kingsley ogbu | Univeristy of Nigeria, Nsukka (original) (raw)

Papers by kingsley ogbu

Archives of current research international, Jan 10, 2016

Participatory variety selection is the most important breeding program which enhanced adoption of... more Participatory variety selection is the most important breeding program which enhanced adoption of suitable improved varieties in order to address the needs of a broader range of users and to enhance farmer skills in variety selection and seed production efforts. It plays significant role in collaboration between breeders, farmers, marketers, processors, consumers, and policy makers. It also allows farmers to take part in the development of new varieties more suitable to marginal environments and to organic farming agronomic practices. Several different improved sorghum varieties are released at different international and national research institutions in different times, however the technologies were not properly addressed the farmers based on participatory, client oriented and demand driven. Therefore, the experiment was conducted in Eastern part of Ethiopia of Oromia regional state to evaluate the performance of improved sorghum varieties and to identify farmers' preference traits through continuous performance evaluation at different stages of the crop. Five sorghum varieties along with local check collected from study area were evaluated in randomized complete block design in 2019 main cropping season. Farmers' evaluation was made at two different stages of the crop, namely at flowering and maturity using both direct-matrix and pair-wise ranking methods of selection scheme. Farmers' set; grain yield, disease resistance, grain color and seed size as selection criteria to evaluate and identify their preferred varieties. The results of analysis of variance indicated the existence of highly significant differences among varieties for all traits measured except plant height at 5% probability level. The highest mean grain yield was obtained from the variety Dibaba (11325 Kgha-1) and Jiru (10200 Kgha-1) respectively. Grain yield had positive and highly significantly correlated with thousand seed weight (0.95**) and also positively and significantly correlated with days to 50% flowering (0.85*). Likewise, based on the overall farmer's preference (from both pair-wise and direct matrix ranking evaluations), Dibaba and Jiru were ranked first and second and followed by Adelle, ETS2752 and Chiro respectively. Thus, the varieties Dibaba and Jiru were chosen for their performance in the field and from farmers' evaluation perspective. Moreover, this study indicated participatory varietal selection is a viable method to gain greater insight into farmers' perceptions, preferences, merits and shortcomings of sorghum varieties. Therefore, based on the results of this study, Dibaba and Jiru are recommended for multiplication and distribution to farmers through both formal and informal seed systems. Generally, the integration of plant breeders and farmer's perception used to increase the adoption rate and design a good breeding program for future improvement.

ASM science journal, Dec 5, 2022

In this study, selected types of grasses were studied to determine their hydraulic roughness coef... more In this study, selected types of grasses were studied to determine their hydraulic roughness coefficient and to select the most suitable grass for erosion control. The experiments were performed in twelve trapezoidal open channels measuring 5 m x 0.12 m x 0.03 m at different flow depths (0.001m, 0.002m, 0.003m, 0.004m and 0.005m) and at varying bed slope (0.2%, 0.3%, and 0.4%). Overall, Bahama grass showed the highest Manning's n-value due to its deep root system and creeping nature. For each slope, the degree of submergence, Reynolds number, and flow depth increases as Manning's n decreases. As the flow depth increases, the Reynolds number increased while the drag coefficient, Cd decreases.

Hydrology

Hydrologic modeling in Nigeria is plagued by non-existent or paucity of hydro-metrological/morpho... more Hydrologic modeling in Nigeria is plagued by non-existent or paucity of hydro-metrological/morphological records, which has detrimental impacts on sustainable water resource management and agricultural production. Nowadays, freely accessible remotely sensed products are used as inputs in hydrologic modeling, especially in regions with deficient observed records. Therefore, it is appropriate to utilize the fine-resolution spatial coverage offered by these products in a parameter regionalization method that supports sub-grid variability. This study assessed the transferability of optimized model parameters from a gauged to an ungauged basin using the mesoscale Hydrologic Model (mHM)—Multiscale Parameter Regionalization (MPR) technique. The ability of the fifth generation European Centre for Medium-Range Weather Forecasts Reanalysis product (ERA5), Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS), Global Precipitation Climatology Centre (GPCC), and Multi-Source W...

