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• Exploring the urban inundation response law based on designed rainstorms by coupled hydrodynamic and rainfall-tracking model. • Source tracking analysis method is novelty proposed to excavate the response law of the connectivity among source areas to characteristics of rainstorms. • The analysis of source areas contribution further illustrates the reason why the study area would undergo inundation damage when the precipitation exceeds 100 mm. • The study is helpful to further understand the response law of inundation and relationship among source areas to characteristics of rainstorms, provide novel insights for constructing integrated flooding intervention practices. Extreme stormwater and high-impervious area, caused by climate change and high-urbanization, are widely considered as the essential factors for causing urban flood. Understanding the response law of urban inundation to characteristics of rainstorms is helpful to implement integrated flood mitigation measures. Therefore, this paper is focused on exploring the urban inundation response law based on designed rainstorms by coupled hydrodynamic and rainfall-tracking model. Pilot area of Guyuan sponge city, which is divided into 5 source areas, is adopted to conduct 36 types of rainfall scenario simulations with the combination of different rainfall amounts and durations as well as peak coefficients. Inundation analysis methods is used to obtain the relationship between maximum inundation maps and characteristics of rainstorms, and source tracking analysis method is novelty proposed to excavate the response law of the connectivity among source areas to characteristics of rainstorms. First, Results of inundation analysis reveal that rainfall amount, duration and peak value are the first, second and third critical rainstorm characteristics that determine the severity of disasters, the variation of inundation volume are 140 %, 30 % and 4.2 % when precipitation and duration as well as peak value double. Second, the inundation area that water depth more than 0.5 m increases quickly is the major reason that inundation volume varies with 2 times as the increasing of precipitation; the transferring runoff volume between source areas and land use reaches 0–6 % and 0–10 % of inundation volume. Third, SA 1 and 2 are the critical sub-areas to manage the runoff, when precipitation equals to 200 mm, SA 1 contributes 19.5–33.7 % of inundation volume in SA 2, and SA 2 contributes 28–30 % of inundation volume in SA 3. The study is helpful to further understand the response law of inundation and relationship among source areas to characteristics of rainstorms, provide novel insights for constructing integrated flooding intervention practices. [ABSTRACT FROM AUTHOR]

• A review of challenges and advances in flood design under non-stationarity. • Sources of non-stationarity in hydrologic extremes are described. • Methods for design flood estimates assuming stationarity are discussed. • Methods assuming climate change induced non-stationarity are discussed. • Strategies to manage uncertainties and their consequences are discussed. Conventional methods for designing infrastructure that is subject to flood risk, such as dams and levees, assume a stationary design flood. However, observed and potential non-stationarity in floods can result in costly over-design or dangerous under-design. Despite substantial attention, evidence from the literature makes clear there is no consensus methodology for estimating design variables under climate change. Practical guidance remains elusive. This paper presents a review of the challenges and advances in design of infrastructure for floods under non-stationarity. First, potential sources of non-stationarity in time series of floods are described to provide context and motivation. Second, methods for estimating design floods that rely on the stationary assumption are presented and their limitations are discussed. Third, methods for estimating design floods that assume non-stationarity resulting from climate change are summarized. Finally, the inadequacies of current design methodologies in view of the pervasive uncertainties are assessed and strategies to manage the consequences of those uncertainties are presented. [ABSTRACT FROM AUTHOR]

Climate change will affect precipitation and flood regimes. It is anticipated that the Probable Maximum Precipitation (PMP) and Probable Maximum Flood (PMF) will be modified in a changing climate. This paper aims to quantify and analyze climate change influences on PMP and PMF in three watersheds with different climatic conditions across the province of Québec, Canada. Output data from the Canadian Regional Climate Model (CRCM) was used to estimate PMP and Probable Maximum Snow Accumulation (PMSA) in future climate projections, which was then used to force the SWAT hydrological model to estimate PMF. PMP and PMF values were estimated for two time horizons each spanning 30 years: 1961–1990 (recent past) and 2041–2070 (future). PMP and PMF were separately analyzed for two seasons: summer-fall and spring. Results show that PMF in the watershed located in southern Québec would remain unchanged in the future horizon, but the trend for the watersheds located in the northeastern and northern areas of the province is an increase of up to 11%. [ABSTRACT FROM AUTHOR]

