Ekstremer i avrenning under klima endringer, hvordan kan vi anvende resultater fra JOVA - programmet Pros and cons of using INCA and SWAT for modelling the effects of mitigation measures: tillage, fertilization, buffer strips and wetlands The Bioforsk and NIVA SeaLink Team: Csilla Farkas, Johannes Deelstra, Per Stålnacke, Line Barkved, Tuomo Saloranta, Øyvind Kaste, Richard Wright

Ekstremer i avrenning under klima endringer, hvordan kan vi anvende resultater fra JOVA - programmet INCA-N model (flow, nitrate and ammonium)  Brazil, Denmark, England, Finland, France, Netherlands, Norway, Spain, Sweden, Wales INCA-SED (sediment transport and erosion)  Denmark, England, Finland, Norway INCA-P  England, Finland (is being parameterized for Skuterud at the moment) INCA-C  England, Finland Other version for heavy metal transport etc.  Romania Aquatic Environments Research Centre, Dep. of Geography, Univ. of Reading INCA and EURO-Limacs European Projects

Ekstremer i avrenning under klima endringer, hvordan kan vi anvende resultater fra JOVA - programmet INCA model: process-based semi-distributed model of the N-cycle in the plant/soil and in-stream systems dynamic INCA simulates at a daily time-step water flow and storage soil, N and P export from different land-use types within a river system in-stream SS, nitrate, ammonium, total P and dissolved P concentrations Catchment hydrology: direct runoff soil zone groundwater zone

Ekstremer i avrenning under klima endringer, hvordan kan vi anvende resultater fra JOVA - programmet Driving variables in daily time-step INCA Daily estimates of water discharge and SS, NO 3, NH 4, TP, TDP concentrations in river water Average annual riverine load of N, P or SS Soil loss and N and P- balance elements for different land use types soil moisture deficit hydraulically effective rainfall air temperature actual precipitation Model parameters sub-catchment reach in-stream land-phase general parameters

Ekstremer i avrenning under klima endringer, hvordan kan vi anvende resultater fra JOVA - programmet In-stream cell Hydraulically effective rainfall Soil zone Groundwater zone Soil surface Percolation =  * q sz Transport to stream = (1 –  * q sz Transport to stream = q gz Cell Model Land component Precipitation Evaporation Surface runoff to stream

Ekstremer i avrenning under klima endringer, hvordan kan vi anvende resultater fra JOVA - programmet The INCA models are semi-distributed the location-specific mitigation measures can not be directly introduced in the model The models calculate for 6 different land use groups, but their retentions and losses are assumed of that of a “box” Management options, that can be considered in the INCA models  soil tillage (timing (directly), tillage systems (indirectly))  mineral fertilization, manure – directly (timing and amount)  deposition – directly  channel or river bed changes, effecting the instream retention capacity – indirectly  wetlands – as a separate land use class, YES, as an accumulator of losses from other land use sectors – NO  vegetation buffer zones – NO  sedimentation ponds – NO

Ekstremer i avrenning under klima endringer, hvordan kan vi anvende resultater fra JOVA - programmet  incorporation of vegetation buffer zones directly  incorporation of sedimentation ponds  incorporation of wetland retention  advanced calculation of winter conditions (freezing – thawing cycles)  uncertainty analyses tool for INCA-SED and INCA-P

Ekstremer i avrenning under klima endringer, hvordan kan vi anvende resultater fra JOVA - programmet Several models have been tested for Norwegian catchments  SWAT (water balance, nutrient and soil loss) The SWAT model has also been applied in Norway as part of EuroHarp and Striver, two EU – projects (large scale). The model is tested now in Skuterud. Needs modification (saturation from below, subsurface drainage, winter)  DRAINMOD, developed at NCSU (Skaggs) simulating subsurface drainage/surface runoff/nitrogen dynamics  HBV – model (hydrology)  INCA – model (hydrology, nutrient dynamics)  SOIL/SOIL_NO and COUP (hydrology,nitrogen); have been tested (developed by SLU)  AgriCat

Ekstremer i avrenning under klima endringer, hvordan kan vi anvende resultater fra JOVA - programmet Step 1. Start a model journal Step 2. Set up a modelling project Step 3.Select and set up the model – Benchmark criteria Step 4. Analyse the model (sensitivity analyses & calibration) Step 5. Using the model (simulations & uncertainty analyses) Step 6. Interpret the results Step 7. Report Van Waveren et al., Good modelling practice. A handbook.

