Search results for: light rainfall events

Authors: Bumjo Kim, Hyun Jin Kim, Joon Ha Kim

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The separate sewer system is that collects the wastewater as a sewer pipe and rainfall as a stormwater pipe separately, and then sewage is treated in the wastewater treatment plant, the stormwater is discharged to rivers or lakes through stormwater drainage pipes. Unfortunately, even for separate sewer systems, it is not possible to prevent Rainfall Driven Inflow/Infiltration(RDII) completely to the sewer pipe. Even if the sewerage line is renovated, there is an ineluctable RDII due to the combined sewer system in the house or the difficulty of sewage maintenance in private areas. The basic statistical analysis was performed using environmental data including rainfall, sewage, water qualities and groundwater level in the strict of Gwangju in ​South Korea. During rainfall in the target area, RDII showed an increased rate of 13.4 ~ 53.0% compared to that of a clear day and showed a rapid hydrograph response of 0.3 ~ 3.0 hr. As a result of water quality analysis, BOD5 concentration decreased by 17.3 % and salinity concentration decreased by 8.8 % at the representative spot in the project area compared to the sunny day during rainfall. In contrast to the seasonal fluctuation range of 0.38 m ~ 0.55 m in groundwater in Gwangju area and 0.58 m ~ 0.78 m in monthly fluctuation range, while the difference between groundwater level and the depth of sewer pipe laying was 2.70 m on average, which is larger than the range of fluctuation. Comprehensively, it can be concluded that the increasing of flowrate at sewer line is due to not infiltration water caused by groundwater level rise, construction failure, cracking due to joint failure or conduit deterioration, rainfall was directly inflowed into the sewer line rapidly. Acknowledgements: This work was supported by the 'Climate Technology Development and Application' research project (#K07731) through a grant provided by GIST in 2017.

Keywords: ground water, rainfall, rainfall driven inflow/infiltration, separate sewer system

Procedia PDF Downloads 128

Authors: Sara Patricia Ibarra-Zavaleta, Rabindranarth Romero-Lopez, Rosario Langrave, Annie Poulin, Gerald Corzo, Mathias Glaus, Ricardo Vega-Azamar, Norma Angelica Oropeza

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The progressive change in climatic conditions worldwide has increased frequency and severity of extreme hydrometeorological events (EHE). Mexico is an example; this has been affected by the presence of EHE leaving economic, social and environmental losses. The objective of this research was to apply a Canadian distributed hydrological model (DHM) to tropical conditions and to evaluate its capacity to predict flows in a basin in the central Gulf of Mexico. In addition, the DHM (once calibrated and validated) was used to calculate the theoretical hydraulic power and the performance to predict streamflow before the presence of an EHE. The results of the DHM show that the goodness of fit indicators between the observed and simulated flows in the calibration process (NSE=0.83, RSR=0.021 and BIAS=-4.3) and validation: temporal was assessed at two points: point one (NSE=0.78, RSR=0.113 and BIAS=0.054) and point two (NSE=0.825, RSR=0.103 and BIAS=0.063) are satisfactory. The DHM showed its applicability in tropical environments and its ability to characterize the rainfall-runoff relationship in the study area. This work can serve as a tool for identifying vulnerabilities before floods and for the rational and sustainable management of water resources.

Keywords: HYDROTEL, hydraulic power, extreme hydrometeorological events, streamflow

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Authors: Radha Krishan, Deepak Khare, Bhaskar R. Nikam, Ayush Chandrakar

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Every irrigation project is planned considering long-term historical climatic conditions; however, the prompt climatic shift and change has come out with such circumstances which were inconceivable in the past. Considering this fact, scrutiny of rainfall and temperature trend has been carried out over the command area of Eastern Ganga Canal project for pre-climate shift period and post-climate shift periods in the present study. Non-parametric Mann-Kendall and Sen’s methods have been applied to study the trends in annual rainfall, seasonal rainfall, annual rainy day, monsoonal rainy days, average annual temperature and seasonal temperature. The results showed decreasing trend of 48.11 to 42.17 mm/decade in annual rainfall and 79.78 tSo 49.67 mm/decade in monsoon rainfall in pre-climate to post-climate shift periods, respectively. The decreasing trend of 1 to 4 days/decade has been observed in annual rainy days from pre-climate to post-climate shift period. Trends in temperature revealed that there were significant decreasing trends in annual (-0.03 ºC/yr), Kharif (-0.02 ºC/yr), Rabi (-0.04 ºC/yr) and summer (-0.02 ºC/yr) season temperature during pre-climate shift period, whereas the significant increasing trend (0.02 ºC/yr) has been observed in all the four parameters during post climate shift period. These results will help project managers in understanding the climate shift and lead them to develop alternative water management strategies.

