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-1841 Peer reviewed articles 2024 Zheng Fu, Philippe Ciais, Jean-Pierre Wigneron, Pierre Gentine, Andrew F. Feldman, David Makowski, Nicolas Viovy, Armen R. Kemanian, Daniel S. Goll, Paul C. Stoy, Iain Colin Prentice, Dan Yakir, Liyang Liu, Hongliang Ma, Xiaojun Li, Yuanyuan Huang, Kailiang Yu, Peng Zhu, Xing Li, Zaichun Zhu, Jinghui Lian, William K. Smith Global critical soil moisture thresholds of plant water stress Nature Communications 10.1038/s41467-024-49244-7 Simulation & Modeling Natural Water Bodies AbstractDuring extensive periods without rain, known as dry-downs, decreasing soil moisture (SM) induces plant water stress at the point when it limits evapotranspiration, defining a critical SM threshold (θcrit). Better quantification of θcrit is needed for improving future projections of climate and water resources, food production, and ecosystem vulnerability. Here, we combine systematic satellite observations of the diurnal amplitude of land surface temperature (dLST) and SM during dry-downs, corroborated by in-situ data from flux towers, to generate the observation-based global map of θcrit. We find an average global θcrit of 0.19 m3/m3, varying from 0.12 m3/m3 in arid ecosystems to 0.26 m3/m3 in humid ecosystems. θcrit simulated by Earth System Models is overestimated in dry areas and underestimated in wet areas. The global observed pattern of θcrit reflects plant adaptation to soil available water and atmospheric demand. Using explainable machine learning, we show that aridity index, leaf area and soil texture are the most influential drivers. Moreover, we show that the annual fraction of days with water stress, when SM stays below θcrit, has increased in the past four decades. Our results have important implications for understanding the inception of water stress in models and identifying SM tipping points. 787203
publications-1842 Peer reviewed articles 2023 Wang, H., Prentice, I.C., Wright, I.J., Warton, D.I., Qiao, S., Xu, X., Zhou, J., Kikuzawa, K., and Stenseth, N.C. Leaf economics fundamentals explained by optimality principles Science Advances 10.1126/sciadv.add5667 Simulation & Modeling River Basins The life span of leaves increases with their mass per unit area (LMA). It is unclear why. Here, we show that this empirical generalization (the foundation of the worldwide leaf economics spectrum) is a consequence of natural selection, maximizing average net carbon gain over the leaf life cycle. Analyzing two large leaf trait datasets, we show that evergreen and deciduous species with diverse construction costs (assumed proportional to LMA) are selected by light, temperature, and growing-season length in different, but predictable, ways. We quantitatively explain the observed divergent latitudinal trends in evergreen and deciduous LMA and show how local distributions of LMA arise by selection under different environmental conditions acting on the species pool. These results illustrate how optimality principles can underpin a new theory for plant geography and terrestrial carbon dynamics. 787203
publications-1843 Peer reviewed articles 2021 Dongyang Wei, Penélope González-Sampériz, Graciela Gil-Romera, Sandy P. Harrison, I. Colin Prentice Seasonal temperature and moisture changes in interior semi‐arid Spain from the last interglacial to the Late Holocene Quaternary Research 10.1017/qua.2020.108 Simulation & Modeling River Basins Abstract The El Cañizar de Villarquemado pollen record covers the last part of MIS 6 to the Late Holocene. We use Tolerance-Weighted Averaging Partial Least Squares (TWA-PLS) to reconstruct mean temperature of the coldest month (MTCO) and growing degree days above 0°C (GDD0) and the ratio of annual precipitation to annual potential evapotranspiration (MI), accounting for the ecophysiological effect of changing CO2 on water-use efficiency. Rapid summer warming occurred during the Zeifen-Kattegat Oscillation at the transition to MIS 5. Summers were cold during MIS 4 and MIS 2, but some intervals of MIS 3 had summers as warm as the warmest phases of MIS 5 or the Holocene. Winter temperatures declined from MIS 4 to MIS 2. Changes in temperature seasonality within MIS 5 and MIS 1 are consistent with insolation seasonality changes. Conditions became progressively more humid during MIS 5, and MIS 4 was also humid, although MIS 3 was more arid. Changes in MI and GDD0 are anti-correlated, with increased MI during summer warming intervals. Comparison with other records shows glacial-interglacial changes were not unform across the circum-Mediterranean region, but available quantitative reconstructions are insufficient to determine if east-west differences reflect the circulation-driven precipitation dipole seen in recent decades. 787203
publications-1844 Peer reviewed articles 2020 Bonnie Waring, Mathias Neumann, Iain Colin Prentice, Mark Adams, Pete Smith, Martin Siegert Forests and Decarbonization – Roles of Natural and Planted Forests Frontiers in Forests and Global Change 10.3389/ffgc.2020.00058 Simulation & Modeling Natural Water Bodies No abstract available 787203
