Search results for: multivariate disaggregation rainfall model

Authors: Mohd Khairul Bazli Mohd Aziz, Fadhilah Yusof, Zulkifli Yusop, Zalina Mohd Daud, Mohammad Afif Kasno

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Recent developed rainfall network design techniques have been discussed and compared by many researchers worldwide due to the demand of acquiring higher levels of accuracy from collected data. In many studies, rain-gauge networks are designed to provide good estimation for areal rainfall and for flood modelling and prediction. In a certain study, even using lumped models for flood forecasting, a proper gauge network can significantly improve the results. Therefore existing rainfall network in Johor must be optimized and redesigned in order to meet the required level of accuracy preset by rainfall data users. The well-known geostatistics method (variance-reduction method) that is combined with simulated annealing was used as an algorithm of optimization in this study to obtain the optimal number and locations of the rain gauges. Rain gauge network structure is not only dependent on the station density; station location also plays an important role in determining whether information is acquired accurately. The existing network of 84 rain gauges in Johor is optimized and redesigned by using rainfall, humidity, solar radiation, temperature and wind speed data during monsoon season (November – February) for the period of 1975 – 2008. Three different semivariogram models which are Spherical, Gaussian and Exponential were used and their performances were also compared in this study. Cross validation technique was applied to compute the errors and the result showed that exponential model is the best semivariogram. It was found that the proposed method was satisfied by a network of 64 rain gauges with the minimum estimated variance and 20 of the existing ones were removed and relocated. An existing network may consist of redundant stations that may make little or no contribution to the network performance for providing quality data. Therefore, two different cases were considered in this study. The first case considered the removed stations that were optimally relocated into new locations to investigate their influence in the calculated estimated variance and the second case explored the possibility to relocate all 84 existing stations into new locations to determine the optimal position. The relocations of the stations in both cases have shown that the new optimal locations have managed to reduce the estimated variance and it has proven that locations played an important role in determining the optimal network.

Keywords: geostatistics, simulated annealing, semivariogram, optimization

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Authors: Panpan Xu, Qiying Zhang, Hui Qian

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Groundwater is main source of water supply in the Guanzhong Basin, China. To investigate the quality of groundwater for agricultural purposes in Jiaokou Irrigation District located in the east of the Guanzhong Basin, 141 groundwater samples were collected for analysis of major ions (K⁺, Na⁺, Mg²⁺, Ca²⁺, SO₄^2-, Cl^-, HCO₃^-, and CO₃^2-), pH, and total dissolved solids (TDS). Sodium percentage (Na%), residual sodium carbonate (RSC), magnesium hazard (MH), and potential salinity (PS) were applied for irrigation water quality assessment. In addition, multivariate statistical techniques were used to identify the underlying hydrogeochemical processes. Results show that the content of TDS mainly depends on Cl^-, Na⁺, Mg²⁺, and SO₄^2-, and the HCO₃^- content is generally high except for the eastern sand area. These are responsible for complex hydrogeochemical processes, such as dissolution of carbonate minerals (dolomite and calcite), gypsum, halite, and silicate minerals, the cation exchange, as well as evaporation and concentration. The average evaluation levels of Na%, RSC, MH, and PS for irrigation water quality are doubtful, good, unsuitable, and injurious to unsatisfactory, respectively. Therefore, it is necessary for decision makers to comprehensively consider the indicators and thus reasonably evaluate the irrigation water quality.

Keywords: irrigation water quality, multivariate statistical analysis, groundwater, hydrogeochemical process

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Authors: Keiwoma Mark Yila, Mathew Lamrana Siaffa Gboku, Mohamed Sahr Lebbie, Lamin Ibrahim Kamara

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Rainfall and temperature are the important variables which are often used to trace climate variability and change. A perception study and analysis of climatic data were conducted to assess the changes in rainfall and temperature and their impact on crop production in Moyamba district, Sierra Leone. For the perception study, 400 farmers were randomly selected from farmer-based organizations (FBOs) in 4 chiefdoms, and 30 agricultural extension workers (AWEs) in the Moyamba district were purposely selected as respondents. Descriptive statistics and Kendall’s test of concordance was used to analyze the data collected from the farmers and AEWs. Data for the analysis of variability and trends of rainfall and temperature from 1991 to 2020 were obtained from the Sierra Leone Meteorological Agency and Njala University and grouped into monthly, seasonal and annual time series. Regression analysis was used to determine the statistical values and trend lines for the seasonal and annual time series data. The Mann-Kendall test and Sen’s Slope Estimator were used to analyze the trends' significance and magnitude, respectively. The results of both studies show evidence of climate change in the Moyamba district. A substantial number of farmers and AEWs perceived a decrease in the annual rainfall amount, length of the rainy season, a late start and end of the rainy season, an increase in the temperature during the day and night, and a shortened harmattan period over the last 30 years. Analysis of the meteorological data shows evidence of variability in the seasonal and annual distribution of rainfall and temperature, a decreasing and non-significant trend in the rainy season and annual rainfall, and an increasing and significant trend in seasonal and annual temperature from 1991 to 2020. However, the observed changes in rainfall and temperature by the farmers and AEWs partially agree with the results of the analyzed meteorological data. The majority of the farmers perceived that; adverse weather conditions have negatively affected crop production in the district. Droughts, high temperatures, and irregular rainfall are the three major adverse weather events that farmers perceived to have contributed to a substantial loss in the yields of the major crops cultivated in the district. In response to the negative effects of adverse weather events, a substantial number of farmers take no action due to their lack of knowledge and technical or financial capacity to implement climate-sensitive agricultural (CSA) practices. Even though few farmers are practising some CSA practices in their farms, there is an urgent need to build the capacity of farmers and AEWs to adapt to and mitigate the negative impacts of climate change. The most priority support needed by farmers is the provision of climate-resilient crop varieties, whilst the AEWs need training on CSA practices.

Keywords: climate change, crop productivity, farmer’s perception, rainfall, temperature, Sierra Leone

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Authors: M. R. Dahmardeh Ghaleno, M. Nohtani, S. Khaledi

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Flood simulation and prediction is one of the most active research areas in surface water management. WetSpa is a distributed, continuous, and physical model with daily or hourly time step that explains precipitation, runoff, and evapotranspiration processes for both simple and complex contexts. This model uses a modified rational method for runoff calculation. In this model, runoff is routed along the flow path using Diffusion-Wave equation which depends on the slope, velocity, and flow route characteristics. Golestan Dam Basin is located in Golestan province in Iran and it is passing over coordinates 55° 16´ 50" to 56° 4´ 25" E and 37° 19´ 39" to 37° 49´ 28"N. The area of the catchment is about 224 km², and elevations in the catchment range from 414 to 2856 m at the outlet, with average slope of 29.78%. Results of the simulations show a good agreement between calculated and measured hydrographs at the outlet of the basin. Drawing upon Nash-Sutcliffe model efficiency coefficient for calibration periodic model estimated daily hydrographs and maximum flow rate with an accuracy up to 59% and 80.18%, respectively.

Keywords: watershed simulation, WetSpa, stream flow, flood prediction

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Authors: Akram Khaleghei Ghosheh Balagh, Viliam Makis, Leila Jafari

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In this paper, we present a new maintenance model for a partially observable system subject to two failure modes, namely a catastrophic failure and a failure due to the system degradation. The system is subject to condition monitoring and the degradation process is described by a hidden Markov model. A cost-optimal Bayesian control policy is developed for maintaining the system. The control problem is formulated in the semi-Markov decision process framework. An effective computational algorithm is developed and illustrated by a numerical example.

Keywords: partially observable system, hidden Markov model, competing risks, multivariate Bayesian control

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Authors: Abhisek Chakrabarty, Subhraprakash Mandal

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Flash flood is one of the catastrophic natural hazards in the mountainous region of India. The recent flood in the Mandakini River in Kedarnath (14-17th June, 2013) is a classic example of flash floods that devastated Uttarakhand by killing thousands of people.The disaster was an integrated effect of high intensityrainfall, sudden breach of Chorabari Lake and very steep topography. Every year in Himalayan Region flash flood occur due to intense rainfall over a short period of time, cloud burst, glacial lake outburst and collapse of artificial check dam that cause high flow of river water. In Sikkim-Derjeeling Himalaya one of the probable flash flood occurrence zone is Teesta Watershed. The Teesta River is a right tributary of the Brahmaputra with draining mountain area of approximately 8600 Sq. km. It originates in the Pauhunri massif (7127 m). The total length of the mountain section of the river amounts to 182 km. The Teesta is characterized by a complex hydrological regime. The river is fed not only by precipitation, but also by melting glaciers and snow as well as groundwater. The present study describes an attempt to model surface runoff in upper Teesta basin, which is directly related to catastrophic flood events, by creating a system based on GIS technology. The main object was to construct a direct unit hydrograph for an excess rainfall by estimating the stream flow response at the outlet of a watershed. Specifically, the methodology was based on the creation of a spatial database in GIS environment and on data editing. Moreover, rainfall time-series data collected from Indian Meteorological Department and they were processed in order to calculate flow time and the runoff volume. Apart from the meteorological data, background data such as topography, drainage network, land cover and geological data were also collected. Clipping the watershed from the entire area and the streamline generation for Teesta watershed were done and cross-sectional profiles plotted across the river at various locations from Aster DEM data using the ERDAS IMAGINE 9.0 and Arc GIS 10.0 software. The analysis of different hydraulic model to detect flash flood probability ware done using HEC-RAS, Flow-2D, HEC-HMS Software, which were of great importance in order to achieve the final result. With an input rainfall intensity above 400 mm per day for three days the flood runoff simulation models shows outbursts of lakes and check dam individually or in combination with run-off causing severe damage to the downstream settlements. Model output shows that 313 Sq. km area were found to be most vulnerable to flash flood includes Melli, Jourthang, Chungthang, and Lachung and 655sq. km. as moderately vulnerable includes Rangpo,Yathang, Dambung,Bardang, Singtam, Teesta Bazarand Thangu Valley. The model was validated by inserting the rain fall data of a flood event took place in August 1968, and 78% of the actual area flooded reflected in the output of the model. Lastly preventive and curative measures were suggested to reduce the losses by probable flash flood event.

Keywords: flash flood, GIS, runoff, simulation model, Teesta river basin

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Authors: Elahe Memari, Ahmad Aslizadeh, Ahmad Memari

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Today strategic planning is counted as the most important duties of senior directors in each organization. Strategic planning allows the organizations to implement compiled strategies and reach higher competitive benefits than their competitors. The present research work tries to prepare and rank the strategies form effective factors on strategic planning in fulfillment of the State Road Management and Transportation Organization in order to indicate the role of organizational factors in efficiency of the process to organization managers. Connection between six main factors in fulfillment of State Road Management and Transportation Organization were studied here, including Improvement of Strategic Thinking in senior managers, improvement of the organization business process, rationalization of resources allocation in different parts of the organization, coordination and conformity of strategic plan with organization needs, adjustment of organization activities with environmental changes, reinforcement of organizational culture. All said factors approved by implemented tests and then ranked using fuzzy multivariate decision-making technique.

