Search results for: March-May 2013 rainfall season

Authors: Ajit Kumar Behera, Saranya P., Sudhir Kumar, Krishnakumar A

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The stable isotope (δ¹⁸ O and δ²H) composition of groundwater of the coastal areas of Periyar and Mahanadi basins falling along East and West coast of India during North-East (NE) monsoon season have been studied. The east and west coast regions are surrounded by the Bay of Bengal and the Arabian Sea respectively, which are considered to be the primary sources for precipitation over India. The major difference between the Bay of Bengal and the Arabian Sea is that a number of large rivers feed the Bay of Bengal, whereas the Arabian Sea is fed by very few small rivers, resulting in enriched stable isotopic composition of the Arabian Sea than the Bay of Bengal. Previous studies have reported depleted ratios of stable isotopes during Northeast monsoon along East and West coasts due to the influence of the Bay of Bengal moisture source. The isotopic composition of groundwater of the Mahanadi delta in the east coast region varies from -6.87 ‰ to -3.40 ‰ for δ¹⁸ O and -45.42 ‰ to -22.43‰ for δ²H. However, the groundwater of the Periyar basin in the west coast has enriched stable isotope value varying from -4.3‰ to -2.5 ‰ for δ¹⁸ O and for δ²H from -23.7 to -6.4 ‰ which is a characteristic of South-West monsoon season. This suggests the groundwater system of the Mahanadi delta and the Periyar basins are influenced by dissimilar moisture sources. The δ¹⁸ O and δ² H relationship (δ²H= 6.513 δ¹⁸ O - 1.39) and d-excess value (< 10) in the east coast region indicates the influence of NE monsoon implying the quick groundwater recharge after precipitation with significant amount of evaporation. In contrast, the δ¹⁸ O and δ²H regression line (δ²H= 8.408 δ¹⁸ O + 11.71) with high d-excess value (>10) in the west coast region implies delayed recharge due to SW monsoon. The observed isotopic enrichment in west coast suggests that NE winter monsoon rainfall does not replenish groundwater quick enough to produce isotopic depletion during the season.

Keywords: Arabian sea, bay of Bengal, groundwater, monsoon, stable isotope

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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

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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: 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: Apu Kumar Saha, Mrinmoy Majumder

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The increase in the concentration of Green House gases all over the World has induced global warming phenomena whereby the average temperature of the world has aggravated to impact the pattern of climate in different regions. The frequency of extreme event has increased, early onset of season and change in an average amount of rainfall all are engrossing the conclusion that normal pattern of climate is changing. Sophisticated and complex models are prepared to estimate the future situation of the climate in different zones of the Earth. As hydro-energy is directly related to climatic parameters like rainfall and evaporation such energy resources will have to sustain the onset of the climatic abnormalities. The present investigation has tried to assess the impact of climatic abnormalities upon hydropower potential of different regions of the World. In this regard multi-criteria, decision making, and the neural network is used to predict the impact of the change cognitively by an index. The results from the study show that hydro-energy potential of Asian region is mostly vulnerable with respect to other regions of the world. The model results also encourage further application of the index to analyze the impact of climate change on the potential of hydro-energy.

Keywords: hydro-energy potential, neural networks, multi criteria decision analysis, environmental and ecological engineering

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Authors: Teguh Nurhidayat, Nurhamid, Dicky Muslim, Zufialdi Zakaria, Irvan Sophian

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This paper presents the role of climate change as the factor that induces landslide. Case study is located at Lahat Regency, South Sumatera Province, Indonesia. Study area has high economic value of coal reserves (mostly subbituminous – bituminous), which is developable for open pit coal mining in the future. Seams are found in Muara Enim Formation. This formation is at south Sumatera basin which is formed at Tertiary as a result of collision between the indian plate and eurasian plate. South Sumatera basin which is a basin located in back arc basin. This study aims to unravel the relationship between slope stability with different season condition in tropical climate. Undisturbed soil samples were obtained in the field along with other geological data. Laboratory works were carried out to obtain physical and mechanical properties of soils. Methodology to analyze slope stability is bishop method. Bishop methods are used to identify safety factor of slope. Result shows that slopes in rainy season conditions are more prone to landslides than in dry season. In the dry seasons with moisture content is 22.65%, safety factor is 1.28 the slope in stable condition. If rain is approaching with moisture content increasing to 97.8%, the slope began to be critical. On wet condition groundwater levels is increased, followed by γ (unit weight), c (cohesion), and φ (angle of friction) at 18.04, 5,88 kN/m2, and 28,04°, respectively, which ultimately determines the security factor FS to be 1.01 (slope in unstable conditions).

