Huge Challenges

In this series of post specially dedicated to the role playing environmental modelling facing the global environmental change, we analysed different models approaches and the huge challenges facing modellers. Probably the most significant analysis that should carry out regarding to the weaknesses of models, it is the opportunity that those areas give us to improve models.

The huge environmental threat has placed to models in a really significant role. As the title of this blog say, there are enormous challenges for a huge concern. This huge concern has led to an intense global debate and models are giving us day to day more understanding and more accuracy in the prediction about our future and the potential negatives impacts; the threat is real.

As a result of this massive concern, another challenge arises from the necessity to communicate how the different models work and how the outcomes obtained by complex methods should be suitably communicated to stakeholders. This group involves not only decision makers (authorities) but also the global community. All of us are potential affected. A suitable way in this direction it is to include the technical aspect behind environmental modelling in an accessible and clear system for the community and political authorities. For instance, through simplified and interactive web tools or through open public presentations. In this task, as Hall et al. (2014) have argued, a major difficulty has been that students has been educated in technical aspects of models but the normal tools of education in this field have omitted the role of communication.

When specialists are presenting relevant results to communities, the interpretation of results can be influenced by personal biased concerns which give different point of view from a non-technical perspective. The experience of knowing the concerns (even from personal and partial point of view) of potentially affected communities could be highly beneficial for certain elements in the research. 

Finally, it is fundamental to look the future with a clear understanding of models as an abstraction of reality, with strengths and weaknesses. Although the final result is taken from the model, this is finally given by the capacity of the modeller to interpret those outcomes in a particular modelling context.

Real-Time Floods Monitoring

I found a really interesting article about an innovative flood monitoring system. The Global Flood Monitoring System (GFMS) consists in a real-time modelling tool, which is based on a hydrological model working at real-time with the TRMM Multi-satellite Precipitation Analysis (TMPA).

In the web page of GFMS, it is possible to take a look on the interactive real-time inundation maps (see Figure below) updated every 3 hours and it is also available a modelling tool for 4 - 5 days flood forecasting. I’m inviting you to explore this brilliant idea!!. If you want to going deep on this, you should look at the paper of the developed study and some relevant details about the model validation.

Some specific limitations are related to the spatial cover of the model between the latitudes 50°N and 50°S. Also, the estimation does not consider the topography due to anthropogenic interventions (e.g. mining projects). However, this quasi-global model represents an excellent tool that contributes to predict the harmful effect of this natural phenomenon on communities.

The Global Flood Monitoring System (GFMS)

Floods: Ways to Predict the Threat

During the last time, northern UK has suffering serious floods events in populated areas. Precipitation and other meteorological variables have reached historical values leading to huge problems for community. In this context, using modelling tools in order to understand and predict this natural process it is essential in order to anticipate future damages for population.

Hydrological modelling has been essential in this analysis. In effect, varied model approaches based on hydrological theory, such as fluid dynamics technics, have been used to simulate floods dynamics, its natural origins and also the effect of climate change on these events. 

Floods in Northern UK, 2015

In some places, floods can be strongly related with snow melt dynamics. Therefore, snowmelt models based on hydrological modelling principles have been widely developed in order to predict future disasters. In addition, some economic activities such as forest harvesting have also been recognized as a determining factor which could contribute to negative impacts in the natural runoff patterns. 

An interesting study partly funded by the Provincial Government of Salzburg was carried out in the Alpine basins. According with the nature of floods events in that area, the researchers included the snowmelt dynamics in a novel real-time flood forecasting. In the Alpine, the snow melt has been relevant in runoff processes and flood events. Thus, building and calibrating a model considering suitably this process, it was fundamental to create an efficient flood forecasting tool.

The model, which was calibrated with monitoring data of precipitation and temperature for the period 1999 – 2005, it was applied on the Salzach watershed. Due to the modelled area has a surface of 600 km², this was divided in 10 sub-basins.

According to the outcomes, even though the model shows some limitations in the snow depth and snow cover simulations, the runoff seasonal behaviour was represented with a significant accuracy. The Figure below presents the modelled runoff in comparison with the observed data for 2004 and 2005.

Runoff Estimation: Ovserved v/s Simulated  

This study case shows a significant contribution due to the ability to predict a natural hazard. In cases such as in the UK, where precipitation is playing a fundamental role in these natural events, using hydrological models including local precipitation dynamics represents a relevant tool for risk management. Therefore, a great challenge of environmental modelling facing the climate change, it is not only the understanding and prediction of this hugely complex phenomenon but also to join this effort with other fundamental disciplines for population welfare, such as urban planning and natural risk-hazard management.