WATER QUALITY MODELING DR. YANTI

LECTURE SERIES Dep. of Geography, Yogyakarta State University

Dr SRI ADIYANTI School of Earth & Environment, Fac. of Science UWA

LECTURE DAY-4

Introduction to Lake Hydrodynamic Water Quality Modelling

DAY 1: ENVIRONMENTAL HYDROLOGY Introduction: Environmental Hydrology Water Balance Rainfall Spatio-temporal Variability DAY 2: LINKAGE CATCHMENT-RIVER-ESTUARINE-OCEAN Case Study: Caboolture River Basin in Queensland

DAY 3: FIELD EXCURSION – WADUK SERMO DAY 4: A : INTRODUCTION TO LAKE HYDRODYNAMIC WATER QUALITY MODELLING: Case Study Waduk Sermo & Group Presentation B : HOW TO GET SCHOLARSHIP & WORK PROFESSIONALLY OVERSEAS

AGENDA: 3-DAY LECTURE + EXCURSION

WHY DO WE NEED A WATER QUALITY MODEL ?

Water Quality Models as ‘Virtual Environmental Laboratories’

• Reconcile theory with observation

• Improve system understanding:

– Quantify processes and controls on variability – Risk assessments – Conduct system budgets (eg. nutrients, metals) – System feedbacks & non-linearity

• Assess management interventions (eg. scenarios):

– Flushing/diversions – Chemical amelioration or bio-manipulation – Engineering interventions (pumping; destratification)

• Real-time prediction:

– Water quality alerts & risk assessment – Fore-casting

The problem we need to solve

light salinity

phytoplankton

zooplankton

CO2 NO3-

PO42-

O2 fish

bacteria

detritus

temperature

Management questions …

• How are the regulated/assimilated once they enter

surface waters? – Physical (hydrodynamic) vs ecological controls

• How do changes in catchment nutrient export manifest

in water bodies?

• Can we unravel this complexity to improve science-basis of load targets?

The modelling process

• Defining your domain – For GLM: Height-Storage relationship (Bathymetry)

• Define what is being simulated:

– Identify state variables (temperature, salinity, nutrients?) – What is the grid resolution & time-step

• Connecting to the external environment:

– Setting boundary conditions: • Inflows (flow, temp, salinity, wq attrobutes) • Meteorology

• Getting ready to start: providing an initial condition

WHAT TYPE OF MODEL SHOULD WE USE?

Empirical models of water quality response ….

• Vollenweider and statistical relationships

Control

+P

Vollenweider example • Annual catchment loading (mass/yr): catchment export

• Waterbody surface area: Larger water bodies will be less affected by a particular P load

than smaller lakes.

• Mean depth of the lake/waterbody: Deeper systems, with more capacity to dilute phosphorus inputs, will be less affected by increased P loads than shallower systems

• Residence Time: Waterbodies that hold water for less time (lower residence time) will be less affected by increased P loads than lakes with long residence times.

• Example: Using a Vollenweider loading model, what would be the expected eutrophication status of a lake with the following conditions ?

• Mean Depth: 5 m • Lake Area: 800,000 m2 (80 ha) • P loading to the lake: 160 kg/yr (160,000 g P/yr) • Water residence time in the lake: 0.25 yrs. Compute Y axis:(P loading)/(lake area) = (160,000 g P/yr)/(800,000 m2) = 0.2 g P/m2/yr Compute X axis value:(Mean depth/Residence Time) = (5 m)/(0.25 yrs) = 20 m/yr Lake is expected to display water quality in the Oligotrophic Zone.

GLM – General Lake Model

… process-based models

• Resolve the complex biogeochemical processes + • Superimposed on a the dynamic physical

environment

From: OzCoasts website

Model Dimension

• 0D – mixed ‘container’, one grid box – Assumes the lake is a ‘bathtub’, ie, homogenous conditions

• 1D – a single dimension is resolved

– rivers: narrow and shallow river, row of grid cells – lakes: layers of cells to resolve vertical stratification

• 2D – shallow lake or coastal lagoon,

2D matrix of grid cells (can be vertically averaged or laterally averaged)

• 3D – wide and deep river, lake or coastal area with vertical stratification, usually a 3D matrix of grid cells

Basic idea of numerical modeling

t

1) Divide area into smaller sub-areas (grid cells)

2) Solve flow and other processes in each grid cell

3) Connect grid cells through transport, diffusion and other processes

Connection between grid cells

Qin Qout

Qw

Horizontal (left) and vertical (right, Qw) transport between grid cells

• Conservation of Mass • Control volume in changes reflect inputs and outputs • Includes inflows/withdrawals

• Conservation of Momentum • Velocity based on balances of forces • Bed slope, elevation differences (gravity) • Depth gradient (pressure slope) • Friction (based on drag with bed / vegetation etc) • Rotation of earth for large domains (coriolis)

Physical Basis Basis for flow and transport models

TUFLOW-FV – www.tuflow.com

Finite volume – complex environments

Connecting our domain to the surrounding environment

Modelling Lake Stratification

surface mixing surface fluxes

artificial destratification

1D – laterally averaged models: assume most variability is vertical

The General Lake Model (GLM

T density

Inflow Surface fluxes

mixing

Model Inputs: • Discharges: Inflow & Outflow • Meteorology: solar radiation, long-wave radiation, air temperature, wind

speed and direction, humidity

CASE STUDY: WADUK SERMO, Kulon Progo

• Temperature profiles • pH Profiles • Dissolved Oxygen profiles

For validation:

Waduk Sermo

Waduk Sermo

Lake Water Balance Component

INFLOW

OUTFLOW

EVAP

ORA

TIO

N

RAINFALL

Bathymetry (Area-Storage-Elevation Relationship) / Kurva Karasteristik

GROUP I: WATER BALANCE GROUP II: OUTFLOW DISCHARGE MEASUREMENT GROUP III: PHYSICO-CHEMICAL PROPERTY MEASUREMENT

GROUP PRESENTATION: