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  "agreement": "true",
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  "agreement": "true",
            
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  "alternative_identifier": "DOI: 10.1016/j.agwat.2025.109592",
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  "alternative_identifier": "DOI: 10.1016/j.agwat.2025.109592",
            
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  "author": null,
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  "author": null,
            
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  "author_email": null,
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  "authors": [
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  "authors": [
            
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    {
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    {
            
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      "author_department": "Plant and Soil Sciences",
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      "author_department": "Plant and Soil Sciences",
            
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      "author_email": "cindy.viviers63@gmail.com",
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      "author_email": "cindy.viviers63@gmail.com",
            
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      "author_name": "Cindy",
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      "author_name": "Cindy",
            
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      "author_organization": "University of Pretoria",
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      "author_organization": "University of Pretoria",
            
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      "author_surname": "Viviers",
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      "author_surname": "Viviers",
            
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      "contact_same_as_author": "true"
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      "contact_same_as_author": "true"
            
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    },
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    {
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    {
            
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      "author_department": "",
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      "author_department": "",
            
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      "author_email": "vanderLaanM@arc.agric.za",
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      "author_email": "vanderLaanM@arc.agric.za",
            
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      "author_name": "Michael",
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      "author_name": "Michael",
            
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      "author_organization": "Agricultural Research Council",
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      "author_organization": "Agricultural Research Council",
            
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      "author_surname": "van der Laan"
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      "author_surname": "van der Laan"
            
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    }
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    }
            
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  ],
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  ],
            
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  "citation_title": "VIVIERS C and VAN DER LAAN M (2025) Assessing the 
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  "citation_title": "VIVIERS C and VAN DER LAAN M (2025) Assessing the 
            
24
use of remotely sensed surface water flux to estimate net groundwater 
24
use of remotely sensed surface water flux to estimate net groundwater 
            
25
storage change in an aquifer predominantly used for irrigation. 
25
storage change in an aquifer predominantly used for irrigation. 
            
26
Agricultural Water Management 316 109592. 
26
Agricultural Water Management 316 109592. 
            
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https://doi.org/10.1016/j.agwat.2025.109592.",
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https://doi.org/10.1016/j.agwat.2025.109592.",
            
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  "contact_person": [
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  "contact_person": [
            
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    {
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    {
            
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      "contact_department": "Plant and Soil Sciences",
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      "contact_department": "Plant and Soil Sciences",
            
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      "contact_email": "cindy.viviers63@gmail.com",
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      "contact_email": "cindy.viviers63@gmail.com",
            
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      "contact_name": "Cindy",
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      "contact_name": "Cindy",
            
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      "contact_orgnization": "University of Pretoria"
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      "contact_orgnization": "University of Pretoria"
            
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    }
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    }
            
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  ],
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  ],
            
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  "creator_user_id": "bc28a33f-dc21-4795-a57f-da7cd1aa23ea",
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  "creator_user_id": "bc28a33f-dc21-4795-a57f-da7cd1aa23ea",
            
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  "data_classification": "time series",
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  "data_classification": "time series",
            
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  "data_collection_organization": "Agricultural Research Council",
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  "data_collection_organization": "Agricultural Research Council",
            
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  "data_reference_date": [
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  "data_reference_date": [
            
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    {
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    {
            
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      "data_reference_date_from": "1981-01-01",
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      "data_reference_date_from": "1981-01-01",
            
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      "data_reference_date_to": "2021-12-31"
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      "data_reference_date_to": "2021-12-31"
            
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    }
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    }
            
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  ],
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  ],
            
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  "data_structure_category": "semi-structured",
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  "data_structure_category": "semi-structured",
            
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  "dataset_language": "English",
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  "dataset_language": "English",
            
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  "dataset_license_url": 
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  "dataset_license_url": 
            
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"https://creativecommons.org/licenses/by-sa/4.0/",
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"https://creativecommons.org/licenses/by-sa/4.0/",
            
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  "did_author_or_contact_organization_collect_the_data": "true",
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  "did_author_or_contact_organization_collect_the_data": "true",
            
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  "email": "vanderLaanM@arc.agric.za",
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  "email": "vanderLaanM@arc.agric.za",
            
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  "groups": [],
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  "groups": [],
            
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  "id": "80d05bc9-e67b-4341-9843-5889d69f4d6e",
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  "id": "80d05bc9-e67b-4341-9843-5889d69f4d6e",
            
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  "isopen": false,
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  "isopen": false,
            
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  "keywords": "Independent cultivation classification, Integrated 
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  "keywords": "Independent cultivation classification, Integrated 
            
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water use management, Google Earth Engine, South Africa",
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water use management, Google Earth Engine, South Africa",
            
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  "license": "Open (Creative Commons)",
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  "license": "Open (Creative Commons)",
            
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  "license_id": null,
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  "license_id": null,
            
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  "license_title": null,
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  "license_title": null,
            
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  "maintainer": null,
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  "maintainer": null,
            
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  "maintainer_email": null,
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  "maintainer_email": null,
            
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  "metadata_created": "2026-02-25T09:30:03.495842",
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  "metadata_created": "2026-02-25T09:30:03.495842",
            
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  "metadata_modified": "2026-03-09T02:43:36.593532",
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  "metadata_modified": "2026-03-09T02:45:35.883215",
            
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  "minimum_maximum_extent": [
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  "minimum_maximum_extent": [
            
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    {
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    {
            
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      "maximum_vertical_extent": "1592",
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      "maximum_vertical_extent": "1592",
            
