Excessive Rainfall Research Articles

Seed treatment affected establishment and yield in two pennycress lines

IntroductionOilseed pennycress (Thlaspi arvense L.) is an emerging biofuel crop for use in the aviation industry that has potential as a rotational crop in corn (Zea mays L.)–soybean [Glycine max (L.) Merr.] cropping sequences. Ensuring autumn emergence of pennycress after early broadcast seeding is key because this practice may result in uneven spatial distribution due to the small seed size and variable germination, soil contact, and moisture availability. The objective of this research was to evaluate the impact of five seed treatments and enhancements on autumn establishment in two pennycress lines (MN106NS and tt8-t/ARV1) in broadcast seeding compared with no treatment.MethodsTested treatments were (i) gibberellic acid (GA) soak, (ii) fludioxonil fungicide, (iii) pelleting with diatomaceous earth and a commercial binder, (iv) fungicide plus pelleting, or (v) fungicide plus pelleting with GA added to the binder. Seeds were planted at nine sites in four U.S. states to assess establishment (stand counts and percentage canopy cover) in the autumn and spring and seed yield after maturity.ResultsThe MN106NS line had greater plants m−2 and percent green cover with treatments that included GA compared to the control. Line tt8-t/ARV1 had reduced stands when pelleted compared to the untreated, and establishment was unchanged when treated with GA compared to the untreated. Pelleting treatments without GA were not beneficial for stand establishment of either line. Seed yield for MN106NS was 20% greater than the untreated when treated with GA only or pelleted. Seed yield for tt8-t/ARV1 did not increase over the untreated with any treatment and was reduced by 20%–40% when pelleted.DiscussionThese results suggest minimal benefit of seed treatment and pelleting for the tested lines under broadcast seeding, though black-seeded lines may still benefit from GA treatment. Plant establishment and yield were negatively correlated with total precipitation post-planting, suggesting that excessive rainfall post-planting (>60 mm) may impede establishment when broadcast seeded.

A Comprehensive Review on Climate Change Adaptation Strategies and Challenges in Agriculture

This review examines the impact of climate change on Indian agriculture and adaptation strategies. Climate change, driven by human activities, poses challenges like rising temperatures and extreme weather events. Rising temperatures can induce heat stress in crops, leading to reduced yields and poor quality produce. Farmers use adaptation measures like altering planting dates and developing climate-resilient crops. Changing rainfall patterns, erratic or insufficient rainfall can trigger drought conditions, parching farmlands and causing crop failures. On the other hand, excessive rainfall can result in flooding, which damages crops and soil, disrupting agricultural operations especially during the monsoon. Soil conservation, precision agriculture, and urban food production initiatives promote food security and resource recycling. Addressing water scarcity requires improved irrigation and efficient water management. Climate change affects agricultural pests population and threatening global food security. Various adaptation strategies, including traditional practices, resource-conservation technologies, and socio-economic interventions, are being implemented. Climate-smart agriculture technologies like precision agriculture increase yields and resilience. Success depends on regional suitability, economic viability, and collective implementation. Agriculture operates within a complex socio-ecological system with uncertainties in policy, economics, and climate. Site-specific climate-smart agriculture practices are crucial for smallholders' resilience and food security. Publicly provided agricultural extension services can help adopt these technologies, but barriers like financial constraints and cultural factors must be considered. This review emphasizes the need for comprehensive, context-specific approaches to address vulnerabilities in Indian agriculture to climate change and ensure a sustainable future for food production and smallholder livelihoods.

The association between timing in pregnancy of drought and excess rainfall, infant sex, and birthweight: Evidence from Nepal.

Past research on the impact of climatic events, such as drought, on birth outcomes has primarily been focused in Africa, with less research in South Asia, including Nepal. Existing evidence has generally found that drought impacts birthweight and infant sex, with differences by trimester. Additionally, less research has looked at the impact of excess rain on birth outcomes or focused on the impact of rainfall extremes in the preconception period. Using data from a large demographic surveillance system in Nepal, combined with a novel measure of drought/excess rainfall, we explore the impact of these on birthweight by time in pregnancy. Using survey data from the 2016 to 2019 Chitwan Valley Study in rural Nepal combined with data from Climate Hazards InfraRed Precipitation with Station, we explored the association between excess rainfall and drought and birthweight, looking at exposure in the preconception period, and by trimester of pregnancy. We also explore the impact of excess rainfall and drought on infant sex and delivery with a skilled birth attendant. We used multilevel regressions and explored for effect modification by maternal age. Drought in the first trimester is associated with lower birthweight (β = -82.9 g; 95% confidence interval [CI] = 164.7, -1.2) and drought in the preconception period with a high likelihood of having a male (odds ratio [OR] = 1.41; 95% CI = 1.01, 2.01). Excess rainfall in the first trimester is associated with high birthweight (β = 111.6 g; 95% CI = 20.5, 202.7) and higher odds of having a male (OR = 1.48; 95% CI = 1.02, 2.16), and in the third trimester with higher odds of low birth weight (OR = 2.50; 95% CI = 1.40, 4.45). Increasing rainfall extremes will likely impact birth outcomes and could have implications for sex ratios at birth.

Wind and Water: How Extreme Weather Conditions Impact Residential Real Estate in Developing Countries

The damaging effects of extreme weather is concerning for many countries across the globe. Though the impact of these events on the housing market has been studied extensively, one aspect that remains unexplored is the value of mortgages. Further, there is no clarity on the impact of the specific types of homes. This study analyzed mortgages and apartment values and included residential land sale prices over 16 years for different localities across Jamaica. The analysis revealed that mortgages are adversely affected by excess rainfall while apartment sale prices are reduced by hurricanes but increased by excess rain. However, residential land prices remain unaffected by both events. The results point to the importance of climate adaptation for the local real estate market and property investment.

Study of Tiu Kulit Dam Reservoir Operational Pattern Simulation in Sumbawa Island

Tiu Kulit Reservoir plays a pivotal role in managing water resources in West Nusa Tenggara, Indonesia, serving as a vital source for raw water, irrigation, and livestock consumption in the neighboring regions. This study aims to assess the operational dynamics of Tiu Kulit Reservoir across varying hydrological conditions, namely dry, normal, and wet years. The analysis is based on inflow rates and equilibrium water surface elevations. To achieve the objectives, an investigation of the reservoir's operation pattern was conducted. Inflow rates and equilibrium water surface elevations were scrutinized to discern operational behaviors under different hydrological scenarios. The findings indicate distinct operational strategies for Tiu Kulit Reservoir. During dry years, the outflow rate is restricted to 1.20 m3/s at a water surface elevation of +53.07 m. Conversely, the reservoir's operation in normal and wet years allows for a maximum outflow rate aimed at satisfying water demand, set at +57.00 m. In instances of excessive rainfall, the study highlights the potential for overflow beyond the spillway threshold. The study underscores the significance of these results for effective water management and resource allocation in the region. Understanding the reservoir's behavior under various conditions enables informed decision-making and sustainable utilization of water resources. To build upon this study, it is recommended to implement continuous monitoring systems for both inflow and outflow rates. Furthermore, the installation of rainfall monitoring stations within the catchment area would enhance data accuracy. Regular evaluations of the reservoir's operational patterns are also advised, allowing for adaptive strategies in response to evolving climate conditions. Moreover, future research endeavors should focus on augmenting water supply to meet the demands of a growing population and livestock, while optimizing agricultural practices to boost productivity.