publications-1845 Peer reviewed articles 2021 Mark G. Turner, Dongyang Wei, Iain Colin Prentice, Sandy P. Harrison The impact of methodological decisions on climate reconstructions using WA-PLS Quaternary Research 10.1017/qua.2020.44 Uncategorized Precipitation & Ecological Systems AbstractMost techniques for pollen-based quantitative climate reconstruction use modern assemblages as a reference data set. We examine the implication of methodological choices in the selection and treatment of the reference data set for climate reconstructions using Weighted Averaging Partial Least Squares (WA-PLS) regression and records of the last glacial period from Europe. We show that the training data set used is important because it determines the climate space sampled. The range and continuity of sampling along the climate gradient is more important than sampling density. Reconstruction uncertainties are generally reduced when more taxa are included, but combining related taxa that are poorly sampled in the data set to a higher taxonomic level provides more stable reconstructions. Excluding taxa that are climatically insensitive, or systematically overrepresented in fossil pollen assemblages because of known biases in pollen production or transport, makes no significant difference to the reconstructions. However, the exclusion of taxa overrepresented because of preservation issues does produce an improvement. These findings are relevant not only for WA-PLS reconstructions but also for similar approaches using modern assemblage reference data. There is no universal solution to these issues, but we propose a number of checks to evaluate the robustness of pollen-based reconstructions. 787203
publications-1846 Peer reviewed articles 2023 Ravindra R. Patil, Mohamad Y. Mustafa, Rajnish Kaur Calay, Saniya M. Ansari S-BIRD: A Novel Critical Multi-Class Imagery Dataset for Sewer Monitoring and Maintenance Systems Sensors 10.3390/s23062966 Data Management & Analytics Groundwater Computer vision in consideration of automated and robotic systems has come up as a steady and robust platform in sewer maintenance and cleaning tasks. The AI revolution has enhanced the ability of computer vision and is being used to detect problems with underground sewer pipes, such as blockages and damages. A large amount of appropriate, validated, and labeled imagery data is always a key requirement for learning AI-based detection models to generate the desired outcomes. In this paper, a new imagery dataset S-BIRD (Sewer-Blockages Imagery Recognition Dataset) is presented to draw attention to the predominant sewers’ blockages issue caused by grease, plastic and tree roots. The need for the S-BIRD dataset and various parameters such as its strength, performance, consistency and feasibility have been considered and analyzed for real-time detection tasks. The YOLOX object detection model has been trained to prove the consistency and viability of the S-BIRD dataset. It also specified how the presented dataset will be used in an embedded vision-based robotic system to detect and remove sewer blockages in real-time. The outcomes of an individual survey conducted at a typical mid-size city in a developing country, Pune, India, give ground for the necessity of the presented work. 821423
publications-1847 Peer reviewed articles 2024 Subhashis Das, Rajnish Kaur Calay Experimental Study of Power Generation and COD Removal Efficiency by Air Cathode Microbial Fuel Cell Using Shewanella baltica 20 Energies 10.3390/en15114152 Simulation & Modeling Precipitation & Ecological Systems Microbial fuel cells (MFCs) are a kind of bioreactor for generating electricity, facilitated by exoelectrogens while treating wastewater. The present article focuses on the performance of an air cathode plexiglass MFC in terms of chemical oxygen demand (COD) removal efficiency and power output by performing two sets of experiments. The proton exchange membrane and electrode materials were Nafion 117 and carbon felts, whereas, for stable biofilm formation on the anode surface, a pure culture of Shewanella baltica 20 was used. Firstly, sterile Luria-Bertani (LB) media containing lactate, ranging from 20 to 100 mM, was continuously fed to an MFC, and a maximum power density of 55 mW/m2 was observed. Similarly, artificial wastewater with COD ranging from 3250 mg/L to 10,272 mg/L was supplied to the MFC in the second set of experiments. In this case, the maximum power density and COD removal efficiency were 12 mW/m2 and 57%, respectively. In both cases, the hydraulic retention time (HRT) was 1.5 h. It was found that electricity generation depends on the characteristics of the wastewater. These initial findings confirm that the design aspects of an MFC, i.e., surface area to volume ratio, and external resistance with respect to the quality of influent need to be optimised to improve the MFC’s performance. 821423
publications-1848 Peer reviewed articles 2022 Eusun Han, Dorte Bodin Dresbøll, Kristian Thorup-Kristensen Tracing deep P uptake potential in arable subsoil using radioactive 33P isotope Plant and Soil 10.1007/s11104-021-05178-3 Uncategorized Uncategorized No abstract available 884364
publications-1849 Peer reviewed articles 2022 Eusun Han, Weronika Czaban, Dorte Bodin Dresbøll, Kristian Thorup-Kristensen Exploitation of neighbouring subsoil for nutrient acquisition under annual-perennial strip intercropping systems Agriculture, Ecosystems & Environment 10.1016/j.agee.2022.108106 Simulation & Modeling Irrigation Systems No abstract available 884364
publications-1850 Peer reviewed articles 2023 P. Mohan Doss; M.M. Rokstad; D. Steffelbauer; F. Tscheikner-Gratl Uncertainties in different leak localization methods for water distribution networks: a review Urban Water Journal 10.1080/1573062x.2023.2229301 Uncategorized Uncategorized No abstract available 869171