IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Hydraulic fracturing has been inferred to trigger the majority of injection-induced earthquakes in western Canada, in contrast to the midwestern United States where massive saltwater disposal is the dominant triggering mechanism. A template-based earthquake catalog from a seismically active Canadian shale play, combined with comprehensive injection data during a 4-month interval, shows that earthquakes are tightly clustered in space and time near hydraulic fracturing sites. The largest event [moment magnitude (MW) 3.9] occurred several weeks after injection along a fault that appears to extend from the injection zone into crystalline basement. Patterns of seismicity indicate that stress changes during operations can activate fault slip to an offset distance of >1 km, whereas pressurization by hydraulic fracturing into a fault yields episodic seismicity that can persist for months.
This document summarizes a study that characterized cyclones in the Bay of Bengal using cyclone tracking data from the International Best Track Archive for Climate Stewardship (IBTrACS) from 1986 to 2016. The following key points are made:
- Most cyclones occurred during October and November and had landfalls along the northwest coast of the Bay of Bengal, affecting India.
- There is an inverse relationship between wind speed and pressure - high wind speeds are associated with low pressures, resulting in cyclones.
- Spatial analyses showed maximum wind speeds and lowest pressures predominantly in the northeast region of the Bay of Bengal.
- There is a decreasing trend observed in the number of cyclones occurring in the Bay
Prediction of earthquakes and reducing damageseSAT Journals
The document discusses methods for predicting earthquakes, reducing earthquake damage, and summarizes the key points as follows:
1. Prediction methods aim to forecast future earthquakes through identifying seismic zones, monitoring rock stresses, and observing precursors like foreshocks. Short term predictions provide emergency preparedness while long term predictions allow preventative measures.
2. Reducing damage is done through modifying structures to relieve geological stresses, and mitigation efforts like enforcing earthquake-resistant building codes and retrofitting existing structures.
3. Key safety measures for structures in quake zones include ductile designs, lowering centers of gravity, base isolation, and using materials like timber that absorb stresses without collapsing. Education and disaster planning are also
This document analyzes drought characteristics in the Pedda Vagu and Ookacheti Vagu watersheds in India using rainfall data from 1986-2013. Key findings include:
- Drought occurrence, magnitude, and recurrence varied significantly between stations in the watershed.
- Spatial maps of drought severity created using spline interpolation showed some regions experienced more severe drought while others were less affected.
- Empirical relationships were developed between drought duration and magnitude to help inform agricultural and water management decisions.
This document discusses renewable energy sources and energy conversion devices. It begins by defining renewable energy sources as those that can provide energy indefinitely, such as solar, wind, geothermal, tidal, wave, hydropower and biomass. It then provides a table summarizing the status, installed capacity, theoretical potential and environmental considerations of these different renewable energy sources. The majority of the document then focuses on solar energy, providing equations to calculate extraterrestrial radiation, variation in radiation over time and location, and atmospheric attenuation effects. It also discusses how to estimate monthly average solar radiation and calculate the beam and diffuse components of radiation.
International Journal of Computational Engineering Research(IJCER) is an intentional online Journal in English monthly publishing journal. This Journal publish original research work that contributes significantly to further the scientific knowledge in engineering and Technology
Detection of hazard prone areas in the upper himalayan region in gis environmenteSAT Publishing House
This document summarizes a study that used GIS and remote sensing tools to identify hazard-prone areas in the Alakananda River basin located in Uttarakhand, India. The study analyzed digital elevation data, soil maps, and extracted river networks to determine areas vulnerable to flooding from cloudbursts and heavy rainfall. Slope maps showed that over 50% of the region has moderate to steep slopes unsuitable for development. Soil maps indicated the presence of thin, coarse soils that are easily eroded. Overlaying village locations on river networks revealed that many villages are situated directly in stream paths, exposing them to flood risks. The integrated analysis identified highly vulnerable regions for future disaster mitigation planning.
Hydraulic fracturing has been inferred to trigger the majority of injection-induced earthquakes in western Canada, in contrast to the midwestern United States where massive saltwater disposal is the dominant triggering mechanism. A template-based earthquake catalog from a seismically active Canadian shale play, combined with comprehensive injection data during a 4-month interval, shows that earthquakes are tightly clustered in space and time near hydraulic fracturing sites. The largest event [moment magnitude (MW) 3.9] occurred several weeks after injection along a fault that appears to extend from the injection zone into crystalline basement. Patterns of seismicity indicate that stress changes during operations can activate fault slip to an offset distance of >1 km, whereas pressurization by hydraulic fracturing into a fault yields episodic seismicity that can persist for months.
This document summarizes a study that characterized cyclones in the Bay of Bengal using cyclone tracking data from the International Best Track Archive for Climate Stewardship (IBTrACS) from 1986 to 2016. The following key points are made:
- Most cyclones occurred during October and November and had landfalls along the northwest coast of the Bay of Bengal, affecting India.
- There is an inverse relationship between wind speed and pressure - high wind speeds are associated with low pressures, resulting in cyclones.
- Spatial analyses showed maximum wind speeds and lowest pressures predominantly in the northeast region of the Bay of Bengal.
- There is a decreasing trend observed in the number of cyclones occurring in the Bay
Prediction of earthquakes and reducing damageseSAT Journals
The document discusses methods for predicting earthquakes, reducing earthquake damage, and summarizes the key points as follows:
1. Prediction methods aim to forecast future earthquakes through identifying seismic zones, monitoring rock stresses, and observing precursors like foreshocks. Short term predictions provide emergency preparedness while long term predictions allow preventative measures.
2. Reducing damage is done through modifying structures to relieve geological stresses, and mitigation efforts like enforcing earthquake-resistant building codes and retrofitting existing structures.
3. Key safety measures for structures in quake zones include ductile designs, lowering centers of gravity, base isolation, and using materials like timber that absorb stresses without collapsing. Education and disaster planning are also
This document analyzes drought characteristics in the Pedda Vagu and Ookacheti Vagu watersheds in India using rainfall data from 1986-2013. Key findings include:
- Drought occurrence, magnitude, and recurrence varied significantly between stations in the watershed.
- Spatial maps of drought severity created using spline interpolation showed some regions experienced more severe drought while others were less affected.
- Empirical relationships were developed between drought duration and magnitude to help inform agricultural and water management decisions.