Archives of Current Research International, 2016

<p>Predictive hydrologic modelling to understand and support agricultural water res... more <p>Predictive hydrologic modelling to understand and support agricultural water resources management and food security policies in Nigeria is a demanding task due to the paucity of hydro-meteorological measurements. This study assessed the skill of using different remotely-sensed products in a multi-calibration framework for evaluating the performance of the mesoscale Hydrologic Model (mHM) across four (4) different data-scarce basins within the Guinea-Sudano region of Nigeria.  Satellite rainfall estimates (SFEs) obtained from the Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS), Climate Prediction Center (CPC), European Center for Medium-Range Weather Forecast (ECMWF) Reanalysis 5<sup>th</sup> Generation (ERA5), Global Precipitation Climatological Center (GPCC) and Multi-Source Weighted Ensemble Precipitation (MSWEP) models were used to drive the mHM for different basins across different climatic regions in Nigeria. The multiscale parameter regionalization (MPR) approach was implemented to overcome the problems of over-parameterization and equifinality of model parameters during model calibration. Model calibration was first performed using discharge (Q), and next calibrated by using a combination of discharge (Q) and actual evapotranspiration (AET) for each setup driven by a rainfall product. A multi-variable approach using both Q and AET was also used during model evaluation. The mHM model driven with CHIRPS dataset showed reasonable results (0.5 < KGE ≤ 0.85) during calibration with both Q and AET variables while KGE varied between 0.34 – 0.63 during model validation using the same variables across all basins under consideration. This study underscores the utility of the CHIRPS model for hydrologic modelling in sub-Saharan Africa as well as the spatial predictive skill of the mHM. Generally, this study draws special attention to the MPR approach as a good alternative to consider for distributed hydrologic modelling in poorly-gauged basins.</p>

Rainwater harvesting has become an alternative water source especially in developing countries wh... more Rainwater harvesting has become an alternative water source especially in developing countries where many people lack access to pipe borne water. The build-up of greenhouse gases (GHGs) in the atmosphere has had negative impacts on the quality of rainwater and poses great risks to people who depend on this source of water resources. Hence this study assess the physico-chemical and microbiological parameters of rainwater collected in the open in Oko, Orumba North L.G.A. of Anambra State. In the study, direct harvested rainwater were collected from three stations in Oko community and analyzed to investigate the quality of harvested rainwater within the region. Thirty-one water quality parameters were considered and analyzed in the laboratory. The laboratory results were compared to permissible water quality level as recommended by NAFDAC. The comparative parameters analysis shows that the sample collected rainwater were within the permissible limit except for pH which was slightly aci...

Natural Resource Modeling, 2021

Quantifying possible sources of uncertainty in simulations of hydrological extreme events is very... more Quantifying possible sources of uncertainty in simulations of hydrological extreme events is very important for better risk management in extreme situations and water resource planning. The main objective of this research work is to identify and address the role of input data quality and hydrological parameter sets, and uncertainty propagation in hydrological extremes estimation. This includes identifying and estimating their contribution to flood and low flow magnitude using two objective functions (NSE for flood and LogNSE for low flow), 20,000 Hydrologiska Byråns Vattenbalansavdelning (HBV) hydrological parameter sets, and three frequency distribution models (Log-Normal, Pearson-III, and Generalized Extreme Value). The influence of uncertainty on the simulated flow is not uniform across all the selected three catchments due to different flow regimes and runoff generation mechanisms. The result shows that the uncertainty in high flow frequency modeling mainly comes from the input This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

Nigerian Journal of Technology, Jan 15, 2018

Soil and Water Assessment Tool, (SWAT) model was used to predict the impacts of Climate Change on... more Soil and Water Assessment Tool, (SWAT) model was used to predict the impacts of Climate Change on Ajali River watershed, Aguobu-Umumba, Ezeagu, Enugu State, Nigeria. The model was first used to simulate stream flow using observed data. After model run, parameterization, sensitivity analysis, the monthly coefficients of determination (R 2) were 0.5739 and 0.6776 for calibration and validation respectively. Having performed fairly well, the model was thereafter run to simulate climate change impacts on streamflow. Two GCMs-CCCMA and GFDL, were used to generate future climate data and run in SWAT. Total observed streamflow for the baseline (1981-2000) was compared with that predicted (2046-2064) from the GCMs. The results of the CCCMA models showed an increase of 383.72m 3 /s and 2.1% in the streamflow of the Ajali river watershed when projected to 2046-2064 as against the historical baseline while GFDL showed 3358.58 m 3 /s and 18.9% respectively. The study, when applied, will help watershed managers and planners in the management of the watershed for effectiveness and efficiency. It will also increase our awareness of the effect of climate change on other water bodies in the hinterlands.

