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Climate change impact on flood hazard in a central Portugal alluvial plain
... Moreover, in order to investigate the catchments' geometries, shape tilting and hydrological conditions, several other parameters were calculated as well: (a) the form factor (Rf ) (the ratio of the watershed area to the square of the catchment length; indicates the flow intensity of the drainage network-catchments with high Rf experience more significant peak flows in a shorter time), (b) the circularity ratio (Rc) (the ratio of the watershed area to the area of a circle with the same perimeter to the watershed; it is influenced by the frequency of the streams, the slopes and the geological structure), (c) the elongation ratio (Re) (the ratio of the watershed diameter, projected as a circle, to the watershed length; attributes the proportion of the catchment that has been elongated by tectonic activity, principally) and (d) the sinuosity index (C) (the ratio of the stream length to the catchment length; defines how straight/direct is a stream; completely straight/direct channels have a sinuosity index value close to 1.0, while low meandering streams have a sinuosity index value of 1.25-2.0 and high meandering streams >2.0 or more) [96] (Table 1). ...
Morphometric analysis can be used to investigate catchment dynamics and tectonic processes responsible for the development of drainage catchments and to support flood risk assessment. In this study, a comparative GIS-based morphometric analysis between the main southern and northern sub-catchments of the Sperchios River basin, Central Greece, was performed, using geospatial and remote sensing data. The goal was to investigate their correlation with the peculiar geotectonic activity and the frequent flash-flood events that occur in the river floodplain. All sub-catchments characteristics are linked with the geological formation types of the area, in combination with ongoing tectonic activity. The results indicate that drainage network development is significantly controlled by the region's overall tectonic activity. The morphometric characteristics-i.e., bifurcation ratio, drainage density, circularity ratio, elongation ratio and water concentration-time values, reflect the flood-prone character of the southern part of Sperchios River catchment in comparison to the northern part, especially during intense rainfall events. The study can provide valuable insight into identifying how morphometric characteristics are associated with increased flood hazard.
According to the EU flood risks directive, flood hazard map must be used to assess the flood risk. These maps can be developed with hydraulic modelling tools using a Digital Surface Runoff Model (DSRM). During the last decade, important evolutions of the spatial data processing has been developed which will certainly improve the hydraulic models results. Currently, images acquired with Red/Green/Blue (RGB) camera transported by Unmanned Aerial Vehicles (UAV) are seen as a good alternative data sources to represent the terrain surface with a high level of resolution and precision. The question is if the digital surface model obtain with this data is adequate enough for a good representation of the hydraulics flood characteristics. For this purpose, the hydraulic model HEC-RAS was run with 4 different DSRM for an 8.5 km reach of the Lis River in Portugal. The computational performance of the 4 modelling implementations is evaluated. Two hydrometric stations water level records were used as boundary conditions of the hydraulic model. The records from a third hydrometric station were used to validate the optimal DSRM. The HEC-RAS results had the best performance during the validation step were the ones where the DSRM with integration of the two altimetry data sources.
In the current work we present six hindcast WRF (Weather Research
and Forecasting model) simulations for the
EURO-CORDEX (European Coordinated Regional Climate Downscaling Experiment) domain with different configurations in microphysics, convection
and radiation for the time period 1990–2008. All regional model simulations
are forced by the ERA-Interim reanalysis and have the same spatial
resolution (0.44°). These simulations are evaluated for surface
temperature, precipitation, short- and longwave downward radiation at the
surface and total cloud cover. The analysis of the WRF ensemble indicates
systematic temperature and precipitation biases, which are linked to
different physical mechanisms in the summer and winter seasons.
Overestimation of total cloud cover and underestimation of downward
shortwave radiation at the surface, mostly linked to the Grell–Devenyi
convection and CAM (Community
Atmosphere Model) radiation schemes, intensifies the negative bias in
summer temperatures over northern Europe (max −2.5 °C). Conversely, a
strong positive bias in downward shortwave radiation in summer over central
(40–60%) and southern Europe mitigates the systematic cold bias over
these regions, signifying a typical case of error compensation. Maximum
winter cold biases are over northeastern Europe (−2.8 °C); this location
suggests that land–atmosphere rather than cloud–radiation interactions are to
blame. Precipitation is overestimated in summer by all model configurations,
especially the higher quantiles which are associated with summertime deep
cumulus convection. The largest precipitation biases are produced by the
Kain–Fritsch convection scheme over the Mediterranean. Precipitation biases
in winter are lower than those for summer in all model configurations
(15–30%). The results of this study indicate the importance of evaluating
not only the basic climatic parameters of interest for climate change
applications (temperature and precipitation), but also other components of the
energy and water cycle, in order to identify the sources of systematic
biases, possible compensatory or masking mechanisms and suggest pathways for
model improvement.
Atmospheric datasets coming from long term reanalyzes of low spatial resolution are used for different purposes. Wind over the sea is, for example, a major ingredient of oceanic simulations. However, the shortcomings of those datasets prevent them from being used without an adequate corrective preliminary treatment. Using a regional climate model (RCM) to perform a dynamical downscaling of those large scale reanalyzes is one of the methods used in order to produce fields that realistically reproduce atmospheric chronology and where those shortcomings are corrected. Here we assess the influence of the configuration of the RCM used in this framework on the representation of wind speed spatial and temporal variability and intense wind events on a daily timescale. Our RCM is ALADIN-Climate, the reanalysis is ERA-40, and the studied area is the Mediterranean Sea.
First, the dynamical downscaling significantly reduces the underestimation of daily wind speed, in average by 9 % over the whole Mediterranean. This underestimation has been corrected both globally and locally, and for the whole wind speed spectrum. The correction is the strongest for periods and regions of strong winds. The representation of spatial variability has also been significantly improved. On the other hand, the temporal correlation between the downscaled field and the observations decreases all the more that one moves eastwards, i.e. further from the atmospheric flux entry. Nonetheless, it remains ∼0.7, the downscaled dataset reproduces therefore satisfactorily the real chronology.
Second, the influence of the choice of the RCM configuration has an influence one order of magnitude smaller than the improvement induced by the initial downscaling. The use of spectral nudging or of a smaller domain helps to improve the realism of the temporal chronology. Increasing the resolution very locally (both spatially and temporally) improves the representation of spatial variability, in particular in regions strongly influenced by the complex surrounding orography. The impact of the interactive air-sea coupling is negligible for the temporal scales examined here. Using two different forcing datasets induces differences on the downscaled fields that are directly related to the differences between those datasets. Our results also show that improving the physics of our RCM is still necessary to increase the realism of our simulations. Finally, the choice of the optimal configuration depends on the scientific objectives of the study for which those wind datasets are used.
Within the framework of the European project ENSEMBLES (ensembles-based predictions of climate changes and their impacts) we explore the systematic bias in simulated monthly mean temperature and precipitation for an ensemble of thirteen regional climate models (RCMs). The models have been forced with the European Centre for Medium Range Weather Forecasting Reanalysis (ERA40) and are compared to a new high resolution gridded observational data set. We find that each model has a distinct systematic bias relating both temperature and precipitation bias to the observed mean. By excluding the twenty-five percent warmest and wettest months, respectively, we find that a derived second-order fit from the remaining months can be used to estimate the values of the excluded months. We demonstrate that the common assumption of bias cancellation (invariance) in climate change projections can have significant limitations when temperatures in the warmest months exceed 4â6 °C above present day conditions.
This paper investigates how using different regional climate model (RCM) simulations affects climate change impacts on hydrology
in northern Europe using an offline hydrological model. Climate change scenarios from an ensemble of seven RCMs, two global
climate models (GCMs), two global emissions scenarios and two RCMs of varying resolution were used. A total of 15 climate
change simulations were included in studies on the Lule River basin in Northern Sweden. Two different approaches to transfer
climate change from the RCMs to hydrological models were tested. A rudimentary estimate of change in hydropower potential
on the Lule River due to climate change was also made. The results indicate an overall increase in river flow, earlier spring
peak flows and an increase in hydropower potential. The two approaches for transferring the signal of climate change to the
hydrological impacts model gave similar mean results, but considerably different seasonal dynamics, a result that is highly
relevant for other types of climate change impacts studies.