Keywords: climate shift, rainfall trend, temperature trend, Mann-Kendall test, sen slope estimator, eastern Ganga canal command

Procedia PDF Downloads 108

Authors: Sabyasachi Mukhopadhyay, Joseph Ogutu, Gundula Bartzke, Hans-Peter Piepho

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Rainfall is a critical component of climate governing vegetation growth and production, forage availability and quality for herbivores. However, reliable rainfall measurements are not always available, making it necessary to predict rainfall values for particular locations through time. Predicting rainfall in space and time can be a complex and challenging task, especially where the rain gauge network is sparse and measurements are not recorded consistently for all rain gauges, leading to many missing values. Here, we develop a flexible Bayesian model for predicting rainfall in space and time and apply it to Narok County, situated in southwestern Kenya, using data collected at 23 rain gauges from 1965 to 2015. Narok County encompasses the Maasai Mara ecosystem, the northern-most section of the Mara-Serengeti ecosystem, famous for its diverse and abundant large mammal populations and spectacular migration of enormous herds of wildebeest, zebra and Thomson's gazelle. The model incorporates geographical and meteorological predictor variables, including elevation, distance to Lake Victoria and minimum temperature. We assess the efficiency of the model by comparing it empirically with the established Gaussian process, Kriging, simple linear and Bayesian linear models. We use the model to predict total monthly rainfall and its standard error for all 5 * 5 km grid cells in Narok County. Using the Monte Carlo integration method, we estimate seasonal and annual rainfall and their standard errors for 29 sub-regions in Narok. Finally, we use the predicted rainfall to predict large herbivore biomass in the Maasai Mara ecosystem on a 5 * 5 km grid for both the wet and dry seasons. We show that herbivore biomass increases with rainfall in both seasons. The model can handle data from a sparse network of observations with many missing values and performs at least as well as or better than four established and widely used models, on the Narok data set. The model produces rainfall predictions consistent with expectation and in good agreement with the blended station and satellite rainfall values. The predictions are precise enough for most practical purposes. The model is very general and applicable to other variables besides rainfall.

Keywords: non-stationary covariance function, gaussian process, ungulate biomass, MCMC, maasai mara ecosystem

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Authors: Racha El Kadiri, Mohamed Sultan, Henrique Momm, Zachary Blair, Rachel Schultz, Tamer Al-Bayoumi

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The Mediterranean Basin is a very diverse region of nationalities and climate zones, with a strong dependence on agricultural activities. Predicting long term (with a lead of 1 to 12 months) rainfall, and future droughts could contribute in a sustainable management of water resources and economical activities. In this study, an integrated approach was adopted to construct predictive tools with lead times of 0 to 12 months to forecast rainfall amounts over nine subzones of the Mediterranean Basin region. The following steps were conducted: (1) acquire, assess and intercorrelate temporal remote sensing-based rainfall products (e.g. The CPC Merged Analysis of Precipitation [CMAP]) throughout the investigation period (1979 to 2016), (2) acquire and assess monthly values for all of the climatic indices influencing the regional and global climatic patterns (e.g., Northern Atlantic Oscillation [NOI], Southern Oscillation Index [SOI], and Tropical North Atlantic Index [TNA]); (3) delineate homogenous climatic regions and select nine pilot study zones, (4) apply data mining methods (e.g. neural networks, principal component analyses) to extract relationships between the observed rainfall and the controlling factors (i.e. climatic indices with multiple lead-time periods) and (5) use the constructed predictive tools to forecast monthly rainfall and dry and wet periods. Preliminary results indicate that rainfall and dry/wet periods were successfully predicted with lead zones of 0 to 12 months using the adopted methodology, and that the approach is more accurately applicable in the southern Mediterranean region.

Keywords: rainfall, neural networks, climatic indices, Mediterranean

Procedia PDF Downloads 285

Authors: Ji-Yuan Lin, Yu-Ming Liou, Yi-Ting Chen, Chen-Syuan Lin

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Soil water index obtained by tank model is now commonly used in soil and sand disaster alarm system in Japan. Comparing with the rainfall trigging index in Taiwan, the tank model is easy to predict the slope water content on large-scale landslide. Therefore, this study aims to estimate the threshold value of large-scale landslide using the soil water index Sixteen typhoons and heavy rainfall events, were selected to establish the, to relationship between landslide event and soil water index. Finally, the proposed threshold values for landslides on country road No.89 are suggested in this study. The study results show that 95% landslide cases occurred in soil water index more than 125mm, and 30% of the more serious slope failure occurred in the soil water index is greater than 250mm. Beside, this study speculates when soil water index more than 250mm and the difference value between second tank and third tank less than -25mm, it leads to large-scale landslide more probably.

Keywords: soil water index, tank model, landslide, threshold values

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Authors: M. Sharif Imam Ibne Amir, Mohammad Masud Kamal Khan, Mohammad Golam Rasul, Raj H. Sharma, Fatema Akram

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Future flood can be predicted using the probable maximum flood (PMF). PMF is calculated using the historical discharge or rainfall data considering the other climatic parameter stationary. However, climate is changing globally and the key climatic variables are temperature, evaporation, rainfall and sea level rise (SLR). To develop scenarios to a basin or catchment scale these important climatic variables should be considered. Nowadays scenario based on climatic variables is more suitable than PMF. Six scenarios were developed for a large Fitzroy basin and presented in this paper.