Keywords: Fuzzy TOPSIS, improvement of organization business process, multivariate decision-making, strategic planning

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Authors: Salako Rotimi, Oshungade Stephen, Ojewoye Opeyemi

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The maintenance of price stability is one of the macroeconomic challenges facing Nigeria as a nation. This paper attempts to build a co-integration multivariate time series model for inflation movement in Nigeria using data extracted from the abstract of statistics of the Central Bank of Nigeria (CBN) from 2008 to 2017. The Johansen cointegration test suggests at least one co-integration vector describing the long run relationship between Consumer Price Index (CPI), Food Price Index (FPI) and Non-Food Price Index (NFPI). All three series show increasing pattern, which indicates a sign of non-stationary in each of the series. Furthermore, model predictability was established with root-mean-square-error, mean absolute error, mean average percentage error, and Theil’s unbiased statistics for n-step forecasting. The result depicts that the long run coefficient of a consumer price index (CPI) has a positive long-run relationship with the food price index (FPI) and non-food price index (NFPI).

Keywords: economic, inflation, model, series

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Authors: K. Mirudhula, R. Saravanan

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Bhavani basin is the fourth largest Sub Basin in the Cauvery basin. The entire command area of all three major canals that takes off from the Bhavani river falls within the Erode District i.e. Lower Bhavani Project (LBP), Kodiveri and Kalingarayan canals. The LBP canal is a major source of irrigation in Erode District. Many of these canals are unlined and leakage takes place from them. Thus the seepage from the canal helps in recharging the wells in the area, enabling to get adequate water supply for the crops when water was not released from Bhavanisagar Dam. In this study, the groundwater recharge is determined by groundwater flow modeling using Visual MODFLOW model. For this purpose, three major natural sources of groundwater recharge are taken into consideration such as rainfall infiltration, canal seepage and return flow of irrigation. The model was run and ZONEBUDGET gives an idea about the amount of recharge from lined/unlined canal to the field. Unlined canal helps to recharge the groundwater about 20% more than the lined canal. The analysis reveals that the annual rainfall also has rapidly changed in this region. In the LBP canal Head reach meets their requirement with available quantity of water from the canal system. Tail end reach does not receive the required quantity of water because of seepage loss and conveyance loss. Hence the lined canal can be provided for full length of the main canal. Branch canals and minor distributaries are suggested to maintain the canals with unlined canal system.

Keywords: lower Bhavani basin, erode, groundwater flow modeling, irrigation practice, lined canal system

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Authors: Y. Fekir, K. Mederbal, M. A. Hamadouche, D. Anteur

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The soil erosion by water has become one of the biggest problems of the environment in the world, threatening the majority of countries. There are several models to evaluate erosion. These models are still a simplified representation of reality. They permit the analysis of complex systems, measurements are complementary to allow an extrapolation in time and space and may combine different factors. The empirical model of soil loss proposed by Wischmeier and Smith (Universal Soil Loss Equation), is widely used in many countries. He considers that erosion is a multiplicative function of five factors: rainfall erosivity (the R factor) the soil erodibility factor (K), topography (LS), the erosion control practices (P) and vegetation cover and agricultural practices (C). In this work, we tried to develop a tool based on Web GIS functionality to evaluate soil losses caused by erosion taking into account five factors. This tool allows the user to integrate all the data needed for the evaluation (DEM, Land use, rainfall ...) in the form of digital layers to calculate the five factors taken into account in the USLE equation (R, K, C, P, LS). Accordingly, and after treatment of the integrated data set, a map of the soil losses will be achieved as a result. We tested the proposed tool on a watershed basin located in the weste of Algeria where a dataset was collected and prepared.

Keywords: USLE, erosion, web gis, Algeria

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Authors: Faisal G. Khamis, Ghaleb A. El-Refae

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Many researchers have studied socioeconomic, health, and security variables in the developed countries; however, very few studies used multivariate analysis in developing countries. The current study contributes to the scarce literature about the determinants of the variance in socioeconomic, health, and security factors. Questions raised were whether the independent variables (IVs) of governorate and year impact the socioeconomic, health, and security dependent variables (DVs) in Jordan, whether the marginal mean of each DV in each governorate and in each year is significant, which governorates are similar in difference means of each DV, and whether these DVs vary. The main objectives were to determine the source of variances in DVs, collectively and separately, testing which governorates are similar and which diverge for each DV. The research design was time series and cross-sectional analysis. The main hypotheses are that IVs affect DVs collectively and separately. Multivariate and univariate analyses of variance were carried out to test these hypotheses. The population of 12 governorates in Jordan and the available data of 15 years (2000–2015) accrued from several Jordanian statistical yearbooks. We investigated the effect of two factors of governorate and year on the four DVs of divorce rate, mortality rate, unemployment percentage, and crime rate. All DVs were transformed to multivariate normal distribution. We calculated descriptive statistics for each DV. Based on the multivariate analysis of variance, we found a significant effect in IVs on DVs with p < .001. Based on the univariate analysis, we found a significant effect of IVs on each DV with p < .001, except the effect of the year factor on unemployment was not significant with p = .642. The grand and marginal means of each DV in each governorate and each year were significant based on a 95% confidence interval. Most governorates are not similar in DVs with p < .001. We concluded that the two factors produce significant effects on DVs, collectively and separately. Based on these findings, the government can distribute its financial and physical resources to governorates more efficiently. By identifying the sources of variance that contribute to the variation in DVs, insights can help inform focused variation prevention efforts.

Keywords: ANOVA, crime, divorce, governorate, hypothesis test, Jordan, MANOVA, means, mortality, unemployment, year

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Authors: Chandranath Chatterjee, Amina Khatun, Bhabagrahi Sahoo

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With the changing climate, precipitation events are intensified in the tropical river basins. Since these river basins are significantly influenced by the monsoonal rainfall pattern, critical impacts are observed on the agricultural practices in the downstream river reaches. This study analyses the crop damage and associated flood risk in terms of net benefit in the paddy-dominated tropical Indian delta of the Mahanadi River. The Mahanadi River basin lies in eastern part of the Indian sub-continent and is greatly affected by the southwest monsoon rainfall extending from the month of June to September. This river delta is highly flood-prone and has suffered from recurring high floods, especially after the 2000s. In this study, the lumped conceptual model, Nedbør Afstrømnings Model (NAM) from the suite of MIKE models, is used for rainfall-runoff modeling. The NAM model is laterally integrated with the MIKE11-Hydrodynamic (HD) model to route the runoffs up to the head of the delta region. To obtain the precipitation-derived future projected discharges at the head of the delta, nine Global Climate Models (GCMs), namely, BCC-CSM1.1(m), GFDL-CM3, GFDL-ESM2G, HadGEM2-AO, IPSL-CM5A-LR, IPSL-CM5A-MR, MIROC5, MIROC-ESM-CHEM and NorESM1-M, available in the Coupled Model Intercomparison Project-Phase 5 (CMIP5) archive are considered. These nine GCMs are previously found to best-capture the Indian Summer Monsoon rainfall. Based on the performance of the nine GCMs in reproducing the historical discharge pattern, three GCMs (HadGEM2-AO, IPSL-CM5A-MR and MIROC-ESM-CHEM) are selected. A higher Taylor Skill Score is considered as the GCM selection criteria. Thereafter, the 10-year return period design flood is estimated using L-moments based flood frequency analysis for the historical and three future projected periods (2010-2039, 2040-2069 and 2070-2099) under Representative Concentration Pathways (RCP) 4.5 and 8.5. A non-dimensional hydrograph analysis is performed to obtain the hydrographs for the historical/projected 10-year return period design floods. These hydrographs are forced into the calibrated and validated coupled 1D-2D hydrodynamic model, MIKE FLOOD, to simulate the flood inundation in the delta region. Historical and projected flood risk is defined based on the information about the flood inundation simulated by the MIKE FLOOD model and the inundation depth-damage-duration relationship of a normal rice variety cultivated in the river delta. In general, flood risk is expected to increase in all the future projected time periods as compared to the historical episode. Further, in comparison to the 2010s (2010-2039), an increased flood risk in the 2040s (2040-2069) is shown by all the three selected GCMs. However, the flood risk then declines in the 2070s as we move towards the end of the century (2070-2099). The methodology adopted herein for flood risk assessment is one of its kind and may be implemented in any world-river basin. The results obtained from this study can help in future flood preparedness by implementing suitable flood adaptation strategies.

Keywords: flood frequency analysis, flood risk, global climate models (GCMs), paddy cultivation

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Authors: Noratiqah Mohd Ariff, Abdul Aziz Jemain, Mohd Aftar Abu Bakar

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The construction of Intensity-Duration-Frequency (IDF) curves is one of the most common and useful tools in order to design hydraulic structures and to provide a mathematical relationship between rainfall characteristics. IDF curves, especially those in Peninsular Malaysia, are often built using moving windows of rainfalls. However, these windows do not represent the actual rainfall events since the duration of rainfalls is usually prefixed. Hence, instead of using moving windows, this study aims to find regionalized distributions for IDF curves of extreme rainfalls based on storm events. Homogeneity test is performed on annual maximum of storm intensities to identify homogeneous regions of storms in Peninsular Malaysia. The L-moment method is then used to regionalized Generalized Extreme Value (GEV) distribution of these annual maximums and subsequently. IDF curves are constructed using the regional distributions. The differences between the IDF curves obtained and IDF curves found using at-site GEV distributions are observed through the computation of the coefficient of variation of root mean square error, mean percentage difference and the coefficient of determination. The small differences implied that the construction of IDF curves could be simplified by finding a general probability distribution of each region. This will also help in constructing IDF curves for sites with no rainfall station.

Keywords: IDF curves, L-moments, regionalization, storm events

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Authors: Hadi Allafta, Christian Opp

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Soil erosion is a major concern in the Shatt Al-Arab basin owing to the steepness of its topography as well as the remarkable altitudinal deference between the upstream and downstream parts of the basin. Such conditions resulted in soil vulnerability to erosion; huge amounts of soil are annually transported, creating enormous implications such as land degradation, structure damage, biodiversity loss, productivity decline, etc. Thus, evaluation of soil erosion risk and its spatial distribution is crucial to build adatabase for efficient control measures. The present study used revised universal soil loss equation (RUSLE) model integrated with Geographic Information System (GIS) for depicting soil erosion hazard zones in the Shatt Al-Arab basin. The RUSLE model incorporated several parameters such as rainfall-runoff erosivity, soil erodibility, slope length and steepness, land cover and management, and conservation support practice for soil erosion zonation. High to medium soil loss of 100 to 20 ton perhectare per year represents around 25% of the basin area, while the areas of low soil loss of less than 20 ton per hectare per year occupied the rest of the total area. The high soil loss rates are linked to areas of high rainfall levels, loamy soil domination, elevated terrains/plateau margins with steep side slope, and high cultivation activities. The findings of the current study can be useful for managers and policy makers in the implementation of a suitable conservation program to reduce soil erosion or to recommend soil conservation acts if development projects are to be continued at regions of high soil erosion risk.