Over the last two decades, the frequency of water resource drought in the UK, coupled with the more recent pan-European drought of 2003, has increased concern over changes in climate. Using the UKCIP02 Medium-High (SRES A2) scenario for 2070?2100, this study investigates the impact of climate change on the operation of the Integrated Resource Zone (IRZ), a complex conjunctive-use water supply system in north-western England. The results indicate that the contribution of individual sources to yield may change substantially but that overall yield is reduced by only 18%. Notwithstanding this significant effect on water supply, the flexibility of the system enables it to meet modelled demand for much of the time under the future climate scenario, even without a change in system management, but at significant expense for pumping additional abstraction from lake and borehole sources. This research provides a basis for the future planning and management of the complex water resource system in the north-west of England.
Recent coordinated efforts, in which numerous climate models have been run for a common set of experiments, have produced large datasets of projections of future climate for various scenarios. Those multi-model ensembles sample initial condition, parameter as well as structural uncertainties in the model design, and they have prompted a variety of approaches to quantify uncertainty in future climate in a probabilistic way. This paper outlines the motivation for using multi-model ensembles, reviews the methodologies published so far and compares their results for regional temperature projections. The challenges in interpreting multi-model results, caused by the lack of verification of climate projections, the problem of model dependence, bias and tuning as well as the difficulty in making sense of an 'ensemble of opportunity', are discussed in detail.
General mathematical results are obtained for a system of cascades, each consisting of a number of linear reservoirs in series. For a watershed this system can be derived from its drainage network. Several popular hydrologic models can be shown to be special cases of the general results obtained here. These results are extended to two cases: when rainfall excess is input, and when rainfall, infiltration, evaporation and runoff are simultaneously considered.
Mathematical modeling of watershed hydrology is employed to address a wide spectrum of environmental and water re- sources problems. A historical perspective of hydrologic modeling is provided, and new developments and challenges in watershed models are discussed. These include data acquisition by remote sensing and space technology, digital terrain and elevation models, chemical tracers, geographic information and data management systems, topographic representation, upscaling of hydrologic conservation equa- tions, spatial variability of hydraulic roughness, infiltration and precipitation, spatial and temporal scaling, model calibration, and linking with water quality models. Model construction, calibration, and data processing have received a great deal of attention, while model validation, error propagation, and analyses of uncertainty, risk, and reliability have not been treated as thoroughly. Finally, some remarks are made regarding the future outlook for watershed hydrology modeling.
We assess the impact of two sources of uncertainties in a limited area model (LAM) on the representation of intense precipitation: the size of the domain of integration and the use of the spectral nudging technique (driving of the large-scale within the domain of integration). We work in a perfect-model approach where the LAM is driven by a general circulation model (GCM) run at the same resolution and sharing the same physics and dynamics as the LAM. A set of three 50 km resolution simulations run over Western Europe with the LAM ALADIN-Climate and the GCM ARPEGE-Climate are performed to address this issue. Results are consistent with previous studies regarding the seasonal-mean fields. Furthermore, they show that neither the use of the spectral nudging nor the choice of a small domain are detrimental to the modelling of heavy precipitation in the present experiment.
The influence of climate change on river discharges in five major Danish rivers divided into 29 sub-catchments is investigated for the future period of 2071–2100. Climate changes are modelled by the HIRHAM regional climate model on the basis of the IPCC A2 scenario. A hydrological model (NAM) is used to convert precipitation to river discharges. Difficulties are found in the direct use of climate model generated precipitation and potential evapotranspiration (reference evaporation) because of too many rainy days, deviations from mean annual values of precipitation and potential evapotranspiration from observed values, and poor agreement on seasonality. Therefore climate model generated data is corrected to match observed mean annual values and the mean monthly distribution. Mean annual precipitation is found to increase 7%, potential evapotranspiration to increase 3% and river discharges to increase 12% on average, between a control period (1961–1990) and the future period. Because of increased precipitation from October to March and reduced precipitation from July to September the monthly river discharges are found to increase from December to August and decrease in September and October. Extreme values of precipitation and river discharge are examined and the level of the highest precipitation and the highest river discharge events are estimated to increase. The precipitation amount exceeded 0.1% of all days increases by an average of 7%, the river discharge exceeded 0.1% of all days increases approximately 15%. The 100-year flood is modelled to increase 11% on average.
HEC-RAS River Analysis System, Hydraulic Reference Manual, US Army Corps of Engineers
- Hydrologic Engineering Usace
- Center
USACE, Hydrologic Engineering Center (HEC), HEC-RAS River Analysis System, Hydraulic Reference Manual,
US Army Corps of Engineers, Hydrologic Engineering Center, Davis (2010).