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Satellite gravimetry is a unique measurement technique for observing mass transport processes in the Earth system on a global scale, providing essential indicators of both subtle and dramatic global change. Although past and current satellite gravity missions have achieved spectacular science results, due to their limited spatial and temporal resolution as well as limited length of the available time series numerous important questions are still unresolved. Therefore, it is important to move from current demonstration capabilities to sustained observation of the Earth’s gravity field. In an international initiative performed under the umbrella of the International Union of Geodesy and Geophysics, consensus on the science and user needs for a future satellite gravity observing system has been derived by an international panel of scientists representing the main fields of application, i.e., continental hydrology, cryosphere, ocean, atmosphere and solid Earth. In this paper the main results and findings of this initiative are summarized. The required target performance in terms of equivalent water height has been identified as 5 cm for monthly fields and 0.5 cm/year for long-term trends at a spatial resolution of 150 km. The benefits to meet the main scientific and societal objectives are investigated, and the added value is demonstrated for selected case studies covering the main fields of application. The resulting consolidated view on the required performance of a future sustained satellite gravity observing system represents a solid basis for the definition of technological and mission requirements, and is a prerequisite for mission design studies of future mission concepts and constellations.

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WATERNOMICS focuses on the development of ICT as an enabling technology to manage water as a resource, increase end-user conservation awareness and affect behavioral changes. Unique aspects of WATERNOMICS include personalized feedback about end-user water consumption, the development of systematic and standards-based water resource management systems, new sensor hardware developments, and the introduction of forecasting and fault detection diagnosis to the analysis of water consumption data. These services will be bundled into the WATERNOMICS Water Information Services Platform. This paper presents the overall architectural approach to WATERNOMICS and details the potential interactive services possible based on this novel platform.

Monitoring Earth’s terrestrial water conditions is critically important to many hydrological applications such as global food production; assessing water resources sustainability; and flood, drought, and climate change prediction. These needs have motivated the development of pilot monitoring and prediction systems for terrestrial hydrologic and vegetative states, but to date only at the rather coarse spatial resolutions (∼10–100 km) over continental to global domains. Adequately addressing critical water cycle science questions and applications requires systems that are implemented globally at much higher resolutions, on the order of 1 km, resolutions referred to as hyperresolution in the context of global land surface models. This opinion paper sets forth the needs and benefits for a system that would monitor and predict the Earth’s terrestrial water, energy, and biogeochemical cycles. We discuss six major challenges in developing a system: improved representation of surface‐subsurface interactions due to fine‐scale topography and vegetation; improved representation of land‐atmospheric interactions and resulting spatial information on soil moisture and evapotranspiration; inclusion of water quality as part of the biogeochemical cycle; representation of human impacts from water management; utilizing massively parallel computer systems and recent computational advances in solving hyperresolution models that will have up to 109 unknowns; and developing the required in situ and remote sensing global data sets. We deem the development of a global hyperresolution model for monitoring the terrestrial water, energy, and biogeochemical cycles a “grand challenge” to the community, and we call upon the international hydrologic community and the hydrological science support infrastructure to endorse the effort.

In the last times, infiltration facilities to reduce the load on the drainage systems have been introduced in many urban areas. These facilities allow water to infiltrate or to drain depending of the level it reaches in the ground. It results easy to conclude that this infiltrating and draining process is likely to be controlled in real time so extra storage can be created on the urban subsurface when necessary or, on the other way round, store water when a shortage is expected. To study the possibilities of controlling the groundwater levels to create extra storage, an area of study was selected in the municipality of Delft, which was interested as well in being able to create extra storage. This area includes an infiltration system. After insight on the area was acquired, the only element which is likely to be controlled in the whole process turns to be the head levels at the infiltration facility. Therefore, it becomes necessary to find the influence the infiltration facility has on the groundwater system on its surroundings and obtain a model which allows tuning a proper controller afterwards. A mathematical model of the response of the groundwater levels within the area of study was created by using system identification. The inputs to this identification process are net precipitation, the historical precipitation and the water level at the infiltration facility. The output is, of course, the groundwater levels. All the data was obtained after a measurement campaign using both “in situ” measurements and remote sensing. Once a proper model was obtained, a simple feedback controller for the infiltration facility levels was tuned. A visible improvement on the groundwater levels behavior was observed when the controlled system was simulated. It results clear then that groundwater levels, within an area where an infiltration facility is present, can becontrolled in theory. A simple actuator was designed and built to be able to run practical experiments in the area later on. With this, the real relation of the infiltration system with the surrounding grounds can be checked as well as different control methods can be tried in further research.