This document discusses renewable energy sources and energy conversion devices. It begins by defining renewable energy sources as those that can provide energy indefinitely, such as solar, wind, geothermal, tidal, wave, hydropower and biomass. It then provides a table summarizing the status, installed capacity, theoretical potential and environmental considerations of these different renewable energy sources. The majority of the document then focuses on solar energy, providing equations to calculate extraterrestrial radiation, variation in radiation over time and location, and atmospheric attenuation effects. It also discusses how to estimate monthly average solar radiation and calculate the beam and diffuse components of radiation.
International Journal of Computational Engineering Research(IJCER) is an intentional online Journal in English monthly publishing journal. This Journal publish original research work that contributes significantly to further the scientific knowledge in engineering and Technology
Detection of hazard prone areas in the upper himalayan region in gis environmenteSAT Publishing House
This document summarizes a study that used GIS and remote sensing tools to identify hazard-prone areas in the Alakananda River basin located in Uttarakhand, India. The study analyzed digital elevation data, soil maps, and extracted river networks to determine areas vulnerable to flooding from cloudbursts and heavy rainfall. Slope maps showed that over 50% of the region has moderate to steep slopes unsuitable for development. Soil maps indicated the presence of thin, coarse soils that are easily eroded. Overlaying village locations on river networks revealed that many villages are situated directly in stream paths, exposing them to flood risks. The integrated analysis identified highly vulnerable regions for future disaster mitigation planning.
Understanding the Kerala Floods of 2018: Role of Mixed Rossby-Gravity WavesS Kiran
Kerala, the south-west coastal state of India, was ravaged by a series of floods during the South-West Monsoon of 2018. The season was marked by severely anomalous rainfall trends, with upto 150 mm of departures from the mean daily precipitation in the northern districts of the State. Although, there were many studies about the hydrogeological factors which aggravated the floods in Kerala, no attempt was made to delve into the physics which actually resulted in anomalous precipitation during the year. This study intends to document the dynamical phenomenon which caused the Kerala Floods of 2018. The westward propagating convectively-coupled Mixed Rossby-Gravity (MRG) waves were excited by the synoptic disturbances of the tropical Pacific at the pressure level of 700 hPa, during the Indian Monsoon of 2018. They travelled across the Indian Ocean in two significant modes -- a predominant slow moving wave of 20-40 days period (as Madden-Julian Oscillation) and a secondary faster wave of 5-8 days period. They are characterised by vertical phase propagation to the upper troposphere, a precursor to deep convection and intense precipitation. Further, the propagation of these waves through a medium enhances its relative vorticity and the gyres or circulations thus formed are symmetrical about the equator. Consequently, the meanders in the wind field and widening of the Intertropical Convergence Zone were observed. The MRG waves, especially the slow mode induced divergence in the wind field, which fueled convection in tropics and brought very heavy rainfall to the State of Kerala in 2018.
Comments: 14 pages, 12 figures, 1 table
Subjects: Atmospheric and Oceanic Physics (physics.ao-ph)
Cite as: arXiv:2103.09771 [physics.ao-ph]
(or arXiv:2103.09771v1 [physics.ao-ph] for this version)
Time Series Analysis of Rainfall in North Bangalore Metropolitan Region using...Dr Ramesh Dikpal
Rainfall studies are of utmost utility for understanding nature & hence the behaviour of climate changes. Time series is a set of observations taken at specified times usually at equal interval. The inherent variability displayed by many hydrological time series usually mask trends and periodic patterns. This situation has often led to “something” the original time series so that the effects of random variations are reduced and trends or cyclical patterns enhanced. Thus a set of data depending on time is called a Time series. Here, Rainfall series represent the time series. The time series analysis is helpful to compare the actual performance and analyse the cause of variations. By comparing different time series we can draw important conclusion. Graphical method implies in increasing trend for pre-monsoon, south-west monsoon, north-east monsoon and annually.Geo- informatics module consists of GIS mapping for Location map, Geomorphology map and Season wise Rainfall maps are generated. Autocorrelation indicates the periodicity observed as 37,16 & 6 years (PM), 12, 37 & 16 years (SWM), 8, 18 & 6 years (NEM) and 16, 22 & 8 years (Annual) respectively. Power spectral depicts the cyclicity of 37, 4 & 3 years (PM), 2, 4& 2 years (SWM), 3, 7 & 2 years (NEM) and 2, 4 & 2 years (Annual) respectively. Moving average displays prominent positive correlation coefficients at lags of 18 to 42 years in PM & SWM and 12 to 24 years in NEM & Annual. The southwest and southeast parts of the study area experience the heavy rainfall whereas the least rainfall areas are the northern parts of the study area.The short term and long term cyclicity observed in Autocorrelation, power spectrum and Moving Average. Spatial variation of rainfall for the three seasons and annual has been studied
1) Satellites provide a new tool for monitoring extreme rainfall events globally, including over oceans where gauges are sparse.
2) Analysis of TRMM satellite data shows that the relationship between maximum rainfall and duration (the Jennings law) exhibits two slopes for short and long durations, unlike the single slope seen in gauge data.
3) Satellites allow identifying regions experiencing the most extreme rainfall over timescales from days to years, such as Vietnam, Northeast India, and Colombia's Pacific coast.
International Journal of Research in Engineering and Science is an open access peer-reviewed international forum for scientists involved in research to publish quality and refereed papers. Papers reporting original research or experimentally proved review work are welcome. Papers for publication are selected through peer review to ensure originality, relevance, and readability.
Determination of Rainfall Characteristics and Soil Water Index for Debris and...IRJET Journal
This document summarizes a study that determined rainfall characteristics and soil water index associated with debris and mud flows in Cameron Highlands, Malaysia. The study found that debris and mud flows occurred most frequently during the Northwest Monsoon and had an average soil water index of 61. Specifically, 65% of events were associated with low intensity, prolonged rainfall (>80mm over 24 hours), rather than high intensity, short rainfall as defined by previous guidelines. The soil water index can help forecast debris and mud flow risk in Cameron Highlands.
Remote Sensing Method for Flood Management SystemIJMREMJournal
Flood occurred when heavy and continuous rainfall exceeding the absorptive capacity of soil and the flow
capacity of rivers, streams, and coastal areas. Land areas that are most subjected to floods are areas situated
adjacent to rivers and streams, that are known as floodplain and therefore considered as “flood-prone”. These
areas are hazardous to development activities if the vulnerability of those activities exceeds an acceptable level.
