| packages |
[{'agreement': 'true', 'alternative_identifier': 'https://doi.org/10.1016/j.ejrh.2020.100736', 'author': None, 'author_email': None, 'citation_title': 'Johnson, KA and Smithers, JC. 2020. Updating the estimation of 1-day probable maximum precipitation in South Africa. Journal of Hydrology: Regional Studies 32 (2020): 1-15. DOI: https://doi.org/10.1016/j.ejrh.2020.100736.', 'creator_user_id': '9454753e-d5a2-4c0a-9a94-c88231bb54de', 'data_classification': 'static', 'data_collection_organization': 'South African Weather Services', 'data_structure_category': 'structured', 'dataset_language': 'English', 'dataset_license_url': '', 'did_author_or_contact_organization_collect_the_data': 'true', 'email': 'johnsonk1@ukzn.ac.za', 'id': '14a12540-ee4d-44e5-985a-4f1737363422', 'isopen': False, 'keywords': 'Probable maximum precipitation, extreme design rainfall estimation', 'license': 'Open (Creative Commons)', 'license_id': None, 'license_title': None, 'maintainer': None, 'maintainer_email': None, 'metadata_created': '2023-06-13T08:11:02.860695', 'metadata_modified': '2024-09-20T15:13:40.878322', 'name': 'updating-the-estimation-of-1-day-probable-maximum-precipitation-in-south-africa', 'notes': 'Updating the estimation of 1-day probable maximum precipitation in South Africa', 'num_resources': 4, 'num_tags': 0, 'organization': {'id': '8c449720-ff4d-47d5-be20-0984fb24d89f', 'name': 'http-www-nfsp-co-za', 'title': 'National Flood Studies Programme', 'type': 'organization', 'description': 'The South African National Committee on Large Dams (SANCOLD) in conjunction with the WRC, identified the urgent need to update the data and methods used for design flood estimation in South Africa and have initiated a National Flood Studies Programme (NFSP) to undertake and oversee the new developments. This programme is a collaboration between the Department of Water and Sanitation, the Water Research Commission, SANCOLD , the University of KwaZulu-Natal, the Central University of Technology and Stellenbosch University.\r\n', 'image_url': '2022-10-18-060500.30371420221018NFSPlogo.JPG', 'created': '2022-10-18T06:05:00.324895', 'is_organization': True, 'approval_status': 'approved', 'state': 'active'}, 'owner_org': '8c449720-ff4d-47d5-be20-0984fb24d89f', 'private': False, 'publication_date': '2020-10-31', 'publisher': 'UKZN', 'state': 'active', 'title': 'Updating the estimation of 1-day probable maximum precipitation in South Africa', 'type': 'metadata-form', 'uploader_estimation_of_extent_of_processing': 'refined', 'url': None, 'version': None, 'vertical_extent_datum': '', 'wrc_project_number': 'WRC 2022/2023-00773', 'wro_theme': 'hydrological_data_and_modelling', 'authors': [{'author_department': 'Civil Engineering', 'author_email': 'johnsonk1@ukzn.ac.za', 'author_name': 'Katelyn', 'author_organization': 'UKZN', 'author_surname': 'Johnson', 'contact_same_as_author': 'true'}, {'author_department': 'Bioresources Engineering & CWRR', 'author_email': 'smithers@ukzn.ac.za', 'author_name': 'Jeff', 'author_organization': 'UKZN', 'author_surname': 'Smithers'}], 'contact_person': [{'contact_department': '', 'contact_email': '', 'contact_name': '', 'contact_orgnization': ''}], 'data_reference_date': [{'data_reference_date_from': '', 'data_reference_date_to': ''}], 'extras': [{'key': 'cloud_path', 'value': 'Hydrological_Data_And_Modelling/Structured/Refined/Static'}], 'minimum_maximum_extent': [{'maximum_vertical_extent': '', 'minimum_vertical_extent': ''}], 'resources': [{'cache_last_updated': None, 'cache_url': None, 'created': '2023-06-13T08:13:30.010550', 'dataset_description': '', 'datastore_active': False, 'description': None, 'file_to_bigquery_table': 'False', 'format': 'pdf', 'hash': '', 'id': '4fde127d-5e8c-49a9-b1ad-5b8f971f7138', 'is_bigquery_table': False, 'is_data_supplementary': 'False', 'last_modified': None, 'metadata_modified': '2023-06-13T08:13:30.980599', 'mimetype': None, 