Maurizio Mazzoleni

Vrije Universiteit Amsterdam | VU

Advances in impact modeling and numerical weather forecasting have allowed accurate drought monitoring and skilful forecasts that can drive decisions at the regional scale. State‐of‐the‐art drought early‐warning systems are currently based on statistical drought indicators, which do not account for dynamic regional vulnerabilities, and hence neglec...

What role can a speculative political ecology play in (re)imaging urban futures of climate extremes? In recent years, narratives of dystopian futures of climate extremes have proliferated in geosciences, and across the media and creative arts. These anxiety-fueled narratives often generate a sense of resignation and unavoidability, which contribute...

Flooding during or after droughts poses significant challenges to disaster risk management. However, interactions between droughts and floods are often overlooked by studying these events individually, with potential under- or overestimation of flood risk. Here we analyse global datasets of hydrometeorological and biophysical variables for 8255 cat...

As the adverse impacts of hydrological extremes increase in many regions of the world, a better understanding of the drivers of changes in risk and impacts is essential for effective flood and drought risk management and climate adaptation. However, there is currently a lack of comprehensive, empirical data about the processes, interactions, and fe...

Over the past two decades, more than 80 metropolitan cities across the world have faced severe water shortages due to droughts and unsustainable water use. Future projections are even more alarming, since urban water crises are expected to escalate and most heavily affect those who are socially, economically and politically disadvantaged. Here we s...

Societal awareness is a crucial factor driving floodplain dynamics. When modelling these dynamics, flood awareness decay is considered constant. However, empirical studies have shown that the intensity of an experienced event can influence awareness decay. Here we explore and model the influence of variable flood awareness decay on flood losses for...

As the adverse impacts of hydrological extremes increase in many regions of the world, a better understanding of the drivers of changes in risk and impacts is essential for effective flood and drought risk management and climate adaptation. However, there is currently a lack of comprehensive, empirical data about the processes, interactions and fee...

In this manuscript, we present B-AMA (Basic dAta-driven Models for All), an easy, flexible, fully coded Python-written protocol for the application of data-driven models (DDM) in hydrology. The protocol, which is open source and freely available for academic and non-commercial purposes, has been realized to allow early career scientists, with a bas...

Human actions are increasingly altering most river basins worldwide, resulting in changes in hydrological processes and extreme events. Yet, global patterns of changes between seasonal surface water and urbanization remain largely unknown. Here we perform a worldwide analysis of 106 large river basins and uncover global trends of annual maximum flo...

Risk management has reduced vulnerability to floods and droughts globally1,2, yet their impacts are still increasing³. An improved understanding of the causes of changing impacts is therefore needed, but has been hampered by a lack of empirical data4,5. On the basis of a global dataset of 45 pairs of events that occurred within the same area, we sh...

Whether disasters influence adaptation actions in cities is contested. Yet, the extant knowledge base primarily consists of single or small-N case studies, so there is no global overview of the evidence on disaster impacts and adaptation. Here, we use regression analysis to explore the effects of disaster frequency and severity on four adaptation a...

Probabilistic methods are widely adopted for residual flood hazard assessment in flood‐prone areas protected by levees. Such methods can consider various sources of uncertainty, including breach location and flood event characteristics, and allow for the quantification of the result confidence. However, the possible occurrence of multiple levee bre...

We present a system-dynamics model to simulate the interplay between water management, hydrological extremes (droughts and floods), and society. We illustrate the potential and limitations of the model with an example application to the Brisbane river basin (Australia). In particular, we test its capability to explain various phenomena that have be...

Predicting floods and droughts is essential to inform the development of policy in water management, climate change adaptation and disaster risk reduction. Yet, hydrological predictions are highly uncertain, while the frequency, severity and spatial distribution of extreme events are further complicated by the increasing impact of human activities...

Efficient water resources management is highly dependent on the use of simulation modelling although the success of simulation modelling calls for the availability of sufficient hydrometeorological and other required data. Scarcity of hydrometeorological data limits the possibility of optimal water management using simulated information. Advances i...

The sustainability of large dams has been questioned on several grounds. One aspect that has been less explored is that the development of dams and reservoirs often enables agricultural expansion and urban growth, which in turn increase water consumption. As such, dam development influences, while being influenced by, the spatial and temporal distr...

This study presents a global explanatory analysis of the interplay between the severity of flood losses and human presence in floodplain areas. In particular, we relate economic losses and fatalities caused by floods during 1990‐2000, with changes in human population and built‐up areas in floodplains during 2000‐2015 by exploiting global archives....

In this study, we explore the long-term trends of floodplain population dynamics at different spatial scales in the contiguous United States (U.S.). We exploit different types of datasets from 1790–2010—i.e., decadal spatial distribution for the population density in the US, global floodplains dataset, large-scale data of flood occurrence and damag...

Natural hazard events provide opportunities for policy change to enhance disaster risk reduction (DRR), yet it remains unclear whether these events actually fulfill this transformative role around the world. Here, we investigate relationships between the frequency (number of events) and severity (fatalities, economic losses, and affected people) of...