Keywords: climate change, rainfall, potential evaporation, scenario, sea level rise (SLR), sub-catchment

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Authors: Nadarajah I. Ramesh

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Much of the research on stochastic point process models for rainfall has focused on Poisson cluster models constructed from either the Neyman-Scott or Bartlett-Lewis processes. The doubly stochastic Poisson process provides a rich class of point process models, especially for fine-scale rainfall modelling. This paper provides an account of recent development on this topic and presents the results based on some of the fine-scale rainfall models constructed from this class of stochastic point processes. Amongst the literature on stochastic models for rainfall, greater emphasis has been placed on modelling rainfall data recorded at hourly or daily aggregation levels. Stochastic models for sub-hourly rainfall are equally important, as there is a need to reproduce rainfall time series at fine temporal resolutions in some hydrological applications. For example, the study of climate change impacts on hydrology and water management initiatives requires the availability of data at fine temporal resolutions. One approach to generating such rainfall data relies on the combination of an hourly stochastic rainfall simulator, together with a disaggregator making use of downscaling techniques. Recent work on this topic adopted a different approach by developing specialist stochastic point process models for fine-scale rainfall aimed at generating synthetic precipitation time series directly from the proposed stochastic model. One strand of this approach focused on developing a class of doubly stochastic Poisson process (DSPP) models for fine-scale rainfall to analyse data collected in the form of rainfall bucket tip time series. In this context, the arrival pattern of rain gauge bucket tip times N(t) is viewed as a DSPP whose rate of occurrence varies according to an unobserved finite state irreducible Markov process X(t). Since the likelihood function of this process can be obtained, by conditioning on the underlying Markov process X(t), the models were fitted with maximum likelihood methods. The proposed models were applied directly to the raw data collected by tipping-bucket rain gauges, thus avoiding the need to convert tip-times to rainfall depths prior to fitting the models. One advantage of this approach was that the use of maximum likelihood methods enables a more straightforward estimation of parameter uncertainty and comparison of sub-models of interest. Another strand of this approach employed the DSPP model for the arrivals of rain cells and attached a pulse or a cluster of pulses to each rain cell. Different mechanisms for the pattern of the pulse process were used to construct variants of this model. We present the results of these models when they were fitted to hourly and sub-hourly rainfall data. The results of our analysis suggest that the proposed class of stochastic models is capable of reproducing the fine-scale structure of the rainfall process, and hence provides a useful tool in hydrological modelling.

Keywords: fine-scale rainfall, maximum likelihood, point process, stochastic model

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Authors: Farideh Aramideh

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The aim of this essay is to study the light in Zoroastrianism, and Masnavi by Rumi. The use of light goes back to thousand years B.C. the light in the legacy of ancient Iranian wisdom has been used in Mithraism, Zurvanism, Zoroastrianism and Manichaean religion and spirituality has been emanated in the world through the light. Ontology and angelology and the sacredness of fire in Zoroastrianism have been interpreted according to the concept of light. The ruling atmosphere on mazdaism world is the world which is full of light and angels, and light is one of the basis of worldview in ancient Iranian mysticism, especially Zoroastrianism and Manichaean, continued widely in Islamic mysticism, and also it always provokes discussions among scholars and mystics especially Iranian mystics. Light and fire are used as the signs and symbols of God's existence, The Shining lights emanated from the sacred essence of God, knowledge, and mysticism, love, discovering the wisdom and a way to God. Rumi speaks eloquently about light in Masnavi, and by using the light; he could render his readers the fundamental mystic subjects such as the true existence of God, the verity of prophets and saints, intuition of God, spiritual states of union with God and abiding in God, which are the most complicated mystic terms.

Keywords: zoroastrianism, myticims, Masnavi, light

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Authors: Iliya Bitrus Abaje

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This study examines the evidence of climate change scenario in Kaduna State from the analysis of temperature and rainfall data (1976-2015) from three meteorological stations along a geographic transect from the southern part to the northern part of the State. Different statistical methods were used in determining the changes in both the temperature and rainfall series. The result of the linear trend lines revealed a mean increase in average temperature of 0.73oC for the 40 years period of study in the State. The plotted standard deviation for the temperature anomalies generally revealed that years of temperatures above the mean standard deviation (hotter than the normal conditions) in the last two decades (1996-2005 and 2006-2015) were more than those below (colder than the normal condition). The Cramer’s test and student’s t-test generally revealed an increasing temperature trend in the recent decades. The increased in temperature is an evidence that the earth’s atmosphere is getting warmer in recent years. The linear trend line equation of the annual rainfall for the period of study showed a mean increase of 316.25 mm for the State. Findings also revealed that the plotted standard deviation for the rainfall anomalies, and the 10-year non-overlapping and 30-year overlapping sub-periods analysis in all the three stations generally showed an increasing trend from the beginning of the data to the recent years. This is an evidence that the study area is now experiencing wetter conditions in recent years and hence climate change. The study recommends diversification of the economic base of the populace with emphasis on moving away from activities that are sensitive to temperature and rainfall extremes Also, appropriate strategies to ameliorate the scourge of climate change at all levels/sectors should always take into account the recent changes in temperature and rainfall amount in the area.