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      "minimum_vertical_extent": "1560"
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      "minimum_vertical_extent": "1560"
            
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    }
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    }
            
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  ],
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  ],
            
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  "name": 
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  "name": 
            
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a-surface-flux-and-groundwater-storage-change-steenkoppies-2018-2021",
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a-surface-flux-and-groundwater-storage-change-steenkoppies-2018-2021",
            
71
  "notes": "A set of remotely sensed and derived monthly data products 
71
  "notes": "A set of remotely sensed and derived monthly data products 
            
72
was compiled and analysed for the Steenkoppies Dolomitic Compartment 
72
was compiled and analysed for the Steenkoppies Dolomitic Compartment 
            
73
(South Africa) to enable near real-time monitoring of irrigated 
73
(South Africa) to enable near real-time monitoring of irrigated 
            
74
cultivation and aquifer stress. Monthly actively cultivated areas were 
74
cultivation and aquifer stress. Monthly actively cultivated areas were 
            
75
identified from Sentinel\u20112 imagery using an independently trained 
75
identified from Sentinel\u20112 imagery using an independently trained 
            
76
Random Forest classifier on seasonal median composites that captured 
76
Random Forest classifier on seasonal median composites that captured 
            
77
crop phenological changes. The cultivated-area outputs were integrated 
77
crop phenological changes. The cultivated-area outputs were integrated 
            
78
with WaPOR actual evapotranspiration (ETa) data to estimate monthly 
78
with WaPOR actual evapotranspiration (ETa) data to estimate monthly 
            
79
crop water use at 250 m resolution, while monthly precipitation from 
79
crop water use at 250 m resolution, while monthly precipitation from 
            
80
CHIRPS was aligned and resampled to the same reference system. Monthly 
80
CHIRPS was aligned and resampled to the same reference system. Monthly 
            
81
net irrigation water use was estimated as ETa minus precipitation 
81
net irrigation water use was estimated as ETa minus precipitation 
            
82
(with negative values set to zero to indicate no irrigation 
82
(with negative values set to zero to indicate no irrigation 
            
83
requirement), and monthly surface water flux was estimated as 
83
requirement), and monthly surface water flux was estimated as 
            
84
precipitation minus ETa. Net groundwater storage change was estimated 
84
precipitation minus ETa. Net groundwater storage change was estimated 
            
85
by combining downscaled GLDAS groundwater storage anomaly changes with 
85
by combining downscaled GLDAS groundwater storage anomaly changes with 
            
86
irrigated areas, enabling comparison of surface water flux with 
86
irrigated areas, enabling comparison of surface water flux with 
            
87
groundwater storage dynamics. The outputs were used to quantify 
87
groundwater storage dynamics. The outputs were used to quantify 
            
88
changes in irrigated cropped area and to examine seasonal patterns 
88
changes in irrigated cropped area and to examine seasonal patterns 
            
89
showing that irrigation demand and groundwater abstraction peaks 
89
showing that irrigation demand and groundwater abstraction peaks 
            
90
coincided with low precipitation periods, while precipitation was the 
90
coincided with low precipitation periods, while precipitation was the 
            
91
primary aquifer recharge source. The complete Google Earth Engine 
91
primary aquifer recharge source. The complete Google Earth Engine 
            
92
scripts (including datasets) were provided as part of the 
92
scripts (including datasets) were provided as part of the 
            
93
manuscript.",
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manuscript.",
            
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    "approval_status": "approved",
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    "created": "2025-11-12T19:07:25.734791",
            
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    "description": "The Agricultural Research Council is a premier 
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    "description": "The Agricultural Research Council is a premier 
            
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science institution that conducts research with partners, develops 
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science institution that conducts research with partners, develops 
            
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human capital and fosters innovation to support and develop the 
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human capital and fosters innovation to support and develop the 
            
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agricultural sector. ",
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agricultural sector. ",
            
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    "id": "83b40f98-af75-4fd2-9a27-9ef7295092b2",
            
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    "name": "agricultural-research-council",
            
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    "state": "active",
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    "state": "active",
            
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    "title": "Agricultural Research Council",
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    "title": "Agricultural Research Council",
            
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  "private": false,
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  "publication_date": "2025-06-07",
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  "publication_date": "2025-06-07",
            
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  "publisher": "Agricultural Water Management (Elsevier)",
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  "publisher": "Agricultural Water Management (Elsevier)",
            
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      "dataset_description": "Google Earth Engine script used to model 
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      "dataset_description": "Google Earth Engine script used to model 
            
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water fluxes at a monthly time-step.",
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water fluxes at a monthly time-step.",
            
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      "name": "MONTHLY CROP WATER AND IRRIGATION WATER USE ACROSS 
            
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CROPLAND.txt",
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CROPLAND.txt",
            
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      "url": 
            
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load/monthly-crop-water-and-irrigation-water-use-across-cropland.txt",
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load/monthly-crop-water-and-irrigation-water-use-across-cropland.txt",
            
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  "state": "active",
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  "state": "active",
            
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  "tags": [],
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  "tags": [],
            
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  "title": "Monthly irrigation, ETa, surface flux and groundwater 
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  "title": "Monthly irrigation, ETa, surface flux and groundwater 
            
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storage change: Steenkoppies (2018\u20132021)",
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storage change: Steenkoppies (2018\u20132021)",
            
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  "type": "dataset",
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  "type": "dataset",
            
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  "wrc_project_number": "C2020/2021\u201300440",
            
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  "wro_theme": "agriculture"
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  "wro_theme": "agriculture"
            
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}
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}