ALBERT

Description: As the negative impacts of hydrological extremes increase in large parts of the world, a better understanding of the drivers of change in risk and impacts is essential for effective flood and drought risk management and climate adaptation. However, there is a lack of comprehensive, empirical data about the processes, interactions and feedbacks in complex human-water systems leading to flood and drought impacts. To fill this gap, we present an IAHS Panta Rhei benchmark dataset containing socio-hydrological data of paired events, i.e. two floods or two droughts that occurred in the same area (Kreibich et al. 2017, 2019). The contained 45 paired events occurred in 42 different study areas (in three study areas we have data on two paired events), which cover different socioeconomic and hydroclimatic contexts across all continents. The dataset is unique in covering floods and droughts, in the number of cases assessed and in the amount of qualitative and quantitative socio-hydrological data contained. References to the data sources are provided in 2022-002_Kreibich-et-al_Key_data_table.xlsx where possible. Based on templates, we collected detailed, review-style reports describing the event characteristics and processes in the case study areas, as well as various semi-quantitative data, categorised into management, hazard, exposure, vulnerability and impacts. Sources of the data were classified as follows: scientific study (peer-reviewed paper and PhD thesis), report (by governments, administrations, NGOs, research organisations, projects), own analysis by authors, based on a database (e.g. official statistics, monitoring data such as weather, discharge data, etc.), newspaper article, and expert judgement. The campaign to collect the information and data on paired events started at the EGU General Assembly in April 2019 in Vienna and was continued with talks promoting the paired event data collection at various conferences. Communication with the Panta Rhei community and other flood and drought experts identified through snowballing techniques was important. Thus, data on paired events were provided by professionals with excellent local knowledge of the events and risk management practices.

Description: Floods are becoming more frequent due to unplanned urbanization, climate change, and poor control of mitigation strategies such as detention ponds and stormwater reservoirs. They can have better flood control performance if active control is implemented. Orifices can be retrofitted with controlled valves and spillways can have movable gates, allowing better control of flooding in real-time. In this paper, we develop a model predictive control (MPC) algorithm to maximize flood performance by actively controlling the valve and gate openings in a real-world detention pond and in real-time. To this end, a watershed model is developed, and its generated runoff is directly connected to the detention pond. Estimation of the inflow hydrograph is performed via a distributed hydrodynamic diffusive-like model that served as the input data for an MPC algorithm that optimally solves the control schedule of the valves and gates and determines the reservoir operation over time. The numerical case studies show how the watershed hydrodynamic model compares with HEC-RAS for steady and unsteady rain-on-the-grid events and how the MPC strategy outperforms the passive control (i.e., valves and gates always opened). We compared MPC performance with the passive scenario under design storms and under a 1-year continuous simulation with spatially varied rainfall and evapotranspiration in the watershed. This work is the continuation of the recent published work entitled “Flood Risk Mitigation and Valve Control in Stormwater Systems: State-Space Modeling, Control Algorithms, and Case Studies”.

Description: Given the global context of environmental change presented by the Sixth Intergovernmental Panel on Climate Change (IPCC) Assessment Report (AR6), unprecedented extreme events are becoming more frequent due to human-induced climate changes, thus being considered as “surprises”. On the one hand, extreme weather events can lead to disasters when interacting with vulnerable social conditions. On the other hand, climate services are decision aids derived from climate information that assist society to make improved ex-ante decision-making. But the change in frequency of extremes of a certain magnitude also encounters human systems with different spatiotemporal degrees of vulnerability, with an increase of the price of risk premium and insurance availability in disaster-prone areas. We hypothesize that coupled human-environment changes require a more comprehensive multi-risk assessment procedure that incorporates pathways of climate change and societal adaptation, rather than only relying on historical data on disasters. First, our new index-based insurance for multi-hazard risk (I2MHR) framework promotes a dynamic resilience when including climate change scenarios by Shared Socioeconomic Pathways (SSP) with difference Representative Concentration Pathways (RCP) [1]. Second, the I2MHR concept brings smaller premiums when compared to a sum of uni-hazard-uni-risk coverage, with a non-stationary transitional behavior depending on the Confidence Level, the Loss Amount, Tail-Value-at-Risk and Expected Annual Damage .Third, we discuss how dynamic resilience permeates in the I2MHR, when it incorporates both changes in frequency and severity of extreme events and variability of vulnerability. [1] https://doi.org/10.5194/egusphere-2022-498