Keywords: rainfall, moisture content, slope analysis, landslide prone

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Authors: Nwanneka Mmonwuba

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Solid waste disposal to the environment was investigated by analyzing the quality characteristics of waste, air quality, and heavy metal concentration in the soil. The characteristics of waste were analyzed by enumerating the number of houses, hostels, hotels, markets, schools, and industries with the type of waste being discharged or deposited into the dump site. The percentage of waste was estimated with organic ranking first for both wet and dry seasons, 54% and 44%, respectively. The ambient air quality was analyzed using the crown gas monitor analyzer. The analysis showed that the mean concentration of NO₂, SO₂, and Co is 0.74, 0.37, and 47.35 ppm for the wet season and 0.47, 0.35, and 37.65 ppm for the dry season, respectively, and do not conform with the USEPA standard. The chemical analysis of the groundwater sample indicates alkalinity ranging from 7.38 to 9.11. the heavy metals concentration in the soil of cadmium, iron, copper, calcium, and potassium with 0.053, 0.722, 0227, 21.3, and 9.019, respectively, obtained from 0.3 m at the subsurface failed to conform to the NRC (2013) standard. Iron consent in the soil can be corrected using ascorbic acid and soda ash. The permanent reduction of effects is to try relocating people who live very close to the dumpsite, or the dumpsite should be sited elsewhere and replaced with a sanitary landfill.

Keywords: solid waste, groundwater, disposal, dumpsite

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Authors: Eman. K. Ramadan, Abdelgawad. S. El-Tahawy

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The objective of this study was to evaluate the effects of calving season on the production and economic efficiency of dairy farms in Egypt. Our study was performed at dairy production farms in the Alexandria, Behera, and Kafr El-Sheikh provinces of Egypt from summer 2010 to winter 2013. The randomly selected dairy farms had herds consisting of Baladi, Holstein-Friesian, or cross-bred (Baladi × Holstein-Friesian) cows. The data were collected from production records and responses to a structured questionnaire. The average total return differed significantly (P < 0.05) between the different cattle breeds and calving seasons. The average total return was highest for the Holstein-Friesian cows that calved in the winter (29106.42 EGP/cow/year), and it was lowest for Baladi cows that calved in the summer (12489.79 EGP/cow/year). Differences in total returns between the cows that calved in the winter or summer or between the foreign and native breeds, as well as variations in calf prices, might have contributed to the differences in milk yield. The average net profit per cow differed significantly (P < 0.05) between the cattle breeds and calving seasons. The average net profit values for the Baladi cows that calved in the winter or summer were 2413 and 2994.96 EGP/cow/year, respectively, and those for the Holstein-Friesian cows were 10744.17 and 7860.56 EGP/cow/year, respectively, whereas those for the cross-bred cows were 10174.86 and 7571.33 EGP/cow/year, respectively. The variations in net profit might have resulted from variation in the availability or price of feed materials, milk prices, or sales volumes. Our results show that the breed and calving season of dairy cows significantly affected the economic efficiency of dairy farms in Egypt. The cows that calved in the winter produced more milk than those that calved in the summer, which may have been the result of seasonal influences, such as temperature, humidity, management practices, and the type of feed or green fodder available.

Keywords: calving season, economic, production, efficiency, dairy

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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: Pius Borona, Cheikh Mbow, Issa Ouedraogo

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In the Sahel, climate variability has been associated with a complex web of direct and indirect impacts. This natural phenomenon has been an impediment to agro-pastoral communities who experience uncertainty while involving in farming activities which is also their key source of livelihood. In this scenario, the role of climate variability in influencing the performance, quantity and quality of staple cereals yields, vital for food and nutrition security has been a topic of importance. This response of crops and subsequent yield variability is also a subject of immense debate due to the complexity of crop development at different stages. This complexity is further compounded by influence of slowly changing non-climatic factors. With these challenges in mind, the present paper initially explores the occurrence of climate variability at an inter annual and inter decadal level in South Burkina Faso. This is evidenced by variation of the total annual rainfall and the number of rainy days among other climatic descriptors. Further, it is shown how district-scale cereal yields in the study area including maize, sorghum and millet casually associate variably to the inter-annual variation of selected climate variables. Statistical models show that the three cereals widely depict sensitivity to the length of the growing period and total dry days in the growing season. Maize yields on the other hand relate strongly to the rainfall amount variation (R2=51.8%) showing high moisture dependence during critical growth stages. Our conclusions emphasize on adoption of efficient water utilization platforms especially those that have evidently increased yields and strengthening of forecasts dissemination.