Journal of Water and Land Development, 2020

This study is aimed at evaluating the applicability of Artificial Neural Network (ANN) model tech... more This study is aimed at evaluating the applicability of Artificial Neural Network (ANN) model technique for river discharge forecasting. Feed-forward multilayer perceptron neural network trained with back-propagation algorithm was employed for model development. Hydro-meteorological data for the Imo River watershed, that was collected from the Anambra-Imo River Basin Development Authority, Owerri – Imo State, South-East, Nigeria, was used to train, validate and test the model. Coefficients of determination results are 0.91, 0.91 and 0.93 for training, validation and testing periods respectively. River discharge forecasts were fitted against actual discharge data for one to five lead days. Model results gave R values of 0.95, 0.95, 0.92, 0.96 and 0.94 for first, second, third, fourth, and fifth lead days of forecasts, respectively. It was generally observed that the R values decreased with increase in lead days for the model. Generally, this technique proved to be effective in river d...

<p>The variability and changes noted in the climate over the past decades emphasizes the im... more <p>The variability and changes noted in the climate over the past decades emphasizes the importance of climate information such as precipitation datasets in the management of flood risks in Benin and Togo. The lack of extensive and functional ground observation networks, introduces satellite-based rainfall datasets as a better alternative which needs however to be evaluated beforehand. This study investigated the performance of four satellite and gauge-based rainfall products &#8211;Climate Hazards Group Infrared Precipitation with Station data version v2.0 (CHIRPS), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN), Tropical Applications of Meteorology using Satellite data and ground-based observations (TAMSAT) and the Global Precipitation Climatology Centre full daily data (GPCC) &#8211; at gauge point level over the Mono River basin which is stretched over Benin and Togo territories. Three synoptic stations located in Tabligbo, Atakpam&#233; and Sokod&#233; were considered because of the completeness of their time series during the study period 1983-2012. The assessments were conducted at daily, dekadal (10-day period), seasonal and annual scale using both continuous and categorical statistics. Results show poor performances at daily and annual temporal scales while the seasonal cycles were well reproduced with Nash-Sutcliffe efficiency equal or higher than 0.94, and correlation coefficient above 0.9. At Tabligbo, CHIRPS and GPCC showed the best statistical results whereas the performance of PERSIANN and TAMSAT varies with the temporal scale and the station. The probability of rainfall detection (POD) and the capability of reproducing extreme daily maxima indicate GPCC as the best product for flood monitoring purposes at daily scale. However, all assessed products exhibited high POD and low false alarm ratio (FAR) at dekadal scale.</p>

Journal of Hydrology: Regional Studies

African Journal of Agricultural Research, Jan 25, 2018

Vegetation has a marked effect on runoff and soil moisture and plays an important the hydrologic ... more Vegetation has a marked effect on runoff and soil moisture and plays an important the hydrologic cycle. The Watershed Resources Management (WRM) model, a process-based, continuous, distributed parameter simulation model developed for hydrologic and soil erosion studies at the watershed scale lack a crop growth component. As such, this model assumes a constant parameter values for vegetation and hydraulic parameters throughout the duration of hydrologic simulation. A crop growth algorithm based on the original plant growth model used in the Environmental Policy Integrated Climate (EPIC) model was developed for coupling to the WRM model. The developed model was tested for yield simulations using data from a field plot within the Oyun River basin, Ilorin, Nigeria. Model prediction closely matched observed values with R 2 of 0.9 for the years under study. This model will be incorporated into the WRM model in other to improve its representation of vegetation growth stages in a natural basin. This modification will further enhance its capability for accurate hydrologic and crop growth studies.

