Results and deliverables
3.1 Large-scale modelling and effect analysis – regional patterns and water quality
High resolution pan-European and Swedish assessment
Results from climate models are down-scaled and bias corrected using the new methods developed in WP2 for . Future water resources are mapped and emerging large-scale patterns are studied as well as changes in extremes.
Modelled changes for a large number of hydrological variables are analysed, such as mean water discharge, return periods of extreme high and low flows, ground water fluctuations, snow cover and soil moisture. The changes over large regions are analysed using rather high resolution to distinguish changes in regional patterns. The results are published in web products covering Sweden and Europe.
In addition, climate change impact on water status is studied. Water quality is reflecting emissions of pollutions but also various biogeochemical processes, water volumes and flow paths. The latter are affected by temperature and precipitation, and thus, climate change.
The HYPE model has been used to evaluate possible changes in nutrient concentrations and transport from land to sea. The climate effect on nutrient reducing remedies and management plans have been studied, for instance by evaluating the Baltic Sea Action Plan (BSAP) from HELCOM for present and future climate conditions. The results have been communicated to end-users within the project ECOSUPPORT.
Finally, HYDROIMPACTS2.0 study uncertainties involved in climate change impact modeling at the large scale, both from the scaling of climate data and from the impact model itself. The applied studies are done in cooperation with other in each model domain and results are published in scientific journals.
Spring flood (Seasonal) forecasting by downscaling large scale circulation patterns
Large scale circulation patterns are the engines that drive the weather at the local scale. It is difficult to find the connection between these phenomena at the higher temporal resolutions of hours or days but they become more apparent when the temporal resolution is decreased towards the seasonal scale.
By using a multivariate statistical model it is possible to make a connection between these large scale circulation variables and river discharge. In northern Sweden winter precipitation is stored in the form of snow and this serves to amplify the connection signal which makes it possible to use the climatic conditions during the winter season to forecast the spring discharge volume with a relatively long lead time.
Future changes in the variability of large scale circulation patterns
By understanding the natural variability characteristics of the large scale circulation patterns that drive the local climate it is possible to make general assumptions about local phenomena such as river discharge. Many of these large scale circulation patterns have two different modes that they oscillate between, i.e. the North Atlantic Oscillation pattern, and studies have shown that there are temporal trends to these oscillations where the circulation pattern tends to have a bias to manifest in one mode or the other both in strength and duration. This is translated into variability trends in local hydrology.
Using a similar approach to that used in the seasonal forecasts, large scale circulation patterns were downscaled to monthly discharges. By using climate model historical runs (represents the climate for 1850-2005) to train the model it is possible to compare the variability in the model outputs driven by both the historical runs and future projections (representing the climate 2006-2100) to say something about the possible changes in the inter-annual variability in the local hydrology of northern Sweden.
Results suggest that future climates will result in changes in the inter-annual variability of the hydrology in northern Sweden. The results for all projections suggest that there will be a decrease in variability-patterns that have a longer period of oscillation while results for projections that employ a RCP (Representative Concentration Pathways) of 8.5 suggest an increase in variability-patterns that have a shorter period of oscillation.
3.2 Small scale modelling and effect analysis
Urban storm water is recognized as a significant source of pollution heavily impacting the water quality of many receiving environments. The quality of storm water depends on several factors, especially the type of land use and precipitation characteristics. If those factors change due to climate change and a higher level of urbanization, it is likely that the quality of storm water change as well.
Climate change is one of the biggest future challenges leading to changed hydrological conditions especially in urban areas. Global climate models show an increasing trend in averaged precipitation over the next century. In the northern part of Sweden the hourly rain fall maxima will increase, especially during spring and autumn. At the same time many areas will face an increased urbanization.
Combined effects of high intensity rain and urbanization will have a dramatic effect on the hydrologic conditions as well as the pollution generation in urban areas. Increasing rainfall intensities and more impervious areas will affect the runoff process being more rapid and creating higher peak flows and will change the transport capacity of pollutants.
Consequently there is an interest in assessing possible future trends in order to develop adaptation strategies and to install suitable and well-designed measures. Such assessment has to be based on computer simulations for different climate change and urbanization scenarios.
The aim is to develop a strategy allowing examining combined effects of climate change and urbanization on simulated storm water quality in Sweden.
Solute transport in unsaturated soil
Transport of contaminants in the unsaturated soil zone poses a threat to clean groundwater resources. A future climate with higher precipitation might increase transport velocities, however, the transport processes in unsaturated soil are highly non-linear. Some of the objectives within the project are to:
- Examine climate effects on solute transport in Swedish agricultural soils
- Quantifying the effect of hysteresis and rainfall input resolution
- Establish relationships between solute transport depth (or velocity) and rainfall patterns, e.g., total volume, number of rain events, maximum rainfall concentration, drought periods using measured rainfall data
- From other WP the agreement between these rainfall patterns for measured and simulated data will be established for current climate
- Simulations will be made using future scenarios, the changes in solute transport depth for future scenarios will be assessed
Effects of hysteresis and rainfall distribution
Simulations were made using the HYDRUS 1D software. Concentration profiles were simulated for 12 summer seasons (1996-2007), with and without considering hysteresis, three soil types and three locations.
Five different rainfall input time steps (dt) were used for soil 1 (0.5, 1, 2, 4, and 24 h), for the other soils only three different time resolutions were used (0.5, 4, and 24). In total 792 simulations were made.
The results of this study are presented in Saifadeen and Gladnyeva (2012). Under non-hysteretic water flow solute migration is faster which in turn means an overestimation of the solute velocity.
Analysis of the downward migration of the solutes indicates that the effect of hysteresis is more pronounced in the coarse textured soils. Results of the simulations also show that during study period, with the measured precipitation input data, there are small amounts of solutes leached into the groundwater. It is also found that the downward migration of solutes is deeper in Petisträsk compared to the other two sites. On the other hand, the transport of solutes in Norrköping is the slowest among the selected sites.
The simulations show that a lower temporal resolution of the meteorlogical input data increases both underestimation of the downward movement of the solutes for non-hysteretic simulations and overestimation for hysteretic ones. Meanwhile, in most cases, this overestimation and underestimation rises with increasing hydraulic conductivity of the soil.
Finally, the analysis of the results displays that the differences between hysteretic and non-hysteretic simulations are negligible when using daily input data. Consequently, we may recommend disregarding the effect of hysteresis when using daily input data.
Read more: Modeling of solute transport in the unsaturated zone using HYDRUS-1D: Effects of hysteresis and temporal variabilty in meteorological input data