Keywords: geographic information system, revised universal soil loss equation, shatt Al-Arab basin, soil erosion

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Authors: Jose Flores, Nadia Gamboa

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A proper water quality management requires the establishment of a monitoring network. Therefore, evaluation of the efficiency of water quality monitoring networks is needed to ensure high-quality data collection of critical quality chemical parameters. Unfortunately, in some Latin American countries water quality monitoring programs are not sustainable in terms of recording historical data or environmentally representative sites wasting time, money and valuable information. In this study, multivariate statistical techniques, such as principal components analysis (PCA) and hierarchical cluster analysis (HCA), are applied for identifying the most significant monitoring sites as well as critical water quality parameters in the monitoring network of the Jequetepeque River basin, in northern Peru. The Jequetepeque River basin, like others in Peru, shows socio-environmental conflicts due to economical activities developed in this area. Water pollution by trace elements in the upper part of the basin is mainly related with mining activity, and agricultural land lost due to salinization is caused by the extensive use of groundwater in the lower part of the basin. Since the 1980s, the water quality in the basin has been non-continuously assessed by public and private organizations, and recently the National Water Authority had established permanent water quality networks in 45 basins in Peru. Despite many countries use multivariate statistical techniques for assessing water quality monitoring networks, those instruments have never been applied for that purpose in Peru. For this reason, the main contribution of this study is to demonstrate that application of the multivariate statistical techniques could serve as an instrument that allows the optimization of monitoring networks using least number of monitoring sites as well as the most significant water quality parameters, which would reduce costs concerns and improve the water quality management in Peru. Main socio-economical activities developed and the principal stakeholders related to the water management in the basin are also identified. Finally, water quality management programs will also be discussed in terms of their efficiency and sustainability.

Keywords: PCA, HCA, Jequetepeque, multivariate statistical

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Authors: Resham Lal Phuldel

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This study based on a bilateral development cooperation project funded by the governments of Nepal and Finland. The first phase of the project has been completed in August 2012 and the phase II started in September 2013 and will end September 2018. The project strengthens the capacity of local governments in 14 districts to deliver services in water supply, sanitation and hygiene in Western development region and in Mid-Western development region of Nepal. In recent days, several spring sources have been dried out or slowly decreasing its yield across the country due to changing character of rainfall, increasing evaporative losses and some other manmade causes such as land use change, infrastructure development work etc. To sustain the hilly communities, the sources have to be able to provide sufficient water to serve the population, either on its own or in conjunction with other sources. Phase III have measured all water sources in Tanahu district in 2004 and sources were located with the GPS. Phase II has repeated the exercise to see changes in the district. 3320 water sources as identified in 2004 and altogether 4223 including new water sources were identified and measured in 2014. Between 2004 and 2014, 50% flow rate (yield) deduction of point sources’ average yield in 10 years is found. Similarly, 21.6% and 34% deductions of average yield were found in spring and stream water sources respectively. The rainfall from 2002 to 2013 shows erratic rainfalls in the district. The monsoon peak month is not consistent and the trend shows the decrease of annual rainfall 16.7 mm/year. Further, the temperature trend between 2002 and 2013 shows warming of + 0.0410C/year.

Keywords: climate change, rainfall, source discharge, water sources

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Authors: Achut Manandhar, Kenneth D. Morton, Peter A. Torrione, Leslie M. Collins

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The current trends in affect recognition research are to consider continuous observations from spontaneous natural interactions in people using multiple feature modalities, and to represent affect in terms of continuous dimensions, incorporate spatio-temporal correlation among affect dimensions, and provide fast affect predictions. These research efforts have been propelled by a growing effort to develop affect recognition system that can be implemented to enable seamless real-time human-computer interaction in a wide variety of applications. Motivated by these desired attributes of an affect recognition system, in this work a multi-dimensional affect prediction approach is proposed by integrating multivariate Relevance Vector Machine (MVRVM) with a recently developed Output-associative Relevance Vector Machine (OARVM) approach. The resulting approach can provide fast continuous affect predictions by jointly modeling the multiple affect dimensions and their correlations. Experiments on the RECOLA database show that the proposed approach performs competitively with the OARVM while providing faster predictions during testing.

Keywords: dimensional affect prediction, output-associative RVM, multivariate regression, fast testing

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Authors: Souad Romdhane, Lotfi Belkacem

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When referring to actuarial analysis of lifetime, only models accounting for observable risk factors have been developed. Within this context, Cox proportional hazards model (CPH model) is commonly used to assess the effects of observable covariates as gender, age, smoking habits, on the hazard rates. These covariates may fail to fully account for the true lifetime interval. This may be due to the existence of another random variable (frailty) that is still being ignored. The aim of this paper is to examine the shared frailty issue in the Cox proportional hazard model by including two different parametric forms of frailty into the hazard function. Four estimated methods are used to fit them. The performance of the parameter estimates is assessed and compared between the classical Cox model and these frailty models through a real-life data set from the Quebec Pension Plan and then using a more general simulation study. This performance is investigated in terms of the bias of point estimates and their empirical standard errors in both fixed and random effect parts. Both the simulation and the real dataset studies showed differences between classical Cox model and shared frailty model.

