The rootzone storage capacity (Sr) is a crucial part of the hydrological cycle. This storage provides water access for vegetation, in order to meet the atmospheric water demand through transpiration. The spatio-temporal variability of Sr is not well represented in current hydrological and climate models. The root zone storage capacity receives rapidly increasing interest from scientists. Recent studies developed a climate-based method to determine Sr. This method is based on the insight that ecosystems efficiently adapt their rootzone storage capacity to survive a drought with a certain return period. However, this method requires a vast amount of data. Long hydrological time-series with a rather fine temporal resolution are required. These time-series are not always available for many poorly gauged catchments. Therefore, it is important to explore what is exactly controlling this Sr, and if we can eventually predict it.  This study aims to describe the spatial and temporal variability of Sr with a combination of climate and land cover variables in Austria for the study period 1982 - 2008. To anticipate on expected snowfall, a snowfall module is included and calibrated with the use of a MODIS satellite snow cover product. The most important climate and land cover variables are identified, using multiple linear regression analysis. The best performing regression models are selected with a diverse combination of variables. This is done by comparing 21 catchments across the central and eastern part of Austria. Additionally, a stationary time-series split method is used to explore how Sr is changing in time. Subsequently, another multiple linear regression analysis is performed to explore the controls of the dynamics of Sr for these catchments.  According to this study, the Run-off coefficient describes Sr best in all studied regression models. A multiple linear regression model compiled out of the Run-off coefficient and the seasonality index performed best with an R2adj of 0.8. The seasonality index seems to be specific for this study since the highest fraction of precipitation and evaporation coincides in summer.  Land cover seems of less importance for the estimation of Sr. However, no conclusion could be drawn for the importance of land cover types in the regression analysis considering the disputable applicability of the land cover data. Furthermore, the relations of fractional cropland cover and fractional forest cover with Sr are in contradiction with current literature.  Apart from the spatial relationships, it is discovered that on average increased from the year 1992 onwards. However, no indisputable explanation is encountered (R2adj 0.55). The decreasing Run-off coefficient explains most of the increase in Sr. No conclusions could be drawn on the influence of land cover change on Sr, caused by an irregular land cover time-series.  Since the catchments in this study are rather humid and have similar seasonal patterns, it would be interesting to investigate if the discovered relationships are also valid for more arid and seasonal varying catchments. Also, it would be useful to investigate the unexpected relationship between land cover and Sr further.

In Bangladesh, groundwater from shallow aquifers is used for communal drinking water supply on a large scale. This water is often polluted by naturally occurring arsenic, causing the largest scale poisoning through drinking water in the world (D. v. Halem, S. Bakker, G. Amy, & J. Van Dijk, 2009). In this report, a highly arsenic affected area in Bangladesh has been investigated. The main objective of this research is to obtain more insight in the three aspects of the DELTAP project: geology, water quality monitoring and safe water supply. It is aimed to analyse the relation between arsenic contamination and the local geology, to monitor the drinking water quality using mobile applications and to design and construct a water treatment unit. An important aspect of this research is to develop a monitoring and maintenance protocol in order to ensure safe water supply in the future. In the study area, 150 households have been selected and the water quality has been tested. The water quality has been assessed by measuring four chemical parameters and five physical parameters, using simple strip tests and mobile water quality applications. The results of the strip tests have been compared to the results of ICP-MS analysis in order to check the performance of the tests and the mobile apps. The arsenic and iron strip tests showed good performance. However, the manganese and mmonium strip tests did not perform well. Furthermore, no relations between the presence of arsenic and other chemicals have been found. It can be concluded that simple strip tests in combination with mobile applications are a promising tool for water quality monitoring, applying the Mobile Crowd Participation strategy. Since arsenic in groundwater has a geological origin, the relation between arsenic concentration in the groundwater and geology should be understood distinctly. In order to get a better understanding of this relationship, multiple tools and theories have been investigated and tested. Firstly, a geo information system has been used to map arsenic concentrations that have been obtained from the performed water quality tests. Based on the spatial analysis of the arsenic concentrations, three drillings have been performed: one drilling in a high, medium and low arsenic contaminated area. By use of the SASMIT tool, a link between sediment colour and arsenic contamination has been observed. Furthermore, geomorphological data and satellite images have been used to identify geological features in landscape which could also be linked to arsenic levels. The sediment colour found in drillings is in good accordance with the arsenic levels found in groundwater and thus, proves to be a useful tool to predict arsenic concentrations in the fieldwork area. However, the geological features in the research area are hard to identify and link to the measured arsenic concentrations. A water treatment unit has been designed and constructed in order to provide safe water to 5 to 10 households. Based on the iron and arsenic concentrations from the ICP-MS results and on practical considerations, a suitable location for the water treatment unit has been selected. The ratio of these parameters is important to remove arsenic from the groundwater efficiently. The water treatment unit is based on oxidation of arsenic along with iron and subsequent filtration with a rapid sand filter. Both chemical and biotic oxidation of arsenic and iron are ensured by setting up a biofilm carrier column before the rapid sand and anthracite filter unit. Finally, a parallel resin column has been installed to remove the residual arsenic. The water quality throughout the system varied substantially during the timeline of the project. The produced safe water at the end of the fieldwork did not meet the drinking water standards set by the WHO. Nevertheless, several recommendations have been provided and, in the future, more intensive backwash of the water treatment unit might be the key to produce and distribute safe water. Overall, a deeper knowledge on arsenic contamination and their effects have been achieved, and the improvement of the Bangladeshis live quality has been attempted.