Climate

Understanding the variability of rainfall is important for sustaining rain-dependent agriculture ... more Understanding the variability of rainfall is important for sustaining rain-dependent agriculture and driving the local economy of Nigeria. Paucity and inadequate rain gauge network across Nigeria has made satellite-based rainfall products (SRPs), which offer a complete spatial and consistent temporal coverage, a better alternative. However, the accuracy of these products must be ascertained before use in water resource developments and planning. In this study, the performances of Climate Hazards Group Infrared Precipitation with Station data (CHIRPS), Precipitation estimation from Remotely Sensed Information using Artificial Neural Networks–Climate Data Record (PERSIANN-CDR), and Tropical Applications of Meteorology using SATellite data and ground-based observations (TAMSAT), were evaluated to investigate their ability to reproduce long term (1983–2013) observed rainfall characteristics derived from twenty-four (24) gauges in Nigeria. Results show that all products performed well in...

Journal of Water and Land Development

Solar radiation (Rs) is an essential input for estimating reference crop evapotranspiration, ETo.... more Solar radiation (Rs) is an essential input for estimating reference crop evapotranspiration, ETo. An accurate estimate of ETo is the first step involved in determining water demand of field crops. The objective of this study was to assess the accuracy of fifteen empirical solar radiations (Rs) models and determine its effects on ETo estimates for three sites in humid tropical environment (Abakaliki, Nsukka, and Awka). Meteorological data from the archives of NASA (from 1983 to 2005) was used to derive empirical constants (calibration) for the different models at each location while data from 2006 to 2015 was used for validation. The results showed an overall improvement when comparing measured Rs with Rs determined using original constants and Rs using the new constants. After calibration, the Swartman–Ogunlade (R2 = 0.97) and Chen 2 models (RMSE = 0.665 MJ∙m−2∙day−1) performed best while Chen 1 (R2 = 0.66) and Bristow–Campbell models (RMSE = 1.58 MJ∙m−2∙day−1) performed least in es...

Journal of Water and Land Development

Changes in runoff trends have caused severe water shortages and ecological problems in agricultur... more Changes in runoff trends have caused severe water shortages and ecological problems in agriculture and human well-being in Nigeria. Understanding the long-term (inter-annual to decadal) variations of water availability in river basins is paramount for water resources management and climate change adaptation. Climate change in Northern Nigeria could lead to change of the hydrological cycle and water availability. Moreover, the linkage between climatic changes and streamflow fluctuations is poorly documented in this area. Therefore, this study examined temporal trends in rainfall, temperature and runoff records of Kaduna River basin. Using appropriate statistical tools and participatory survey, trends in streamflow and their linkages with the climate indices were explored to determine their amplifying impacts on water availability and impacts on livelihoods downstream the basin. Analysis indicate variable rainfall trend with significant wet and dry periods. Unlike rainfall, temperatur...

Quantifying possible sources of uncertainty in simulations of hydrological extreme events is very... more Quantifying possible sources of uncertainty in simulations of hydrological extreme events is very important for better risk management in extreme situations and water resource planning. The main objective of this research work is to identify and address the role of input data quality and hydrological parameter sets, and uncertainty propagation in hydrological extremes estimation. This includes identifying and estimating their contribution to flood and low flow magnitude using two objective functions (NSE for flood and LogNSE for low flow), 20,000 Hydrologiska Byråns Vattenbalansavdelning (HBV) hydrological parameter sets, and three frequency distribution models (Log-Normal, Pearson-III, and Generalized Extreme Value). The influence of uncertainty on the simulated flow is not uniform across all the selected three catchments due to different flow regimes and runoff generation mechanisms. The result shows that the uncertainty in high flow frequency modeling mainly comes from the input This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

Nigerian Journal of Technology

The quantity and quality of water present in the soil determine to a greater extent the performan... more The quantity and quality of water present in the soil determine to a greater extent the performance of agricultural crops. Real-time determination of moisture content has a greater advantage over the traditional gravimetric method of determining soil moisture content. Thus, this work was based on the design and construction of a cost effective digital capacitive soil moisture sensor for real-time measurement. The moisture sensors comprised four integrated units namely: power supply unit with a 9V DC battery as a power source, sensor unit with a locally sourced Printed Circuit Board (PCB) as the single sensing probe, control unit made up of PIC16f877 microcontroller programmed with a C language and the C source code compiled in Corporate Computer Services Compiler (CSS C) compiler development environment, and a 16x2 display unit which displays the readings in percentage moisture content (%MC) and capacitance (μF) of the soil obtained from the sensor on its screen. Standard gravimetri...