Quantifying the relative contributions of different flood generating mechanisms to floods across CONUS

The occurrence of flooding in a catchment is attributable to various mechanisms. Several researchers have used linear models to quantify the relative contributions of different flood generating mechanisms. However, the use of linear models for this quantification may not be suitable given the complex and nonlinear processes from climate to floods. In this study, we used nonlinear machine learning models with interpretability methods to quantify the contributions of multiple flood generating mechanisms to floods across the continental United States (CONUS). Four flood generating mechanisms were considered comprehensively, which varied in terms of the influence of antecedent soil moisture condition or snowmelt on flood generation. These mechanisms involved three common mechanisms (rainfall, rainfall excess, and snowmelt/rain on snow) and one complex mechanism (effective precipitation) that accounts for snowmelt/rain on snow lost to unsaturated soil zone. Consistent with previous studies, we observed that rainfall alone (i.e., without considering other hydrometeorological processes) is seldom the dominant mechanism for flood generation. Floods in most catchments are largely attributable to rainfall excess and snowmelt. Unlike previous studies, we noted that in the midwest and northeastern CONUS, snowmelt/rain on snow upon saturated soil was the greatest contributor to local flood generation. This finding highlights that both snowmelt and soil moisture condition affect flood generation in the midwest and northeastern CONUS, instead of only snowmelt as has been reported previously. Overall, this study provides new insights into flood generating mechanisms in CONUS and demonstrates the potential of applying interpretable machine learning to examine flood generating mechanisms.

Assessing the effectiveness of site real-time adaptive control for stormwater quality control

Urban sprawl, excessive rainfall, and resource limitations have challenged the performance of conventional water-sensitive urban designs (WSUD). To address these issues, there is a growing interest in adopting site real-time adaptive control (SRAC) for integrated and real-time water management. This research evaluates the effectiveness of SRAC technology in reducing stormwater pollutants in a highly developed urban area, comparing it with conventional WSUD methods. The study focuses on examining the impact of the SRAC-WSUD method on stormwater quality. Findings indicate that the SRAC-WSUD method reliably reduces stormwater pollutants under varying rainfall conditions. Moreover, it enhances the resilience and performance of existing stormwater systems without the need for additional infrastructure upgrades. For the whole year scenario, the SRAC-WSUD method resulted in reductions in total pollutant loads. Notably, there was a 196.72 kg/year decrease in total suspended solids (TSS), a 0.07 kg/year decrease in total phosphorus (TP), and a 0.78 kg/year decrease in total nitrogen (TN). These findings highlight the potential of SRAC-WSUD in improving stormwater quality and its implications for sustainable urban water management. Overall, this research contributes to advancing the understanding and practical implementation of SRAC technology in stormwater management, offering valuable insights for urban planning and water resource preservation.

The Chloroplast Genome of Endive (Cichorium endivia L.): Cultivar Structural Variants and Transcriptome Responses to Stress Due to Rain Extreme Events.

The chloroplast (cp) genome diversity has been used in phylogeny studies, breeding, and variety protection, and its expression has been shown to play a role in stress response. Smooth- and curly-leafed endives (Cichorium endivia var. latifolium and var. crispum) are of nutritional and economic importance and are the target of ever-changing breeding programmes. A reference cp genome sequence was assembled and annotated (cultivar 'Confiance'), which was 152,809 base pairs long, organized into the angiosperm-typical quadripartite structure, harboring two inverted repeats separated by the large- and short- single copy regions. The annotation included 136 genes, 90 protein-coding genes, 38 transfer, and 8 ribosomal RNAs and the sequence generated a distinct phyletic group within Asteraceae with the well-separated C. endivia and intybus species. SSR variants within the reference genome were mostly of tri-nucleotide type, and the cytosine to uracil (C/U) RNA editing recurred. The cp genome was nearly fully transcribed, hence sequence polymorphism was investigated by RNA-Seq of seven cultivars, and the SNP number was higher in smooth- than curly-leafed ones. All cultivars maintained C/U changes in identical positions, suggesting that RNA editing patterns were conserved; most cultivars shared SNPs of moderate impact on protein changes in the ndhD, ndhA, and psbF genes, suggesting that their variability may have a potential role in adaptive response. The cp transcriptome expression was investigated in leaves of plants affected by pre-harvest rainfall and rainfall excess plus waterlogging events characterized by production loss, compared to those of a cycle not affected by extreme rainfall. Overall, the analyses evidenced stress- and cultivar-specific responses, and further revealed that genes of the Cytochrome b6/f, and PSI-PSII systems were commonly affected and likely to be among major targets of extreme rain-related stress.