Most research on hydrological risks focuses either on flood risk or drought risk, whilst floods and droughts are two extremes of the same hydrological cycle. To better design disaster risk reduction (DRR) measures and strategies, it is important to consider interactions between these closely linked phenomena. We show examples of: (a) how flood or d...

Widely available digital technologies are empowering citizens who are increasingly well informed and involved in numerous water, climate, and environmental challenges. Citizen science can serve many different purposes, from the “pleasure of doing science” to complementing observations, increasing scientific literacy, and supporting collaborative be...

Floods are the natural hazards that are causing the most deaths worldwide. Flood early warning systems are one of the most cost-efficient methods to reduce death rates, triggering decisions about evacuation of exposed population. Although previous studies have investigated the effect of human behaviours on evacuation processes, studies analysing a...

The past few years have seen the raise of unmanned aerial vehicles (UAV) in geosciences for generating highly accurate digital elevation models (DEM) at low costs, which promises to be an interesting alternative to satellite data for small river basins. The reliability of UAV-derived topography as input to hydraulic modelling is still under investi...

Dry spells are sequences of days without precipitation. They can have negative implications for societies, including water security and agriculture. For example, changes in their duration and within-year timing can pose a threat to food production and wildfire risk. Conversely, wet spells are sequences of days with precipitation above a certain thr...

Over the last few years, several socio-hydrological studies have investigated the risk dynamics generated by the complex interactions between floods and societies, with a focus on either changing reservoir operation rules or raising levees. In this study, we propose a new socio-hydrological model of human–flood interactions that represents both cha...

Two-way interactions and feedback between hydrological and social processes in settled floodplains determine the complex human–flood system and change vulnerability over time. To focus on the dynamic role of individual and governmental decision making on flood-risk management, we developed and implemented a coupled agent-based and hydraulic modelli...

Multi-hazard events can be associated with larger socio-economic impacts than single-hazard events. Understanding the spatio-temporal interactions that characterize the former is therefore of relevance to disaster risk reduction measures. Here, we consider two high-impact hazards, namely wet and dry hydrological extremes, and quantify their global...

Poorly monitored catchments could pose a challenge in the provision of accurate flood predictions by hydrological models, especially in urbanized areas subject to heavy rainfall events. Data assimilation techniques have been widely used in hydraulic and hydrological models for model updating (typically updating model states) to provide a more relia...

Flood hazard maps are useful tools for land planning and flood risk management in order to increase the safety of flood‐prone areas that can be inundated in the event of levee failure. However, flood hazard assessment is affected by various uncertainties, both aleatory and epistemic. The flood hazard analysis should hence take into account the main...

We compare statistical and hydrological methods to estimate design floods by proposing a framework that is based on assuming a synthetic scenario considered as ‘truth’ and use it as a benchmark for analysing results. To illustrate the framework, we used probability model selection and model averaging as statistical methods, while continuous simulat...

This chapter aims to describe the latest innovative approaches for integrating heterogeneous observations from static social sensors within hydrological and hydrodynamic modelling to improve flood prediction. The distinctive characteristic of such sensors, with respect to the traditional ones, is their varying lifespan and space-time coverage as we...

We are experiencing a proliferation of satellite derived precipitation datasets. Advantages and limitations of their promising application in hydrological modelling application have been broadly investigated. However, most studies have analysed only the performance of one or few datasets, were limited to selected small-scale case studies or used lu...

This study aims at proposing novel approaches for integrating qualitative flow observations in a lumped hydrologic routing model and assessing their usefulness for improving flood estimation. Routing is based on a three‐parameter Muskingum model used to propagate streamflow in five different rivers in the USA. Qualitative flow observations, synthet...

Over the past decades, a variety of valuable research studies has helped to advance our understanding of the advantages and limitations of satellite derived precipitation datasets as a forcing to hydrological models, in combination with or as an alternative to gauge data. However, most studies have assessed the performance of only one single datase...

Multi-hazard events can be associated with larger socio-economic impacts than single-hazard events. Understanding the spatio-temporal interactions characterising the former is, therefore, of relevance to disaster risk reduction measures. Here, we consider two high-impact hazards, namely wet and dry hydrological extremes, and quantify their global c...

This paper is the outcome of a community initiative to identify major unsolved scientific problems in hydrology motivated by a need for stronger harmonisation of research efforts. The procedure involved a public consultation through on-line media, followed by two workshops through which a large number of potential science questions were collated, p...

Multi-hazard events can be associated with larger socio-economic impacts than single-hazard events. Understanding the spatio-temporal interactions characterising the former is, therefore, of relevance to disaster risk reduction measures. Here, we consider two high-impact hazards, namely wet and dry hydrological extremes, and quantify their global c...

It is crucial to be able to forecast flows and overflows in urban drainage systems to build good and effective real-time control and warning systems. Due to computational constraints, it may often be unfeasible to employ detailed 1D hydrodynamic models for real-time purposes, and surrogate models can be used instead. In rural hydrology, forecast mo...

