Problems of underwater cultural heritage research in the context of the Baltic Sea drainage basin ecology

The article considers key issues of the underwater cultural heritage and the ways to reveal investigate and preserve it. Due to the lack of knowledge of the problem, the authors have developed a method that allows detecting the potential of the object in order to obtain the status of underwater cultural heritage in the future. These eventual objects are based on the UNESCO World Heritage List. The Baltic Drainage Sea is on the top of this List by the total number of these sites. The authors paid great attention to mark the wreck influence on ecological condition of the sea and they noticed the need of environmental monitoring. As a solution of some issues of preserving underwater cultural heritage. The term “ecology of underwater heritage” was proposed, as well as examples of international cooperation on the integration of environmental and archaeological underwater research.

Data-driven scale extrapolation: estimating yearly discharge for a large region by small sub-basins

Large-scale hydrological models and land surface models are so far the only tools for assessing current and future water resources. Those models estimate discharge with large uncertainties, due to the complex interaction between climate and hydrology, the limited availability and quality of data, as well as model uncertainties. A new purely data-driven scale-extrapolation method to estimate discharge for a large region solely from selected small sub-basins, which are typically 1–2 orders of magnitude smaller than the large region, is proposed. Those small sub-basins contain sufficient information, not only on climate and land surface, but also on hydrological characteristics for the large basin. In the Baltic Sea drainage basin, best discharge estimation for the gauged area was achieved with sub-basins that cover 5% of the gauged area. There exist multiple sets of sub-basins whose climate and hydrology resemble those of the gauged area equally well. Those multiple sets estimate annual discharge for the gauged area consistently well with 6 % average error. The scale-extrapolation method is completely data-driven; therefore it does not force any modelling error into the prediction. The multiple predictions are expected to bracket the inherent variations and uncertainties of the climate and hydrology of the basin.

Data-based discharge extrapolation: estimating annual discharge for a partially gauged large river basin from its small sub-basins

Large-scale hydrological models and land surface models are by far the only tools for accessing future water resources in climate change impact studies. Those models estimate discharge with large uncertainties, due to the complex interaction between climate and hydrology, the limited quality and availability of data, as well as model uncertainties. A new purely data-based scale-extrapolation method is proposed, to estimate water resources for a large basin solely from selected small sub-basins, which are typically two-orders-of-magnitude smaller than the large basin. Those small sub-basins contain sufficient information, not only on climate and land surface, but also on hydrological characteristics for the large basin In the Baltic Sea drainage basin, best discharge estimation for the gauged area was achieved with sub-basins that cover 2–4% of the gauged area. There exist multiple sets of sub-basins that resemble the climate and hydrology of the basin equally well. Those multiple sets estimate annual discharge for gauged area consistently well with 5% average error. The scale-extrapolation method is completely data-based; therefore it does not force any modelling error into the prediction. The multiple predictions are expected to bracket the inherent variations and uncertainties of the climate and hydrology of the basin. The method can be applied in both un-gauged basins and un-gauged periods with uncertainty estimation.