and functional thermal variation were shaped by two environmental predictors (i.e., microclimates estimated locally and vegetation structure estimated from remote sensing). It was found that the community structure was more strongly predicted by the canopy surface reflectance values obtained via remote sensing than by microclimate variables. Environmental temperatures were not the most important factor affecting the occurrence of species, and the variations in ecothermal traits demonstrated a pattern within the taxonomic hierarchy at the family level. This pattern may indicate a tendency for evolutionary history to indirectly influence these functional features. Considering the estimates of the thermal tolerance range and warming tolerance, thermoconformer lizards are likely to be more vulnerable and at greater risk of extinction due to global warming than thermoregulators. The latter, more associated with open environments, seem to take advantage of their lower vulnerability and occur in both habitat types across the transition, potentially out-competing and further increasing the risk of extinction and vulnerability of forest-adapted thermoconformer lizards in these transitional areas.

White-nose syndrome, winter duration, and pre-hibernation climate impact abundance of reproductive female bats.

White-nose syndrome (WNS) is an infectious disease that disrupts hibernation in bats, leading to premature exhaustion of fat stores. Though we know WNS does impact reproduction in hibernating female bats, we are unsure how these impacts are exacerbated by local climate factors. We compiled data from four southeastern U.S. states and used generalized linear mixed effects models to compare effects of WNS, pre-hibernation climate variables, and winter duration on the number of reproductive females in species across the range of WNS susceptibility. We predicted we would see a decline in the number of reproductive females in WNS-susceptible species, with the effect exaggerated by longer winter durations and pre-hibernation climate variables that lead to reductions in foraging. We found that the number of reproductive females in WNS-susceptible species was positively correlated with pre-hibernation local climate conditions conducive to foraging; however, WNS-susceptible species experienced an overall decline with the presence of WNS and as winter duration increased. Our long-term dataset provides evidence that pre-hibernation climate, specifically favorable summer weather conditions for foraging, greatly influences the reproduction, regardless of WNS status.

Energy poverty in EU: Using regional climatic conditions and incidence of electricity prices to map vulnerability areas across 214 NUTS2 European regions

The rising political instabilities and the associated variations in energy prices have recently amplified the existing debate on energy poverty. Generally defined as the inability to afford enough energy services to live a comfortable life, energy poverty represents a serious issue affecting multidimensional elements of life. To address disparities and to achieve the 7th goal of the 2030 Agenda, EU Member States have been requested to track energy poverty within the National Energy and Climate Plans. The lack of a commonly adopted methodological approach makes however difficult to compare the energy poverty risks. To address this gap, this paper proposes, for the first time, an energy poverty vulnerability indicator that can be used to investigate the differences across NUTS2 European regions. By combining data on regional income, electricity prices and local climatic conditions, the proposed methodology uses a threshold approach to maps vulnerability risks for the years 2010 and 2020. Results show that in 2010 15% of the considered households classified into the highest vulnerability risk and by 2020, 40 additional regions moved to a higher category of risk. Mediterranean countries have been the most affected with extensive climatic and price incidence changes. The proposed indicator can support the definition of policies aiming to reduce regional disparities and improve the average European trends.

Biochemical Characterization of Microsymbionts Associated with Zornia gibbosa Span. in Central Aravalli Range

In current scenario, with increasing world population there is a strong demand to enhance crop productivity to feed the population. Characterization of indigenous rhizobia is very crucial for developing biofertilizers tailored to local climatic conditions, with the goal of increasing food production without excess use of chemical fertilizers. In the present investigation 44 root nodule bacterial strains or microsymbionts were isolated from root nodules of Zornia gibbosa growing in Central Aravalli region. These isolated RNB strains were examined for their phenotypic and biochemical activities such as salt tolerance, pH tolerance, bromo thymol blue (BTB) reaction, catalase activity, oxidase activity, cellulase activity, amylase production, indole production, citrate utilization and gelatin hydrolysis. All tested isolates showed significant diversity in their phenotypic and biochemical activities. The majority of the strains were limited to a tolerance of up to 3% NaCl concentration; however, strains Z2, Z13, Z14, Z15, Z21, and Z22 demonstrated tolerance up to a 5% NaCl concentration. A total of 29 isolates were able to grow within the pH range of 5-10. Few isolates showed positive results for citrate utilization (Z4, Z18, Z22, Z32 and Z44) and amylase production (Z4, Z6, Z21, Z25 and Z42). In this study only one isolate Z22 showed indole production. Conversely, when assessing various enzyme activities such as cellulase, catalase, protease, and gelatinase, all the isolates demonstrated considerable diversity. This type of study is essential for developing superior biofertilizers containing indigenous bacterial strains to enhance production.

The effect of explicit convection on simulated malaria transmission across Africa.