Beyond climate change: Examining the role of environmental justice, agricultural mechanization, and social expenditures in alleviating rural poverty

Extreme weather events and extreme poverty are two sides of the same coin, with far-reaching consequences for emerging nations like Pakistan. Rural people are more likely to experience poverty and inequality as climate change worsens. This research aspires to close the gap between environmental ethics and justice by investigating how climate change issues contribute to poverty in Pakistan. The study used Robust Least Squares (RLS) regression to analyze the impact of water scarcity, extreme temperatures, and excessive rainfall on rural poverty in Pakistan from 1990Q1 to 2022Q4. Further, the study examines the effect of environmental justice interventions, access to healthcare and education, agricultural value-added and agricultural mechanization on the country's rural poverty. Results reveal that climate change contributes to rural poverty in Pakistan, while environmental justice initiatives, healthcare access, and agricultural automation alleviate poverty incidence. The Impulse Response Function (IRF) estimates suggested that rural poverty will be exacerbated over the next decade by water scarcity, high temperatures, and low agricultural value added but alleviated by excessive rainfall, environmental justice intervention, healthcare access, and agricultural mechanization. According to Variance Decomposition Analysis (VDA) projections, agricultural value added will substantially impact rural poverty by 2032, increasing it by 11.431%. Addressing these problems requires policymakers to prioritize the interests of the most marginalized groups by fostering fair results. Policies should cut GHG emissions and encourage sustainable development to combat climate change. Modernizing farming techniques and expanding access to healthcare are also necessary for increasing efficiency and production. It is essential to execute environmental justice interventions so that all communities have access to environmental resources and protections equitably. Promoting equitable outcomes and reducing poverty in Pakistan's climate change context may be achieved by closing the gap between environmental ethics and justice.

Analysis of Extreme Rainfall and its Impacts of Rice Production in Krishnagiri District

Extreme rainfall in Krishnagiri district can have significant implications for agriculture and the overall socio-economic landscape of the region. Krishnagiri district, located in Tamil Nadu, India, experiences a monsoon-driven climate, making it susceptible to both deficient and excessive rainfall. Extreme rainfall events have significant impacts on rice production, affecting planting, growth, yield, and grain quality. Excessive rainfall delays planting, causes waterlogging, and reduces crop establishment. Water stress, hindered root growth, and nutrient leaching impact growth and development, lowering plant height, tiller production, and leaf area. Lodging, disease susceptibility, and nutrient loss reduce yield. Fungal diseases, grain sprouting, and post-harvest losses affect grain quality. To mitigate these impacts, strategies like improved drainage, crop diversification, suitable variety selection, and water management should be employed. Early warning systems and supportive policies are crucial for adaptation and resilience in rice production. During the growth and development stages, excessive rainfall can hinder the progress of rice crops. Waterlogged soils deprive plants of oxygen, leading to water stress and hampering root growth, nutrient uptake, and photosynthesis. This, in turn, results in stunted plant height, reduced tiller production, and decreased leaf area, ultimately affecting the overall growth and health of the crop.The impact of extreme rainfall on rice yield is significant. Heavy downpours can cause lodging, where plants bend or collapse due to weak root systems unable to support the weight of the crop. Lodging reduces the crop's ability to photosynthesize effectively and makes it more susceptible to diseases and pests. Additionally, excessive rainfall can leach essential nutrients from the soil, diminishing their availability for the rice plants and ultimately leading to lower grain yield.. Key words: extreme rainfall, Rice production,Krishnagiri District

Influencing factors associated with the second dominant pattern of the Indian summer monsoon

