Landslides are one of the most widespread natural hazards, causing thousands of casualties every year and significant economic damage worldwide. In mountainous regions of Thailand, damages and fatalities due to landslides have increased over the last decades due to intensified human interventions.

This research aims to contribute to the development of a near real-time, joint early warning system for flash floods and landslides in Khao Yai National Park, Thailand. Spatial and temporal landslide occurrences in Khao Yai National Park were assessed. To extend the available landslide inventory, the detection of historical landslides was automated on the Google Earth Engine platform using remotely sensed relative changes in NDVI. Predisposing factors of landslide occurrence were determined using the frequency ratio method. A susceptibility map was then derived by linking the detected landslides to the predisposing factors: slope angle, aspect, land use, lithology, and distance to road. Validation with the landslide inventory shows excellent classification performance.

The temporal probability was assessed using a physically-based multi-hazard model. The hydrological model includes the driving hydrological processes for each grid cell. The streamflow model output was calibrated using observed nested river discharge events. The model performance was tested under spatially distributed precipitation forcing of varying quality. The results show good performance in predicting streamflow and landslide occurrence based on modeled antecedent conditions when using high-quality weather radar information as forcing.

This research demonstrates the effectiveness of integrating fully distributed physically-based modeling with high-resolution spatial rainfall observations from weather radar. The findings are expected to enhance the development of a multi-hazard early warning system and improve disaster risk management in northeastern Thailand.

PWN is responsible for supplying sufficient quantities of high-quality water to its customers. The growing population and the effects of climate change, such as heat waves and droughts, are straining the capacity of the water supply network, especially during dry and warm periods when water demand increases. A significant portion of the drinking water is produced in Andijk. From there, the drinking water is transported to Hoorn, where it is further distributed to customers. The connection between Andijk and Hoorn is therefore crucial, and in the event of a pipeline failure due to a calamity or maintenance, capacity issues can arise. To maintain the redundancy of this connection and to smooth out the daily water demand and supply fluctuations, PWN is exploring the implementation of an Aquifer Storage and Recovery (ASR) system in Hoorn.

The ASR system in Hoorn faces strict requirements, which address the challenge of maintaining water quality standards and optimising recovery efficiency. These requirements must ensure that the extracted water remains suitable for consumption, with no more than 1% dilution with ambient groundwater. The objective of this study is to identify a method to improve the recovery efficiency of the ASR system in Hoorn. The ASR system operates by injecting drinking water into an aquifer during periods of water availability and recovering it when needed. Compared to installing a new pipeline, the ASR system offers a more cost-effective solution with additional benefits such as space efficiency and temperature stability. However, the ASR system in Hoorn faces challenges related to maintaining water quality standards and optimising recovery efficiency. Processes such as lateral flow, dispersion, and buoyancy affect the system’s performance, and a thorough understanding of these processes is crucial for accurately predicting recovery efficiency. A comprehensive analysis of a pilot ASR system in Hoorn was conducted by PWN to address these challenges. The pilot system consists of a single well where two pumps operate at two different filter depths in an aquifer. In the final layout of the ASR, additional wells are necessary to achieve the desired capacity.

A radially symmetric model was used to simulate groundwater flow, conservative solute transport, and heat transport. Due to the stringent water quality requirements, the radially symmetric model must accurately capture essential processes in an Aquifer Storage and Recovery (ASR) system, such as flow, dispersion, retardation, and buoyancy. The performance of a radial symmetric model in SEAWAT and MODFLOW 6 was assessed based on analytical methods and 3D models. Through this analysis, it was decided to utilise a radial symmetric model in SEAWAT due to the presence of numerical dispersion in a model using MODFLOW 6.

After this analysis, the model’s performance was tested against various measurements, including hydraulic head, temperature, and electrical conductivity. It is evident that the model effectively captures both solute transport and heat transport. Discrepancies between measurements and the model can be attributed to assumptions made during the study and uncertainties in the measured values. However, the presence of clay layers between the deep and shallow filters in the pumping well significantly contributes to local differences between the model and the measurements. The main reason for this difference is that these layers are not homogeneous throughout the depths, allowing water to flow between them. This heterogeneity cannot be simulated with a radially symmetric model. However, despite this heterogeneity, these clay layers consistently result in low recovery efficiency in the current system.