Keywords: climate variability, cereal yields, seasonality, rain fed farming, Burkina Faso, rainfall

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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: T. N. Girish, B. E. Pradeep, Ravi Parkash

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Insects from tropical wet or dry seasons are likely to cope starvation stress through seasonal phenotypic plasticity in energy metabolites. Accordingly, we analyzed such plastic changes in Zaprionus indianus flies reared under wet or dry season-specific conditions; and also after adult acclimation at 32℃ for 1 to 6 days; and to low (40% RH) or high (70% RH) humidity. Both thermal or humidity acclimation revealed significant accumulation of body lipids for wet season flies but low humidity acclimation did not change the level of body lipids in dry season flies. Developmental and adult acclimation showed sex specific differences i.e., starvation resistance and body lipids were higher in the males of dry season but in females of wet season. We found seasonal and sex specific differences in the relative level for body lipids at death; and in the rates of accumulation or utilization of energy metabolites (body lipids, carbohydrates and proteins). Body lipids constitute the preferred energy source under starvation for flies of both the seasons. However, utilization of carbohydrates (~20% to 30%) and proteins (~20% to 25%) was evident only in dry season flies. Higher starvation resistance after thermal or humidity acclimation is achieved by increased accumulation of lipids. Adult acclimation of wet or dry season flies revealed plastic changes in mean daily fecundity despite reduction in fecundity under starvation. Thus, thermal or humidity induced plastic responses in body lipids support starvation resistance under wet or dry seasons.

Keywords: heat or humidity acclimation, plastic changes in body lipids and starvation resistance, tropical drosophilid, Wet- or Dry seasons, Zaprionus indianus

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Authors: Ikenna Charles Onyema, Tolut Prince Bako

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A study was carried out in the Atlantic Ocean off the Lighthouse Beach, Lagos. There were monthly and spatial variations in physical and chemical characteristics of the neritic ocean (August - December, 2014). Mean and standard deviation values for air temperature were 27. 67, ± 2.98 °C, water temperature (28.37 ± 1.88), pH (7.85 ± 0.17), conductivity (44738.75 ± 6262.76 µS/cm), total dissolved solids (29236.71 ± 4273.30 mg/L), salinity (27.11 ± 3.91 ‰), alkalinity (126.99 ± 42.81 mg/L) and chloride (15056. 67 ± 2165.78 mg/L). Higher estimates were recorded in the dry than wet months for these characteristics. On the other hand, reducing values were recorded for acidity (2.34 ± 0.63 mg/L), total hardness (4711.98 ± 691.50 mg/L), phosphate (1.1 ± 0.78 mg/L), sulphate (2601.99 ± 447.04 mg/L) and nitrate (0.12 ± 0.06 mg/L). Values for total suspended solids and biological oxygen demand values were low (<1mg/L). Twenty-one species of phytoplankton were recorded. Diatoms recorded 80.92% and were the dominant group. Hemidiscus cuneiformis, Coscinodiscus centralis, Coscinodiscus lineatus, Coscinodiscus radiatus and Oscillatoria limosa were more frequently occurring species. Biddulphia sinensis and four species of Ceratium, were representatives of the dry season. The dry season also recorded comparatively higher individuals of phytoplankton than the wet season. Spirogyra sp. (green algae) appeared only in the wet season. Species abundance (N) was highest in December at Station 1 (13.15%) (dry season) and lowest in August (wet season) at Station 3 (2.96%). The physico-chemical factors and phytoplankton reflected a tropical unpolluted neritic oceanic environment.

