The estimation of PMP and PMF on alpine basins in Switzerland

This paper presents a very fine grid hydrological model based on the spatiotemporal repartition of precipitation and on the topography. The goal is to estimate the flood on a catchment area, using a Probable Maximum Precipitation (PMP) leading to a Probable Maximum Flood (PMF). The spatiotemporal distribution of the precipitation was realized using six clouds modeled by the advection-diffusion equation. The equation shows the movement of the clouds over the terrain and also gives the evolution of the rain intensity in time. This hydrological modeling is followed by a hydraulic modeling of the surface and subterranean flows, done considering the factors that contribute to the hydrological cycle, such as the infiltration, the exfiltration and the snowmelt. This model was applied to several Swiss basins using measured rain, with results showing a good correlation between the simulated and observed flows. This good correlation proves that the model is valid and gives us the confidence that the results can be extrapolated to phenomena of extreme rainfall of PMP type. In this article we present some results obtained using a PMP rainfall and the developed model.

Determination of extreme floods using a distributed hydrological model

Hydrological models developed for extreme precipitation of PMP type are difficult to calibrate because of the scarcity of available data for these events. This article presents the process and results of calibration for a distributed hydrological model at fine scale developed for the estimation of probable maximal floods in the case of a PMP. This calibration is done on two Swiss catchments for two events of summer storms. The calculation done is concentrated on the estimation of the parameters of the model, divided in two parts. The first is necessary for the computation of flow speeds while the second is required for the determination of the initial and final infiltration capacities for each terrain type. The results, validated with the Nash equation show a good correlation between the simulated and observed flows. We also apply this model on two Romanian catchments, showing the river network and estimated flow.

A methodology for the adaptation of a PMP at the determination of a PMF

This paper presents a new type of very fine grid hydrological model based on the spatiotemporal repartition of a PMP (Probable Maximum Precipitation) and on the topography. The goal is to estimate the influence of this rain on a PMF (Probable Maximum Flood) on a catchment area in Switzerland. The spatiotemporal distribution of the PMP was realized using six clouds modeled by the advection-diffusion equation. The equation shows the movement of the clouds over the terrain and also gives the evolution of the rain intensity in time. This hydrological modeling is followed by a hydraulic modeling of the surface and subterranean flow, done considering the factors that contribute to the hydrological cycle, such as the infiltration, the resurgence and the snowmelt. These added factors make the developed model closer to reality and also offer flexibility in the initial condition that is added to the factors concerning the PMP, such as the duration of the rain, the speed and direction of the wind. All these initial conditions taken together offer a complete image of the PMF.

Modélisation hydrologique des précipitations et des crues extrêmes dans les bassins versants alpins

Cet article présente un nouveau type de modèle hydrologique distribué à maille très fine intégrant le calcul de la distribution spatio-temporelle d'une PMP (Précipitation Maximale Probable). Le but est de déterminer les hydrogrammes de crue extrêmes correspondent à la PMF (Probable Maximum Flood) d'un bassin versant alpin. Un modèle de type distribué est indispensable pour transférer la distribution de la pluie dans l'espace et dans le temps, ainsi que pour tenir compte des caractéristiques très variables de ces bassins versants. Le modèle développé comprend trois parties importantes. Dans la première partie une distribution de la précipitation extrême, calculée a méso-échelle (1 à 2 km), est répartie dans l'espace et dans le temps à l'échelle de la maille (environ 30 m). La deuxième partie concerne la modélisation de l'écoulement de l'eau en surface et dans le sous-sol en incluant l'infiltration et l'exfiltration. La troisième partie inclut la modélisation de la fonte des neiges, basée sur un calcul de transfert de chaleur. Les débits simulés montrent une bonne corrélation avec ceux mesurés, validé à l'aide du critère de Nash.

Reducing inconsistencies in point observations of maximum flood inundation level

Flood simulation models and hazard maps are only as good as the underlying data against which they are calibrated and tested. However, extreme flood events are by definition rare, so the observational data of flood inundation extent are limited in both quality and quantity. The relative importance of these observational uncertainties has increased now that computing power and accurate lidar scans make it possible to run high-resolution 2D models to simulate floods in urban areas. However, the value of these simulations is limited by the uncertainty in the true extent of the flood. This paper addresses that challenge by analyzing a point dataset of maximum water extent from a flood event on the River Eden at Carlisle, United Kingdom, in January 2005. The observation dataset is based on a collection of wrack and water marks from two postevent surveys. A smoothing algorithm for identifying, quantifying, and reducing localized inconsistencies in the dataset is proposed and evaluated showing positive results. The proposed smoothing algorithm can be applied in order to improve flood inundation modeling assessment and the determination of risk zones on the floodplain.