Keywords: anomalies, linear trend, rainfall, temperature

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Authors: Yasmeen Saleem, Pedro Berliner, Nurit Agam

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The most severe limitation for plant production in arid areas is water. Rainfall events are rare but can have pulses of high intensity. As a result, crusts are formed, which decreases infiltration into the soil, and results additionally in erosive losses of soil. Direct evaporation of water from the wetted soil can account for large fractions of the water stored in the soil. Different kinds of mulches have been used to decrease the loss of water in arid and semi-arid region. This study aims to evaluate the effect of polystyrene styrofoam pellets mulch on soil infiltration, runoff, and evaporation as a more efficient and economically viable mulch alternative. Polystyrene styrofoam pellets of two sizes (0.5 and 1 cm diameter) will be placed on top of the soil in two mulch layer depths (1 and 2 cm), in addition to the non-mulched treatment. The rainfall simulator will be used as an artificial source of rain. The preliminary results in the prototype experiment indicate that polystyrene styrofoam pellets decreased runoff, increased soil-water infiltration. We are still testing the effect of these pellets on decreasing the soil-water evaporation.

Keywords: synthetic mulch, runoff, evaporation, infiltration

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Authors: Evangelos Baltas, Elissavet Feloni, Dimitrios Karpouzos

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A crucial issue in hydrologic design is the sizing of structures and flood-control works in areas with limited data. This research work highlights the significant variation in probable maximum flood (PMF) for a design hyetograph, using different theoretical functions of rainfall-runoff transformation. The analysis focuses on seven subbasins with different characteristics in the municipality of Florina, northern Greece. This area is a semi-agricultural one which hosts important activities, such as the operation of one of the greatest fields of lignite for power generation in Greece. Results illustrate the notable variation in estimations among the methodologies used for the examined subbasins.

Keywords: rainfall, runoff, hydrologic design, PMF

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Authors: Anthony Iyenjamu, Josiah Adeyemo

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Due to the increasing water scarcity in South Africa, the prime focus of irrigation in South Africa shifts to creating feasible water sources and the efficient use of these sources. These irrigation systems in South Africa are implemented because of low and erratic rainfall and high evaporative demand. Irrigation contributes significantly to crop production in South Africa, as the mean annual precipitation for the country is usually less than 500mm. This is considered to be the minimum required for rain fed cropping. Even though the rainfall is low, a lot of the water in various areas in South Africa is lost due to runoff into storm water systems that run to the rivers and eventually into the sea. This study reviews the irrigation systems in South Africa which can be vastly improved by creating irrigation dams. A method of which may seem costly at first but rewarding with time. The study investigates the process of creating dam capacity capable of sustaining a suitable area size of land to be irrigated and thus diverting all runoff into these dams. This type of infrastructure method vastly improves various sectors in our irrigation systems. Extensive research is carried out in the surrounding area in which the dam should be constructed. Rainfall patterns and rainfall data is used for calculations of which period the dam will be at its optimum using rainfall. The size of the area irrigated was used to calculate the size of the irrigation dam to be constructed. The location of the dam must be situated as close to the river as possible to minimize the excessive use of pipelines to the dam. This study also investigated all existing resources to alleviate the cost. It was found that irrigation dams could solve the erratic distribution of rainfall in South Africa for irrigation purposes.

Keywords: irrigation, rainfed, rain harvesting, reservoir

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Authors: Nitaya Buntao

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This paper considers the problems of interval estimation for rainfall mean of the lognormal distribution and the delta-lognormal distribution in Northeastern Thailand. We present here the modified generalized pivotal approach (MGPA) compared to the modified method of variance estimates recovery (MMOVER). The performance of each method is examined in term of coverage probabilities and average lengths by Monte Carlo simulation. An extensive simulation study indicates that the MMOVER performs better than the MGPA approach in terms of the coverage probability; it results in highly accurate coverage probability.

Keywords: rainfall mean, interval estimation, lognormal distribution, delta-lognormal distribution

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Authors: Chulsang Yoo, Gildo Kim

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Dual polarization radar provides comprehensive information about rainfall by measuring multiple parameters. In Korea, for the rainfall estimation, JPOLE and CSU-HIDRO algorithms are generally used. This study evaluated the local applicability of JPOLE and CSU-HIDRO algorithms in Korea by using the observed rainfall data collected on August, 2014 by the Biseulsan dual polarization radar data and KMA AWS. A total of 11,372 pairs of radar-ground rain rate data were classified according to thresholds of synthetic algorithms into suitable and unsuitable data. Then, evaluation criteria were derived by comparing radar rain rate and ground rain rate, respectively, for entire, suitable, unsuitable data. The results are as follows: (1) The radar rain rate equation including KDP, was found better in the rainfall estimation than the other equations for both JPOLE and CSU-HIDRO algorithms. The thresholds were found to be adequately applied for both algorithms including specific differential phase. (2) The radar rain rate equation including horizontal reflectivity and differential reflectivity were found poor compared to the others. The result was not improved even when only the suitable data were applied. Acknowledgments: This work was supported by the Basic Science Research Program through the National Research Foundation of Korea, funded by the Ministry of Education (NRF-2013R1A1A2011012).