'mimetype_inner': None, 'name': 'Johnson and Smithers 2020.pdf', 'package_id': '14a12540-ee4d-44e5-985a-4f1737363422', 'position': 0, 'resource_name': 'Updating the estimation of 1-day probable maximum precipitation in South Africa', 'resource_type': None, 'size': None, 'state': 'active', 'url': 'https://storage.cloud.google.com/wrc_wro_datasets/hydrological_data_and_modelling/structured/access/static/updating-the-estimation-of-1-day-probable-maximum-precipitation-in-south-africa/Johnson_and_Smithers_2020-7138.pdf', 'url_type': 'link', 'zipped_file': 'False'}, {'cache_last_updated': None, 'cache_url': None, 'created': '2023-06-13T08:15:34.691820', 'dataset_description': '', 'datastore_active': False, 'description': None, 'file_to_bigquery_table': 'False', 'format': 'pdf', 'hash': '', 'id': '18cf30a2-3d6d-4e1e-95be-3b34a9696fbc', 'is_bigquery_table': False, 'is_data_supplementary': 'False', 'last_modified': None, 'metadata_modified': '2023-06-13T08:15:35.547249', 'mimetype': None, 'mimetype_inner': None, 'name': 'WRC Project C2022_2023_00773 Booklet_May 2023.pdf', 'package_id': '14a12540-ee4d-44e5-985a-4f1737363422', 'position': 1, 'resource_name': 'WRC Project C2022_2023_00773 Booklet_May 2023', 'resource_type': None, 'size': None, 'state': 'active', 'url': 'https://storage.cloud.google.com/wrc_wro_datasets/hydrological_data_and_modelling/structured/access/static/updating-the-estimation-of-1-day-probable-maximum-precipitation-in-south-africa/WRC_Project_C2022_2023_00773_Booklet_May_2023-6fbc.pdf', 'url_type': 'link', 'zipped_file': 'False'}, {'cache_last_updated': None, 'cache_url': None, 'created': '2023-06-13T08:17:00.986437', 'dataset_description': '', 'datastore_active': False, 'description': None, 'file_to_bigquery_table': 'False', 'format': 'pdf', 'hash': '', 'id': '0396cfa5-a80f-42cf-9dcb-26b9cf3150ae', 'is_bigquery_table': False, 'is_data_supplementary': 'False', 'last_modified': None, 'metadata_modified': '2023-06-13T08:17:01.899776', 'mimetype': None, 'mimetype_inner': None, 'name': 'WRC Project C2022_2023_00773 PMP Workshop 25 May 2023.pdf', 'package_id': '14a12540-ee4d-44e5-985a-4f1737363422', 'position': 2, 'resource_name': 'WRC Project C2022_2023_00773 PMP Workshop 25 May 2023', 'resource_type': None, 'size': None, 'state': 'active', 'url': 'https://storage.cloud.google.com/wrc_wro_datasets/hydrological_data_and_modelling/structured/access/static/updating-the-estimation-of-1-day-probable-maximum-precipitation-in-south-africa/WRC_Project_C2022_2023_00773_PMP_Workshop_25_May_2023-50ae.pdf', 'url_type': 'link', 'zipped_file': 'False'}, {'cache_last_updated': None, 'cache_url': None, 'created': '2023-06-13T08:27:58.857140', 'dataset_description': 'Tabulated 1-day PMP estimates for SA on a 5 x 5 km grid in CSV format. This data can be uploaded in GIS to create a shapefile containing the table attributes. ', 'datastore_active': False, 'description': None, 'file_to_bigquery_table': 'False', 'format': 'csv', 'hash': '', 'id': '94edc48f-ca79-4520-8982-35e20ec6a2fc', 'is_data_supplementary': 'False', 'last_modified': None, 'metadata_modified': '2024-09-20T15:13:40.885053', 'mimetype': None, 'mimetype_inner': None, 'name': 'PMP gridded database Rev 2024.csv', 'package_id': '14a12540-ee4d-44e5-985a-4f1737363422', 'position': 3, 'resource_name': 'PMP gridded database SA (2024)', 'resource_type': None, 'size': None, 'state': 'active', 'url': 'https://data.waterresearchobservatory.org/dataset/14a12540-ee4d-44e5-985a-4f1737363422/resource/94edc48f-ca79-4520-8982-35e20ec6a2fc/download/___', 'url_type': 'upload', 'zipped_file': 'False'}], 'tags': [], 'groups': [], 'relationships_as_subject': [], 'relationships_as_object': []}, {'agreement': 'true', 'alternative_identifier': 'https://doi.org/10.2166/hydro.2024.268', 'author': None, 'author_email': None, 'citation_title': 'Schutte, C., Van der Laan, M., & Van der Merwe, B. (2024). Leveraging historic streamflow and weather data with