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On May 26, 2021 at 2:45:45 AM UTC, seanh:
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Updated description of Constructing dataset of classified drainage areas based on surface water-supply patterns in High Mountain Asia from
The High Mountain Asia (HMA) region is a geographical unit, holds the largest reservoir of glaciers and snow outside Earth poles. Four datasets were thus obtained: Glacier- and Stream-fed Drainage Area (GSDA), Glacier-fed and stream-free Drainage Area(GDA), glacier-free and Stream-fed Drainage Area(SDA), and the Glacier- and Stream-free Drainage Area (NGSDA), with the numbers of 87, 107, 32, and 448 separately. The statistical results show GSDA has the largest surface area, accounting for 82.2% of the total basin area in HMA, mainly in the region of the outflow basin. Dominated by small basins, the GDA area accounts for the smallest surface area, only 3.86% of the total, the SDA accounts for 5.62%. For NGSDA, most of these are with small areas, accounting for 8.32%, and mainly distributes in the inflow basin of the Qiangtang Plateau.
toThe High Mountain Asia (HMA) region is a geographical unit, holds the largest reservoir of glaciers and snow outside Earth poles. Four datasets were thus obtained: Glacier- and Stream-fed Drainage Area (GSDA), Glacier-fed and stream-free Drainage Area(GDA), glacier-free and Stream-fed Drainage Area(SDA), and the Glacier- and Stream-free Drainage Area (NGSDA), with the numbers of 87, 107, 32, and 448 separately. The statistical results show GSDA has the largest surface area, accounting for 82.2% of the total basin area in HMA, mainly in the region of the outflow basin. Dominated by small basins, the GDA area accounts for the smallest surface area, only 3.86% of the total, the SDA accounts for 5.62%. For NGSDA, most of these are with small areas, accounting for 8.32%, and mainly distributes in the inflow basin of the Qiangtang Plateau.
f | 1 | { | f | 1 | { |
2 | "author": "Jieyu Lu, Yubao Qiu, Xingxing Wang, Wenshan Liang, | 2 | "author": "Jieyu Lu, Yubao Qiu, Xingxing Wang, Wenshan Liang, | ||
3 | Pengfei Xie, Lijuan Shi, Massimo Menenti, Dongshui Zhang", | 3 | Pengfei Xie, Lijuan Shi, Massimo Menenti, Dongshui Zhang", | ||
4 | "author_email": "qiuyb@aircas.ac.cn", | 4 | "author_email": "qiuyb@aircas.ac.cn", | ||
5 | "creator_user_id": "2e9fa41b-0394-4070-98d0-205f79d5738b", | 5 | "creator_user_id": "2e9fa41b-0394-4070-98d0-205f79d5738b", | ||
6 | "extras": [ | 6 | "extras": [ | ||
7 | { | 7 | { | ||
8 | "key": "Geographic Coverage", | 8 | "key": "Geographic Coverage", | ||
9 | "value": "24\u00b040\u2032N-45\u00b058\u2032N, | 9 | "value": "24\u00b040\u2032N-45\u00b058\u2032N, | ||
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11 | }, | 11 | }, | ||
12 | { | 12 | { | ||
13 | "key": "Time", | 13 | "key": "Time", | ||
14 | "value": "2003-2013" | 14 | "value": "2003-2013" | ||
15 | } | 15 | } | ||
16 | ], | 16 | ], | ||
17 | "groups": [ | 17 | "groups": [ | ||
18 | { | 18 | { | ||
19 | "description": "CAS-GMELT, the Gla.cial Melt Toolbox for High | 19 | "description": "CAS-GMELT, the Gla.cial Melt Toolbox for High | ||
20 | Mountain Asia, are collections of dataset, models, and tools by the | 20 | Mountain Asia, are collections of dataset, models, and tools by the | ||
21 | GMELT project funded by Chinese Academy of Sciences. CAS-GMELT | 21 | GMELT project funded by Chinese Academy of Sciences. CAS-GMELT | ||
22 | provides an operational publicly open platform for the exchange and | 22 | provides an operational publicly open platform for the exchange and | ||
23 | collaboration with NASA's Earth Science\u00a0Division (ESD). The | 23 | collaboration with NASA's Earth Science\u00a0Division (ESD). The | ||
24 | CAS-GMELT is aiming to develop newly geophysical parameters based on | 24 | CAS-GMELT is aiming to develop newly geophysical parameters based on | ||
25 | space Earth observations.", | 25 | space Earth observations.", | ||
26 | "display_name": "CAS-GMELT", | 26 | "display_name": "CAS-GMELT", | ||
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30 | "name": "cas-gmelt", | 30 | "name": "cas-gmelt", | ||