Comparison of generalized estimates of probable maximum precipitation with greatest observed rainfalls /

Mar. 1980.

EVALUATION OF NON-STATIONARITY IN ANNUAL MAXIMUM FLOOD SERIES OF MODERATELY IMPAIRED WATERSHEDS IN THE UPPER MIDWEST AND NORTHEASTERN UNITED STATES

United States federal agencies assess flood risk using Bulletin 17B procedures which assume annual maximum flood series are stationary. This represents a significant limitation of current flood frequency models as the flood distribution is thereby assumed to be unaffected by trends or periodicity of atmospheric/climatic variables and/or anthropogenic activities. The validity of this assumption is at the core of this thesis, which aims to improve understanding of the forms and potential causes of non-stationarity in flood series for moderately impaired watersheds in the Upper Midwest and Northeastern US. Prior studies investigated non-stationarity in flood series for unimpaired watersheds; however, as the majority of streams are located in areas of increasing human activity, relative and coupled impacts of natural and anthropogenic factors need to be considered such that non-stationary flood frequency models can be developed for flood risk forecasting over relevant planning horizons for large scale water resources planning and management.

Global scale water stages from SAR imagery (GlosSARi) to support global flood forecasting

Despite the success of studies attempting to integrate remotely sensed data and flood modelling and the need to provide near-real time data routinely on a global scale as well as setting up online data archives, there is to date a lack of spatially and temporally distributed hydraulic parameters to support ongoing efforts in modelling. Therefore, the objective of this project is to provide a global evaluation and benchmark data set of floodplain water stages with uncertainties and assimilation in a large scale flood model using space-borne radar imagery. An algorithm is developed for automated retrieval of water stages with uncertainties from a sequence of radar imagery and data are assimilated in a flood model using the Tewkesbury 2007 flood event as a feasibility study. The retrieval method that we employ is based on possibility theory which is an extension of fuzzy sets and that encompasses probability theory. In our case we first attempt to identify main sources of uncertainty in the retrieval of water stages from radar imagery for which we define physically meaningful ranges of parameter values. Possibilities of values are then computed for each parameter using a triangular ‘membership’ function. This procedure allows the computation of possible values of water stages at maximum flood extents along a river at many different locations. At a later stage in the project these data are then used in assimilation, calibration or validation of a flood model. The application is subsequently extended to a global scale using wide swath radar imagery and a simple global flood forecasting model thereby providing improved river discharge estimates to update the latter.

Evaluation of flood risk in response to climate variability

Standard procedures for forecasting flood risk (Bulletin 17B) assume annual maximum flood (AMF) series are stationary, meaning the distribution of flood flows is not significantly affected by climatic trends/cycles, or anthropogenic activities within the watershed. Historical flood events are therefore considered representative of future flood occurrences, and the risk associated with a given flood magnitude is modeled as constant over time. However, in light of increasing evidence to the contrary, this assumption should be reconsidered, especially as the existence of nonstationarity in AMF series can have significant impacts on planning and management of water resources and relevant infrastructure. Research presented in this thesis quantifies the degree of nonstationarity evident in AMF series for unimpaired watersheds throughout the contiguous U.S., identifies meteorological, climatic, and anthropogenic causes of this nonstationarity, and proposes an extension of the Bulletin 17B methodology which yields forecasts of flood risk that reflect climatic influences on flood magnitude. To appropriately forecast flood risk, it is necessary to consider the driving causes of nonstationarity in AMF series. Herein, large-scale climate patterns—including El Niño-Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), North Atlantic Oscillation (NAO), and Atlantic Multidecadal Oscillation (AMO)—are identified as influencing factors on flood magnitude at numerous stations across the U.S. Strong relationships between flood magnitude and associated precipitation series were also observed for the majority of sites analyzed in the Upper Midwest and Northeastern regions of the U.S. Although relationships between flood magnitude and associated temperature series are not apparent, results do indicate that temperature is highly correlated with the timing of flood peaks. Despite consideration of watersheds classified as unimpaired, analyses also suggest that identified change-points in AMF series are due to dam construction, and other types of regulation and diversion. Although not explored herein, trends in AMF series are also likely to be partially explained by changes in land use and land cover over time. Results obtained herein suggest that improved forecasts of flood risk may be obtained using a simple modification of the Bulletin 17B framework, wherein the mean and standard deviation of the log-transformed flows are modeled as functions of climate indices associated with oceanic-atmospheric patterns (e.g. AMO, ENSO, NAO, and PDO) with lead times between 3 and 9 months. Herein, one-year ahead forecasts of the mean and standard deviation, and subsequently flood risk, are obtained by applying site specific multivariate regression models, which reflect the phase and intensity of a given climate pattern, as well as possible impacts of coupling of the climate cycles. These forecasts of flood risk are compared with forecasts derived using the existing Bulletin 17B model; large differences in the one-year ahead forecasts are observed in some locations. The increased knowledge of the inherent structure of AMF series and an improved understanding of physical and/or climatic causes of nonstationarity gained from this research should serve as insight for the formulation of a physical-casual based statistical model, incorporating both climatic variations and human impacts, for flood risk over longer planning horizons (e.g., 10-, 50, 100-years) necessary for water resources design, planning, and management.