AbstractThe interannual variation of the Indian summer monsoon (ISM) affects millions of people in India and the global weather and climate. The teleconnections that affect this variation are not stable. The recent four decades of the second dominant mode of ISM rainfall show a unique north–south tripole pattern, with above‐normal rainfall in the north and peninsular India sandwiching suppressed rainfall in central‐east India. The pattern relates to extending the Indo‐Pacific warm‐pool's warmer sea‐surface temperature (SST) towards the south of the equatorial eastern Indian Ocean. Most of the time, this warming and the extension of the warm‐pool's warmer SST are associated with La Niña events, which activate more in situ vigorous convection. The Rossby‐gyres generated west of the equatorial heating increase the tropospheric height over north India, shifting and strengthening the Tibetan High northwards, facilitating heavy rainfall in the north. Meanwhile, the more vigorous convection south of the equatorial eastern Indian Ocean produces compensatory subsidence over central‐east India, suppressing rainfall. The northern hemispheric Rossby‐gyres brings anomalous cyclonic circulation over peninsular India, producing excess rainfall. Also, the dipole pressure anomaly between the northwest Pacific and south tropical Indian Ocean generates anomalous lower‐level easterly winds over the Bay of Bengal. It supplies excess moisture to the north India convections. The co‐occurrence of the active Atlantic intertropical convergence zone supports this tripole rainfall pattern. This teleconnection could further be examined in climate models.

On the successful acclimatization of the Colorado potato beetle Leptinotarsa decemlineata (Say, 1824) (Coleoptera: Chrysomelidae) in Primorsky kray

The successful naturalization of the Colorado potato beetle in Primorsky Kray is limited by the monsoon climate, namely unstable fluctuating weather conditions with periodic catastrophic precipitation. The most of potato fields are located in the bottomlands of rivers or in close proximity to water bodies and a drastic increase in the runoff due to excessive simultaneous rainfall leads to the flooding of agricultural lands and the elimination of the fodder plants. The Colorado potato beetle is an oligophage and can not switch to alternative food sources during these periods. Moreover, beetles that enter diapause under these conditions die because of flooding and cold injury. Despite this fact, the pest remains a threat to the potato production in the region and can cause significant damage in case of repeated invasions during periods with more favorable conditions.

Climate change and its adaptation strategies on tea plantation in West Java, Indonesia

Climate change, i.e., changing rainfall refers to drought and excess rainfall, is known to affect the growth and yield of tea production in many regions. However, research on the impact of climate change on tea plantations in Indonesia is still limited. The study aimed to evaluate the impact of changing rainfall on the productivity of tea plantation at Cianjur, West Java. The data was collected from interviews, field data, and company records from April to July 2022. The results showed that changing rainfall of both limited rainfalls during El Nino and excess rainfall during La Nina affected the tea production. Annual tea productivity declined during both climatic events. Shortage of water during El Nino primarily reduced crop growth, while excess rainfall during La Nina reduced the capacity of tea pickers and increased labor for crop maintenance. Failure to adapt to the direct and indirect impacts of climate change could contribute to declining tea production in Indonesia. Thus, comprehensive action is needed including capacity building in human resources, water management, and microclimate adaptation such as shading plants and tolerant clones to sustain tea production under climate change events.

