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-1781 Peer reviewed articles 2022 Miles ES, Steiner JF, Buri P, Immerzeel WW, Pellicciotti F Controls on the relative melt rates of debris-covered glacier surfaces Environmental Research Letters 10.1088/1748-9326/ac6966 Uncategorized Irrigation Systems Abstract Supraglacial debris covers 7% of mountain glacier area globally and generally reduces glacier surface melt. Enhanced energy absorption at ice cliffs and supraglacial ponds scattered across the debris surface leads these features to contribute disproportionately to glacier-wide ablation. However, the degree to which cliffs and ponds actually increase melt rates remains unclear, as these features have only been studied in a detailed manner for selected locations, almost exclusively in High Mountain Asia. In this study we model the surface energy balance for debris-covered ice, ice cliffs, and supraglacial ponds with a set of automatic weather station records representing the global prevalence of debris-covered glacier ice. We generate 5000 random sets of values for physical parameters using probability distributions derived from literature, which we use to investigate relative melt rates and to isolate the melt responses of debris, cliffs and ponds to the site-specific meteorological forcing. Modelled sub-debris melt rates are primarily controlled by debris thickness and thermal conductivity. At a reference thickness of 0.1 m, sub-debris melt rates vary considerably, differing by up to a factor of four between sites, mainly attributable to air temperature differences. We find that melt rates for ice cliffs are consistently 2–3× the melt rate for clean glacier ice, but this melt enhancement decays with increasing clean ice melt rates. Energy absorption at supraglacial ponds is dominated by latent heat exchange and is therefore highly sensitive to wind speed and relative humidity, but is generally less than for clean ice. Our results provide reference melt enhancement factors for melt modelling of debris-covered glacier sites, globally, while highlighting the need for direct measurement of debris-covered glacier surface characteristics, physical parameters, and local meteorological conditions at a variety of sites around the world. 772751
publications-1782 Peer reviewed articles 2018 Evan S. Miles, Ian Willis, Pascal Buri, Jakob F. Steiner, Neil S. Arnold, Francesca Pellicciotti Surface Pond Energy Absorption Across Four Himalayan Glaciers Accounts for 1/8 of Total Catchment Ice Loss Geophysical Research Letters 10.1029/2018gl079678 Uncategorized Precipitation & Ecological Systems AbstractGlaciers in High Mountain Asia, many of which exhibit surface debris, contain the largest volume of ice outside of the polar regions. Many contain supraglacial pond networks that enhance melt rates locally, but no large‐scale assessment of their impact on melt rates exists. Here we use surface energy balance modeling forced using locally measured meteorological data and monthly satellite‐derived pond distributions to estimate the total melt enhancement for the four main glaciers within the 400‐km2 Langtang catchment, Nepal, for a 6‐month period in 2014. Ponds account for 0.20 ± 0.03 m/year of surface melt, representing a local melt enhancement of a factor of 14 ± 3 compared with the debris‐covered area, and equivalent to 12.5 ± 2.0% of total catchment ice loss. Given the prevalence of supraglacial ponds across the region, our results suggest that effective incorporation of melt enhancement by ponds is essential for accurate predictions of future mass balance change in the region. 772751
publications-1783 Peer reviewed articles 2023 Pascal Buri; Simone Fatichi; Thomas E. Shaw; Evan S. Miles; Michael J. McCarthy; Catriona L. Fyffe; Stefan Fugger; Shaoting Ren; Marin Kneib; Achille Jouberton; Jakob Steiner; Koji Fujita; Francesca Pellicciotti Land Surface Modeling in the Himalayas: On the Importance of Evaporative Fluxes for the Water Balance of a High‐Elevation Catchment Water Resources Research 10.1029/2022wr033841 Simulation & Modeling Irrigation Systems AbstractHigh Mountain Asia (HMA) is among the most vulnerable water towers globally and yet future projections of water availability in and from its high‐mountain catchments remain uncertain, as their hydrologic response to ongoing environmental changes is complex. Mechanistic modeling approaches incorporating cryospheric, hydrological, and vegetation processes in high spatial, temporal, and physical detail have never been applied for high‐elevation catchments of HMA. We use a land surface model at high spatial and temporal resolution (100 m and hourly) to simulate the coupled dynamics of energy, water, and vegetation for the 350 km2 Langtang catchment (Nepal). We compare our model outputs for one hydrological year against a large set of observations to gain insight into the partitioning of the water balance at the subseasonal scale and across elevation bands. During the simulated hydrological year, we find that evapotranspiration is a key component of the total water balance, as it causes about the equivalent of 20% of all the available precipitation or 154% of the water production from glacier melt in the basin to return directly to the atmosphere. The depletion of the cryospheric water budget is dominated by snow melt, but at high elevations is primarily dictated by snow and ice sublimation. Snow sublimation is the dominant vapor flux (49%) at the catchment scale, accounting for the equivalent of 11% of snowfall, 17% of snowmelt, and 75% of ice melt, respectively. We conclude that simulations should consider sublimation and other evaporative fluxes explicitly, as otherwise water balance estimates can be ill‐quantified. 772751