A method for measuring whole-tree interception of precipitation is presented which employs mechanical displacement sensors to measure trunk compression caused by the water captured by the tree. This direct and nondestructive method is demonstrated to be sensitive to less than 5 kg of interception field tests in Netherlands and Ghana.

The temporal signature of terrestrial storage changes inferred from the Gravity Recovery and Climate Experiment (GRACE) has been assessed by comparison with outputs from a calibrated hydrological model (lumped elementary watershed (LEW)) of the upper Zambezi and surroundings and an inspection of the within?month ground track coverage of GRACE together with spatial?temporal rainfall patterns. The comparison of the hydrological model with GRACE reveals temporal inconsistencies between both data sets. Because the LEW model has been calibrated and validated with independent data sources, we believe that this is a GRACE artifact. The within?month ground track coverage shows an irregular orbit behavior which may well cause aliasing in the GRACE monthly deconvolutions. This aliasing is the most probable cause of observed temporal inconsistencies between GRACE and other data sets.

In semi-arid regions at the margins of the Sahel, large numbers of small reservoirs capture surface runoff during the rainy season, making water available during the dry season. For the local population, small reservoirs are important water sources which help them cope with droughts. The lack of knowledge of the number of existing reservoirs, their distribution, and their storage volumes hinders efficient water management and reservoir planning. The authors have developed a simple method that allows the estimation of reservoir storage volumes as a function of their surface areas. This function is based on an extensive bathymetrical survey that was conducted in the Upper East Region of Ghana. In combination with satellite imagery, this function can be used determine and monitor the storage volumes of large numbers of small reservoirs on a regional scale.

Rain gauges that count drops, mobile radars that scan clouds, and hundreds of wind vanes mounted on the windows of the EEMCS building. TU Delft researchers are busily transforming the campus into a laboratory for climate research in the urban environment.

This thesis set out to develop methodologies that promote cooperation, peace and development instead of conflict and violence in transboundary water resources management. In particular, its objectives were the following: o To examine and understand the complexity of water systems and water conflict management o To investigate factors affecting resilience of water treaties o To develop methods for equitable water allocation in transboundary river basins using bankruptcy theory o To develop a risk-based Multi Attribute Decision Making method (RB-MADM) to select, rank and/or classify alternatives among a set of available options in negotiation and decision making processes over shared natural resources o To demonstrate the applicability of the developed methods in practice through some real cases: the Euphrates and Tigris Rivers and the Caspian Sea. This thesis starts with an in-depth discussion of the complexity of transboundary water systems and the nexus between resource scarcity and resource conflict. Water systems are complex coupled human-natural systems. This complexity can be exacerbated when water is shared between two or more riparian countries. Shared water resources can be a source of both conflict and cooperation among riparian countries. Conflict resolution in a complex system is also a complex task that cannot be managed by means of scientific methods or modelling approaches only. This thesis focuses on conflict resolution in transboundary river basins. Rather than looking at the issues just from a technical point of view, the research endeavours to recognize the complexity in conflict resolution in transboundary river basins. The nexus between resource scarcity and resource conflict is analyzed in terms of several schools of thought, including the Neo-Malthusians, Cornucopians, and the Distributionists. Furthermore, the missing link between water scarcity, as a main issue in international water resources management, and water crisis and conflict is examined. The evidence suggests that water scarcity can be both a cause and the result of conflict. Water systems have been affected by various human and natural perturbations and changes, such as global environmental and climate changes that are at least partly humanly induced. These disturbances can potentially affect conflict and cooperation between riparian countries. Water treaties should be resilient to cope with these changes and disturbances. Chapter three raises questions concerning main factors affecting non-resilience of water treaties as well as some reasons increasing the difficulty of implementation of treaties. Additional insights into these factors can help to enhance their resilience and reduce the risk of conflict among riparian countries. Among several factors affecting hydropolitical relationships, water quantity is the perhaps most conflictive issue. The principle of “equitable and reasonable utilization” is the main normative principle referred to for allocating internationally shared water resources. Despite this, a serious limitation of international water laws and conventions is that they have not introduced a generally accepted allocation mechanism to achieve an equitable and reasonable water allocation. Therefore, equitable water allocation among riparian countries is one of the main critical issues in water conflict management. Using bankruptcy theory, as a form of cooperative game theory method, novel flexible allocation methods have been developed in chapters four and five. The proposed rules have been applied to the Euphrates and Tigris Rivers, shared between Turkey, Syria, and Iraq, to illustrate the application of the rule to a real conflictive allocation problem. The results reveal that the proposed approaches may facilitate negotiation and have a great potential to help solving conflict and dispute over river resources allocation problems in transboundary river basins. A risk-based Multi Attribute Decision Making method was developed to support consensus-based decision making over several allocation mechanisms. This method was applied to help establish the legal status of the Caspian Sea, which is shared among five states: Azerbaijan, Iran, Kazakhstan, Russia, and Turkmenistan. To date, these nations have been unable to reach an allocation agreement. We apply a methodology to propose the most appropriate solution among a set of options under different risk attitudes of the states. The analyses show that the overall ranking of options varies even when the states slightly change their risk attitudes from pessimistic to fairly pessimistic.

