Aggregation of soil and climate input data can underestimate simulated biomass loss and nitrate leaching under climate change

Predicting areas of severe biomass loss and increased N leaching risk under climate change is critical for applying appropriate adaptation measures to support more sustainable agricultural systems. The frequency annual winter wheat its coincidence with an increase in a temperate region Germany was estimated including the error from using soil input data at coarser spatial scales, soil-crop model CoupModel. We ran reference period (1980–2010) used predicted by four model(s) Representative Concentration Pathways (RCP) 2.6, 4.5 8.5. median estimations showed that 2070–2100, RCP8.5 scenario, entire would suffer almost every year. Annual incidence RCP4.5 8.5 scenario. During 2070–2100 RCP8.5, than half years area 95% projected both leaching. SPEI3 range 32 (P3 RCP4.5) 55% RCP8.5) episodes simulated scenarios. simulations losses SPEI index which indicates water deficits are important determining crop future There overestimating where “no + leaching” occurred when aggregated data. In contrast, underestimation situations “severe Larger differences compared finest resolution aggregating rather were even larger region, could be erroneously single year 40% if results suggest higher especially needed predict reliably estimates