The objective of this study was to identify a method to improve the recovery efficiency of the ASR system in Hoorn. The current system has a recovery efficiency of about 30%. This can improved by implementing a check valve in the shallow filter of the pump well, with 60% to 65% of the filter dedicated to recovery to achieve a recovery efficiency of 80%. During the testing of this system, an injection period was followed by a recovery period with specific pumping rates. It took three cycles to achieve the desired recovery efficiency. It is important to note that these cycles did not include storage and rest phases. The system’s recovery efficiency may change when these phases are incorporated. However, an important assumption is that homogeneous layers are present. Heterogeneity of layers can lead to deviations from the modelled recovery efficiency. This research contributes to a better understanding of the pilot ASR system in Hoorn and provides insights into improving its recovery efficiency. With the lessons learned from this study,
PWN can assist in developing the final design for the ASR system. This design will involve multiple wells to meet the required capacity.

In this study, the relationship between water quality and agriculture in the upstream region of the Brantas catchment has been investigated, with a focus on Electric Conductivity (EC), Dissolved Oxygen (DO), pH, nitrate, Biological Oxygen Demand (BOD), phosphate and ammonia concentrations. The EC concentrations ranged from 120 to 570 μS/cm, the DO concentrations from 3.15 to 8.57 mg/L, the nitrate concentrations from 0 to 20 ppm, the nitrite concentrations from 0 to 3 ppm, the BOD concentrations from 6.22 to 6.87 mg/L, the phosphate concentrations from 0.25 to 1 mg/L and the ammonia concentrations from 0 to 0.25 mg/L. Using detailed land use data, the correlation between land use classes and water quality parameters was analyzed. Nitrate concentrations of streams of which the catchment area consists of over 70% Ladang area ranged from 2.5 to 11 ppm, while catchment areas consisting of over 70% of Kebun area featured nitrate concentrations of up until 4 ppm. Regarding EC, this difference is 200 to 475 μS/cm versus 200 up until 375 μS/cm. Certain parameter concentrations, in particular BOD, raise potential concern. While this research provides some insights into water quality in the Brantas catchment, it also underlines the need for further investigations employing improved methodologies, increased sampling over a larger timescale and area, and comprehensive, multidisciplinary approaches. It is recommended that further studies in the area focus more on different parameters, in particular BOD.

In today's world, extreme flooding and drought events are becoming increasingly common globally. These challenges arise from various factors, with climate change and changes in land use being among the most significant contributors.

While numerous studies have explored the combined impact of climate change and land use on streamflow, there is a research gap when it comes to analyzing historical data for changes in the magnitude and timing of discharge peaks and low-flow periods. To address this gap, this MSc Thesis investigates river discharge in five European countries: Belgium, Germany, France, Luxembourg, and the Netherlands.

To analyze potential patterns and variations in magnitude changes, trend analyses were conducted for annual and monthly mean daily flows. Non-parametric methods such as Sen's slope and the Mann-Kendall test were employed to calculate trends in average, maximum, and minimum daily flows at both yearly and monthly levels. The issue of autocorrelation in discharge flows was also addressed by using a modified version of the Mann-Kendall test for stations with autocorrelated data. Furthermore, the possible shifts in the timing of discharge peaks and low-flow periods were examined. We employed statistical tools such as statistical entropy, Kullback-Leibler divergence, and various descriptive statistics to determine if there have been changes in the month with the highest flow over the years.

The study's results generally align with existing research. Regarding annual discharges, for average and maximum analyses, stations with decreasing trends were predominantly found in the North, East, and central parts of the study area (Germany), while the North-West exhibited stations with significant increasing trends in most cases (North France).

In yearly minima discharge flows, the patterns were aligned with average and maximum analyses; however, additional stations showed decreasing trends, which were located in Belgium. In the monthly analysis, positive trends were primarily observed during winter months (February, December, and January), while April and March showed decreasing trends in most cases (monthly average and maxima analyses), with a few exceptions in minimum daily flows.

Notably, more than 50% of the stations exhibited shifts in the month when they experienced maximum and minimum discharge, particularly between 1980-2000 and 2000-2021. This finding suggests potential avenues for future research.