Archives of current research international, Jan 10, 2016

Participatory variety selection is the most important breeding program which enhanced adoption of... more Participatory variety selection is the most important breeding program which enhanced adoption of suitable improved varieties in order to address the needs of a broader range of users and to enhance farmer skills in variety selection and seed production efforts. It plays significant role in collaboration between breeders, farmers, marketers, processors, consumers, and policy makers. It also allows farmers to take part in the development of new varieties more suitable to marginal environments and to organic farming agronomic practices. Several different improved sorghum varieties are released at different international and national research institutions in different times, however the technologies were not properly addressed the farmers based on participatory, client oriented and demand driven. Therefore, the experiment was conducted in Eastern part of Ethiopia of Oromia regional state to evaluate the performance of improved sorghum varieties and to identify farmers&amp;amp;#39; preference traits through continuous performance evaluation at different stages of the crop. Five sorghum varieties along with local check collected from study area were evaluated in randomized complete block design in 2019 main cropping season. Farmers&amp;amp;#39; evaluation was made at two different stages of the crop, namely at flowering and maturity using both direct-matrix and pair-wise ranking methods of selection scheme. Farmers&amp;amp;#39; set; grain yield, disease resistance, grain color and seed size as selection criteria to evaluate and identify their preferred varieties. The results of analysis of variance indicated the existence of highly significant differences among varieties for all traits measured except plant height at 5% probability level. The highest mean grain yield was obtained from the variety Dibaba (11325 Kgha-1) and Jiru (10200 Kgha-1) respectively. Grain yield had positive and highly significantly correlated with thousand seed weight (0.95**) and also positively and significantly correlated with days to 50% flowering (0.85*). Likewise, based on the overall farmer&amp;amp;#39;s preference (from both pair-wise and direct matrix ranking evaluations), Dibaba and Jiru were ranked first and second and followed by Adelle, ETS2752 and Chiro respectively. Thus, the varieties Dibaba and Jiru were chosen for their performance in the field and from farmers&amp;amp;#39; evaluation perspective. Moreover, this study indicated participatory varietal selection is a viable method to gain greater insight into farmers&amp;amp;#39; perceptions, preferences, merits and shortcomings of sorghum varieties. Therefore, based on the results of this study, Dibaba and Jiru are recommended for multiplication and distribution to farmers through both formal and informal seed systems. Generally, the integration of plant breeders and farmer&amp;amp;#39;s perception used to increase the adoption rate and design a good breeding program for future improvement.

ASM science journal, Dec 5, 2022

In this study, selected types of grasses were studied to determine their hydraulic roughness coef... more In this study, selected types of grasses were studied to determine their hydraulic roughness coefficient and to select the most suitable grass for erosion control. The experiments were performed in twelve trapezoidal open channels measuring 5 m x 0.12 m x 0.03 m at different flow depths (0.001m, 0.002m, 0.003m, 0.004m and 0.005m) and at varying bed slope (0.2%, 0.3%, and 0.4%). Overall, Bahama grass showed the highest Manning's n-value due to its deep root system and creeping nature. For each slope, the degree of submergence, Reynolds number, and flow depth increases as Manning's n decreases. As the flow depth increases, the Reynolds number increased while the drag coefficient, Cd decreases.

Hydrology

Hydrologic modeling in Nigeria is plagued by non-existent or paucity of hydro-metrological/morpho... more Hydrologic modeling in Nigeria is plagued by non-existent or paucity of hydro-metrological/morphological records, which has detrimental impacts on sustainable water resource management and agricultural production. Nowadays, freely accessible remotely sensed products are used as inputs in hydrologic modeling, especially in regions with deficient observed records. Therefore, it is appropriate to utilize the fine-resolution spatial coverage offered by these products in a parameter regionalization method that supports sub-grid variability. This study assessed the transferability of optimized model parameters from a gauged to an ungauged basin using the mesoscale Hydrologic Model (mHM)—Multiscale Parameter Regionalization (MPR) technique. The ability of the fifth generation European Centre for Medium-Range Weather Forecasts Reanalysis product (ERA5), Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS), Global Precipitation Climatology Centre (GPCC), and Multi-Source W...