The main objectives of this study are; to identify floodplains and other susceptible areas, and to assess the
extent of disaster impact in the study area which is located at Kota Tinggi, Johor, Malaysia. This area
experienced an unprecedented flood during December of 2006 to January of 2007.Questions such as how often
and how long the floodplain will be covered by water, and at what time of year flooding can be expected need to
be answered. Thus, an understanding of the dynamic nature of floodplains is greatly required. Multi-temporal
Radarsat-1images, Landsat ETM+ image, topographical maps and land use maps were used in this study for
the purpose of delineating the flood extend before, during and after the flood event. DEM acquired from
topographic map is used to derive flood depth. The final outputs of this study are flood extent and flood depth
maps where both of these maps show the impact of the flood to environment, lives and properties. This map is
also important and can be applied to develop a comprehensive relief effort immediately after flooding.
This study analyzes how aerosol size and concentration can impact precipitation by serving as cloud condensation nuclei. Data on aerosol particle size distribution from AERONET and vertical profiles from a ceilometer were collected in Mayagüez, Puerto Rico during storms in May and June 2013 that produced over 50 mm of rain. The results suggest that fine aerosols can suppress precipitation while coarse aerosols can trigger more rainfall, as larger particles contain heavier droplets. Clouds with a higher concentration of smaller aerosolic particles rose higher with a greater cloud base height, while clouds with fewer but larger particles produced precipitation earlier.
This document describes a study that uses a multivariate non-homogenous Hidden Markov model to analyze rainfall data over the Bhakra region of northwest India from 1984-2004. The model classifies daily rainfall into three hidden states (dry, somewhat dry/wet, wet) and examines how factors like seasonal cycle, ENSO, and IOD affect transitions between these states. The results show the seasonal cycle significantly impacts summer rainfall through emission distributions, while ENSO and IOD effects are insignificant. For winter, the region is mainly dry with some intense storm events, and transition probabilities between states are not significantly impacted by ENSO or IOD either. Understanding rainfall dynamics in this region can help water management and agriculture.
Predicting Meteorological Drought in Iraq: An Evaluation of Machine Learning ...IRJET Journal
This document presents research on using machine learning techniques to predict meteorological drought in Iraq. It evaluates the Random Forest and Artificial Neural Network models for forecasting the Standardized Precipitation Index (SPI) over different time scales (3, 6, 9, and 12 months). The models are developed using monthly rainfall data from 1981 to 2021 from meteorological stations in northern Iraq. This region experiences a continental and subtropical semi-arid climate and frequent droughts. The document provides background on drought and the SPI index. It also describes the study area, data, Random Forest and Artificial Neural Network methods, and presents preliminary results of the model evaluations. The aim is to better understand drought patterns in Iraq to help mitigate impacts
Floodplain Mapping of Krishna River at Karad Using Hec-RasIRJET Journal
This document summarizes a study that used the HEC-RAS modeling software to map flood inundation areas along the Krishna River in India. The study collected topographic and flow data for the Krishna River basin and used HEC-RAS to perform a 1D steady-state hydraulic analysis. Cross-section and flow path data were created in RAS Mapper software. The HEC-RAS model was run for peak flows corresponding to 25, 50, and 100-year return periods. Floodplain maps showing inundated areas along the Krishna River were produced for each return period. The floodplain maps can help agencies better plan for flood risks and mitigate impacts in low-lying flood-prone
The document provides details about the Chennai floods of 2015. It describes how Chennai received over 33 cm of rain in a 24-hour period from December 1-2, causing widespread flooding and damage. Over 500 people lost their lives. The document examines factors like heavy rainfall, changes in weather patterns from global warming, destruction of wetlands, improper sewage and drainage systems, and human development that exacerbated the flooding in Chennai. It provides statistics on rainfall amounts, discusses the city's geology and infrastructure, and analyzes the impacts and response to the floods.
Record Setting: The Origins of Extreme Hail on 19 March 2018 during VORTEX-SEDeanMeyer14
Authors Dean Meyer and Ryan Wade. UAH Department of Atmospheric Science. Completed as Dean Meyer's student research as part of the UAH RCEU program at SWIRLL.
Robust Strategies of GIS and Geospatial Data mining techniques for drinking g...IJERA Editor
Dependency factors of drought in Maharashtra state of drinking water are groundwater resources, for rural, Urban and Agriculture commercial zone .this situation exploits the development and progress of groundwater management study. No doubt the climate has a vital role in it. So Researcher and decision maker have a new topic of study and research with increasing product of Geospatial data and different temporal of characteristics, geometrics, and Geospatial information systems. And it has been capabilities to control and handle a case like diverse range of geospatial data with varieties of skills. One of the major aspect and issues in geospatial data management is to explore the ratio and future trends of the data and which is smoothly possible with the GIS and Geospatial Data mining techniques and that is being brought into our consideration to discussed and to write this paper on this issue and for this we introduced geospatial data mining applications in drinking ground water quality Management, At last about the abundance of industrial Zones in state of Maharashtra, of India and their effects on water quality in this region, correlation between industrial pollutions and water quality indicators through geospatial data mining has been modeled as a case study at Jalna District Maharashtra.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Flood risk mapping using GIS and remote sensing and SARRohan Tuteja
This document summarizes a presentation on using synthetic aperture radar (SAR) data from RADARSAT-1 to map flooding in Kendrapara District, India. SAR data from four dates in September 2008 were used to map the spatial extent and temporal progression of flooding over time. Traditional flood mapping methods are time-consuming and difficult during floods, while SAR data can penetrate clouds and capture flooding regardless of weather conditions. The methodology involved preprocessing the SAR data, removing noise, correcting geometrically, and classifying images to map flooding and analyze how floodwaters spread over the four dates. Peak flooding occurred on September 22nd, affecting over 37,400 hectares. The results demonstrate how SAR data can effectively monitor flooding and inform disaster response
Synoptic and regional meteorological ingredients which induced severe flash f...Global Risk Forum GRFDavos
The document summarizes a study on flash floods in Romania. It provides background on Romania's climate and meteorological characteristics, describes several representative flash flood events that occurred from 1973-2009, and analyzes the synoptic and mesoscale conditions that led to heavy rainfall and flash flooding, including a case study of a 2007 flood in the Tecucel River basin. Key factors identified include atmospheric patterns bringing moisture from the Atlantic and interactions between low-level flows, topography, and regional energy/moisture supply producing intense precipitation.
Flooding problem raised seriously in the watershed
of Medjerda indeed flood risk factors still exists for some cities.
Studies forecasting and flood management may be important to
address these problems. The plain of Bou Salem had long known
catastrophic floods. Sudden rain, releases of dams and tributaries
flows caused historic flooding at the level of this plain. We
recovered thirty floods in the station of Bou Salem during the
period 1973-2013. Among the thirty floods, we distinguish mainly
three Flash floods. In fact, Flash flood is a short and sudden local
flood with great volume, it has a limited duration which follows
within few (usually less than six) hours of heavy or excessive
rainfall, rapid rain, or after a sudden release of water from a
dam. This communication is designed to analyze the results of the
flash floods forecasting by simple propagation models namely
Muskingum and Regression. The method of forecasting depends
on the upstream station flow and models coefficients of
antecedent floods. Forecast periods range from 2 to 8 hours, with
a pitch of 2 hours. We used numerical criteria, such as Nash
coefficient, peak relative error and time separating observed and
calculated pic, to evaluate the results. We noted that the
satisfaction of all criteria together is not touched. The results
were satisfactory with Nash coefficient ranging from 71% to
99.8%.
Systematic Variation of Rain Rate and Radar Reflectivity Relations for Micro ...iosrjce
This document analyzes two years of rainfall measurement data collected using a vertically-pointing micro rain radar located in Akure, Nigeria to develop empirical models relating rain rate and radar reflectivity over different heights. Time series plots of rain events show variations in rain rate with stratiform and convective rain types observed at different heights. Power law relationships between rain rate (R) and radar reflectivity factor (Z) of the form Z = aRb were obtained through regression analysis for stratiform and convective rain, with different coefficients a and b values for each rain type. The relationships were compared to those reported in other studies and show that coefficients can vary between locations due to the dynamic nature of rainfall.
This document summarizes a study that used GIS techniques to model spatial variation in rainfall runoff erosivity (R-factor) in the Nzoia River basin in Western Kenya. Rainfall and erosion data were collected from 14 stations in the basin. R-factor values, which represent the ability of rainfall to cause soil erosion, ranged from 339.39 to 855.00 MJ mmha-1year-1. Higher R-factor values occurred in the middle to lower basin, likely due to relief rainfall from nearby hills and mountains. The study found significant spatial variation in R-factor across the basin and concluded that accounting for this variation is important to understand soil erosion risk.
An Examination of Effectuation Dimension as Financing Practice of Small and M...iosrjce
IOSR Journal of Business and Management (IOSR-JBM) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of business and managemant and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications inbusiness and management. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Does Goods and Services Tax (GST) Leads to Indian Economic Development?iosrjce
IOSR Journal of Business and Management (IOSR-JBM) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of business and managemant and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications inbusiness and management. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Understanding the Kerala Floods of 2018: Role of Mixed Rossby-Gravity WavesS Kiran
Kerala, the south-west coastal state of India, was ravaged by a series of floods during the South-West Monsoon of 2018. The season was marked by severely anomalous rainfall trends, with upto 150 mm of departures from the mean daily precipitation in the northern districts of the State. Although, there were many studies about the hydrogeological factors which aggravated the floods in Kerala, no attempt was made to delve into the physics which actually resulted in anomalous precipitation during the year. This study intends to document the dynamical phenomenon which caused the Kerala Floods of 2018. The westward propagating convectively-coupled Mixed Rossby-Gravity (MRG) waves were excited by the synoptic disturbances of the tropical Pacific at the pressure level of 700 hPa, during the Indian Monsoon of 2018. They travelled across the Indian Ocean in two significant modes -- a predominant slow moving wave of 20-40 days period (as Madden-Julian Oscillation) and a secondary faster wave of 5-8 days period. They are characterised by vertical phase propagation to the upper troposphere, a precursor to deep convection and intense precipitation. Further, the propagation of these waves through a medium enhances its relative vorticity and the gyres or circulations thus formed are symmetrical about the equator. Consequently, the meanders in the wind field and widening of the Intertropical Convergence Zone were observed. The MRG waves, especially the slow mode induced divergence in the wind field, which fueled convection in tropics and brought very heavy rainfall to the State of Kerala in 2018.
Comments: 14 pages, 12 figures, 1 table
Subjects: Atmospheric and Oceanic Physics (physics.ao-ph)
Cite as: arXiv:2103.09771 [physics.ao-ph]
(or arXiv:2103.09771v1 [physics.ao-ph] for this version)
Time Series Analysis of Rainfall in North Bangalore Metropolitan Region using...Dr Ramesh Dikpal
Rainfall studies are of utmost utility for understanding nature & hence the behaviour of climate changes. Time series is a set of observations taken at specified times usually at equal interval. The inherent variability displayed by many hydrological time series usually mask trends and periodic patterns. This situation has often led to “something” the original time series so that the effects of random variations are reduced and trends or cyclical patterns enhanced. Thus a set of data depending on time is called a Time series. Here, Rainfall series represent the time series. The time series analysis is helpful to compare the actual performance and analyse the cause of variations. By comparing different time series we can draw important conclusion. Graphical method implies in increasing trend for pre-monsoon, south-west monsoon, north-east monsoon and annually.Geo- informatics module consists of GIS mapping for Location map, Geomorphology map and Season wise Rainfall maps are generated. Autocorrelation indicates the periodicity observed as 37,16 & 6 years (PM), 12, 37 & 16 years (SWM), 8, 18 & 6 years (NEM) and 16, 22 & 8 years (Annual) respectively. Power spectral depicts the cyclicity of 37, 4 & 3 years (PM), 2, 4& 2 years (SWM), 3, 7 & 2 years (NEM) and 2, 4 & 2 years (Annual) respectively. Moving average displays prominent positive correlation coefficients at lags of 18 to 42 years in PM & SWM and 12 to 24 years in NEM & Annual. The southwest and southeast parts of the study area experience the heavy rainfall whereas the least rainfall areas are the northern parts of the study area.The short term and long term cyclicity observed in Autocorrelation, power spectrum and Moving Average. Spatial variation of rainfall for the three seasons and annual has been studied
1) Satellites provide a new tool for monitoring extreme rainfall events globally, including over oceans where gauges are sparse.
2) Analysis of TRMM satellite data shows that the relationship between maximum rainfall and duration (the Jennings law) exhibits two slopes for short and long durations, unlike the single slope seen in gauge data.
3) Satellites allow identifying regions experiencing the most extreme rainfall over timescales from days to years, such as Vietnam, Northeast India, and Colombia's Pacific coast.
