Reliable long-term groundwater level (GWL) prediction is essential to assess the availability of resources and the risk to drinking water supply in changing climatic and socio-economic conditions, especially in areas with water deficits. The modern approach in this area involves the use of machine learning methods. However, the greatest challenge in these methods lies in the optimization of input selection. The presented research concerns the selection of the best combination of predictors using the Hellwig method. It served as a preprocessing technique before GWL prediction using support vector regression (SVR) and multilayer perceptron (MLP) for three wells in the Greater Poland Province, where the largest water deficits occur, in the period 1975-2014. The results of this method were compared with those of the regression method, general regression model. For the case study under investigation, the Hellwig method found GWL at lags of -1 and -2 months, all precipitation from the current month, and delayed by -1 to -6 months, and past temperature at months -1, -3, -4 and -6 as the most informative input set. Such input led to a model accuracy of 0.003-0.022 for a mean squared error and r(2) of >0.8. The results obtained with SVR were slightly better than those with MLP. Moreover, every well required an individual set of predictors, and additional meteorological inputs improved the models' performance.

The climate change that has been observed in recent years has affected the water balance, including the groundwater resources recharge. The paper is an attempt to evaluate the groundwater recharge in dry years. The initial stage of the research consisted of selecting the years when meteorological and hydrological droughts occurred, with use of the standardized indices Standardized Precipitation Index (SPI) and Standardized Water Level Index (SWI). With the use of the WetSpass model for selected periods and for comparative long-term periods the volume of groundwater recharge was estimated. It was determined that the meteorological drought of 1982 led to a considerable decrease in the mean groundwater recharge to a negative level in the summer half-year in the Western Pomeranian region in Poland. On the other hand, the winter season was characterised by positive values, but they were still lower than those characteristic for the comparative long-term periods. The hydrological drought in 1992 did not have such noticeable consequences.

Booming urbanization has negative impact on hydrological processes at different scales, which occurring both on and below the earth surface. However, there is still a question of how modifications in the land use affect the regional water balance and searching the tools that will enable it. In the current work, a simulation WetSpass model was used to assess the water balance structure in the city of Wroclaw (total area 295 km2, with significant share, amounting 40%, of typical rural areas). The relationship between land use and components of the water balance (groundwater recharge, actual evapotranspiration, surface runoff) for the entire urban agglomeration as well as individual historical districts has been presented. The average annual groundwater recharge in Wroclaw in the years 1981-2010 was only 16.5 mm/year (3% mean annual precipitation), evapotranspiration 443.7 mm/year, and surface runoff 79.3 mm/year. A similarity was observed between the Stare Miasto and the Śródmieście districts, where the values of evapotranspiration equal to approx. 410 mm and surface runoff of about 110 mm and between Psie Pole and Fabryczna districts with higher evapotranspiration (450 mm) and lower surface runoff (70 mm) were calculated.

Original paper can be found at: http://www.ask-eu.com/default.asp?Menue=149&AnbieterID=586 [Full text of this paper is not available in the UHRA]

Condensed abstract: In the paper the DRASTIC method and the Attenuation Factor technique have been ap- plied to asses the groundwater vulnerability to pollution by pesticides within a small, typical agricultural catch- ment of Polish lowlands. According to DRASTIC approach within the studied basin almost the entire catchment is highly and very highly susceptible to pollution by pesticides. According to the Attenuation Factor method the risk of applying pesticides is relatively high at only less than 1 % of the studied basin. The studied example has shown clearly an extremely important role of pesticides chemical properties for proper assessments of ground-

A methodology is presented for identifying and assessing source areas of sediment, phosphorus and nitrate emissions into surface waters and river systems of the South Baltic unconsolidated rock region by water erosion. This task is included into the characterization of the pressures and impacts in river basins as an important milestone in implementing the EC Water Framework Directive set out by 2004. The Nutrient Input Into River Systems (NIIRS) approach has been developed and tested in the Odra river basin in Poland, Czech Republic and Germany. Mesoscale distributed analyses are facilitated for identifying erosion risk areas with non-point phosphorus and nitrate inputs into water bodies via surface flow. Using statistical information and available geodata, analyses are based on empirical (NIIRS), but preferably process-oriented modelling (EROSION-3D). Thus, besides better understanding the system behaviour, detailed quantitative knowledge of spatial nutrient export rates from potential source areas will be acquired. The application of the distributed approaches is demonstrated in the entire Odra River basin and its sub-catchment Uecker River. Additionally spatial effects are shown for the field scale transfer of eroded material in the Uecker sub-catchment by using the physically based model EROSION-3D. Scenario calculations incorporated into a Geographical Information System (GIS) environment are feasible for estimating the development of erosion risk as well as N and P loads entering water bodies. Supplemented by impact analyses of land use changes, the methodology can serve as physical precondition for the cost-benefit oriented allocation of mitigation strategies.