Analysis of Climate Change Effects on Floods Frequency Through a Continuous Hydrological Modelling

Derived flood frequency models can be used to study climate and land use change effects on the flood frequency curve. Intra‐annual (i.e., within year) climate variability strongly impacts upon the flood frequency characteristics in two ways: in a direct way through the seasonal variability of storm characteristics and indirectly through the seasonality of rainfall and evapotranspiration which then affect the antecedent catchment conditions for individual storm events. In this paper we propose a quasi‐analytical derived flood frequency model that is able to account for both types of seasonalities. The model treats individual events separately. It consists of a rainfall model with seasonally varying parameters. Increased flood peaks, as compared to block rainfall, due to random within‐storm rainfall time patterns are represented by a factor that is a function of the ratio of storm duration and catchment response time. Event runoff coefficients are allowed to vary seasonally and include a random component. Their statistical characteristics are derived from long‐term water balance simulations. The components of the derived flood frequency model are integrated in probability space to derive monthly flood frequency curves. These are then combined into annual flood frequency curves. Comparisons with Monte Carlo simulations using parameters that are typical of Austrian catchments indicate that the approximations used here are appropriate. We perform sensitivity analyses to explore the effects of the interaction of rainfall and antecedent soil moisture seasonalities on the flood frequency curve. When the two seasonalities are in phase, there is resonance, which increases the flood frequency curve dramatically. We are also able to isolate the contributions of individual months to the annual flood frequency curve. Monthly flood frequency curves cross over for the parameters chosen here, as extreme floods tend to mainly occur in summer while less extreme floods may occur throughout the year.

Understanding how climate change affects the frequency and magnitude of floods is essential for adaptation strategies. Usually, the impact of climate change on extreme weather and floods is assessed using the projections of the Regional Climate Model (RCM) in a hydrological model. Nevertheless, RCM projections are usually too coarse to describe convective storms, and they can underestimate the intensity of short-duration extreme precipitation that is usually responsible for flash flood events in small river basins. For this reason, Convection Permitting Models have been proven to perform better than RCM in describing sub-daily extreme precipitation.The objective of the work is to assess the impact of climate change on the flood frequency of the Arno River basin using CPM projections to also better describe future flood hazards in its small tributaries. The hydrological model used in the analysis is the Soil and Water Assessment Tool Plus (SWAT+). The projections used as input of the model are VHR-PRO_IT, Very High-Resolution Projections over Italy (Raffa et al., 2023). The projections have a 2.2 km spatial resolution and 1h temporal resolution, and they cover 90 years from 1981 to 2070 in the emission scenarios RCP 4.5 and RCP 8.5. First, the model has been calibrated with 15 years of observed data. Then, the projections have been bias-corrected and used as input in the continuous hydrological model. Therefore, SWAT+ performs a continuous hydrological simulation for 90 years at the hourly timestep.The bias correction of the precipitation projections has been done with a parametric approach (Mamalakis et al., 2017) to adjust the frequency distribution of precipitation events. The correction of temperature projections has been done with an easier approach based on the linear scaling of monthly average temperatures. The bias correction used ground observations of rain gauges and thermometers of the Hydrological Regional Service of the Tuscany Region.The results are expressed with a delta-change approach to extract possible trends in the simulated discharges. The delta change expresses the ratio between the peak discharge associated with a given return period T in the future and the peak discharge for the same frequency in the historical period. The Generalized Extreme Value Distribution (GEV) is used to fit the cumulative distribution of the annual maximum series for three-time windows of 30 years: 1981-2010 (Historical), 2011-2040 (Near Future), and 2041-2070 (Far Future). The results show an increase in the flood hazard in the city of Florence in the RCP8.5, especially in the far future.  ACKNOWLEDGEMENT: The research is carried out within the RETURN – multi-Risk sciEnce for resilienT comUnities undeR a changiNg climate Extended Partnership and received funding from the  European Union Next-GenerationEU (National Recovery and Resilience Plan – NRRP, Mission 4, Component 2, Investment 1.3 – D.D. 1243 2/8/2022, PE0000005).