International Journal of Research in Engineering and Science is an open access peer-reviewed international forum for scientists involved in research to publish quality and refereed papers. Papers reporting original research or experimentally proved review work are welcome. Papers for publication are selected through peer review to ensure originality, relevance, and readability.
Determination of Rainfall Characteristics and Soil Water Index for Debris and...IRJET Journal
This document summarizes a study that determined rainfall characteristics and soil water index associated with debris and mud flows in Cameron Highlands, Malaysia. The study found that debris and mud flows occurred most frequently during the Northwest Monsoon and had an average soil water index of 61. Specifically, 65% of events were associated with low intensity, prolonged rainfall (>80mm over 24 hours), rather than high intensity, short rainfall as defined by previous guidelines. The soil water index can help forecast debris and mud flow risk in Cameron Highlands.
Remote Sensing Method for Flood Management SystemIJMREMJournal
Flood occurred when heavy and continuous rainfall exceeding the absorptive capacity of soil and the flow
capacity of rivers, streams, and coastal areas. Land areas that are most subjected to floods are areas situated
adjacent to rivers and streams, that are known as floodplain and therefore considered as “flood-prone”. These
areas are hazardous to development activities if the vulnerability of those activities exceeds an acceptable level.
The main objectives of this study are; to identify floodplains and other susceptible areas, and to assess the
extent of disaster impact in the study area which is located at Kota Tinggi, Johor, Malaysia. This area
experienced an unprecedented flood during December of 2006 to January of 2007.Questions such as how often
and how long the floodplain will be covered by water, and at what time of year flooding can be expected need to
be answered. Thus, an understanding of the dynamic nature of floodplains is greatly required. Multi-temporal
Radarsat-1images, Landsat ETM+ image, topographical maps and land use maps were used in this study for
the purpose of delineating the flood extend before, during and after the flood event. DEM acquired from
topographic map is used to derive flood depth. The final outputs of this study are flood extent and flood depth
maps where both of these maps show the impact of the flood to environment, lives and properties. This map is
also important and can be applied to develop a comprehensive relief effort immediately after flooding.
This study analyzes how aerosol size and concentration can impact precipitation by serving as cloud condensation nuclei. Data on aerosol particle size distribution from AERONET and vertical profiles from a ceilometer were collected in Mayagüez, Puerto Rico during storms in May and June 2013 that produced over 50 mm of rain. The results suggest that fine aerosols can suppress precipitation while coarse aerosols can trigger more rainfall, as larger particles contain heavier droplets. Clouds with a higher concentration of smaller aerosolic particles rose higher with a greater cloud base height, while clouds with fewer but larger particles produced precipitation earlier.
This document describes a study that uses a multivariate non-homogenous Hidden Markov model to analyze rainfall data over the Bhakra region of northwest India from 1984-2004. The model classifies daily rainfall into three hidden states (dry, somewhat dry/wet, wet) and examines how factors like seasonal cycle, ENSO, and IOD affect transitions between these states. The results show the seasonal cycle significantly impacts summer rainfall through emission distributions, while ENSO and IOD effects are insignificant. For winter, the region is mainly dry with some intense storm events, and transition probabilities between states are not significantly impacted by ENSO or IOD either. Understanding rainfall dynamics in this region can help water management and agriculture.
Predicting Meteorological Drought in Iraq: An Evaluation of Machine Learning ...IRJET Journal
This document presents research on using machine learning techniques to predict meteorological drought in Iraq. It evaluates the Random Forest and Artificial Neural Network models for forecasting the Standardized Precipitation Index (SPI) over different time scales (3, 6, 9, and 12 months). The models are developed using monthly rainfall data from 1981 to 2021 from meteorological stations in northern Iraq. This region experiences a continental and subtropical semi-arid climate and frequent droughts. The document provides background on drought and the SPI index. It also describes the study area, data, Random Forest and Artificial Neural Network methods, and presents preliminary results of the model evaluations. The aim is to better understand drought patterns in Iraq to help mitigate impacts
Floodplain Mapping of Krishna River at Karad Using Hec-RasIRJET Journal
This document summarizes a study that used the HEC-RAS modeling software to map flood inundation areas along the Krishna River in India. The study collected topographic and flow data for the Krishna River basin and used HEC-RAS to perform a 1D steady-state hydraulic analysis. Cross-section and flow path data were created in RAS Mapper software. The HEC-RAS model was run for peak flows corresponding to 25, 50, and 100-year return periods. Floodplain maps showing inundated areas along the Krishna River were produced for each return period. The floodplain maps can help agencies better plan for flood risks and mitigate impacts in low-lying flood-prone
The document provides details about the Chennai floods of 2015. It describes how Chennai received over 33 cm of rain in a 24-hour period from December 1-2, causing widespread flooding and damage. Over 500 people lost their lives. The document examines factors like heavy rainfall, changes in weather patterns from global warming, destruction of wetlands, improper sewage and drainage systems, and human development that exacerbated the flooding in Chennai. It provides statistics on rainfall amounts, discusses the city's geology and infrastructure, and analyzes the impacts and response to the floods.
Record Setting: The Origins of Extreme Hail on 19 March 2018 during VORTEX-SEDeanMeyer14
Authors Dean Meyer and Ryan Wade. UAH Department of Atmospheric Science. Completed as Dean Meyer's student research as part of the UAH RCEU program at SWIRLL.
Robust Strategies of GIS and Geospatial Data mining techniques for drinking g...IJERA Editor
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International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
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Studies forecasting and flood management may be important to
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Cloudburst Predetermination System
1. IOSR Journal of Computer Engineering (IOSR-JCE)
e-ISSN: 2278-0661,p-ISSN: 2278-8727, Volume 17, Issue 3, Ver. V (May – Jun. 2015), PP 47-56
www.iosrjournals.org
DOI: 10.9790/0661-17354756 www.iosrjournals.org 47 | Page
Cloudburst Predetermination System
Arpit Tiwari 1
, S K Verma2
(Departmentof CSE, GBPEC, Pauri, India)
Abstract: Cloudburst is a devastating disaster that usually occurs during rainy seasons at Himalayan regions.
The recent floods in the ‘Kedarnath’ area, Uttarakhand are a classic example of flash floods in the Mandakini
River due to cloudburst that devastated the country by killing thousands of people besides livestock. The
traditional methods used for cloudburst prediction are weather forecasting, data mining techniques for weather
prediction by modelling meteorological data, laser beam atmospheric extinction measurements from manned
and unmanned aerospace vehicles. These techniques are more expensive and time consuming along with
uncertainty of accurate prediction. The proposed method in this paper is Arduino based cloudburst
predetermination system with real time calculation of rainfall intensity.