Saltwater intrusion in groundwater is a concern in many aquifers around the world. It results in deterioration of potable and irrigation water quality and degradation of ecosystems. The problem is exacerbated by fresh groundwater abstraction, drying climates and a rising seawater level.
Esperance is a small town situated on the south coast of Western Australia. The drinking water is supplied by a borefield located on the coastal plain in between the Southern Ocean and the saline lakes: Lake Warden and the terminal Pink Lake. Saltwater intrusion has been monitored for over two decades in this aquifer.
Managing Saltwater intrusion has been a priority for the local water company and the regulator for decades yet a numerical model of the aquifer capable of quantifying flows and salinity distributions does not exist.
In this study, a numerical flow model was developed as a first step towards a model that also includes saltwater movement, i.e. density-dependent flow. A site-specific literature review is documented in this report, as well as relevant saltwater intrusion studies.
A 3-dimensional hydrogeological model was created with a kriging geostatistical algorithm with data from Airborne Electromagnetic (AEM) surveys and borehole logs. A database including climatological fluxes, abstraction rates, groundwater heads, lake stages and lithographic data was created. The salinity distribution in the catchment was analysed using borehole observations and AEM data. Groundwater salinity is more prevalent in the east and northeast of the domain. Salts from inland sources are transported to the coastal lakes by a combination of groundwater and surface water.
The flow model was calibrated with PEST++ and a linear parameter error and sensitivity reduction was carried out with GENLINPRED from the PEST++ suite. The result of the study is a groundwater flow model that is able to quantify the approximate fluxes and heads within the catchment. However, it must be noted that the calibration can be improved. The relative error reduction for some parameters is large, for example groundwater recharge in areas with sparse and dense vegetation (0.91, 0.84 respectively), the runoff/quickflow factors towards the lakes (0.87, 0.95 and 0.88 for the Pink Lake, Lake Warden and Windabout/Woody lakes respectively) and reasonable for some of the hydraulic conductivities. The identifiability for other parameters (such as specific yields and vertical hydraulic conductivity) is low.
Zone budget calculations show that groundwater annual recharge and evaporation are the largest fluxes in the catchment and are equal in magnitude. The annual average evaporation rate over the entire catchment is 0.74 mm/d. The annual average groundwater abstraction is the same order of magnitude of the flow that enters the ocean, 5,656 m3/d vs. 8,169 m3/d respectively.
Modelling indicates that abstraction has a large effect on groundwater levels. The decline is the largest (> 1 m) a couple of kilometres west from the town area where abstraction decreases the water table. The effect is less south of the Pink Lake (~0.40 m).
(Hyper) salinity is the result of the net transport of saline groundwater entering into the lakes in combination with net evaporation. Water budget calculations show that the groundwater inflow in the hypersaline lakes exceeds groundwater outflow by a factor 8.1 for the Pink Lake and 1.7 for Lake Warden. Freshwater entering the lakes originates from direct precipitation and a calibrated runoff/quickflow component. This results in an effective lake area for precipitation of 1.6 times for the Pink Lake and 2 times for Lake Warden. In the lakes the evaporation exceeds the freshwater inflow by a factor of 1.5 and 1.1 for the terminal Pink Lake and Lake Warden respectively.
The low flow velocities towards the ocean in the eastern part of the catchment underline the risk of saltwater intrusion in this area. Flow field modelling suggests that groundwater abstracted in areas directly south of the Pink Lake is saline.
Finally, the current model is able to support recommendations for expansion of the borefield towards the area in the west of the catchment.

To reduce the Urban Heat Island (UHI) effect Green Infrastructure (GI) is seen as a key measure. Though, often the need for water to evaporate is neglected. This study focuses on showing the effects of irrigation and increased soil moisture contents on GI within urban areas to reduce the UHI-effect. ENVI-met, a micro-climate model, is used to model various scenarios for a tropical day and a heatwave in the Netherlands. For two Dutch urban areas, with different building typology and subsoil, the current situation, a greener scenario and various soil moisture profiles have been modelled to show the effects of increased soil moisture content on thermal comfort and the UHI-effect.

Extensive usage of vital freshwater is highly undesirable in the current era of climate change and population growth. However, the 6 millionm3/y of brackish seepage that occurs in the deep Horstermeer Polder, located in between the cities of Amsterdam and Hilversumin the Netherlands, is mitigated by using up to 207 millionm3/y of freshwater. This is very unsustainable, especially since the
pressure on the freshwater reserves in the Netherlands is rising. Therefore, this research focuses on evaluating a new mitigation measure of the brackish
upconing below the polder: the extraction of brackish water. In March 2021 AD, a pilot well has been installed in the polder, and its effects were assessed in this research. To enable the evaluation, an extensive analysis of all available measurements of the geology, hydraulic head, and chloride distribution in the area was performed, and a 3D regional variable-density groundwater model using MODFLOW 6 was built. The model result has a reasonable good agreement with these measurements, since at 70% of the measurement locations, the simulated hydraulic head deviates less than 30 cm, and at 80% of them, the simulated chloride concentration deviates less than 200 mg/l. Moreover, compared to previous research, the representation of the brackish upconing was significantly improved. The effects of the pilot well were calculated using five different operational settings. The results indicated that a shallow well, starting below -50 m NAP, reduces the chloride load in the polder more than a deep well (-100 m NAP). However, even in the best scenario, i.e. an active shallow well with a constant pumping rate of 100 m3/h, the reduction of the chloride load is limited to 5.5%. In perspective, these results suggested that at least 24 of these wells are needed to lower the chloride concentration in the discharge water out of the polder to 250 mg/l. On the contrary, the shallow wells cause a considerable average drawdown of 4 cm at surface level in a radius of 50 meters around the well, which might result in damage to wooden pile foundations in the northeast of the polder.

In this report, the tidal method is used to estimate hydraulic aquifer parameters. The principle of the tidal method is to use head fluctuations in observation wells, caused by tidal motion in a sea or river, to determine regional hydrological characteristics of an aquifer system. As the wave propagates into the aquifer, the amplitude of the signal decreases and the phase increasingly lags behind the tide at sea. The extent of this is determined by hydrological aquifer characteristics, hence aquifer parameters can be estimated, by calibrating a model that reproduces the measured tidal propagation. Knowledge of hydraulic aquifer parameters is important since these are needed in groundwater models. The case study was performed on Schouwen-Duiveland where use was made of hydraulic head fluctuations from three groundwater observation wells and water-level observations in the Oosterschelde. First, these time series were analyzed to estimate the amplitudes and phases of the constituents present in the data. Noise in the data was reduced with the use of Pastas (a model to analyze hydrological time series; Collenteur et al., 2019) and a Butterworth filter, after which both methods were compared. Pastas was used to decompose the fluctuations observed in the groundwater to different contributions of hydrological stresses (e.g. rain and evaporation) and Butterworth was used to flatten the frequency response for frequencies that are not of interest. The use of the Butterworth filter is preferred, partly because it produces the smallest standard deviations for the amplitude and phase estimates and because it is easier to use. Moreover, especially for the wells with a low signal to noise ratio, the Butterworth filter is better at extracting the tidal signal. In addition, a graphical determination of the amplitude and phase was performed to check if this relatively quick and easy analysis gives accurate estimates of the M2 amplitude and phase as well. It was concluded that with a high signal to noise ratio and a dominantly present constituent (M2 in this case), the amplitude can be reliably estimated. Determining the phase with this method did not give satisfactory results. In the inverse modeling part, the hydraulic aquifer parameters are determined, which is done with a least-squares minimization of the observed and modeled amplitudes and phases. For the optimization, both a one-aquifer and a two-aquifer model were used, both based on the one-dimensional, multi-layer solution presented by Bakker (2019). The optimization was performed with a global optimizer. The obtained fit to the observations was somewhat poor, moreover, unrealistic optimal parameter estimates indicate that the model, to some extent, incorrectly represents the real system. This also implies that some of the model simplifications do significantly impact the results. Simplifications presumed to mostly influence the model results include homogeneity, one-dimensional flow and the use of a straight shoreline. The presence of some model error signifies that the resulting parameter estimates should be treated with care. The hydraulic conductivity and the resistance of the one-layer model were consistently estimated at their upper boundary and the storage in the leaky layer was estimated to be negligible. Therefore, only one parameter group (i.e. the diffusivity) could be estimated with the optimization. The fit of the model was not perfect, a compromise must be sought based on what residual the model minimizes. As a result, all diffusivity estimates within and around the range [1.07E6, 1.31E6] m²/day are all considered to be reasonable estimates. For the resistance of the aquitard (CU) and the storage in both the aquifer (S_sU) and the aquitard (σU) it was analyzed which parameter values gave unreasonable results. This resulted in a lower bound for CU (CU=663 days) and an upper bound for σU  (σU =1.22E-4 m^-1). For S_sU reasonable results are obtained between 2.28E-6 m^-1 and 1.87E-5 m^-1. The lower bound for the CU estimate seems to comply with estimates based on two models (REGIS-II and GeoTOP). Finally, the two-aquifer model was considered to be useless for parameter estimation. Presumably, this is predominantly caused by a small amount of amplitude and phase data compared to the number of parameters to be optimized.

Seawater intrusion modeling is challenging either because of a lack of many approaches' ability to cope with complex environments or significant computational expense. Seawater intrusion models also face issues with parameterization and validation due to problems with many parameters and also a lack of observational data. Bakker and Schaars (2013) proposed a method to solve for the steady-state interface using a single-density flow model (MODFLOW). In this thesis, this method was applied to 3 existing coastal flow models and shown to be able to compute the steady interface. The work also contains examples of applying critical pumping solutions to the models to demonstrate its applicability as a management tool. The research also contains an effort to solve for an interface when the saltwater is moving but was ineffective. Modifications may be made to resolve the issues with the latter approach that could lead to a advances in interface modeling methods.

