Friedrich-Schiller-Universität JenaInstitut für Geographie

Lehrstuhl für Geoinformatik, Geohydrologie und Modellierung

UPPER GERA WATERSHED (GERMANY)AREAL ASSESSMENT OF WATER-QUALITY MONITORING

Marcel Wetzel Holm Kipka Daniel Varga Manfred Fink

QAND ASSOCIATED MODEL APPLICATION

Marcel Wetzel, Holm Kipka, Daniel Varga, Manfred Fink, Sven Kralisch, Peter Krause, W.-A. Flügel

INTRODUCTION

o The ILMS - project (Integrated Landscape Management System) y )

o Provide a modular structured software system

• Modeling framework JAMS System coreGUI

• Model components based on the hydrological model J2000

o One of the key components is the nutrient transport

Model parametrization

Model design Libraries•Data types

model J2000_S

Component libraryh d l l

yp•Core functions (I/O, …)•Core model components

JAMS – modeling framework

M d l d i ti (XML)

Runtime system•Model setup•Model execution•Component communication

(hydrological processes, statistical analysis, GUI components, …)

J2000 - hydrological model

J2000_GW – groundwater surface water interaction moduleJ2000_S – nutrient transport module

Knowledge representation

Model description (XML)J2000_E_P – erosion and phosphorus moduleJ2000_WQ – water quality module

J2000_S - HRU DELINEATION

• The scalable Response Unit Topography Response Unit distribution concept allows process oriented

GISOverlay

Landuse, land-cover

oriented classification of catchments without l f i t t

Soil-types

Hydrogeology

loss of important information

• Combined with a topological routing scheme vertical and lateral processes can

Flügel, 1996Bongartz, 2001

lateral processes can be modeled fully distributedStaudenrausch 2001

J2000_S PROCESS BASED N-MODEL

Driving data: P, T, …ET Additional drivers: Radiation …

Plant GrowthModuleH

arve

st

Interception SnowBiomass

Rooting depth

Mod

ule

H

Unsaturated zoneRunoff

Surface ROInfiltration DPS

MPS LPSNHRU 1 HRU 2 HRU 3Soil Temperature

LAI

agem

ent

Mrt

iliza

tion

Interflow 1

Interflow 2

MPS LPS

MPS LPS

MPS LPS

N

N

HRU 1

HRU 4

HRU 2 HRU 3

HRU 5

Soil Temperature Module

ndus

e M

an Fer

Soil Nitrogen Module

Saturated zone

Upper zone

Interflow 2

Baseflow

MPS LPS N

NHRU 6

Lan

llage

Soil Nitrogen Module

Nitrification

Denitrification

Volatilisation Upper zone

Lower zone

Reach 1 Reach 3

Reach 2

Ti Volatilisation

Plant uptake

UPPER GERA TEST SITE

Thuringian Forest: 400 to 980 m a.s.lP = 1200 mm

Sandstone Woodland:400 to 600 m a.s.lP = 550 – 800 mmP 550 800 mm

Limestone Plate:300 to 600 m a.s.lP = 550 – 750 mm

Central ThuringianFarmland:200 to 400 m a.s.lP = 500 600 mmP = 500 – 600 mm

J2000 MODEL RESULTS

160

180 observed runoffsimulated runoff

100

120

140Reff = 0.74; lnReff = 0.75

³/s

60

80

100

m³

20

40

0

.11.

1993

.05.

1994

.11.

1994

.05.

1995

.11.

1995

.05.

1996

.11.

1996

.05.

1997

.11.

1997

.05.

1998

.11.

1998

.05.

1999

.11.

1999

.05.

2000

01 01 01 01 01 01 01 01 01 01 01 01 01 01

Observed and simulated runoff (m³/s) at the gauge station Erfurt-Moebisburg (catchment outlet)

J2000_S MODEL RESULTS

14000

16000

10000

12000

4000

6000

8000

0

2000

Jan. Jul. Jan. Jul. Jan. Jul. Jan. Jul. Jan. Jul. Jan. Jul.Jan.

95

Jul.

95

Jan.

96

Jul.

96

Jan.

97

Jul.

97

Jan.

98

Jul.

98

Jan.

99

Jul.

99

Jan.

00

Jul.

