DSD-INT 2015 - The river basin explorer – Marieke Fennema, Witteveen+Bos, Clara Chrzanowski,...

The River Basin Explorer A modelling tool for river basin planning in Turkey

Clara Chrzanowski (clara.chrzanowski@deltares.nl) &

Marieke Fennema (marieke.fennema@witteveenbos.com)

Delft Software Days 2015

November 2nd 2015

Bűyűk Menderes catchment

E. Meijers E. Meijers

Water body classes

Artificial

Heavily modified

Natural

Basin: 24873 km²

E. Meijers

E. Meijers

INDUSTRIES Largeherds.co.nz AGRICULTURE

RESERVOIRS E. Meijers

River Basin Explorer

0D-RIBASIM

GIS maps

Networks

Meteo

Flow

Hydrology Ecology

Species

EQR

EKF

Ecological

knowledge rules

PUNN

WFD-Explorer

Loads

Substances

Processes

Water Quality

WFD Explorer schematization

Emissions

Retention

Workflow of modelling activities

WFD Explorer schematization

Hydrology

(RIBASIM) Domestic Industrial Diffuse

Model

results Monitoring data

Calibrate, validate

Import

flows

Ecological

Module

Ecological

Key Factors

Measures

Ecology

Hydrology

RIBASIM is a water balance tool, able to match water demands and

supplies.

Objective: to prepare the hydrological input for the WFD-Explorer

providing

• flow through all the WFD water bodies

• In a dry, a wet and a normal year

• On a quarterly basis

Used in WFD-Explorer:

• To calculate transport of pollutants

• To assess difference between natural and artificial flow regime

RIBASIM – WFD-Explorer coupling

Water bodies = Surface water

units

WFD Explorer schematization

Hydrology

(RIBASIM) Domestic Industrial Diffuse

Emissions

Model

results Monitoring data

Calibrate, validate

Import

flows

Retention

Ecological

Module

Ecological

Key Factors

Measures

Water Quality

Ecology

Water Quality

Domestic Industrial Diffuse

Emissions

Animal/ or manure

Land use

Fertilizer

Septic tanks

Treated sewer water (WWTP)

Untreated sewer water

Industrial plants

Regulation tables

• steady state

• Σ Qin = Σ Qout

• Σ Min = Σ Mout + Mretention

• simplified first order decay processes to model retention processes

• seasonal intervals of 4 seasons per year

Point sources Diffuse sources

Focus on nitrogen, phosphorus and COD

WFD Explorer schematization

Hydrology

(RIBASIM) Domestic Industrial Diffuse

Emissions

Model

results Monitoring data

Calibrate, validate

Import

flows

Retention

Ecological

Module

Ecological

Key Factors

Measures

Water Quality

Ecology

Calibration (1): TP

1. Hydrological analysis:

• Add flows per capita in RIBASIM

• Minimal outflow of Cine reservoir

Calibration (2): TP

2. Time dependent diffuse sources

• They come with the runoff of the land

• Peak in winter season

Calibration (3): TP

3. Add decay:

• First order decay for TN, TP and COD (k =0.01 d-1)

• Related to residence time

Calibration (4): TP

4. Add temperature:

• Decay is dependent on water temperature:

k = k20 * theta(T-20) with theta = 1.047

Monitoring locations for validation/calibration

WQ Results Downstream: near Soke

WQ Results Upstream: Denizli tributary

07-21-00-002

TN: Modeled (2010) vs. Observed (2010)

Factor = Modelled / Observed:

• Green: good aggreement

• Pink: Moderate aggreement

(underestimate)

• Red: Bad agreement (underestimate)

WFD Explorer schematization

Hydrology

(RIBASIM) Domestic Industrial Diffuse

Emissions

Model

results Monitoring data

Calibrate, validate

Import

flows

Retention

Ecological

Module

Ecological

Key Factors

Measures

WQ and Ecology

Ecology

Ecological knowlegde rules WFD-Explorer

EQR = f (KF) Ecological quality ratio : WFD (0-1) expression of ecological quality for

different biological groups (fish, macrophytes, algae, ...)

Key factors for ecology: most determining factors for ecological water

quality (country specific Turkey, NL)

Function calculated with the use of a deep learning network

-PUNN (product unit neural network)

-Regression trees

-Standard neural network

Predicts the effect of

measures

Ecological knowlegde rules WFD-Explorer

EQR = f (KF) Ecological quality ratio : WFD (0-1) expression of ecological quality for

different biological groups (phytoplankton, phytobentos, macro-

invertebrates, macrophytes, fish)

Water Framework Directive:

European directive on

(ecological) water quality

Ecological knowlegde rules WFD-Explorer

PUNN: product-unit neural network

(deep lakes)

K

F

E

Q

R

Training set and validation set

Ecological knowlegde rules WFD-Explorer

Work steps to derive ecological knowledge rules:

- Water types clustering (enough data)

- Key factors for ecology

- Gather EQR data (WFD monitoring) and build up a data matrix

- PUNN calculations to determine ecological knowledge rules

- Expert validation

- Implementation in the WFD explorer

Ecological knowlegde rules WFD-Explorer

Water type clustering & key factors for ecology

Turkish ecology experts from:

Universities

Ministry

Monitoring departments

Water institutes

Several experts sessions to determine

which measurable factors influence eco-

logical water quality the most, and to

define clusters of water types

Ecological knowlegde rules WFD-Explorer

Water type clustering & key factors for ecology

rivers lakes

fast flowing , high rivers

fast flowing perma-nent low

fast flowing temporal low

Slow flowing rivers

Deep lakes (saline and fresh)

COD X X X X X

Temperature X X X X

tot-N X X

tot-P X X

Modifications X X X X

Conductivity X X

Toxic elements X X X X X

Artificial flow regime

X X X X

Suspended solids X X X X X

Ecological knowlegde rules WFD-Explorer

Results:

Phyto-plankton

Phyto-benthos

Macro-phytes

Macro invertebrates

Fish

Deep lakes -

Fast flowing high rivers ++ ++ +

Fast, low and permanent rivers

++ +/- +

Slow flowing rivers ++ +/- + +

Fast, low and temporal rivers

++ + +

Ecological knowlegde rules WFD-Explorer

EQR at slow flowing rivers

Training set Test set perc. inside 0.10

RMSE coeff. of determ.

perc. inside 0.10

RMSE coeff. of determ.

Phytobenthos 92 % 0.044 0.94 83 % 0.064 0.89

Conclusions of the Buyuk Menderes project

• Data availability and accessibility is an issue!

• First step in creating a River Basin Management model

• Model is not perfect can be improved

• Hydrological improved rainfall runoff concepts

• Emissions and water quality use of monitoring data of point

sources

• Ecology enhanced EKF, more data to train PUNN

• Model can be used to:

• Evaluate relative contribution of different sources

(domestic/industrial/agriculture)

• Identify and evaluate measures

Stakeholder process

• Explanation use of models in water resource management

• Dutch water board: use of WFD-Explorer in Dutch measure

strategies

• Use of model to determine strategies with stakeholders

Questions

?