publications-1784 Peer reviewed articles 2021 Compagno L; Huss M; Miles ES; McCarthy MJ; Zekollari H; Dehecq A; Pellicciotti F; Farinotti D Modelling supraglacial debris-cover evolution from the single-glacier to the regional scale: an application to High Mountain Asia The Cryosphere 10.5194/tc-16-1697-2022 Data Management & Analytics Precipitation & Ecological Systems Abstract. Currently, about 12 %–13 % of High Mountain Asia’s glacier area is debris-covered, which alters its surface mass balance. However, in regional-scale modelling approaches, debris-covered glaciers are typically treated as clean-ice glaciers, leading to a bias when modelling their future evolution. Here, we present a new approach for modelling debris area and thickness evolution, applicable from single glaciers to the global scale. We derive a parameterization and implement it as a module into the Global Glacier Evolution Model (GloGEMflow), a combined mass-balance ice-flow model. The module is initialized with both glacier-specific observations of the debris' spatial distribution and estimates of debris thickness. These data sets account for the fact that debris can either enhance or reduce surface melt depending on thickness. Our model approach also enables representing the spatiotemporal evolution of debris extent and thickness. We calibrate and evaluate the module on a selected subset of glaciers and apply GloGEMflow using different climate scenarios to project the future evolution of all glaciers in High Mountain Asia until 2100. Explicitly accounting for debris cover has only a minor effect on the projected mass loss, which is in line with previous projections. Despite this small effect, we argue that the improved process representation is of added value when aiming at capturing intra-glacier scales, i.e. spatial mass-balance distribution. Depending on the climate scenario, the mean debris-cover fraction is expected to increase, while mean debris thickness is projected to show only minor changes, although large local thickening is expected. To isolate the influence of explicitly accounting for supraglacial debris cover, we re-compute glacier evolution without the debris-cover module. We show that glacier geometry, area, volume, and flow velocity evolve differently, especially at the level of individual glaciers. This highlights the importance of accounting for debris cover and its spatiotemporal evolution when projecting future glacier changes. 772751
publications-1785 Peer reviewed articles 2022 Wang, H., Wang, R., Harrison, S.P., Prentice, I.C. Leaf morphological traits as adaptations to multiple climate gradients. Journal of ecology 10.1111/1365-2745.13873 Predictive Analytics River Basins Abstract Leaf morphological traits vary systematically along climatic gradients. However, recent studies in plant functional ecology have mainly analysed quantitative traits, while numerical models of species distributions and vegetation function have focused on traits associated with resource acquisition; both ignore the wider functional significance of leaf morphology. A dataset comprising 22 leaf morphological traits for 662 woody species from 92 sites, representing all biomes present in China, was subjected to multivariate analysis in order to identify leading dimensions of trait covariation (correspondence analysis), quantify climatic and phylogenetic contributions (canonical correspondence analysis with variation partitioning) and characterise co‐occurring trait syndromes (k‐means clustering) and their climatic preferences. Three axes accounted for >20% of trait variation in both evergreen and deciduous species. Moisture index, precipitation seasonality and growing‐season temperature explained 8%–10% of trait variation; family 15%–32%. Microphyll or larger, mid‐ to dark green leaves with drip tips in wetter climates contrasted with nanophyll or smaller glaucous leaves without drip tips in drier climates. Thick, entire leaves in less seasonal climates contrasted with thin, marginal dissected, aromatic and involute/revolute leaves in more seasonal climates. Thick, involute, hairy leaves in colder climates contrasted with thin leaves with marked surface structures (surface patterning) in warmer climates. Distinctive trait clusters were linked to the driest and most seasonal climates, for example the clustering of picophyll, fleshy and succulent leaves in the driest climates and leptophyll, linear, dissected, revolute or involute and aromatic leaves in regions with highly seasonal rainfall. Several trait clusters co‐occurred in wetter climates, including clusters characterised by microphyll, moderately thick, patent and entire leaves or notophyll, waxy, dark green leaves. Synthesis. The plastic response of size, shape, colour and other leaf morphological traits to climate is muted, thus their apparent shift along climate gradients reflects plant adaptations to environment at a community level as determined by species replacement. Information on leaf morphological traits, widely available in floras, could be used to strengthen predictive models of species distribution and vegetation function. 787203
