Because of the fortunate absence of great flood events in The Netherlands during the second half of the twentieth century, no physical data was added to the structural understanding of flood fragility on walls. Considering that during the same period the cavity wall became standard in the construction of houses, a certain inconsistency can be recognized between the expected and observed (structural) behaviour of a modern wall during flood events. Nevertheless, failure, or collapse, of residential buildings is included in the Dutch flood protection standards as an important cause of damage and one of the main reasons for loss of life. It is generally believed that the developments in terms of building materials translate to a safer residence i.e. less prone to flood actions. This consensus is also found in the trade-off for certain mitigation measures, especially in areas where horizontal evacuation is difficult. An improved understanding of the flood fragility of a modern cavity wall is thus needed to prove the general consensus or to adjust the current mitigation measures to comply with the allowed fatality risks. A window-featured cavity wall section was constructed at the Flood Proof Holland facility, using calcium silicate bricks, fired clay bricks, and a weaker mortar to partly account for the virgin effect of any newly-built wall. Both inner and outer walls were connected with adequate wall ties. The wall section was subjected to several hydrostatic pressures at both sides. These experiments were performed to physically grasp the deformations corresponding to certain flood scenarios affecting cavity wall sections from ordinary terraced houses. Additionally, the effect of the window was investigated; both on the stability and its contribution to the water height inside a residence. Computations showed that the cavity wall in a one-way bending configuration starts to show significant cracks between 1.3 and 1.6 meters of outside water level. Because of the brittleness of the masonry, this would imply failure. It was further found that the non-linear deformations would reach 4 millimeters. Considering that for these water levels the internal moments were still far from their maximum capacity, the results suggest that failure occurred due to cracks that were forced to form because of the deformations. This indicates that modern cavity walls are still quite vulnerable for floods and their flood actions. The influence of the hydrostatic pressure, however, can be decreased considerably by a water level inside the residence that acts as a counter force. Contrary to what was expected, the window does not contribute to this inside water level, since its leakages turn out to be negligible. To keep the damages to a minimum and preserve the overall stability, it is advised to seal the residence to a height of 1.0 meter; floods that exceed this sealing should not be countered anymore and rather be allowed to enter the residence.

Like other cities in Kathmandu Valley, Bhaktapur faces rapid urbanisation and population growth. Unsafe, new settlements are partly located at the floodplains and the government lags behind in implementing proper land-use policy to control unrestrained settlement. The rivers are not only constrained by uncontrolled settlements, but also by insufficient width and freeboard of bridges, and waste blockages causes problems. Combined with more extreme rain events during the monsoon due to climate change, flooding has become a reoccurring problem in Bhaktapur. To gain better understanding of the river and the corresponding flood risk, historical data is essential. Unfortunately, historical databases of water levels are non-existent for this river. Only starting from monsoon 2019, water levels and discharge have been measured on a regular basis. To reconstruct the missing historical data for a return level analysis, this research introduces the Classical Model for Structured Expert Judgment (SEJ) in combination with citizen science (CS). The objective of this research was to use Structured Expert Judgment in a flood risk analysis for the city of Bhaktapur. As a result of using SEJ, we were able to obtain sufficient water level data and estimate the return levels of extreme water levels of Hanumante river by fitting a Generalized Extreme Value distribution (GEV). This eventually led to a reverse Weibull fit, which in this case does not seem accurate. This research discusses in detail the advantages and issues of using Structured Expert Judgement in situations like this and also discusses the reliability of the results.

The Kathmandu Valley in Nepal is facing the combined effects of population growth, rapid urbanization, economic development, and climate change. This results in serious water management challenges: growing freshwater demands, declining water tables, drying of streams, and deteriorating water quality. Insufficient surface water supplies have led to increased reliance on groundwater, especially during the dry winter and pre-monsoon seasons (November - May). Despite groundwater’s importance, it is sparsely measured, poorly understood, and insufficiently managed. As it is difficult and costly to measure all groundwater extractions in the Valley, a water balance approach is an alternative method to estimate total net groundwater pumping. Therefore, the aim of this research was to develop and evaluate potential methods for quantifying total pre-monsoon baseflow supplies by extrapolating baseflow measurements of a subsample of watersheds to unmeasured watersheds. Estimated baseflow was used, together with other water balance fluxes and changes in storage, to evaluate net groundwater pumping in the Valley. Three different methods were used: (1) Spatial Analysis, (2) Regression Model, and (3) Black Box (machine learning). All methods relied on streamflow data from 2017 to 2019, collected by citizen scientists from S4W-Nepal. Based on the three methods we presented, we cautiously conclude that it is possible to determine the pre-monsoon baseflow contributions from a sub-sample of head water catchments. Total baseflow estimates for the Valley using Spatial Analysis, Regression Model, Black Box were 2.32, 2.30, 2.65 m3/s respectively. These values show orders of magnitude that correspond with expected values. By using the average baseflow values of all three methods, we were able to close the water balance and make an assumption for the net groundwater pumping in the Valley. Based on a population of 3.5 million, a net groundwater extraction of 96 L/person/day during pre-monsoon was found. This striking outcome emphasizes the need for more discharge and groundwater extraction measurements, to decrease the uncertainties and to refine the methods.