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Search Results: 1 - 10 of 14000 matches for " Martins Yusuf Otache "
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Nonlinear Deterministic Chaos in Benue River Flow Daily Time Sequence  [PDF]
Otache Yusuf Martins, Mohammed Abubakar Sadeeq, Isiguzo Edwin Ahaneku
Journal of Water Resource and Protection (JWARP) , 2011, DOI: 10.4236/jwarp.2011.310085
Abstract: The Various physical mechanisms governing river flow dynamics act on a wide range of temporal and spatial scales. This spatio-temporal variability has been believed to be influenced by a large number of variables. In the light of this, an attempt was made in this paper to examine whether the daily flow sequence of the Benue River exhibits low-dimensional chaos; that is, if or not its dynamics could be explained by a small number of effective degrees of freedom. To this end, nonlinear analysis of the flow sequence was done by evaluating the correlation dimension based on phase space reconstruction and maximal Lyapunov estimation as well as nonlinear prediction. Results obtained in all instances considered indicate that there is no discernible evidence to suggest that the daily flow sequence of the Benue River exhibit nonlinear deterministic chaotic signatures. Thus, it may be conjectured that the daily flow time series span a wide dynamical range between deterministic chaos and periodic signal contaminated with additive noise; that is, by either measurement or dynamical noise. However, contradictory results abound on the existence of low-dimensional chaos in daily streamflows. Hence, it is paramount to note that if the existence of low-dimension deterministic component is reliably verified, it is necessary to investigate its origin, dependence on the space-time behavior of precipitation and therefore on climate and role of the inflow-runoff mechanism.
Conditional Heteroscedasticity in Streamflow Process: Paradox or Reality?  [PDF]
Martins Yusuf Otache, Isiguzo Edwin Ahaneku, Abubakar Sadeeq Mohammed, John Jiya Musa
Open Journal of Modern Hydrology (OJMH) , 2012, DOI: 10.4236/ojmh.2012.24010
Abstract: The various physical mechanisms governing the dynamics of streamflow processes act on a seemingly wide range of temporal and spatial scales; almost all the mechanisms involved present some degree of nonlinearity. Against the backdrop of these issues, in this paper, attempt was made to critically look at the subject of Autoregressive Conditional Heteroscedasticity (ARCH) or volatility of streamflow processes, a form of nonlinear phenomena. Towards this end, streamflow data (both daily and monthly) of the River Benue, Nigeria were used for the study. Results obtained from the analyses indicate that the existence of conditional heteroscedasticity in streamflow processes is no paradox. Too, ARCH effect is caused by seasonal variation in the variance for monthly flows and could partly explain same in the daily streamflow. It was also evident that the traditional seasonal Autoregressive Moving Average (ARMA) models are inadequate in describing ARCH effect in daily streamflow process though, robust for monthly streamflow; and can be removed if proper deseasonalisation pre-processing was done. Considering the findings, the potential for a hybrid Autoregressive Moving Average (ARMA) and Generalised Autoregressive Conditional Heteroscedasticity (GARCH)type models should be further explored and probably embraced for modelling daily streamflow regime in view of the relevance of statistical modelling in hydrology.
Application of Parametric-Based Framework for Regionalisation of Flow Duration Curves  [PDF]
Martins Yusuf Otache, Muhammad Abdullahi Tyabo, Iyanda Murtala Animashaun, Lydia Pam Ezekiel
Journal of Geoscience and Environment Protection (GEP) , 2016, DOI: 10.4236/gep.2016.45009
Abstract: It is common knowledge that the end user of stream flow data may necessarily not have any prior knowledge of the quality control measures applied in their generation, therefore, conclusions drawn most often times may not be effective as desired. Thus, this study is an attempt at providing an independent quality construct to boost the confidence in the use of stream flow data by developing regional flow duration curves for selected ungauged stations of the upper Niger River Basin, Nigeria. Toward this end, stream flow data for seven gauging stations cover some sub basins in the Basin were obtained; precisely, monthly stream flow data covering a range of eleven to fifty-three years period. The flow duration curves from the gauging stations were fitted with three probability distribution models; i.e., logarithmic, power and exponential regression models. For the regionalisation, parameterisation was carried out in terms of the drainage area alone to allow for simplicity of models. Results obtained showed that the exponential regression model, in terms of Coefficient of Determination (R2) had the best fit. Though the regionalised model was simple, measurable agreement was obtained during the calibration and validation phases. However, considering the length of data used and probable variability in the stream flow regime, it is not possible to objectively generalise on the quality of the results. Against this backdrop, it suffices to take into cognisance the need to use an ensemble of catchment characteristics in the development of the flow duration curves and the overall regional models; this is important considering the implications of anthropogenic activities and hydro-climatic variations.
