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Iguniwari Thomas Ekeu-Wei
Kawari Technical Services Nigeria Limited, Yenagoa, Nigeria

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Journal article
Published: 25 August 2020 in ISPRS International Journal of Geo-Information
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Consistent data are seldom available for whole-catchment flood modelling in many developing regions, hence this study aimed to explore an integrated approach for flood modelling and mapping by combining available segmented hydrographic, topographic, floodplain roughness, calibration, and validation datasets using a two-dimensional Caesar-Lisflood hydrodynamic model to quantify and recreate the extent and impact of the historic 2012 flood in Nigeria. Available segments of remotely-sensed and in situ datasets (including hydrological, altimetry, digital elevation model, bathymetry, aerial photo, optical imagery, and radar imagery data) available to different degrees in the Niger-South hydrological area were systematically integrated to draw maximum benefits from all available data. Retrospective modelling, calibration, and validation were undertaken for the whole Niger- South hydrological catchment area of Nigeria, and then these data were segmented into sub-domains for re-validation to understand how data variability and uncertainties impact the accuracy of model outcomes. Furthermore, aerial photos were applied for the first time in the study area for flood model validation and for understanding how different physio-environmental properties influenced the synthetic aperture radar flood delineation capacity in the Niger Delta region of Nigeria. This study demonstrates how the complementary strengths of open, readily available geospatial datasets and tools can be leveraged to model and map flooding within acceptable levels of uncertainty for flood risk management.

ACS Style

Iguniwari Ekeu-Wei; George Blackburn. Catchment-Scale Flood Modelling in Data-Sparse Regions Using Open-Access Geospatial Technology. ISPRS International Journal of Geo-Information 2020, 9, 512 .

AMA Style

Iguniwari Ekeu-Wei, George Blackburn. Catchment-Scale Flood Modelling in Data-Sparse Regions Using Open-Access Geospatial Technology. ISPRS International Journal of Geo-Information. 2020; 9 (9):512.

Chicago/Turabian Style

Iguniwari Ekeu-Wei; George Blackburn. 2020. "Catchment-Scale Flood Modelling in Data-Sparse Regions Using Open-Access Geospatial Technology." ISPRS International Journal of Geo-Information 9, no. 9: 512.

Preprint
Published: 10 July 2020
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Consistent data is seldom available for whole-catchment flood modelling in many developing regions, thus this study demonstrates how the complementary strengths of open and readily available geospatial datasets and tools can be leverage to map flood risk within acceptable levels of uncertainty for flood risk management. Available fragmented remotely-sensed and in situ datasets (including hydrological data, altimetry, digital elevation model, bathymetry, aerial photos, optical and radar imageries) are systematically integrated using 2-dimensional CAESAR-LISFLOOD model to quantify and recreate the extent and impact of the historic 2012 flood in Nigeria. Experimental modelling, calibration and validation is undertaken for the whole Niger-South hydrological catchment area of Nigeria, then segmented into sub-domains for re-validation to understand how data variability and uncertainties impact on the accuracy of model outcomes. Furthermore, aerial photos are applied for the first time in the study area for flood model validation and to understand how different physio-environmental properties influence synthetic aperture radar flood delineation capacity in the Niger Delta region of Nigeria.

ACS Style

Iguniwari Thomas Ekeu-Wei; Alan George Blackburn. Catchment-Scale Flood Modelling in Data-Sparse Regions Using Open-Access Geospatial Technology. 2020, 1 .

AMA Style

Iguniwari Thomas Ekeu-Wei, Alan George Blackburn. Catchment-Scale Flood Modelling in Data-Sparse Regions Using Open-Access Geospatial Technology. . 2020; ():1.

Chicago/Turabian Style

Iguniwari Thomas Ekeu-Wei; Alan George Blackburn. 2020. "Catchment-Scale Flood Modelling in Data-Sparse Regions Using Open-Access Geospatial Technology." , no. : 1.

Journal article
Published: 20 October 2018 in Water
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In developing regions missing data are prevalent in historical hydrological datasets, owing to financial, institutional, operational and technical challenges. If not tackled, these data shortfalls result in uncertainty in flood frequency estimates and consequently flawed catchment management interventions that could exacerbate the impacts of floods. This study presents a comparative analysis of two approaches for infilling missing data in historical annual peak river discharge timeseries required for flood frequency estimation: (i) satellite radar altimetry (RA) and (ii) multiple imputation (MI). These techniques were applied at five gauging stations along the floodprone Niger and Benue rivers within the Niger River Basin. RA and MI enabled the infilling of missing data for conditions where altimetry virtual stations were available and unavailable, respectively. The impact of these approaches on derived flood estimates was assessed, and the return period of a previously unquantified devastating flood event in Nigeria in 2012 was ascertained. This study revealed that the use of RA resulted in reduced uncertainty when compared to MI for data infilling, especially for widely gapped timeseries (>3 years). The two techniques did not differ significantly for data sets with gaps of 1–3 years, hence, both RA and MI can be used interchangeably in such situations. The use of the original in situ data with gaps resulted in higher flood estimates when compared to datasets infilled using RA and MI, and this can be attributed to extrapolation uncertainty. The 2012 flood in Nigeria was quantified as a 1-in-100-year event at the Umaisha gauging station on the Benue River and a 1-in-50-year event at Baro on the Niger River. This suggests that the higher levels of flooding likely emanated from the Kiri and Lagdo dams in Nigeria and Cameroon, respectively, as previously speculated by the media and recent studies. This study demonstrates the potential of RA and MI for providing information to support flood management in developing regions where in situ data is sparse.