deep learning for enhanced streamflow predictions. Journal of Hydroinformatics.', 'creator_user_id': '7ceb61ee-8458-44bd-9990-62b71be18dd4', 'data_classification': 'time series', 'data_collection_organization': '', 'data_structure_category': 'structured', 'dataset_language': '', 'dataset_license_url': '', 'did_author_or_contact_organization_collect_the_data': 'true', 'email': 'ceschutte34@gmail.com', 'id': '52d35ec0-4d95-49a3-b596-fa7e109dca75', 'isopen': False, 'keywords': 'GRU, LSTM, Rainfall-runoff modelling', 'license': 'Open (Creative Commons)', 'license_id': None, 'license_title': None, 'maintainer': None, 'maintainer_email': None, 'metadata_created': '2023-07-27T15:17:57.228411', 'metadata_modified': '2024-08-17T16:40:18.609565', 'name': 'deep-learning-for-streamflow-prediction-project-data', 'notes': 'This dataset contains daily streamflow and weather data and the python code that was used to developed deep learning models for streamflow prediction. The data and code can be used to replicate the experiment on Google Drive using Google Colaboratory.\r\n\r\nStreamflow information is crucial for effectively managing water resources. The declining number of active gauging stations in many rivers is a global concern, necessitating the need for reliable streamflow estimates. Deep learning (DL) techniques offer potential solutions, but their application in southern Africa remains largely underexplored. To fill this gap, this study evaluated the predictive performance of Gated Recurrent Unit (GRU) and Long Short-Term Memory (LSTM) networks using two headwater catchments of the Steelpoort River, South Africa, as case studies. The model inputs included rainfall, maximum and minimum temperature, as well as past streamflow, which was utilized in an autoregressive sense. The inclusion of streamflow in this way allowed for the incorporation of simulated streamflow values into the look-back window (LBW) for predicting the streamflow of the testing set. Two modifications were required to the GRU and LSTM architectures to ensure physically consistent predictions. Including a change in activation function of the GRU/LSTM cells in the final hidden layer, and a non-negative constraint that was used in the dense layer. Models trained using commercial weather station data produced reliable streamflow estimates, while moderately accurate predictions were obtained using freely available gridded weather data.', 'num_resources': 1, 'num_tags': 0, 'organization': {'id': '4e8a617a-148a-4440-adde-e503f9346fcd', 'name': 'university-of-pretoria', 'title': 'University of Pretoria', 'type': 'organization', 'description': 'The University of Pretoria (UP) is one of Africa’s top universities and the largest contact university in South Africa. ', 'image_url': '2022-05-24-062305.772520UP-logo24May2022.JPG', 'created': '2022-05-24T06:23:05.795364', 'is_organization': True, 'approval_status': 'approved', 'state': 'active'}, 'owner_org': '4e8a617a-148a-4440-adde-e503f9346fcd', 'private': False, 'publication_date': '2024-04-30', 'publisher': 'Water Research Commission', 'spatial': '{"type": "Polygon", "coordinates": [[[16.4699, -22.1265], [32.8931, -22.1265], [32.8931, -34.8212], [16.4699, -34.8212], [16.4699, -22.1265]]]}', 'state': 'active', 'title': 'Deep recurrent neural networks for daily streamflow prediction', 'type': 'metadata-form', 'uploader_estimation_of_extent_of_processing': 'access', 'url': None, 'version': None, 'vertical_extent_datum': '1800', 'wrc_project_number': 'C2020/2021-00440', 'wro_theme': 'hydrological_data_and_modelling', 'authors': [{'author_department': 'Plant and Soil Sciences', 'author_email': 'ceschutte34@gmail.com', 'author_name': 'Christiaan', 'author_organization': 'University of Pretoria', 'author_surname': 'Schutte', 'contact_same_as_author': 'true'}], 'contact_person': [{'contact_department': '', 'contact_email': '', 'contact_name': '', 'contact_orgnization': ''}, {'contact_department': '', 