Keywords: aerospace; disaster; forecasting; intensity; prediction;
I. Introduction
Cloudburst is an extreme amount of precipitation, sometimes with hail and thunder,which normally
lasts no longer than a few minutes but is capable of creating flood.A cloud burst can suddenly dump 72300 tons
of water over one square area. A cloudburst usually occurs when rainfall intensity is greater than or equal to
100mm per hour.Cloudburst events over remote and unpopulated hilly areas often go unreported. The states of
Himachal Pradesh and Uttaranchal are the most affected due to the steep topography. Most of the damage to
property, communication systems and human causalities result from the flash floods that accompany
cloudbursts. In Kedarnath disaster [3]the main reason for flood was cloud burst causing a glacial lake burst and
flash flood downstream. Though the duration of the event was small compared to other flood disasters in the
country, it resulted in severe damage to property and life. Post-disaster satellite images depict that the river
banks were eroded completely along the Kedarnath valley due to the flash floods and few new channels were
visible. Extreme erosion took place in the upstream portion of Kedarnath. The satellite images show in figure 1
and 2 that massive landslides occurred in the upstream northeast region of the Kedarnath valley due to high
intensity rainfall. The disaster was due to an integrated effect of heavy rainfall intensity, sudden outburst of a
lake „Chorabari‟, and very steep topographic conditions. During the peak pilgrimage season from 13th-17th
June 2013, peaking on 16th, the region received unexpectedly heavy rain, about 375% more than normal,
causing unprecedented magnitude of death and destruction[15]. Rainfall measurements for June 16 and 17 at the
Dehradun station, of 220 mm and 370 mm respectively, indicate the severity of the rain during these days in the
region. Haridwar received 107 mm and 218 mm of rainfall on the two days. Uttarkashi received 122 mm and
207 mm. Mukteshwar (altitude over 2000 meters) received 237 mm and 183 mm respectively on June 17 and
18. Nainital on the same days received 176 mm and 170 mm of rainfall in these two days. Tough rainfall over a
24-hour period in different parts of Uttarakhand has greatly exceeded these figures in past (on many occasions
above 450-500 mm and once even 900 mm at Rajpur near Dehradun), prolonged heavy rainfall for nearly three
days over a large area. More pertinently, these numbers do not give the actual quantitative picture of the very
heavy rainfall in the higher reaches of the Himalayas (above 3000 meter) in Uttarakhand. Kedarnath, Gangotri
and Badrinath are located in this region and the impact has been most severe. This is because the rain gauge
stations of the India Meteorological Department are located largely in the lower Himalayan reaches (below 2000
meter) and there is no stations in the higher reaches (above 3000 meter). The satellite images of pre disaster and
post disaster clearly state that the town has almost disappeared from both east and west valley [8]. There is no
actual rain gauge present at the affected region. The satellite images were provided by NASA and IMD after the
devastating disaster took place. The image below shows the flow of water after cloud burst in both „Mandakini‟
and „Alaknanda‟ rivers[7].
2. Cloudburst Predetermination System
DOI: 10.9790/0661-17354756 www.iosrjournals.org 48 | Page
Fig 1: Satellite Image of the valley after cloudburst.
Fig 2: pre disaster and post disaster images of the valley.
On 13th September 2012 night in Chwanni, Mangoli and Kimana villages of Okhimath block in
Rudraprayag district of Uttarakhand (India), heavy rains completely inundated over 4 villages and eroded 2
more villages. There are no clues about 20-25 families in these villages. Given that the rainy days were almost
over, in western parts of Indian Himalayanmountains, there was continuous rainfall for over 2 months, that is
usually erratic, leading to flash floods and huge land-slides. The nature‟s fury is on, and people are paying the
toll to natural calamities, an alarming situation all over the region in terms of increasing disaster frequencies in
last few years. The Uttarkashi flood was one of the recent in this in Uttarakhand state. The area flooded has
huge chunk of dense forest that forms is part of famous protected corridor Kedarnath Musk deer sanctuary and
beautiful natural lake „Devaria tal‟ in mid-Himalayan range.A cloud burst was reported near Leh in Jammu and
Kashmir around 0130–0200 hours IST on 6th August, 2010 leading to flash flood and mud slides over the
region. It caused huge loss of lives and properties. The orography of the region plays a dominant role by
increasing the convection and hence the intensity of cloud burst. It also occurs over other orographically
dominant regions like the north-eastern states and Western Ghats region. It can occur also over the plain areas,
but the frequency of such occurrence is very rare. However Laddakh region of J&K is not known to be
frequently affected by this type of phenomena. It is a cold desert and average rainfall for the month of August is
15.4 mm only. The satellite images of Leh cloudburst are shown in figure.
3. Cloudburst Predetermination System
DOI: 10.9790/0661-17354756 www.iosrjournals.org 49 | Page
Fig 3: Satellite Images of Leh Cloudburst.
The above satellite image displays the formation of clouds over the affected region. If we see the cloud
formations before the cloudburst at Leh, we conclude that monsoon from Indian ocean and Bay of Bengal hit the
Himalayan region to form denser clouds and produce rain in western and southern parts of Himalayan
mountains. These denser clouds with continuous rain result Cloudburst. The satellite image of monsoon clouds
is shown below.
