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  • 1
    Publication Date: 2023-06-14
    Description: Global Water Models (GWMs), which include Global Hydrological, Land Surface, and Dynamic Global Vegetation Models, present valuable tools for quantifying climate change impacts on hydrological processes in the data scarce high latitudes. Here we performed a systematic model performance evaluation in six major Pan-Arctic watersheds for different hydrological indicators (monthly and seasonal discharge, extremes, trends (or lack of), and snow water equivalent (SWE)) via a novel Aggregated Performance Index (API) that is based on commonly used statistical evaluation metrics. The machine learning Boruta feature selection algorithm was used to evaluate the explanatory power of the API attributes. Our results show that the majority of the nine GWMs included in the study exhibit considerable difficulties in realistically representing Pan-Arctic hydrological processes. Average APIdischarge (monthly and seasonal discharge) over nine GWMs is 〉 50% only in the Kolyma basin (55%), as low as 30% in the Yukon basin and averaged over all watersheds APIdischarge is 43%. WATERGAP2 and MATSIRO present the highest (APIdischarge 〉 55%) while ORCHIDEE and JULES-W1 the lowest (APIdischarge ≤ 25%) performing GWMs over all watersheds. For the high and low flows, average APIextreme is 35% and 26%, respectively, and over six GWMs APISWE is 57%. The Boruta algorithm suggests that using different observation-based climate data sets does not influence the total score of the APIs in all watersheds. Ultimately, only satisfactory to good performing GWMs that effectively represent cold-region hydrological processes (including snow-related processes, permafrost) should be included in multi-model climate change impact assessments in Pan-Arctic watersheds.
    Description: Bundesministerium für Bildung und Forschung http://dx.doi.org/10.13039/501100002347
    Keywords: ddc:551.48 ; Global Water Models ; Model performance ; Model evaluation ; Arctic watersheds ; Boruta feature selection
    Language: English
    Type: doc-type:article
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  • 2
    Publication Date: 2023-06-14
    Description: Importance of evaluation of global hydrological models (gHMs) before doing climate impact assessment was underlined in several studies. The main objective of this study is to evaluate the performance of six gHMs in simulating observed discharge for a set of 57 large catchments applying common metrics with thresholds for the monthly and seasonal dynamics and summarize them estimating an aggregated index of model performance for each model in each basin. One model showed a good performance, and other five showed a weak or poor performance in most of the basins. In 15 catchments, evaluation results of all models were poor. The model evaluation was supplemented by climate impact assessment for a subset of 12 representative catchments using (1) usual ensemble mean approach and (2) weighted mean approach based on model performance, and the outcomes were compared. The comparison of impacts in terms of mean monthly and mean annual discharges using two approaches has shown that in four basins, differences were negligible or small, and in eight catchments, differences in mean monthly, mean annual discharge or both were moderate to large. The spreads were notably decreased in most cases when the second method was applied. It can be concluded that for improving credibility of projections, the model evaluation and application of the weighted mean approach could be recommended, especially if the mean monthly (seasonal) impacts are of interest, whereas the ensemble mean approach could be applied for projecting the mean annual changes. The calibration of gHMs could improve their performance and, consequently, the credibility of projections.
    Description: BMBF
    Description: JSPS KAKENHI
    Description: NSFC
    Keywords: ddc:551.48 ; Climate change ; Global hydrological models ; River discharge projections ; Model evaluation ; Model performance ; Model weighting ; Credibility of projections
    Language: English
    Type: doc-type:article
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  • 3
    Publication Date: 2023-04-14
    Description: Assessing global freshwater resources and human water demand is of value for a number of needs but challenging. The global water use and water availability model WaterGAP is in development since 1996 and serves a range of applications and topics as such as Life Cycle Assessments, a better understanding of terrestrial water storage variations (e.g., jointly with satellite observations), water (over)use and consequently depletion of water resources, as well as model evaluation and model development. In the paper connected to this dataset, the newest model version, WaterGAP 2.2d is described by providing the water balance equations, insights to input data used and typical model applications. The most important and requested model outputs (total water storage variations, streamflow and water use) are evaluated against observation data. Standard model output is described and the reader is guided to the location where those data can be downloaded. Caveats of specific output data and an overview of model applications as well as an outlook of future model development lines are presented as well.
