Small-scale hydrological modelling

How do we get ahead of the fast flood?

Hydrological processes operate at different scales, depending on the size and character of the river basin. In large and predominantly rural basins, rainfall and snow melt over a large area are slowly transformed into discharge. It takes a long time (days, weeks) for contributing water from peripheral locations to reach the river and spatial variations over the basin are smoothed out over time. In small and especially urban basins, the process is much faster and the discharge response to rainfall or snow melt can happen in hours or even minutes. The response is highly sensitive to spatial variations, in particular the exact location of high or extreme rainfall intensities.

In the focus area small-scale hydrological modelling, we work towards improving our understanding and description of hydrological processes and flood risk in small and fast-responding basins. This work is largely based on exploring how high-resolution geographical data bases as well as hydro-meteorological observations and simulations can be utilized to develop systems and tools for small-scale hydrological analysis, modelling and risk assessment. The activities involve innovative types of observations (for example, rainfall from microwave link networks and private weather stations), big data (for example, from national hydrological and hydrodynamic models as well as climate models) and new methodology (for example, neural networks and other types of AI).

Real-time event and long-term planning

Generally, we work with two perspectives or time horizons; real-time event and long-term planning. With real-time event we mean the management of single floods and in this respect we work towards providing society with decision support before, during and after the flood. Exemples of activities involved include the following:

  • Before the flood: Processing and interpretation of different types of rainfall forecasts, translation of the rainfall forecasts into discharge and inundation through high-resolution hydrological and hydro-dynamic simulation, etc.
  • During the flood: Observation of rainfall with high temporal and spatial resolution in real time, facilitation of “situation awareness” through visualization and communication, etc.
  • After the flood: Integration of rainfall observations from different sensors (for example, stations, weather radar and microwave links) into optimized and quality-assured products, open access provision of data and simulations for post-event analysis, etc. 

In terms of long-term planning, our general target is to provide society with best possible decision support for design and construction of infrastructure and components that are sensitive to small-scale hydrological impacts. Examples of activities include the following:

  • Estimation of rainfall and discharge extremes in present climate, including long return periods (that is, very unusual events), regional variations and concurrent events (that may enhance overall risk and damage).
  • Climate change impact assessment, by using high-resolution climate model output to estimate small-scale hydrological climate change impacts in terms of, for example, surface runoff and flood risk.
Prototype of an app for visualization of extreme short-duration rainfall in observations and forecasts.
Prototype of an app for visualization of extreme short-duration rainfall in observations and forecasts. Enlarge Image

Research and Development questions

  • How can we make best use of high-resolution rainfall observations, forecasts and climate projections for small-scale hydrological impact assessment? 
  • How can we develop and integrate hydrological and hydro-dynamic models for better flood forecasting and risk assessment?
  • How can we provide society with the best possible support both at real-time events – before, during and after the flood – and for long-term planning – in present and future climate?

Our core publications in this Scientific focus

Olsson, J., Bengtsson, L., Pers, B.C., Berg, P., Pechlivanidis, I., and H. Körnich (2017) Distance-dependent depth-duration analysis in high-resolution hydro-meteorological ensemble forecasting: a case study in Malmö, Sweden. Environ. Model. Softw., 93, 381-397, doi.org/10.1016/j.envsoft.2017.03.025.

Olsson, J., Arheimer, B., Borris, M., Donnelly, C., Foster, K., Nikulin, G., Persson, M., Perttu, A.-M., Uvo, C.B., Viklander, M., and W. Yang (2016) Hydrological climate change impact assessment at small and large scales: key messages from recent progress in Sweden, Climate, 4, 39, doi.org/10.3390/cli4030039.

Berg, P., Norin, L., and J. Olsson (2016) Creation of a high resolution precipitation data set by merging gridded gauge data and radar observations for Sweden, J. Hydrol., 541, 6-13, doi.org/10.1016/j.jhydrol.2015.11.031.      

Olsson, J., Berg, P., and A. Kawamura (2015) Impact of RCM spatial resolution on the reproduction of local, sub-daily precipitation, J. Hydrometeorol., 16, 534–547, doi.org/10.1175/JHM-D-14-0007.1

Rana, A., Foster, K., Bosshard, T., Olsson, J., and L. Bengtsson (2014) Impact of climate change on rainfall over Mumbai using Distribution-Based Scaling of Global Climate Model projections, J. Hydrol. Reg. Stud., 1, 107-128, doi.org/10.1016/j.ejrh.2014.06.005.

Olsson, J., and K. Foster (2014) Short-term precipitation extremes in regional climate simulations for Sweden, Hydrol. Res., 45.3, 479-489, doi:10.2166/nh.2013.206.

Olsson, J., Simonsson, L., and M. Ridal (2014) Rainfall nowcasting: predictability of short-term extremes in Sweden, Urban Water J., 11, https;//doi.org/10.1080/1573062X.2013.847465.

Olsson, J., Amaguchi, H., Alsterhag, E., Dåverhög, M., Adrian, P.-E., and A. Kawamura (2013) Adaptation to climate change impacts on urban flooding: a case study in Arvika, Sweden, Clim. Chang., 116, 231-247, doi.org/10.1007/s10584-012-0480-y.

Olsson, J., Gidhagen, L., Gamerith,  V., Gruber,  G., Hoppe,  H., and P. Kutschera (2012) Downscaling of short-term precipitation from Regional Climate Models for sustainable urban planning, Sustainability, 4, 866-887, https;//doi.org/10.3390/su4050866.

Amaguchi, H., Kawamura, A., Olsson, J., and T. Takasaki (2012) Development and testing of a distributed urban storm runoff event model with a vector-based catchment delineation, J. Hydrol., 420–421, 205-215, doi.org/10.1016/j.jhydrol.2011.12.003.

Olsson, J., Willén, U., and A. Kawamura (2012) Downscaling extreme Regional Climate Model (RCM) precipitation for urban hydrological applications, Hydrol. Res., 43, 341-351, doi.org/10.2166/nh.2012.135.

Olsson, J., Berggren, K., Olofsson, M., and M. Viklander (2009) Applying climate model precipitation scenarios for urban hydrological assessment: a case study in Kalmar City, Sweden, Atmos. Res., 92, 364-375, doi.org/10.1016/j.atmosres.2009.01.015.