31 | "title": "CAS-GMELT" | 31 | "title": "CAS-GMELT" | ||
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33 | { | 33 | { | ||
34 | "description": "Big Earth Data - Based Environment Monitoring | 34 | "description": "Big Earth Data - Based Environment Monitoring | ||
35 | and Information Service for Arctic Seaway, is an International | 35 | and Information Service for Arctic Seaway, is an International | ||
36 | Partnership Program of the Chinese Academy of Sciences (Grant No. | 36 | Partnership Program of the Chinese Academy of Sciences (Grant No. | ||
37 | 131211KYSB20150035), operated from 2018.01-2020.12.", | 37 | 131211KYSB20150035), operated from 2018.01-2020.12.", | ||
38 | "display_name": "Environment Monitoring and Information Service | 38 | "display_name": "Environment Monitoring and Information Service | ||
39 | for Arctic Searoute", | 39 | for Arctic Searoute", | ||
40 | "id": "b17dbae0-e9e9-45ed-b628-04a138fbdc90", | 40 | "id": "b17dbae0-e9e9-45ed-b628-04a138fbdc90", | ||
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44 | "title": "Environment Monitoring and Information Service for | 44 | "title": "Environment Monitoring and Information Service for | ||
45 | Arctic Searoute" | 45 | Arctic Searoute" | ||
46 | }, | 46 | }, | ||
47 | { | 47 | { | ||
48 | "description": "The JRC-AO, Joint Research Center for Arctic | 48 | "description": "The JRC-AO, Joint Research Center for Arctic | ||
49 | Observations, is a joint research center for the collabration effort | 49 | Observations, is a joint research center for the collabration effort | ||
50 | by AIR-CAS, and ASC FMI.", | 50 | by AIR-CAS, and ASC FMI.", | ||
51 | "display_name": "JRC-AO", | 51 | "display_name": "JRC-AO", | ||
52 | "id": "9fe5fbb1-f9e5-4ebe-8623-b60b7d6255b4", | 52 | "id": "9fe5fbb1-f9e5-4ebe-8623-b60b7d6255b4", | ||
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55 | "name": "jrc-ao", | 55 | "name": "jrc-ao", | ||
56 | "title": "JRC-AO" | 56 | "title": "JRC-AO" | ||
57 | }, | 57 | }, | ||
58 | { | 58 | { | ||
59 | "description": "MARIS/NTAROS project (Grant No. 2017YFE0111700), | 59 | "description": "MARIS/NTAROS project (Grant No. 2017YFE0111700), | ||
60 | the Multi-Parameters Arctic Environmental Observations and Information | 60 | the Multi-Parameters Arctic Environmental Observations and Information | ||
61 | Services, is a Chinese counterpart project to EU-H2020 INTAROS, funded | 61 | Services, is a Chinese counterpart project to EU-H2020 INTAROS, funded | ||
62 | the Ministry of Science and Technology of China. The consortium is | 62 | the Ministry of Science and Technology of China. The consortium is | ||
63 | Aerospace Information Research Institute, Chinese Academy of Science | 63 | Aerospace Information Research Institute, Chinese Academy of Science | ||
64 | (AIR, CAS), National Marine Environmental Forecasting Center (NMEFC), | 64 | (AIR, CAS), National Marine Environmental Forecasting Center (NMEFC), | ||
65 | and Polar Research Institute of China of State Oceanic Administration | 65 | and Polar Research Institute of China of State Oceanic Administration | ||
66 | (SOA), operated from 1 April 2018 - 30 April 2021. MARIS will be | 66 | (SOA), operated from 1 April 2018 - 30 April 2021. MARIS will be | ||
67 | providing several datasets for the Arctic region.", | 67 | providing several datasets for the Arctic region.", | ||
68 | "display_name": "MARIS", | 68 | "display_name": "MARIS", | ||
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72 | "name": "maris", | 72 | "name": "maris", | ||
73 | "title": "MARIS" | 73 | "title": "MARIS" | ||
74 | } | 74 | } | ||
75 | ], | 75 | ], | ||
76 | "id": "f07acfb2-6572-4bd8-9e9e-95b3124eaa2c", | 76 | "id": "f07acfb2-6572-4bd8-9e9e-95b3124eaa2c", | ||
77 | "isopen": true, | 77 | "isopen": true, | ||
78 | "license_id": "other-open", | 78 | "license_id": "other-open", | ||
79 | "license_title": "Other (Open)", | 79 | "license_title": "Other (Open)", | ||
80 | "maintainer": "", | 80 | "maintainer": "", | ||
81 | "maintainer_email": "", | 81 | "maintainer_email": "", | ||