Keywords: sea, physico-chemistry, lighthouse beach, microalgae

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Authors: Ikenna Charles Onyema, Prince Tolut Bako

Abstract:

A study was carried out in the Atlantic Ocean off the Lighthouse Beach, Lagos. There were monthly and spatial variations in physical and chemical characteristics of the neritic ocean (August-December, 2014). Mean and standard deviation values for air temperature were 27. 67, ± 2.98 oC, water temperature (28.37 ± 1.88), pH (7.85 ± 0.17), Conductivity (44738.75 ± 6262.76 µS/cm), Total dissolved solids (29236.71 ± 4273.30 mg/L), Salinity (27.11 ± 3.91 ‰), Alkalinity (126.99 ± 42.81 mg/L) and Chloride (15056. 67 ± 2165.78 mg/L). Higher estimates were recorded in the dry than wet months for these characteristics. On the other hand, reducing values were recorded for Acidity (2.34 ± 0.63 mg/L), Total hardness (4711.98 ± 691.50 mg/L), Phosphate (1.1 ± 0.78 mg/L), Sulphate (2601.99 ± 447.04 mg/L) and Nitrate (0.12 ± 0.06 mg/L). Values for Total suspended solids and Biological oxygen demand values were low ( < 1mg/L). Twenty-one species of phytoplankton were recorded. Diatoms recorded 80.92% and were the dominant group. Hemidiscus cuneiformis, Coscinodiscus centralis, Coscinodiscus lineatus, Coscinodiscus radiatus and Oscillatoria limosa were more frequently occurring species. Biddulphia sinensis and four species of Ceratium, were representatives of the dry season. The dry season also recorded comparatively higher individuals of phytoplankton than the wet season. Spirogyra sp. (green algae) appeared only in the wet season. Species abundance (N) was highest in December at Station 1 (13.15%) (dry season) and lowest in August (wet season) at Station 3 (2.96%). The physico-chemical factors and phytoplankton reflected a tropical unpolluted neritic oceanic environment.

Keywords: sea, physico-chemistry, micro-algae, lighthouse beach

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Authors: Susmita Ghosh

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Catchment area of Damodar River, India experiences seasonal rains due to the south-west monsoon every year and depending upon the intensity of the storms, floods occur. During the monsoon season, the rainfall in the area is mainly due to active monsoon conditions. The upstream reach of Damodar river system has five dams store the water for utilization for various purposes viz, irrigation, hydro-power generation, municipal supplies and last but not the least flood moderation. But, in the downstream reach of Damodar River, known as Lower Damodar region, is severely and frequently suffering from flood due to heavy monsoon rainfall and also release from upstream reservoirs. Therefore, an effective flood management study is required to know in depth the nature and extent of flood, water logging, and erosion related problems, affected area, and damages in the Lower Damodar region, by conducting mathematical model study. The design flood or discharge is needed to decide to assign the respective model for getting several scenarios from the simulation runs. The ultimate aim is to achieve a sustainable flood management scheme from the several alternatives. there are various methods for estimating flood discharges to be carried through the rivers and their tributaries for quick drainage from inundated areas due to drainage congestion and excess rainfall. In the present study, the flood frequency analysis is performed to decide the design flood discharge of the study area. This, on the other hand, has limitations in respect of availability of long peak flood data record for determining long type of probability density function correctly. If sufficient past records are available, the maximum flood on a river with a given frequency can safely be determined. The floods of different frequency for the Damodar has been calculated by five candidate distributions i.e., generalized extreme value, extreme value-I, Pearson type III, Log Pearson and normal. Annual peak discharge series are available at Durgapur barrage for the period of 1979 to 2013 (35 years). The available series are subjected to frequency analysis. The primary objective of the flood frequency analysis is to relate the magnitude of extreme events to their frequencies of occurrence through the use of probability distributions. The design flood for return periods of 10, 15 and 25 years return period at Durgapur barrage are estimated by flood frequency method. It is necessary to develop flood hydrographs for the above floods to facilitate the mathematical model studies to find the depth and extent of inundation etc. Null hypothesis that the distributions fit the data at 95% confidence is checked with goodness of fit test, i.e., Chi Square Test. It is revealed from the goodness of fit test that the all five distributions do show a good fit on the sample population and is therefore accepted. However, it is seen that there is considerable variation in the estimation of frequency flood. It is therefore considered prudent to average out the results of these five distributions for required frequencies. The inundated area from past data is well matched using this flood.