Keywords: life insurance-pension plan, survival analysis, risk factors, cox proportional hazards model, multivariate failure-time data, shared frailty, simulations study

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Authors: Gashaw Gismu Chakilu

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Climate and land cover change are very important issues in terms of global context and their responses to environmental and socio-economic drivers. The dynamic of these two factors is currently affecting the environment in unbalanced way including watershed hydrology. In this paper individual and combined impacts of climate change and land use land cover change on hydrological processes were evaluated through applying the model Soil and Water Assessment Tool (SWAT) in Gumara watershed, Upper Blue Nile basin Ethiopia. The regional climate; temperature and rainfall data of the past 40 years in the study area were prepared and changes were detected by using trend analysis applying Mann-Kendall trend test. The land use land cover data were obtained from land sat image and processed by ERDAS IMAGIN 2010 software. Three land use land cover data; 1973, 1986, and 2013 were prepared and these data were used for base line, model calibration and change study respectively. The effects of these changes on high flow and low flow of the catchment have also been evaluated separately. The high flow of the catchment for these two decades was analyzed by using Annual Maximum (AM) model and the low flow was evaluated by seven day sustained low flow model. Both temperature and rainfall showed increasing trend; and then the extent of changes were evaluated in terms of monthly bases by using two decadal time periods; 1973-1982 was taken as baseline and 2004-2013 was used as change study. The efficiency of the model was determined by Nash-Sutcliffe (NS) and Relative Volume error (RVe) and their values were 0.65 and 0.032 for calibration and 0.62 and 0.0051 for validation respectively. The impact of climate change was higher than that of land use land cover change on stream flow of the catchment; the flow has been increasing by 16.86% and 7.25% due to climate and LULC change respectively, and the combined change effect accounted 22.13% flow increment. The overall results of the study indicated that Climate change is more responsible for high flow than low flow; and reversely the land use land cover change showed more significant effect on low flow than high flow of the catchment. From the result we conclude that the hydrology of the catchment has been altered because of changes of climate and land cover of the study area.

Keywords: climate, LULC, SWAT, Ethiopia

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Authors: Shotiros Protong

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In recent years, Thailand has been affected by climate change phenomenon, which is clearly seen from the season change for different times. The occurrence of violent storms, heavy rains, floods, and drought were found in several areas. In a long dry period, the water supply is not adequate in drought areas. Nowadays, it is renowned that there is a significant decrease of rainwater use for household consumption in rural area of Thailand. Rainwater harvesting is the practice of collection and storage of rainwater in storage tanks before it is lost as surface run-off. Rooftop rainwater harvesting is used to provide drinking water, domestic water, and water for livestock. Rainwater harvesting in households is an alternative for people to readily prepare water resources for their own consumptions during the drought season, can help mitigate flooding of flooded plains, and also may reduce demand on the basin and well. It also helps in the availability of potable water, as rainwater is substantially free of salts. Application of rainwater harvesting in rural water system provide a substantial benefit for both water supply and wastewater subsystems by reducing the need for clean water in water distribution systems, less generated storm water in sewer systems, and a reduction in storm water runoff polluting freshwater bodies. The combination of rainwater quality and rainfall quantity is used to determine proper rainwater harvesting for household consumption to be safe and adequate for survivals. Rainwater quality analysis is compared with the drinking water standard. In terms of rainfall quantity, the observed rainfall data are interpolated by GIS 10.5 and showed by map during 1980 to 2020, used to assess the annual yield for household consumptions.

Keywords: rainwater harvesting, drinking water standard, annual yield, rainfall quantity

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Authors: Rabih Ghostine, Craig Kapfer, Viswanathan Kannan, Ibrahim Hoteit

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Urban flooding resulting from a sudden release of water due to dam-break or excessive rainfall is a serious threatening environment hazard, which causes loss of human life and large economic losses. Anticipating floods before they occur could minimize human and economic losses through the implementation of appropriate protection, provision, and rescue plans. This work reports on the numerical modelling of flash flood propagation in urban areas after an excessive rainfall event or dam-break. A two-dimensional (2D) depth-averaged shallow water model is used with a refined unstructured grid of triangles for representing the urban area topography. The 2D shallow water equations are solved using a second-order well-balanced discontinuous Galerkin scheme. Theoretical test case and three flood events are described to demonstrate the potential benefits of the scheme: (i) wetting and drying in a parabolic basin (ii) flash flood over a physical model of the urbanized Toce River valley in Italy; (iii) wave propagation on the Reyran river valley in consequence of the Malpasset dam-break in 1959 (France); and (iv) dam-break flood in October 1982 at the town of Sumacarcel (Spain). The capability of the scheme is also verified against alternative models. Computational results compare well with recorded data and show that the scheme is at least as efficient as comparable second-order finite volume schemes, with notable efficiency speedup due to parallelization.

Keywords: dam-break, discontinuous Galerkin scheme, flood modeling, shallow water equations

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Authors: Prozorkevitch D., Mishurov A., Sokolov K., Karsakov L., Pestrikova L.

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The current body of knowledge about the marine environment and the dynamics of marine ecosystems includes a huge amount of heterogeneous data collected over decades. It generally includes a wide range of hydrological, biological and fishery data. Marine researchers collect these data and analyze how and why the ecosystem changes from past to present. Based on these historical records and linkages between the processes it is possible to predict future changes. Multivariate analysis of trends and their interconnection in the marine ecosystem may be used as an instrument for predicting further ecosystem evolution. A wide range of information about the components of the marine ecosystem for more than 50 years needs to be used to investigate how these arrays can help to predict the future.