'contact_email': '', 'contact_name': '', 'contact_orgnization': ''}], 'data_reference_date': [{'data_reference_date_from': '1979-10-01', 'data_reference_date_to': '2002-02-22'}], 'extras': [{'key': 'cloud_path', 'value': 'Hydrological_Data_And_Modelling/Structured/Access/Time Series'}], 'minimum_maximum_extent': [{'maximum_vertical_extent': '2263', 'minimum_vertical_extent': '1336'}], 'resources': [{'cache_last_updated': None, 'cache_url': None, 'created': '2024-02-13T15:39:11.287624', 'dataset_description': 'The folder contains the data needed to train GRU and LSTM models for streamflow prediction. See the ReadMe note inside the zipped folder for details on how to tun the experiment from Google Drive using Google Colab.\r\n\r\nDaily weather data, consisting of rainfall (mm), minimum and maximum temperature (̊C), and streamflow data (m3s-1) were used as input variables. The data included both in-situ measured data and gridded products. Daily weather data were obtained from three sources: 1) a weather station operated by the Agricultural Research Council (referred to as ARC in this study), 2) the Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) data (Funk et al. 2015) (https://www.chc.ucsb.edu/data/chirps), and 3) the National Aeronautics and Space Administration Prediction of Worldwide Energy Resources (NASAP) project (https://power.larc.nasa.gov/). Streamflow data were obtained from the DWS website (https://www.dws.gov.za/Hydrology/Verified/hymain.aspx) for stations B4H007 and B4H001 for Catchment A and Catchment B, respectively.', 'datastore_active': False, 'description': None, 'file_to_bigquery_table': 'False', 'format': 'zip', 'hash': '', 'id': 'd5e90237-e8f0-40e9-996e-2a19ea158669', 'is_bigquery_table': False, 'is_data_supplementary': 'False', 'last_modified': None, 'metadata_modified': '2024-02-13T15:39:13.933620', 'mimetype': None, 'mimetype_inner': None, 'name': 'Data_and_Code.zip', 'package_id': '52d35ec0-4d95-49a3-b596-fa7e109dca75', 'position': 0, 'resource_name': 'Project Data and Code', 'resource_type': None, 'size': None, 'state': 'active', 'url': 'https://storage.cloud.google.com/wrc_wro_datasets/hydrological_data_and_modelling/structured/access/time series/deep-learning-for-streamflow-prediction-project-data/Data_and_Code-8669.zip', 'url_type': 'link', 'zipped_file': 'False'}], 'tags': [], 'groups': [], 'relationships_as_subject': [], 'relationships_as_object': []}, {'agreement': 'true', 'alternative_identifier': '', 'author': None, 'author_email': None, 'citation_title': '', 'creator_user_id': '7ceb61ee-8458-44bd-9990-62b71be18dd4', 'data_classification': 'static', 'data_collection_organization': '', 'data_structure_category': 'structured', 'dataset_language': '', 'dataset_license_url': 'Https://Creativecommons.Org/Licenses/By/4.0/', 'did_author_or_contact_organization_collect_the_data': 'true', 'email': 'vanderlaanm@arc.agric.za', 'id': '26ce7c99-69ad-43d1-a18a-337d6a92043e', 'isopen': False, 'keywords': 'HAMSA, SWAT, HAWQS, Soil Map', 'license': 'Open (Creative Commons)', 'license_id': None, 'license_title': None, 'maintainer': None, 'maintainer_email': None, 'metadata_created': '2024-01-31T16:13:28.323655', 'metadata_modified': '2024-01-31T16:15:32.186014', 'name': 'swatcrossborder', 'notes': 'This WRC Funded Study Collated Multiple Geo-Spatial Datasets At A National Scale And Interpreted/Formatted The Data For Use As Baseline Input To Run The Soil And Water Assessment Tool (SWAT) In Any Catchment In SA. ArcSWAT Is A Graphical User Interface For SWAT And ArcGIS® Software Extension, Streamlining Access To Key Databases And Facilitating The Preparation Of Input Datasets. These Layers Can Also Be Used In QGIS And QSWAT. This dataset contains the swat input data for drainage areas that drain into South African rivers but fall outside the country boundary, such as in Botswana or Mozambique.', 'num_resources': 1, 'num_tags': 0, 