Simulating the hydrology of the Sole (Sun) Valley The SteepStream perspective

Riccardo Rigon, Stefano Tasin, Michele Bottazzi, Francesco Serafin & Marialaura Bancheri

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SteepStream Annual Meeting, Lisbon, October 6th, 2017

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Objective

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To study some basin taken as prototype in the project. Get they hydrology

right and, eventually, determine the solid transport, besides the water

transport, as a function of the foreseen climate change.

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Hydrometers

Meteo stations

River network

Catchment boundary

Legend

0 2.5 5 7.5 10 km

The Area

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The Real Area

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Why we do not study the smallest, Meledrio, basin ?

Because:

•we do not have appropriate data for the basin (so far)

•it is too small for having reliable projection of

forcings.

Therefore we study the whole Noce basin closed at Malè and then,

downscale/ and or specialise to Meledrio.

We’ll also try to assess errors in estimates.

Why the whole area ?

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Now assume to have a river network

Consider the path starting in A1, for example. It can be decomposed into steps (states)

and we can write the water budget for each of them.

River Networks

We are using, an planning to use, spatially semi-distributed, time-

continuous models

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This paths can be described by a graph whose diagrams is

River Networks

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The squares are fluxes

The ball is a storage

This is the corresponding equation*

*Usually they are ordinary differential equations but they could be also partial differential equations

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A little of explanationThe full story @ Rigon & Bancheri, 2017

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The full network interactions can be represented as follows

River Networks

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Actually any “ball” (reservoir) can be exploded in parts (further graphs = further ODEs)

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Embedded networks of reservoirs

!12*Image from Li, H., Hydrological consequences of climate change in Scandinavia, 2014

*

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Embedded networks of reservoirs

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Time continuous vs event based

Traditional studies on hydraulic construction refers to event-based modelling.

This is normed in the concept of return period and is based on the assumed stationarity of climate*

*Milly, P. C. D., Betancourt, J., Falkenmark, M., Hirsch, R. M., Kundzewicz, Lettenmaier, D. P., & Stouffer, R. J. (2008). Stationarity Is Dead: Whither Water Management? Science, 319, 1–2. See also: Serinaldi, F., & Kilsby, C. G. (2015). Stationarity is undead: Uncertainty dominates the distribution of extremes. Advances in Water Resources, 77(C), 17–36. http://doi.org/10.1016/j.advwatres.2014.12.013

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In any case, our strategy I is to simulate

1. long series of climate forcing (hundreds of years) using Breinl’s Weather Generator

2. for several times 3. the hydrological cycle of the Sole-Non valleys

From them

4. Extract relevant events and estimating their statistics 5. Cope with uncertainties 6. Feed with those results hydraulic modelling

Time continuous vs event based

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Multimodel

We do not use a single model

but at least two (three) submodels based on GEOFRAME components

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Marialaura Bancheri – A TRAVEL TIME MODEL FOR WATER BUDGET OF COMPLEX

CATCHMENTS

add further calibration parameters and complexities. Baseflow

from the groundwater is modeled using a non-linear reservoir.

Total runoff is the sum of the direct runoff and of the baseflow.

Figure 3.2 represent the embedded reservoir model using the

time-varying Petri-nets. Each place has been implemented in a

different component, in order to give the maximum flexibility of

connections. Therefore, five different components forming a MS

were used for each HRU in which the domain was discretized.

Figure 3.2: Representation of the embedded reservoir model using time-varying Petri-Nets. Five components are storage, snow, canopy, rootzone, surface flow, and groundwater, which are represented throughcircles of different colors and specifications. Snow storage is repre-sented using two overlapped circles, since it solved two coupled ODEs.Each storage has been implemented into a different Jgrass-NewAgecomponent.

The detailed representation of each reservoir using PN, together

with the table of associations and of symbols are discussed in

the following sections.