Changes in Mediterranean flood processes and seasonality

Abstract. Floods are a major natural hazard in the Mediterranean region, causing deaths and extensive damages. Recent studies have shown that intense rainfall events are becoming more extreme in this region but, paradoxically, without leading to an increase in the severity of floods. Consequently, it is important to understand how flood events are changing to explain this absence of trends in flood magnitude despite increased rainfall extremes. A database of 98 stations in southern France with an average record of 50 years of daily river discharge data between 1959 and 2021 was considered, together with a high-resolution reanalysis product providing precipitation and simulated soil moisture and a classification of weather patterns associated with rainfall events over France. Flood events, corresponding to an average occurrence of 1 event per year (5317 events in total), were extracted and classified into excess-rainfall, short-rainfall, and long-rainfall event types. Several flood event characteristics have been also analyzed: flood event durations, base flow contribution to floods, runoff coefficient, total and maximum event rainfall, and antecedent soil moisture. The evolution through time of these flood event characteristics and seasonality was analyzed. Results indicated that, in most basins, floods tend to occur earlier during the year, the mean flood date being, on average, advanced by 1 month between 1959–1990 and 1991–2021. This seasonal shift could be attributed to the increased frequency of southern-circulation weather types during spring and summer. An increase in total and extreme-event precipitation has been observed, associated with a decrease of antecedent soil moisture before rainfall events. The majority of flood events are associated with excess rainfall on saturated soils, but their relative proportion is decreasing over time, notably in spring, with a concurrent increased frequency of short rain floods. For most basins there is a positive correlation between antecedent soil moisture and flood event runoff coefficients that is remaining stable over time, with dryer soils producing less runoff and a lower contribution of base flow to floods. In a context of increasing aridity, this relationship is the likely cause of the absence of trends in flood magnitudes observed in this region and the change of event types. These changes in flood characteristics are quite homogeneous over the domain studied, suggesting that they are rather linked to the evolution of the regional climate than to catchment characteristics. Consequently, this study shows that even in the absence of trends, flood properties may change over time, and these changes need to be accounted for when analyzing the long-term evolution of flood hazards.

Insights into Rainfall Extremities Across the Agroclimatic Zones of Tamil Nadu, India

Rainfall is a crucial agrometeorological parameter that impacts hydrology and agricultural planning in a region. The spatiotemporal changes in the occurrences of precipitation extremes must be monitored to reduce the hazards caused by the fluctuating rainfall pattern. The extreme rainfall indices for each year categorized under excess, normal and deficit rainfall categories were calculated over the agroclimatic zones of Tamil Nadu using the high-resolution CHIRPS datasets from 1991 to 2022. The results highlighted that High Rainfall Zone has more consecutive wet days (22 days), minimum consecutive dry days (25 days) and Daily Intensity Index with threshold of 2.5 mm (28.6 mm) compared to other zones. The maximum consecutive dry days of 99 days, a high rainy day of 142 days, and minimum daily intensity of 8.9 mm are experienced by the Cauvery Delta Zone, High Altitude and Hilly Zone, and Western Zone, respectively. Overall, the High Rainfall Zone faces a higher number of extreme rainfall events in terms of wet days and intensity, whereas the average maximum consecutive dry days and minimum rainfall intensity is observed over the north eastern zone and north western zone, respectively indicating high dry periods.

Singular Spectrum Analysis to Identify Excessive Rainfall

Indonesia is known for its excessive rainfall. Rainfall trends in an area have different characteristics. Differences in latitude, apparent motion of the sun, geographical position, topography, and the interaction of many forms of air circulation all contribute to this. Rainfall time series is essential for engineering planning, particularly for water infrastructure like irrigation, dams, urban drainage, ports, and wharves. Although meteorological technologies provide short-term rainfall predictions, long-term rainfall prediction is difficult and fraught with uncertainty. Unpredictability and seasonality can cause complex behavior in rainfall time series. This research utilizes the Singular Spectrum Analysis approach to extract trends; seasonality, cyclists, and noise can all be identified with potentially high accuracy.

Factors affecting interannual variation in late summer rainfall in the Red River Delta of Vietnam

Based on station monthly observational statistics, the major rainfall in the Red River Delta (RRD) of Vietnam occurs in late summer (July–September) with conspicuous year-to-year variation. Using the ± 0.8 of the seasonal total rainfall standard deviation as criteria, seven wet and six dry years are identified over the period 1983–2015. In addition to the 70.5% of the seasonal total rainfall contributed by the heavy rainfall days, the distinct heavy rainfall accumulation difference between wet and dry years seems to fundamentally establish these two separated extreme wet and dry groups. As revealed from further analyses, the large variability in rainfall is attributed to the influence of tropical cyclones (TCs) and 7–24- and 30–60-day intraseasonal oscillations (ISOs); in particular, the number of TCs affecting the RRD and rainfall produced by TCs are more (less) during the wet (dry) years, and the amplitudes of ISOs are also enhanced (reduced). In many cases, heavy rainfall days are induced by the combined effect of both ISOs and TCs, while some heavy rainfall events are mainly triggered by ISOs. It is found from the water vapor budget analyses that an anomalous cyclone (anticyclone) dominates over the Indochina Peninsula in wet (dry) years, resulting in more (less) water vapor being transported to the RRD, whereas the anomalous convergence (divergence) of water vapor flux leads to the maintenance of excessive (insufficient) rainfall over the RRD. However, the El Niño–Southern Oscillation (ENSO) forcing shows minor effects on the interannual variation in rainfall in the RRD.

