Scientific Results

This catalogue is obtained by conducting a systematic literature review of scientific studies and reviews related to monitoring, forecasting, and simulating the inland water cycle. The analysis maps scientific expertise across research groups and classifies findings by the type of inland water studied, application focus, and geographical scope. A gap analysis will identify missing research areas and assess their relevance to policymaking.

ID â–Č Type Year Authors Title Venue/Journal DOI Research type Water System Technical Focus Abstract Link with Projects Link with Tools Related policies ID
publications-2641 Peer reviewed articles 2018 Klemen Kenda, Matej Čerin, Mark Bogataj, Matej SenoĆŸetnik, Kristina Klemen, Petra Pergar, Chrysi Laspidou, Dunja Mladenić Groundwater Modeling with Machine Learning Techniques: Ljubljana polje Aquifer Proceedings 10.3390/proceedings2110697 Uncategorized Uncategorized No abstract available 734409
publications-2642 Peer reviewed articles 2018 Stamatia Rizou, Klemen Kenda, Dimitris Kofinas, Nikos Mellios, Petra Pergar, Panagiotis D. Ritsos, John Vardakas, Kostas Kalaboukas, Chrysi Laspidou, Matej SenoĆŸetnik, Alexandra Spyropoulou Water4Cities: An ICT Platform Enabling Holistic Surface Water and Groundwater Management for Sustainable Cities Proceedings 10.3390/proceedings2110695 Simulation & Modeling Natural Water Bodies No abstract available 734409
publications-2643 Peer reviewed articles 2018 Klemen Kenda, Dunja Mladenić Autonomous Sensor Data Cleaning in Stream Mining Setting Business Systems Research Journal 10.2478/bsrj-2018-0020 Simulation & Modeling Natural Water Bodies Abstract Background: Internet of Things (IoT), earth observation and big scientific experiments are sources of extensive amounts of sensor big data today. We are faced with large amounts of data with low measurement costs. A standard approach in such cases is a stream mining approach, implying that we look at a particular measurement only once during the real-time processing. This requires the methods to be completely autonomous. In the past, very little attention was given to the most time-consuming part of the data mining process, i.e. data pre-processing. Objectives: In this paper we propose an algorithm for data cleaning, which can be applied to real-world streaming big data. Methods/Approach: We use the short-term prediction method based on the Kalman filter to detect admissible intervals for future measurements. The model can be adapted to the concept drift and is useful for detecting random additive outliers in a sensor data stream. Results: For datasets with low noise, our method has proven to perform better than the method currently commonly used in batch processing scenarios. Our results on higher noise datasets are comparable. Conclusions: We have demonstrated a successful application of the proposed method in real-world scenarios including the groundwater level, server load and smart-grid data 734409
publications-2644 Peer reviewed articles 2019 David GarcĂ­a-LeĂłn, Sergio Contreras, Johannes Hunink Comparison of meteorological and satellite-based drought indices as yield predictors of Spanish cereals Agricultural Water Management 10.1016/j.agwat.2018.10.030 Uncategorized Natural Water Bodies No abstract available 705408
publications-2645 Peer reviewed articles 2019 Dennis Becker, Christina Jungfer, Thomas Track Integrated Industrial Water Management – Challenges, Solutions, and Future Priorities Chemie Ingenieur Technik 10.1002/cite.201900086 Uncategorized Uncategorized AbstractWater is used intensively by various sectors such as agriculture, industry, and the public. Increasing global water demand and the effects of climate change are leading to overuse of water resources in many regions. One strategy to meet these challenges is to implement an integrated industrial water management, e.g., by water reuse or the use of alternative water resources. The development of new concepts and technical, digital, and nontechnical innovations together with priorities will continue to set the course for future integrated water management, particularly in the industrial environment. 723702
publications-2646 Peer reviewed articles 2018 J. Kochan, M. Pastur Romey, J. Palacin, L. Barbera Campos, C. Niewersch, J. Koppe, C. Patrut, L. van Dijk, C. Kazner, F. Zorn The best wastewater is wastewater that barely exists Chemie Ingenieur Technik 10.1002/cite.201855126 Uncategorized Uncategorized No abstract available 723702
publications-2647 Peer reviewed articles 2017 Ivån Rivilla, Abel de Cózar, Thomas SchÀfer, Frank J. Hernandez, Alexander M. Bittner, Aitziber Eleta-Lopez, Ali Aboudzadeh, José I. Santos, José I. Miranda, Fernando P. Cossío Catalysis of a 1,3-dipolar reaction by distorted DNA incorporating a heterobimetallic platinum( ii ) and copper( ii ) complex Chemical Science 10.1039/c7sc02311a Simulation & Modeling Wastewater Treatment Plants A novel catalytic system based on covalently modified DNA is described. 713641
