Remote sensing and measuring technology in coupling of process-based catchment and lake models (Catch_Lake)
Topic and objectives
In the Catch_Lake project (2006?2007), funded by Tekes (Finnish Funding Agency for Technology and Innovation), integrated use of process-based catchment and lake models is developed by i) utilizing remote sensing technology, and ii) by intensive measurements with water quality sensors coupled with wireless data transmission technology. Satellite images are used together with other sources of observation data in environmental modeling. On the other hand, spot sampling is used for quality assurance and evaluation of the remote sensing data. Lake Pyhäjärvi (154 km2) in Säkylä is a highly valuable lake in terms of water supply and recreational use, and serves as the pilot area of the project together with its 306 km2 catchment.
Mathematical models produce information for the support of decision-making. Models help to understand the processes and mechanisms of ecosystems, and they can be used for testing of scientific hypotheses, as well as for evaluations of optional scenarios on e.g. how to reduce the environmental loading cost-efficiently. The exploitability of the models not only depends on the validity of the incorporated processes, but also on the available input data.
Catch_Lake is a joint venture project between Finnish Environment Institute (SYKE) and the Laboratory of Space Technology of the Helsinki University of Technology (TKK). The project has direct links with i) the research made in the EU's 6th Framework Programme (Euro-limpacs project), ii) with the GMES (Global Monitoring of Environment and Security) programme coordinated by EU and ESA, and iii) with GSE Land Information Services of ESA.
Fig 1. Säkylän Pyhäjärvi (154 km2), together with its 306-km2 catchment, serves as the pilot area of the project
The project is divided into two subtasks, (1) Catchment and (2) Lakes 1. The development of process-based modelling in catchments (SWAT, INCA)
In the Catchment ?subtask, integrated catchment models (SWAT and INCA) are developed and applied. The models will be compared in order to quantify the uncertainties. Moreover, the intensive long-term measurements will be utilized from the selected local research catchments, where effects of agriculture on nutrient and sediment loading are studied.
SWAT is a GIS-based catchment model developed in the USA. It can be used for simulations of nutrient and sediment transport from catchments with a 1-h timestep. The basic input data consists of three types of GIS data; (i) elevation, (ii) soil type and (iii) land use. Based on these data, a channel network with sub-catchments will be created. The functioning of the model and the validity of the process descriptions will be evaluated against the local intensive measurements. A special attention will be paid for the significance of the coastal areas of the lake ("close-catchments" from where waters discharge directly into the lake instead of a distinct major channel), contributing to the total loading into the lake.
INCA-N is a dynamic, process-based nitrogen model for simulations of nutrient leaching and the underlying factors at catchment-scale. The INCA model takes into account all major sources of nutrients and simulates the transformation processes, nutrient pathways, water flow and nutrient concentrations in selected spots along a river channel. The model is being developed and applied jointly with the Euro-limpacs project. Also here the water quality data obtained from the intensive measurements will be utilized. Moreover, the new EU Corine Land Cover data will be applied with the INCA modeling.
 
Fig. 2. Clorophyll-a indicates the spatial variation of phytoplankton biomass (Luode Consulting Oy). 2. Spatial water quality and modelling of the lake
Spatial water quality (turbidity/suspended solids, chlorophyll-a) maps of the Lake Pyhäjärvi will be constructed by interpretations of the time series of satellite images taken from the lake. This will be accomplished by the interpretation algorithms developed at SYKE and TKK, for the observations made with American (NASA) MODIS and the European (ESA) MERIS instruments. The time series data of water quality will be produced with the data assimilation algorithms developed by TKK. The algorithms are able to integrate the satellite data with any relevant in situ observations in a mathematically optimized way.
High resolution spatial measuring means here measurement technology, where water quality variables (measurements of absorption and attenuation, fluorometric measurements, and measurements of temperature, conductivity and turbidity) are determined from a rapidly moving boat with GPS, in order to efficiently cover a large area during a short period of time. The collected information will be compared with the data obtained by remote sensing technology.
LakeState is a non-linear, dynamic lake model that is based on the balances of macronutrients and the phytoplankton kinetics. With LakeState, the response of biological variables to nutrient loading will be simulated. The model calculates the concentrations of total P and total N in water column as well as the processes between water and sediment. Lake modeling will be developed for utilization of the water quality time series obtained from the satellite images, which are available on an almost-daily basis. Related publications
Coherens 3D Water Quality Model, a poster (pdf, 279 kb)
ELLS - poster (pdf, 569 kb)
Aquatox - ecolocigal risk assessment model (ppt, 953 kb)
Bärlund, I., Kirkkala, T. Malve, O. and Kämäri, J. Assessing SWAT model performance in the evaluation of management actions for the implementation of the Water Framework Directive in a Finnish Catchment.Environmental Modelling and Assessment (in press)
Ekholm, P., Malve, O. & Kirkkala, T. 1997. Internal and external loading as regulators of nutrient concentrations in the agriculturally loaded lake Pyhäjärvi (southwest Finland). Hydrobiologia 345: 3-14.
Koponen S., Pulliainen J., Kallio K., Hallikainen M. 2002. Lake water quality classification with airborne hyperspectral spectrometer and simulated MERIS data. Remote Sensing of Environment, 79(1): 51-59.
Wade, A.J., Durand, P., Beaujouan, V., Wessels, W.W., Raat, K.J., Whitehead, P.G., Butterfield, D., Rankinen, K. & Lepistö, A. 2002. A nitrogen model for European ecosystems: INCA, new model structure and equations Hydrology and Earth System Sciences 6: 559-582. More information
Project head: Senior researcher, Dr Ahti Lepistö, SYKE, firstname.lastname@ymparisto.fi
Project liaison: Doc. Timo Huttula, SYKE Jyväskylä unit, firstname.lastname@ymparisto.fi
Space Technology/TKK: Prof. Jouni Pulliainen, firstname.lastname@hut.fi, Lic. Sampsa Koponen
Pyhäjärvi Protection Fund: Project manager Marjo Tarvainen
Lounais-Suomen vesi- ja ympäristötutkimus Oy, Executive director Teija Kirkkala
Luode Consulting Oy, Dr Mikko Kiirikki
AERC, University of Reading, Dr Andrew Wade
Project group: Hydrologist Sirkka Tattari SYKE/VTO, Senior researcher Ilona Bärlund SYKE/PTO, Lic. Kirsti Granlund SYKE/VTO, Research engineer Jari Koskiaho SYKE/VTO, Research engineer Olli Malve SYKE/VTO, Special planner Timo Pyhälahti SYKE/GEO, Senior Researcher Pekka Härmä SYKE/GEO, Senior researcher Kari Kallio SYKE/ITO
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