Keywords: CSU-HIDRO algorithm, dual polarization radar, JPOLE algorithm, radar rainfall estimation algorithm

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Authors: L.Jowkar. M.Samiee

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Models or systems based on rainfall and runoff are numerous and have been formulated and applied depending on the precipitation regime, temperature, and climate. In this study, the ArcCN-Runoff rain-runoff modeling tool was used to estimate the spatial variability of the rainfall-runoff relationship in Sartang Ramon in Jiroft watershed. In this study, the runoff was estimated from 6-hour rainfall. The results showed that based on hydrological soil group map, soils with hydrological groups A, B, C, and D covered 1, 2, 55, and 41% of the basin, respectively. Given that the majority of the area has a slope above 60 percent and results of soil hydrologic groups, one can conclude that Sartang Ramon Basin has a relatively high potential for producing runoff. The average runoff height for a 6-hour rainfall with a 2-year return period is 26.6 mm. The volume of runoff from the 2-year return period was calculated as the runoff height of each polygon multiplied by the area of the polygon, which is 137913486 m³ for the whole basin.

Keywords: Arc CN-Run off, rain-runoff, return period, watershed

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Authors: Haider Karar, Saghir Ahmad, Amjad Ali, Ibrar Ul Haq

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The experiment was conducted at Cotton Research Station, Multan to study the impact of weather factors and red cotton bug (RCB) on cotton boll disease yielded yellowish lint during 2012. The population on RCB along with abiotic factors was recorded during three consecutive years i.e. 2012, 2013, and 2014. Along with population of RCB and abiotic factors, the number of unopened/opened cotton bolls (UOB), percent yellowish lint (YL) and whitish lint (WL) were also recorded. The data revealed that the population per plant of RCB remain 0.50 and 0.34 during years 2012, 2013 but increased during 2014 i.e. 3.21 per plant. The number of UOB were more i.e. 13.43% in 2012 with YL 76.30 and WL 23.70% when average maximum temperature 34.73◦C, minimum temperature 22.83◦C, RH 77.43% and 11.08 mm rainfall. Similarly in 2013 the number of UOB were less i.e. 0.34 per plant with YL 1.48 and WL 99.53 per plant when average maximum temperature 34.60◦C, minimum temperature 23.37◦C, RH 73.01% and 9.95 mm rainfall. During 2014 RCB population per plant was 3.22 with no UOB and YL was 0.00% and WL was 100% when average maximum temperature 23.70◦C, minimum temperature 23.18◦C, RH 71.67% and 4.55 mm rainfall. So it is concluded that the cotton bolls disease was more during 2012 due to more rainfall and more percent RH. The RCB may be the carrier of boll rot disease pathogen during more rainfall.

Keywords: red cotton bug, cotton, weather factors, years

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Authors: Darshan Panda, Lambodar Behera, M. J. Baig, Sudhanshu Sekhar

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Low light intensity is a significant limitation for grain yield and quality in rice. However, yield is not significantly reduced in low-light tolerant rice varieties. The work, therefore, planned for comparative transcriptome profiling under low light stress to decipher the genes involved and molecular mechanism of low light tolerance in rice. At the active tillering stage, 50% low light exposure for one day, three days, and five days were given to Swarnaprabha (low light tolerant) and IR8 (low light sensitive) rice varieties. Illumina (HiSeq) platform was used for transcriptome sequencing. A total of 6,652 and 12,042 genes were differentially expressed due to low light intensity in Swarnaprabha and IR8, respectively, as compared to control. CAB, LRP, SBPase, MT15, TF PCL1, and Photosystem I & II complex related gene expressions were mostly increased in Swarnaprabha upon the longer duration of low light exposure, which was not found in IR8 as compared to control. Their expressions were validated by qRT-PCR. The overall study suggested that the maintenance of grain yield in the tolerant variety under low light might be the result of accelerated expression of the genes, which enable the plant to keep the photosynthetic processes moving at the same pace even under low light.

Keywords: rice, low light, photosynthesis, yield

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Authors: Vinay C. Doranalu, Amba Shetty

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In recent days due to climate change, there is a large variation in spatial distribution of daily rainfall within a small region. Rainfall is one of the main end climatic variables which affect spatio-temporal patterns of water availability. The real task postured by the change in climate is identification, estimation and understanding the uncertainty of rainfall. This study intended to analyze the spatial variations and temporal trends of daily precipitation using high resolution (0.25º x 0.25º) gridded data of Indian Meteorological Department (IMD). For the study, 38 grid points were selected in the study area and analyzed for daily precipitation time series (113 years) over the period 1901-2013. Grid points were divided into two zones based on the elevation and situated location of grid points: Low Land (exposed to sea and low elevated area/ coastal region) and High Land (Interior from sea and high elevated area/western Ghats). Time series were applied to examine the spatial analysis and temporal trends in each grid points by non-parametric Mann-Kendall test and Theil-Sen estimator to perceive the nature of trend and magnitude of slope in trend of rainfall. Pettit-Mann-Whitney test is applied to detect the most probable change point in trends of the time period. Results have revealed remarkable monotonic trend in each grid for daily precipitation of the time series. In general, by the regional cluster analysis found that increasing precipitation trend in shoreline region and decreasing trend in Western Ghats from recent years. Spatial distribution of rainfall can be partly explained by heterogeneity in temporal trends of rainfall by change point analysis. The Mann-Kendall test shows significant variation as weaker rainfall towards the rainfall distribution over eastern parts of the Western Ghats region of Karnataka.