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ERM model

Embedded Reservoirs Model

Bancheri, M, A flexible approach to the estimation of water budgets and its connection to the travel time theory, Ph.D. Dissertation, 2017 Bancheri, N, Serafin, F. and R. Rigon, Travel time consequences of different modeling schemes, in preparation, 2017

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Marialaura Bancheri – A TRAVEL TIME MODEL FOR WATER BUDGET OF COMPLEX

CATCHMENTS

add further calibration parameters and complexities. Baseflow

from the groundwater is modeled using a non-linear reservoir.

Total runoff is the sum of the direct runoff and of the baseflow.

Figure 3.2 represent the embedded reservoir model using the

time-varying Petri-nets. Each place has been implemented in a

different component, in order to give the maximum flexibility of

connections. Therefore, five different components forming a MS

were used for each HRU in which the domain was discretized.

Figure 3.2: Representation of the embedded reservoir model using time-varying Petri-Nets. Five components are storage, snow, canopy, rootzone, surface flow, and groundwater, which are represented throughcircles of different colors and specifications. Snow storage is repre-sented using two overlapped circles, since it solved two coupled ODEs.Each storage has been implemented into a different Jgrass-NewAgecomponent.

The detailed representation of each reservoir using PN, together

with the table of associations and of symbols are discussed in

the following sections.

42

ERM model

Embedded Reservoirs Model

Bancheri, M, A flexible approach to the estimation of water budgets and its connection to the travel time theory, Ph.D. Dissertation, 2017 Bancheri, N, Serafin, F. and R. Rigon, Travel time consequences of different modeling schemes, in preparation, 2017

Snow modelling

Canopy

Root zone/

Shallow GroundwaterHydrological Routing

Groundwater

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HBV model

Seibert, J., & Vis, M. J. P. (2012). Teaching hydrological modeling with a user-friendly catchment-runoff-model software package. Hydrology and Earth System Sciences, 16(9), 3315–3325. http://doi.org/10.5194/hess-16-3315-2012

Hydrologiska Byråns Vattenavdelning

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HBV model

Seibert, J., & Vis, M. J. P. (2012). Teaching hydrological modeling with a user-friendly catchment-runoff-model software package. Hydrology and Earth System Sciences, 16(9), 3315–3325. http://doi.org/10.5194/hess-16-3315-2012

Hydrologiska Byråns Vattenavdelning

Snow

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Soil/Canopy

Shallow Groundwater Hydrological

routing

Groundwater

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A few slides on OMS

OMS Object Modelling System version 3

http://oms.colostate.edu/

David et al.

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Figure 5.7: Schema of the connection of the JGrass-NewAge components, necessaries to perform the modelling solution: the bluarrows represents the connection out-to-in made possibile thanks to OMS3.

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Schemes of work inside OMS

When you really deploy, they appear

hidden modelling parts

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A few slides on OMS

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Details upon request

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Where to find details

The full story @ Rigon & Bancheri, 2017b and @Rigon et Al., 2017

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Source code OMS projects

Community blog Documentation

Manca Mailing list

General Information

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Methods

We estimate the whole hydrological cycle budgetMarialaura Bancheri – A TRAVEL TIME MODEL FOR WATER BUDGET OF COMPLEX

CATCHMENTS

Figure 5.12: Waterfall charts of the relative contributes of the waterbalance for the canopy, root zone and groundwater reservoirs. Greenbars represent the inputs of the storage, blu bars represents the outputsand red bars represent the change in storage. Two selected month,March 1994 and September 1994, are shown in order to compare theannual variability of each contribute.

Plot like like Figure 5.12and 5.13 can be produced for any of the

HRU, for any hour or more aggregated temporal scale.

Figure 5.13 shows the daily total actual evapotranspiration

(evaporation from the wet canopy plus evapotranspiration from

the root zone) in selected days of the years. As it is clear from the

maps, the AET does not vary much over the year. This situation

is common to many other places in humid areas, (Lewis et al. ,

2000; Oishi et al. , 2010). Some HRUs presents values of AET

always smaller than the rest of the basins. This is mainly given to

a lower net radiation input and, thus, a lower ETP. The lower net

radiation is due to a different exposition of the HRU and a lower

sky-view factor (0.6). Since the evaporation from the wet canopy

doesn’t represent an important contribute to the total AET, the

spatial variability of the canopy cannot be appreciated.