Places with limited coverage of rainfall gauges could present the challenge of providing accurate predictions, especially in cases of urbanised areas with rapid responses to heavy rainfall events. Physically-based models can represent the physics and spatial distribution of rainfall events in urban watersheds. Data assimilation techniques have been...

The design of flood defence structures requires the estimation of flood water levels corresponding to a given probability of exceedance, or return period. In river flood management, this estimation is often done by statistically analysing the frequency of flood discharge peaks. This typically requires three main steps. First, direct measurements of...

Sustainable water management is one of the important priorities set out in the Sustainable Development Goals (SDGs) of the United Nations, which calls for efficient use of natural resources. Efficient water management nowadays depends a lot upon simulation models. However, the availability of limited hydro-meteorological data together with limited...

One common approach to cope with floods is the implementation of structural flood protection measures, such as levees or flood-control reservoirs, which substantially reduce the probability of flooding at the time of implementation. Numerous scholars have problematized this approach. They have shown that increasing the levels of flood protection ca...

Many cities face issues with rain induced flooding and combined sewer overflows, which can be addressed by using hydrodynamic models. These models are often simplified in a real-time setting to make them faster, and their performance can be improved by using data assimilation. In this study we use the Ensemble Kalman Filter to update a simplified m...

Places with limited coverage of rainfall gauges could present the challenge of providing accurate predictions, especially in cases of urbanised areas with rapid responses to heavy rainfall events. Physically-based models can represent the physics and spatial distribution of rainfall events in urban watersheds. Data assimilation techniques have been...

To understand the spatiotemporal changes of flood risk, we need to determine the way in which humans adapt and respond to flood events. One adaptation option consists of resettling away from flood-prone areas to prevent or reduce future losses. We use satellite nighttime light data to discern the relationship between long-term changes in human prox...

One common approach to cope with floods is the implementation of structural flood protection measures, such as levees or flood-control reservoirs, which substantially reduce the probability of flooding at the time of implementation. Numerous scholars have problematized this approach. They have shown that increasing the levels of flood protection ca...

Diverse hydrologic and hydraulic models of varying complexities have been proposed in the past few decades to accurately predict the water levels and discharges along rivers. Among them, the hydrologic routing models are widely used because of their simplicity, minimal data, and computational requirements. Due to their simplified assumptions, howev...

This paper comparatively assesses the performance of five data assimilation techniques for three parameter Muskingum routing with a spatially lumped or distributed model structure. The assimilation techniques used include direct insertion (DI), nudging scheme (NS), Kalman filter (KF), ensemble Kalman filter (EnKF) and asynchronous ensemble Kalman f...

To improve hydrological predictions, real-time measurements derived from traditional physical sensors are integrated within mathematic models. Recently, traditional sensors are being complemented with crowdsourced data (social sensors). Although measurements from social sensors can be low cost and more spatially distributed, other factors like spat...

One common approach to cope with floods is the implementation of structural flood protection measures, such as levees or flood-control reservoirs, which substantially reduce the probability of flooding at the time of implementation. Numerous scholars have problematized this approach. They have shown that increasing the levels of flood protection ca...

As flood impacts are increasing in large parts of the world, understanding the primary drivers of changes in risk is essential for effective adaptation. To gain more knowledge on the basis of empirical case studies, we analyze eight paired floods, i.e. consecutive flood events that occurred in the same region, with the second flood causing signific...

Monitoring stations have been used for decades to properly measure hydrological variables and better predict floods. To this end, methods to incorporate these observations into mathematical water models have also been developed. Besides, in recent years, the continued technological advances, in combination with the growing inclusion of citizens in...

In recent years, the continued technological advances have led to the spread of low-cost sensors and devices supporting crowdsourcing as a way to obtain observations of hydrological variables in a more distributed way than the classic static physical sensors. The main advantage of using these type of sensors is that they can be used not only by tec...

The aim of this study is to assess the influence of sensor locations and varying observation accuracy on the assimilation of distributed streamflow observations, also taking into account different structures of semi-distributed hydrological models. An ensemble Kalman filter is used to update a semi-distributed hydrological model as a response to me...

The reliability of a levee system is a crucial factor in flood risk management. In this study we present a probabilistic methodology to assess the effects of levee cover strength on levee failure probability, triggering time, flood propagation and consequent impacts on population and assets. A method for determining fragility curves is used in comb...

In this study, we carried out a series of hindcasting experiments in order to evaluate the effects of two hydrological routing model structures, lumped or distributed, on downstream flow predictions posterior to assimilating downstream flow observations. The hydrologic routing model used is a 3-parameter Muskingum, proposed by [1]. In case of distr...

The EC-FP7 WeSenseIt project proposes to develop a Citizen Observatory of wate r, aiming at enhancing environmental monitoring and forecasting with the help of citizens equipped with low-cost sensors and personal devices such as smartphones and smart umbrellas. At this point, the following question arises: how can citizens, who are part of a citize...

Accurate flood predictions are essential to reduce the risk and damages over large urbanized areas. To improve prediction capabilities, hydrological measurements derived by traditional physical sensors are integrated in real-time within mathematic models. Recently, traditional sensors are complemented with low-cost social sensors. However, measurem...