NWS's Flash Flood Warning and Disaster Preparedness Programs

Flash floods account for a large proportion of flood-based fatalities, and they are becoming more frequent due to climate change. A global flash flood warning system therefore has the potential to be life saving.Standard approaches to flash flood forecasting – such as the Flash Flood Guidance (FFG) system in the US National Weather Service (NWS), or the European Runoff Index based on Climatology (ERIC) in the European Flood Awareness System (EFAS) – are utilizing recent weather and soil conditions, physiographic characteristics of basins, and weather forecasts, in order to produce a forecast for possible flash floods. These forecasts are not disseminated directly to the public. Instead, they are firstly refined by hydrologists that have intimate knowledge of the relevant basins and of previous flood events. This introduces a difficulty to scaling these methods worldwide, as the training of professional hydrologists in every region is costly and time consuming.Recent applications of Machine Learning (ML) to hydrology show that a learning system has the potential to train on data-rich basins and generalize to data-poor basins, with a skill that is comparable to state of the art hydrological models. In this work we attempt to build a ML model to produce daily flash flood forecasts, based on globally available weather reanalysis and physiographic characteristics from HydroATLAS. We discuss the model architecture, and evaluate it against NWS Flash Flood Warnings (FFW). While such models may not surpass the skill of a professional hydrologist, they have the potential to provide reasonable warnings in regions that do not currently have any such system in place.

Flash floods have the potential to damage infrastructure and buildings, and pose a considerable threat to human life. The short lag times associated with flash floods (typically a few hours) present a significant challenge to existing flood warning systems. These systems currently rely on rainfall and runoff measurements, as well as hydrological models. Consequently, they are of limited applicability in ungauged catchments. This is a critical issue given that climate change is intensifying extreme rainfall and thereby increasing the potential for flash flooding.This study investigates the detection of flash floods based solely on rainfall characteristics, thus eliminating dependency on runoff measurements and hydrological infrastructure. Using high-resolution radar rainfall data and 15-minute runoff observations, 1,330 extreme rainfall-runoff events are selected across 147 German catchments with an area of up to 100 km². These events are subsequently classified as either flash or non-flash floods using a rainfall-runoff-based classification scheme as a reference, with 103 of the selected events identified as flash floods. For each event, various space-time rainfall characteristics are quantified. A random forest model for flash flood detection is then trained using only the rainfall metrics and static catchment attributes. The main aim is to assess the potential for rainfall-driven flash flood detection without relying on runoff. In addition, the most relevant rainfall characteristics associated with flash floods are identified, thereby improving our understanding of the underlying drivers.In future work, the developed detection approach will be combined with real-time rainfall nowcasting to enable earlier prediction and warning of flash floods.

National Oceanic and Atmospheric Administration's National Weather Service (NWS) flash flood warnings are issued by Weather Forecast Offices and are underpinned by information from the Flash Flood Guidance (FFG) system operated by the River Forecast Centers (RFCs). This study focuses on the quantitative evaluation and limitations of the FFG system using reported flash flood cases in 2010 and 2011. The flash flood reports were obtained from the NWS Storm Event database for the Arkansas‐Red Basin RFC (ABRFC). The current FFG system at the ABRFC provides gridded flash flood guidance (GFFG) system using the NWS Hydrology Laboratory‐Research Distributed Hydrologic Model to translate the upper zone soil moisture to estimates of Soil Conservation Service Curve Numbers. Comparisons of the GFFG and real‐time Multisensor Precipitation Estimator‐derived Quantitative Precipitation Estimate for the same duration and location were used to analyze the success of the system. Typically, the six‐hour duration was characterized by higher probability of detection values than the three‐hour duration, which highlights the difficulty of hydrologic process estimation for shorter time scales. The current system does not take into account physical characteristics such as land use, including irrigated agricultural farm and urban areas, hence, overly dry soil moisture estimates over these areas can lower the success rate of the GFFG product.