82 | "metadata_created": "2020-05-07T08:22:08.790407", | 82 | "metadata_created": "2020-05-07T08:22:08.790407", | ||
n | 83 | "metadata_modified": "2021-05-21T10:56:42.971196", | n | 83 | "metadata_modified": "2021-05-26T02:45:45.443118", |
84 | "name": | 84 | "name": | ||
85 | -of-classified-drainage-areas-based-on-surface-water-supply-patterns", | 85 | -of-classified-drainage-areas-based-on-surface-water-supply-patterns", | ||
86 | "notes": "The High Mountain Asia (HMA) region is a geographical | 86 | "notes": "The High Mountain Asia (HMA) region is a geographical | ||
87 | unit, holds the largest reservoir of glaciers and snow outside Earth | 87 | unit, holds the largest reservoir of glaciers and snow outside Earth | ||
88 | poles. Four datasets were thus obtained: Glacier- and Stream-fed | 88 | poles. Four datasets were thus obtained: Glacier- and Stream-fed | ||
89 | Drainage Area (GSDA), Glacier-fed and stream-free Drainage Area(GDA), | 89 | Drainage Area (GSDA), Glacier-fed and stream-free Drainage Area(GDA), | ||
90 | glacier-free and Stream-fed Drainage Area(SDA), and the Glacier- and | 90 | glacier-free and Stream-fed Drainage Area(SDA), and the Glacier- and | ||
91 | Stream-free Drainage Area (NGSDA), with the numbers of 87, 107, 32, | 91 | Stream-free Drainage Area (NGSDA), with the numbers of 87, 107, 32, | ||
92 | and 448 separately. The statistical results show GSDA has the largest | 92 | and 448 separately. The statistical results show GSDA has the largest | ||
93 | surface area, accounting for 82.2% of the total basin area in HMA, | 93 | surface area, accounting for 82.2% of the total basin area in HMA, | ||
94 | mainly in the region of the outflow basin. Dominated by small basins, | 94 | mainly in the region of the outflow basin. Dominated by small basins, | ||
95 | the GDA area accounts for the smallest surface area, only 3.86% of the | 95 | the GDA area accounts for the smallest surface area, only 3.86% of the | ||
96 | total, the SDA accounts for 5.62%. For NGSDA, most of these are with | 96 | total, the SDA accounts for 5.62%. For NGSDA, most of these are with | ||
97 | small areas, accounting for 8.32%, and mainly distributes in the | 97 | small areas, accounting for 8.32%, and mainly distributes in the | ||
t | 98 | inflow basin of the Qiangtang Plateau.", | t | 98 | inflow basin of the Qiangtang Plateau. ", |
99 | "num_resources": 1, | 99 | "num_resources": 1, | ||
100 | "num_tags": 2, | 100 | "num_tags": 2, | ||
101 | "organization": { | 101 | "organization": { | ||
102 | "approval_status": "approved", | 102 | "approval_status": "approved", | ||
103 | "created": "2020-04-30T11:11:08.802657", | 103 | "created": "2020-04-30T11:11:08.802657", | ||
104 | "description": "Aerospace Information Research Institute (AIR) | 104 | "description": "Aerospace Information Research Institute (AIR) | ||
105 | under the Chinese Academy of Sciences (CAS) was established in July | 105 | under the Chinese Academy of Sciences (CAS) was established in July | ||
106 | 2017, following the approval for consolidation of three CAS | 106 | 2017, following the approval for consolidation of three CAS | ||
107 | institutes: the Institute of Electronics (IECAS), the Institute of | 107 | institutes: the Institute of Electronics (IECAS), the Institute of | ||
108 | Remote Sensing and Digital Earth (RADI), and the Academy of | 108 | Remote Sensing and Digital Earth (RADI), and the Academy of | ||
109 | Opto-Electronics (AOE) at CAS President Board Meeting. The merger is | 109 | Opto-Electronics (AOE) at CAS President Board Meeting. The merger is | ||
110 | the outcome of CAS efforts towards reformation of its R&D system to | 110 | the outcome of CAS efforts towards reformation of its R&D system to | ||
111 | meet future R&D challenges and to better meet the national demands.", | 111 | meet future R&D challenges and to better meet the national demands.", | ||
112 | "id": "c25dce84-97be-4153-8b90-d38f9ab73e5f", | 112 | "id": "c25dce84-97be-4153-8b90-d38f9ab73e5f", | ||
113 | "image_url": "2021-05-18-080509.992585AIRlogo.png", | 113 | "image_url": "2021-05-18-080509.992585AIRlogo.png", | ||
