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 ▲ Type Year Authors Title Venue/Journal DOI Research type Water System Technical Focus Abstract Link with Projects Link with Tools Related policies ID
publications-2671 Peer reviewed articles 2018 Remco J. de Kok, Obbe A. Tuinenburg, Pleun N. J. Bonekamp, Walter W. Immerzeel Irrigation as a Potential Driver for Anomalous Glacier Behavior in High Mountain Asia Geophysical Research Letters 10.1002/2017GL076158 AI & Machine Learning Groundwater AbstractMany glaciers in the northwest of High Mountain Asia (HMA) show an almost zero or positive mass balance, despite the global trend of melting glaciers. This phenomenon is often referred to as the “Karakoram anomaly,” although strongest positive mass balances can be found in the Kunlun Shan mountain range, northeast of the Karakoram. Using a regional climate model, in combination with a moisture‐tracking model, we show that the increase in irrigation intensity in the lowlands surrounding HMA, particularly in the Tarim basin, can locally counter the effects of global warming on glaciers in Kunlun Shan, and parts of Pamir and northern Tibet, through an increase in summer snowfall and decrease in net radiance. Irrigation can thus affect the regional climate in a way that favors glacier growth, and future projections of glacier melt, which may impact millions of inhabitants surrounding HMA, will need to take into account predicted changes in irrigation intensity. 676819
publications-2672 Peer reviewed articles 2017 René R. Wijngaard, Arthur F. Lutz, Santosh Nepal, Sonu Khanal, Saurav Pradhananga, Arun B. Shrestha, Walter W. Immerzeel Future changes in hydro-climatic extremes in the Upper Indus, Ganges, and Brahmaputra River basins PLOS ONE 10.1371/journal.pone.0190224 Cloud Technologies River Basins No abstract available 676819
publications-2673 Peer reviewed articles 2018 Jakob F. Steiner, Philip D. A. Kraaijenbrink, Sergiu G. Jiduc, Walter W. Immerzeel Brief communication: The Khurdopin glacier surge revisited – extreme flow velocities and formation of a dammed lake in 2017 The Cryosphere 10.5194/tc-12-95-2018 Data Management & Analytics Groundwater Abstract. Glacier surges occur regularly in the Karakoram, but the driving mechanisms, their frequency and its relation to a changing climate remain unclear. In this study, we use digital elevation models and Landsat imagery in combination with high-resolution imagery from the Planet satellite constellation to quantify surface elevation changes and flow velocities during a glacier surge of the Khurdopin Glacier in 2017. Results reveal that an accumulation of ice volume above a clearly defined steep section of the glacier tongue since the last surge in 1999 eventually led to a rapid surge in May 2017 peaking with velocities above 5000 m a−1, which were among the fastest rates globally for a mountain glacier. Our data reveal that velocities on the lower tongue increase steadily during a 4-year build-up phase prior to the actual surge only to then rapidly peak and decrease again within a few months, which confirms earlier observations with a higher frequency of available velocity data. The surge return period between the reported surges remains relatively constant at ca. 20 years. We show the potential of a combination of repeat Planet and ASTER imagery to (a) capture peak surge velocities that are easily missed by less frequent Landsat imagery, (b) observe surface changes that indicate potential drivers of a surge and (c) monitor hazards associated with a surge. At Khurdopin specifically, we observe that the surging glacier blocks the river in the valley and causes a lake to form, which may grow in subsequent years and could pose threats to downstream settlements and infrastructure in the case of a sudden breach. 676819
publications-2674 Peer reviewed articles 2018 A. Candelieri, R. Perego, F. Archetti Bayesian optimization of pump operations in water distribution systems Journal of Global Optimization 10.1007/s10898-018-0641-2 Predictive Analytics Irrigation Systems No abstract available 690900
publications-2675 Peer reviewed articles 2017 Ali Dinar Abdullah, Ioana Popescu, Ali Dastgheib, Pieter van der Zaag, Ilyas Masih, Usama F. A. Karim Analysis of Possible Actions to Manage the Longitudinal Changes of Water Salinity in a Tidal River Water Resources Management 10.1007/s11269-017-1634-5 Data Management & Analytics Industrial Water Management No abstract available 690900
publications-2676 Peer reviewed articles 2018 Sina Shabani, Antonio Candelieri, Francesco Archetti, Gholamreza Naser Gene Expression Programming Coupled with Unsupervised Learning: A Two-Stage Learning Process in Multi-Scale, Short-Term Water Demand Forecasts Water 10.3390/w10020142 Uncategorized Wastewater Treatment Plants This article proposes a new general approach in short-term water demand forecasting based on a two-stage learning process that couples time-series clustering with gene expression programming (GEP). The approach was tested on the real life water demand data of the city of Milan, in Italy. Moreover, multi-scale modeling using a series of head-time was deployed to investigate the optimum temporal resolution under study. Multi-scale modeling was performed based on rearranging hourly based patterns of water demand into 3, 6, 12, and 24 h lead times. Results showed that GEP should receive more attention among the emerging nonlinear modelling techniques if coupled with unsupervised learning algorithms in detailed spherical k-means. 690900
publications-2677 Peer reviewed articles 2019 Antonio Candelieri; Francesco Archetti Global optimization in machine learning: the design of a predictive analytics application Soft Computing Uncategorized Uncategorized No abstract available 690900
publications-2678 Peer reviewed articles 2017 Marcelo Bernardes Secron, Marcelo Montaño, Marcelo Gomes Miguez, Andreja Jonoski, José Paulo Soares de Azevedo, Ioana Popescu, Paulo Cesar Colonna Rosman Proposal of a hydric index to support industrial site location decision-making applying a fuzzy multi-attribute methodology Ecological Indicators 10.1016/j.ecolind.2017.08.002 Hydrological modeling River Basins No abstract available 690900
publications-2679 Peer reviewed articles 2019 Antonio Candelieri, Ilaria Giordani, Francesco Archetti, Konstantin Barkalov, Iosif Meyerov, Alexey Polovinkin, Alexander Sysoyev, Nikolai Zolotykh Tuning hyperparameters of a SVM-based water demand forecasting system through parallel global optimization Computers & Operations Research 10.1016/j.cor.2018.01.013 Data Management & Analytics Natural Water Bodies No abstract available 690900
publications-2680 Peer reviewed articles 2018 Ali D. Abdullah, Mario Erik Castro-Gama, Ioana Popescu, Pieter van der Zaag, Usama Karim, Qusay Al Suhail Optimization of water allocation in the Shatt al-Arab River under different salinity regimes and tide impact Hydrological Sciences Journal 10.1080/02626667.2018.1446213 Simulation & Modeling Precipitation & Ecological Systems No abstract available 690900