Effects of climate change and agricultural adaptation on nitrogen loading from Finnish watersheds simulated by VEMALA model
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1 Effects of climate change and agricultural adaptation on nitrogen loading from Finnish watersheds simulated by VEMALA model Inese Huttunen 1, Heikki Lehtonen 2, Markus Huttunen 1, Vanamo Piirainen 1, Bertel Vehviläinen 1 1 Finnish Environment Institute SYKE 2 Luonnonvarakeskus LUKE Marisplan project
2 Contents Description of the methodology and VEMALA-N model TN loading results for two rivers Changes in hydrology Changes in TN agricultural loading in Archipelago Sea and Bothnian Bay catchments Changes in TN riverine loading to the different Baltic Sea sub-basins Summary
3 Background: climatechangeimpacton agroclimatic characteristics Longer growing season by an extra days by 2100 The temperature sum during the growing period is forecasted to increase: from 1300 degree days up to 1900 in southern Finland from 1100 up to 1600 degree days in middle parts from 900 up to 1200 degree days in northern Finland. Since the summer precipitation may increase only little, increasing temperature stress and early summer droughts, may become more common Climate change impact on crop growth: longer growing season and higher effective temperature sum will increase the crop yield potential while an increasing number of dry days may significantly reduce crop yield levels and increase their inter-annual volatility the yield potential will be sustained close to the current level if new cultivars are adopted 3
4 MARISPLAN project methodology World price scenarios Climate change scenarios DREMFIA - economic agricultural sector model Land use Fertilizer yield Nutrient VEMALA - nutrient loading model loading Nutrient loading
5 Nutrient loading model VEMALA Version Substance Hydrological model agricultural loading Terrestrial model non-agricultural loading River model Lake model VEMALA 1.1 TP, TN, SS WSFS concentrationrunoff relationship runoff concentration- relationship VEMALA- ICECREAM VEMALA-N TP NO 3 - orgn+nh 4 WSFS, ICECREAM WSFS field scale process based model semi-process based, 5 crop classes concentrationrunoff relationship semi-process based, 1 forest class concentrationrunoff relationship runoff concentration- relationship nutrient transport model nutrient mass balance model
6 VEMALA-N - catchment scale nitrate leaching model Fresh org mineralization Fresh org N 6 Land use/crop classes: spring cereals, winter cereals, root crops, grasslands, forest, green fallow
7 VEMALA-N model processes Nitrogen transformation in the soil Process Equation Reference Parameter Value kg/ha for agriculture kg/ha for forest mineralization nitrfication denitrification immobilization NO 3 = Wade et al.(2002), Johnsson (1990) Wade et al.(2002) This study Wade et al.(2002) M org k min k temp - k soilm - k nitr day -1 for agriculture day -1 for forest M NH day -1 for agriculture, k denitr day -1 for forest day -1 for agriculture day -1 for forest 1.0, if relative soil moisture >80%, k soilmden 0.0, if relative soil moisture 80% M NO3 k immobn day -1 for agriculture for forest day -1 for agriculture = immobilization NH 4 Wade et al.(2002) k immoba for forest Tsoil T1 Rankinen et al. k Q 10 temp = 10, ift soil < T1 (2004) Q 10 2,0-3,0 Soil temperature coef. 2 temp =.0035Tsoil Tsoil 1.165, ift soil > k 0 T 1 This study T soil T 1 20 C =!"#$% & ' ( $% & ))1)+!"#$% & ' ( $% & +, Soil moisture coef. Myers et al. (1982) b 2.1 soil moist wilting p field c from hydrological model, mm mm mm 7
8 VEMALA-N model processes Plant uptake Nitrate leaching Biomass growth B mat input data, kg/m 2 NO 3 plant uptake., (0-0 $1 )2 3 Knisel (1993) C N input data, % NH 4 plant uptake NO 3 fertilizer appl. NH 4 fertilizer appl. Rekolainen and Posch (1993) w Knisel (1993) k NO This study k soilmplup - Karvonen and Varis F undis,no3 - (1992) k d 0.15 day -1 Karvonen and Varis (1992) F undis,nh4 -, =,$1 DDC +E ). ) NO 3 mass balance )F ' )F G ) ) This study Dep NO3 input data, =,$1 DDC D NH 4 mass balance DE )). ) This study Dep NH4 input data Subsurface leaching Groundwater leaching 0 A 3 A 3, + % B0., 1) )(0-0 $1 ) )98:; <8= > )98:; +?.@ C =C 3, C =C 3, F ' 678 D.HID6J6 '% DHK 6J6 '% F % =L % ;9 '% This study This study PUW subs flow 2.0 for cereals, 1.0 for grass, 3.0 for root crops mm from hydrological model, mm US from hydrological model, mm mg/l for agriculture, c gw mg/l for forest 8 from hydrological model, mm gw flow
9 Results-nutrientdaily concentrationand loading for rivers Observatio n point Aurajoki outlet Aurajoki outlet Aurajoki outlet Aurajoki outlet Substance, version Number of observation s NSE load Observe d conc. µg L -1 Simulate d conc. µg L -1 NSE conc. TN VEMALA N TN VEMALA TP VEMALA - ICECREAM TP VEMALA Simulated NO 3- -concentration, mg/l Simulated NO 3- -loading, kg/day
10 Kalajoki river results in Bothnian Bay catchment High spring concentrations on some years due to the two reaons: Warmer soils during the winter on some years (2012), High snow pack/runoff during the spring (2011) Model is not capturing highest concentrations after some winters, can it represent the climate change conditions? Simulated TN -concentration, mg/l Simulated TN -loading, kg/day
