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  • 1
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    PANGAEA
    In:  Supplement to: Zamrsky, Daniel; Oude Essink, Gualbert H P; Bierkens, Marc F P (2018): Estimating the thickness of unconsolidated coastal aquifers along the global coastline. Earth System Science Data, 10(3), 1591-1603, https://doi.org/10.5194/essd-10-1591-2018
    Publication Date: 2023-01-13
    Description: Information on aquifer thickness is one of the crucial inputs to numerical groundwater flow models, especially in the coastal areas that are threatened by increasing salt water intrusion leading to declining fresh groundwater resources. Since aquifer thickness data is missing in many parts of the world we designed a methodology to estimate it on global scale using state of the art datasets. We estimated the aquifer thickness by combining global topographical (Weatherhall et al., 2015, doi:10.1002/2015EA000107), lithological (Hartmann et. al, 2012, doi:10.1029/2012GC004370), soil thickness (Pelletier et al., 2016, doi:10.1002/2015MS000526) and sediment thickness from the global PCR-GLOBWB model (de Graaf et. al, 2015, doi:10.5194/hess-19-823-2015) to find the position and slope of the bedrock formation that are overlaid by unconsolidated sediments forming the aquifer system. The dataset includes the estimates of aquifer thickness at the coastline for each cross-section together with corresponding "anchor points" (last point with known thickness from Pelletier et. al, 2016). With this information it is possible to create 2D cross-sectional groundwater flow coupled with salt transport models to estimate the fresh groundwater resources in coastal areas. More attention should be paid to the composition of unconsolidated sediment aquifers in terms of low permeable layers that can play a large role in the distribution of fresh and saline groundwater.
    Type: Dataset
    Format: application/zip, 3.2 MBytes
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  • 2
    Publication Date: 2023-01-13
    Description: This dataset provides a consistent and comprehensive outlook of global wastewater production, collection, treatment and re-use at both the country-level and 5 arc-min resolution (gridded) for the year 2015. Country-level estimates of wastewater reported from various sources are used as basis, supplemented with predictions based on multiple linear regression using social, economic, hydrological and geographical predictor variables. Country-level wastewater data are provided in both volume flow rate (million m3 yr-1) and percentage terms. Wastewater data is downscaled to gridded (5 arc-min; m3 yr-1) estimates based on simulations of domestic and industrial return flows from the Water Futures and Solutions (WFaS; Wada et al., 2016) using the approach developed for PCRaster GlOBal Water Balance model (PCR-GLOBWB2; Sutanudjaja et al (2018)). Estimates of downscaled wastewater treatment and re-use are validated based on wastewater treatment plant capacities reported in various databases.
    Keywords: Municipal wastewater; PCR-GLOBWB; return flow; wastewater collection; Wastewater production; wastewater re-use; wastewater treatment; WFaS
    Type: Dataset
    Format: application/zip, 3.9 MBytes
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  • 3
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    PANGAEA
    In:  Supplement to: Gruber, Thomas; Bamber, Jonathan L; Bierkens, Marc F P; Dobslaw, Henryk; Murböck, M; Thomas, M; van Beek, L P H; van Dam, T; Vermeersen, L L A; Visser, P N A M (2011): Simulation of the time-variable gravity field by means of coupled geophysical models. Earth System Science Data, 3(1), 19-35, https://doi.org/10.5194/essd-3-19-2011
    Publication Date: 2023-09-02
    Description: Time variable gravity fields, reflecting variations of mass distribution in the system Earth is one of the key parameters to understand the changing Earth. Mass variations are caused either by redistribution of mass in, on or above the Earth's surface or by geophysical processes in the Earth's interior. The first set of observations of monthly variations of the Earth gravity field was provided by the US/German GRACE satellite mission beginning in 2002. This mission is still providing valuable information to the science community. However, as GRACE has outlived its expected lifetime, the geoscience community is currently seeking successor missions in order to maintain the long time series of climate change that was begun by GRACE. Several studies on science requirements and technical feasibility have been conducted in the recent years. These studies required a realistic model of the time variable gravity field in order to perform simulation studies on sensitivity of satellites and their instrumentation. This was the primary reason for the European Space Agency (ESA) to initiate a study on ''Monitoring and Modelling individual Sources of Mass Distribution and Transport in the Earth System by Means of Satellites''. The goal of this interdisciplinary study was to create as realistic as possible simulated time variable gravity fields based on coupled geophysical models, which could be used in the simulation processes in a controlled environment. For this purpose global atmosphere, ocean, continental hydrology and ice models were used. The coupling was performed by using consistent forcing throughout the models and by including water flow between the different domains of the Earth system. In addition gravity field changes due to solid Earth processes like continuous glacial isostatic adjustment (GIA) and a sudden earthquake with co-seismic and post-seismic signals were modelled. All individual model results were combined and converted to gravity field spherical harmonic series, which is the quantity commonly used to describe the Earth's global gravity field. The result of this study is a twelve-year time-series of 6-hourly time variable gravity field spherical harmonics up to degree and order 180 corresponding to a global spatial resolution of 1 degree in latitude and longitude. In this paper, we outline the input data sets and the process of combining these data sets into a coherent model of temporal gravity field changes. The resulting time series was used in some follow-on studies and is available to anybody interested.
    Keywords: DATE/TIME; File name; Method comment; Uniform resource locator/link to file
    Type: Dataset
    Format: text/tab-separated-values, 180 data points
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