Archives of Current Research International, 2016

&lt;p&gt;Predictive hydrologic modelling to understand and support agricultural water res... more &lt;p&gt;Predictive hydrologic modelling to understand and support agricultural water resources management and food security policies in Nigeria is a demanding task due to the paucity of hydro-meteorological measurements.&amp;#160;This study assessed the skill of using different remotely-sensed products in a multi-calibration framework for evaluating the performance of the mesoscale Hydrologic Model (mHM) across four (4) different data-scarce basins within the Guinea-Sudano region of Nigeria. &amp;#160;Satellite rainfall estimates (SFEs) obtained from the Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS), Climate Prediction Center (CPC), European Center for Medium-Range Weather Forecast (ECMWF) Reanalysis 5&lt;sup&gt;th&lt;/sup&gt; Generation (ERA5), Global Precipitation Climatological Center (GPCC) and Multi-Source Weighted Ensemble Precipitation (MSWEP) models were used to drive the mHM for different basins across different climatic regions in Nigeria. The multiscale parameter regionalization (MPR) approach was implemented to overcome the problems of over-parameterization and equifinality of model parameters during model calibration. Model calibration was first performed using discharge (Q), and next calibrated by using a combination of discharge (Q) and actual evapotranspiration (AET) for each setup driven by a rainfall product. A multi-variable approach using both Q and AET was also used during model evaluation. The mHM model driven with CHIRPS dataset showed reasonable results (0.5 &lt; KGE &amp;#8804; 0.85) during calibration with both Q and AET variables while KGE varied between 0.34 &amp;#8211; 0.63 during model validation using the same variables across all basins under consideration. This study underscores the utility of the CHIRPS model for hydrologic modelling in sub-Saharan Africa as well as the spatial predictive skill of the mHM. Generally, this study draws special attention to the MPR approach as a good alternative to consider for distributed hydrologic modelling in poorly-gauged basins.&lt;/p&gt;

Rainwater harvesting has become an alternative water source especially in developing countries wh... more Rainwater harvesting has become an alternative water source especially in developing countries where many people lack access to pipe borne water. The build-up of greenhouse gases (GHGs) in the atmosphere has had negative impacts on the quality of rainwater and poses great risks to people who depend on this source of water resources. Hence this study assess the physico-chemical and microbiological parameters of rainwater collected in the open in Oko, Orumba North L.G.A. of Anambra State. In the study, direct harvested rainwater were collected from three stations in Oko community and analyzed to investigate the quality of harvested rainwater within the region. Thirty-one water quality parameters were considered and analyzed in the laboratory. The laboratory results were compared to permissible water quality level as recommended by NAFDAC. The comparative parameters analysis shows that the sample collected rainwater were within the permissible limit except for pH which was slightly aci...

Natural Resource Modeling, 2021

Quantifying possible sources of uncertainty in simulations of hydrological extreme events is very... more Quantifying possible sources of uncertainty in simulations of hydrological extreme events is very important for better risk management in extreme situations and water resource planning. The main objective of this research work is to identify and address the role of input data quality and hydrological parameter sets, and uncertainty propagation in hydrological extremes estimation. This includes identifying and estimating their contribution to flood and low flow magnitude using two objective functions (NSE for flood and LogNSE for low flow), 20,000 Hydrologiska Byråns Vattenbalansavdelning (HBV) hydrological parameter sets, and three frequency distribution models (Log-Normal, Pearson-III, and Generalized Extreme Value). The influence of uncertainty on the simulated flow is not uniform across all the selected three catchments due to different flow regimes and runoff generation mechanisms. The result shows that the uncertainty in high flow frequency modeling mainly comes from the input This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

Nigerian Journal of Technology, Jan 15, 2018

Soil and Water Assessment Tool, (SWAT) model was used to predict the impacts of Climate Change on... more Soil and Water Assessment Tool, (SWAT) model was used to predict the impacts of Climate Change on Ajali River watershed, Aguobu-Umumba, Ezeagu, Enugu State, Nigeria. The model was first used to simulate stream flow using observed data. After model run, parameterization, sensitivity analysis, the monthly coefficients of determination (R 2) were 0.5739 and 0.6776 for calibration and validation respectively. Having performed fairly well, the model was thereafter run to simulate climate change impacts on streamflow. Two GCMs-CCCMA and GFDL, were used to generate future climate data and run in SWAT. Total observed streamflow for the baseline (1981-2000) was compared with that predicted (2046-2064) from the GCMs. The results of the CCCMA models showed an increase of 383.72m 3 /s and 2.1% in the streamflow of the Ajali river watershed when projected to 2046-2064 as against the historical baseline while GFDL showed 3358.58 m 3 /s and 18.9% respectively. The study, when applied, will help watershed managers and planners in the management of the watershed for effectiveness and efficiency. It will also increase our awareness of the effect of climate change on other water bodies in the hinterlands.

