RegCM for the estimation of flood risk maps: providing driving data for the CHyM hydrological model

1.0 - Observations

We have access to several Italian observational datasets provided by the University of L'Aquila for:

• temperature
• precipitation
• water level
• discharge

~2000-2017

only!

1.1 - Observations

Outliers

1.2 - Observations

FIRST-STAGE FILTERING

FLAGGING

FLAG CHECKING

CLEANED DATASET!

1.3 - Observations

First-stage filtering procedures

• Removal of extreme values > 200 mm/h
• Removal of isolated > 100 mm/h reports
• Removal of complete months with > 1800 mm (2.5 mm/h)
• Removal of continuous identical values

1.4 - Observations

Flagging procedures

• Mean + n*SD threshold
• Median + n*IQR threshold
• Peaks in the values distribution
• Isolated dry/wet event flagging
• Low correlation of close stations

Results so far...

(by applying first-stage filtering procedures only)

1.5 - Observations

FILTERED

ORIGINAL

1.6 - Observations

1.7 - Observations

2.0 - Regional Climate Models

How to reproduce 200-years floods with just ~15 years of precipitation data?

Statistical analysis helps, but a longer time period is required

RegCM as driving data for the CHyM hydrological model

EURO-CORDEX Simulations (thanks James Ciarlo`!):

• RegCM 4.6.1 (ERA-Interim driven) 1979-2016
• RegCM 4.6.1 (HadGEM driven) 1971-2100 (WIP)

2.1 - Regional Climate Models

First, a basic validation of the data:

• 4 regions
• 2000-2016
• precipitation only

Available datasets:

• RegCM-ERA-In (12km)
• RegCM-HadGEM (12km)
• Italian OBS data (~12km)
• E-OBS (~25km)
• EURO4M-APGD (~5km)
• CHIRPS (~5km)
• ...

2.2 - Regional Climate Models

2.3 - Regional Climate Models

2.4 - Regional Climate Models

3.0 - Cetemps Hydrological Model

CHyM Is a distributed (gridded) hydrological model. Peculiarities:

• Can build DEM from various sources, smoothing by cellula automata algorithms
• Can use several kind of inputs, such as station observations, gridded model data, etc.
• Designed to work on any domain
• NetCDF output
• Maintained at the ICTP by Fabio Di Sante

3.1 - Cetemps Hydrological Model

3.1 - Cetemps Hydrological Model

Creating the river network is sometimes easier said than done...

Real Po river

CHyM simulation 1

CHyM simulation 2

3.2 - Cetemps Hydrological Model

Sanity check:

can we reproduce river basins?

3.2 - Cetemps Hydrological Model

Sanity check: skill of the model driven with the observations

3.6 - Cetemps Hydrological Model

Sanity check: how does the model assimilate RegCM's precipitation?

3.5 - Cetemps Hydrological Model

How does the model perform if driven with RegCM, compared with if driven with observations? (Liguria example)

CHyM (RegCM-driven)

CHyM (OBS-driven)

3.6 - Cetemps Hydrological Model

3.6 - Cetemps Hydrological Model

How does the model perform if driven with RegCM, compared with if driven with observations? (Central-South Italy example)

3.6 - Cetemps Hydrological Model

3.7 - Cetemps Hydrological Model