'organization': {'id': '4e8a617a-148a-4440-adde-e503f9346fcd', 'name': 'university-of-pretoria', 'title': 'University of Pretoria', 'type': 'organization', 'description': 'The University of Pretoria (UP) is one of Africa’s top universities and the largest contact university in South Africa. ', 'image_url': '2022-05-24-062305.772520UP-logo24May2022.JPG', 'created': '2022-05-24T06:23:05.795364', 'is_organization': True, 'approval_status': 'approved', 'state': 'active'}, 'owner_org': '4e8a617a-148a-4440-adde-e503f9346fcd', 'private': False, 'publication_date': '2024-01-30', 'publisher': 'Water Research Commission', 'spatial': '{"type": "Polygon", "coordinates": [[[16.4699, -22.1265], [32.8931, -22.1265], [32.8931, -34.8212], [16.4699, -34.8212], [16.4699, -22.1265]]]}', 'state': 'active', 'title': 'SWAT Cross Border Data', 'type': 'metadata-form', 'uploader_estimation_of_extent_of_processing': 'access', 'url': None, 'version': None, 'vertical_extent_datum': '', 'wrc_project_number': 'WRC Project C2019-2020-00089', 'wro_theme': 'hydrological_data_and_modelling', 'authors': [{'author_department': 'Department Of Geography', 'author_email': 'LeRouxJJ@Ufs.Ac.Za', 'author_name': 'Jay', 'author_organization': 'University of the Free State', 'author_surname': 'Le Roux', 'contact_same_as_author': 'true'}], 'contact_person': [{'contact_department': '', 'contact_email': '', 'contact_name': '', 'contact_orgnization': ''}], 'data_reference_date': [{'data_reference_date_from': '', 'data_reference_date_to': ''}], 'extras': [{'key': 'cloud_path', 'value': 'Hydrological_Data_And_Modelling/Structured/Access/Static'}], 'minimum_maximum_extent': [{'maximum_vertical_extent': '3450', 'minimum_vertical_extent': '0'}], 'resources': [{'cache_last_updated': None, 'cache_url': None, 'created': '2024-01-31T16:14:36.594117', 'dataset_description': 'This WRC Funded Study Collated Multiple Geo-Spatial Datasets At A National Scale And Interpreted/Formatted The Data For Use As Baseline Input To Run The Soil And Water Assessment Tool (SWAT) In Any Catchment In SA. 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ArcSWAT Is A Graphical User Interface For SWAT And ArcGIS® Software Extension, Streamlining Access To Key Databases And Facilitating The Preparation Of Input Datasets. These Layers Can Also Be Used In QGIS And QSWAT.', 'num_resources': 2, 'num_tags': 0, 'organization': {'id': '4e8a617a-148a-4440-adde-e503f9346fcd', 'name': 'university-of-pretoria', 'title': 'University of Pretoria', 'type': 'organization', 'description': 'The University of Pretoria (UP) is one of Africa’s top universities and the largest contact university in South Africa. 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ArcSWAT Is A Graphical User Interface For SWAT And ArcGIS® Software Extension, Streamlining Access To Key Databases And Facilitating The Preparation Of Input Datasets. These Layers Can Also Be Used In QGIS And QSWAT.', 'datastore_active': False, 'description': None, 'file_to_bigquery_table': 'False', 'format': '.zip', 'hash': '', 'id': 'bf779890-6811-45a3-9e1f-e7c91dd0f1e8', 'is_bigquery_table': False, 'is_data_supplementary': 'False', 'last_modified': None, 'metadata_modified': '2024-01-30T14:42:15.619057', 'mimetype': None, 'mimetype_inner': None, 'name': 'QSWAT_SA_usersoil_20240130.zip', 'package_id': '3e7d7d13-232a-4ace-95f3-18cd474d3ada', 'position': 1, 'resource_name': 'QSWAT RSA Soil_30January2024', 'resource_type': None, 'size': None, 'state': 'active', 'url': 'https://storage.cloud.google.com/wrc_wro_datasets/hydrological_data_and_modelling/structured/access/static/a-south-african-national-input-database-to-run-the-swat-model-in-a-gis-soil-map_updated30jan2024/QSWAT_SA_usersoil_20240130-f1e8.zip', 'url_type': 'link', 'zipped_file': 'False'}], 'tags': [], 'groups': [], 'relationships_as_subject': [], 'relationships_as_object': []}, {'agreement': 'true', 'alternative_identifier': '', 'author': None, 