• Future rainfall and sea level rise are predicted. • Impact of sea level rise and future rainfall change on compound flooding is assessed. • Changes in depth, extent, and duration of floods under climate change are analyzed. Flood disasters in coastal cities are generally caused by the combined effect of typhoon rainfall, storm surge and other factors. Coastal cities will face more severe compound flooding under climate change. Although some studies have analyzed compound flooding under climate change, there is a lack of research considering the combined effect of sea level rise (SLR) and future rainfall changes, especially lack of the jacking effect of SLR on the volume and duration of compound flooding. This paper investigates the impact of future rainfall changes and SLR on compound flood risk, via a case study of a coastal city, Haikou, China. Future rainfall in Haikou is obtained by bias correction of rainfall from five global climate models (GCMs) in CMIP5. The SLR in 2050 and 2090 is predicted according to IPCC. Then, a 1D/2D hydrological-hydrodynamic model for dynamic simulation of surface runoff is applied to simulate compound flooding. Results show that both future rainfall changes and SLR will lead to the increase of flood extent, flood depth and flood duration. But future rainfall changes will have a greater impact on flood, and the combined effect of future rainfall changes and SLR on flood is greater than the sum of their individual effects. The individual effects of SLR and future rainfall changes would increase flood depth in 10.6 % and 32.1 % of the study area, respectively, while their combined effect would increase this proportion to 34.9 %. Also, the jacking effect of SLR on compound flooding will lead to an increase in flood volume, but it presents a nonlinear relationship that gradually slows down with the increase of SLR. A SLR of 0.3 m and 0.63 m will lead to a 2.34 % and 3.22 % increase in flood volume, respectively. And the jacking effect of SLR is more obvious when future rainfall changes are considered, which will lead to a sharp increase in the duration of compound flooding. Moreover, water storage facilities and tidal gates are effective ways to reduce the impact of climate change on compound flooding. [ABSTRACT FROM AUTHOR]

Recently developed methodologies such as climate reanalysis make it possible to create a historical record of climate systems. This paper proposes a methodology called Hydrological Retrospective (HR), which essentially simulates large rainfall datasets, using this as input into hydrological models to develop a record of past hydrology, making it possible to analyze past floods and droughts. We developed a methodology for the Amazon basin, where studies have shown an increase in the intensity and frequency of hydrological extreme events in recent decades. We used eight large precipitation datasets (more than 30 years) as input for a large scale hydrological and hydrodynamic model (MGB-IPH). HR products were then validated against several in situ discharge gauges controlling the main Amazon sub-basins, focusing on maximum and minimum events. For the most accurate HR, based on performance metrics, we performed a forecast skill of HR to detect floods and droughts, comparing the results with in-situ observations. A statistical temporal series trend was performed for intensity of seasonal floods and droughts in the entire Amazon basin. Results indicate that HR could represent most past extreme events well, compared with in-situ observed data, and was consistent with many events reported in literature. Because of their flow duration, some minor regional events were not reported in literature but were captured by HR. To represent past regional hydrology and seasonal hydrological extreme events, we believe it is feasible to use some large precipitation datasets such as i) climate reanalysis, which is mainly based on a land surface component, and ii) datasets based on merged products. A significant upward trend in intensity was seen in maximum annual discharge (related to floods) in western and northwestern regions and for minimum annual discharge (related to droughts) in south and central-south regions of the Amazon basin. Because of the global coverage of rainfall datasets, this methodology can be transferred to other regions for better estimation of future hydrological behavior and its impact on society. [ABSTRACT FROM AUTHOR]