The presence of organic micro-pollutants (OMPs) has caused increasing contamination of aquatic systems. In recent years, the selective adsorption of target OMPs by zeolites have been proved efficient for OMP removal. For the potential application of zeolites in the wastewater treatment plants, zeolite granules are preferably used in order to avoid the post-filtration for zeolite powders. Therefore, the knowledge on the performance of zeolite granules for the removal of OMPs should be fully understood. In this research, BEA and MOR zeolite granules were used as adsorbents for the removal of 11 OMPs from water, which were carbamazepine, diclofenac, 1H-benzotriazole, methyl-benzotriazole, hydrochlorothiazide, sulfamethoxazole, clarithromycin, propranolol, trimethoprim, metoprolol and sotalol. The aims of this study were: (1) to investigate the adsorption capacity and kinetics of the 11 OMPs by zeolite granules in both demineralized water and wastewater (WW), in batch experiments; (2) to predict the breakthrough curve of columns packed with zeolite granules by using a mathematical model combining the parameters determined by batch experiments. It was found that the charge and hydrophobicity of OMPs were the two main factors that affected the adsorption capacity of OMPs by zeolites, while the effect of OMP size on the adsorption capacity was negligible. The OMP adsorption capacities by zeolite granules were less than OMP adsorption capacities by zeolite powders. The fittings of the IPD model to the adsorption kinetic data showed that film diffusion and intra-particle diffusion were both the rate-limiting steps in the adsorption of OMPs by zeolite granules. Furthermore, the adsorption capacity and rate of OMPs in WW were lower in comparison with OMP adsorption in demineralized water, which could be caused by the higher pH in WW and the pore-blocking effect by background organic matters. In the column experiments, it was found that OMP breakthrough percentage in the column was determined by both the adsorption capacity and kinetics of OMPs by zeolite granules. In the breakthrough model, the kinetic and isotherm constants from batch experiments overestimated the adsorption rate and capacity of zeolite granules in the columns, and the overestimated isotherm constant was the main factor that caused the deviation of the model prediction. With a lower isotherm constant, the model was able to provide good resemblance between modelled and measured breakthrough curves. Furthermore, with a known breakthrough curve at a certain EBCT, the model was able to determine a proper isotherm constant, which can be used to predict the breakthrough curve at a different EBCT.

The construction of drinking-water reservoirs in previously free-flowing river basins introduces challenges in operational water management, especially in data scarce environments. Often resulting in effectively un- gauged basins. In order to be able to estimate the expected increase in water supply, the hydrology of the ungauged sub-basins must be deduced from the whole basin. This can be done by estimation based on rel- ative area to the whole. However such a method neglects the potential differences in boundary conditions and ecosystems. This research presents an improved hydrological modeling method. Through the devel- opment of a process-based, flexible model (FLEX-Topo) with four classes the hydrology of a polar-desert, high-mountainous basin in the Cordillera Real (Bolivia) is investigated. To increase realism additional data- sources are used in model development and calibration. Internal model states related to vegetation- and snow-presence are evaluated in the frequency- respectively time domain. The calibrated model is applied to the sub-domains to identify important hydrological differences. To further support operational decision making the correlation between the ENSO-Index and the local climate is investigated, which is not found to be significant. The research shows that the developed FLEX-Topo model is suited to function in a data scarce- and low data quality environment. The model is able to reproduce the natural flow regime to a high degree. Appropriate model realism can be assumed and sensible sub-basin hydrology investigation is achieved. Sub- sequent reservoir dynamics hind-casting is performed to increase knowledge on the to be expected flows and water levels.