ACS Style

Iguniwari Thomas Ekeu-Wei; George Alan Blackburn; Philip Pedruco. Infilling Missing Data in Hydrology: Solutions Using Satellite Radar Altimetry and Multiple Imputation for Data-Sparse Regions. Water 2018, 10, 1483 .

AMA Style

Iguniwari Thomas Ekeu-Wei, George Alan Blackburn, Philip Pedruco. Infilling Missing Data in Hydrology: Solutions Using Satellite Radar Altimetry and Multiple Imputation for Data-Sparse Regions. Water. 2018; 10 (10):1483.

Chicago/Turabian Style

Iguniwari Thomas Ekeu-Wei; George Alan Blackburn; Philip Pedruco. 2018. "Infilling Missing Data in Hydrology: Solutions Using Satellite Radar Altimetry and Multiple Imputation for Data-Sparse Regions." Water 10, no. 10: 1483.

Review
Published: 31 July 2018 in Hydrology
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Flood modelling and mapping typically entail flood frequency estimation, hydrodynamic modelling and inundation mapping, which require specific datasets that are often unavailable in developing regions due to financial, logistical, technical and organizational challenges. This review discusses fluvial (river) flood modelling and mapping processes and outlines the data requirements of these techniques. This paper explores how open-access remotely sensed and other geospatial datasets can supplement ground-based data and high-resolution commercial satellite imagery in data sparse regions of developing countries. The merits, demerits and uncertainties associated with the application of these datasets, including radar altimetry, digital elevation models, optical and radar images, are discussed. Nigeria, located within the Niger river basin of West Africa is a typical data-sparse country, and it is used as a case study in this review to evaluate the significance of open-access datasets for local and transboundary flood analysis. Hence, this review highlights the vital contribution that open access remotely sensed data can make to flood modelling and mapping and to support flood management strategies in developing regions.

ACS Style

Iguniwari Thomas Ekeu-Wei; George Alan Blackburn. Applications of Open-Access Remotely Sensed Data for Flood Modelling and Mapping in Developing Regions. Hydrology 2018, 5, 39 .

AMA Style

Iguniwari Thomas Ekeu-Wei, George Alan Blackburn. Applications of Open-Access Remotely Sensed Data for Flood Modelling and Mapping in Developing Regions. Hydrology. 2018; 5 (3):39.

Chicago/Turabian Style

Iguniwari Thomas Ekeu-Wei; George Alan Blackburn. 2018. "Applications of Open-Access Remotely Sensed Data for Flood Modelling and Mapping in Developing Regions." Hydrology 5, no. 3: 39.

Journal article
Published: 14 March 2018 in Environment and Natural Resources Research
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In recent years, flooding has become a recurring problem in many regions including Nigeria, owing to changing climatic conditions, as well as anthropogenic factors such as poor land use management and urbanization that aggravate flood impact. To effectively manage and mitigate flood impact, hydrological data is required, and in many developing regions gauging stations are established, and gauge readers recruited and trained to collect and transmit such data to designated hydrological or water resource management agencies. This study focuses on understanding the challenges associated with hydrological data collection in Nigeria, using the Ogun-Osun River as a typical case, while analytically assessing how these challenges result in uncertainties that propagate unto flood frequency estimates that are used to inform flood management decisions. The findings reveal that (i) capacity and institutional gaps; lack of maintenance of hydrological infrastructure and surrounding landscape; poor data management architecture; and floods events that destroy hydrological equipment and inundate roads thereby restricting access to collected data during peak floods, are some of the challenges associated with hydrological data collection in developing regions; (ii) these conditions result in gaps in and shortened length of annual maximum hydrological time series required for flood frequency estimation, consequently leading to under or overestimation of low and high flood quantiles such as 1-in-2year and 1-in-100year floods, to levels of 0.67 m and 0.9 m respectively for the Ogun Osun River Basin. The need for improved data collation, management and adaptation of new technologies such as radar or sonar by the Ogun-Osun River Basin Development Authority is recommended in this study, to ensure sustainable and improved hydrological data collection, management, transferability and usability for flood management.

ACS Style

Iguniwari Thomas Ekeu-Wei. Evaluation of Hydrological Data Collection Challenges and Flood Estimation Uncertainties in Nigeria. Environment and Natural Resources Research 2018, 8, 44 .

AMA Style

Iguniwari Thomas Ekeu-Wei. Evaluation of Hydrological Data Collection Challenges and Flood Estimation Uncertainties in Nigeria. Environment and Natural Resources Research. 2018; 8 (2):44.