• Adverse impacts of sea-level rises are not limited to a landward shift in shoreline. • Shallow groundwater can impact inland infrastructure kilometers from the coastline. • About 2/3 of the stormdrain length is subject to seawater & groundwater intrusion. • Coastal stressors can increase flood magnitude, frequency, and duration. • Compound flooding volume increases up to 6 times by a 2 m sea-level rise. Low-lying coastal areas are susceptible to multiple types of flooding from marine, subsurface, and surface sources. The co-occurrence of a rainfall event with high sea level, which raises coastal groundwater tables conjointly, may result in a compound flooding event, which could be much more widespread and dangerous than that of an individual flooding source. Focusing on Imperial Beach as a low-elevation coastal community in California, this paper provides a generalized methodology to determine the vulnerability of coastal stormdrain systems to compound seawater, groundwater, and stormwater flooding under a changing climate. Although marine inundation by itself is expected to flood only 7% of the study area by 2100 under the most pessimistic scenario (i.e. 2 m rise), our results show that more than 20% of the study area's subterranean stormdrain system is already at the risk of subsurface flooding at current sea levels. While marine inundation is a concern near the coastline as sea level rises, the results show that seawater intrusion into the stormdrain system can impact areas kilometers away from the coastline. The consequences of sea-level rise (SLR) can be exacerbated by an under-resourced stormdrain system, caused by groundwater infiltration through system defects. As such, by a 2 m rise in current sea-level, the flooding volume may double in an ideal system (i.e., no defects) while this ratio can increase six fold in a slightly defective stormdrain system (with 0.25 % porosity systemwide). The continuous simulations of the stormdrain system performance indicate that flood events will be more destructive and frequent under these circumstances. [ABSTRACT FROM AUTHOR]

• A novel method for assessing prediction of extremal hydrological events. • Bayesian causal modelling tool for predictive assessment. • Hybridization of Classical and new Hydrology based on Artificial Intelligence. • HydroPredicT_Extreme as a new tool for the prediction of potential flooding events. • Applicability to different time scales of extreme and sudden events. Disastrous losses related to high-flow events have increased dramatically over the past decades largely due to an increase in flood-prone regions settlements and shift in hydrological trends largely due to Climate Change. To mitigate the societal impact of hydrological and hydraulic extremes, knowledge of the processes leading to these extreme events is vital. Hydrological modelling is one of the main tools in this quest for knowledge but comes with uncertainties. For that it is necessary to deeply study the impact of hydrological models' structure on the magnitude and timing of extreme rainfall-runoff events. This paper is mainly aimed to show the development of a method called "HydroPredicT_Extreme" based on Bayesian Causal Modelling (BCM), a technique within Artificial Intelligence (AI). This method may enhance predictive capacity of extreme rainfall-runoff events. "HydroPredicT_Extreme" follows an iterative methodology that comprise 2 main stages. First one comprises a mixed graphical/analytical method from Hydrograph. This stage is conditioned by two initial constraints which are, a) pluviometry station is representative of hydrograph downstream flow behaviour; b) there must be independence of events. This first stage comprises sub-phases such as: 1.1. Calculation of Response Time (RT) through a mixed graphical/analytical approach, 1.2 Subtraction of RT from the flow series to remove the Rainfall-Flow delay; 1.3 Calculation base flow rate; 1.4 Subtraction base-flow from flow series to work on absolute inputs. Second man stage is called Bayesian Causal Modelling Translation (BCMT) that comprises the 2.1 Learning, 2.2 Training, 2.3 Simulation through BCM modelling, 2.4 Sensitivity Analysis-Validation. This whole methodology will become a digital application and software that could be extrapolated to several similar case studies. This may be coupled with posterior devices for the prevention of catastrophic flood consequences in the form of MultiHazard-Early Warning System (MH-EWS) or others. [ABSTRACT FROM AUTHOR]