Keywords: design discharge, flood frequency, goodness of fit, sustainable flood management

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Authors: Balogun R. Ayodeji, Adefisan E. Adesanya, Adeyewa Z. Debo, E. C. Okogbue

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The need to investigate diurnal weather circles in West Africa is coined in the fact that complex interactions often results from diurnal weather patterns. This study investigates diurnal circles of wind, rainfall and convective properties using six (6) hour interval data from the ERA-Interim and the Tropical Rainfall Measurement Mission (TRMM). The seven distinct zones, used in this work and classified as rainforest (west-coast, dry, Nigeria-Cameroon), Savannah (Nigeria, and Central Africa and South Sudan (CASS)), Sudano-Sahel, and Sahel, were clearly indicated by the rainfall pattern in each zones. Results showed that the land‐ocean warming contrast was more strongly sensitive to seasonal cycle and has been very weak during March-May (MAM) but clearly spelt out during June-September (JJAS). Dipoles of wind convergence/divergence and wet/dry precipitation, between CASS and Nigeria Savannah zones, were identified in morning and evening hours of MAM, whereas distinct night and day anomaly, in the same location of CASS, were found to be consistent during the JJAS season. Diurnal variation of convective properties showed that stratiform precipitation, due to the extremely low occurrence of flashcount climatology, was dominant during morning hours for both MAM and JJAS than other periods of the day. On the other hand, diurnal variation of the system sizes showed that small system sizes were most dominant during the day time periods for both MAM and JJAS, whereas larger system sizes were frequent during the evening, night, and morning hours. The locations of flashcount and system sizes agreed with earlier results that morning and day-time hours were dominated by stratiform precipitation and small system sizes respectively. Most results clearly showed that the eastern locations of Sudano and Sahel were consistently dry because rainfall and precipitation features were predominantly few. System sizes greater than or equal to 800 km² were found in the western axis of the Sudano and Sahel zones, whereas the eastern axis, particularly in the Sahel zone, had minimal occurrences of small/large system sizes. From the results of locations of extreme systems, flashcount greater than 275 in one single system was never observed during the morning (6Z) diurnal, whereas, the evening (18Z) diurnal had the most frequent cases (at least 8) of flashcount exceeding 275 in one single system. Results presented had shown the importance of diurnal variation in understanding precipitation, flashcount, system sizes patterns at diurnal scales, and understanding land-ocean contrast, precipitation, and wind field anomaly at diurnal scales.

Keywords: convective properties, diurnal circle, flashcount, system sizes

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

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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

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Authors: Youness Laaroussi, Zine Elabidine Guennoun, Amine Amar

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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: Benedictus Asriparusa, Lathifah Al Hakimi, Aulia Husada

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A large amount of energy is being wasted by the release of natural gas associated with the oil industry. This release interrupts the environment particularly atmosphere layer condition globally which contributes to global warming impact. This research presents an overview of the methods employed by researchers in PT. Chevron Pacific Indonesia in the Minas area to determine a new prediction method of measuring and reducing gas flaring and its emission. The method emphasizes advanced research which involved analytical studies, numerical studies, modeling, and computer simulations, amongst other techniques. A flaring system is the controlled burning of natural gas in the course of routine oil and gas production operations. This burning occurs at the end of a flare stack or boom. The combustion process releases emissions of greenhouse gases such as NO2, CO2, SO2, etc. This condition will affect the chemical composition of air and environment around the boundary layer mainly during transition season. Transition season in Indonesia is absolutely very difficult condition to predict its pattern caused by the difference of two air mass conditions. This paper research focused on transition season in 2013. A simulation to create the new pattern of the pollutants distribution is needed. This paper has outlines trends in gas flaring modeling and current developments to predict the dominant variables in the pollutants distribution. A Fluent model is used to simulate the distribution of pollutants gas coming out of the stack, whereas WRF model output is used to overcome the limitations of the analysis of meteorological data and atmospheric conditions in the study area. Based on the running model, the most influence factor was wind speed. The goal of the simulation is to predict the new pattern based on the time of fastest wind and slowest wind occurs for pollutants distribution. According to the simulation results, it can be seen that the fastest wind (last of March) moves pollutants in a horizontal direction and the slowest wind (middle of May) moves pollutants vertically. Besides, the design of flare stack in compliance according to EPA Oil and Gas Facility Stack Parameters likely shows pollutants concentration remains on the under threshold NAAQS (National Ambient Air Quality Standards).

