Application of open-access and 3rd party geospatial technology for
      integrated flood risk management in data sparse regions of developing
      countries
Creators: name: Ekeu-Wei, Iguniwari
Publisher: name: Lancaster University
Year: 2018
Subjects: Flood mapping; Remote Sensing; Hydrology; Hydrodynamics; CAESAR-LISFLOOD, GIS; crowd-sourcing; Multiple Imputation; Radar Altimetry; Flood Frequency Analysis

description: Floods are one of the most devastating disasters known to man, caused by
      both natural and anthropogenic factors. The trend of flood events is
      continuously rising, increasing the exposure of the vulnerable populace in
      both developed and especially developing regions. Floods occur
      unexpectedly in some circumstances with little or no warning, and in other
      cases, aggravate rapidly, thereby leaving little time to plan, respond and
      recover. As such, hydrological data is needed before, during and after the
      flooding to ensure effective and integrated flood management. Though
      hydrological data collection in developed countries has been somewhat well
      established over long periods, the situation is different in the
      developing world. Developing regions are plagued with challenges that
      include inadequate ground monitoring networks attributed to deteriorating
      infrastructure, organizational deficiencies, lack of technical capacity,
      location inaccessibility and the huge financial implication of data
      collection at local and transboundary scales. These limitations,
      therefore, result in flawed flood management decisions and aggravate
      exposure of the most vulnerable people. Nigeria, the case study for this
      thesis, experienced unprecedented flooding in 2012 that led to the
      displacement of 3,871,53 persons, destruction of infrastructure,
      disruption of socio-economic activities valued at 16.9 billion US Dollars
      (1.4% GDP) and sadly the loss of 363 lives. This flood event revealed the
      weakness in the nation’s flood management system, which has been linked to
      poor data availability. This flood event motivated this study, which aims
      to assess these data gaps and explore alternative data sources and
      approaches, with the hope of improving flood management and decision
      making upon recurrence. This study adopts an integrated approach that
      applies open-access geospatial technology to curb data and financial
      limitations that hinder effective flood management in developing regions,
      to enhance disaster preparedness, response and recovery where resources
      are limited. To estimate flood magnitudes and return periods needed for
      planning purposes, the gaps in hydrological data that contribute to poor
      estimates and consequently ineffective flood management decisions for the
      Niger-South River Basin of Nigeria were filled using Radar Altimetry (RA)
      and Multiple Imputation (MI) approaches. This reduced uncertainty
      associated with missing data, especially at locations where virtual
      altimetry stations exist. This study revealed that the size and
      consistency of the gap within hydrological time series significantly
      influences the imputation approach to be adopted. Flood estimates derived
      from data filled using both RA and MI approaches were similar for
      consecutive gaps (1-3 years) in the time series, while wide
      (inconsecutive) gaps (&gt; 3 years) caused by gauging station
      discontinuity and damage benefited the most from the RA infilling
      approach. The 2012 flood event was also quantified as a 1-in-100year
      flood, suggesting that if flood management measures had been implemented
      based on this information, the impact of that event would have been
      considerably mitigated. Other than gaps within hydrological time series,
      in other cases hydrological data could be totally unavailable or limited
      in duration to enable satisfactory estimation of flood magnitudes and
      return periods, due to finance and logistical limitations in several
      developing and remote regions. In such cases, Regional Flood Frequency
      Analysis (RFFA) is recommended, to collate and leverage data from gauging
      stations in proximity to the area of interest. In this study, RFFA was
      implemented using the open-access International Centre for Integrated
      Water Resources Management–Regional Analysis of Frequency Tool (ICI-RAFT),
      which enables the inclusion of climate variability effect into flood
      frequency estimation at locations where the assumption of hydrological
      stationarity is not viable. The Madden-Julian Oscillation was identified
      as the dominant flood influencing climate mechanism, with its effect
      increasing with return period. Similar to other studies, climate
      variability inclusive regional flood estimates were less than those
      derived from direct techniques at various locations, and higher in others.
      Also, the maximum historical flood experienced in the region was less than
      the 1-in-100-year flood event recommended for flood management. The 2012
      flood in the Niger-South river basin of Nigeria was recreated in the
      CAESAR-LISFLOOD hydrodynamic model, combining open-access and third-party
      Digital Elevation Model (DEM), altimetry, bathymetry, aerial photo and
      hydrological data. The model was calibrated/validated in three sub-domains
      against in situ water level, overflight photos, Synthetic Aperture Radar
      (SAR) (TerraSAR-X, Radarsat2, CosmoSkyMed) and optical (MODIS) satellite
      images where available, to access model performance for a range of
      geomorphological and data variability. Improved data availability within
      constricted river channel areas resulted in better inundation extent and
      water level reconstruction, with the F-statistic reducing from 0.808 to
      0.187 downstream into the vegetation dominating delta where data
      unavailability is pronounced. Overflight photos helped improve the model
      to reality capture ratio in the vegetation dominated delta and highlighted
      the deficiencies in SAR data for delineating flooding in the delta.
      Furthermore, the 2012 flood was within the confine of a 1-in-100-year
      flood for the sub-domain with maximum data availability, suggesting that
      in retrospect the 2012 flood event could have been managed effectively if
      flood management plans were implemented based on a 1-in-100-year flood.
      During flooding, fast-paced response is required. However, logistical
      challenges can hinder access to remote areas to collect the necessary data
      needed to inform real-time decisions. Thus, this adopts an integrated
      approach that combines crowd-sourcing and MODIS flood maps for
      near-real-time monitoring during the peak flood season of 2015. The
      results highlighted the merits and demerits of both approaches, and
      demonstrate the need for an integrated approach that leverages the
      strength of both methods to enhance flood capture at macro and micro
      scales. Crowd-sourcing also provided an option for demographic and risk
      perception data collection, which was evaluated against a government risk
      perception map and revealed the weaknesses in the government flood models
      caused by sparse/coarse data application and model uncertainty. The C4.5
      decision tree algorithm was applied to integrate multiple open-access
      geospatial data to improve SAR image flood detection efficiency and the
      outputs were further applied in flood model validation. This approach
      resulted in F-Statistic improvement from 0.187 to 0.365 and reduced the
      CAESAR-LISFLOOD model overall bias from 3.432 to 0.699. Coarse data
      resolution, vegetation density, obsolete/non-existent river bathymetry,
      wetlands, ponds, uncontrolled dredging and illegal sand mining, were
      identified as the factors that contribute to flood model and map
      uncertainties in the delta region, hence the low accuracy depicted,
      despite the improvements that were achieved. Managing floods requires the
      coordination of efforts before, during and after flooding to ensure
      optimal mitigation in the event of an occurrence. In this study, and
      integrated flood modelling and mapping approach is undertaken, combining
      multiple open-access data using freely available tools to curb the effects
      of data and resources deficiency on hydrological, hydrodynamic and
      inundation mapping processes and outcomes in developing countries. This
      approach if adopted and implemented on a large-scale would improve flood
      preparedness, response and recovery in data sparse regions and ensure
      floods are managed sustainably with limited resources.