Statistical Variation of Physico-Chemical Properties of Shallow Wells Used for Agricultural Activities in an Agrarian Community, North Central Nigeria  [PDF]
John Jiya Musa, Martins Yusuf Otache, Elijah TsadoMusa, Michael Eneojo Omale, Ibrahim Ibrahim Yahuza Yerima
Open Access Library Journal (OALib Journal) , 2019, DOI: 10.4236/oalib.1105683
Water quality is gradually falling due to human activities, thus making clean water for both domestic and agricultural activities scarce. Population growth is expected to directly or indirectly move up from its current status by about 55%, thus increasing water stress or severe water scarcity over the next generation. This study is aimed at statistically ascertaining and determining the physico-chemical properties of some hand-dug wells in Niykangbe, an agrarian community in Nigeria. A total of twenty five samples were collected for each year during the dry season for a period of three years. Replicate samples were collected on monthly bases for a period of five months during the years 2014, 2015 and 2016. The results obtained indicated that aluminum, cyanide and manganese were not present in the water samples. The pH ranged between 7.10 and 7.70, electric conductivity ranged between 157 and 467 μs/cm and the temperature ranged between 30℃ and 33℃. The nitrate content ranged between 5.00 and 67.30 mg/l while nitrite ranged between 0.02 and 0.09 mg/l. The analysis should be that most of the parameters were still within the recommended standards of NSDWQ and WHO. It was concluded that intermittent test is carried out to ascertain the level of fitness of the various water samples for both domestic and agricultural use.
Stochastic Characteristics and Modelling of Monthly Rainfall Time Series of Ilorin, Nigeria  [PDF]
Ahaneku, I. Edwin, Otache, Y. Martins
Open Journal of Modern Hydrology (OJMH) , 2014, DOI: 10.4236/ojmh.2014.43006
The analysis of time series is essential for building mathematical models to generate synthetic hydrologic records, to forecast hydrologic events, to detect intrinsic stochastic characteristics of hydrologic variables as well to fill missing and extend records. To this end, this paper examined the stochastic characteristics of the monthly rainfall series of Ilorin, Nigeria vis-à-vis modelling of same using four modelling schemes. The Decomposition, Square root transformation-deseasonalisation, Composite, and Periodic Autoregressive (T-F) modelling schemes were adopted. Results of basic analysis of the stochastic characteristics revealed that the monthly series does not show any discernible presence of long-term trend, though there is a seeming inter-decadal annual variation. The series exhibits strong seasonality throughout its length, both in the moments and autocorrelation and significantly intermittent. Based on assessment of the respective models, the performance of the different modelling schemes can be expressed in this order: T-F > Composite > Square root transformation-Deseasonalised > Decomposition. Considering the results obtained, modelling of monthly rainfall series in the presence of serial correlation between months should be based on the establishment of conditional probability framework. On the other hand, in view of the inadequacy of these modelling schemes, because of the autoregressive model components in the coupling protocol, nonlinear deterministic methods such as Artificial Neural Network, Wavelet models could be viable complements to the linear stochastic framework.
ARMA Modelling of Benue River Flow Dynamics: Comparative Study of PAR Model  [PDF]
Otache Y. Martins, M. A. Sadeeq, I. E. Ahaneku
Open Journal of Modern Hydrology (OJMH) , 2011, DOI: 10.4236/ojmh.2011.11001
Abstract: The seemingly complex nature of river flow and the significant variability it exhibits in both time and space, have largely led to the development and application of the stochastic process concept for its modelling, forecasting, and other ancillary purposes. Towards this end, in this study, attempt was made at stochastic modelling of the daily streamflow process of the Benue River. In this regard, Autoregressive Moving Average (ARMA) models and its derivative, the Periodic Autoregressive (PAR) model were developed and used for forecasting. Comparative forecast performances of the different models indicate that despite the shortcomings associated with univariate time series, reliable forecasts can be obtained for lead times, 1 to 5 day-ahead. The forecast results also showed that the traditional ARMA model could not robustly simulate high flow regimes unlike the periodic AR (PAR). Thus, for proper understanding of the dynamics of the river flow and its management, especially, flood defense, in the light of this study, the traditional ARMA models may not be suitable since they do not allow for real-time appraisal. To account for seasonal variations, PAR models should be used in forecasting the streamflow processes of the Benue River. However, since almost all mechanisms involved in the river flow processes present some degree of nonlinearity thus, how appropriate the stochastic process might be for every flow series may be called to question.
Parametric Linear Stochastic Modelling of Benue River flow Process  [PDF]
Otache ., Y. Martins, I. E. Ahaneku, M. A. Sadeeq
Open Journal of Marine Science (OJMS) , 2011, DOI: 10.4236/ojms.2011.13008
Abstract: The dynamics and accurate forecasting of streamflow processes of a river are important in the management of extreme events such as floods and droughts, optimal design of water storage structures and drainage networks. In this study, attempt was made at investigating the appropriateness of stochastic modelling of the streamflow process of the Benue River using data-driven models based on univariate streamflow series. To this end, multiplicative seasonal Autoregressive Integrated Moving Average (ARIMA) model was developed for the logarithmic transformed monthly flows. The seasonal ARIMA model’s performance was compared with the traditional Thomas-Fiering model forecasts, and results obtained show that the multiplicative seasonal ARIMA model was able to forecast flow logarithms. However, it could not adequately account for the seasonal variability in the monthly standard deviations. The forecast flow logarithms therefore cannot readily be transformed into natural flows; hence, the need for cautious optimism in its adoption, though it could be used as a basis for the development of an Integrated Riverflow Forecasting System (IRFS). Since forecasting could be a highly “noisy” application because of the complex river flow system, a distributed hydrological model is recommended for real-time forecasting of the river flow regime especially for purposes of sustainable water resources management.
Studies on Dog Population in Makurdi, Nigeria (I): Demography and Survey of Pet Owners' Beliefs and Attitudes
EA Omudu, EO Otache, SM Adelusi
Journal of Research in Forestry, Wildlife and Environment , 2010,
Abstract: A survey of dog population in some residential areas of Makurdi, Nigeria, was investigated using household census and street observation methods, while residents' dog-related attitudes and beliefs were investigated using a structured questionnaire. The average number of dogs per household was 1.43. Dog-human ratio in the study location was 1 dog to every 4 persons, in Wurukum residential area this was however less with the ratio of 1 dog to every 3 persons. There was no significant (X2 = 1.42, df = 1, P > 0.05) difference in the distribution of sexes of dogs. The difference between free roaming dogs and those restricted within residential compounds was also not statistically significant (X2 = 1.08, P > 0.05). A total of 198 (98.0%) respondents who owned dogs kept them as house guards and/or security alert; only 18.8% of dog owners kept them as pets. The variation in reasons for keeping dogs was significant (X2 = 12.1, P < 0.05). The majority of respondents who do not own dog (91.7%) said it was to avoid dog bites. A significant proportion of respondents (48.0%) who kept dog could not mention any dog disease or disease transmitted by dogs. The implications of these findings are very critical in the control of rabies and other dog-borne disease and mobilization of residents for more responsible dog ownership in Nigeria.
Determination of Cyanide Content in Three Sweet Cassava Cultivars in Three Local Government Areas of Benue State, Nigeria  [PDF]
Simon Terver Ubwa, Monday Abel Otache, Gillian Ogbene Igbum, Tseaa Shambe
Food and Nutrition Sciences (FNS) , 2015, DOI: 10.4236/fns.2015.612112
Abstract: The cyanide content of the parenchyma (pulp) of three sweet cassava cultivars: Alhaji (Tropical Manihot Selection; TMS 98/0581), Ochengbila (Tropical Manihot Selection; TMS 98/0505), and Onono (Tropical Manihot Selection; TMS 98/0524) from three local government areas of Benue State were studied. Their contents were: TMS 98/0581 (41.46 - 53.40) mg/kg, TMS 98/0505 (45.12 - 58.93) mg/kg and TMS 98/0524 (46.38 - 58.08) mg/kg for all the local government areas. For the peels, it ranged from (63.41 - 108.96) mg/kg for all cultivars. The cyanide content of the cultivars varies from one local government to another and also from one farm to another. No appreciable loss of cyanide was observed after four days of storage. The cyanide content of boiled and roasted cassava parenchyma was (5.26 - 7.85) mg/kg and (9.73 - 10.55) mg/kg respectively for all the cultivars. Air dried parenchyma at (26°C - 32°C for one week and oven dried parenchyma at 60°C for four hours ranged from (16.05 - 18.83) mg/kg and (21.82 - 24.04) mg/kg respectively for all cultivars.
The Dynamic Location Model to Consider Background Traffic  [PDF]
Nahry Yusuf, Sutanto Soehodho
Journal of Transportation Technologies (JTTs) , 2012, DOI: 10.4236/jtts.2012.21005
Abstract: This study concerns to the determination of location of freight distribution warehouses. It is part of a series of research projects on a distribution system we developed to deal with cases in a public service obligation state-owned company (PSO-SOC). This current research is characterized by the consideration of background traffic of the entire time period of planning rather than one certain time target on location model. It is aimed that the location decision to be more applicable and accommodative to the dynamic of the traffic condition. Once the decision is implemented, it will give the best outcome for the entire time period, not only for the initial time, end time or certain time of time period. A heuristic approach is proposed to simplify complexity of the model and network representation technique is applied to solve the model. A hyphotetical example is discussed to illustrate the mechanism of finding the optimal solution in term of both its objective function and applicability.
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