Quantifying uncertainty associated with flash flood warning or forecast systems is required to enable informed decision making by those responsible for operation and management of natural hazard protection systems. The current system used by the U.S. National Weather Service (NWS) to issue flash-flood warnings and watches over the Unites States is a purely deterministic system. The authors propose a simple approach to augment the Flash Flood Guidance System (FFGS) with uncertainty propagation components. The authors briefly discuss the main components of the system, propose changes to improve it, and allow accounting for several sources of uncertainty. They illustrate their discussion with examples of uncertainty quantification procedures for several small basins of the Illinois River basin in Oklahoma. As the current FFGS is tightly coupled with two technologies, that is, threshold-runoff mapping and the Sacramento Soil Moisture Accounting Hydrologic Model, the authors discuss both as sources of uncertainty. To quantify and propagate those sources of uncertainty throughout the system, they develop a simple version of the Sacramento model and use Monte Carlo simulation to study several uncertainty scenarios. The results point out the significance of the stream characteristics such as top width and the hydraulic depth on the overall uncertainty of the Flash Flood Guidance System. They also show that the overall flash flood guidance uncertainty is higher under drier initial soil moisture conditions. The results presented herein, although limited, are a necessary first step toward the development of probabilistic operational flash flood guidance forecast-response systems.

In recent years, due to various factors such as extreme weather, complex underlying surfaces, and human activities, the trend of flash floods has become frequent and prone to occur, and their threat level and social impact are increasing day by day. This article is based on the theory of natural disaster risk theory and GIS technology, and comprehensively evaluates the risk factors of small watershed flash floods, the sensitivity of prone environments, and the vulnerability of disaster bearing bodies. This article takes Longquan City as a typical research area, selects 10 core indicators to construct a flash flood disaster risk assessment system, and verifies it using historical flash flood disaster information. The results indicate that the risk assessment of flash flood disasters based on small watersheds has good consistency and consistency with historical flash flood disaster information in the study area. The risk identification results are reliable, and the risk assessment model can accurately reflect the risk of regional flash flood disasters.

Huamual District which is located in west peninsula of Seram Island within Ambon Province is one of the under developed areas since its remote location and limited transport facilities from its regency capital and other developed areas. Therefore, the development program for that area needs to be boasted and secured. One of drawback of the economic development growth in Huamual District caused by current frequent flash flood disaster occurrences. Therefore, disaster resilient of both the local government and communities need to be strengthened. The Provincial Disaster Mitigation Agency of Maluku points that Huamual District was the most severe hit area by flash flood in Maluku beside Ambon City areas in 1^(st) August 2012. In order to prepare a program for increasing disaster resilient in that area, investigation of the disaster risk condition along the west coast of Huamual Peninsula within Huamual District has been conducted and reported in this paper. Reference study has been conducted followed by a field survey in the period of July 14^(th) to July 19^(th) 2014. The field survey was conducted on several sub-villages such as Nasiri, Mange-mange, Amaholu Losi, and Hatawano. The activities in the field survey were secondary data collection, interview to Local Disaster Management Agency (BPBD) of West Seram Regency staffs, to sub-village leaders, to local community members, visual observation survey and river bed material sampling. This paper discusses disaster risk aspect found in the areas which consists of hazard, vulnerability, capacity and also mitigation aspect which consists of pre-disaster, disaster response and recovery phases. The results of this study are the following six findings. 1) The flash flood is the main cause of the natural disaster beside landslide. 2) Although the community settled in the prone area, they do not have knowledge about disaster mitigation but now, they are more aware. 3) BPBD in West Seram Regency has no yearly program related to capacity building, standard operating procedure, and disaster mitigation plan due to limited budget on local government budget and limited employee although 2 years of its establishment. 4) There is no community preparedness dealing with any kind of natural disaster except for their experiences in facing the past disaster. 5) The community still relies on their own members when facing any disaster response. 6) In recovering their sub-village condition the community relies on gotong royong spirit an Indonesian indigenous spirit of working together and also on their own resources.

The intensification of global climate change, the increase in extreme weather, and the frequent occurrence of heavy rains have led to frequent flash flood disasters. The flash floods] is fast, the time of convergence is short, and the destructive power is strong, making it difficult to predict prevention, which poses a huge threat to the lives and property of the people living in the hilly areas. Therefore, it is extremely urgent to carry out flash flood disaster prevention and early warning. Taking the three natural villages in Luoning County of Henan Province as an example, we carried out the determination of early warning period of flash flood disaster and calculation of early warning index. The research results can provide scientific support for local flash flood disaster warning work and reduce the loss of people and property caused by flash flood disasters.