Summary Floodplain wetlands and their hydrological connectivity with main river channels in the Australian wet–dry tropics are under increasing pressure from global climate change and water resource development, and there is a need for modelling tools to estimate the time dynamics of connectivity. This paper describes an integrated modelling framework combining conceptual rainfall–runoff modelling, river system modelling and hydrodynamic (HD) modelling to estimate hydrological connectivity between wetlands and rivers in the Flinders and Gilbert river catchments in northern Australia. Three historical flood events ranging from a mean annual flood to a 35-year return period flood were investigated using a two dimensional HD model (MIKE 21). Inflows from upstream catchments were estimated using a river network model. Local runoff within the HD modelling domain was simulated using the Sacramento rainfall–runoff model. The Shuttle Radar Topography Mission (SRTM) derived 30 m DEM was used to reproduce floodplain topography, stream networks and wetlands in the HD model. The HD model was calibrated using stream gauge data and inundation maps derived from satellite (MODIS: MODerate resolution Imaging Spectroradiometer) imagery. An algorithm was developed to combine the simulated water heights with the DEM to quantify inundation and flow connection between wetlands and rivers. The connectivity of 18 ecologically important wetlands on the Flinders floodplain and 7 on the Gilbert floodplain were quantified. The impacts of climate change and water resource development on connectivity to individual wetlands were assessed under a projected dry climate (2nd driest of 15 GCMs), wet climate (2nd wettest of 15 GCMs) and dam conditions. The results indicate that changes in rainfall under a wetter and drier future climate could have large impacts on area, duration and frequency of inundation and connectivity. Topographic relief, river bank elevation and flood magnitude were found to be the key factors contributing to the level of connectivity. Under a wetter future climate the average duration of connection of wetlands to the main river channel increased by 7% and under a drier climate it decreased by 18%. Construction of a 248 GL dam in the Flinders catchment and two (498 and 271 GL capacity) in the Gilbert catchment could reduce the average duration of connectivity by 1% and 2% in the Flinders and Gilbert catchments respectively. This information is potentially useful to future studies on the flood-dependent ecology in this region. [ABSTRACT FROM AUTHOR]

Summary This paper presents a review of trend analysis of extreme precipitation and hydrological floods in Europe based on observations and future climate projections. The review summaries methods and methodologies applied and key findings from a large number of studies. Reported analyses of observed extreme precipitation and flood records show that there is some evidence of a general increase in extreme precipitation, whereas there are no clear indications of significant trends at large-scale regional or national level of extreme streamflow. Several studies from regions dominated by snowmelt-induced peak flows report decreases in extreme streamflow and earlier spring snowmelt peak flows, likely caused by increasing temperature. The review of likely future changes based on climate projections indicates a general increase in extreme precipitation under a future climate, which is consistent with the observed trends. Hydrological projections of peak flows show large impacts in many areas with both positive and negative changes. A general decrease in flood magnitude and earlier spring floods are projected for catchments with snowmelt-dominated peak flows, which is consistent with the observed trends. Finally, existing guidelines in Europe on design flood and design rainfall estimation are reviewed. The review shows that only few countries have developed guidelines that incorporate a consideration of climate change impacts. [ABSTRACT FROM AUTHOR]

• Use of distributed storage with optimised layout and control reduces peak flows. • Two-step optimisation identifies contribution of layout/RTC to peak flow reduction. • Peak flow reductions due to distributed storage range from 5% to 40% • RTC achieves higher relative peak flow reduction for a smaller storage volume. • Flood hydrograph analysis provides insights on peak flow reduction mechanisms. The impact of urban flooding is increasing due to the effects of increasing urbanisation and climate change. The use of storages is a relatively well-established approach to reduce peak flows and therefore reduce the need for costly upgrades to stormwater conveyance infrastructure. Recently, real-time control (RTC) has been considered as a means of increasing the performance of these storages. However, previous RTC studies have generally focussed on evaluating RTC with pre-determined storage layouts, i.e., storage locations and volumes, and have ignored the impact of optimising the storage layout. Hence, the objectives of this paper are (i) to introduce a two-step approach to minimising peak flows at the catchment scale by firstly optimising the layout of distributed storages and then optimising their RTC strategies, and (ii) to test the effectiveness of this approach on a real catchment in Adelaide, South Australia. Results show that distributed storage with optimised layouts can achieve significantly higher peak flow reductions than more commonly used end-of-system storage. These range from 5% for 100 m3 of system storage up to 40% for 700 m3 of system storage – whereas end-of-system storage achieved no peak flow reduction for up to 700 m3 of storage. The addition of optimised RTC to distributed storages is able to achieve an additional 10% in peak flow reduction. This increase in performance due to RTC is more significant for smaller system storage volumes. Analysis of the flood hydrographs shows the system peak flow reductions are achieved by attenuating hydrographs at individual storages, as well as delaying hydrographs to reduce their coincidence at the confluence of sub-catchments. These results highlight the potential for using optimised distributed storage layout and RTC as an alternative approach to end-of-system storage to reduce flood peaks. [ABSTRACT FROM AUTHOR]