11 Scenarios Climate change scenarios: Mean A1B mean of 19 GCM, prec +11.5%, temp +3.2 C Wet (RCA3-HadCM3-A1B), prec +16.2%, temp +2.6 C Dry (HIRHAM-ARPEGE-A1B), prec +4.7%, temp +2.5 C Agricultural change scenarios: The Baseline. In this business as usual scenario unchanged yields and agricultural policy are assumed Successful adaptation (Su_A). In this optimistic scenario yields increase by 30% for cereals and grasslands (0.9% a year) and by 60% for oilseeds and winter cereals in Prices, policies, research and development imply an effective adaptation, including new cultivars suitable for a longer growing season Moderate adaptation (Mo_A). Yields increase linearly by 10% between 2013 and 2050 (0.25% per year). Little adaptation (Li_A). Adaptation is rare even if some individual farms can avoid cereals yield reductions, with the help of some adaptations based on fungicide use and liming. Since adaptations at the farm and crop level are rare, yields decrease by 10% on both cereals and grass. 11
12 Agricultural production and land use development in Finland (DREMFIA results) Adaptation to the climate change influences the amount of fertilization and the resultant yield levels and nutrient balances in the different study areas An example: a) Nitrogen fertilization for barley (kg N/ha) b) Yield level for barley (kg/ha) c) Nitrogen balance for barley (kg N/ha) in different scenarios, Southern Finland, support region B 12
13 Changes in hydrology ( vs ) Runoff is changing from -5%...+17% in Finnihs catchments Evapotranspiration is increasing +5%...+10% in Finnish catchments Runoff Evapotranspiration Runoff, mm/year Mean A1B Wet Dry Evapotranspiration, mm/year Mean A1B Wet Dry
14 Results: nitrate leaching from agricultural areas a largest increase in nitrate leaching per hectare takes place in the little agricultural adaptation scenario, mainly due to higher nitrogen balance in the soils. In the successful adaptation scenario, an increase in the area of spring cereals increases leaching from cultivated areas as to compare to the reference decade. The lowest leaching takes place in the moderate adaptation scenario, because nitrogen balance is only slightly increasing due to the balanced fertilizer use and plant uptake. 14
15 Total nitrogen gross loading from agricultural areas (AS and BS) Archipelago Sea TN loading is changing 0 +36% Bothnian Sea - TN loading is changing % In wet scenario there is more increase, in dry scenario there is a decrease Archipelago Sea Bothnian Sea 8 18 Agricultural loading, 1000 t/year Mean A1B Wet Dry Agricultural loading, 1000 t/year Mean A1B Wet Dry 0 REF M A1B SuA MoA LiA 0 REF M A1B SuA MoA LiA 15
16 Changes in nitrate leaching from different crops In present conditions the highest NO 3 is from cereals than grass crops In agricultural scenarios there are changes in crop division, that effects on the resulting leaching NO 3 leaching, kg ha -1 yr Archipelago Sea REF A1B Li_A Mo_A Su_A Spring cereals Grass Winter cereals Root crops Fallow Crop division, % Archipelago Sea A1B Li_A Mo_A Su_A Fallow Root crops Winter cereals Grass Spring cereals 16
17 Total nitrogen loading from agricultural areas (BB and Baltic Sea) In Bothnian Bay TN loading is decreasing -26%...+4%, because Runoff is increasing the least +3% (M A1B) The main crop is grass, and plant uptake by grass is increasing There is a decrease in manure use in agric. scen. There is increase in denitrification from soils in BB area Bothnian Bay Baltic Sea Agricultural loading, 1000 t/year Mean A1B Wet Dry Agricultural loading, 1000 t/year Mean A1B Wet Dry 0 REF M A1B SuA MoA LiA 0 REF M A1B SuA MoA LiA 17
18 Nitrogen riverine loading into the sea Changes in agricultural loading Changes in natural background leaching + forestry: Loading from non-agricultural areas Changes in retention Table 1. Gross loading of total nitrogen (TN NA ) from non-agricultural land areas Watersheds draining into the different Baltic Sea sub-basins Present TN NA (2001- The share of TN 2010) NA from total N load NO 3 share of total riverine loading 1000 t year -1 % % Vuoksi (VUO) Gulf of Finland (GF) Archipelago Sea (AS) Bothnian Sea (BS) Bothnian Bay (BB) Total
19 TN riverine loading to the Baltic Sea 19
20 How to avoid and mitigate increased nutrient loading Farmers should be encouraged to invest in the adaptation measures: choosing new cultivars, which can utilize the longer growing season in the future and give higher potential yields investing in soil improvements, e.g. by proper drainage system and liming of the soils crop protection. higher fertilizer use will lead to higher leaching of nitrogen in dry years when crop yield is low. Split fertilization has been suggested to apply also to cereal crops To control erosion the steepest fields should be changed from annual crops to perennial vegetation cover. This would be possible in the successful adaptation scenario, as higher yields would allow some of the agricultural area to be left for water protection measures 20
21 Summary General conclusions: The modelling framework to simulate combined effect of climate and agricultural change has been developed and can be used further to simulate the effect of mitigation measures Combined climate and agricultural change is expected to increase nitrogen and phosphorus loading to the Baltic Sea in Mean A1B scenario Higher yields are needed for reducing nutrient balances, and more land should be allocated to water protection programs Limitations of the model / development needs: Model can reproduce the nutrient loading changes caused by runoff changes and changes in nutrient balance in agricultural areas, Can model simulate the effect of temperature and soil moisture changes on soil processes especially during cold season of the year? Processes in the soil needs to be more developed and validated against measurements (river concentrations, mineralization amounts, denitrification amounts), Process based model for forested soils is needed also including leaching of organic N
22 Thank you! 22
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