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Bancheri, M, A flexible approach to the estimation of water budgets and its connection to the travel time theory, Ph.D. Dissertation, 2017

for any reservoir, actually. Closing the budget thought necessary for an accurate assessment of fluxes and runoff. Especially in view of climate projections.

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Methods

Standard procedure:

• calibration first • projection (driven by the weather generation)

eventually

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Very first trials: the whole basin

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Very first trials: the whole basin

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Very first trials: Meledrio

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Very first trials: Meledrio

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Very first trials: Meledrio

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Suppose for end of March 2018 or before we have solved all the calibration issues, and and

made the simulations required what we could do next (besides projections):

• We give our hydrography (for channels where debris flow or sediment transport happens) to our friends to do hydraulic of sediment transport

• We can move to evaluate sediment production outside channels

For this we need a different type of modeling (os, as a minimum, idealise some sub-grid processes)

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Beyond that

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GEOtop 2.0 ?

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In What GEOtop is different ?

Snow height, density, temperature)Freezing Soil - Permafrost

Zanotti et al, 2004; Dall’Amico et al., 2011

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GEOtop 2.0 ?

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Some relevant references:

Giuseppe, F., Simoni, S., Godt, J. W., Lu, N., & Rigon, R. (2016). Geomorphological control on variably saturated hillslope hydrology and slope instability. Water Resources Research, 52(6), 4590–4607. http://doi.org/10.1002/2015WR017626

Formetta, G., Capparelli, G., David, O., Green, T., & Rigon, R. (2016). Integration of a Three-Dimensional Process-Based Hydrological Model into the Object Modeling System. Water, 8(1), 12–15. http://doi.org/10.3390/w8010012

Simoni, S., Zanotti, F., Bertoldi, G., & Rigon, R. (2008). Modelling the probability of occurrence of shallow landslides and channelized debris flows using GEOtop-FS. Hydrological Processes, 22(4), 532–545. http://doi.org/10.1002/hyp.6886

Lanni, C., Borga, M., Rigon, R., & Tarolli, P. (2012). Modelling shallow landslide susceptibility by means of a subsurface flow path connectivity index and estimates of soil depth spatial distribution. Hydrology and Earth System Sciences, 16(11), 3959–3971. http://doi.org/10.5194/hess-16-3959-2012

Endrizzi, S., Gruber, S., Dall'Amico, M., & Rigon, R. (2014). GEOtop 2.0: simulating the combined energy and water balance at and below the land surface accounting for soil freezing, snow cover and terrain effects. Geoscientific Model Development, 7(6), 2831–2857. http://doi.org/10.5194/gmd-7-2831-2014

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GEOtop about landslides

!36Simoni, S., Zanotti, F., Bertoldi, G., & Rigon, R. (2008). Modelling the probability of occurrence of shallow landslides and channelized debris flows using GEOtop-FS. Hydrological Processes, 22(4), 532–545. http://doi.org/10.1002/hyp.6886

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Further data for GEOtop

!37Simoni, S., Zanotti, F., Bertoldi, G., & Rigon, R. (2008). Modelling the probability of occurrence of shallow landslides and channelized debris flows using GEOtop-FS. Hydrological Processes, 22(4), 532–545. http://doi.org/10.1002/hyp.6886

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To obtain something like this

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As paper testifies, we have the tools for doing it since quite a long time. However,

• Numerics we use now is much more refined with respect to ten years ago

• Geotechnics is better and based on new theories by Ning Lu • Possibly we could use a new model, say GEOtop-w, which uses

even more refined algorithms, derived from recent numerical work by colleagues.

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This we can already do (in principle)

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Some missing steps:

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This we have to solve

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Moving sediment to the channel network

Adding it to the flood

See which effects it has to the flood waves

Some missing steps:

This we have to solve

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Find this presentation at

http://abouthydrology.blogspot.com

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Other material at

Questions ?

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