Marian Muste and Ton Hoitink
With a continuous global increase in flood frequency and intensity, there is an immediate need for new science-based solutions for flood mitigation, resilience, and adaptation that can be quickly deployed in any flood-prone area. An integral part of these solutions is the availability of river discharge measurements delivered in real time with high spatiotemporal density and over large-scale areas. Stream stages and the associated discharges are the most perceivable variables of the water cycle and the ones that eventually determine the levels of hazard during floods. Consequently, the availability of discharge records (a.k.a. streamflows) is paramount for flood-risk management because they provide actionable information for organizing the activities before, during, and after floods, and they supply the data for planning and designing floodplain infrastructure. Moreover, the discharge records represent the ground-truth data for developing and continuously improving the accuracy of the hydrologic models used for forecasting streamflows. Acquiring discharge data for streams is critically important not only for flood forecasting and monitoring but also for many other practical uses, such as monitoring water abstractions for supporting decisions in various socioeconomic activities (from agriculture to industry, transportation, and recreation) and for ensuring healthy ecological flows. All these activities require knowledge of past, current, and future flows in rivers and streams.
Given its importance, an ability to measure the flow in channels has preoccupied water users for millennia. Starting with the simplest volumetric methods to estimate flows, the measurement of discharge has evolved through continued innovation to sophisticated methods so that today we can continuously acquire and communicate the data in real time. There is no essential difference between the instruments and methods used to acquire streamflow data during normal conditions versus during floods. The measurements during floods are, however, complex, hazardous, and of limited accuracy compared with those acquired during normal flows. The essential differences in the configuration and operation of the instruments and methods for discharge estimation stem from the type of measurements they acquire—that is, discrete and autonomous measurements (i.e., measurements that can be taken any time any place) and those acquired continuously (i.e., estimates based on indirect methods developed for fixed locations). Regardless of the measurement situation and approach, the main concern of the data providers for flooding (as well as for other areas of water resource management) is the timely delivery of accurate discharge data at flood-prone locations across river basins.
Jonathan J. Gourley and Robert A. Clark III
Flash floods are one of the world’s deadliest and costliest weather-related natural hazards. In the United States alone, they account for an average of approximately 80 fatalities per year. Damages to crops and infrastructure are particularly costly. In 2015 alone, flash floods accounted for over $2 billion of losses; this was nearly half the total cost of damage caused by all weather hazards. Flash floods can be either pluvial or fluvial, but their occurrence is primarily driven by intense rainfall. Predicting the specific locations and times of flash floods requires a multidisciplinary approach because the severity of the impact depends on meteorological factors, surface hydrologic preconditions and controls, spatial patterns of sensitive infrastructure, and the dynamics describing how society is using or occupying the infrastructure.
Real-time flash flood forecasting systems rely on the observations and/or forecasts of rainfall, preexisting soil moisture and river-stage states, and geomorphological characteristics of the land surface and subsurface. The design of the forecast systems varies across the world in terms of their forcing, methodology, forecast horizon, and temporal and spatial scales. Their diversity can be attributed at least partially to the availability of observing systems and numerical weather prediction models that provide information at relevant scales regarding the location, timing, and severity of impending flash floods. In the United States, the National Weather Service (NWS) has relied upon the flash flood guidance (FFG) approach for decades. This is an inverse method in which a hydrologic model is run under differing rainfall scenarios until flooding conditions are reached. Forecasters then monitor observations and forecasts of rainfall and issue warnings to the public and local emergency management communities when the rainfall amounts approach or exceed FFG thresholds. This technique has been expanded to other countries throughout the world. Another approach, used in Europe, relies on model forecasts of heavy rainfall, where anomalous conditions are identified through comparison of the forecast cumulative rainfall (in space and time) with a 20-year archive of prior forecasts. Finally, explicit forecasts of flash flooding are generated in real time across the United States based on estimates of rainfall from a national network of weather radar systems.
Recent extreme hydrological events (e.g., in the United States in 2005 or 2012, Pakistan in 2010, and Thailand in 2011) revealed increasing flood risks due to climate and societal change. Consequently, the roles of multiple stakeholders in flood risk management have transformed significantly. A central aspect here is the question of sharing responsibilities among global, national, regional, and local stakeholders in organizing flood risk management of all kinds. This new policy agenda of sharing responsibilities strives to delegate responsibilities and costs from the central government to local authorities, and from public administration to private citizens. The main reasons for this decentralization are that local authorities can deal more efficiently with public administration tasks concerned with risks and emergency management. Resulting locally based strategies for risk reduction are expected to tighten the feedback loops between complex environmental dynamics and human decision-making processes. However, there are a series of consequences to this rescaling process in flood risk management, regarding the development of new governance structures and institutions, like resilience teams or flood action groups in the United Kingdom. Additionally, downscaling to local-level tasks without additional resources is particularly challenging. This development has tightened further with fiscal and administrative cuts around the world resulting from the global economic crisis of 2007–2008, which tightening eventually causes budget restrictions for flood risk management. Managing local risks easily exceeds the technical and budgetary capacities of municipal institutions, and individual citizens struggle to carry the full responsibility of flood protection. To manage community engagement in flood risk management, emphasis should be given to the development of multi-level governance structures, so that multiple stakeholders share fairly the power, resources, and responsibility in disaster planning. If we fail to do so, some consequences would be: (1), “hollowing out” the government, including the downscaling of the responsibility towards local stakeholders; and (2), inability of the government to deal with the new tasks due to lack of resources transferred to local authorities.