In recent years, disasters caused by flash floods with many casualties have occurred frequently in China. In order to effectively prevent flash flood disasters, the State Council approved the National Flash Flood Control Planning (NFFCP) in 2006. In this planning, non-structural measures are recommended as the first step to be adopted in the prevention of flash floods, debris flow and landslide disasters caused by heavy rainfall. In order to effectively build up a comprehensive non-structural measure system for flash flood disaster prevention, the Ministry of Water Resources has asked the local authorities to conduct studies in 103 pilot counties aiming to explore practical schemes. Based on the experience from these pilot counties, the construction of non-structural measures on flash flood disaster prevention for 1836 counties was officially initiated in 2010. The contents of non-structural measures for flash flood disaster prevention at county level include eight aspects. This paper will systematically illustrate the main contents of this national project for the construction of non-structural measures for flash flood disaster prevention in China. This work could provide a reference for other countries and regions in terms of flash flood prevention.

Flash floods is a sudden flood disaster that can be triggered by several factors, one of which is the landslides that occur in river basins. In Bogor Regency, there are fourteen sub-districts located in the Upper Cisadane watershed area that are prone to flash flood disaster. This study aims to determine social, economic, physical and environmental vulnerability assessment of the community in the Upper Cisadane watershed area based on the modification assessment from PERKA BNPB No. 12 Tahun 2012. According to the vulnerability index, the Upper Cisadane watershed has high and very high classes of flash floods vulnerability. Sub-districts with high vulnerability index class are Nanggung, Pamijahan, West Bogor, South Bogor, Central Bogor, East Bogor, Cibungbulang, Cigudeg, Leuwisadeng, and Sukajaya, meanwhile, sub-districts with very high vulnerability index are Caringin, Ciampea, Ciawi, Cigombong, Cijeruk, Ciomas, Dramaga, Kemang, Leuwiliang, Megamendung, Rancabungur, Rumpin, Tamansari, and Tenjolaya.

The Beringin watershed is one of the watersheds (DAS) located in Semarang, Central Java, Indonesia. During 2010 – 2017 in this watershed area, there have been 8 flood disasters, the last two of which changed from an inundation flood to a flash flood type. The objective of this research is to investigate the characteristics of the rivers or the morphology of the watershed by 1) creating a three-dimensional spatial model of the Beringin watershed and describing its physical profiles and shapes, 2) arranging a satellite imagery map of the settlement at risk of flash flood disaster surrounding the watershed, 3) mapping the morphometric of the watershed, which consists of the landslide potential, the narrowing of river bodies and calculating the peak discharge in order to get the trigger factor of the flash flood, and 4) mapping the vulnerability of the Beringin watershed to minimize the flash flood disaster risk. The research method conducted was a combination of qualitative and quantitative approaches. Clearly, that the output of this research will contribute to the conservation of the Beringin watershed whose outcome is the reduction of the flash flood disaster risk affecting the communities surrounding the Beringin watershed.

The objective of this research is (1) to raise awareness and prepare for flash flooding among people in the Mekong region which promotes inequality reduction from disasters by using Muang Nong Khai District, Nong Khai Province as a model area, and (2) To develop a policy proposal by designing a joint policy for flash flood preparedness in the Mekong region to promote inequality reduction from disasters. This research is action research in conjunction with policy design focusing on brainstorming. Group discussions with in-depth interviews. The research results were found that: [A] People have a basic understanding of (1) the nature of the disaster, and (2) the experience of the flash flood disaster encountered by the WiangKhuk Sub-district people is about remembering the severity Looking at the floods that have been associated, but in terms of preparation, community leaders see together that they want to develop into a system and plan for a joint rehearsal in the future. [B] Flash flood response weaknesses are (1) Weaknesses for early warning, evacuation, and flash flood drills, (2) Weaknesses of flash flood plans for areas that have not yet been formally planned, And (3) weaknesses in communication. [C] The interesting common policy design guidelines that should be developed are (1) Flash flood knowledge development, (2) direction and coordination for emergency operations, (3) agreements that Formal and informal for flash flood response, (4) resource mobilization focused on the certainty of emergency work. [D] The policy recommendations are: (1) Appropriate policy guidelines for flash flood preparedness in the Mekong River Basin should include precautions, evacuation, flash flood drills, and community-level plans to tackle flash floods. (2) The public sector, civil society, and communities should jointly develop policies to prepare for flash floods, that is, to develop flash flood knowledge to keep up with the changing circumstances of the local context. (3) The key policy to deal with flash floods to help reduce inequality is to develop community capacity or community potential. This is a collaboration of community organizations, the government sector, civil society in the area, which together with driving a community-level response plan. [E] The operation recommendations include (1) the community must be the host to invite government organizations such as the Provincial Disaster Prevention and Mitigation and the Mekong Community Organization Council to drive community-level planning. (2) Organizing a network meeting on flash flood response such as communities, Provincial Disaster Prevention and Mitigation Agency, and Mekong Community Organization Council should hold meetings at least twice a year to understand the situation and implement measures to deal with flash floods in a timely manner. (3) Flash flood drills should be conducted at least once a year in order to build mutual learning among communities and networks in flash flood preparedness, it is also an analysis of the weaknesses each year and can be used to develop the capacity and capacity of the community to handle the flash flood in the future.