Cement-Bentonite (CB) walls are low permeability vertical cut-off barriers that are mainly used to prevent groundwater flow and isolate contaminated areas. The hydraulic performance of the CB walls depends on the flow rate (discharge) through the wall. Therefore, the walls must achieve very low hydraulic conductivity. Poor in-situ hydraulic performance of these walls due to construction and post-construction defects may lead to surface settlements, groundwater contamination, and instability of the construction. This thesis investigates the range of in-situ hydraulic conductivity values of CB walls installed within the Netherlands. To achieve this, pump data for the various projects (Westerschelde Tunnel, A2 Motorway at Best, Motorway A4 Delft-Schiedam, Griftpark Utrecht, and Richard Hageman Akwadukt) were analyzed to determine the discharge through the walls. The in-situ hydraulic conductivity of the walls was calculated by Darcy’s law using groundwater level data and dimensions of the walls. The CB walls must be "keyed" into an underlying low permeable layer (aquitard), so that seepage of water through the aquitard is prevented. It was difficult to compute the in-situ hydraulic conductivity of the CB walls for Motorway A4 Delft-Schiedam and Griftpark Utrecht. The reason was that the walls in these projects were embedded in a permeable aquitard, which affected the total discharge value. The calculated in-situ hydraulic conductivity values were compared with the required hydraulic conductivity values and laboratory test results. In most of the cases, the in-situ hydraulic conductivity values of the walls were larger than the values acquired from the laboratory samples. The reason is that the estimation of the hydraulic conductivity of the CB walls from laboratory tests was based on small sample areas. This remains unreliable to evaluate the field performance of the CB walls. The average hydraulic conductivity of the CB walls at Richard Hageman Akwadukt was required to be less than or equal to 1·10-9 m/s. The calculated hydraulic conductivity values of the CB walls for the northern and southern polders were approximately 2.5·10-9 m/s and 2·10-8 m/s, respectively. This study also shows that the hydraulic performance of the CB walls is mainly affected by insufficient connections between the panels. Also, the impact of the defects on the discharge through the wall has been investigated by developing a threedimensional numerical groundwater flow model using MODFLOW. Simulations were performed for different types of defects, such as fully and partially penetrating windows, insufficient embedment, and connection between the panels of the CB walls. The results of the simulations indicated that fully penetrating windows have more impact on the discharge through the wall compared to partially penetrating windows. Partially penetrating windows with a hydraulic conductivity lower than 1·10-6 m/s are often insignificant. The size of a fully penetrating window also plays an important role. The difference in discharge (ΔQ) was calculated by subtracting the discharge through a perfect wall and imperfect wall (Qimperfect - Qperfect). The (ΔQ) through a CB wall with a window whose area is equal to 1 m2 can increase by a factor of 10 compared to a window whose area is equal to 0.1 m2. The location of the defects has no impact on the discharge through the wall. The simulations also show that the flow rate is unaffected by the embedment depth of the wall, but it must be ensured that the wall is in direct contact with the aquitard (low permeability soil layer). The vertical deviation of panels also affects the discharge through the wall. The MODFLOW results can be used to get an indication of the increase in discharge caused by various types of defects. From this, the possible defects for a particular project can be determined.

Hydrological regimes of alpine catchments are expected to be strongly influenced by climate change due to their dependence on snow dynamics. While seasonal changes have been studied extensively, studies on changes in the timing and magnitude of annual extremes remain rare. This study investigates the effects of climate change on runoff patterns in six alpine catchments in Austria by using a topography-driven semi-distributed hydrological model and 14 climate projections for both RCP 4.5 and RCP 8.5. The study catchments represent a range of alpine catchments, from pluvial-nival to nivo-glacial, as the study focuses on exploring the effects of climate change on catchments of different altitudes.
Simulations of 1981-2010 were compared to projections of 2071-2100 and changes in timing and magnitude of annual maximum and minimum flows as well as monthly discharges and melt were examined. Our results indicate a substantial shift to earlier occurrences in annual maximum flows by 9 to 31 days and an extension of the potential flood season by 1 to 3 months for high elevation catchments. For lower elevation catchments, changes in timing of annual maximum flows are less pronounced. Magnitudes of annual maximum flows are likely to increase, with four catchments exhibiting larger increases under RCP 4.5 than RCP 8.5. The timing of minimum annual discharges shifts to earlier in the winter months for high elevation catchments, whereas for lower elevation catchments a shift from winter to autumn is observed. While all catchments show an increase in mean magnitude of minimum flows under RCP 4.5, this is only the case for four catchments under RCP 8.5. Our results suggest a relationship between the altitude of catchments and changes in timing of annual maximum and minimum flows and magnitude of low flows, whereas no relationship between altitude and magnitude of annual maximum flows could be distinguished. The degree of future change in timing and monthly discharges is larger under RCP 8.5, a change of up to twice as large in monthly discharges is found for RCP 8.5 compared to RCP 4.5.