Keywords: barents sea ecosystem, abiotic, biotic, data sets, trends, prediction

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Authors: Azadeh Golshan, Craig Evans, Phillip Geary, Abigail Morrow, Zoe Rogers, Marcel Maeder

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22 physicochemical variables have been determined in water samples collected weekly from January to December in 2013 from three sampling stations located within a major drinking water reservoir. Classical Multivariate Curve Resolution Alternating Least Squares (MCR-ALS) analysis was used to investigate the environmental factors associated with the physico-chemical variability of the water samples at each of the sampling stations. Matrix augmentation MCR-ALS (MA-MCR-ALS) was also applied, and the two sets of results were compared for interpretative clarity. Links between these factors, reservoir inflows and catchment land-uses were investigated and interpreted in relation to chemical composition of the water and their resolved geographical distribution profiles. The results suggested that the major factors affecting reservoir water quality were those associated with agricultural runoff, with evidence of influence on algal photosynthesis within the water column. Water quality variability within the reservoir was also found to be strongly linked to physical parameters such as water temperature and the occurrence of thermal stratification. The two methods applied (MCR-ALS and MA-MCR-ALS) led to similar conclusions; however, MA-MCR-ALS appeared to provide results more amenable to interpretation of temporal and geological variation than those obtained through classical MCR-ALS.

Keywords: drinking water reservoir, multivariate analysis, physico-chemical parameters, water quality

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Authors: Nida Rizvi, Deeksha Katyal, Varun Joshi

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River Hindon is an important river catering the demand of highly populated rural and industrial cluster of western Uttar Pradesh, India. Water quality of river Hindon is deteriorating at an alarming rate due to various industrial, municipal and agricultural activities. The present study aimed at identifying the pollution sources and quantifying the degree to which these sources are responsible for the deteriorating water quality of the river. Various water quality parameters, like pH, temperature, electrical conductivity, total dissolved solids, total hardness, calcium, chloride, nitrate, sulphate, biological oxygen demand, chemical oxygen demand and total alkalinity were assessed. Water quality data obtained from eight study sites for one year has been subjected to the two multivariate techniques, namely, principal component analysis and cluster analysis. Principal component analysis was applied with the aim to find out spatial variability and to identify the sources responsible for the water quality of the river. Three Varifactors were obtained after varimax rotation of initial principal components using principal component analysis. Cluster analysis was carried out to classify sampling stations of certain similarity, which grouped eight different sites into two clusters. The study reveals that the anthropogenic influence (municipal, industrial, waste water and agricultural runoff) was the major source of river water pollution. Thus, this study illustrates the utility of multivariate statistical techniques for analysis and elucidation of multifaceted data sets, recognition of pollution sources/factors and understanding temporal/spatial variations in water quality for effective river water quality management.

Keywords: cluster analysis, multivariate statistical techniques, river Hindon, water quality

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Authors: Rajendra Kumar Isaac, Monisha Isaac

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Climate variability and changes are the emerging challenges for Indian agriculture with the growing population to ensure national food security. A study was conducted to assess the Climatic Change effects in medium to low altitude areas of the Himalayan region causing changes in land use and cereal crop productivity with the various climatic parameters. The rainfall and temperature changes from 1951 to 2013 were studied at four locations of varying altitudes, namely Hardwar, Rudra Prayag, Uttar Kashi and Tehri Garwal. It was observed that there is noticeable increment in temperature on all the four locations. It was surprisingly observed that the mean rainfall intensity of 30 minutes duration has increased at the rate of 0.1 mm/hours since 2000. The study shows that the combined effect of increasing temperature, rainfall, runoff and urbanization at the mid-Himalayan region is causing an increase in various climatic disasters and changes in agriculture patterns. A noticeable change in cropping patterns, crop productivity and land use change was observed. Appropriate adaptation and mitigation strategies are necessary to ensure that sustainable and climate-resilient agriculture. Appropriate information is necessary for farmers, as well as planners and decision makers for developing, disseminating and adopting climate-smart technologies.

Keywords: climate variability, agriculture, land use, mitigation strategies

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Authors: Emmanuel Yussuf, John Muthama, John Ng'ang'A

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There has been increasing noise levels all over the world in the last decade. Many factors contribute to this increase, which is causing health related effects to humans. Developing countries are not left out of the whole picture as they are still growing and advancing their development. Motor vehicles are increasing on urban roads; there is an increase in infrastructure due to the rising population, increasing number of industries to provide goods and so many other activities. All this activities lead to the high noise levels in cities. This study was conducted in Nairobi’s Central Business District (CBD) with the main objective of simulating noise levels in order to understand the noise exposed to the people within the urban area, in relation to weather parameters namely temperature, rainfall and wind field. The study was achieved using the Neighbourhood Proximity Model and Time Series Analysis, with data obtained from proxies/remotely-sensed from satellites, in order to establish the levels of noise exposed to which people of Nairobi CBD are exposed to. The findings showed that there is an increase in temperature (0.1°C per year) and a decrease in precipitation (40 mm per year), which in comparison to the noise levels in the area, are increasing. The study also found out that noise levels exposed to people in Nairobi CBD were roughly between 61 and 63 decibels and has been increasing, a level which is high and likely to cause adverse physical and psychological effects on the human body in which air temperature, precipitation and wind contribute so much in the spread of noise. As a noise reduction measure, the use of sound proof materials in buildings close to busy roads, implementation of strict laws to most emitting sources as well as further research on the study was recommended. The data used for this study ranged from the year 2000 to 2015, rainfall being in millimeters (mm), temperature in degrees Celsius (°C) and the urban form characteristics being in meters (m).

Keywords: simulation, noise exposure, weather, proxy

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Authors: Bry X., Trottier C., Mortier F., Cornu G., Verron T.

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We address component-based regularization of a Multivariate Generalized Linear Model (MGLM). A set of random responses Y is assumed to depend, through a GLM, on a set X of explanatory variables, as well as on a set T of additional covariates. X is partitioned into R conceptually homogeneous blocks X1, ... , XR , viewed as explanatory themes. Variables in each Xr are assumed many and redundant. Thus, Generalised Linear Regression (GLR) demands regularization with respect to each Xr. By contrast, variables in T are assumed selected so as to demand no regularization. Regularization is performed searching each Xr for an appropriate number of orthogonal components that both contribute to model Y and capture relevant structural information in Xr. We propose a very general criterion to measure structural relevance (SR) of a component in a block, and show how to take SR into account within a Fisher-scoring-type algorithm in order to estimate the model. We show how to deal with mixed-type explanatory variables. The method, named THEME-SCGLR, is tested on simulated data.

Keywords: Component-Model, Fisher Scoring Algorithm, GLM, PLS Regression, SCGLR, SEER, THEME

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Authors: Ahmad Shayeq Azizi, Yuji Toda

Abstract:

In Afghanistan, floods are the most frequent and recurrent events among other natural disasters. On the other hand, lack of monitoring data is a severe problem, which increases the difficulty of making the appropriate flood countermeasures of flood forecasting. This study is carried out to simulate the flood inundation in Harirud River Basin by application of distributed hydrological model, Integrated Flood Analysis System (IFAS) and 2D hydrodynamic model, International River Interface Cooperative (iRIC) based on satellite rainfall combined with historical peak discharge and global accessed data. The results of the simulation can predict the inundation area, depth and velocity, and the hardware countermeasures such as the impact of levee installation can be discussed by using the present method. The methodology proposed in this study is suitable for the area where hydrological and geographical data including river survey data are poorly observed.

Keywords: distributed hydrological model, flood inundation, hydrodynamic model, ungauged basins

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Authors: Abhishek Saha, Serene Tay, Gerard Pijcke

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The availability of high-resolution topography and rainfall information in urban areas has made it necessary to revise modeling approaches used for simulating flood risk assessments. Lidar derived elevation models that have 1m or lower resolutions are becoming widely accessible. The classical approaches of 1D-2D flow models where channel flow is simulated and coupled with a coarse resolution 2D overland flow models may not fully utilize the information provided by high-resolution data. In this context, a study was undertaken to compare three different modeling approaches to simulate flooding in an urban area. The first model used is the base model used is Sobek, which uses 1D model formulation together with hydrologic boundary conditions and couples with an overland flow model in 2D. The second model uses a full 2D model for the entire area with shallow water equations at the resolution of the digital elevation model (DEM). These models are compared against another shallow water equation solver in 2D, which uses a subgrid method for grid refinement. These models are simulated for different horizontal resolutions of DEM varying between 1m to 5m. The results show a significant difference in inundation extents and water levels for different DEMs. They are also sensitive to the different numerical models with the same physical parameters, such as friction. The study shows the importance of having reliable field observations of inundation extents and levels before a choice of model and data can be made for spatial flood risk assessments.

Keywords: flooding, DEM, shallow water equations, subgrid

Procedia PDF Downloads 141

Authors: Ayten Ekin Meşe, Selahattin Şentürk, Melike Duvanoğlu

Abstract:

Petroleum refineries are a highly complex process industry with continuous production and high operating costs. Physical separation of crude oil starts with the crude oil distillation unit, continues with various conversion and purification units, and passes through many stages until obtaining the final product. To meet the desired product specification, process parameters are strictly followed. To be able to ensure the quality of distillates, routine analyses are performed in quality control laboratories based on appropriate international standards such as American Society for Testing and Materials (ASTM) standard methods and European Standard (EN) methods. The cut point of distillates in the crude distillation unit is very crucial for the efficiency of the upcoming processes. In order to maximize the process efficiency, the determination of the quality of distillates should be as fast as possible, reliable, and cost-effective. In this sense, an alternative study was carried out on the crude oil distillation unit that serves the entire refinery process. In this work, studies were conducted with three different crude oil distillates which are Light Straight Run Naphtha (LSRN), Heavy Straight Run Naphtha (HSRN), and Kerosene. These products are named after separation by the number of carbons it contains. LSRN consists of five to six carbon-containing hydrocarbons, HSRN consist of six to ten, and kerosene consists of sixteen to twenty-two carbon-containing hydrocarbons. Physical properties of three different crude distillation unit products (LSRN, HSRN, and Kerosene) were determined using Near-Infrared Spectroscopy with multivariate calibration. The absorbance spectra of the petroleum samples were obtained in the range from 10000 cm⁻¹ to 4000 cm⁻¹, employing a quartz transmittance flow through cell with a 2 mm light path and a resolution of 2 cm⁻¹. A total of 400 samples were collected for each petroleum sample for almost four years. Several different crude oil grades were processed during sample collection times. Extended Multiplicative Signal Correction (EMSC) and Savitzky-Golay (SG) preprocessing techniques were applied to FT-NIR spectra of samples to eliminate baseline shifts and suppress unwanted variation. Two different multivariate calibration approaches (Partial Least Squares Regression, PLS and Genetic Inverse Least Squares, GILS) and an ensemble model were applied to preprocessed FT-NIR spectra. Predictive performance of each multivariate calibration technique and preprocessing techniques were compared, and the best models were chosen according to the reproducibility of ASTM reference methods. This work demonstrates the developed models can be used for routine analysis instead of conventional analytical methods with over 90% accuracy.

Keywords: crude distillation unit, multivariate calibration, near infrared spectroscopy, data preprocessing, refinery

Procedia PDF Downloads 129