Description: Tropical freshwater reservoirs (TFR) are key systems for the allocation and supply of water for competing multiple purposes. Unprecedented droughts, attributed to climate change, make the planning and management of multipurpose water security of TFR increasingly complex. Indeed, to achieve viable Sustainable Development Goals (SDGs), new local water-human peculiarities constrain even more their multisectorial risks, including ecosystem's resilience. Supported by the FAPESP-FACEPE project "Global changes and sustainable development with water-energy viability and economic solvency", we propose insurance mechanisms to optimize TFR functionality by interlinking allocation for water, energy, food and ecosystem (WEFE nexus), mitigating impacts of extreme events, and adapting society to learn from changes, balancing economic water benefits over wet and dry periods and thus dampening water demand during droughts. We analyze adaptive risk-transfer pathways of introducing insurance mechanisms to attain WEFE allocation in TFRs of Northeast and Southeast Brazil. Thus, we discuss promising tradeoffs of flexible schemes, alternative water uses, regulatory framework and innovation, e.g. hybrid energy generation, recycling water habits, water reuse incentives and ecosystem restoration.

Description: The hydrological cycle has been intensified by climate change, and more people are exposed to extreme events such as floods and droughts, exacerbating water-related vulnerabilities. Global warming has resulted in unprecedented changes not only in the quantity of water but also in quality. More intense rainfall due to climate change would lead to greater rates of erosion, which would cause an increase in suspended solids in lakes and reservoirs. Also, due to the lower dilution capacity in drought events, the concentration of eutrophication-enhancing pollutants may increase and, further, there is a growing concern that this changing environment affects the structure and composition of the phytoplankton community, including a greater prevalence and geographic spread of harmful algal blooms, events that can produce toxic substances, in addition to making the treatment difficult and expensive. In this way, both hydrological extremes and water quality degradation impact the water supply generating financial losses to water utilities and welfare losses to end users. Index insurance has been investigated as a potential solution for coping with hydrological drought events that lead to water insecurity in the water supply sector. However, the supply sector is not only affected by drought events but also by flood and water pollution. Therefore, this work aims to propose a framework to nourish risk transfer mechanisms application to cover financial and welfare losses incurred by water utility companies and end-users as a result of these hydrological extremes, bringing opportunities to improve insurance application to the sector.

Description: Hydrological droughts have affected several cities worldwide. The communities and the decision makers have not only searched for alternative water sources, but also for improving the management of the water available. Despite all the technology and knowledge, managing water resources remains a challenge because of all the uncertainties and the stakeholders involved. This is the case of the Sao Paulo Metropolitan Region, where a water supply system, responsible to deliver water to millions of people, operated below the dead pool level for almost a year during a drought event between 2013 and 2015. Therefore, this study borrows the Failure Mode and Effect Analysis (FMEA) from the risk-management literature to estimate if there was a right moment when the water saving policies should have started to avoid the reservoirs’ emptiness. Thus, the FMEA methodology was combined with a system dynamic model to represent the reservoir’s processes and find the Risk Priority Number (RPN) that indicates such moment. The optimization demonstrated that the RPN equal to 550 would be the target to start the water saving policies, observed at the drought period, and avoid the reservoir from reaching the dead pool level. Finally, an alternative scenario considering the ideal RPN concludes that the FMEA would have led decision makers to start those policies 3 months in advance in comparison to the baseline.

Description: Drought episodes that are spatially compounding affect numerous locations at the same time and can have serious consequences for water risk management. Risk management is critical for survival in changing environments; thus, risk pooling, a type of informal social insurance, involves sharing risk with others and can protect individuals against unexpected losses. To construct an effective pool, however, individuals must be separated into groups exposed to the same risk at different times. Thus, we classify 511 Brazilian catchments into drought similarity regions based on hydrological drought spatial connectedness. We use a hierarchical clustering algorithm using the drought characteristics, i.e., deficit, intensity, duration, the number of events, and spatial connectedness to define similar regions. The suitable number of clusters was defined by the computation of the hierarchical clustering tree at different levels and the average silhouette width. Our findings indicate that Brazil can be classified into five regions with comparable local and regional drought characteristics, as well as catchment characteristics. Risk pooling regions could then be formed by joining catchments from different drought similarity regions. Because spatially compounding events are a systemic risk, the risk pooling regions can reduce management costs among members. Our research contributes to the development of future adaptation plans for hydrological extreme multi-hazards at the catchment and regional scales, as well as risk-transfer mechanisms. Acknowledgment: This study was supported by the OUR-EYES project under the FAPESP/FACEPE grant 2022/07521-5.