Utilizing Indicator Kriging to Identify Suitable Zones for Manual Drilling in Weathered Crystalline Basement Aquifers
Contributors: Philip Deal
... Manual drilling offers a practical and affordable method of increasing access to groundwater supply in regions struggling with economic water scarcity. However, manual techniques are limited to specific hydrogeological contexts and must be sited appropriately. Indicator kriging is proposed as an interpolation method that builds upon previous efforts to identify suitable zones for manual drilling, particularly in weathered crystalline basement aquifers. This approach allows for heterogeneity within weathering profiles and provides probability mapping of success for regional planning. Modeling was conducted in the Upper East Region of Ghana using available borehole-log data, including: transmissivity, static water depth, laterite thickness, depth to hard rock, water quality parameters, and the degree of weathering. Indicator kriging interpolations predicted binary variables with over 90% accuracy. The model predicts that drilling into highly weathered layers will be common, and percussion techniques will be necessary to reach sufficient depths. The results suggest that suitable zones occur near Bolgatanga, Bawku, and Zebila, which coincide with historical drilling efforts in the central and eastern portions of the region. The original dataset was derived from the Hydrogeological Assessment of the Northern Regions of Ghana Project (HAP) implemented by SNC-Lavalin, Institut national de Recherche Scientifique (INRS) and the Water Resources Comission (WRC) of Ghana, and was supported by the Canadian International Development Agency. Hydrogeological data was collected and aggregated for the Voltaian Sedimentary Basin and Precambrian Basement complexes in Ghana from numerous sources. The data was compiled into a GIS databased for further study and analysis of the groundwater resources in Ghana. For this study, the dataset was obtained from the University of Ghana upon request with a focus on manual drilling feasibility. Borehole records were manipulated with various interpolation methods within the Upper East Region in ArcGIS, as described within the journal article.
Contributors: Tetsuji Okada
... DSA files of human (N to Z, by gene name) : UniProt ID is used for a protein to which no gene name is assigned.
Contributors: Tetsuji Okada
... DSA files of human (A to M, by gene name) : UniProt ID is used for a protein to which no gene name is assigned.
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Contributors: Tetsuji Okada
... DSA files of E. coli (A to M, by gene name) UniProt ID is used for a protein to which no gene name is assigned.
Contributors: Juan Gabriel Bayona
... the folder contains input and setup files of the article An Alternative Method to Determine Extreme Hydrodynamic Forces with Data Limitations for Offshore Engineering
Contributors: Phil Symonds
... These data were used to quantify the impacts of air pollution policies on population health and health inequalities within a microsimulation model, MicroEnv . They provide a basis for comparing results from similar models and allow researchers to integrate additional model components.  P. Symonds, E. Hutchinson, A. Ibbetson, J. Taylor, J. Milner, Z. Chalabi, M. Davies, P. Wilkinson, MicroEnv: A microsimulation model for quantifying the impacts of environmental policies on population health and health inequalities, Science of The Total Environment, Volume 697, (2019) 134105, ISSN 0048-9697, https://doi.org/10.1016/j.scitotenv.2019.134105.
Contributors: Tongtong Wang, Yuankun Luo, Zhilin Tao, Weijie Chen, Xin Gu
... The zip file contains project files, screenshots of research results, chart data, experimental data, simulation data, and grid independence verification data.
Contributors: Jacqueline Zadelaar
... Are Individual Differences Quantitative Or Qualitative? An Integrated Behavioral And Fmri Mimic Approach. Authors: Jacqueline N. Zadelaar, Wouter D. Weeda, Lourens J. Waldorp, Anna C. K. Van Duijvenvoordee, N. E. Blankenstein, Hilde M. Huizenga In cognitive neuroscience there is a growing interest in individual differences. We propose the Multiple Indicators Multiple Causes (MIMIC) model of combined behavioral and fMRI data to determine whether such differences are quantitative or qualitative in nature. A simulation study revealed the MIMIC model to have adequate power for this goal, and parameter recovery to be satisfactory. The MIMIC model was illustrated with a re-analysis of Van Duijvenvoorde et al. (2016) and Blankenstein et al. (2018) decision making data. This showed individual differences in Van Duijvenvoorde et al. (2016) to originate in qualitative differences in decision strategies. Parameters indicated some individuals to use an expected value decision strategy, while others used a loss minimizing strategy, distinguished by individual differences in vmPFC activity. Individual differences in Blankenstein et al. (2018) were explained by quantitative differences in risk aversion. Parameters showed that more risk averse individuals preferred safe over risky choices, as predicted by heightened vmPFC activity. We advocate using the MIMIC model to empirically determine, rather than assume, the nature of individual differences in combined behavioral and fMRI datasets.
Contributors: Lukas Graf, Levente Papp
... This dataset provides sample data demonstrating the capacities of the OBIA4RTM tool. OBIA4RTM combines radiative transfer modelling (RTM) of vegetation with object-based image analysis (OBIA). Its main purpose is to provide vegetation parameters such as Leaf Area Index (LAI) or leaf Chlorophyll a+b content (CAB) on a per-object rather than per pixel base. In this dataset, the OBIA4RTM tool was applied to two Sentinel-2 scenes covering an agricultural area in Southern Germany. Field parcels were used as image objects that were delineated from high-resolution ortho-photography and classified into vegetated and non-vegetated parcels using a Support Vector Machine trained on manually selected samples. For each of the two scenes - dating back on the 6th and 18th of July 2017 - the canopy RTM ProSAIL was run in forward mode and the synthetic spectra stored in a Lookup-Table (LUT). For parameter retrieval, the 5 closest matches between spectra in the LUT and a given observed satellite spectrum averaged per parcel were used. Matches were found in terms of the lowest Root Mean Squared Error (RMSE). The utilized vegetation parameterisation is provided additionally. The results include the Leaf Area Index (LAI), the Chlorophyll a+b content (CAB) of leaves and the fraction of brown leaves (Cbrown). In addition, the retrieval error in terms of RMSE is provided together with the average of the 5 best matching synthetic spectra in the LUT to a given object-based spectrum. This allows for evaluating the quality of the inversion results and enables user to further improve the results by applying a more appropiate vegetation parameterisation. The structure of the dataset (see below) is straightforward: - The "Field Parcels" folder contains an ESRI shapefile with the field parcels as well as the classification results for the two image acquisition dates - The "ProSAIL Parametersisation" directory provides the vegetation parameters used to run the ProSAIL model. - The actual results are stored as ESRI-shapefiles in "Retrieved Vegetation Parameters" folder containing the LAI, CAB, Fraction of brown leaves and the RMSE as well as inverted Sentinel-2 spectra - "Sentinel-2 data" contains the utilized Sentinel-2 data as GeoTiff clipped to the study area in Level-2A This information should allow for reproducing the results using the freely available base version of OBIA4RTM (for research and education) or within other software packages. All geodata is projected in UTM-Zone 32N, WGS-84.
Data for: Legacy of a Pleistocene bacterial community: Patterns in community dynamics through changing ecosystems.
Contributors: Senthil Kumar Sadasivam, Anbarasu Kumaresan, Sivakumar Krishnan, Bhavatharini Shanmuganathan, Manoj Kumar Jaiswal, SHAN P THOMAS
... The dataset contains supplementary data files for the manuscript titled "Legacy of a Pleistocene bacterial community: Patterns in community dynamics through changing ecosystems."