Abstract. The aim of this paper is to illustrate the effects of selected catchment storage thresholds upon runoff behaviour, and specifically their impact upon flood frequency. The analysis is carried out with the use of a stochastic rainfall model, incorporating rainfall variability at intra-event, inter-event and seasonal timescales, as well as infrequent summer tropical cyclones, coupled with deterministic rainfall-runoff models that incorporate runoff generation by both saturation excess and subsurface stormflow mechanisms. Changing runoff generation mechanisms (i.e. from subsurface flow to surface runoff) associated with a given threshold (i.e. saturation storage capacity) is shown to be manifested in the flood frequency curve as a break in slope. It is observed that the inclusion of infrequent summer storm events increases the temporal frequency occurrence and magnitude of surface runoff events, in this way contributing to steeper flood frequency curves, and an additional break in the slope of the flood frequency curve. The results of this study highlight the importance of thresholds on flood frequency, and provide insights into the complex interactions between rainfall variability and threshold nonlinearities in the rainfall-runoff process, which are shown to have a significant impact on the resulting flood frequency curves.

This paper provides an analysis of maximum annual and flood discharges on the upper Svratka River during a period of systematic hydrological measurements before and after the construction of the reservoirs known as Vír I and Vír II. The water-gauge stations of Borovnice (upstream from the reservoirs) and Vír (downstream from the reservoirs) are used to analyse peak discharges (Qk) with a return period equal to or higher than two years (Q2), from 1925 to 2010. The flood regime is evaluated in terms of the frequency of floods, their seasonality and extremity. The article explores anthropogenic influence on maximum annual discharges and flood discharges on the upper Svratka River after construction of the two reservoirs, using numerical and statistical methods. These are evident, primarily, in the disruption of the homogeneity of observations, reductions in the frequency and extremity of floods, decreasing in the values and variability of maximum annual discharges, and delay in their culminations. The construction of the reservoir provides a unique example of modification of a natural hydrological regime that facilitates the quantification of an anthropogenic influence.

A summary of the results of regional flood frequency analyses that have been carried out in many tropical and sub-tropical countries is presented. The results provide a set of flood estimation methods which should be of immediate usefulness in practical applications, bearing in mind the errors of generalization. By defining the representative values of the mean annual flood and of the flood frequency curves for each region, an attempt has been made to develop relationships between the methods and climatic characteristics. These show that adequate relationships can be obtained based solely on the median annual average rainfall and the median catchment area for the regions. In particular, the steepness of the regional flood frequency curve can be estimated reasonably well from these two parameters. The relationships confirm that, broadly speaking, for humid regions the “average” flood—the flood that occurs regularly every one or two years—is relatively large, but the flood frequency curve is not very steep; rare floods (occurring once in every 100 to 1000 years) are not very much larger than the average flood. Conversely, in arid regions, the average flood is small, but rare floods can be extremely large multiples of the average. These relationships provide a useful initial indication of the type of regional flood frequency estimation method likely to be found in tropical and sub-tropical regions throughout the world.

This paper describes a case study of event and continuous hydrologic modeling in the Kelani River basin in Sri Lanka using the Hydrologic Engineering Center—Hydrologic Modeling System (HEC–HMS). An extremely high rainfall event in November 2005 was used to calibrate model parameters, and extremely high rainfall events in April–May 2008, May–June 2008, and May 2010 were used to validate the event model. The calibrated, direct runoff and base flow parameters were then used in the continuous hydrologic model. The Green and Ampt infiltration loss method was used to account for infiltration loss in event-based modeling and a five-layer soil moisture accounting loss method was employed in continuous modeling. The Clark unit hydrograph method and the recession base flow method were used to simulate direct runoff and base flow, respectively. The results depict the capability of HEC–HMS to reproduce streamflows in the basin to a high accuracy with averaged computed Nash–Sutcliffe efficiencies of 0.91 for e...

Flood frequency analysis is used by water resources professionals to estimate the probability of exceedence associated with a flood of a given magnitude. The estimation of flood frequencies is important because they are used in the planning and design of hydraulic structures, in flood-plain management, and in reservoir operation. The index flood method is commonly used to develop a flood frequency curve that relates flood magnitude to flood rarity. This method involves scaling a dimensionless flood frequency curve by the index flood. The index flood is a middle-sized flood for which the mean or median of the flood data series is typically used. When the catchment of interest is ungauged, statistical models, such as multiple regression, are often used to relate the index flood to catchment descriptors. In this study six different parameter estimation techniques and three regionalization techniques are compared in terms of ability to predict the index flood for an ungauged catchment. A case study employing a split-sample experiment with data from catchments in Ontario, Canada, was used to evaluate the approaches. The models were assessed using three performance indices to evaluate the capability to predict the index flood for 20 stations. The dimensionless nonlinear model outperformed all of the other parameter estimation techniques for each of the three indices selected. The performance was improved through the use of geostatistical residual mapping, however, the improvement was small. The residual mapping was found to greatly improve the estimates obtained using ordinary least-squares regression.Key words: index flood, flood frequency analysis, regression, residual mapping, geostatistics.

A grid‐based flow routing and runoff‐production model, configured to employ regional climate model (RCM) precipitation estimates as input, is used to assess the effects of climate change on river flows in catchments across the UK. This model, the Grid‐to‐Grid model or G2G, has previously been calibrated and assessed with respect to observed river flows under current climate conditions. Here, the G2G distributed model together with a lumped catchment model, the parameter‐generalized PDM, are applied to simulate river flow and derive flood frequency curves. Two sets of RCM precipitation time‐series, on a 25‐km grid and at hourly intervals, are used: (1) Current (1961–1990) and (2) Future (2071–2100). The effect of one extreme rainfall event in the current precipitation series is to raise the estimated peak flows for some catchments for high return periods under present day rainfall conditions. The future flow series does not contain a comparable flow peak. This significantly affects comparison of the flood frequency curves derived from the flow simulations obtained using the current and future precipitation estimates. Such variability in the results and the dependence on one or two extreme rainfall events emphasizes the need to examine more than one set of current/future precipitation scenarios for flood impact studies. In the absence of a formal ensemble of climate predictions, a resampling method is used to investigate the robustness of the modelled changes in flood frequency. Changes in flood frequency at higher return periods are, not surprisingly, found to be generally less robust than at lower return periods. This is particularly the case for catchments in the south and east of England, which were especially affected by the extreme rainfall event in the current precipitation series. Copyright © 2007 Royal Meteorological Society

<p>In recent times water-related hazards have captured public attention and led to an increased interest in developing hydrologic forecasting systems, and quantifying their reliability. Despite major investments in flood forecasting and flood protection measures undertaken after recurring widespread inundations (e.g. 2002 and 2013 in Eastern Europe), heavy rainfall events led to severe flooding in Western Europe during July of the past summer, resulting in severe impacts and massive losses, including over two hundred deaths. Extreme precipitation, breaking observed records, is expected to have an increased likelihood under global warming, all the more we should question and scrutinize our knowledge about the frequency and severity of floods. Reliable estimates of these, and a better quantification of their uncertainty are key information for improving our preparedness and developing adaption measures in the future.</p><p>For this purpose we explore the potential of running pooled weather reforecasts through the flexible hydrological model framework DECIPHeR (Coxon et al.2019) in Switzerland, modified to include snow, glaciers and the effect of lakes and reservoirs on the river network. For three case studies of different climatic regions (one including regulated lakes), we compare floods generated by the 10 largest precipitation events and precipitation events of low frequency (return period >= 100 years), both extracted from the pooled data, for three accumulation periods (1, 3, 5 days) with the official flood frequency curves and flood frequency curves generated with long continuous simulation using the pooled data (> 1000 years). This analysis will show us possible deficiencies of record-based flood frequency curves, if running selected precipitation events according to a return period already gives us a representative “flood sample”, and what is the gain of running long continuous simulations (e.g. are there overlooked events, summoning hydrological extremes through particular spatio-temporal patterns? What is the effect of different initial conditions?).</p><p> </p><p>References</p><p>Coxon G., Freer J., Lane R., Dunne T., Knoben W.J.M., Howden N.J.K., Quinn N., Wagener T. and Woods R. : DECIPHeR v1: Dynamic fluxEs and ConnectIvity for Predictions of HydRology. <em>Geosci Model Dev</em>.,12,2285-2306, https://doi.org/10.5194/gmd-12-2285-2019, 2019.</p>