Simulation of shallow landslides induced by typhoon in July 2018 in Gogoshima, Ehime Prefecture, Japan based on a simple model

Every year, many typhoons make landfall in Japan causing disasters on mountain slopes across the country. Rainfall induced landslides in Japan mostly occur at shallow depths. Developing simple models of rainfall-induced landslides provides a practical alternative to finite element methods in large-scale landslide modelling and prediction. Therefore, authors previously developed a simple method to calculate the advance of the wetting front into fine sand slopes subjected rainfall. However, during intense rainfall, the excess rainfall that cannot be absorbed into the soil will generate runoff on the slope surface, which has not been included in the previous model. Thus, this study integrated the model with a surface water modeling module to simulate the disasters more comprehensively. The surface water is controlled by 2D shallow water equations and the digital elevation model depression removal process. The combined model is able to provide the maps of the wetting front, surface water depth, and factor of safety of slope during rainstorms. The newly integrated model was used to simulate rainfall-induced disasters in the Gogoshima Island during the July 2018 typhoon. The simulation results disclosed that both moving of the wetting front and surface water flows contributed to shallow landslides along catchments in this island.

Application of the Single Exponential Smoothing Method For Flood Disaster Prediction

The country of Indonesia is seen as one that is particularly vulnerable to natural catastrophes as well as calamities brought on by human activity. A disaster that may be brought on by both natural and human sources is a flood. Disasters brought on by flooding are unpredictable occurrences that frequently cause losses in the form of property damage, the theft of assets, and lost productivity at work and in school. Through this prediction information system, the people can find out the level of risk of flooding through excessive rainfall. in order to better anticipate and prepare for all possibilities that occur before the flood, the method used is Single Exponential Smoothing. This method was chosen because of the simple way the system works to find predictive values ??through past data. With this system, researchers can input rainfall data taken from the Meteorology, Climatology and Geophysics Agency, then the data is processed through the system and if rainfall gets high results. The risk of flooding will also be very high and a warning will be given to the public so that better prepared for the risk of flooding. The results obtained from this study are the results of an analysis of the exponential method single to obtain accurate rainfall prediction information with data MAD, MSE and MAPE.

Impact of Climate Change on Paddy Yield in Bastar District of Chhattisgarh

Agriculture and forest product collection are the economic foundations of the Bastar district. Paddy and maize are widely grown in the Bastar region. Paddy is grown in 76 percent of the gross cropped area in Bastar district. To assess the impact of climate change on paddy productivity a simple ordinary least square (OLS) Regression analysis have been analysed. Observation revealed that the rainfall during the month of June to September affected the crop yield positively, Monsoon rainfall affects more the crop yield negatively. Bastar district is mainly rainfed and only 2.14 percent area near to the water resources can be irrigated, the lack of irrigation effects the crop yield greatly hence, any increase in rainfall in the germination and booting period (June to August) will help in increase the productivity of crop. The month of or before harvesting if gets rain, it can destroy the standing crop and cause huge lose to the production.An increase in annual maximum Temperature affects the paddy crop productivity negatively whereas productivity increases with every per cent increase with the annual minimum Temperature. Paddy is a tropical and subtropical crop hence, the result had positive relationship with maximum Temperature, Excessive rainfall can negatively or positively impact crop yield.The study suggests to develop such varieties which can withstand with minimum Temperature.