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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
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