Keywords: flare motion, new prediction, pollutants distribution, transition season, WRF model

Procedia PDF Downloads 510

Authors: Ayman M. A. Rashwan, Mohamed F. Mohamed, Mohamed M. A. Abdalla

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A field experiment was conducted in the Agricultural Research Station, at El-Ghoraieb, Assiut to study dry seed yield performance of two locally adapted cultivars (‘Azmerly’ and ‘Cream 7’) and two line introductions (IT81D-1032 and IT82D-812) of common cowpea (Vigna unguiculata (L.) Walp) grown at three different within-row spaces (20, 30 and 40 cm) and two planting dates in the summer (April 15th and 30th) and in the fall season (Aug. 12th and 27th) of two successive seasons. The data showed that total dry-seed yield produced by plants grown at 20 cm was greater than at 30 cm in all cvs/lines in both years. Increases in 1000-seed weight were detected in cv ‘Azmerly’ and line IT82D-812 when they were grown at 30 cm as compared with 20 cm in the summer season. However, in the fall season such increases were found in all cvs/lines. Planting at 40 cm produced seeds of greater weight than planting at 30 cm for all cvs/lines in the fall season and also in cv. Cream 7 and line IT82D-812 in the summer season. Planting on April 15th in the summer and also planting on Aug. 12th in the fall had plants which showed increases in 1000-seed weight and total dry-seed yield. The greatest 1000-seed weight was found in the line IT81D-1032 in the summer season and in the line IT82D-812 in the fall season. The sum up results revealed that ‘Azmerly’ produced greater dry-seed yield than ‘Cream 7’ and both of them were superior to the line IT82D-812 and IT81D-1032 in the summer season. In the fall, however, the line IT82D-812 produced greater dry-seed yield than the other cultivars/lines.

Keywords: Cowpea, Assiut, fall, planting dates, El-Ghoraieb, dry-seed yield

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Authors: A. W. Kashimawo

Abstract:

Fish check list of Bayeku water, Lagos, Nigeria was investigated between February 2012 and January 2013. Fish specimens were caught with gill and cast-nets, and non-return valve basket trap. Services of artisanal fishermen were employed for the setting of gears and collections of fish. Species not captured after sampling were assumed to be absent or so rare as to be of minimal ecological importance. The 632 specimens were preserved in 10 % formaldehyde in the field prior to their identification. Physicochemical parameters such as temperature, salinity, dissolved oxygen and pH were determined from the lagoon water samples following standard methods. A total of 632 fish were encountered, belonging to 23 families, 27 genera and 29 species. The most abundant species were Chrysichthys nigrodigitatus (9.65 %), Macrobrachium vollenhoveni (7.94 %), Ethmalosa fimbriata (7.12 %), Elops lacerta (6.96 %), Cynoglossus browni (6.17 %), Gobioides broussonnetii (5.69 %), Sphyraena piscatorum (5.39 %), Polydactylus quadrifilis (5.06 %), and Mugil cephalus (4.91 %). There were seasonal variations in species occurrence and abundance. Marine fishes were found in dry season.. Freshwater fishes were more during the wet season. There are marine and freshwater fishes that have euryhaline characteristics and have adapted to the lagoon environment such that they were encountered both in dry and wet seasons.

Keywords: fish check list, species occurrence, abundance, ecological importance

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Authors: Evren Ozgur, Kasim Kocak

Abstract:

As a result of global warming and climate change, air temperature has increased and will continue to increase in the future. Increases in air temperatures have effects on a large number of variables in meteorology. One of the most important effects is the changes in the types of precipitation, especially in mid-latitudes. Because of increasing air temperatures, less snowfall was observed in the eastern parts of Turkey. Snowfall provides most of the water supply in spring and summer months, especially in mountainous regions of Turkey. When the temperature begins to increase in spring season, this snow starts to melt and plays an important role in agricultural purposes, drinking water supply and energy production. On the other hand, defining the snow season is very crucial especially in mountainous areas which have winter tourism opportunities. A reduction in the length of the snow season (LSS) in these regions will result in serious consequences in the long run. In the study, snow season was examined for 10 meteorological stations that are located above the altitude of 1000m. These stations have decreasing trends in the ratio of number of snowy days to total precipitation days considering earlier studies. Daily precipitation records with the observation period of 1971-2011 were used in the study. Then, the observation period was separated into 4 non-overlapping parts in order to identify decadal variations. Changes in the length of the snow season with increasing temperatures were obtained for these stations. The results of LSS were evaluated with the number of snowy days for each station. All stations have decreasing trend in number of snowy days for 1971-2011 period. In addition, seven of the results are statistically significant. Besides, decrease is observed regarding the length of snow season for studied stations. The decrease varies between 6.6 and 47.6 days according to decadal snow season averages of the stations.

Keywords: climate change, global warming, precipitation, snowfall, Turkey

Procedia PDF Downloads 149

Authors: Renato Morbidelli, Carla Saltalippi, Alessia Flammini, Marco Cifrodelli, Corrado Corradini

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The trend of magnitude and frequency of extreme rainfalls seems to be different depending on the investigated area of the world. In this work, the impact of climate change on extreme rainfalls in Umbria, an inland region of central Italy, is examined using data recorded during the period 1921-2015 by 10 representative rain gauge stations. The study area is characterized by a complex orography, with altitude ranging from 200 to more than 2000 m asl. The climate is very different from zone to zone, with mean annual rainfall ranging from 650 to 1450 mm and mean annual air temperature from 3.3 to 14.2°C. Over the past 15 years, this region has been affected by four significant droughts as well as by six dangerous flood events, all with very large impact in economic terms. A least-squares linear trend analysis of annual maximums over 60 time series selected considering 6 different durations (1 h, 3 h, 6 h, 12 h, 24 h, 48 h) showed about 50% of positive and 50% of negative cases. For the same time series the non-parametrical Mann-Kendall test with a significance level 0.05 evidenced only 3% of cases characterized by a negative trend and no positive case. Further investigations have also demonstrated that the variance and covariance of each time series can be considered almost stationary. Therefore, the analysis on the magnitude of extreme rainfalls supplies the indication that an evident trend in the change of values in the Umbria region does not exist. However, also the frequency of rainfall events, with particularly high rainfall depths values, occurred during a fixed period has also to be considered. For all selected stations the 2-day rainfall events that exceed 50 mm were counted for each year, starting from the first monitored year to the end of 2015. Also, this analysis did not show predominant trends. Specifically, for all selected rain gauge stations the annual number of 2-day rainfall events that exceed the threshold value (50 mm) was slowly decreasing in time, while the annual cumulated rainfall depths corresponding to the same events evidenced trends that were not statistically significant. Overall, by using a wide available dataset and adopting simple methods, the influence of climate change on the heavy rainfalls in the Umbria region is not detected.

Keywords: climate changes, rainfall extremes, rainfall magnitude and frequency, central Italy

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Authors: V. I. Chukwuemeka, S. M. Tsadu, R. O. Ojutiku, R. J. Kolo

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The food and feeding habits of Auchenoglanis occidentalis, which is commonly called the “BuBu” cat fish or the giraffe cat fish from Tagwai Lake Minna, was analysed from January to June, 2013. A total of 216 fish specimen were used for the study which were obtained from the local fishermen operating in Tagwai Lake Minna. Fishing gears used include cast nets and gills nets of various sizes. They also use hook and lines. The frequency of occurrence and dominance method were used to analyse the food in the gut. Auchenoglanis occidentalis from Tagwai Lake, Minna had a broad spectrum of food items in the gut, ranging from insects, fish, plant materials to protozoan. The percentage of insects was (31.75%), fish (12.70%), Chyme (20.63%), plant materials (20.63%), protozoa (1.59%) and soil (12.70%). The presence of different food items in the gut of the Auchenoglanis occidentalis which ranged from animal to plant and soil made it to be considered as an omnivore bottom feeder. The food habits of this fish showed no remarkable difference between the dry season months and the rainy season months. The broad food spectrum of the fish makes them a good aquaculture candidate. It also suggests that the specie feed both in surface water and near the substratum (sand).

Keywords: Auchenoglanis occidentalis, ecology, Tagwai Lake, Nigeria

Procedia PDF Downloads 548