Fresh water supply and flood protection are two central issues in water management. Society needs more and more fresh water and a safe water system to guarantee a better life. A more severe climate will result in more droughts and extreme storms. As a consequence, salt water intrusion will increase. Therefore, clean and fresh water is becoming scarce. Potentially, there lies a severe conflict between people's demands and what nature can provide. In practice, water systems are complex. Both water quantity and quality criteria must be served. Moreover, water is normally used as a multi-functional resource. For example, water in a reservoir is used for irrigation, power generation, flood protection and reclamation. These objectives are usually in conflict most of the time and it is not easy for people to cope with these contradictions. Smart regulation of water systems is essential not only from the world-wide water issue perspective, but also from the specific water problem aspect. Real-time control is a powerful tool to help people with accurate regulation of water systems. In practice, water quantity control is extensively studied, but fully integrated water quantity and quality control has hardly been touched. Moreover, in order to deal with multi-objectives in a water system, advanced control techniques, such as model predictive control (MPC), are often required which require extensive computational resources. This brings forward two research questions: 1: What is the possibility of controlling both water quantity and quality in a water system? 2: In MPC, what is the possibility to reduce the computational burden in order to make the control implementation possible? In this PhD thesis, a case of polder flushing in real-time is selected for the first research question, which includes both water quantity and quality problems.The task is to flush polluted water out of the polder with clean water while keeping water levels close to the setpoints. Instead of manual operation which is often applied in practice, control systems were designed with feedback control and MPC. In MPC, different types of internal models were applied ranging from a linear reservoir model to hydrodynamic models. The different control performance of the two controllers were compared. We conclude that real-time control is possible to maintain both water quantity and quality at the same time in a one dimensional water system model. Furthermore, MPC performs much better than the classic feedback control in controlling the water quality when operational limits are very strict. In MPC, using different internal models will also result in different control performance, affecting both control effectiveness and computation time. Being an advanced control technique, MPC is playing a more and more important role in controlling water systems. The computational burden is the main barrier for MPC implementation. In this PhD thesis, we propose a control procedure of MPC with a model reduction technique, Proper Orthogonal Decomposition (POD), in order to speed up the computation. POD is able to reduce the order of states and disturbances, and speed up the matrix operation in MPC. In a test case, we concluded that MPC using the reduced model is a good trade-off between control effectiveness and computation time. Therefore, the proposed MPC procedure is considered as a successful method for MPC implementation.

Water systems consist of natural and man-made objects serving multiple essential purposes. They are affected by many types of meteorological disturbances. In order to deal with these disturbances and to serve the desired objectives, infrastructures have been built and managed by societies for specific purposes. Given a water system, and its purposes, the control of the existing infrastructures is the subject of operational water management. The system controller, either a natural person or a mathematical algorithm, takes his recursive decisions observing the state of the system and trying to bring it to the desired condition. Model Predictive Control (MPC) is an advanced method for the control of complex dynamic systems. When applied to water systems operation, MPC provides integrated and optimal management. If disturbance forecasts are available, this information can be integrated in the control policy and water management becomes proactive. Before the realization of the disturbance, the MPC controller sets the system to a state which is optimal to accommodate the expected disturbance. A typical example is lowering the water level of a reservoir before an expected storm event in order to avoid floods. In proactive control of open water systems, the main uncertainty is generally related to the difficulty of producing good forecasts. Weather and hydrological processes are difficult to predict, and meteorological or rainfall-runoff models can be wrong. Especially when using only one deterministic estimate, the control is more vulnerable to forecast uncertainty, running the risk of taking action against a predicted event that will not occur. The research question of this thesis is: How to use existing forecasting methods in optimal control schemes, thereby enhancing robustness in the face of forecasting uncertainty? In open water systems, such as rivers, canals, or reservoirs, the available forecast is generally the natural inflow, which is the output of a deterministic rainfall-runoff model. The model produces a point estimate, which is the expected value of the variable of interest. Nevertheless, the nonlinearity of the control problem requires the forecast of the entire probability distribution. When residuals are assumed independent, identically distributed, zero-mean, and Gaussian, then the variance is the only extra parameter required to build up the entire distribution, and its value can be estimated from the data. However, residuals of rainfall-runoff models are in fact heteroscedastic (i.e. the variance changes in time) and autocorrelated. In Chapter 2 it is shown how to deal with both deficiencies. Dynamic modelling of predictive uncertainty is built up by regression on absolute residuals, and applied to two test cases: the Rhone River, in Switzerland, and Lake Maggiore, at the border between Italy and Switzerland. When the information on the catchment state does not offer sufficient anticipation, for example because the catchment dynamics are fast compared to the controlled system, it is necessary to include weather forecasts. Meteorological agencies produce not only a deterministic trajectory of the future state of the weather system, but a set of them, called ensemble, to communicate the forecast uncertainty. The algorithm presented in Chapter 3, called Tree-Based Model Predictive Control (TB-MPC), exploits the information contained in the ensemble, setting up a Multistage Stochastic Programming (MSP) problem within the MPC framework. MSP is a stochastic optimization scheme that takes into account not only the present uncertainty, but its resolution in time as well. Going on in time along the control horizon, information will enter the system. Consequently, uncertainty will be reduced, and the control strategy after uncertainty reduction will change according to the occurring ensemble member. The key idea of TB-MPC is producing a tree topology from the ensemble data and using this tree in the following MSP optimization. A tree specifies in fact the moments when uncertainties are resolved. Generating a tree from ensemble data is both difficult and of critical importance. It has been considered an open problem until now, especially regarding the tree branching structure, which also strongly affects control performance. Chapter 4 shows a new methodology that produces a tree topology from ensemble data. The proposed method models the information flow to the controller. This implies the explicit definition of the available observations and their degree of uncertainty. Chapter 5 summarizes the contribution of my PhD and the research directions that, in my opinion, deserve more investigation.