Fig 4: Satellite images before cloudburst at Leh
II. Related Work
The basic research method of cloud burst prediction is Synoptic weather prediction [6]. It is the
traditional approach in weather prediction. Synoptic concerns with the observation of different weather elements
within the specific time of observation. In order to keep track of the changing weather, a meteorological centre
prepares a series of synoptic charts every day, which forms the very basic of weather forecasts [10]. It involves
huge collection and analysis of observational data obtained from thousands of weather stations. The method
consists of predicting meteorological data with the help of satellite images. The images provide data regarding
various types of atmospheric changes and expected change in climate due to current atmospheric conditions of
particular area. The modern weather forecasting began by the invention of Electric Telegraph in 1835. Weather
4. Cloudburst Predetermination System
DOI: 10.9790/0661-17354756 www.iosrjournals.org 50 | Page
forecasting provides data about change in oceans, wind, clouds, temperature etc. Numerical weather prediction
[12] is the technique for weather forecasting. The technique uses the current state of the fluid and applying
equations of fluid dynamics or thermodynamics to predict the state after some time. Numerical weather
prediction (NWP) models are reasonably successful for large-scale medium-range weather forecasting,
prediction of precipitation remains a challenge. Mesoscale models, forced by the initial and boundary conditions
from the global model forecasts, are widely used to obtain regional forecasts at high spatial and temporal
resolution. They account for the influence of detailed topography, land cover, vegetation which are either
missing or smoothed in global models. Several operational forecasting centres apply mesoscale models for
detailed weather forecasts over small geographical regions. Mesoscale processes are influenced by surface
inhomogeneities in elevation, moisture, temperature, snow cover, vegetation, and surface roughness. Mesoscale
weather systems can be divided into two general categories: those forced primarily by instabilities in travelling
systems (e.g., squall lines or mesoscale convective complexes) and those forced by surface inhomogeneities
(e.g.mountain/valley circulations). Pielke (1984) noted that terrain-induced mesoscale systems are easier to
predict because they are forced by geographically fixed features. Paegle et al (1990) suggested that terrain
forced circulation is inherently more predictable than the synoptically induced flows, which are sensitive to the
data used to initialize the NWP models. Cloud Burst forecasting is predicted by the prediction of rainfall and
formation of clouds. The satellite based systems are expensive and require complete support system. Another
technique for cloud burst prediction is Data Mining techniques for weather prediction. Data mining is a process
which finds useful patterns from large amount of data. Data mining can also be defined as the process of
extracting implicit, previously unknown and useful information and knowledge from large quantities of noisy,
ambiguous, random, incomplete data for practical application. Weather prediction in Data mining concern with
finding hidden and useful patterns from a large amount of meteorological data. E. G. Petre presented a small
application of CART decision tree algorithm for weather prediction [16]. The data collected is registered over
Hong Kong. The data is recorded between 2002 and 2005. The data used for creating the dataset includes
parameters year, month, average pressure, relative humidity, clouds quantity, precipitation and average
temperature. Laser beam atmospheric extinction measurements from manned and unmanned aerospace vehicles
are also a method to predict cloud burst. The technique is based on measurements of the laser energy incident on
target surfaces of known geometric and reflective properties, by means of infrared detectors or infrared cameras
calibrated for radiance. The technique is too costly and needs full government support in order to be used.
III. Proposed Work
The work proposed in this paper is based on Arduino connected to a rain gauge in order to calculate
real time rainfall intensity. A Float Switch is connected to the rain gauge that monitors the water level in the rain
gauge. Additionally a submersible pump is also attached to the rain gauge. The main advantage of this type of
pump is that it prevents pumpcavitation, a problem associated with a high elevation difference between pump
and the fluidsurface. Submersible pumps push fluid to the surface as opposed to jet pumps having to pullfluids.
Submersibles are more efficient than jet pumps. A float is a device used to measure the level of water in the
water gauge. It consists of a fixed contact and moving contact. The fixed contact is fixed to the gauge and the
moving contact moves up and down based on the level of water. Float switches range from small to large and
may be as simple as a mercury switch inside a hinged float or as complex as a series of optical or conductance
sensors producing discrete outputs as the liquid reaches many different levels within the tank. The most
common type of float switch is simply a float raising a rod that actuates a micro-switch. A very common
application is in sump pumps and condensate pumps where the switch detects the rising level of liquid in the
sump or gauge and energizes an electrical pump which then pumps liquid out until the level of the liquid has
been substantially reduced, at which point the pump is switched off again. Float switches are often adjustable
and can include substantial hysteresis. That is, the switch's "turn on" point may be much higher than the "shut
off" point. This minimizes the on-off cycling of the associated pump.The pump shaft is connected to the gas
separator or the protector by a mechanical coupling at the bottom of the pump. Well fluids enter the pump
through an intake screen and are lifted by the pump stages. Other parts include the radial bearings (bushings)
distributed along the length of the shaft providing radial support to the pump shaft turning at high rotational
speeds. An optional thrust bearing takes up part of the axial forces arising in the pump but most of those forces
are absorbed by the protector‟s thrust bearing. Arduino is a single-board microcontroller, intended to make the
application of interactive objects or environments more accessible. The hardware consists of an open-source
hardware board designed around an 8-bit Atmel AVR microcontroller, or a 32-bit Atmel ARM. Current models
feature a USB interface, 6 analog input pins, as well as 14 digital I/O pins which allow the user to attach various
extension boards [1]-[2]. Multiple Arduino boards are connected to form a shield called Arduino Shield.
Arduino Shield is used for various types of applications. The Arduino Uno board is shown in figure below.
5. Cloudburst Predetermination System
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Fig 6: Arduino Uno board.
Arduino works on plug and program principle. The board is attached to the pc via USB and is
programmed with Arduino IDE, Integrated DevelopmentEnvironment, a tool kit to program the attached board.
The programs written in IDE are uploaded to the board and the board works as an automatic microcontroller.
External power come either from an AC-to-DC adapter which is plugged directly in wall-wart or battery. Leads
can be inserted in Gnd and Vin pin headers of the power connector. The board can operate on an external supply
of 6 to 20 volts. The recommended range is 7 to 12 volts. Each of the 14 digital pins of the board are used as an
input or output, using pinMode(), digitalWrite(), digitalRead() functions. They operate at 5 volts. Each pin is
able to provide or receive of maximum of 40 mA and has an internal pull-up resistor of 20-50 kOhms. Some of
the pins have specialized functions. Pin0(RX) and Pin1(TX) are reserved for receiving(RX) and
transmitting(TX) TTL serial data. These pins are connected to the corresponding pins of the ATmega8U2 USB-
to-TTL Serial chip.Pin2 and Pin3 are configured to trigger an interrupt on a low value, a rising or falling edge,
or a change in value.The Arduino has a number of facilities for communication with a computer, another
Arduino, or other microcontrollers. The ATmega328 provides UART TTL serial communication, available on
digital pins 0 (RX) and 1 (TX). An ATmega16U2 on the board channels this serial communication over USB
and appears as a virtual com port to software on the computer. The „16U2 firmware uses the standard USB
COM drivers, and no external driver is needed. The Arduino software includes a serial monitor that allows
simple textual data to be sent to and from the Arduino board. The RX and TX LEDs on the board will flash
when data is being transmitted via the USB-to-Serial chip and USB connection to the computer (but not for
serial communication on pins 0 and 1). A Software Serial library allows for serial communication on any of the
Arduino‟s digital pins. After the desired use, the uploaded program is removed and any new program is
uploaded to the board for a different functionality. The rain gauge calculates real time rainfall intensity with the
help of arduino and arduino records the data. The Servo mounted on arduino board provides the capability of
controlling the board from anywhere in the world. The board is programmed with 3 stages of alarms which are
raised according to the real time intensity. Cloud burst generally occurs at rainfall intensity greater than or equal
to 100 mm per hour. Alarm stages are associated with 3 threshold values. The data recorded by Arduino board is
monitored at base station or is sent to the configured device directly. Whenever alarm rises, alert messages are
broadcasted to the cellular phones of the people of nearby areas.The extreme condition of alarm is Alarm 3 at
which people are transported to a safe place. Message broadcasting to the cellular phones of the nearby people is
done with the help of an extra module mounted on the board. This extra module is plugged in the Arduino board
and is called „Arduino GSM Shield‟. GSM shield is an effective element of Arduino for communications. GSM
shield is shown in following figure.