Ekstremer i avrenning under klima endringer, hvordan kan vi anvende resultater fra JOVA - programmet Benchmark criteria (Saloranta et al., 2003) provides a structured way to evaluate the suitability of model codes to be used in decision making Evaluation: 14 questions, 3-level scoring system model’s output Q1.1. How well does the model’s output relate to the management task? spatio-temporal resolution Q1.2. How well does the model’s span and spatio-temporal resolution compare with the requirements of the task? tested Q1.3. How well the model has been tested? (under conditions of the study site) complicated Q1.4. How complicated is the model in relation to the task? input data data availability Q1.5. How is the balance between the model’s input data and data availability? acceptancescientific theory Q1.8. How is the peer acceptance for the model with scientific theory? adaptation Q3.5. How is the model’s flexibility for adaptation and improvements? Saloranta, T.M et al., Benchmark criteria: a tool for selecting appropriate models in the field of water management. Environmental Management 32,

Ekstremer i avrenning under klima endringer, hvordan kan vi anvende resultater fra JOVA - programmet physically based main processes 1. The model has to provide physically based description of the main processes governing erosion and phosphorus leaching from agricultural catchments input requirements 2. Model output input requirements of the MyLake model 3. Time 3. Time resolution /fine enough to follow process dynamics but avoiding robustious calculations/ 4. Spatial 4. Spatial resolution / fine enough to consider incorporation of different land use types but considering, that only integrated values from the particular catchment are needed/ 5. Applicability 5. Applicability for physico-geographical conditions of Southern Norway 6. Available dataset 6. Available dataset and information driving variables; model parameters

Ekstremer i avrenning under klima endringer, hvordan kan vi anvende resultater fra JOVA - programmet  Evaluated model codes are presented in a Table  Evaluation is connected to the following management/modelling task: „Describing surface water runoff formation and nutrient mobilisation in the Vansjø lake catchment in order to provide appropriate input data for the MyLake model and to analyse response of the whole system to future environmental changes using climate change scenarios.” (???)  MyLake model non-meteorological driving variables: o Inflow volume [m 3 d -1 ] o Inflow temperature [C o ] (can be set as missing value) o Inflow concentration of the passive tracer [-] o Inflow concentration of the passive sedimenting tracer [-] o Inflow concentration of dissolved inorganic phosphorus (phosphate) [mg m -3 ] o Inflow concentration of chlorophyll a [mg m -3 ] o Inflow concentration of particulate phosphorus [mg m -3 ]

Ekstremer i avrenning under klima endringer, hvordan kan vi anvende resultater fra JOVA - programmetKIWASWATDrainModHBVINCA-P Soil_NO COUP AgriCat? Q1.1. How well does the model’s output relate to the task? Q1.2. How well does the model’s spatio-temporal resolution compare with the requirements of the task? Q1.3. How well the model has been tested under conditions in focus? Q1.4. How complicated is the model in relation to the task? Q1.5. How is the balance between the input data and data availability? Q1.8. How is the peer acceptance for the model with scientific theory? Q3.5. How is the model’s flexibility for adaptation and improvements? Possible answers: Good; Adequate; Inadequate

Ekstremer i avrenning under klima endringer, hvordan kan vi anvende resultater fra JOVA - programmet

MeasuresSWATINCA Spatial resolutionHRU levelLand use level (max. 6 or 7 classes) Land use Very detailed, at HRU level Land use level (max. 6 or 7 classes) Soil management (type and timing) Fertilisation and manure timing and amount Crop rotationno Point sourcesIdentified locationYES Sedimentation pondsAs located reservoirsNO WetlandsAs separate land use class, detailed As a separate land use class Vegetation buffer zonesYes (?)NO Defining measures according to soil P_AL or erosion class YESNO

Ekstremer i avrenning under klima endringer, hvordan kan vi anvende resultater fra JOVA - programmet DEM map Soil mapLanduse map 36 subbasins 1869 HRU’s SWAT INCA Spatial resolution

Ekstremer i avrenning under klima endringer, hvordan kan vi anvende resultater fra JOVA - programmet Management, crop rotation SWAT Winter wheat May10Harrowing August25Harvesting September15Ploughing September20Fertilising October1Planting

Ekstremer i avrenning under klima endringer, hvordan kan vi anvende resultater fra JOVA - programmet AspectsSWATINCA Time to build up a projectrobustmoderate Data requirementhugemoderate Uncertainty analyses and calibration tools SWAT-CUP Only for INCA-N, developing for INCA-P Computer capacity requesthugesmall Available literaturehugemoderate Contact with the developers greatgood Model selection – particular case NO model can substitute the experts knowledge BUT Any model, used on a wise way – understanding its strengths and weaknesses - can be a useful tool in decision making