Terrestrial Gamma-ray Flashes (TGF) are very short bursts of gamma-rays associated to thunderstorm activity, cur- rently observed by detectors onboard satellites or research airplanes. TGFs are likely produced by Bremsstrahlung of energetic electrons accelerated by a mechanism (e.g., the Relativistic Runaway Electron Avalanche mechanism, RREA) in close association with the lightning leader propagation. The AGILE satellite is one of the only three currently active space instruments capable of TGF detection and is especially tailored for the detection of high- energy photons in the tens of MeV regime. Up to November 2011 the full AGILE TGF sample includes more than 300 events, with an average detection rate of about 10 TGFs/month. AGILE indicates that TGF high energy spectral behaviour deviates from the canonical RREA model, reporting photon energies as large as 100MeV which require electrons acceleration across a large fraction of the full available potential difference in a thundercloud. We will report on the most recent AGILE observations that suggest the existence of two distinct populations in our TGF sample. The first population includes about 90% of the TGFs and consists of events with maximum energy lower than 30 MeV, whose cumulative spectrum can be well described by a powerlaw with exponential cutoff well reproduced by the canonical RREA model. The geographical and local time distributions of this population well match those of standard lightning. The remaining 10% of the AGILE TGF sample include events with photon energy as large as 100 MeV and a cumulative spectrum well described by a powerlaw with no evidence for a spectral cutoff. This spectral behaviour can hardly be reconciled with the standard RREA model. The geographical distribution of this latter sub-class may be different from the low-energy sub-class. We discuss the hypothesis that this high-energy population is a separate class of TGFs whose production process and parent lightning can differ significantly from the bulk of TGFs population. We present the characteristics of the two TGF populations, with particular emphasis on their different spectral and geographical properties. Finally, we speculate on the properties of the parent lightning that can be conducive to the high-energy population.

In this thesis, a riverflow modelling framework developed for monthly riverflow prediction in the 400,000 km2 Volta Basin of West Africa is presented. By analysing available catchment rainfall, runoff and potential evapotranspiration series in the basin using methods such as correlation plots, autoregressive (AR) and autoregressive with exogenous input (ARX) modelling, it is shown that the monthly catchment rainfall-runoff process is better characterised by non-linear models. First, a spatio-temporal linear dynamic model employing the Kalman smoother and the Expectation-Maximisation (EM) algorithm was developed and applied to filling in short gaps, of up to one month, in daily riverflow series in the basin. This model was found to be a very good and powerful tool for filling in such data gaps. Then, two non-linear modelling frameworks - a non-linear autoregressive and moving average with exogenous input (NARMAX) polynomial and a data-based mechanistic (DBM) modelling framework - were developed and applied to the monthly rainfall-runoff series in the basin for river catchment runoff prediction. Both methods predicted monthly runoff adequately, with the DBM framework also providing physically interpretable results. This indicates that data-driven approaches are appropriate for riverflow modelling in the data-poor Volta Basin