Journal of Water and Land Development, 2020

This study is aimed at evaluating the applicability of Artificial Neural Network (ANN) model tech... more This study is aimed at evaluating the applicability of Artificial Neural Network (ANN) model technique for river discharge forecasting. Feed-forward multilayer perceptron neural network trained with back-propagation algorithm was employed for model development. Hydro-meteorological data for the Imo River watershed, that was collected from the Anambra-Imo River Basin Development Authority, Owerri – Imo State, South-East, Nigeria, was used to train, validate and test the model. Coefficients of determination results are 0.91, 0.91 and 0.93 for training, validation and testing periods respectively. River discharge forecasts were fitted against actual discharge data for one to five lead days. Model results gave R values of 0.95, 0.95, 0.92, 0.96 and 0.94 for first, second, third, fourth, and fifth lead days of forecasts, respectively. It was generally observed that the R values decreased with increase in lead days for the model. Generally, this technique proved to be effective in river d...

<p>The variability and changes noted in the climate over the past decades emphasizes the im... more <p>The variability and changes noted in the climate over the past decades emphasizes the importance of climate information such as precipitation datasets in the management of flood risks in Benin and Togo. The lack of extensive and functional ground observation networks, introduces satellite-based rainfall datasets as a better alternative which needs however to be evaluated beforehand. This study investigated the performance of four satellite and gauge-based rainfall products &#8211;Climate Hazards Group Infrared Precipitation with Station data version v2.0 (CHIRPS), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN), Tropical Applications of Meteorology using Satellite data and ground-based observations (TAMSAT) and the Global Precipitation Climatology Centre full daily data (GPCC) &#8211; at gauge point level over the Mono River basin which is stretched over Benin and Togo territories. Three synoptic stations located in Tabligbo, Atakpam&#233; and Sokod&#233; were considered because of the completeness of their time series during the study period 1983-2012. The assessments were conducted at daily, dekadal (10-day period), seasonal and annual scale using both continuous and categorical statistics. Results show poor performances at daily and annual temporal scales while the seasonal cycles were well reproduced with Nash-Sutcliffe efficiency equal or higher than 0.94, and correlation coefficient above 0.9. At Tabligbo, CHIRPS and GPCC showed the best statistical results whereas the performance of PERSIANN and TAMSAT varies with the temporal scale and the station. The probability of rainfall detection (POD) and the capability of reproducing extreme daily maxima indicate GPCC as the best product for flood monitoring purposes at daily scale. However, all assessed products exhibited high POD and low false alarm ratio (FAR) at dekadal scale.</p>

Journal of Hydrology: Regional Studies

African Journal of Agricultural Research, Jan 25, 2018

Vegetation has a marked effect on runoff and soil moisture and plays an important the hydrologic ... more Vegetation has a marked effect on runoff and soil moisture and plays an important the hydrologic cycle. The Watershed Resources Management (WRM) model, a process-based, continuous, distributed parameter simulation model developed for hydrologic and soil erosion studies at the watershed scale lack a crop growth component. As such, this model assumes a constant parameter values for vegetation and hydraulic parameters throughout the duration of hydrologic simulation. A crop growth algorithm based on the original plant growth model used in the Environmental Policy Integrated Climate (EPIC) model was developed for coupling to the WRM model. The developed model was tested for yield simulations using data from a field plot within the Oyun River basin, Ilorin, Nigeria. Model prediction closely matched observed values with R 2 of 0.9 for the years under study. This model will be incorporated into the WRM model in other to improve its representation of vegetation growth stages in a natural basin. This modification will further enhance its capability for accurate hydrologic and crop growth studies.