As climate change intensifies, shifts in temperature and precipitation extremes raise concerns about increasing river flood risks. Understanding and quantifying how climate change influences floods is relevant from both theoretical and practical perspectives. From a research standpoint, although flood trend detection has been widely investigated, attributing observed changes to specific drivers remains challenging. From a practical perspective, reliable methods are needed to incorporate evolving climate conditions into flood predictions—particularly in ungauged basins—since traditional flood frequency analysis assumes stationarity.In this work, we present research conducted at Politecnico di Torino addressing these issues. The objectives are to investigate the relationship between floods and climate extremes at both local and large spatial scales, and to propose methods for linking changes in flood frequency curves to evolving precipitation and temperature patterns. The study area is the Great Alpine Region (GAR), including the Po River valley in Northern Italy. Both data-based and modelling approaches are employed.The data-based approach relies on the derived flood frequency framework and estimates flood sensitivity to changes in precipitation extremes by linking flood frequency curves and Intensity–Duration–Frequency curves through quantile–quantile relationships at the local scale. The modelling approach is based on the application of a regionally distributed rainfall–runoff model forced by climate model outputs, allowing changes in flood event characteristics to be investigated at the regional scale.This study is carried out within the Clim2FlEx project and the RETURN Extended Partnership and is funded by the Italian Ministry of Education, Universities and Research (MUR, PRIN project 2022AX3882) and the European Union NextGenerationEU (National Recovery and Resilience Plan – NRRP, Mission 4, Component 2, Investment 1.3 – D.D. 1243 2/8/2022, PE0000005 – Spoke VS1).

<p>In view of recent dramatic floods and drought events, the detection of trends in the frequency and magnitude of long time series of flood data is of scientific interest and practical importance. It is essential in many fields, from climate change impact assessment to water resources management, from flood forecasting to drought monitoring, for the planning of future water resources and flood protection systems. <br>To detect long-term changes in river discharge a dense, in space and time, network of monitoring stations is required. However, ground hydro-meteorological monitoring networks are often missing or inadequate in many parts of the world and the global supply of the available river discharge data is often restricted, preventing to identify trends over large areas.  <br>The most direct method of deriving such information on a global scale involves satellite earth observation. Over the last two decades, the growing availability of satellite sensors, and the results so far obtained in the estimation of river discharge from the monitoring of the water level through satellite radar altimetry has fostered the interest on this subject.  <br>Therefore, in the attempt to overcome the lack of long continuous observed time series, in this study satellite altimetry water level data are used to set-up a consistent, continuous and up-to-date daily discharge dataset for different sites across the world. Satellite-derived water levels provided by publicly available datasets (Podaac, Dahiti, River& Lake, Hydroweb and Theia) are used along with available ground observed river discharges to estimate rating curves. Once validated, the rating curves are used to fill and extrapolate discharge data over the whole period of altimetry water level observations. The advantage of using water level observations provided by the various datasets allowed to obtain discharge time series with improved spatio-temporal coverages and resolutions, enabling to extend the study on a global scale and to efficiently perform the analysis even for small to medium-sized basins.  <br>Long continuous discharge time series so obtained are used to perform a global trend analysis on extreme flood and drought events. Specifically, annual maximum discharge and peak-over threshold values are extracted from the simulated daily discharge time series, as proxy variables of independent flood events. For flood and drought events, a trend analysis is carried out to identify changes in the frequency and magnitude of extreme events through the Mann-Kendall (M-K) test and a linear regression model between time and the flood magnitude.  <br>The analysis has permitted to identify areas of the world prone to floods and drought, so that appropriate actions for disaster risk mitigation and continuous improvement in disaster preparedness, response, and recovery practices can be adopted. </p>

With the objective of improving flood predictions, in recent years sophisticated continuous hydrologic models that include complex land‐surface sub‐models have been developed. This has produced a significant increase in parameterization; consequently, applications of distributed models to ungauged basins lacking specific data from field campaigns may become redundant.The objective of this paper is to produce a parsimonious and robust distributed hydrologic model for flood predictions in Italian alpine basins. Application is made to the Toce basin (area 1534 km2). The Toce basin was a case study of the RAPHAEL European Union research project, during which a comprehensive set of hydrologic, meteorological and physiographic data were collected, including the hydrologic analysis of the 1996–1997 period. Two major floods occurred during this period. We compare the FEST04 event model (which computes rainfall abstraction and antecedent soil moisture conditions through the simple Soil Conservation Service curve number method) and two continuous hydrologic models, SDM and TDM (which differ in soil water balance scheme, and base flow and runoff generation computations).The simple FEST04 event model demonstrated good performance in the prediction of the 1997 flood, but shows limits in the prediction of the long and moderate 1996 flood. More robust predictions are obtained with the parsimonious SDM continuous hydrologic model, which uses a simple one‐layer soil water balance model and an infiltration excess mechanism for runoff generation, and demonstrates good performance in both long‐term runoff modelling and flood predictions. Instead, the use of a more sophisticated continuous hydrologic model, the TDM, that simulates soil moisture dynamics in two layers of soil, and computes runoff and base flow using some TOPMODEL concepts, does not seem to be advantageous for this alpine basin. Copyright © 2006 John Wiley & Sons, Ltd.

During nine small-scale laboratory experiments simulating combined wave overtopping and storm surge overflow on a trapezoidal levee, time series measurements of flow thickness and velocity were acquired at a location on the levee crest and at a location on the landward-side slope. Flow thickness and velocity were combined to estimate time series of the instantaneous discharge. Comparisons of the calculated overtopping discharge time series at the two locations revealed that the time series of instantaneous discharge was the same at both locations with the only difference being a short phase lag. Individual peaks of the discharge time series were examined, and an empirical expression was determined for the root-mean-squared discharge peak. The largest discharge peaks were overestimated by the Rayleigh distribution. For locations on the landward-side slope where the friction slope is approximately the same as the levee slope, it is possible to derive a stream power probability density function based on the overtopping discharge cumulative exceedance probability. The stream power probability density function may be a useful tool for assessing erosion potential of overtopped earthen levees.

Groundwater is a vital water source in semi-arid and arid regions characterized by little and erratic precipitation and ephemeral river flow. In these regions, water scarcity is becoming more critical due to population growth, increasing irrigation demands, and climate change. Groundwater recharge here primarily occurs as episodic events and specifically as focused recharge during high river flow, but the controlling processes are poorly understood. Thus, understanding and quantifying the relationships between climate, streamflow and groundwater dynamics is crucial to assess the impact of climate change on future water availability. Historically, water resources assessments in Africa have relied on large-scale hydrological models, however, they often lack validation from groundwater observations. Here, we take an observation-based approach to identify climatic controls on streamflow and groundwater dynamics in the semi-arid Hout-Sand River catchment, Limpopo, South Africa. Using data spanning from 1940-2023, we analyze time series of precipitation, air temperature, stream discharge, and groundwater level and evaluate long term trends and relationships across a range of climatic indices and hydrologic and groundwater signatures. While we find no significant trends in long-term annual precipitation, the precipitation patterns are becoming increasingly extreme and exhibit higher intensities with longer dry periods. In response, streamflow patterns are changing towards longer no-flow periods although there is no significant trend in total annual flows. Long-term groundwater levels are not unanimously increasing or decreasing. However, we observe a dependence of streamflow and groundwater levels on multi-annual patterns of climate variability. Furthermore, preliminary results suggest that episodic precipitation and streamflow events contribute to the majority of total groundwater recharge, and that the recharge mainly occurs close to streams, i.e. as focused recharge. Finally, we aim to use machine-learning regression techniques to identify the most important controls on focused and diffuse recharge in order to perform spatial regionalization.

POLEMIO, M.; PAMBUKU, A.; LIMONI, P.P., and PETRUCCI, O., 2011. Carbonate coastal aquifer of Vlora Bay and groundwater submarine discharge (southwestern Albania). In: Tursi, A. and Corselli, C. (eds.), Coastal Research in Albania: Vlora Gulf, Journal of Coastal Research, Special Issue No. 58, pp. 26–34. West Palm Beach (Florida), ISSN 0749-0208. The study discusses the large karstic coastal aquifer of Vlora Bay. This case is peculiar, as the submarine groundwater discharge has a relevant rate of terrestrial inflow in an almost closed bay that is located in an environmentally valuable area. The study is based on four methodological activities: geological and hydrogeological conceptualisation, climatic study and hydrological balance, numerical modelling, and monitoring. A geodatabase was created considering hundreds of data points (wells, springs, rivers, lagoons, and seas) and monthly time series of rainfall, temperature, and river discharge. Monitoring activity was realised over a hydrological year, installing a rainfall network tool and using a network of tens of sampling points, including springs, wells, lagoons, and sea. Chemical–physical and stable isotope determinations were realised. Two main groups of aerial springs are fed by the aquifer, one of which is of a coastal type. The total spring discharge is roughly 4 m 3 /s. The submarine groundwater discharge (SGD) was assessed as being equal to 1.4 m 3 /s on the basis of the current rate of anthropic discharge and climatic conditions. The study showed the peculiarities of this carbonate coastal aquifer and the importance of its groundwater, which is the chief water source for the third-largest Albanian town.The groundwater quality was generally high, mainly due to the negligible presence of contamination sources on the relief in which the aquifer outcrops. The rate of seawater intrusion effects was also low, thanks to favourable aquifer threedimensional geometry and high recharge levels. The increasing anthropic activities constitute a relevant risk in the absence of the introduction of rigorous land and water management criteria.