In the face of climate change, urban stormwater management practices are subject to an uncertain context. More frequent and extreme rainfall events are expected in many urban areas. The extent how climate change will affect weather patterns is however uncertain. This challenges contemporary stormwater management practices. A post-disaster reconstruction of an urban area would potentially be an opportunity to anticipate climate change uncertainties from the initial design phase of new urban development. This would allow for taking advantage of the disaster recovery by rebuilding a more resilient stormwater system than was present before, in which the uncertainties are anticipated. A resilient stormwater system would thus be able to cope a wide range of plausible futures, rather than the average. As academic literature lacks insight on re-establishing resilient urban stormwater management in a post-disaster reconstruction, this thesis aims to gain more insights into what extent resilient urban stormwater management has been established in a Tsunami reconstruction, with regard to uncertainties on climate change and urban development. A case study is conducted in which is focused on a) the conducted design approach, b) the realm of conditions for which the implemented stormwater system would be vulnerable and c) which solutions could be implemented to reduce the vulnerability, and reflected upon opportunities of an interdisciplinary approach from a stormwater management perspective. The selected study area is a town called Ötsuchi Town, in Northern Japan, Iwate Prefecture, which was severely hit during the 2011 Tsunami. The disaster necessitated a comprehensive reconstruction. To gain more insight into what extent a resilient urban stormwater system has been implemented, an exploratory modelling and analysis approach has been applied, which is also known as Scenario Discovery. Prime drivers of Scenario Discovery are exploring the system's performance for wide-ranging plausible futures by sampling the system myriad times with aid of computational modelling, and, the use of regional sensitivity mapping algorithms to understand the dominant factors that lead to insufficient system performance. The latter can be used as input for seeking vulnerability-reducing strategies. In this research, the Patient Rule Induction Method (PRIM) algorithm is used to understand the conditions for which the stormwater drainage system capacity would be exceeded, for an acceptable flooding level of 0.2 meter. Two open-source tools were combined: the conceptual stormwater flow model EPA-SWMM, and, python library EMA-workbench which provides the tools needed for applying Scenario Discovery and supportive analysis. After the 2011 Tsunami a separate half-open sewer system was established in the reclamation area of Ötsuchi Town. No natural-based solutions, or Blue-Green infrastructure were implemented, even though the residential is adjacent to steep mountain slopes. The uncertainty parameters over which is sampled, include rainfall intensity, rainfall duration, external runoff coefficient, imperviousness, the hydraulic conductivity, Manning's roughness coefficient and depression storage. The Scenario Discovery results show that the system has been built robust. For almost all locations no flooding occurrence arise from the sampling, even for very extreme rainfall events (>100 mm/hr, for a duration of 60 min). However, when the runoff coefficient of the external runoff from the mountain would be above 0.58, a small area in the northern part would be vulnerable. The dominant factors, are found with PRIM and the relative weights are with very high precision and recall found by pre-processing the sampling data with Principal Component Analysis. It showed that for the vulnerable area, the hydraulic conductivity of the soil and the proportion of paved area are decisive in whether or not flooding occurs. Paying attention to certain thresholds, would significantly reduce the vulnerability of flooding occurrence. Given the high volumes for which flooding would occur, a preliminary feasibility study has been done for both a vegetative swale and infiltration trenches, in combination with a storage retention area in the lower lying area, such that the pressure on the stormwater drainage system can be released. The vegetative swale reduce the vulnerability significantly. The infiltration trenches seem to be effective for the lower rainfall duration and rainfall intensity. PCA-PRIM outcome showed that when implementing infiltration trenches in the vulnerable area, the impervious rate becomes relatively less sensitive in comparison with outcomes of PRIM with the reference situation. More information on mountain runoff, soil properties and land use would enhance the accuracy of the results. In addition, since, no information is known yet on initial losses of mountain runoff, more information on runoff flow processes from the mountains would enable to perform joint probability analysis with the results of this research, to better assess whether or not the time is now to implement additional measures. From the results of this research it seems that the urban stormwater drainage of Ötsuchi Town has been rebuilt very robust, however when the system would fail, no additional measures outside the grey infrastructure are taken. An interdisciplinary approach could have encouraged a more resilient stormwater management. As this research shows that multiple commutative reconstruction measures could be found from a stormwater management perspective, the obtained information with applying Scenario Discovery, would have been useful to encourage an interdisciplinary approach during the reconstruction process. It is therefore suggested to explore the usage of Scenario Discovery on urban stormwater management even further, such that it enables to take advantage of the disaster reconstruction to establish a resilient urban stormwater management. An example would be to investigate whether the relative sensitivity of the uncertainty parameters would change when a less robust system would be examined. For example, for an urban drainage system for which the threshold would already be exceeded for lower rainfall intensity and duration than 100 mm/hr, and 60 minutes respectively. In addition, a coarse representation of rainfall events are considered in this research. Therefore it would be suggested to examine the applicability of region-specific storm profiles in combination with an exploratory modelling and analysis approach, to better assess the implication of the PRIM outcomes for implementing resilient urban stormwater management strategies.