Climate

Understanding the variability of rainfall is important for sustaining rain-dependent agriculture ... more Understanding the variability of rainfall is important for sustaining rain-dependent agriculture and driving the local economy of Nigeria. Paucity and inadequate rain gauge network across Nigeria has made satellite-based rainfall products (SRPs), which offer a complete spatial and consistent temporal coverage, a better alternative. However, the accuracy of these products must be ascertained before use in water resource developments and planning. In this study, the performances of Climate Hazards Group Infrared Precipitation with Station data (CHIRPS), Precipitation estimation from Remotely Sensed Information using Artificial Neural Networks–Climate Data Record (PERSIANN-CDR), and Tropical Applications of Meteorology using SATellite data and ground-based observations (TAMSAT), were evaluated to investigate their ability to reproduce long term (1983–2013) observed rainfall characteristics derived from twenty-four (24) gauges in Nigeria. Results show that all products performed well in...

Journal of Water and Land Development

Solar radiation (Rs) is an essential input for estimating reference crop evapotranspiration, ETo.... more Solar radiation (Rs) is an essential input for estimating reference crop evapotranspiration, ETo. An accurate estimate of ETo is the first step involved in determining water demand of field crops. The objective of this study was to assess the accuracy of fifteen empirical solar radiations (Rs) models and determine its effects on ETo estimates for three sites in humid tropical environment (Abakaliki, Nsukka, and Awka). Meteorological data from the archives of NASA (from 1983 to 2005) was used to derive empirical constants (calibration) for the different models at each location while data from 2006 to 2015 was used for validation. The results showed an overall improvement when comparing measured Rs with Rs determined using original constants and Rs using the new constants. After calibration, the Swartman–Ogunlade (R2 = 0.97) and Chen 2 models (RMSE = 0.665 MJ∙m−2∙day−1) performed best while Chen 1 (R2 = 0.66) and Bristow–Campbell models (RMSE = 1.58 MJ∙m−2∙day−1) performed least in es...

Journal of Water and Land Development

Changes in runoff trends have caused severe water shortages and ecological problems in agricultur... more Changes in runoff trends have caused severe water shortages and ecological problems in agriculture and human well-being in Nigeria. Understanding the long-term (inter-annual to decadal) variations of water availability in river basins is paramount for water resources management and climate change adaptation. Climate change in Northern Nigeria could lead to change of the hydrological cycle and water availability. Moreover, the linkage between climatic changes and streamflow fluctuations is poorly documented in this area. Therefore, this study examined temporal trends in rainfall, temperature and runoff records of Kaduna River basin. Using appropriate statistical tools and participatory survey, trends in streamflow and their linkages with the climate indices were explored to determine their amplifying impacts on water availability and impacts on livelihoods downstream the basin. Analysis indicate variable rainfall trend with significant wet and dry periods. Unlike rainfall, temperatur...

Quantifying possible sources of uncertainty in simulations of hydrological extreme events is very... more Quantifying possible sources of uncertainty in simulations of hydrological extreme events is very important for better risk management in extreme situations and water resource planning. The main objective of this research work is to identify and address the role of input data quality and hydrological parameter sets, and uncertainty propagation in hydrological extremes estimation. This includes identifying and estimating their contribution to flood and low flow magnitude using two objective functions (NSE for flood and LogNSE for low flow), 20,000 Hydrologiska Byråns Vattenbalansavdelning (HBV) hydrological parameter sets, and three frequency distribution models (Log-Normal, Pearson-III, and Generalized Extreme Value). The influence of uncertainty on the simulated flow is not uniform across all the selected three catchments due to different flow regimes and runoff generation mechanisms. The result shows that the uncertainty in high flow frequency modeling mainly comes from the input This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

Nigerian Journal of Technology

The quantity and quality of water present in the soil determine to a greater extent the performan... more The quantity and quality of water present in the soil determine to a greater extent the performance of agricultural crops. Real-time determination of moisture content has a greater advantage over the traditional gravimetric method of determining soil moisture content. Thus, this work was based on the design and construction of a cost effective digital capacitive soil moisture sensor for real-time measurement. The moisture sensors comprised four integrated units namely: power supply unit with a 9V DC battery as a power source, sensor unit with a locally sourced Printed Circuit Board (PCB) as the single sensing probe, control unit made up of PIC16f877 microcontroller programmed with a C language and the C source code compiled in Corporate Computer Services Compiler (CSS C) compiler development environment, and a 16x2 display unit which displays the readings in percentage moisture content (%MC) and capacitance (μF) of the soil obtained from the sensor on its screen. Standard gravimetri...