Peter Burek

Assimilation of MODIS Snow Cover Area Data in a Distributed Hydrological Model Using the Particle Filter

Snow is an important component of the water cycle, and its estimation in hydrological models is of great significance concerning the simulation and forecasting of flood events due to snow-melt. The assimilation of Snow Cover Area (SCA) in physical distributed hydrological models is a possible source of improvement of snowmelt-related floods. In this study, the assimilation in the LISFLOOD model of the MODIS sensor SCA has been evaluated, in order to improve the streamflow simulations of the model. This work is realized with the final scope of improving the European Flood Awareness System (EFAS) pan-European flood forecasts in the future. For this purpose daily 500 m resolution MODIS satellite SCA data have been used. Tests were performed in the Morava basin, a tributary of the Danube, for three years. The particle filter method has been chosen for assimilating the MODIS SCA data with different frequencies. Synthetic experiments were first performed to validate the assimilation schemes, before assimilating MODIS SCA data. Results of the synthetic experiments could improve modelled SCA and discharges in all cases. The assimilation of MODIS SCA data with the particle filter shows a net improvement of SCA. The Nash of resulting discharge is consequently increased in many cases.

Technologies to Support Community Flood Disaster Risk Reduction

Abstract Floods affect more people globally than any other type of natural hazard. Great potential exists for new technologies to support flood disaster risk reduction. In addition to existing expert-based data collection and analysis, direct input from communities and citizens across the globe may also be used to monitor, validate, and reduce flood risk. New technologies have already been proven to effectively aid in humanitarian response and recovery. However, while ex-ante technologies are increasingly utilized to collect information on exposure, efforts directed towards assessing and monitoring hazards and vulnerability remain limited. Hazard model validation and social vulnerability assessment deserve particular attention. New technologies offer great potential for engaging people and facilitating the coproduction of knowledge.

A multi-criteria optimisation of scenarios for the protection of water resources in Europe: Support to the EU Blueprint to Safeguard Europe’s Waters

A modelling environment has been developed to assess optimum combinations of water retention measures, water savings measures, and nutrient reduction measures for continental Europe. This modelling environment consists of linking the agricultural CAPRI model, the LUMP land use model, the LISFLOOD water quantity model, the EPIC water quality model, the LISQUAL combined water quantity, quality and hydro-economic model, and a multi-criteria optimisation routine. Simulations have been carried out to assess the effects of water retention measures, water savings measures, and nutrient reduction measures on several hydro-chemical indicators, such as the Water Exploitation Index, Environmental Flow indicators, N and P concentrations in rivers, the 50-year return period river discharge as an indicator for flooding, and economic losses due to water scarcity for the agricultural sector, the industrial sector, and the public sector. Also, potential flood damage of a 100-year return period flood has been used as an indicator.

Integrating remotely sensed surface water extent into continental scale hydrology

Highlights • First continent-scale assimilation of surface water extent into hydrological model.• Improvements in flood peaks timing and volume for 60% of validated gauges.• Daily surface water extent provide promising opportunities for ungauged regions.

Multi-model and multi-scenario assessments of Asian water futures: the Water Futures and Solutions (WFaS) initiative

This paper presents one of the first quantitative scenario assessments for future water supply and demand in Asia to 2050. The assessment, developed by the Water Futures and Solutions (WFaS) initiative, uses the latest set of global climate change and socioeconomic scenarios and state-of-the-art global hydrological models. In Asia, water demand for irrigation, industry and households is projected to increase substantially in the coming decades (30-40% by 2050 compared to 2010). These changes are expected to exacerbate water stress, especially in the current hotspots such as north India and Pakistan, and north China. By 2050, 20% of the land area in the Asia-Pacific region, with a population of 1.6-2 billion, is projected to experience severe water stress. We find that socioeconomic changes are the main drivers of worsening water scarcity in Asia, with climate change impacts further increasing the challenge into the 21st century. Moreover, a detailed basin-level analysis of the hydro-economic conditions of 40 Asian basins shows that although the coping capacity of all basins is expected to improve due to GDP growth, some basins continuously face severe water challenges. These basins will potentially be home to up to 1.6 billion people by mid-21st century.

The impact of lake and reservoir parameterization on global streamflow simulation

Highlights • The effects of lakes and reservoirs on global daily streamflow are evaluated.• Reservoirs affect model performance substantially in the global domain.• Lakes’ effects on model performance are limited to few catchments.• Lakes and reservoirs reduce return levels discharge thresholds globally.• Reservoir parameters contribute to uncertainty of model performance metrics.

A continental-scale hydro-economic model for integrating water-energy-land nexus solutions

This study presents the development of a new bottom‐up large‐scale hydro‐economic model, Extended Continental‐scale Hydro‐economic Optimization (ECHO), that works at a sub‐basin scale over a continent. The strength of ECHO stems from the integration of a detailed representation of local hydrological and technological constraints with regional and global policies, while accounting for the feedbacks between water, energy and agricultural sectors. In this study, ECHO has been applied over Africa as a case study with the aim of demonstrating the benefits of this integrated hydro‐economic modeling framework. Results of this framework are overall consistent with previous findings evaluating the cost of water supply and adaptation to global changes in Africa. Moreover, results provide critical assessments of future investment needs in both supply and demand side water management options, economic implications of contrasting future socio‐economic and climate change scenarios, and the potential tradeoffs among economic and environmental objectives. Overall, this study demonstrates the capacity of ECHO to address challenging research questions examining the sustainability of water supply, and the impacts of water management on energy and food sectors and vice versa. As such, we propose ECHO as useful tool for water‐related scenario analysis and management options evaluation.

Global assessment of water challenges under uncertainty in water scarcity projections

Water scarcity, a critical environmental issue worldwide, has primarily been driven by a significant increase in water extractions during the last century. In the coming decades, climate and societal changes are projected to further exacerbate water scarcity in many regions worldwide. Today, a major issue for the ongoing policy debate is to identify interventions able to address water scarcity challenges in the presence of large uncertainties. Here, we take a probabilistic approach to assess global water scarcity projections following feasible combinations of shared socioeconomic pathways and representative concentration pathways for the first half of the twenty-first century. We identify—alongside trends in median water scarcity—changes in the uncertainty range of anticipated water scarcity conditions. Our results show that median water scarcity and the associated range of uncertainty are generally increasing worldwide, including many major river basins. On the basis of these results, we develop a general decision-making framework to enhance policymaking by identifying four representative clusters of specific water policy challenges and needs.Designing interventions to address water scarcity under climate change is challenging given the large uncertainties in projected water availability. In this study, changes in the uncertainty range of anticipated water scarcity conditions are identified, and a general decision-making framework to support policy decisions is developed.