Malaria transmission across sub-Saharan Africa is sensitive to rainfall and temperature. Whilst different malaria modelling techniques and climate simulations have been used to predict malaria transmission risk, most of these studies use coarse-resolution climate models. In these models convection, atmospheric vertical motion driven by instability gradients and responsible for heavy rainfall, is parameterised. Over the past decade enhanced computational capabilities have enabled the simulation of high-resolution continental-scale climates with an explicit representation of convection. In this study we use two malaria models, the Liverpool Malaria Model (LMM) and Vector-Borne Disease Community Model of the International Centre for Theoretical Physics (VECTRI), to investigate the effect of explicitly representing convection on simulated malaria transmission. The concluded impact of explicitly representing convection on simulated malaria transmission depends on the chosen malaria model and local climatic conditions. For instance, in the East African highlands, cooler temperatures when explicitly representing convection decreases LMM-predicted malaria transmission risk by approximately 55%, but has a negligible effect in VECTRI simulations. Even though explicitly representing convection improves rainfall characteristics, concluding that explicit convection improves simulated malaria transmission depends on the chosen metric and malaria model. For example, whilst we conclude improvements of 45% and 23% in root mean squared differences of the annual-mean reproduction number and entomological inoculation rate for VECTRI and the LMM respectively, bias-correcting mean climate conditions minimises these improvements. The projected impact of anthropogenic climate change on malaria incidence is also sensitive to the chosen malaria model and representation of convection. The LMM is relatively insensitive to future changes in precipitation intensity, whilst VECTRI predicts increased risk across the Sahel due to enhanced rainfall. We postulate that VECTRI's enhanced sensitivity to precipitation changes compared to the LMM is due to the inclusion of surface hydrology. Future research should continue assessing the effect of high-resolution climate modelling in impact-based forecasting.

Envelope retrofits for enhancing thermal comfort in detached houses in hot semi-arid climatic conditions: A year-long monitoring and simulation study

Retrofitting residential buildings could substantially reduce the sector's energy and carbon footprint and provide significant economic benefits in the long run. Building retrofits must be urgently developed and promoted in India, where most residences are constructed without any consideration of energy efficiency due to the lack of a mandatory residential energy code. However, building retrofits must be devised considering the local construction practices and climatic conditions since an improper retrofit can deteriorate the indoor environment and even increase the building's energy consumption. Therefore, through year-long monitoring and simulations of the comfort conditions of a room inside a detached single-story house, this investigation evaluated different envelope retrofit options for improving it in India's hot semi-arid climate.The results showed that the room's indoor environment (without the retrofit) was comfortable for only 26–43 % of the year, depending on the room's configuration, with the roof being the major contributor to the heat gain and the floor and external walls largely contributing to heat losses. The comfort duration increased by 6–21 percentage points annually by applying cool/super-cool roof paints since they significantly reduce the roof's heat gain. Similar comfort enhancements could also be obtained by insulating the roof or the entire envelope, mainly due to reduced roof heat gains. However, insulating the walls alone deteriorated the comfort conditions since it became difficult for the heat to escape the room. Overall, applying cool/super-cool roof paints was recommended over other studied options since they provide substantial comfort benefits with low cost and easy implementation.

Investigating the Factors Impacting the Performance of Small and Medium-Scale Irrigation Construction Projects in Eastern Amhara

Recently due to their economic value, there has been a rapid increment of water work construction projects in Ethiopia. However, there is a problems regarding their performance, like cost overrun, time overrun, low productivity & low quality. The same is true for water work projects that are constructed by Amhara Water Works Construction Enterprise. This research work aims to identify and evaluate the main factors affecting the performance of small & medium-scale irrigation construction projects in eastern Amhara region-Ethiopia. To achieve the objectives of this research study, five irrigation construction projects were targeted as the population of the study and both qualitative & quantitative data were collected by desk study, questioner survey, and interviews. Total 75 questionnaires were distributed to the respondents and out of these 75 distributed questionnaires, 70 (93.33%) questionnaires were returned. The data collected were analysed using SPSS version 25 and the significance factors were ranked by using their Relative Importance Index (RII). The results show that the top ten critical factors that affecting performance agreed upon by all parties were an escalation of material prices, unavailability of resources, number of disputes between owner and project parties, quality of equipment or machinery and raw materials, unavailability of competent staff, financial constraints, material and equipment cost, local climate conditions cost of variation orders and leadership skills for project manager.

Detecting Nonadditive Biotic Interactions and Assessing Their Biological Relevance among Temperate Rainforest Trees.