114 | "is_organization": true, | 114 | "is_organization": true, | ||
115 | "name": "air", | 115 | "name": "air", | ||
116 | "state": "active", | 116 | "state": "active", | ||
117 | "title": "Aerospace Information Research Institute, CAS", | 117 | "title": "Aerospace Information Research Institute, CAS", | ||
118 | "type": "organization" | 118 | "type": "organization" | ||
119 | }, | 119 | }, | ||
120 | "owner_org": "c25dce84-97be-4153-8b90-d38f9ab73e5f", | 120 | "owner_org": "c25dce84-97be-4153-8b90-d38f9ab73e5f", | ||
121 | "private": false, | 121 | "private": false, | ||
122 | "relationships_as_object": [], | 122 | "relationships_as_object": [], | ||
123 | "relationships_as_subject": [], | 123 | "relationships_as_subject": [], | ||
124 | "resources": [ | 124 | "resources": [ | ||
125 | { | 125 | { | ||
126 | "cache_last_updated": null, | 126 | "cache_last_updated": null, | ||
127 | "cache_url": null, | 127 | "cache_url": null, | ||
128 | "created": "2020-05-07T08:22:56.225765", | 128 | "created": "2020-05-07T08:22:56.225765", | ||
129 | "datastore_active": false, | 129 | "datastore_active": false, | ||
130 | "description": "", | 130 | "description": "", | ||
131 | "format": "SHP", | 131 | "format": "SHP", | ||
132 | "hash": "", | 132 | "hash": "", | ||
133 | "id": "4a50bf3a-4b59-4064-9d32-935dc0d6f97f", | 133 | "id": "4a50bf3a-4b59-4064-9d32-935dc0d6f97f", | ||
134 | "last_modified": null, | 134 | "last_modified": null, | ||
135 | "metadata_modified": "2020-05-07T08:22:56.225765", | 135 | "metadata_modified": "2020-05-07T08:22:56.225765", | ||
136 | "mimetype": null, | 136 | "mimetype": null, | ||
137 | "mimetype_inner": null, | 137 | "mimetype_inner": null, | ||
138 | "name": "Constructing dataset of classified drainage areas based | 138 | "name": "Constructing dataset of classified drainage areas based | ||
139 | on surface water-supply patterns in High Mountain Asia", | 139 | on surface water-supply patterns in High Mountain Asia", | ||
140 | "package_id": "f07acfb2-6572-4bd8-9e9e-95b3124eaa2c", | 140 | "package_id": "f07acfb2-6572-4bd8-9e9e-95b3124eaa2c", | ||
141 | "position": 0, | 141 | "position": 0, | ||
142 | "resource_type": null, | 142 | "resource_type": null, | ||
143 | "size": null, | 143 | "size": null, | ||
144 | "state": "active", | 144 | "state": "active", | ||
145 | "url": | 145 | "url": | ||
146 | ainage+areas+in+High+Asia+based+on+surface+water+supply+patterns.zip", | 146 | ainage+areas+in+High+Asia+based+on+surface+water+supply+patterns.zip", | ||
147 | "url_type": null | 147 | "url_type": null | ||
148 | } | 148 | } | ||
149 | ], | 149 | ], | ||
150 | "state": "active", | 150 | "state": "active", | ||
151 | "tags": [ | 151 | "tags": [ | ||
152 | { | 152 | { | ||
153 | "display_name": "High Mountain Asia", | 153 | "display_name": "High Mountain Asia", | ||
154 | "id": "217bb74a-7145-44cf-a89f-601d1eb91132", | 154 | "id": "217bb74a-7145-44cf-a89f-601d1eb91132", | ||
155 | "name": "High Mountain Asia", | 155 | "name": "High Mountain Asia", | ||
156 | "state": "active", | 156 | "state": "active", | ||
157 | "vocabulary_id": null | 157 | "vocabulary_id": null | ||
158 | }, | 158 | }, | ||
159 | { | 159 | { | ||
160 | "display_name": "Water Resources", | 160 | "display_name": "Water Resources", | ||
161 | "id": "b202bf4b-5b7c-426b-81d3-6c9f519c7e48", | 161 | "id": "b202bf4b-5b7c-426b-81d3-6c9f519c7e48", | ||
162 | "name": "Water Resources", | 162 | "name": "Water Resources", | ||
163 | "state": "active", | 163 | "state": "active", | ||
164 | "vocabulary_id": null | 164 | "vocabulary_id": null | ||
165 | } | 165 | } | ||
166 | ], | 166 | ], | ||
167 | "title": "Constructing dataset of classified drainage areas based on | 167 | "title": "Constructing dataset of classified drainage areas based on | ||
168 | surface water-supply patterns in High Mountain Asia", | 168 | surface water-supply patterns in High Mountain Asia", | ||
169 | "type": "dataset", | 169 | "type": "dataset", | ||
170 | "url": "http://www.sciencedb.cn/dataSet/handle/923", | 170 | "url": "http://www.sciencedb.cn/dataSet/handle/923", | ||
171 | "version": "" | 171 | "version": "" | ||
172 | } | 172 | } |