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Fig 7: Arduino GSM Shield.
GSM shield is a small module with Sim Card slot provided to communicate with other devices,
terminals, Arduino boards. GSM shield uses GSM or CDMAsim cards. These cards are registered to the
corresponding network services provider by a sketch. A set of instructions in Arduino SDK is called a sketch.
Configuration of the sim card is done by connecting it to the computer. The Arduino GSM shield allows an
arduino to make/receive voice calls, send/receive sms messages. To make/receive voice calls, Arduino requires
an external speaker and a microphone. The shield uses a radio modem M10 by Quectel. The GSM library
consists of a large number of methods to communicate with the Arduino board. The shield uses digital pins Pin
2 and Pin 3 for software serial communication with M10. Pin 2 is connected to M10‟s transmitter pin TX and
Pin 3 is connected to M10‟s receiver pin RX. M10 is a Quad-band GSM/GPRS modem that works at GSM850
MHz, GSM900 MHz, DCS1800MHz and PCS1900 MHz. The GSM shield supports TCP/UDP and HTTP
protocols due to internet services. It provides a maximum speed of 85.6 kbps for both uplink and downlink. The
shield supports audio interfaces AIN1 and AOUT1, analog input channel and analog output channel
respectively. The functionality of GSM shield is similar to a cellular phone with internet facility. The real time
data is uploaded to the server with the help of GPRS services or is sent to the base station by text messages.
Arduino broadcasts UDP messages to multiple terminals. UDP broadcasting allow us to communicate with other
terminals without using GSM shield. The proposed method is represented diagrammatically as follows.
Fig 8: Design of proposed system
The proposed system uses rain gauge in order to save cost for rainfall intensity calculation. Rain gauge
is easy to build accurately and monitoring is easy by using float switch. The float switch monitors the
precipitation depth of the rainfall and sends results to the Arduino and Arduino calculates real time rainfall
intensity.
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IV. Simulation And Results
The design of the rain gauge plays a crucial role for accurate calculation of precipitation depth. The
pump is used to withdraw water from the gauge when the gauge is full. Pump-Gauge mechanism is simulated in
Proteus software. Proteus allows virtual arrangement of electronic components and their real time simulation. It
provides a powerful set of tools to build real time systems. Simulation screenshot of automatic pump-gauge
mechanism is shown in the figure below.
Fig 9: Proteus simulation of pump-gauge mechanism.
Water level indication in Gauge is simulated in labVIEW software and block diagram of circuit and simulation
screenshots are shown in figure below.
Fig 10: Circuit diagram of water level indication
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Fig 11: Increasing water level in the gauge
First of all the circular area of the top of the gauge is calculated. Let the diameter of the rain gauge is d mm. Let
precipitation depth is P mm.
Radius=d/2 mm
(1)Circular Area of top of the gauge = π*(d/2)² mm² (2)Current rainfall intensity = Precipitation Depth/Area of
top of the rain gauge(3)
Current rainfall intensity =P/ [3.142*(d/2)²] mm (4)
The rainfall intensity is calculated by Arduino on the basis of precipitation depth provided by the float
switch.Three types of threshold values are provided according to the real time rainfall intensity. These threshold
values are responsible for alarm generation. Variation in threshold values is provided according to the season.
Rainfall intensity is maximum in rainy season as compared to that of winter and summer seasons. Therefore
threshold values for monsoon season are greater than that of winter and summer 0seasons. Whenever rainfall
intensity crosses the first threshold i.e. 45 mm, Alarm 1 is generated and first alert message is broadcasted to the
people of nearby area concerning the cloud burst may occur. As the current rainfall intensity crosses the second
threshold i.e. 60 mm, Alarm 2 is generated and second alert message is broadcasted to the people of nearby area
to pack their essential things up and be ready to move towards safe place. When the current rainfall intensity
crosses the third threshold i.e. 80 mm, Alarm 3 is generated and third alert message is broadcasted to the people
of nearby area insuring them to leave as when the rainfall intensity crosses the value of 80 mm, there are 90%
chances of cloud burst to occur. The simulation is done in LabVIEW. LabVIEW is a breadboard
simulator.LabVIEW is the software that was used to interface the computer with the control device. It allows for
easy interfacing and control because of the fundamental concept behind which it has been developed, that is,
graphical programming. In order to interface the parallel port of the computer with the drive control hardware,
and ultimately, the synchronous pair, National Instruments LabVIEW was used. LabVIEW is an acronym for:
Laboratory Virtual Instrumentation Engineering Workbench. The programs written inLabVIEW are called
"Virtual Instruments" or VI‟s due to the instrumentation-related origin. The programs created are independent of
the type of machine that they are created for so programs can be transferred between different operating
systems. Additionally LabVIEW has a large set of built-in mathematical functions and graphical data
visualization and data input objects typically found in data acquisition and analysis applications.
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Fig13: Circuit layout of proposed system in LabVIEW.
The another cloud burst sensitive zone Pauri Garhwal, Uttarakhand, average temperature-rainfall intensity on
yearly basis is shown in following figure.
Fig 14: Average temperature rainfall analysis of Pauri
V. Conclusion
The proposed method for cloud burst predetermination is very effective as it calculates real time rainfall
intensity. No special permission or complex assembly is needed. No database is needed to predict as compared
to traditional methods. It consumes very less amount of time to be implemented unlike other techniques that
consume a lot of time to process very huge database and further finding patterns of hidden knowledge in order
to produce predictions. The method costs very less as the rain gauge can be built by human efforts and board is
programmed easily. We can use same board for different purposes.
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