    Keywords: File format; File name; File size; GHM; global Hydrological Modelling; hydrology; Uniform resource locator/link to file
    Type: Dataset
    Format: text/tab-separated-values, 204 data points
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  • 4
    Publication Date: 2023-01-13
    Description: This dataset provides decadal changes in total terrestrial water storage (TWS) across global endorheic basins, as observed by the Gravity Recovery and Climate Experiment (GRACE) satellites from April 2002 to March 2016. GRACE observations applied here are monthly equivalent water thickness (EWT) anomalies in the JPL 3-degree equal-area mason solution (JPL-RL05M version 2). Endorheic basin extents are acquired from the 15-second HydroSHEDS drainage basin dataset, with regional supplement of the Global Drainage Basin Database (GDBD). The global endorheic basins cover a total area of 33.7 million square kilometers, ranging from 52.8º S to 62.0º N and from 122.8º W to 157.6º E. TWS changes are calculated at two enumeration scales: 173 endorheic units and 10 endorheic zones (including Western North America, Dry Andes and Patagonia, Sahara and Arabia, Great Rift Valley and Southern Africa, Australia, Central Eurasia, and four secondary zones in Central Eurasia: the Caspian Sea Basin, the Aral Sea Basin, the Inner Tibetan Plateau, and Other Central Eurasia). At the unit scale, we provide 1) the trend of deseasonalized TWS anomalies from April 2002 to March 2016 and, 2) the trend uncertain (one standard deviation) propagated from the inherent errors in the original mascon data and the residuals of the best-fit linear trend fitting. At the zonal scale, we provide detailed monthly time series of 1) TWS anomalies (both original values and deseasonalized values) and 2) TWS uncertainties propagated from the inherent mason errors and rescaling uncertainties due to signal leakage in fringe mascons. Please see the source paper (Wang et al. 2018) for detailed data references, collections and processing.
    Keywords: File content; File format; File name; File size; Uniform resource locator/link to file
    Type: Dataset
    Format: text/tab-separated-values, 20 data points
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  • 5
    Publication Date: 2024-04-20
    Description: Assessing global freshwater resources and human water demand is of value for a number of needs but challenging. The global water use and water availability model WaterGAP is in development since 1996 and serves a range of applications and topics as such as Life Cycle Assessments, a better understanding of terrestrial water storage variations (e.g., jointly with satellite observations), water (over)use and consequently depletion of water resources, as well as model evaluation and model development. In the paper connected to this dataset (doi:10.5194/gmd-14-1037-2021), the newest model version, WaterGAP 2.2d is described by providing the water balance equations, insights to input data used and typical model applications. The most important and requested model outputs (total water storage variations, streamflow and water use) are evaluated against observation data. Standard model output, driven by the climate input WFD-WFDEI (for the years 1901-2016) is described. Caveats of specific output data and an overview of model applications as well as an outlook of future model development lines are presented as well. Here, the reader can download model output driven by an alternative climate forcing, the so called GSWP3-W5E5 forcing (available for the years 1901-2019). This climate forcing was created in the ISIMIP context (https://www.isimip.org) and is described in https://www.isimip.org/gettingstarted/input-data-bias-adjustment/details/80/ as Combination of W5E5 v2.0 (Cucchi et al., 2020, doi:10.5194/essd-2020-28 and Lange et al., 2021, doi:10.48364/ISIMIP.342217) for 1979-2019 with GSWP3 v1.09 (Kim, 2017, doi:10.20783/DIAS.501) homogenized to W5E5 for 1901-1978. The homogenization reduces discontinuities at the 1978/1979 transition and was done using the ISIMIP3BASD v2.5.0 bias adjustment method (Lange, 2019, doi:10.5194/gmd-12-3055-2019 and Lange, 2021, doi:10.5281/zenodo.4686991).
    Keywords: File content; File format; GHM; global Hydrological Modelling; Global Water Use; hydrology; ISIMIP; Model output, NetCDF format; Model output, NetCDF format (File Size)
    Type: Dataset
    Format: text/tab-separated-values, 150 data points
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  • 6
    Publication Date: 2023-10-24
    Description: Similar to other research fields, new knowledge in the Earth System Sciences is increasingly produced by computational research. However, the reproducibility of this type of research has been shown to be very limited, and its efficiency and quality need to be improved. Reproducibility requires researchers to publish both their research outcome in the form of a paper and their research workflows, software and data so that other researchers can reproduce the findings without any further support still years later. Efficient and high-quality computational research requires skills beyond programming as well as the capacity for software maintenance. Inspired by a best-practice example from the Netherlands, we provide 15 recommendations for universities, research funders and the scientific community who wish to support the development of sustainable high-quality computational research in Germany. They relate to the training and support of researchers by universities and other research organizations and to research funding. Of particular importance are options for establishing institutional support by research software engineers who are employed in permanent positions, funding of research software as research infrastructure as well as approaches for increasing the scientific merit that is achieved by producing sustainable research software and providing reproducible research output.
    Description: Deutsche Forschungsgemeinschaft, Rundgespräch DO 737/22-1
    Description: report
    Language: English
    Type: doc-type:book
    Format: 10
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