Flood triggering in Switzerland: the role of daily to monthly preceding precipitation

Determining the role of different precipitation periods for peak discharge generation is crucial for both projecting future changes in flood probability and for short- and medium-range flood forecasting. In this study, catchment-averaged daily precipitation time series are analyzed prior to annual peak discharge events (floods) in Switzerland. The high number of floods considered – more than 4000 events from 101 catchments have been analyzed – allows to derive significant information about the role of antecedent precipitation for peak discharge generation. Based on the analysis of precipitation times series, a new separation of flood-related precipitation periods is proposed: (i) the period 0 to 1 day before flood days, when the maximum flood-triggering precipitation rates are generally observed, (ii) the period 2 to 3 days before flood days, when longer-lasting synoptic situations generate "significantly higher than normal" precipitation amounts, and (iii) the period from 4 days to 1 month before flood days when previous wet episodes may have already preconditioned the catchment. The novelty of this study lies in the separation of antecedent precipitation into the precursor antecedent precipitation (4 days before floods or earlier, called PRE-AP) and the short range precipitation (0 to 3 days before floods, a period when precipitation is often driven by one persistent weather situation like e.g., a stationary low-pressure system). A precise separation of "antecedent" and "peak-triggering" precipitation is not attempted. Instead, the strict definition of antecedent precipitation periods permits a direct comparison of all catchments. The precipitation accumulating 0 to 3 days before an event is the most relevant for floods in Switzerland. PRE-AP precipitation has only a weak and region-specific influence on flood probability. Floods were significantly more frequent after wet PRE-AP periods only in the Jura Mountains, in the western and eastern Swiss plateau, and at the outlet of large lakes. As a general rule, wet PRE-AP periods enhance the flood probability in catchments with gentle topography, high infiltration rates, and large storage capacity (karstic cavities, deep soils, large reservoirs). In contrast, floods were significantly less frequent after wet PRE-AP periods in glacial catchments because of reduced melt. For the majority of catchments however, no significant correlation between precipitation amounts and flood occurrences is found when the last 3 days before floods are omitted in the precipitation amounts. Moreover, the PRE-AP was not higher for extreme floods than for annual floods with a high frequency and was very close to climatology for all floods. The fact that floods are not significantly more frequent nor more intense after wet PRE-AP is a clear indicator of a short discharge memory of Pre-Alpine, Alpine and South Alpine Swiss catchments. Our study poses the question whether the impact of long-term precursory precipitation for floods in such catchments is not overestimated in the general perception. The results suggest that the consideration of a 3–4 days precipitation period should be sufficient to represent (understand, reconstruct, model, project) Swiss Alpine floods.

FLOOD RISK ASSESSMENT UNDER HISTORICAL AND PREDICTED LAND USE CHANGE USING CONTINUOUS HYDROLOGIC MODELING

Current procedures for flood risk estimation assume flood distributions are stationary over time, meaning annual maximum flood (AMF) series are not affected by climatic variation, land use/land cover (LULC) change, or management practices. Thus, changes in LULC and climate are generally not accounted for in policy and design related to flood risk/control, and historical flood events are deemed representative of future flood risk. These assumptions need to be re-evaluated, however, as climate change and anthropogenic activities have been observed to have large impacts on flood risk in many areas. In particular, understanding the effects of LULC change is essential to the study and understanding of global environmental change and the consequent hydrologic responses. The research presented herein provides possible causation for observed nonstationarity in AMF series with respect to changes in LULC, as well as a means to assess the degree to which future LULC change will impact flood risk. Four watersheds in the Midwest, Northeastern, and Central United States were studied to determine flood risk associated with historical and future projected LULC change. Historical single framed aerial images dating back to the mid-1950s were used along with Geographic Information Systems (GIS) and remote sensing models (SPRING and ERDAS) to create historical land use maps. The Forecasting Scenarios of Future Land Use Change (FORE-SCE) model was applied to generate future LULC maps annually from 2006 to 2100 for the conterminous U.S. based on the four IPCC-SRES future emission scenario conditions. These land use maps were input into previously calibrated Soil and Water Assessment Tool (SWAT) models for two case study watersheds. In order to isolate effects of LULC change, the only variable parameter was the Runoff Curve Number associated with the land use layer. All simulations were run with daily climate data from 1978-1999, consistent with the 'base' model which employed the 1992 NLCD to represent 'current' conditions. Output daily maximum flows were converted to instantaneous AMF series and were subsequently modeled using a Log-Pearson Type 3 (LP3) distribution to evaluate flood risk. Analysis of the progression of LULC change over the historic period and associated SWAT outputs revealed that AMF magnitudes tend to increase over time in response to increasing degrees of urbanization. This is consistent with positive trends in the AMF series identified in previous studies, although there are difficulties identifying correlations between LULC change and identified change points due to large time gaps in the generated historical LULC maps, mainly caused by unavailability of sufficient quality historic aerial imagery. Similarly, increases in the mean and median AMF magnitude were observed in response to future LULC change projections, with the tails of the distributions remaining reasonably constant. FORE-SCE scenario A2 was found to have the most dramatic impact on AMF series, consistent with more extreme projections of population growth, demands for growing energy sources, agricultural land, and urban expansion, while AMF outputs based on scenario B2 showed little changes for the future as the focus is on environmental conservation and regional solutions to environmental issues.

Floods of June 17, 1990 and July 9, 1993, Along Squaw Creek and the South Skunk River in Ames, Iowa, and Vicinity, HR-140, 1996

Water-surface-elevation profiles and peak discharges for the floods of June 17, 1990, and July 9, 1993, along Squaw Creek and the South Skunk River, in Ames, Iowa, are presented in this report. The maximum flood-peak discharge of 24,300 cubic feet per second for the streamflow-gaging station on Squaw Creek at Ames, Iowa (station number 05470500) occurred on July 9, 1993. This discharge was 80 percent larger than the 100-year recurrence-interval discharge and exceeded the previous record flood-peak discharge of June 17, 1990, by 94 percent. The July 9, 1993, flood-peak discharge of 26,500 cubic feet per second on the South Skunk River below Squaw Creek (station number 05471000) was also a peak of record, exceeding the previous record flood-peak discharge of June 27,1975, by 80 percent, and the 100-year recurrence-interval discharge by 60 percent. A flood history describes rainfall conditions for floods that occurred during 1990 and 1993.

Noble gas, CFC and other geochemical evidence for the age and origin of the Bath thermal waters, UK

The city of Bath is a World Heritage site and its thermal waters, the Roman Baths and new spa development rely on undisturbed flow of the springs (45 °C). The current investigations provide an improved understanding of the residence times and flow regime as basis for the source protection. Trace gas indicators including the noble gases (helium, neon, argon, krypton and xenon) and chlorofluorocarbons (CFCs), together with a more comprehensive examination of chemical and stable isotope tracers are used to characterise the sources of the thermal water and any modern components. It is shown conclusively by the use of 39Ar that the bulk of the thermal water has been in circulation within the Carboniferous Limestone for at least 1000 years. Other stable isotope and noble gas measurements confirm previous findings and strongly suggest recharge within the Holocene time period (i.e. the last 12 kyr). Measurements of dissolved 85Kr and chlorofluorocarbons constrain previous indications from tritium that a small proportion (<5%) of the thermal water originates from modern leakage into the spring pipe passing through Mesozoic valley fill underlying Bath. This introduces small amounts of O2 into the system, resulting in the Fe precipitation seen in the King’s Spring. Silica geothermometry indicates that the water is likely to have reached a maximum temperature of between 69–99 °C, indicating a most probable maximum circulation depth of ∼3 km, which is in line with recent geological models. The rise to the surface of the water is sufficiently indirect that a temperature loss of >20 °C is incurred. There is overwhelming evidence that the water has evolved within the Carboniferous Limestone formation, although the chemistry alone cannot pinpoint the geometry of the recharge area or circulation route. For a likely residence time of 1–12 kyr, volumetric calculations imply a large storage volume and circulation pathway if typical porosities of the limestone at depth are used, indicating that much of the Bath-Bristol basin must be involved in the water storage.

The long-term development of avalanche risk in settlements considering the temporal variability of damage potential

Recent studies on the avalanche risk in alpine settlements suggested a strong dependency of the development of risk on variations in damage potential. Based on these findings, analyses on probable maximum losses in avalanche-prone areas of the municipality of Davos (CH) were used as an indicator for the long-term development of values at risk. Even if the results were subject to significant uncertainties, they underlined the dependency of today's risk on the historical development of land-use: Small changes in the lateral extent of endangered areas had a considerable impact on the exposure of values. In a second step, temporal variations in damage potential between 1950 and 2000 were compared in two different study areas representing typical alpine socio-economic development patterns: Davos (CH) and Galtür (A). The resulting trends were found to be similar; the damage potential increased significantly in number and value. Thus, the development of natural risk in settlements can for a major part be attributed to long-term shifts in damage potential.