AbstractInteractions between and within abiotic and biotic processes generate nonadditive density-dependent effects on species performance that can vary in strength or direction across environments. If ignored, nonadditivities can lead to inaccurate predictions of species responses to environmental and compositional changes. While there are increasing empirical efforts to test the constancy of pairwise biotic interactions along environmental and compositional gradients, few assess both simultaneously. Using a nationwide forest inventory that spans broad ambient temperature and moisture gradients throughout New Zealand, we address this gap by analyzing the diameter growth of six focal tree species as a function of neighbor densities and climate, as well as neighbor × climate and neighbor × neighbor statistical interactions. The most complex model featuring all interaction terms had the highest predictive accuracy. Compared with climate variables, biotic interactions typically had stronger effects on diameter growth, especially when subjected to nonadditivities from local climatic conditions and the density of intermediary species. Furthermore, statistically strong (or weak) nonadditivities could be biologically irrelevant (or significant) depending on whether a species pair typically interacted under average or more extreme conditions. Our study highlights the importance of considering both the statistical potential and the biological relevance of nonadditive biotic interactions when assessing species performance under global change.

Performance optimization of interleaved boost converter with ANN supported adaptable stepped-scaled P&O based MPPT for solar powered applications

Solar energy is the most promising among many renewable energy sources to meet the increasing demand. Photovoltaic (PV) based power generating solutions are expected to gain popularity as a power source for different applications, including independent and grid connected loads, due to their cleanliness, high performance, and high dependability. The efficacy of photovoltaic systems is impacted by several elements, including geographical location, positioning, shadowing effects, and local climate conditions. In order to fulfil the demands of loads, an interleaved boost converter is utilized, which has a reduced number of filters with less stress on the devices. Solar powered systems employ several maximum power point tracking (MPPT) methodologies. However, when there is partial shading, many power peaks arise, which complicates the identification of the overall peak. Although MPPT approaches are designed to measure and maintain the global maximum power point (GMPP), there are still significant oscillations observed around the GMPP with subpar settling time, tracking efficiency, and conversion efficiency. In this work, novel hybrid MPPT technique called artificial neural network supported adaptable stepped-scaled perturb and observe (ANN-ASSPO) method and water cycle optimization based perturb and observe (WCO-PO) have been proposed. Artificial neural network (ANN) has been used to determine the best scaling factor in ANN-ASSPO MPPT. Performance is enhanced in ANN-ASSPO MPPT by using the optimum scaling factor, particularly in situations when the irradiance is rapidly changing/partial shading conditions. Similarly, in WCO-PO MPPT water cycle optimization is used to determine the peak power when the PV panel is subjected to partial shading conditions. The performances of proposed hybrid MPPT ANN-ASSPO and WCO-PO techniques have been compared in terms of power generated, output voltage, average settling time and conversion efficiency. The MATLAB/Simulink tool is employed to carry out the experiment for this study.

Water Colour Changes in High-Elevation Alpine Lakes during 2017–2022: A Case Study of the Upper Orco Valley Catchment

The water resource is severely compromised by climate change, and its availability and quality can no longer be taken for granted, even in places considered pristine, such as mountains. In this study, we evaluated the water colour variability of three artificial mountain lakes located in a relatively small basin (Western Italian Alps) at high elevations, and related this variability to the local climate conditions of the hydrological basin to which they belong. We estimated the dominant wavelength (DW) of lake water from Sentinel-2 acquisitions for the period 2017–2022, performing a chromaticity analysis. We correlated DW with climatic parameters recorded by two automated weather stations. Average DW varies from 497 nm of Serrù Lake and Agnel Lake to 512 nm of Lake Ceresole, where DW varies seasonally (variation of 75–100 nm in one year). During April–July, the DW of Lake Ceresole is significative correlated with air temperatures and snow cover (−0.8 and +0.8, respectively). During August–October, the relationship with temperature decreases to −0.5, and a correlation of 0.5 with the amount of rainfall appears. This work shows that mountain lake waters can exhibit variable quality (expressed here by water colour) in response to meteorological and hydrological conditions and events.

Farm Assist – Comprehensive Scheme Recommendation System for Enhanced Farming

India’s economy and employment are heavily reliant on agriculture. Farm Assist emerges as a groundbreaking digital platform, reshaping how farmers access and leverage agricultural support. This web-based tool stands at the forefront of facilitating farmers with custom-tailored recommendations for agricultural programs and real-time updates on farming news. At its essence, Farm Assist harnesses the power of advanced data processing techniques, including machine learning, to sift through and interpret a diverse range of data specific to each farmer, such as crop varieties, land extent, and local climatic conditions. This approach ensures the delivery of highly relevant and practical scheme suggestions directly applicable to each farmer’s unique situation. The interface of Farm Assist is crafted for simplicity and ease of use, ensuring that farmers of varying digital literacy can navigate and utilize the platform effectively. This aspect is crucial in diminishing the digital barriers commonly encountered in rural farming sectors. Moreover, Farm Assist incorporates a constantly updating feed of agricultural news, equipping farmers with cutting-edge knowledge and practices in the agricultural realm, thus fostering well-informed agricultural decisions and modern cultivation techniques. Key words: Farm Assist, Web-based Dashboard, Scheme Recommendation System, Crop Prediction, Precision Agriculture, Real Time Farming News, Weather Forecast