ABSTRACT
Pollution with excess nutrients deteriorate the water quality of the Baltic Sea. The effect of combined land use and climate scenarios on nitrate leaching and nitrogen (N) loads to surface waters from two Baltic Sea catchments (Norsminde in Denmark and Kocinka in Poland) was explored using different models; the NLES and Daisy models for nitrate leaching, and MIKE SHE or MODFLOW/MT3DMS for N transport. Three Shared Socioeconomic Pathways (SSP1, SSP2 and SSP5) defined change in land use and agricultural activities. The climate change scenarios covered 2041-2060 compared with 1991-2010 under RCP8.5, applying four different climate models. Increases in predicted N-load from climate change vary from 20 to 60% depending on climate model. SSPs moderate these N-load changes with small changes for SSP1 to large increases for SSP5, with greater increases for Norsminde than Kocinka due to land use differences. This stresses needs for new measures and governing schemes to meet sustainability targets.
Subject(s)
Agriculture , Nitrates , Climate Change , Conservation of Natural Resources , Denmark , PolandABSTRACT
The ability to simulate regional precipitation realistically by climate models is essential to understand and adapt to climate change. Due to the complexity of associated processes, particularly at unresolved temporal and spatial scales this continues to be a major challenge. As a result, climate simulations of precipitation often exhibit substantial biases that affect the reliability of future projections. Here we demonstrate how a regional climate model (RCM) coupled to a distributed hydrological catchment model that fully integrates water and energy fluxes between the subsurface, land surface, plant cover and the atmosphere, enables a realistic representation of local precipitation. Substantial improvements in simulated precipitation dynamics on seasonal and longer time scales is seen for a simulation period of six years and can be attributed to a more complete treatment of hydrological sub-surface processes including groundwater and moisture feedback. A high degree of local influence on the atmosphere suggests that coupled climate-hydrology models have a potential for improving climate projections and the results further indicate a diminished need for bias correction in climate-hydrology impact studies.