Keywords: change point analysis, coastal region India, gridded rainfall data, non-parametric

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Authors: Habib Abida, Noura Dahri

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Flash floods are among the most serious natural hazards that have disastrous environmental and human impacts. They are associated with exceptional rain events, characterized by short durations, very high intensities, rapid flows and small spatial extent. Flash floods happen very suddenly and are difficult to forecast. They generally cause damage to agricultural crops and property, infrastructures, and may even result in the loss of human lives. The city of Gabes (South-eastern Tunisia) has been exposed to numerous damaging floods because of its mild topography, clay soil, high urbanization rate and erratic rainfall distribution. The risks associated with this situation are expected to increase further in the future because of climate change, deemed responsible for the increase of the frequency and the severity of this natural hazard. Recently, exceptional events hit Gabes City causing death and major property losses. A major flooding event hit the region on June 2nd, 2014, causing human deaths and major material losses. It resulted in the stagnation of storm water in the numerous low zones of the study area, endangering thereby human health and causing disastrous environmental impacts. The characterization of flood risk in Gabes Watershed (South-eastern Tunisia) is considered an important step for flood management. Analytical Hierarchy Process (AHP) method coupled with Monte Carlo simulation and geographic information system were applied to delineate and characterize flood areas. A spatial database was developed based on geological map, digital elevation model, land use, and rainfall data in order to evaluate the different factors susceptible to affect flood analysis. Results obtained were validated by remote sensing data for the zones that showed very high flood hazard during the extreme rainfall event of June 2014 that hit the study basin. Moreover, a survey was conducted from different areas of the city in order to understand and explore the different causes of this disaster, its extent and its consequences.

Keywords: analytical hierarchy process, flash floods, Gabes, remote sensing, Tunisia

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Authors: Muhammad Suradi, Sugiarto, Abdullah Latip

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Many roadside slope failures occur during the rainy season, particularly in the period of extreme rainfall along Connecting National Road of Salubatu-Mambi, West Sulawesi, Indonesia. These occurrences cause traffic obstacles and endanger people along and around the road. Research collaboration between P2JN (National Road Construction Board) West Sulawesi Province, who authorize to supervise the road condition, and Ujung Pandang State Polytechnic (Applied University) was established to cope with the landslide problem. This research aims to determine factors triggering roadside slope failures and their optimum stabilizing solution. To achieve this objective, site observation and soil investigation were carried out to obtain parameters for analyses of rainfall-induced slope instability and reinforcement design using the SV Flux and SV Slope software. The result of this analysis will be taken into account for the next analysis to get an optimum design of the slope reinforcement. The result indicates some factors such as steep slopes, sandy soils, and unvegetated slope surface mainly contribute to the slope failures during intense rainfall. With respect to the contributing factors as well as construction material and technology, cantilever/butressing retaining wall becomes the optimum solution for the roadside slope reinforcement.

Keywords: roadside slope, failure, rainfall, slope reinforcement, optimum solution

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Authors: Zhiyuan Tang, Ju Zhang, Wenyuan Wu

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In this research, a car-following model with consideration of the status of the brake light is proposed. The numerical results show that the stability of the traffic flow is improved. The ability of the brake light to reduce car accident is also showed.

Keywords: brake light, car-following model, traffic flow, regional planning, transportation

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Authors: Sudip Kumar Kundu, Charu Singh

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As a great physiographic divide, the Himalayas affecting a large system of water and air circulation which helps to determine the climatic condition in the Indian subcontinent to the south and mid-Asian highlands to the north. It creates obstacles by defending chill continental air from north side into India in winter and also defends rain-bearing southwesterly monsoon to give up maximum precipitation in that area in monsoon season. Nowadays extreme weather conditions such as heavy precipitation, cloudburst, flash flood, landslide and extreme avalanches are the regular happening incidents in the region of North Western Himalayan (NWH). The present study has been planned to investigate the suitable model(s) to find out the rainfall pattern over that region. For this investigation, selected models from Coordinated Regional Climate Downscaling Experiment (CORDEX) and Coupled Model Intercomparison Project Phase 5 (CMIP5) has been utilized in a consistent framework for the period of 1976 to 2000 (historical). The ability of these driving models from CORDEX domain and CMIP5 has been examined according to their capability of the spatial distribution as well as time series plot of rainfall over NWH in the rainy season and compared with the ground-based Indian Meteorological Department (IMD) gridded rainfall data set. It is noted from the analysis that the models like MIROC5 and MPI-ESM-LR from the both CORDEX and CMIP5 provide the best spatial distribution of rainfall over NWH region. But the driving models from CORDEX underestimates the daily rainfall amount as compared to CMIP5 driving models as it is unable to capture daily rainfall data properly when it has been plotted for time series (TS) individually for the state of Uttarakhand (UK) and Himachal Pradesh (HP). So finally it can be said that the driving models from CMIP5 are better than CORDEX domain models to investigate the rainfall pattern over NWH region.

