Applications of Open-Access Remotely Sensed Data for Flood Modelling and Mapping in Developing Regions

Ekeu-wei, Iguniwari Thomas; Blackburn, George Alan

doi:10.3390/hydrology5030039

Cited by 35 publications

(22 citation statements)

References 189 publications

(279 reference statements)

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“…In a statement released by the Nigerian Hydrological Service Agency, "The Lagdo Dam in Cameroon is still impounding water and has not started spilling water into River Benue" [50]. This goes further to show the value of transboundary flood monitoring and early warning, and its applicability across various transboundary river basins [6].…”

Section: The 2012 Flood Event Return Period Estimationsmentioning

confidence: 99%

“…Typically, networks of river gauging stations are established across several locations of interest to collect the necessary data over a given period [3]. However, operating such observatory systems-especially in developing regions-is often problematic due to financial (underfunding of data collection agencies), institutional (lack of technical capacity and commitment), operational (inaccessibility to remote gauge stations due to logistical and security challenges), and technical (equipment malfunction, replacement, damage, modification, discontinuity and manual data entry procedures prone to errors) factors [4][5][6].…”

Section: Introductionmentioning

confidence: 99%

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Infilling Missing Data in Hydrology: Solutions Using Satellite Radar Altimetry and Multiple Imputation for Data-Sparse Regions

Ekeu-wei

Blackburn

Pedruco

2018

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.

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Section: The 2012 Flood Event Return Period Estimationsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Infilling Missing Data in Hydrology: Solutions Using Satellite Radar Altimetry and Multiple Imputation for Data-Sparse Regions

Ekeu-wei

Blackburn

Pedruco

2018

Water

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“…Since most of the population depend on fishing and river water for domestic activities, detailed information on the river network is vital within the framework of management and monitoring of key resources. Likewise, flooding is a common occurrence in the Niger Delta which can have devastating effects on the population and infrastructure (Ekeu-Wei and Blackburn, 2018;NHSA, 2014). However, there is a paucity of digital spatial data for the Niger Delta, and there is no national spatial data infrastructure (Anifowose et al, 2012;Nwilo and Badejo, 2005).…”

Section: Study Sitementioning

confidence: 99%

River network delineation from Sentinel-1 SAR data

Obida

Blackburn

Whyatt

et al. 2019

International Journal of Applied Earth Observation and Geoinfor

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“…Required data can be obtained from the related institutions at this phase. Local/global open access data sets can be used in cases where data at the associated institutions are inexistent [54][55][56]. In order to integrate data, to process numerical and spatial data and to analyze and to visualize the results numerical calculations, geographical information systems and spreadsheet programs are used [4][5][6][7][8].…”

Section: Introductionmentioning

confidence: 99%

Estimation of Water Budget Components of the Sakarya River Basin by Using the WEAP-PGM Model

Yaykiran

Cüceloğlu

Ekdal

2019

Water

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The use of water resources has increased with rapid population growth, industrial development, and agricultural activities. Besides, the problem might increase with the potential climate change impacts on water quantity. Thus, sustainable use of water resources becomes crucial. Modeling studies provide scientific support to the analysis of water resource problems and develop strategies for current and potential problems for the sustainable management of water resources. In this study, WEAP-PGM (Water Evaluation and Planning System—Plant Growth Model) was applied to the Sakarya River Basin in Turkey, where almost 50% of the area is agricultural land. The main goals in the study are compiling/integrating available data from different sources in a data-scarce region for hydrological models, and estimating the water budget components of Sakarya River Basin on an annual basis as well as investigating the applicability of WEAP-PGM. General model performance ratings indicated that model simulations represent streamflow variations at acceptable levels. Model results revealed that, runoff is 4747 million m3, flow to groundwater is 3065 million m3 and evapotranspiration is 23,011 million m3. This model setup can be used as a baseline for calculating the crop yields under climate change in the context of water-food-energy nexus in the further studies.

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Applications of Open-Access Remotely Sensed Data for Flood Modelling and Mapping in Developing Regions

Cited by 35 publications

References 189 publications

Infilling Missing Data in Hydrology: Solutions Using Satellite Radar Altimetry and Multiple Imputation for Data-Sparse Regions

Infilling Missing Data in Hydrology: Solutions Using Satellite Radar Altimetry and Multiple Imputation for Data-Sparse Regions

River network delineation from Sentinel-1 SAR data

Estimation of Water Budget Components of the Sakarya River Basin by Using the WEAP-PGM Model

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