Global flood risk models were developed to identify risk hotspots in a world with increasing flood occurrence. Here we assess the ability and limitations of the current models and suggest what is needed moving forward. Table 1 | Links to models, tools, and programmes discussed in the text.

SummaryBackgroundPredicting when and where pathogens will emerge is difficult, yet, as shown by the recent Ebola and Zika epidemics, effective and timely responses are key. It is therefore crucial to transition from reactive to proactive responses for these pathogens. To better identify priorities for outbreak mitigation and prevention, we developed a cohesive framework combining disparate methods and data sources, and assessed subnational pandemic potential for four viral haemorrhagic fevers in Africa, Crimean–Congo haemorrhagic fever, Ebola virus disease, Lassa fever, and Marburg virus disease.MethodsIn this multistage analysis, we quantified three stages underlying the potential of widespread viral haemorrhagic fever epidemics. Environmental suitability maps were used to define stage 1, index-case potential, which assesses populations at risk of infection due to spillover from zoonotic hosts or vectors, identifying where index cases could present. Stage 2, outbreak potential, iterates upon an existing framework, the Index for Risk Management, to measure potential for secondary spread in people within specific communities. For stage 3, epidemic potential, we combined local and international scale connectivity assessments with stage 2 to evaluate possible spread of local outbreaks nationally, regionally, and internationally.FindingsWe found epidemic potential to vary within Africa, with regions where viral haemorrhagic fever outbreaks have previously occurred (eg, western Africa) and areas currently considered non-endemic (eg, Cameroon and Ethiopia) both ranking highly. Tracking transitions between stages showed how an index case can escalate into a widespread epidemic in the absence of intervention (eg, Nigeria and Guinea). Our analysis showed Chad, Somalia, and South Sudan to be highly susceptible to any outbreak at subnational levels.InterpretationOur analysis provides a unified assessment of potential epidemic trajectories, with the aim of allowing national and international agencies to pre-emptively evaluate needs and target resources. Within each country, our framework identifies at-risk subnational locations in which to improve surveillance, diagnostic capabilities, and health systems in parallel with the design of policies for optimal responses at each stage. In conjunction with pandemic preparedness activities, assessments such as ours can identify regions where needs and provisions do not align, and thus should be targeted for future strengthening and support.FundingPaul G Allen Family Foundation, Bill & Melinda Gates Foundation, Wellcome Trust, UK Department for International Development.

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Recent discharge observations are lacking for most rivers globally. Discharge can be estimated from remotely sensed floodplain and channel inundation area, but there is currently no method that can be automatically extended to many rivers. We examined whether automated monitoring is feasible by statistically relating inundation estimates from moderate to coarse (>0.058) resolution remote sensing to monthly station discharge records. Inundation extents were derived from optical MODIS data and passive microwave sensors, and compared to monthly discharge records from over 8000 gauging stations and satellite altimetry observations for 442 reaches of large rivers. An automated statistical method selected grid cells to construct ''satellite gauging reaches'' (SGRs). MODIS SGRs were generally more accurate than passive microwave SGRs, but there were complementary strengths. The rivers widely varied in size, regime, and morphology. As expected performance was low (R < 0.7) for many (86%), often small or regulated, rivers, but 1263 successful SGRs remained. High monthly discharge variability enhanced performance: a standard deviation of 100-1000 m 3 s 21 yielded ca. 50% chance of R > 0.6. The best results (R > 0.9) were obtained for large unregulated lowland rivers, particularly in tropical and boreal regions. Relatively poor results were obtained in arid regions, where flow pulses are few and recede rapidly, and in temperate regions, where many rivers are modified and contained. Provided discharge variations produce clear changes in inundated area and gauge records are available for part of the satellite record, SGRs can retrieve monthly river discharge values back to around 1998 and up to present. Key Points:Automated method to locate and construct satellite gauging reaches Valuable to gap-fill and extend monthly station discharge records Satellite river discharge gauging is currently feasible for many rivers globally (2016), River gauging at global scale using optical and passive microwave remote sensing, Water Resour. Res., 52, 6404-6418,

Space-based river monitoring can provide a systematic, global, timely and impartial way to monitor disastrous floods. This paper describes a methodology to use daily passive microwave observations to detect, map and size floods, both for the purposes of global humanitarian organizations and national hydrological services. In the best case, floods can be detected as early as 2 h after they occur. Early warning is possible by monitoring upstream areas, with warning lead times up to 30 days. Flood maps are of a low resolution but match maps derived from high-resolution imagery. The interest lies in their daily availability, allowing us to understand the dynamic aspects of floods. Finally, objective flood sizing is achieved by integrating information over time and space. This paper details the results of the technique for the 2009 floods in Southern Africa and experiences for the 2010 flood season in Namibia.

Early flood warning and real-time monitoring systems play a key role in flood risk reduction and disaster response decisions. Global-scale flood forecasting and satellite-based flood detection systems are currently operating, however their reliability for decision-making applications needs to be assessed. In this study, we performed comparative evaluations of several operational global flood forecasting and flood detection systems, using 10 major flood events recorded over 2012-2014. Specifically, we evaluated the spatial extent and temporal characteristics of flood detections from the Global Flood Detection System (GFDS) and the Global Flood Awareness System (GloFAS). Furthermore, we compared the GFDS flood maps with those from NASA's two Moderate Resolution Imaging Spectroradiometer (MODIS) sensors. Results reveal that: (1) general agreement was found between the GFDS and MODIS flood detection systems, (2) large differences exist in the spatio-temporal characteristics of the GFDS detections and GloFAS forecasts, and (3) the quantitative validation of global flood disasters in data-sparse regions is highly challenging. OPEN ACCESSRemote Sens. 2015, 7 15703Overall, satellite remote sensing provides useful near real-time flood information that can be useful for risk management. We highlight the known limitations of global flood detection and forecasting systems, and propose ways forward to improve the reliability of large-scale flood monitoring tools.

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