00

simulated kg N/d observed kg N/d

Observed and simulated N-loads (kg/d) at the gauge station Erfurt-Moebisburg (catchment outlet)

FURTHER MODEL DEVELOPMENT

JAMS – modeling framework

J2000 - hydrological model

J2000_S – nutrient transport moduleJ2000_GW – groundwater surface water interaction moduleJ2000_E_P – erosion and phosphorus moduleJ2000 WQ t lit d l

o The application of water quality models is often confronted

J2000_WQ – water quality module

o pp q ywith a poor basis of calibration and validation data

o Thus a measurement network was installed to provide data f id tifi ti lib ti d lid ti f for process identification, calibration and validation of water quality models in the mesoscale

o We expect from the use of these field data a substantial o We expect from the use of these field data a substantial improvement of the quality and the reliability for our process-modeling system

MEASUREMENT NETWORK: water quality (1)

Online stations(15 minutes)

• Total Phosphorus• Total Phosphorus• Nitrate• Ammonium• TOC/CSB• Dissolved Oxygen• Dissolved Oxygen• pH• Electrical

conductivity• Turbidity• Turbidity• Suspended solids• Temperature• Redox Potential• Runoff• Runoff

MEASUREMENT NETWORK: water quality (2)

Online stations(15 minutes)

• Total Phosphorus• Total Phosphorus• Nitrate• Ammonium• TOC/CSB• Dissolved Oxygen• Dissolved Oxygen• pH• Electrical

conductivity• Turbidity• Turbidity• Suspended solids• Temperature• Redox Potential• Runoff• Runoff

MEASUREMENT NETWORK: water quality (3)

Sample points(monthly)

T t l Ph h• Total Phosphorus• Nitrate• Nitrite• Ammonium

TOC• TOC• CSB• Dissolved Oxygen• pH

Electrical • Electrical conductivity

• Turbidity• Calcium

Magnesium• Magnesium• Temperature• Redox-Potential• Potassium

MEASUREMENT NETWORK: water quality (4)

chemical water quality classification of the germanfederal states working group (LAWA 1998)federal states working group (LAWA 1998)

Quality class

Color assignment

description NH4-N(mg/l)

NO3-N(mg/l)

Total P(mg/l)

I No anthropogenic pollution:Geogenic background

≤ 0,04 ≤ 1 ≤ 0,05

I – II Very low pollution:Up to half the target value

≤ 0,1 ≤ 1,5 ≤ 0,08

II Moderate pollution:Compliance of the target value

≤ 0,3 ≤ 2,5 ≤ 0,15

II – III Significant pollution:Up to twice the target value

≤ 0,6 ≤ 5 ≤ 0,3

III Increased pollution:Up to four times the target value

≤ 1,2 ≤ 10 ≤ 0,6

III – IV High pollution:Up to eight times the target value

≤ 2,4 ≤ 20 ≤ 1,2Up to eight times the target value

IV Very high pollution:Greater then eight times the targetvalue

> 2,4 > 20 > 1,2

MEASUREMENT NETWORK: water quality (5)

qualityclass

colorassignmentg

I

I – II

IIII

II – III

III

III – IV

IV

90th percentile total phosphorus (January 2008 until November 2009)90th percentile NO3-N (January 2008 until November 2009)

MEASUREMENT NETWORK: water quality (6)

o The measurement network was designed to capture the influences of the different landscape types on the water p ypquality

o The first results show that the most important influences of landscape on the water quality could be identified of landscape on the water quality could be identified

o The data gathered from this measurement network will be used for further model development and validationp

JAMS – modeling framework

J2000 - hydrological modelJ2000 hydrological model

J2000_S – nutrient transport moduleJ2000_GW – groundwater surface water interaction moduleJ2000_E_P – erosion and phosphorus module_ _ p pJ2000_WQ – water quality module

J2000_E_P FIRST RESULTS

Present work:• The erosion module is also integrated in theJ2000 HRU linkage approachJ2000 HRU linkage approach

• For the calculation of sediment yield theModified Universal Soil Loss Equation (MUSLE)with a dynamic surface runoff factor is usedwith a dynamic surface runoff factor is used

• The equation calculates sediment yield / soilloss from every rainfall event and in everytemporal resolution

Soil loss (t/ha/yr)

Future work:• The integration of the phosphorus cycle forSoil loss (t/ha/yr)

00 – 11 – 5050 – 100

The integration of the phosphorus cycle forthe calculation of phosphorus loads

> 100

Thank you for your attention!

AcknowledgementgThe authors wish to thank the German Federal Ministry of Education andResearch for funding this work in the course of the program”Entrepreneurial Regions – the BMBF Innovation Initiative for the Newp gGerman Länder