Keywords: global warming, rainfall, CMIP5, CORDEX, NWH

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Authors: Pier Andrea Marras, Daniela Lima, Pedro Matos Soares, Rita Maria Cardoso, Daniela Medas, Elisabetta Dore, Giovanni De Giudici

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Climate change effects on the hydrologic cycle are the main concern for the evaluation of water management strategies. Climate models project scenarios of precipitation changes in the future, considering greenhouse emissions. In this study, the EURO-CORDEX (European Coordinated Regional Downscaling Experiment) climate models were first evaluated in a Mediterranean island (Sardinia) against observed precipitation for a historical reference period (1976-2005). A weighted multi-model ensemble (ENS) was built, weighting the single models based on their ability to reproduce observed rainfall. Future projections (2071-2100) were carried out using the 8.5 RCP emissions scenario to evaluate changes in precipitations. ENS was then used as climate forcing for the SWAT model (Soil and Water Assessment Tool), with the aim to assess the consequences of such projected changes on streamflow and runoff of two small catchments located in the South-West Sardinia. Results showed that a decrease of mean rainfall values, up to -25 % at yearly scale, is expected for the future, along with an increase of extreme precipitation events. Particularly in the eastern and southern areas, extreme events are projected to increase by 30%. Such changes reflect on the hydrologic cycle with a decrease of mean streamflow and runoff, except in spring, when runoff is projected to increase by 20-30%. These results stress that the Mediterranean is a hotspot for climate change, and the use of model tools can provide very useful information to adopt water and land management strategies to deal with such changes.

Keywords: EURO-CORDEX, climate change, hydrology, SWAT model, Sardinia, multi-model ensemble

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Authors: Sheng-Chuan Hsu

Abstract:

Because the existing structure of ambient light sensor is most silicon photodiode device, it is extremely sensitive in the red and infrared regions. Even though the IR-Cut filter had added, it still cannot completely eliminate the influence of infrared light, and the spectral response of infrared light was stronger than that of the human eyes. Therefore, it is not able to present the vision spectrum of the human eye reacts with the ambient light. Then it needs to consider that the human eye feels the spectra that show significant differences between light and dark place. Consequently, in practical applications, we must create and develop advanced device of human-like photosensor which can solve these problems of ambient light sensor and let cognitive lighting system to provide suitable light to achieve the goals of vision spectrum of human eye and save energy.

Keywords: ambient light sensor, vision spectrum, cognitive lighting system, human eye

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Authors: Ayal Siegel, Moshe Inbar, Amatzya Peled

Abstract:

This study examined the characteristic runoff coefficient in different urban areas. The main area studied is located in the city of Haifa, northern Israel. Haifa spreads out eastward from the Mediterranean seacoast to the top of the Carmel Mountain range with an elevation of 300 m. above sea level. For this research project, four watersheds were chosen, each characterizing a different part of the city; 1) Upper Hadar, a spacious suburb on the upper mountain side; 2) Qiryat Eliezer, a crowded suburb on a level plane of the watershed; 3) Technion, a large technical research university which is located halfway between the top of the mountain range and the coast line. 4) Keret, a remote suburb, on the southwestern outskirts of Haifa. In all of the watersheds found suitable, instruments were installed to continuously measure the water level flowing in the channels. Three rainfall gauges scattered in the study area complete the hydrological requirements for this research project. The runoff coefficient C in peak discharge events was determined by the Rational Formula. The main research finding is the significant relationship between the intensity of rainfall, and the impervious area which is connected to the drainage system of the watershed. For less intense rainfall, the full potential of the connected impervious area will not be exploited. As a result, the runoff coefficient value decreases as do the peak discharge rate and the runoff yield from the storm event. The research results will enable application to other areas by means of hydrological model to be be set up on GIS software that will make it possible to estimate the runoff coefficient of any given city watershed.

Keywords: runoff coefficient, rational method, time of concentration, connected impervious area.

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Authors: Seema Paul, John Mango Magero, Prosun Bhattacharya, Zahra Kalantari, Steve W. Lyon

Abstract:

The purpose of this review paper is to develop an understanding of lake hydrodynamics and the potential climate impact on the Lake Victoria (LV) catchment scale. This paper briefly discusses the main problems of lake hydrodynamics and its’ solutions that are related to quality assessment and climate effect. An empirical methodology in modeling and mapping have considered for understanding lake hydrodynamic and visualizing the long-term observational daily, monthly, and yearly mean dataset results by using geographical information system (GIS) and Comsol techniques. Data were obtained for the whole lake and five different meteorological stations, and several geoprocessing tools with spatial analysis are considered to produce results. The linear regression analyses were developed to build climate scenarios and a linear trend on lake rainfall data for a long period. A potential evapotranspiration rate has been described by the MODIS and the Thornthwaite method. The rainfall effect on lake water level observed by Partial Differential Equations (PDE), and water quality has manifested by a few nutrients parameters. The study revealed monthly and yearly rainfall varies with monthly and yearly maximum and minimum temperatures, and the rainfall is high during cool years and the temperature is high associated with below and average rainfall patterns. Rising temperatures are likely to accelerate evapotranspiration rates and more evapotranspiration is likely to lead to more rainfall, drought is more correlated with temperature and cloud is more correlated with rainfall. There is a trend in lake rainfall and long-time rainfall on the lake water surface has affected the lake level. The onshore and offshore have been concentrated by initial literature nutrients data. The study recommended that further studies should consider fully lake bathymetry development with flow analysis and its’ water balance, hydro-meteorological processes, solute transport, wind hydrodynamics, pollution and eutrophication these are crucial for lake water quality, climate impact assessment, and water sustainability.

