Deliverable 5.5

Abstract: Report on the biophysical catchment-scale modelling of Yläneenjoki –Pyhäjärvi demonstration site

The Finnish demonstration site Lake Pyhäjärvi and its catchment is located in a region where agriculture has traditionally been intensive in comparison to the rest of the country, both in terms of number of active farms and in the importance of agriculture for the regional economy. Lake Pyhäjärvi Lake is the largest lake in south-western Finland. It is shallow and mesotrophic with exceptionally high fish productivity, which makes it an important lake for commercial fishing. Increased eutrophication of the Lake Pyhäjärvi – mostly due to agriculture - has been a major concern since the late 1980s as Cyanobacteria blooms have become more and more frequent.

The ecological response of Lake Pyhäjärvi to projected climate and land use changes has been evaluated by chaining watershed, river and lake models. Within the model chain, the hydrological watershed model WSFS provides boundary conditions for the INCA-P and N catchment/river models, whilst INCA-P output serves as input data to the MyLake lake model. INCA-P and INCA-N output together serves as input data to the Lake Load Response (LLR) model. The model chains seem to work adequately as the results were logical throughout the chain.

Responses to total phosphorus (TP) and chlorophyll-α (chl-a) concentrations are simulated to detect if the changes in air temperature and precipitation due to climate change will enhance algal growth in lakes. In response, a series of measures are hypothesized to decrease algal concentrations. Reducing nutrient loading through different management action improves the likelihood of WFD compliance and better water quality in addition to providing a number of benefits for use of the lake such as recreation, fishing etc. Three climate change scenarios (CC) were used together with four land-use (LU) scenarios and mitigation measures to reduce nutrient loading. Close links were maintained throughout between environment policy researchers and biophysical modellers / process researchers at SYKE, as well as with stakeholders at Pyhäjärvi Institute and elsewhere in the study region.
The land-use change scenarios seem to have a more pronounced impact on the lake than climate change scenarios. But the LU scenarios also implicitly include CC scenarios and it is possible that land-use changes are needed to ‘catalyze’ climate change impacts. The interactions and feedback mechanisms between these changes in the time period of 50 yrs are highly complex with numerous changes in hydrological dynamics, snow/frost conditions in milder winters, catchment and lake processes, cultivation practices and timings, crop types etc.

With regard to management measures, increasing winter vegetation in particular (e.g. 40%) seems to decrease Chl-a while decreasing P fertilization seems to have less of an impact.  The probability of achieving ‘Good’ WFD status in the lake is higher if P is the target variable. With Chl-a as target variable, probabilities are somewhat lower, with a higher chance of obtaining ‘Moderate’ class during certain years. The effectiveness of measures (40% increase in winter vegetation) under future climate change was tested with more scenarios – worst and best cases with and without measures. The worst case equates to the most adverse ecological impact in terms of ecological indicator from land cover plus climate. The best case refers to the least adverse ecological impact, respectively. Based on the model runs the above measure seems to be climate-proof, and even more effective under future climate. The measure did also improved the state of the lake, both under worst and best scenarios.

Link - http://www.refresh.ucl.ac.uk/webfm_send/2161

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