publications-1786 Peer reviewed articles 2024 Nie, L.M., Bjerkholt, J.T., Pedersen, P.M., Sivertsen, E., Zhang, K.F., Zhang, W., Silva, C., M. International experience on rainwater harvesting and stormwater utilisation – a literature review. VANN Simulation & Modeling Wastewater Treatment Plants No abstract available 958491
publications-1787 Peer reviewed articles 2020 Benjamin D. Stocker, Han Wang, Nicholas G. Smith, Sandy P. Harrison, Trevor F. Keenan, David Sandoval, Tyler Davis, I. Colin Prentice P-model v1.0: an optimality-based light use efficiency model for simulating ecosystem gross primary production Geoscientific Model Development 10.5194/gmd-13-1545-2020 Uncategorized Uncategorized Abstract. Terrestrial photosynthesis is the basis for vegetation growth and drives the land carbon cycle. Accurately simulating gross primary production (GPP, ecosystem-level apparent photosynthesis) is key for satellite monitoring and Earth system model predictions under climate change. While robust models exist for describing leaf-level photosynthesis, predictions diverge due to uncertain photosynthetic traits and parameters which vary on multiple spatial and temporal scales. Here, we describe and evaluate a GPP (photosynthesis per unit ground area) model, the P-model, that combines the Farquhar–von Caemmerer–Berry model for C3 photosynthesis with an optimality principle for the carbon assimilation–transpiration trade-off, and predicts a multi-day average light use efficiency (LUE) for any climate and C3 vegetation type. The model builds on the theory developed in Prentice et al. (2014) and Wang et al. (2017a) and is extended to include low temperature effects on the intrinsic quantum yield and an empirical soil moisture stress factor. The model is forced with site-level data of the fraction of absorbed photosynthetically active radiation (fAPAR) and meteorological data and is evaluated against GPP estimates from a globally distributed network of ecosystem flux measurements. Although the P-model requires relatively few inputs, the R2 for predicted versus observed GPP based on the full model setup is 0.75 (8 d mean, 126 sites) – similar to comparable satellite-data-driven GPP models but without predefined vegetation-type-specific parameters. The R2 is reduced to 0.70 when not accounting for the reduction in quantum yield at low temperatures and effects of low soil moisture on LUE. The R2 for the P-model-predicted LUE is 0.32 (means by site) and 0.48 (means by vegetation type). Applying this model for global-scale simulations yields a total global GPP of 106–122 Pg C yr−1 (mean of 2001–2011), depending on the fAPAR forcing data. The P-model provides a simple but powerful method for predicting – rather than prescribing – light use efficiency and simulating terrestrial photosynthesis across a wide range of conditions. The model is available as an R package (rpmodel). 787203
publications-1788 Peer reviewed articles 2023 Shen, T., Wang, H., Prentice, I.C., Yang, K., Nobrega, R.L.B., Liu, X., Wang, Y., Yang, Y. Towards a universal evapotranspiration model based on optimality principles Agricultural and forest meteorology 10.1016/j.agrformet.2023.109478 Uncategorized Uncategorized No abstract available 787203
publications-1789 Peer reviewed articles 2020 Yunke Peng, Keith J. Bloomfield, Iain Colin Prentice A theory of plant function helps to explain leaf‐trait and productivity responses to elevation New Phytologist 10.1111/nph.16447 Uncategorized Uncategorized Summary Several publications have examined leaf‐trait and carbon‐cycling shifts along an Amazon–Andes transect spanning 3.5 km in elevation and 16°C in mean annual temperature. Photosynthetic capacity was previously shown to increase as temperature declines with increasing elevation, counteracting enzyme‐kinetic effects. Primary production declines, nonetheless, due to decreasing light availability. We aimed to predict leaf‐trait and production gradients from first principles, using published data to test an emerging theory whereby photosynthetic traits and primary production depend on optimal acclimation and/or adaptation to environment. We re‐analysed published data for 210 species at 25 sites, fitting linear relationships to elevation for both predicted and observed photosynthetic traits and primary production. Declining leaf‐internal/ambient CO2 ratio (χ) and increasing carboxylation (Vcmax) and electron‐transport (Jmax) capacities with increasing elevation were predicted. Increases in leaf nitrogen content with elevation were explained by increasing Vcmax and leaf mass‐per‐area. Leaf and soil phosphorus covaried, but after controlling for elevation, no nutrient metric accounted for any additional variance in photosynthetic traits. Primary production was predicted to decline with elevation. This analysis unifies leaf and ecosystem observations in a common theoretical framework. The insensitivity of primary production to temperature is shown to emerge as a consequence of the optimisation of photosynthetic traits. 787203
publications-1790 Peer reviewed articles 2022 Eusun Han, John A. Kirkegaard, Rosemary White, Abraham George Smith, Kristian Thorup-Kristensen, Timo Kautz, Miriam Athmann Deep learning with multisite data reveals the lasting effects of soil type, tillage and vegetation history on biopore genesis Geoderma 10.1016/j.geoderma.2022.116072 Uncategorized Wastewater Treatment Plants No abstract available 884364