In 2008 the Red Cross Red Crescent (RCRC) started with Forecast-based Financing pilots to improve existing Early-Warning Early Action systems. Forecast-based financing is a new methodology to prepare, deliver and respond in a more effective and efficient manner, based on hazard forecasts. Actions are triggered when a forecast exceeds a danger level in a vulnerable intervention area. Forecast-based financing consists of several implementation steps, of which the first three aim at impact-based forecasting. Therefore, In this study we investigate how forecast skill of agricultural drought forecasts can be achieved. More specifically, the aim is to identify the contribution of machine learning and satellite-derived products in early warning early action systems improving the forecast skill of agricultural drought forecasts. We explore this through a machine learning model for a case-study area of the Lower Shire River Basin in Malawi. Several experiments with different sets of predictors and predictands are conducted to test which data adds to the skill and at what spatial detail. As predictors, the following agro-climatic indices are used: cumulative precipitation, soil moisture anomalies,mland surface temperature anomalies, El Niño Southern Oscillation in July and four different dry spell categories within the growing season (0-2 days dry spell, 3-4 day dry spell, 5-10 day dry spell and larger than 10 day dry spell). As drought predictand, the normalized difference vegetation index (NDVI) and the vegetation optical depth
(VOD) in March are used, the latter obtained from satellite data company VanderSat. The final set of predictors and predictands is narrowed down based on which data is available and with which quality (timeliness, reliability, accuracy). Initial results, show higher accuracy and weighted accuracy values for the models including soil moisture data compared to the ones without soil moisture, expect for the last month in the growing season, where it give opposite results. The outcome of the model can support humanitarian organisations to increase the lead time necessary to act upon a drought trigger and reduce the impact of such event.

Estimating groundwater levels spatially using time series analysis. With time series analysis a response function of an observation well is determined. The response function is used to calibrate a conceptual groundwater model. This conceptual model is used to estimate groundwater levels in an area.

Regional water systems are being controlled to prevent flood events by different measures, such as water storage, weir management and vegetation maintenance. Vegetation maintenance has a significant effect on flood risk, because the hydraulic roughness decreases after cutting of vegetation. Stream restoration is a project in regional water systems, where floodplains are constructed and weirs are removed to recover the ecological value of streams. In streams with floodplains the vegetation is relatively more important because of smaller water depth. Moreover, climate change increases the flood risk, which increases the urgency to investigate the vegetation maintenance strategy.

A vegetation maintenance strategy involves of a cutting frequency, how often and when the vegetation is cut, and a cutting intensity, the percentage of the cross-section that is cut. The aim of this research is to optimize the performance of the vegetation maintenance strategy by consideration of the aspects ‘flood risk’, ‘ecological effects’ and ‘maintenance costs’. The research answers the following question: How can risk-based vegetation maintenance strategy reduce flood risk in a cost-effective way in regional water systems with consideration of ecological effects?

A case study, a recently flooded stream in the south of the Netherlands, is used to answer the research question. The performances of nine selected vegetation maintenance strategies are investigated. Dimensionless performance indicators are designed for the three aspects to assess the total performance of each vegetation maintenance strategy. For the aspect ‘maintenance costs’, data from a water board is retrieved and the aspect ‘ecological effects’ is assessed by a literature study. For the aspect ‘flood risk’, several steps are conducted. The vegetation maintenance strategy is translated into a probability distribution function of roughness coefficients. To that end, use is made of roughness functions including vegetation growth curves and roughness coefficients of the stream. Stochastic modelling of the water level by the hydraulic model Sobek 1D is used to examine the influence of vegetation maintenance on the water levels. A consequence model, the Water Damage Estimator, translates the results of the stochastic modelling step into flood risk. The three performances of the aspects are combined into the total performance of the vegetation maintenance strategy.

The results of the case study show that the timing of cutting has the largest influence on the flood risk, followed by the cutting frequency. The cutting intensity has the smallest influence on the flood risk. For a high performance of ‘maintenance costs’, a low cutting frequency is necessary. For a high ecological value, pattern cutting and cutting in August is important. In conclusion, for streams with floodplains the optimal vegetation maintenance strategy is ‘cutting of the main channel and parts of the floodplains before summer’.

The total performance of the vegetation maintenance strategy can be further optimized by a dynamic maintenance strategy with ‘roughness’ of the stream as maintenance trigger. Hereby, the vegetation maintenance strategy is dependent on the current roughness in spring. Moreover, it is found that the conclusions of the case study can be applied on many other streams in the Netherlands.