'author_email': None, 'citation_title': 'Please reference as: Schütte, S.,, Schulze, R. E. and Horan, M. 2023 [Dataset]. SCS-SA hydrological soil groups over South Africa at terrain unit resolution. Centre for Water Resourses REsearch, University of KwaZulu-Natal, Pietermaritzburg, South Africa.', 'creator_user_id': '62b97d06-64e4-4a22-b9d3-5b5a8b6b4b10', 'data_classification': 'static', 'data_collection_organization': 'University of KwaZulu-Natal', 'data_structure_category': 'structured', 'dataset_language': 'Englisch', 'dataset_license_url': 'https://creativecommons.org/licenses/by-sa/4.0/', 'did_author_or_contact_organization_collect_the_data': 'true', 'email': 'Schuttes@ukzn.ac.za', 'id': '3a2516fd-0098-4b9a-9162-d7a7fab5c705', 'isopen': False, 'keywords': 'SCS, SCS-SA, Hydrological Soil Groups', 'license': 'Open (Creative Commons)', 'license_id': None, 'license_title': None, 'maintainer': None, 'maintainer_email': None, 'metadata_created': '2023-09-29T10:51:26.631148', 'metadata_modified': '2023-11-13T08:45:23.060522', 'name': 'scs-hydrological-soil-groups-over-south-africa-at-terrain-unit-resolution', 'notes': 'This raster file contains the SCS-SA classes on a Terrain unit resolution for South Africa as developed by Schulze and Schütte.\r\nThe attribute table shows the SCS-SA classification (A, A/B, B, B/C, C, C/D, and D).\r\nThey were assigned a corresponding number in CODE_VAL of A=1, A/B = 2, B = 3, B/C =4, C = 5, C/D = 6, D = 7.\r\nSome areas were classified as water and not given an SCS-SA class. The CODE-VAL is 8.', 'num_resources': 1, 'num_tags': 0, 'organization': {'id': '8fc48fc6-e2c7-480f-baac-3fb079ebf89b', 'name': 'https-cwrr-ukzn-ac-za', 'title': 'Centre for Water Resources Research@UKZN', 'type': 'organization', 'description': 'The Centre for Water Resources Research was formed in 2012 out of a cohesive group of academics who have been active in research, teaching and capacity building related to hydrology and water resources research since 1984. The on-going importance and relevance of water resources related research and teaching and the sustained research output of the group provides the basis to formally establish a Centre of Excellence within the University of KwaZulu-Natal. 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[Dataset] Climate Change Impacts on Hydrological Yield under Natural Vegetation: ACRU outputs. WRC Project K5/2833, Water Research Commission, Pretoria, South Africa.', 'creator_user_id': '62b97d06-64e4-4a22-b9d3-5b5a8b6b4b10', 'data_classification': 'static', 'data_collection_organization': 'University of KwaZulu-Natal', 'data_structure_category': 'structured', 'dataset_language': 'Englisch', 'dataset_license_url': 'https://creativecommons.org/licenses/by-sa/4.0/', 'did_author_or_contact_organization_collect_the_data': 'true', 'email': 'Schuttes@ukzn.ac.za', 'id': '26297cab-d1df-4311-8248-efbd1c3ef929', 'isopen': False, 'keywords': 'ACRU stats, Climate Change, Hydrology', 'license': 'Open (Creative Commons)', 'license_id': None, 'license_title': None, 'maintainer': None, 'maintainer_email': None, 'metadata_created': '2023-10-18T11:15:37.393409', 'metadata_modified': '2023-11-02T13:25:35.147121', 'name': 'climate-change-impacts-on-hydrological-yield-under-natural-vegetation-acru', 'notes': ' ACRU output stats for:\r\n* seven scenarios (6 GCMs under RCP8.5 and historical climate conditions)\r\n* for three time periods: 1961-1990, 2015-2044, 2017-2099\r\n* assumed natural vegetation\r\n* 5838 quinary zones in South Africa, Eswatini and Lesotho\r\n* 18 hydrological and 13 climatic variables\r\n* for mean, 10th, 50th and 90th percentile', 'num_resources': 1, 'num_tags': 0, 'organization': {'id': '8fc48fc6-e2c7-480f-baac-3fb079ebf89b', 'name': 'https-cwrr-ukzn-ac-za', 'title': 'Centre for Water Resources Research@UKZN', 'type': 'organization', 'description': 'The Centre for Water Resources Research was formed in 2012 out of a cohesive group of academics who have been active in research, teaching and capacity building related to hydrology and water resources research since 1984. 