publications-2648 Peer reviewed articles 2016 Joseph M. Shea, Walter W. Immerzeel An assessment of basin-scale glaciological and hydrological sensitivities in the Hindu Kush–Himalaya Annals of Glaciology 10.3189/2016AoG71A073 Simulation & Modeling Water Distribution Networks Abstract.Glacier responses to future climate change will affect hydrology at sub-basin scales. The main goal of this study is to assess glaciological and hydrological sensitivities of sub-basins throughout the Hindu Kush-Himalaya region. We use a simple geometrical analysis based on a full glacier inventory and digital elevation model to estimate sub-basin equilibrium-line altitudes (ELAs) from assumptions of steady-state accumulation area ratios. The ELA response to an increase in temperature is expressed as a function of mean annual precipitation, derived from a range of high-altitude studies. Changes in glacier contributions to streamflow in response to increased temperatures are examined for scenarios of both static and adjusted glacier geometries. On average, glacier contributions to streamflow increase by ~50% for a +1 K warming based on a static geometry. Large decreases (-60% on average) occur in all basins when glacier geometries are instantaneously adjusted to reflect the new ELA. Finally, we provide estimates of sub-basin glacier response times that suggest a majority of basins will experience declining glacier contributions by 2100. 676819
publications-2649 Peer reviewed articles 2016 Philip Kraaijenbrink, Sander W. Meijer, Joseph M. Shea, Francesca Pellicciotti, Steven M. De Jong, Walter W. Immerzeel Seasonal surface velocities of a Himalayan glacier derived by automated correlation of unmanned aerial vehicle imagery Annals of Glaciology 10.3189/2016AoG71A072 AI & Machine Learning Water Distribution Networks Abstract.Debris-covered glaciers play an important role in the high-altitude water cycle in the Himalaya, yet their dynamics are poorly understood, partly because of the difficult fieldwork conditions. In this study we therefore deploy an unmanned aerial vehicle (UAV) three times (May 2013, October 2013 and May 2014) over the debris-covered Lirung Glacier in Nepal. The acquired data are processed into orthomosaics and elevation models by a Structure from Motion workflow, and seasonal surface velocity is derived using frequency cross-correlation. In order to obtain optimal surface velocity products, the effects of different input data and correlator configurations are evaluated, which reveals that the orthomosaic as input paired with moderate correlator settings provides the best results. The glacier has considerable spatial and seasonal differences in surface velocity, with maximum summer and winter velocities 6 and 2.5 m a-1, respectively, in the upper part of the tongue, while the lower part is nearly stagnant. It is hypothesized that the higher velocities during summer are caused by basal sliding due to increased lubrication of the bed. We conclude that UAVs have great potential to quantify seasonal and annual variations in flow and can help to further our understanding of debris-covered glaciers. 676819
publications-2650 Peer reviewed articles 2017 A. Orr, C. Listowski, M. Couttet, E. Collier, W. Immerzeel, P. Deb, D. Bannister Sensitivity of simulated summer monsoonal precipitation in Langtang Valley, Himalaya, to cloud microphysics schemes in WRF Journal of Geophysical Research: Atmospheres 10.1002/2016JD025801 Data Management & Analytics Water Distribution Networks AbstractA better understanding of regional‐scale precipitation patterns in the Himalayan region is required to increase our knowledge of the impacts of climate change on downstream water availability. This study examines the impact of four cloud microphysical schemes (Thompson, Morrison, Weather Research and Forecasting (WRF) single‐moment 5‐class, and WRF double‐moment 6‐class) on summer monsoon precipitation in the Langtang Valley in the central Nepalese Himalayas, as simulated by the WRF model at 1 km grid spacing for a 10 day period in July 2012. The model results are evaluated through a comparison with surface precipitation and radiation measurements made at two observation sites. Additional understanding is gained from a detailed examination of the microphysical characteristics simulated by each scheme, which are compared with measurements using a spaceborne radar/lidar cloud product. Also examined are the roles of large‐ and small‐scale forcings. In general, the schemes are able to capture the timing of surface precipitation better than the actual amounts in the Langtang Valley, which are predominately underestimated, with the Morrison scheme showing the best agreement with the measured values. The schemes all show a large positive bias in incoming radiation. Analysis of the radar/lidar cloud product and hydrometeors from each of the schemes suggests that “cold‐rain” processes are a key precipitation formation mechanism, which is also well represented by the Morrison scheme. As well as microphysical structure, both large‐scale and localized forcings are also important for determining surface precipitation. 676819