Chicago/Turabian Style

Iguniwari Thomas Ekeu-Wei. 2018. "Evaluation of Hydrological Data Collection Challenges and Flood Estimation Uncertainties in Nigeria." Environment and Natural Resources Research 8, no. 2: 44.

Journal article
Published: 17 January 2018 in Nigerian Journal of Technology
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This study presents a remote sensing approach of using freely available Landsat 8 satellite Indicators ( Land Surface Temperature ( LST ), Soil Adjusted Vegetation Index ( SAVI )) and Shuttle Radar Topography Mission (SRTM) Digital Elevation Model (DEM) geospatial data to assess the impact of dumpsites on the environment in Benin City, Nigeria. The fin ding reveals that the average derived LST at the dumpsites were higher than the immediate surrounding, and the average SAVI values were lower than the immediate surrounding. The high values of LST at the dumpsites depict the effect of gases released becaus e of decomposition activities, while low values of SAVI indicate vegetation response to soil and ground water contamination due to leachate infiltration. The average elevation within the dumpsite area derived from SRTM DEM was also applied as a proxy to es timate disposed waste quantity, and related closely with LST that depict biodegradation activities. The result presented here shows that bacterial and fungal counts correlate strongly with the LST and SAVI values at each of the dumpsites R 2 : LST vs Bacteri a Count = 0.982, LST vs Fungi Count = 0.951; SAVI vs Bacteria Count = 0.745, SAVI vs Fungi Count = 0.664, thereby suggesting remote sensing can be applied to aid longterm dumpsite monitoring and management. Keywords: Municipal solid waste, Land Surface Temperature (LST), Soil Adjusted Vegetation Index (SAVI), and Remote sensing

ACS Style

I. T. Ekeu-Wei; K. I. Azuma; F. B. B. Ogunmuyiwa. Assessment of environmental impact of solid waste dumpsites using remote sensing. Nigerian Journal of Technology 2018, 37, 275 .

AMA Style

I. T. Ekeu-Wei, K. I. Azuma, F. B. B. Ogunmuyiwa. Assessment of environmental impact of solid waste dumpsites using remote sensing. Nigerian Journal of Technology. 2018; 37 (1):275.

Chicago/Turabian Style

I. T. Ekeu-Wei; K. I. Azuma; F. B. B. Ogunmuyiwa. 2018. "Assessment of environmental impact of solid waste dumpsites using remote sensing." Nigerian Journal of Technology 37, no. 1: 275.

Journal article
Published: 01 January 2018 in Open Journal of Air Pollution
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With the increasing trend of development and industrialization in Malaysia, air pollution has become an inevitable part of the process, resulting from increased vehicular activities and industrial processes. Toll operators are potentially exposed to high levels of air pollutants from working in proximity to traffic pollution sources, thereby increasing their risk of health defects associated with air pollution exposure. This study assessed the levels of Nitrogen dioxide (NO2) toll operators are exposed to, considering the influences traffic density and meteorological factors. This is intended to serve as an indicator of the cumulative pollution emanating from the combustion process of vehicles at toll plazas. Using Passive diffusion samplers saturated with Triethanolamine (TEA), the weekly indoor and outdoor NO2 concentrations at tollbooth were measured at Sungai Besi (SB), Kajang (KJ) and Putra-Makhota (PM) toll Plazas, to capture the varying traffic densities of 138,000, 65,000 and 24,100 vehicles/day respectively. The results showed that NO2 concentrations increase with traffic densities, and indoor NO2 concentrations correlated highly with outdoor NO2 concentrations (R2: SB = 0.767, KJ = 0.689 and PM = 0.877). The indoor/outdoor NO2 ratio varied from 0.7 to 1.2 for all toll booths, suggesting pollution control in-efficiency, caused by technical and behavioural factors. Also, meteorological factors had no significant effect on nitrogen dioxide concentrations, contrary to previous studies, which is likely due to the far distance between tool plazas and meteorological stations. Furthermore, the NO2 concentrations reported in this study were higher in comparison to weekly standards adopted in Germany (0.032 ppm) and previous literature. Therefore, toll operators are potentially exposed to high levels of pollution, and we advise that toll operators to wear pollution protection gears to reduce the risk of exposure, and the ventilation systems and mitigation measure (air curtain) reviewed to assess its efficiency.

ACS Style

Iguniwari Ekeu-Wei; Kate Ihuaku Azuma; Florence Buloere Biu Ogunmuyiwa. Passive Sampling of Ambient Nitrogen Dioxide at Toll Plazas in Malaysia. Open Journal of Air Pollution 2018, 07, 14 -33.

AMA Style

Iguniwari Ekeu-Wei, Kate Ihuaku Azuma, Florence Buloere Biu Ogunmuyiwa. Passive Sampling of Ambient Nitrogen Dioxide at Toll Plazas in Malaysia. Open Journal of Air Pollution. 2018; 07 (01):14-33.

Chicago/Turabian Style

Iguniwari Ekeu-Wei; Kate Ihuaku Azuma; Florence Buloere Biu Ogunmuyiwa. 2018. "Passive Sampling of Ambient Nitrogen Dioxide at Toll Plazas in Malaysia." Open Journal of Air Pollution 07, no. 01: 14-33.