Economic-Ecological Principles and the Question of Mineral Waters in Brazil

The present study addresses the issue of mineral waters in Brazil, its institutional problem, and the consequences and conflicts arising from its irrational exploitation. As a solution to these problems and conflicts, it is proposed to integrate these mineral waters and their different types in the management of water resources and the application of guiding economic and ecological principles as in the case of the conception of post-normal science and the precautionary principle. To meet the objective, the authors opted for an exploratory and bibliographical research regarding the adopted procedure. It is concluded that the implementation of an institutional change will allow a participative and polycentric management, mainly at the level of the hydrographic basin committees, which will contribute to the application of the two mentioned principles and a sustainable management of this resource. However, there is a need for improvements in the national water resources policy to more effectively cover groundwater in which mineral waters are embedded.

VIRTUAL WATER POTENTIAL OF SELECTED COMMODITIES IN CO-OPERATION OF THE SLOVAK REPUBLIC WITH COUNTRIES OF THE WESTERN BALKANS

Our paper rests on two fundamentals: firstly, the EU's initiative to deepen cooperation with and the prospect of its enlargement to the Western Balkans region; and, secondly, the urgency to address sustainable development issues in the international environment. As the virtual water perspective represents an innovative approach in the field of sustainable development, the aim of our paper is to analyse trade-related characteristics based on the water footprint concept (complementary to the alternative RCA/RTA indexes designed to calculate a country's comparative advantage or disadvantage). In our paper, we analyse and evaluate selected commodities traded by the Slovak Republic and the Western Balkans countries in terms of the absolute/comparative advantage related to the national water footprints.

A Comparison of National Water Model Retrospective Analysis Snow Outputs at SNOTEL Sites Across the Western U.S.

This study compares the U.S. National Water Model (NWM) reanalysis snow outputs to observed snow water equivalent (SWE) and snow-covered area fraction (SCAF) at SNOTEL sites across the Western U.S. SWE was obtained from SNOTEL sites, while SCAF was obtained from MODIS observations at a nominal 500 m grid scale. Retrospective NWM results were at a 1000 m grid scale. We compared results for SNOTEL sites to gridded NWM and MODIS outputs for the grid cells encompassing each SNOTEL site. Differences between modeled and observed SWE were attributed to both model errors, as well as errors in inputs, notably precipitation and temperature. The NWM generally under-predicted SWE, partly due to precipitation input differences. There was also a slight general bias for model input temperature to be cooler than observed, counter to the direction expected to lead to under-modeling of SWE. There was also under-modeling of SWE for a subset of sites where precipitation inputs were good. Furthermore, the NWM generally tends to melt snow early. There was considerable variability between modeled and observed SCAF as well as the binary comparison of snow cover presence that hampered useful interpretation of SCAF comparisons. This is in part due to the shortcomings associated with both model SCAF parameterization and MODIS observations, particularly in vegetated regions. However, when SCAF was aggregated across all sites and years, modeled SCAF tended to be more than observed using MODIS. These differences are regional with generally better SWE and SCAF results in the Central Basin and Range and differences tending to become larger the further away regions are from this region. These findings identify areas where predictions from the NWM involving snow may be better or worse, and suggest opportunities for research directed towards model improvements.

Evaluation of a New Observationally Based Channel Parameterization for the National Water Model

Accurate representation of channel properties is important for forecasting in hydrologic models, as it affects height, celerity, and attenuation of flood waves. Yet, considerable uncertainty in the parameterization of channel geometry and hydraulic roughness (Manning’s n) exists within the NOAA National Water Model (NWM), due largely to data scarcity: only ~2,800 out of the 2.7 million river reach segments in the NWM have measured channel properties. In this study, we seek to improve channel representativeness by updating channel geometry and roughness parameters using a large, previously unpublished hydraulic geometry (HyG) dataset of approximately 48,000 gages. We begin with a Sobol’ sensitivity analysis of channel geometry parameters for 12 small semi-natural basins across the continental U.S., which reveals an outsized sensitivity of simulated flow to Manning’s n relative to channel geometry parameters. We then develop and evaluate a set of regression-based regionalizations of channel parameters estimated using the HyG dataset. Finally, we compare the model output generated from updated channel parameter sets to observations and the current NWM v2.1 parameterization. We find that, while the NWM land surface model holds the most influence over flow given its control over total volume, the updated channel parameterization leads to improvements in simulated streamflow performance relative to observed flows, with a statistically significant mean R2 increase from 0.479 to 0.494 across approximately 7,400 gage locations. HyG-based channel geometry and roughness provide a substantial overall improvement in channel representation over the default parameterization, updating the previous set value for most reaches of Manning’s n = 0.060 to a new range between 0.006 and 0.537 (median 0.077). This research provides a more representative, observationally based channel parameter dataset for the NWM routing module, as well as new insight into the influence of the routing module within the overall modeling framework.