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ISRIC 2015/02. collaboration project of African soil information service (AISIS) and global yield gap and water productivity atlas (GYGA)- world soil information wagengen the Netherlands. 108 pp.,;9 tab.;66 ref ', 'creator_user_id': 'ffc3a0ea-c8fa-49c6-b998-42f47ecdd9e7', 'data_classification': 'static', 'data_collection_organization': 'World soil information', 'data_structure_category': 'structured', 'dataset_language': 'English', 'dataset_license_url': 'not provided', 'did_author_or_contact_organization_collect_the_data': 'false', 'email': 'ntandomt@gmail.com', 'id': '7fb4a4cc-777a-4651-8c53-2a760c57d472', 'isopen': False, 'keywords': 'soil profile, soil data, soil information, functional soil properties, rootable soil depth, effective root, zone depth, rootability, plant available soil water holding capacity, padotransfer function, digital soil mapping, regression, statistics, yield gap, yield potential, AfSoilGrids, Africa, AFSIS, GYGA, ISRIC, Angola, Benin, Botswana, Burkina Faso, Burundi, Cameroon, Central Africa Rebuplic, Chad, Cango-Brazzaville, Congo-Demecratic Republic, Cote d"lvore, Ethopia, Gabon, Ghana, Guinea, Guinea-Bissau, Kenya, Liberia, Lesotho, Madagascar,, Malawo, Mali, Mauretania, Mozambique, Namibia, Niger, Nigeria, Rwanda,South Africa, South Sudan, Sudan, Sierra Leone, Senegal, Somalia, Swaziland, Togo, Tanzania, Uganda, Zambia, Zimbabwe', 'license': 'Ohter', 'license_id': None, 'license_title': None, 'maintainer': None, 'maintainer_email': None, 'metadata_created': '2023-05-29T08:25:15.519090', 'metadata_modified': '2023-09-15T05:54:37.352335', 'name': 'root-zone-plant-available-water-holding-capacity-of-the-sub-saharan-afrrican-soil', 'notes': 'Root zone plant available water holding capacity of sub-Saharan African soil', 'num_resources': 1, 'num_tags': 0, 'organization': {'id': 'bdd9b40b-b0ce-46e2-9b10-9ba5d5093fcb', 'name': 'agricultural-research-council-natural-resources-and-engineering', 'title': 'Agricultural Research Council', 'type': 'organization', 'description': 'The Agricultural Research Council is a premier science institution that conducts research with partners, develops human capital and fosters innovation to support and develop the agricultural sector. ', 'image_url': '2022-06-29-044237.19412620220524ARCLogo.JPG', 'created': '2022-05-24T08:09:41.025666', 'is_organization': True, 'approval_status': 'approved', 'state': 'active'}, 'owner_org': 'bdd9b40b-b0ce-46e2-9b10-9ba5d5093fcb', 'private': False, 'publication_date': '2015-02-02', 'publisher': 'World science information ', 'spatial': '{"type": "Polygon", "coordinates": [[[16.4699, -22.1265], [32.8931, -22.1265], [32.8931, -34.8212], [16.4699, -34.8212], [16.4699, -22.1265]]]}', 'state': 'active', 'title': 'Root zone plant - available water holding capacity of the sub-Saharan African soil', 'type': 'metadata-form', 'uploader_estimation_of_extent_of_processing': 'access', 'url': None, 'version': None, 'vertical_extent_datum': 'not provided', 'wrc_project_number': 'not provided', 'wro_theme': 'water_quality', 'authors': [{'author_department': 'not provided', 'author_email': 'not provided', 'author_name': 'J.G.B ', 'author_organization': 'not provided', 'author_surname': 'Leenaars'}, {'author_department': 'not provided', 'author_email': 'not provided', 'author_name': 'T', 'author_organization': 'not provided', 'author_surname': 'Hengl'}, {'author_department': 'not orovided', 'author_email': 'not provided', 'author_name': 'M', 'author_organization': 'not provided', 'author_surname': 'Ruiperez Gonzalez'}, {'author_department': 'not provided', 'author_email': 'not provided', 'author_name': 'J.S', 'author_organization': 'not provided', 'author_surname': 'Meneds de Jesus'}, {'author_department': 