Keywords: climograph, climate scenarios, evapotranspiration, linear trend flow, rainfall event on LV, concentration

Procedia PDF Downloads 61

Authors: Youness Laaroussi, Zine Elabidine Guennoun, Amine Amar

Abstract:

Modeling and forecasting dynamics of rainfall occurrences constitute one of the major topics, which have been largely treated by statisticians, hydrologists, climatologists and many other groups of scientists. In the same issue, we propose in the present paper a new hybrid method, which combines Extreme Values and fractal theories. We illustrate the use of our methodology for transformed Emberger Index series, constructed basing on data recorded in Oujda (Morocco). The index is treated at first by Peaks Over Threshold (POT) approach, to identify excess observations over an optimal threshold u. In the second step, we consider the resulting excess as a fractal object included in one dimensional space of time. We identify fractal dimension by the box counting. We discuss the prospect descriptions of rainfall data sets under Generalized Pareto Distribution, assured by Extreme Values Theory (EVT). We show that, despite of the appropriateness of return periods given by POT approach, the introduction of fractal dimension provides accurate interpretation results, which can ameliorate apprehension of rainfall occurrences.

Keywords: extreme values theory, fractals dimensions, peaks Over threshold, rainfall occurrences

Procedia PDF Downloads 336

Authors: S. Kurian, S. Satpathy, S. K. Gupta, S. Arya, D. K. Sharma

Abstract:

Advances in the use of health care technology have resulted in increased adverse events (AEs) related to the use of medical devices. The study focused on the existing reporting systems. This study was conducted in a tertiary care public sector hospital. Devices included Syringe infusion pumps, Cardiac monitors, Pulse oximeters, Ventilators and Defibrillators. A total of 211 respondents were recruited. Interviews were held with 30 key informants. Medical records were scrutinized. Relevant statistical tests were used. Resident doctors reported maximum frequency of AEs, followed by nurses; and least by consultants. A significant association was found between the cadre of health care personnel and awareness that the patients and bystanders have a risk of sustaining AE. Awareness regarding reporting of AEs was low, and it was generally done verbally. Other critical findings are discussed in the light of the barriers to reporting, reasons for non-compliance, recording system, and so on.

Keywords: adverse events, health care technology, medical devices, public sector hospital, reporting systems

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Authors: Mohammadamin Hashemi, Mohammadreza Kashizadeh

Abstract:

Droughts pose a significant threat to sustainable water resource management, agriculture, and socioeconomic sectors, particularly in the field of climate change. This study investigates drought simulation using rainfall-runoff modelling in the Cuneo district, Italy, over the past 60-year period. The study leverages the TUW model, a lumped conceptual rainfall-runoff model with a semi-distributed operation capability. Similar in structure to the widely used Hydrologiska Byråns Vattenbalansavdelning (HBV) model, the TUW model operates on daily timesteps for input and output data specific to each catchment. It incorporates essential routines for snow accumulation and melting, soil moisture storage, and streamflow generation. Multiple catchments' discharge data within the Cuneo district form the basis for thorough model calibration employing the Kling-Gupta Efficiency (KGE) metric. A crucial metric for reliable drought analysis is one that can accurately represent low-flow events during drought periods. This ensures that the model provides a realistic picture of water availability during these critical times. Subsequent validation of monthly discharge simulations thoroughly evaluates overall model performance. Beyond model development, the investigation delves into drought analysis using the robust Standardized Runoff Index (SRI). This index allows for precise characterization of drought occurrences within the study area. A meticulous comparison of observed and simulated discharge data is conducted, with particular focus on low-flow events that characterize droughts. Additionally, the study explores the complex interplay between land characteristics (e.g., soil type, vegetation cover) and climate variables (e.g., precipitation, temperature) that influence the severity and duration of hydrological droughts. The study's findings demonstrate successful calibration of the TUW model across most catchments, achieving commendable model efficiency. Comparative analysis between simulated and observed discharge data reveals significant agreement, especially during critical low-flow periods. This agreement is further supported by the Pareto coefficient, a statistical measure of goodness-of-fit. The drought analysis provides critical insights into the duration, intensity, and severity of drought events within the Cuneo district. This newfound understanding of spatial and temporal drought dynamics offers valuable information for water resource management strategies and drought mitigation efforts. This research deepens our understanding of drought dynamics in the Cuneo region. Future research directions include refining hydrological modelling techniques and exploring future drought projections under various climate change scenarios.

Keywords: hydrologic extremes, hydrological drought, hydrological modelling, machine learning, rainfall-runoff modelling

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