Nature as the “Natural” goal for water management : a conversation.

The goals for water-quality and ecosystem integrity are often defined relative to “natural” reference conditions in many water-management systems, including the European Union Water Framework Directive. This paper examines the difficulties created for water management by using “natural” as the goal. These difficulties are articulated from different perspectives in an informal (fictional) conversation that takes place after a workshop on reference conditions in water-resources management. The difficulties include defining the natural state and modeling how a system might be progressed toward the natural, as well as the feasibility and desirability of restoring a natural state. The paper also considers the appropriateness for developing countries to adopt the use of natural as the goal for water management. We conclude that failure to critically examine the complexities of having “natural” as the goal will compromise the ability to manage the issues that arise in real basins by not making the ambiguities associated with this “natural” goal explicit. This is unfortunate both for the western world that has embraced this model of “natural as the goal” and for the developing world in so far as they are encouraged to adopt this model

Modeling spatial patterns of saturated areas: a comparison of the topographic wetness index and a dynamic distributed model

Topography is often one of the major controls on the spatial pattern of saturated areas, which in turn is a key to understanding much of the variability in soils, hydrological processes, and stream water quality. The topographic wetness index (TWI) has become a widely used tool to describe wetness conditions at the catchment scale. With this index, however, it is assumed that groundwater gradients always equal surface gradients. To overcome this limitation, we suggest deriving wetness indices based on simulations of distributed catchment models. We compared these new indices with the TWI and evaluated the different indices by their capacity to predict spatial patterns of saturated areas. Results showed that the modelderived wetness indices predicted the spatial distribution of wetlands significantly better than the TWI. These results encourage the use of a dynamic distributed hydrological model to derive wetness index maps for hydrological landscape analysis in catchments with topographically driven groundwater tables

Cross-regional prediction of long-term trajectory of stream water DOC response to climate change

There is no scientific consensus about how dissolved organic carbon (DOC) in surface waters is regulated. Here we combine recent literature data from 49 catchments with detailed stream and catchment process information from nine well established research catchments at mid- to high latitudes to examine the question of how climate controls stream water DOC. We show for the first time that mean annual temperature (MAT) in the range from −3° to +10° C has a strong control over the regional stream water DOC concentration in catchments, with highest concentrations in areas ranging between 0° and +3° C MAT. Although relatively large deviations from this model occur for individual streams, catchment topography appears to explain much of this divergence. These findings suggest that the long-term trajectory of stream water DOC response to climate change may be more predictable than previously thought

Forecasters priorities for improving probabilistic flood forecasts.

Hydrological ensemble prediction systems (HEPS) have in recent years been increasingly used for the operational forecasting of floods by European hydrometeorological agencies. The most obvious advantage of HEPS is that more of the uncertainty in the modelling system can be assessed. In addition, ensemble prediction systems generally have better skill than deterministic systems both in the terms of the mean forecast performance and the potential forecasting of extreme events. Research efforts have so far mostly been devoted to the improvement of the physical and technical aspects of the model systems, such as increased resolution in time and space and better description of physical processes. Developments like these are certainly needed; however, in this paper we argue that there are other areas of HEPS that need urgent attention. This was also the result from a group exercise and a survey conducted to operational forecasters within the European Flood Awareness System (EFAS) to identify the top priorities of improvement regarding their own system. They turned out to span a range of areas, the most popular being to include verification of an assessment of past forecast performance, a multi-model approach for hydrological modelling, to increase the forecast skill on the medium range (>3 days) and more focus on education and training on the interpretation of forecasts. In light of limited resources, we suggest a simple model to classify the identified priorities in terms of their cost and complexity to decide in which order to tackle them. This model is then used to create an action plan of short-, medium- and long-term research priorities with the ultimate goal of an optimal improvement of EFAS in particular and to spur the development of operational HEPS in general

The Use of DEM-Based Approaches to Derive a Priori Information on Flood-Prone Areas

Knowing the location and the extent of areas exposed to floods is the most basic information needed for planning flood management strategies. Unfortunately, a complete identification of these areas is still lacking in many countries. Recent studies have highlighted that a significant amount of information regarding the inundation process is already contained in the structure and morphology of a river basin. Therefore, several geomorphic approaches have been proposed for the delineation of areas exposed to flood inundation using DEMs. Such DEM-based approaches represent a useful tool, characterized by low cost and simple data requirements, for a preliminary identification of the flood-prone areas or to extend flood hazard mapping over large areas. Moreover, geomorphic information may be used as external constraint in remote-sensing algorithms for the identification of inundated areas during or after a flood event