This study quantifies the skill of the National Weather Service’s (NWS) flash flood guidance (FFG) product. Generated by River Forecast Centers (RFCs) across the United States, local NWS Weather Forecast Offices compare estimated and forecast rainfall to FFG to monitor and assess flash flooding potential. A national flash flood observation database consisting of reports in the NWS publication Storm Data and U.S. Geological Survey (USGS) stream gauge measurements are used to determine the skill of FFG over a 4-yr period. FFG skill is calculated at several different precipitation-to-FFG ratios for both observation datasets. Although a ratio of 1.0 nominally indicates a potential flash flooding event, this study finds that FFG can be more skillful when ratios other than 1.0 are considered. When the entire continental United States is considered, the highest observed critical success index (CSI) with 1-h FFG is 0.20 for the USGS dataset, which should be considered a benchmark for future research that seeks to improve, modify, or replace the current FFG system. Regional benchmarks of FFG skill are also determined on an RFC-by-RFC basis. When evaluated against Storm Data reports, the regional skill of FFG ranges from 0.00 to 0.19. When evaluated against USGS stream gauge measurements, the regional skill of FFG ranges from 0.00 to 0.44.

Floods are one of the most devastating natural hazards around the world, and flash floods are extremely dangerous to property and human lives. This study reviews the current flash flood forecasting in China and proposes a new methodology to develop a flash flood potential index (FFPI) based on GIS to further improve China's flash flood guidance system and national weather forecasting services. We collected datasets required to calculate the FFPI and tested a series of schemes to determine the method to calculate the FFPI over China. The result indicates that the calculated China's FFPI distribution can represent the risk of flash flood well, especially in Central and Southeast China. It is also implied that the southwest and western complex terrains are more susceptible to rain storms. Then we chose Yunnan Province as a test-bed and also yielded good results which can offer reference to the current China's flash flood forecasting system. Further research can be placed on incorporation of soil moisture and rainfall frequency components into the FFPI calculation method for dynamic warning and forecasting of flash floods.

Flash flood mitigation: recommendations for research and applications

Small islands have been identified as regions that exhibit susceptibility to natural disasters and the impacts of climate change. This arises from a multitude of constraints, such as limited size, geographical isolation, high population density, closeness to the ocean, and reliance on natural resources. The recurrent flash flood calamities on Ternate Island underscore the deficiencies in disaster management strategies for smaller islands. It is imperative to enhance disaster management on small islands, particularly in light of the anticipated escalation in the severity of disasters in the future. This study examines the underlying factors contributing to the flash floods in Rua Village, Ternate Island, as well as assessing the effectiveness of disaster management strategies implemented on Ternate Island. Through the application of both qualitative and quantitative research methodologies, we meticulously examined the gathered data and represented it in a thematic map. The findings of the study indicated that elements such as precipitation, topography, and river dynamics, along with the properties of rock composition, soil stability, and soil movement characteristics, contribute to the occurrence of flash floods in Rua Village. Moreover, inadequate disaster management challenges all stakeholders in Ternate who are striving to establish a resilient society to disasters.