'not provided', 'author_email': 'not provided', 'author_name': 'G.B.M ', 'author_organization': 'not provided', 'author_surname': 'Heuvelink'}, {'author_department': 'not provided', 'author_email': 'not provided', 'author_name': 'J.', 'author_organization': 'not provided', 'author_surname': 'Wolf'}, {'author_department': 'not provided', 'author_email': 'not provided', 'author_name': 'L.G.J', 'author_organization': 'not provided', 'author_surname': 'vam Bussel '}, {'author_department': 'not provided', 'author_email': 'not provided', 'author_name': 'L.', 'author_organization': 'not provided', 'author_surname': 'Claessens'}, {'author_department': 'not provided', 'author_email': 'not provided', 'author_name': 'H.', 'author_organization': 'not provided', 'author_surname': 'Yang'}, {'author_department': 'not provided', 'author_email': 'not provided', 'author_name': 'K.G.', 'author_organization': 'not provided', 'author_surname': 'Cassman '}], 'contact_person': [{'contact_department': 'Agricultural research council', 'contact_email': 'VanderLaanM@arc.agric.za', 'contact_name': 'Michael van der Laan', 'contact_orgnization': 'Agricultural Research Council'}], 'data_reference_date': [{'data_reference_date_from': '2015-02-01', 'data_reference_date_to': '2015-02-28'}], 'extras': [{'key': 'cloud_path', 'value': 'Water_Quality/Structured/Access/Static'}], 'minimum_maximum_extent': [{'maximum_vertical_extent': 'not provided', 'minimum_vertical_extent': 'not provided'}], 'resources': [{'cache_last_updated': None, 'cache_url': None, 'created': '2023-05-29T08:28:25.074543', 'dataset_description': 'Gridded functional soil information (dataset RZ-PAWHC SSA version 1.0) ', 'datastore_active': False, 'description': None, 'file_to_bigquery_table': 'False', 'format': 'pdf', 'hash': '', 'id': 'bea791b4-5ddf-4604-b407-1ecb2167912f', 'is_bigquery_table': False, 'is_data_supplementary': 'False', 'last_modified': None, 'metadata_modified': '2023-05-29T08:28:26.072194', 'mimetype': None, 'mimetype_inner': None, 'name': '', 'package_id': '7fb4a4cc-777a-4651-8c53-2a760c57d472', 'position': 0, 'resource_name': 'Root zone plant available water holding capacity of the sub-Saharam Africa soil ', 'resource_type': None, 'size': None, 'state': 'active', 'url': 'https://data.waterresearchobservatory.org/dataset/7fb4a4cc-777a-4651-8c53-2a760c57d472/resource/bea791b4-5ddf-4604-b407-1ecb2167912f/download/rootzone_plant_available_water_holding_capacity_of_sub-saharan_africa_soil__1_-912f.pdf', 'url_type': 'upload', 'zipped_file': 'False'}], 'tags': [], 'groups': [], 'relationships_as_subject': [], 'relationships_as_object': []}, {'agreement': 'true', 'alternative_identifier': 'ISBN 978-0-6392-0146-7', 'author': None, 'author_email': None, 'citation_title': 'AGRICULTURAL RESEARCH COUNCIL (ARC) (2019) Irrigation User Manual. ISBN 978-0-6392-0146-7, ARC, Pretoria, South Africa.', 'creator_user_id': '994bdae6-cbc9-47f5-bd04-27672cfa8648', 'data_classification': 'static', 'data_collection_organization': 'Agricultural Research Council', 'data_structure_category': 'unstructured', 'dataset_language': 'English', 'dataset_license_url': 'https://creativecommons.org/licenses/by-sa/4.0/', 'did_author_or_contact_organization_collect_the_data': 'true', 'email': 'vanderlaanm@arc.agric.za', 'id': '9e9ed667-580e-42cb-95e4-3bcaa03db35a', 'isopen': False, 'keywords': 'irrigation, pivot, drip, sprinkler, soil, water, agriculture, crop production', 'license': 'Open (Creative Commons)', 'license_id': None, 'license_title': None, 'maintainer': None, 'maintainer_email': None, 'metadata_created': '2023-08-23T09:52:08.941570', 'metadata_modified': '2023-09-15T05:51:44.248850', 'name': 'arc-irrigation-user-manual', 'notes': 'The purpose of this manual is to serve as a reference guide for producers for the planning, choice, installation, management and maintenance of an irrigation system. 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